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Improving health decision literacy: enhancing informed health decisions through podcast interventions
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Improving health decision literacy: enhancing informed health decisions through podcast interventions
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Content
IMPROVING HEALTH DECISION LITERACY: ENHANCING INFORMED HEALTH
DECISIONS THROUGH PODCAST INTERVENTIONS
by
Katie Elizabeth Sippel Byrd
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(PSYCHOLOGY)
AUGUST 2024
Copyright 2024 Katie E. S. Byrd
ii
Acknowledgments
This path to obtaining my Ph.D. has been one of immense learning, growth, and personal
development. It would not have been possible without the guidance, support, and encouragement
from several individuals to whom I owe my sincerest gratitude.
First and foremost, I extend my thanks to my advisor, Richard John, for his unwavering
support, mentorship, and belief in my potential over the past six years. Thank you for the
knowledge and information that you have given me and the support you have shown me in both
my career and personal life. Richard, thank you for the opportunities you provided me and for
believing in my capacity to pursue and achieve my Ph.D. I couldn’t have asked for a better
advisor.
To my committee members, Mark Lai, Joe Arvai, John Monterosso, and Detlof von
Winterfeldt, your feedback, insights, and guidance have been essential in shaping this research.
Your expertise and constructive suggestions have greatly improved the quality of this
dissertation. Thank you for your time and for serving on my committee.
A special thanks goes to my podcast cohost and best friend, Sydney Miller. Your help in
bringing this dissertation idea to life has been invaluable. Your support, especially during
moments of doubt, has been the thing that kept me moving forward. Sydney, your willingness to
dedicate your time, provide ideas during brainstorming sessions, and take on the role of a
podcaster has been so generous. I am extremely grateful for your friendship and support.
To the USC Psychology Department and all my professors, thank you for providing an
educational and supportive environment throughout my doctoral studies. Your collective
iii.
wisdom, guidance, and the academic challenges you provided have significantly contributed to
my growth as a scholar.
A special thank you to Troy University, where I completed my undergraduate degree.
The foundation I received there, and the support from faculty and mentors, paved the way for my
journey to USC. I am appreciative of everyone at Troy who played a role in helping me reach
this point in my academic career.
To my parents, Tony and Linda, your endless love and support have been the pillars of
my success. Mom, I’ll never understand how you do it all. Your resilience and dedication,
working long night shifts and raising five kids, yet still finding the energy to always be the best
mom is unmatched. You helped me learn math and how to read, but most importantly how to
love others. Dad, your dedication and hard work have always been my inspiration. You have
both always believed in me and shown me unconditional love, for which I am forever thankful.
You have always encouraged my dreams and been my biggest supporters. I couldn’t have asked
for better parents and role models.
My gratitude extends to my entire family and friends, especially my siblings, nieces and
nephews, in-laws, and close friends. Your love and support have been my strength through the
years. Thank you for your unwavering presence and encouragement every step of the way.
Last, but certainly not least, to my husband, Will. Your constant support has been the
foundation of my Ph.D. journey. Your love, encouragement, and sacrifices, including moving all
the way to LA for me to attend USC, have meant the world to me. Through every high and low,
you have been my partner. Will, you are not just my husband but my best friend and the
iv.
love of my life. I can’t imagine going through this process with anyone else. Words could never
fully express my gratitude for all that you have done.
Finally, I want to express my gratitude to God, for leading me to this opportunity,
sustaining me through it, and having a plan for my future. It is with gratitude that I acknowledge
His guidance and grace at every turn.
This dissertation is not just a reflection of my hard work but more importantly of the
support, love, and belief from each of you. Thank you from the bottom of my heart.
v.
Table of Contents
Acknowledgments ...................................................................................................................... ii.
List of Tables ............................................................................................................................. vi.
List of Figures .......................................................................................................................... vii.
Abstract ................................................................................................................................... viii.
Overview of Dissertation .......................................................................................................... ix.
Chapter 1: General Introduction ............................................................................................ 1.
Chapter 2: Study 1 ................................................................................................................... 14.
Abstract ........................................................................................................................ 14.
Introduction ................................................................................................................ 14.
Part I: Guided Interview ............................................................................................ 25.
Part II: Online Survey ................................................................................................. 42.
Limitations, Future Research, & Conclusion............................................................ 67.
Chapter 3: Study 2 ................................................................................................................... 68.
Abstract ........................................................................................................................ 68.
Introduction ................................................................................................................ 68.
Fact Check Your Health Podcast ............................................................................. 81.
Health Decision Literacy (HDL) Scale ...................................................................... 86.
Intervention Experiment ............................................................................................. 93.
Chapter 4: Study 3 ................................................................................................................. 112.
Abstract ...................................................................................................................... 112.
Introduction .............................................................................................................. 113.
Part I: Condensed Intervention Experiment ........................................................... 114.
Part II: Public Intervention Dissemination ............................................................. 129.
Limitations & Future Research................................................................................ 132.
Conclusion.................................................................................................................. 134.
Chapter 5: General Discussion ............................................................................................. 135.
References ............................................................................................................................... 138.
Appendices .............................................................................................................................. 147.
vi.
List of Tables
Table 1-1. Demographic table for Study 1 Part II ...................................................................... 44.
Table 1-2. Binary generalized linear models for participants' reported motivations ................. 60.
Table 1-3. Binary generalized linear models for participants' choice of sources ....................... 63.
Table 2-1. Episode outlines for the intervention podcast Fact Check Your Health. .................. 84.
Table 2-2. Demographic table for the HDL scale development survey...................................... 89.
Table 2-3. Study 2 research design ............................................................................................ 95.
Table 2-4. Demographic table for Study 2 experiment .............................................................. 98.
Table 2-5. Linear regression predicting participants' pretest correct scores in Study 2 ........... 104.
Table 2-6. Linear regression predicting participants' posttest HDL scores ............................. 106.
Table 3-1. Demographic table for Study 3................................................................................ 117.
Table 3-2. Linear regression predicting participants' pretest HDL scores in Study 3 .............. 124.
Table 3-3. Linear regression predicting participants' posttest HDL scores in Study 3 ............ 126.
vii.
List of Figures
Figure 0-1. Dissertation framework ............................................................................................. x.
Figure 1-1. Study 1 path model identifying risk factors for poor health decision habits............ 43.
Figure 1-2. Participants' reported motivations for conducting their own health research.......... 48.
Figure 1-3. Participants’ reported life events when they did their own research ...................... 51.
Figure 1-4. Counts and percentages of participants who researched a topic.............................. 52.
Figure 1-5. Sources participants used, viewed as reliable, and viewed as unreliable................. 55.
Figure 1-6. Participants' response on source trustworthiness..................................................... 56.
Figure 1-7. Participants' responses to handling conflicting information.................................... 58.
Figure 2-1. ICC curves & test information function for the final 12 Health Decision Literacy
(HDL) Scale items........................................................................................................... 92.
Figure 2-2. Plot of the mean pretest and posttest scores for Study 2 ....................................... 100.
Figure 3-1. Plot of the mean pretest and posttest scores for Study 3 ....................................... 120.
viii.
Abstract
This dissertation presents a comprehensive examination of Health Decision Literacy
(HDL) within the current digital information space, focusing specifically on women aged 18-45.
Spanning three studies (N=933), this research examines how individuals seek, perceive, and use
online health information, and evaluates an innovative educational intervention aimed at
improving HDL. Study 1 establishes the foundation by determining motivations behind health
information-seeking behaviors and preferences for specific sources, revealing a relationship of
trust, autonomy, and the influence of cognitive and demographic variables on health literacy
practices. Building on these insights, Study 2 introduces the "Fact Check Your Health" podcast
as a novel boosting intervention designed to enhance HDL. This study details the creation and
validation of an HDL Scale, followed by an assessment of the podcast's efficacy through a
randomized control trial demonstrating significant improvements in HDL among participants.
Study 3 develops a condensed version of the podcast. The effectiveness of this revised format is
also confirmed through a RCT, followed by a public launch demonstrating a step towards
evaluating the podcast's real-world impact. Early engagement metrics and positive audience
feedback from the public launch highlight the intervention's potential for broad application and
its effectiveness in enhancing informed health decision-making. Collectively, these studies offer
a novel perspective on boosting HDL through digital interventions, emphasizing the importance
of understanding target audiences, using innovative media such as podcasts, and the necessity of
adaptability and feedback in educational content creation.
ix.
Overview of Dissertation
This dissertation contains three interconnected studies, each dedicated to identifying and
enhancing Health Decision Literacy (HDL) among women aged 18-45 within the current digital
media space. The studies build upon each other, progressing from an in-depth examination of
health information-seeking behaviors to the development and public launch of a podcast-based
intervention aimed at improving health literacy.
Study 1: Examining Health Information-Seeking Behaviors and Preferences
The first study lays the foundation by examining the motivations behind women's
searches for health information and their preferences among various sources. It identified a
desire for autonomy in health decisions and reliable information. Key findings include the
identification of specific health information-seeking behaviors and how cognitive and
demographic variables influence these practices. This foundational knowledge identifies gaps in
HDL and sets the stage for subsequent intervention development.
Study 2: Development and Evaluation of the "Fact Check Your Health" Podcast
Building on Study 1's insights, Study 2 introduces the "Fact Check Your Health" podcast
as a novel intervention designed to enhance HDL. This stage is marked by the development and
validation of the HDL Scale, combined with the testing of the podcast's effectiveness. The
intervention demonstrates significant improvements in HDL among participants, validating the
podcast as both an effective educational tool and highlighting the benefit of engaging digital
media formats in health literacy efforts.
Study 3: Refinement, Public Launch, and Examination of Scalability
x.
The final study focuses on refining the podcast into a more accessible, condensed format
based on feedback from Study 2 and evaluating its efficacy in a real-world context. This study
examines the podcast's scalability and public impact following its launch on major platforms.
Early engagement metrics and listener feedback indicate a successful transfer of research
findings into a practical and widely accessible health literacy resource demonstrating a step
toward broader public health education.
Together, these studies form a progression from exploratory research to practical
application, highlighting the potential of innovative digital interventions to improve public health
outcomes. Through a methodical process of development, evaluation, and refinement, this
dissertation contributes to the growing field of health literacy, offering insights into effective
strategies for empowering individuals to make informed health decisions in a digital media
environment.
Figure 0-1
Dissertation Framework
1
Chapter 1: General Introduction
With the growing use of social media and the internet, researchers across various
disciplines are increasingly recognizing the relationship between digital media consumption and
health decision-making behaviors. This dissertation seeks to examine this relationship, focusing
on health decision literacy within the context of the digital media revolution. This period is
characterized by both the unprecedented accessibility of health information and the challenge of
identifying misinformation. Central to this investigation is a theoretical framework that integrates
insights from psychology, health communication, and digital media studies.
Digital platforms, especially podcasts, are a novel medium for health education, offering
a distinct avenue for interventions. Based in the Self Determination Theory (Deci & Ryan,
2000), Health Belief Model (Champion & Skinner, 2008; Hochbaum, 1958; Rosenstock, 1974)
and the Theory of Planned Behavior (Ajzen, 1991; Conner & Armitage, 1998), this research
provides a framework to assess how podcasts might boost health decision literacy. These theories
outline the pathways through which individuals process health information and make related
decisions.
Moreover, this dissertation introduces health decision literacy as a compound construct,
encompassing various literacies: Health Literacy (HL), Information Literacy (IL), Media
Literacy (ML), Digital Literacy (DL), Statistical Literacy (SL), Numeracy, Risk Literacy (RL),
Scientific Literacy (SL), and Critical Thinking (CT). These elements are necessary for
effectively managing today's current health information. This dissertation seeks to determine
how educational interventions, particularly through podcasts, can be designed to enhance these
literacies, thus empowering individuals to make informed health decisions.
2
As this dissertation examines the relationship between digital media consumption and
health decision-making behaviors, it is important to acknowledge the cognitive and cultural
biases that affect individual decision-making processes. Cognitive biases, often unconscious,
significantly shape how we perceive information, make judgments, and ultimately decide on our
health behaviors. These biases, such as confirmation bias, the Dunning-Kruger effect, optimism
bias, the framing effect, the availability heuristic, and the affect heuristic can lead to distorted
perceptions and decisions regarding health information and interventions.
The presence of these biases highlights the difficulty of gathering health information
today, where misinformation can easily spread, and choice overload is common. Addressing
these biases is essential for developing effective health interventions and educational strategies
that empower individuals to make informed health decisions.
Numerous interventions have been created to decrease bias and improve skills in literacy,
critical thinking, decision-making, and identifying misinformation. These interventions vary in
effectiveness, influenced by factors such as contextual elements and the nature and duration of
the intervention. This dissertation investigates the potential of an intervention delivered through
a podcast series, designed to enhance health decision-making among women by equipping them
with the necessary skills to evaluate health information critically and effectively.
This theoretical framework acts as the foundation of the dissertation, guiding the design
and execution of three interconnected studies. These studies investigate the motivations for
personal health research, assess a podcast-based intervention's impact on health decision literacy,
and evaluate the intervention's scalability and public reception. By anchoring this research in a
robust theoretical base, the dissertation aims to increase empirical knowledge and enhance the
theoretical comprehension of digital media's role in advancing public health literacy.
3
Key Theories and Models
"Fact Check Your Health," a podcast series comprised of five episodes, uses key
psychological theories to enhance listeners' ability to understand and use online health
information. The theoretical foundation of this intervention is constructed upon the SelfDetermination Theory (SDT), Health Belief Model (HBM) and the Theory of Planned Behavior
(TPB) (Ajzen, 1991; Deci & Ryan, 2000; Rosenstock, 1974).
At the forefront is the Self-Determination Theory (SDT), which highlights the
significance of autonomy, competence, and relatedness in motivating behavior (Deci & Ryan,
2000). SDT states that individuals are more likely to engage in behaviors that are intrinsically
motivated and align with their core values and sense of self. In the context of health decision
literacy, SDT informs the podcast's approach by encouraging an environment that supports
listeners' autonomy in health decision-making, enhances their competence in gathering and
understanding health information, and builds a sense of relatedness or connection with the
broader health and wellness community. By emphasizing these psychological needs, the podcast
aims to cultivate a proactive and empowered approach to health information engagement.
The Health Belief Model (HBM) is a psychological framework designed to predict
health-related behaviors by focusing on individuals' perceptions and beliefs (Rosenstock, 1974).
It identifies several key constructs such as perceived susceptibility, involving individuals' beliefs
about their risk of experiencing a health problem; perceived severity, concerning individuals'
feelings on the seriousness of contracting an illness or leaving it untreated; perceived benefits,
the believed advantages of taking a health-related action; perceived barriers, the perceived
obstacles to taking a health-related action; cues to action, factors that trigger the decision-making
4
process to take action; and self-efficacy, the confidence in one's ability to successfully take
action (Champion & Skinner, 2008).
Building upon this, the Theory of Planned Behavior (TPB) aims to explain how
individuals decide to engage in a particular behavior through three central factors: attitude
toward the behavior, the individual's positive or negative feelings about performing the behavior;
subjective norm, the perceived social pressure to perform or not perform the behavior; and
perceived behavioral control, reflecting the ease or difficulty of performing the behavior as
perceived by the individual (Ajzen, 1991).
The application of the SDT, HBM and TPB collectively support the podcast's mission to
enhance health decision literacy, addressing both the individual's internal belief system and the
external social pressures that influence health behaviors. By detailing how to discern reliable
health information and evaluate research findings, the podcast speaks to listeners' perceived
susceptibility to misinformation and the severity of making uninformed health decisions. It acts
as a cue to action and enhances self-efficacy, empowering listeners with the skills to critically
assess health information. Furthermore, the podcast influences listeners' attitudes towards the
importance of engaging with health research, addresses the subjective norms by highlighting
societal expectations for informed health decisions, and boosts perceived behavioral control by
equipping listeners with the knowledge to understand health research independently.
The series aims to improve specific components of health decision literacy, including
information literacy, statistical literacy, critical thinking, and the other literacies mentioned
previously. It provides practical tips on identifying credible sources, understanding research
methodologies, and applying analytical skills to health information. By incorporating these
theoretical frameworks within the podcast series, "Fact Check Your Health" aims to contribute
5
empirically to the field and advance the theoretical understanding of how digital media can be
used to improve public health literacy.
Health Decision Literacy
In a period characterized by the exponential growth of digital media and the simultaneous
proliferation of both accurate health information and misinformation, the concept of health
decision literacy becomes a necessary competency. In this dissertation, Health Decision
Literacy (HDL) describes an individual's ability to locate, discern, evaluate, understand, and
effectively use online health information and research available to make decisions regarding their
health and wellness. Health decision literacy incorporates a broad spectrum of literacies, each
contributing to the individual's ability to locate, understand, evaluate, and utilize health
information effectively. This dissertation considers health decision literacy to be comprised of
the following literacies:
1) Health Literacy is the ability to obtain, process, and understand basic health information
and services needed to make appropriate health decisions, including interacting with the
healthcare system and communicating with healthcare providers (Brody et al., 2012;
George et al., 2013; Kim & Xie, 2017).
2) Information Literacy entails the ability to identify, locate, evaluate, and effectively use
information. It serves as the foundation for discerning credible sources from misleading
ones (ACRL Board, 2015; American Library Association, 1989).
3) Media Literacy emphasizes understanding how media content is created, distributed, and
consumed, enabling individuals to analyze and evaluate health information presented
across different media platforms (Maksl et al., 2015, 2017; Potter, 2018, 2022).
6
4) Digital Literacy involves the use of information technologies and the internet to find,
evaluate, use, share, and create content, highlighting the importance of digital
competencies in accessing health information (Pangrazio et al., 2020; Park et al., 2021;
Peng & Yu, 2022).
5) Statistical Literacy equips individuals with the skills to understand and interpret data and
statistical findings within the context of health research, encouraging a greater
comprehension of research outcomes and their relevance (Dani & Joan, 2004; Gal, 2002,
2004; Gigerenzer et al., 2007).
6) Numeracy focuses on the ability to use and understand numbers in daily life, important
for interpreting dosages, nutritional labels, and risk probabilities in health contexts
(Jonas, 2018; Reyna et al., 2009; Windisch, 2015, 2016).
7) Risk Literacy highlights the capacity to understand and evaluate risks and benefits,
supporting informed decision-making in the face of health-related uncertainties (Cokely
et al., 2012; Garcia-Retamero & Cokely, 2017; Gigerenzer, 2015; Lusardi, 2015;
Operskalski & Barbey, 2016).
8) Scientific Literacy provides the foundation for understanding scientific concepts and
processes, facilitating the interpretation of scientific studies and their implications for
personal and public health decisions (Krajcik & Sutherland, 2010; National Academies of
Sciences & Medicine, 2016)
9) Critical Thinking promotes the active and skillful analysis, synthesis, and evaluation of
information, encouraging individuals to scrutinize health information and consider
various perspectives (Bensley, 1998; Dunn et al., 2008; Tiruneh et al., 2014).
7
By integrating these literacies, health decision literacy forms a comprehensive framework
that enables individuals to engage effectively with health information. The podcast series
developed as part of this research, demonstrates the practical application of these literacies,
taking listeners through the complexities of health information and misinformation. This
approach to health decision literacy educates listeners on engaging with health information
effectively while also equipping them with a comprehensive skill set for making informed health
decisions.
Role of Digital Media in Health Education
The role of digital media in health education is increasingly recognized for its potential in
disseminating health information and promoting public health literacy. As the digital space
evolves, it becomes an important avenue for health education, offering both opportunities and
challenges in reaching and engaging diverse populations.
Digital platforms, including websites, social media, podcasts, and mobile applications,
have revolutionized access to health information. They provide instant access to a collection of
health advisories, research findings, and wellness strategies, spreading health knowledge and
enabling individuals to make informed decisions about their health.
The reach and accessibility of digital media stand out as its primary advantage in health
education. It breaks down geographical and socioeconomic barriers, allowing for the
dissemination of health information to wide and varied audiences, including those in underserved
communities. Digital platforms enable the delivery of tailored health interventions and
information, enhancing user engagement and the personal relevance of content.
Interactive learning through multimedia content such as videos, infographics, and quizzes
can significantly improve the understanding and retention of health information. Furthermore,
8
the social nature of many digital platforms encourages community building and peer support,
enhancing the health education experience.
However, the proliferation of health information online poses challenges, including the
potential for information overload and the spread of misinformation. Ensuring the accuracy and
reliability of online health content is necessary. Understanding and accommodating the digital
literacy skills of the target audience is necessary for designing accessible and effective health
education initiatives.
Effective digital health education requires evidence-based strategies and adherence to
best practices, including clear, concise, and actionable messaging and the integration of health
literacy and behavior change theories. Collaborative efforts among health professionals,
educators, technologists, and the target audience are essential for creating and evaluating
impactful digital health education programs. Regular monitoring and assessment of digital health
interventions' impact on health outcomes and behaviors are important for continued
improvement and the successful integration of digital media into health education.
Digital media offers significant opportunities for advancing health education and
improving public health outcomes. By utilizing its strengths and addressing its challenges, health
educators and professionals can use digital media to enhance health literacy and encourage
healthy behaviors across populations. This dissertation recognizes the importance of digital
media in the modern health education field, highlighting the need for innovative approaches to
harness its full potential in promoting public health.
The Educational Potential of Podcasts in Health Literacy
Podcasts, with their prominence in the current online media space, represent a unique and
relevant educational tool, particularly regarding health education. The episodic nature of
9
podcasts, combined with their digital accessibility, offers an innovative approach to
disseminating health information in an engaging and digestible manner. This medium allows for
in-depth explanations of health topics, providing listeners with the flexibility to engage with
content at their convenience, thereby enhancing the accessibility and integration of health
education into daily routines.
The auditory nature of podcasts provides a personal connection between the presenter and
the listener, enabling the delivery of health information through compelling storytelling and
expert interviews. This personal touch makes health concepts more relatable and enhances the
listener's engagement and retention of information. Furthermore, the cost-effectiveness of
podcast production and its potential for wide-reaching distribution positions podcasts as an ideal
choice for health education initiatives aimed at diverse audiences.
In this dissertation, the use of podcasts as an intervention tool is motivated by the
medium's unique advantages. By offering an intervention through the "Fact Check Your Health"
podcast series, this project aims to guide listeners through the literacies necessary for effective
health decision-making. The focus on women’s health decision literacy is particularly important,
as it aims to address the specific challenges and needs of this demographic in gathering and
understanding health information.
The following sections of this dissertation will detail the design, implementation, and
evaluation of the podcast series to enhance health decision literacy among women. By using
podcasts' educational potential, this project contributes to the broader effort to improve public
health literacy in a society where digital media plays an increasingly significant role in health
education and communication.
10
Novel Contributions
This dissertation occupies a unique space where digital media and health literacy research
meet, with a focus on the potential of podcasts—a medium yet to be thoroughly examined in this
context. Unlike previous studies, which have primarily focused on broad digital media platforms
or traditional health education tools, this research examines the specificity of podcasts as a
versatile, accessible, and engaging medium for health literacy interventions. Moreover, by
targeting women in a critical age group for health decision-making, this study aims to contribute
to the empirical understanding of how digital interventions can impact health literacy and seeks
to inform the design of more effective, targeted health communication strategies. This approach
addresses a significant gap in the literature by quantifying the educational impact of podcasts on
health decision literacy and offering insights into the cognitive and behavioral outcomes of such
interventions. Through the integration of psychological theories, digital media, and health
education within the framework of podcasts, this dissertation contributes knowledge and
practical implications for the advancement of public health literacy.
Research Objectives and Hypotheses
This study is designed around four main research questions reflecting the following
objectives:
Research Questions:
1) What motivates individuals to conduct their own health research?
Objective: To identify the factors behind individuals' decisions to seek out health
information independently, including the role of digital media in motivating and
facilitating this process.
11
2) Can an individual’s Health Decision Literacy (HDL) be improved through a podcast
intervention?
Objective: To evaluate the effectiveness of a specifically designed podcast series in
enhancing listeners' abilities to find, evaluate, and apply health information accurately
and effectively.
3) Are there attributes that predict an individual’s HDL and/or their response to the
intervention?
Objective: To investigate if certain demographic or cognitive attributes influence
individuals' health-related behaviors and how these attributes may affect their
engagement with and outcomes from the podcast intervention.
4) Can the intervention be scaled to situations "in the wild"?
Objective: To assess the scalability and applicability of the podcast intervention in realworld settings, beyond controlled study environments, to determine its potential impact
on public health literacy at large.
Hypotheses
Corresponding to the objectives derived from these questions, the study theorizes the
following hypotheses:
H1: Individuals' motivation to conduct their own health research is significantly
influenced by factors such as personal health concerns and prior experiences with health
information sources.
H2: Engagement with the health-focused podcast series will lead to measurable
improvements in health decision literacy, as demonstrated by enhanced scores on the
Health Decision Literacy scale.
12
H3: Specific attributes, including but not limited to age, education level, and other
demographic or cognitive variables, will predict the degree of benefit that individuals
gain from the podcast intervention in terms of health decision literacy and behavioral
change.
H4: The podcast intervention demonstrates the potential for scalability and effectiveness
in real-world settings.
These research questions and hypotheses frame the study within a context that
acknowledges the involved nature of health decision-making in the current digital environment.
By examining these topics, this dissertation aims to both contribute to academic knowledge and
offer practical insights into leveraging digital media, specifically podcasts, for public health
advancement.
Focus on Women Aged 18-45
This research specifically targets women aged 18-45, a demographic that occupies an
important role in health decision-making within families and communities. Women in this age
group encounter unique health challenges and make important decisions ranging from
reproductive health to managing emerging chronic conditions. Their active engagement with
digital media (e.g. social media) for health information not just for themselves but also for their
dependents, amplifies the impact of their health literacy on broader public health outcomes.
The choice of focusing on women aged 18-45 is strategic, recognizing their significant
life transitions and the varied health information needs that accompany early adulthood, potential
motherhood, and mid-life. This dissertation seeks to design the podcast intervention to relate
with the specific interests, concerns, and lifestyles of these women, thereby enhancing the
intervention's relevance and effectiveness. It acknowledges the diversity within this demographic
13
and investigates how digital media, particularly podcasts, can support women through their
unique health-related decisions and transitions.
By focusing on this demographic, the study aims to address a gap in targeted health
literacy interventions for women and contribute to a more thorough understanding of digital
media's potential to encourage informed health decision-making.
Significance of Dissertation
This dissertation presents a timely evaluation of the relationship between digital media
and health decision literacy, with a specific emphasis on women aged 18-45. It incorporates
digital health communication, cognitive biases in health decision-making, and the innovative use
of podcasts as a medium for educational interventions. By using the unique attributes of
podcasts—accessibility, personal connection, and the ability to engage listeners in depth—this
research aims to enhance health decision literacy among women, enabling them to make
informed health decisions.
The strategic focus on women aged 18-45 highlights the recognition of their role in health
decision-making, not just for themselves but for their families and communities. This
demographic's unique health information needs and digital media engagement patterns present a
prime opportunity for impactful health literacy interventions. Through a methodically designed
podcast series, "Fact Check Your Health," this study seeks to provide these women with the tools
and knowledge necessary to evaluate health information effectively.
The anticipated outcomes of this research include academic contributions to the fields of
health communication and education in addition to practical insights that can inform the design
of future digital health interventions. In doing so, this dissertation addresses a gap in the existing
literature on health decision literacy and digital media interventions and lays the groundwork for
14
future research and practices aimed at developing digital innovations for health education and
empowerment.
Chapter 2: Study 1
Abstract
This study (N=506) investigates the health decision-making behaviors of women aged
18-45, focusing on their motivations, methods, and sources for health-related research. Through
a mixed-methods approach combining guided interviews (Part I) and a structured online survey
(Part II), this study investigates the processes women use when seeking health information
online. The study highlights the relationship of intrinsic and extrinsic motivations driving health
research, including unresolved health issues, external influences, and distrust in traditional
medicine. Findings reveal a significant reliance on digital platforms, despite varying perceptions
of source reliability, supporting the "social media paradox" where convenience often outweighs
concerns about information accuracy. Cognitive and demographic factors were examined for
their influence on health decision habits, indicating that open-mindedness and critical thinking,
as measured by Actively Open-Minded Thinking (AOT) (Baron, 2019) and Cognitive Reflection
Test (CRT) (Thomson & Oppenheimer, 2016), significantly predict the engagement in health
research and source utilization. The study concludes that enhanced health literacy education is
important for managing complex health information effectively. These insights provide
foundational knowledge for future interventions aimed at promoting informed health decisionmaking.
15
Introduction
In the current digital society and post-pandemic world, individuals are increasingly
assuming the role of health researchers in their own lives. With the influx of diverse and, at
times, disparate health information sources available online, understanding the motivations and
methods by which individuals engage in health research has become neccesarry. This study,
forming the first chapter of a broader exploration into health decision literacy, centers on women
aged 18-45—a demographic that manages both personal health management and caregiving
responsibilities.
Previous research has emphasized the relationship of motivations and their consequential
impact on the pursuit and interpretation of health information. However, gaps remain in
comprehensively understanding the process that women in this age group take when trying to
find health research online. This becomes particularly important when considering the potential
for such research practices to influence health outcomes at both individual and community
levels.
Through a combination of guided interviews and a structured survey, Study 1 aims to
examine the underlying motivations that motivate women to conduct their own health research. It
seeks to determine the sequence of actions they undertake—from the selection of topics to the
evaluation of source credibility. In doing so, the study also examines the relationships between
these practices and various demographic and cognitive variables. By establishing a foundational
understanding of the existing health decision habits (HDH), the resulting insights aim to direct
the "Fact Check Your Health" podcast series, ensuring its content is relevant to its intended
audience.
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Theoretical Frameworks and Motivational Models
Health information-seeking behavior in the current digital society is increasingly
complex, characterized by a variety of sources that range from peer-reviewed articles to personal
blogs and social media platforms. This study focuses on understanding the motivations and
methodologies employed by women when they make informed health decisions. Central to this
exploration are the psychological theories and models that explain the foundations of healthrelated decision-making.
Self-Determination Theory (SDT)
Self-Determination Theory (SDT) proposes that individuals are more likely to engage in
intrinsically motivated behaviors—that is, actions performed for the inherent satisfaction and
personal value they bring, rather than for some separable outcome. Regarding health
information-seeking, this suggests that women who are intrinsically motivated to learn about
health topics—for example, out of a genuine interest in wellness or a desire to improve their
health for personal fulfillment—are more likely to sustain this behavior over time. Extrinsic
motivations, such as seeking health information to avoid social disapproval or to conform to
perceived societal norms, may initiate behavior but are less likely to sustain engagement in the
long term. The interaction between these intrinsic and extrinsic motivations in the digital health
information space is central to understanding how women engage with online health resources
(Deci & Ryan, 2000).
Theory of Planned Behavior (TPB)
The Theory of Planned Behavior (TPB) extends this understanding by incorporating the
role of behavioral intentions, which are influenced by three key factors: attitudes towards the
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behavior (positive or negative evaluations of engaging in the behavior), subjective norms
(perceived social pressure to perform or not perform the behavior), and perceived behavioral
control (the ease or difficulty of performing the behavior). In applying TPB to digital health
information-seeking, it becomes essential to consider how women's attitudes towards seeking
health information online, the influence of their social circles, and their perceived ability to find
and understand health information impact their intention to engage in this behavior. The current
digital space offers both opportunities and challenges in this regard. The large amounts of online
resources can be empowering but also overwhelming, affecting women's perceived behavioral
control in seeking health information (Ajzen, 1991).
Health Belief Model (HBM)
The Health Belief Model (HBM) further enhances our understanding by emphasizing the
role of perceived threats and the cost-benefit analysis individuals undertake when deciding
whether to engage in health-related actions. According to the HBM, four main constructs
influence behavior: perceived susceptibility (belief about the likelihood of getting a condition),
perceived severity (belief about the seriousness of a condition and its consequences), perceived
benefits (belief in the efficacy of the advised action to reduce risk or severity), and perceived
barriers (belief about the tangible and psychological costs of the advised action). In the context
of digital health information-seeking, women's perceptions of their susceptibility to health issues,
the severity of these issues, the benefits of seeking information, and the barriers (such as
difficulty in understanding medical jargon or finding reliable sources) play important roles in
their motivation and behavior. This model highlights the importance of addressing perceived
barriers and enhancing the perceived benefits to encourage health information-seeking behavior
(Rosenstock, 1974).
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By integrating these theories, this study aims to construct a comprehensive understanding
of the motivations and behaviors driving women's health information-seeking. It aims to identify
how intrinsic and extrinsic motivations, alongside behavioral intentions and perceived risks and
benefits, shape how individuals engage with online health information.
Dual-Process Theories in Health Information Processing
Building upon the foundational theories guiding our understanding of motivations in
health information-seeking behaviors, the incorporation of dual-process theories, as outlined by
Kahneman (Kahneman, 2011) and Evans (Evans, 2008), offers a detailed perspective on how
individuals, process health information encountered online. These theories, distinguishing
between two distinct types of cognitive processing—System 1 (intuitive and quick) and System 2
(analytical and deliberate)—provide valuable insights into the nature of decision-making in
health contexts.
System 1 processing operates automatically and rapidly, with minimal effort and without
voluntary control (Kahneman, 2011). This mode, characterized by its reliance on heuristics and
emotional responses, can be particularly influential when individuals face health information that
elicits strong emotional reactions. The role of System 1 processing is important in the digital
health information space, where headlines designed to provoke immediate responses encourage
the initial draw or repulsion based on instinctive reactions rather than detailed analysis.
Conversely, System 2 processing is deliberative, slower, and more logical, involving
conscious thought, reasoning, and the weighing of options (Evans, 2008). When engaged,
individuals are more likely to evaluate the credibility of sources and the validity of information.
Thus System 2 is necessary for making informed health decisions amidst conflicting information.
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The relationship between these systems, as highlighted by researchers such as Stanovich
and West (Stanovich & West, 2000), is complicated. While online accessibility can trigger
immediate and emotionally charged reactions (System 1), it also provides opportunities for
deeper investigation (System 2). Understanding this process, especially considering the
emotional weight often attached to health information, is key to comprehending health
information-seeking behaviors.
Moreover, this dual-process approach highlights the importance of facilitating transitions
from System 1 to System 2 processing in health literacy interventions. Acknowledging initial
emotional responses while encouraging analytical thinking and evaluation can better support
women in making informed health decisions, as suggested by Whitley et al. (Whitley et al.,
2013). Incorporating dual-process theories into the examination of health information-seeking
behaviors enhances the understanding of the cognitive mechanisms at play with digital health
information. This highlights the need for interventions that address both intuitive and analytical
aspects of information processing.
Information-Seeking Behavior Models
The Information-Seeking Behavior Model (ISB), as conceptualized by Wilson (Wilson,
1999), provides a framework for understanding the various factors that influence the process of
seeking information. This model highlights the importance of personal, environmental, and
social variables in shaping information-seeking behaviors. In the context of digital health
information, this model can be particularly insightful in highlighting how individuals handle
health information available online.
While technological access is broadly available in the current world, the focus shifts
toward the roles of health literacy and social support in mediating the information-seeking
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process. Health literacy, encompassing the ability to obtain, process, and understand basic health
information and services, is fundamental for effective information seeking. It determines the
ability to access digital health resources and the competence to evaluate and use the information
found (Nutbeam, 2013). Individuals with higher levels of health literacy are more equipped to
identify health information, assess the credibility of sources, and discern valuable information
from misinformation.
Social support, whether from personal networks or online communities, also plays an
important role in shaping information-seeking behaviors. It can act as both a motivator and a
facilitator for engaging in health information-seeking. Encouragement from friends, family, or
peers can prompt individuals to seek health information, while discussions within social
networks can help in interpreting and validating this information (Savolainen, 2011). Moreover,
social support can buffer the impact of the overwhelming nature of the digital information
environment, providing guidance and recommendations that guide women towards reliable and
relevant resources.
Intervening variables such as personal beliefs, previous experiences with health systems,
and the perceived relevance of information further influence the information-seeking process.
These variables interact with an individual's health literacy and the support of their social
networks, creating a combination of factors that impact how health information is sought,
processed, and used. By applying Wilson's Information-Seeking Behavior Model to the digital
health context, we gain insights into the mechanisms through which individuals interact with
health information online. Acknowledging the roles of health literacy and social support,
alongside personal and environmental variables, is necessary for designing effective health
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literacy interventions. These interventions should aim to improve access to information and
enhance the ability to engage with content, thus supporting informed health decisions.
Cognitive Biases in Health Decision-Making
Seeking and understanding digital health information is significantly influenced by
cognitive biases, which can distort understanding and decision-making. Among these,
confirmation bias, the Dunning-Kruger effect, optimism bias, the framing effect, the availability
heuristic, and the affect heuristic play important roles.
Confirmation bias leads individuals to preferentially seek and interpret information that
supports their existing beliefs, often disregarding contrary evidence (Nickerson, 1998). This bias
is particularly problematic in digital health contexts, where diverse viewpoints and data are
easily accessible, potentially reinforcing incorrect health beliefs. Recent studies highlight the role
of social media in exacerbating confirmation bias, as users often encounter echo chambers that
reflect their viewpoints (Bessi et al., 2015).
The Dunning-Kruger effect describes the phenomenon where individuals with limited
knowledge overestimate their understanding and capabilities (Kruger & Dunning, 1999). In the
health domain, this can result in the misinterpretation of health information and an inflated sense
of self-efficacy in diagnosing and treating medical conditions, a concern emphasized in the
context of online health forums (Canady & Larzo, 2023).
Optimism bias, or the tendency to underestimate the likelihood of experiencing adverse
outcomes, can lead to a disregard for preventive health measures (Weinstein, 1980). This bias
has implications for public health messaging, especially in campaigns addressing lifestyle
diseases and vaccination uptake, where a realistic assessment of risks is important (Sharot,
2011).
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The framing effect illustrates how the presentation of information can influence decisionmaking (Tversky & Kahneman, 1981). In health communication, the framing effect can
significantly impact how individuals interpret the severity and relevance of health risks,
highlighting the need for balanced and clear information presentation in digital platforms
(Gallagher & Updegraff, 2012).
The availability heuristic, where estimates of event likelihood are based on the ease of
recalling examples, can lead to distorted risk perceptions, especially when sensationalized health
stories go viral online (Schwarz & Vaughn, 2002; Tversky & Kahneman, 1973). Enhancing
digital literacy to critically evaluate the prevalence and significance of health risks can mitigate
this bias's impact.
The affect heuristic shows how emotional responses can override analytical thinking. For
example, emotional framing in health news can lead to skewed risk assessments and decisionmaking (Lerner et al., 2023; Slovic et al., 2007). Developing skills to recognize and counteract
emotional responses can improve health decision-making accuracy in digital environments.
These highlighted biases are just a few of the cognitive effects that affect health habits
and health decision literacy. Additional biases such as the representativeness heuristic, choice
overload, sunk cost fallacy, negativity bias, and the bandwagon effect can also significantly
influence health decision-making processes. Recognizing and addressing a broader spectrum of
cognitive biases is necessary for designing more effective health literacy interventions that cater
to a wide range of decision-making challenges. Mitigating these biases is essential for improving
effective health communication and literacy.
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The Role of Social Support and Online Communities in Health Decision-Making
Social media has transformed access to health information and redefined the roles of
social support and community engagement in health decision-making processes. Online health
communities (OHCs) and social media platforms have emerged as significant sources of support,
enabling individuals to share experiences, seek advice, and access a broad spectrum of healthrelated information. This change emphasizes the importance of understanding the role of digital
social networks in influencing health behaviors and decisions.
Recent studies highlight how participation in online health communities can encourage
health empowerment among users. For instance, Jiang et al. (Jiang et al., 2022a) explain how
enhanced social support and access to quality health information through these communities
enhance individuals' ability to make informed health decisions. This sense of empowerment is
important, as it equips individuals with the knowledge and confidence needed to evaluate health
choices effectively. Similarly, research by Johansson et al. (Johansson et al., 2021) and Liu and
Wang (J. Liu & Wang, 2021) note the potential of social media and online communities to
significantly influence health behavior change, highlighting these platforms as effective avenues
for health communication and behavior modification strategies.
However, the benefits of online health information and communities are accompanied by
challenges, such as information overload and the proliferation of misinformation. BujnowskaFedak and Węgierek (2020) highlight the impact of online health information on patient health
behaviors and decision-making, noting the need for individuals to manage these complexities
effectively. This emphasizes the importance of health literacy in evaluating the quality of online
health information and making informed health decisions. This challenge has been particularly
pronounced during the COVID-19 pandemic, which has seen a surge in digital communication
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and information-sharing practices. Eysenbach (2020) highlights the role of reliable online health
information and the significance of digital communication in public health responses during such
crises, illustrating the impact on societal health behaviors and the spread of misinformation.
Moreover, the support gained from online communities and social media can
significantly affect health decision-making. The exchange of personal experiences and
information within these digital spaces can provide emotional comfort, reduce feelings of
isolation, and contribute to a more thorough understanding of health issues. Bujnowska-Fedak
(2020) emphasizes how this collective wisdom is particularly valuable for individuals managing
complex health decisions, offering insights beyond traditional medical consultations and
supporting a sense of empowerment and community.
The role of social support and online communities in health decision-making is
increasingly important within the current social media context. The interactive nature of these
platforms offers unparalleled opportunities for sharing experiences, receiving emotional support,
and accessing a wide range of health-related information. Research has consistently shown that
engaging with online health communities can significantly enhance individuals' health literacy,
enabling them to make more informed health decisions (Jiang et al., 2022b; Johansson et al.,
2021; J. Liu & Wang, 2021). As the digital space continues to evolve, health communication
strategies must adapt to use these digital environments effectively. This involves addressing the
challenges posed by the vast amounts of online health information and harnessing the potential
of online communities to support individuals, especially women, in making health decisions.
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Part I: Guided Interviews
Methods
Objective
The initial phase of Study 1 used guided interviews to examine the motivations,
strategies, and experiences of women aged 18-45 engaging in self-directed health research. This
qualitative approach aimed to identify insights into the various influences on health informationseeking behavior within this demographic.
Recruitment and Participants:
Recruitment was conducted through a combination of methods including convenient
sampling, word of mouth, snowball sampling, and social media outreach. Eligibility criteria
included being female, aged between 18 to 45, and having previously engaged in self-directed
health research. A total of 10 participants were selected, ensuring a varied representation across
the specified age range.
Interview Procedure
Interviews were conducted individually via Zoom to accommodate the convenience of
participants across different locations. Each session, lasting between 20 to 50 minutes, followed
a semi-structured format based on a predetermined set of questions designed to determine
participants’ health research behaviors. Questions covered topics such as motivations for
research, the process undertaken, source evaluation, and decision-making strategies in the face of
conflicting information. The full interview script can be found in Appendix A.
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Data Collection and Analysis
Informed consent was obtained verbally at the start of each interview, with sessions
recorded to facilitate thorough analysis. Following the interviews, recordings were reviewed to
identify recurring themes, commonalities, variations, and unique insights related to participants’
health information-seeking experiences. The analysis aimed to categorize and understand the
patterns within the data without the use of specific software tools, ensuring a well-rounded
interpretation of the findings. Compensation for participation was a $15 Amazon gift card. The
study received exempt approval from the Institutional Review Board (IRB) at the University of
Southern California.
Results
Influence, Motivation, and Catalysts for Personal Health Research
Participants' reported motivations to engage in personal health research were strongly
shaped by their life experiences, familial relationships, and significant life events that acted as
catalysts for seeking information independently.
A common theme was the influential role of family, particularly parental guidance, in
shaping health perspectives from an early age. One interviewee recalled, "My mom has honestly
influenced me a lot because she raised me and my siblings very holistically minded,"
highlighting how familial approaches to health can affect individuals' information-seeking
behaviors.
Additionally, parenthood marked a turning point for many participants, driving them to
research natural health options and make informed decisions for their children's well-being. The
transition into parenthood was often described as a trigger for a more proactive stance towards
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health, reflecting the responsibility felt by new parents. For example, one interviewee
commented, "Becoming a parent changed everything for me. Suddenly, I wasn't just responsible
for my health but for my child's as well. I needed to know more, to do better." Additionally, one
interviewee articulated: "The motivation is just, I want what's best for my child and family and
what's going to make them healthy and happy and be able to thrive."
Further, personal health experiences, whether through adverse reactions to conventional
treatments or the management of chronic conditions, were significant motivators. One
participant's struggle with hormonal birth control led them to seek alternative solutions: "I had
really horrible symptoms...that was really motivating to me to figure out, what are other
options?" Similarly, another shared, "The journey to manage my anxiety without relying solely
on medications led me to research a variety of natural and holistic approaches," highlighting a
shift towards personalized health management strategies.
Specific catalysts for initiating health research varied among participants but shared a
theme of significant life changes or health challenges. For some, a diagnosis prompted a search
for more information: "When I was diagnosed with a chronic condition, I felt lost with the
options my doctor gave me. That's when I decided to look into it myself." For others, a desire for
holistic or integrative approaches aligned with their values and lifestyle preferences motivating
their research: "I've always believed in a more holistic approach to health, but it wasn't until I
faced a health scare that I really started to dive deep into alternative health research."
Global health crises, such as the COVID-19 pandemic, were also a significant catalyst for
some individuals to become more actively engaged in seeking health information. The
unprecedented situation highlighted the importance of being informed and proactive about health
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matters. An interviewee reflected, "The pandemic made me realize just how important it is to be
informed about health issues, leading me to seek out more information than ever before."
These narratives reveal a combination of motivations behind the pursuit of health
information, often stemming from a desire to improve one's own or a loved one's health. Life
experiences, whether through familial influence, the beginning of parenthood, personal health
challenges, or a desire for holistic approaches, act as powerful motivators for individuals to
engage actively in their health literacy and decision-making processes.
Information Sourcing and Trustworthiness
Participants in this study demonstrated a variety of methods when it came to sourcing
health-related information. Their emphasis on the perceived trustworthiness and credibility of
their sources was evident in how they approached the decision-making process.
Engaging with people they knew personally was a frequent starting point, as one
interviewee described: "I tend to start with talking to people I know just because I love hearing
firsthand experiences." This preference indicates a trust in the relatability and relevance of
shared personal experiences.
The digital space, particularly social media groups and online communities, also played a
role in information gathering. Interviewees would turn to these platforms, due to the volume of
shared experiences and stories. As one put it, "I'm part of a Facebook group...they post all kinds
of journals and articles that they find along with their personal stories.", suggesting that these
digital communities are valued for their collective knowledge.
However, for some interviewees, the reliability of these sources was a point of scrutiny.
Some participants were deliberate in seeking out information backed by scientific evidence, such
as independent research or peer-reviewed scientific journals, over less formal sources such as
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personal blogs or unverified online content. For example. one interviewee placed greater trust in
academic validation, stating, "I trust a peer-reviewed scientific journal a lot more than a mommy
blog." However, that was not necessarily the case for all interviewees.
Despite recognizing the benefits of social media for its immediacy and accessibility,
interviewees maintained a hesitance stance towards the information disseminated through these
channels. They were highly aware of the tendency for social media to perpetuate unverified
claims and biases. "Anything on social media I'm highly skeptical of," one interviewee admitted,
voicing a common concern over the reliability of such platforms. Nonetheless, social media's
potential to spread personal health stories and facilitate community discussions was
acknowledged, even as interviewees remained alert to the possibility of exaggeration and hidden
agendas within these narratives.
Concerns were notably raised regarding the objectivity of sources, especially when it
came to studies potentially influenced by those who stand to profit from their outcomes. The
participants were mindful of scrutinizing who conducted the research and who funded it, which
could significantly impact their trust levels. "Looking at who did it and who funded it can be
very telling," one interviewee pointed out, demonstrating the necessity of transparency in
research. Similarly, the process of fact-checking and corroborating information with multiple
reliable sources was a prevalent theme among the participants, showcasing a sophisticated level
of health literacy. This vetting process before reaching conclusions reflects a thorough and
conscientious effort to evaluate health information.
In conclusion, some of the participants showed a balanced approach to health information
sourcing: they appreciated the interconnectedness and the experiential knowledge available on
social media, yet they did not ignore the importance of empirical evidence.
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Decision-Making Process
The decision-making process for health-related issues among participants revealed a
multi-step approach that involved weighing different factors and considering various sources of
information. The process from gathering information to making a final decision highlight a
personal and often involved process, influenced by individual beliefs, experiences, and the desire
for the best possible outcomes.
Participants described a deliberative process in which they balanced the evidence
gathered from their research with personal values and practical considerations. One common
theme was the importance of aligning health decisions with personal beliefs and lifestyles, as
well as the perceived benefits and risks associated with different options. For example, "Making
a decision involved not just looking at the facts but also considering what felt right for me and
my family," one interviewee explained. This statement highlights the interaction between
objective information and subjective judgment in participants' decision-making processes.
The role of intuition and personal experiences, alongside guidance from non-traditional
healthcare providers, played a significant role in shaping some participants' choices. "After
experiencing negative side effects from a medication, I became more cautious and inclined to
look into natural alternatives. My midwife and doula were a great resource in exploring these
options," shared another participant, demonstrating the value of having healthcare providers who
support individual preferences and holistic health approaches.
Moreover, the social aspect of decision-making appeared as a significant factor.
Discussions with family, friends, and healthcare professionals provided valuable perspectives
that participants considered alongside the information they had researched. "I found it helpful to
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talk things over with my doctor and a few close friends who had been through similar situations,"
mentioned one interviewee, pointing to the collaborative nature of their decision-making process.
Despite the amount of information available, participants also acknowledged the
challenges of handling conflicting information and the responsibility that comes with making
informed health decisions. The process often involved sifting through contradictory advice and
deciding which sources to trust. "There were times when I found two credible sources saying
completely opposite things. It was daunting, but ultimately, I had to trust my judgment and make
the best decision based on the information I had," an interviewee recounted.
In conclusion, the decision-making process for health-related issues is very
individualized. Participants emphasized the importance of a balanced approach, incorporating
scientific evidence, personal experiences, and discussions with trusted individuals. This process
demonstrates a proactive and conscientious approach to health management, highlighting the
participants' active engagement in their health and well-being.
Evaluating and Reconciling Conflicting Information
When reading health information, participants often encountered conflicting advice and
data, posing challenges to their decision-making processes. The ability to evaluate and reconcile
such discrepancies was important, reflecting an analytical approach to health literacy.
Participants shared their strategies for managing these challenges, emphasizing the importance of
critical thinking and personal judgment.
One common strategy was seeking out multiple sources of information to cross-check
facts and viewpoints. "It was confusing when I found two credible sources saying completely
opposite things. Ultimately, I had to trust my intuition and make what felt like the best decision
for me at the time" one participant reflected.
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Moreover, the participants highlighted the significance of considering the source of
information, including the author's credentials, the study's funding, and the potential biases that
might influence the findings. "I always look at who funded the study. It helps me to figure out
which information is likely more unbiased," mentioned another interviewee.
Some participants also valued personal experiences and anecdotes, especially when
scientific data was inconclusive or lacking. "I listened to stories from others who had been
through similar health situations. While not scientific, these stories gave me a sense of the realworld outcomes of certain health decisions," shared a participant. This reliance on personal
narratives points to the human aspect of health decision-making, where empirical evidence and
personal experiences overlap.
The role of healthcare professionals in helping participants reconcile conflicting
information was also highlighted. Trust in their healthcare providers, whether traditional
physicians, midwives, or alternative medicine practitioners, provided a sense of guidance and
reassurance. "My doctor was instrumental in helping me talk through the conflicting advice on a
health issue. Her expertise and understanding of my health history made me feel more confident
in my decision," an interviewee recalled.
In conclusion, by using multiple sources, scrutinizing where the information came from,
incorporating personal stories, and consulting with healthcare professionals, participants were
able to make informed health decisions that aligned with their values and circumstances.
Determining Risks and Benefits
The process of evaluating risks and benefits was important in the health-related decisionmaking process for some participants. One interviewee emphasized the deliberative nature of this
process, especially in the context of making medication decisions: "With birth control, I was
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really trying to weigh out, what are the side effects versus the benefits?" The task of reconciling
conflicting information, particularly regarding medical interventions, was highlighted by another
participant: "We had to weigh the cost of the potential negatives or side effects of the anxiety
medicine, with the pros of how this could positively affect my life and my family’s life." This
insight reflects the personal nature of risk evaluation, factoring in the significant impacts on
one’s life and family.
The collaborative aspect of decision-making surfaced as well, with individuals seeking
insights from healthcare professionals and their personal network: "I found it helpful to have
conversations with a few trusted friends who had been through similar situations in addition to
my doctor to decide what to do."
In conclusion, evaluating the risks and benefits demonstrates a reflective process. It is
informed by personal experiences, scientific evidence, and advice from trusted advisors.
Health Literacy and Empowerment
Participants demonstrated a proactive stance toward health literacy, emphasizing the
importance of educating themselves on various health topics. One interviewee noted, "I spend a
lot of time reading up on different health issues. It makes me feel more in control of my health
decisions." Thus, highlighting the link between health literacy and a sense of agency in
managing one's health.
The pursuit of health literacy was often motivated by the desire to challenge or verify the
information provided by healthcare professionals. "I don't just take my doctor's word for it. I like
to do my own research to really understand what's going on with my body," shared another
participant.
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Moreover, the ability to critically assess health information was seen as essential for
managing the vast and sometimes contradictory information. "With so much information out
there, being able to determine what's credible and what's not is important," mentioned one
interviewee. This discernment is a key aspect of health literacy, enabling individuals to make
choices based on reliable information.
Participants also spoke about the empowerment that comes with being knowledgeable
about health issues. "Knowing more about my health options gives me the confidence to
advocate for myself in traditional healthcare settings," one participant expressed. This
empowerment is not just about making informed choices but also about engaging confidently
with healthcare providers and advocating for one's health needs.
Ultimately, health literacy is not just about acquiring health information; it is about
developing the skills and confidence to use it effectively. The participants' experiences highlight
the potential of health literacy in enhancing personal agency and empowerment in health-related
decision-making.
Emotional Impact and Anxiety Management
The emotional toll of seeking health information and making health-related decisions was
a theme that appeared among participants. They discussed how their searches could both
alleviate and exacerbate health-related anxieties, highlighting the need for strategies to manage
the emotional impact of the information they encountered.
One interviewee described the process as "a double-edged sword," explaining, "While
finding the right information can be empowering, the overwhelming amount of conflicting
advice out there can sometimes leave me more anxious and unsure than before." This sentiment
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highlights the paradox of access to vast amounts of health information—the potential for
empowerment versus the risk of increased anxiety.
Participants also shared specific strategies they used to manage the emotional toll of their
health information searches. One common approach was setting boundaries around their
research, such as limiting the time spent searching or avoiding information-seeking late at night.
"I had to set limits for myself," an interviewee shared, "because diving too deep into health
forums at midnight was doing more harm than good to my mental health."
The role of healthcare professionals in mitigating the emotional impact of health
information was also highlighted. Participants valued interactions with professionals who could
provide clear, reassuring guidance. "Talking to my doctor helped me filter through the noise and
focus on what was actually relevant to my situation," another participant reflected, illustrating
the importance of professional support in managing health-related anxieties.
Likewise, the emotional support of friends and family emerged as a buffer against the
stresses of health information seeking. Sharing concerns and findings with trusted others
provided a sense of validation and perspective that was highly valued. "Discussing my fears and
what I learned with my partner helped me keep things in perspective and not spiral into worry,"
mentioned one participant.
In conclusion, the emotional impact of seeking health information is a significant aspect
of participants' experiences, with anxiety being a central theme. The strategies participants used
to manage this anxiety—setting research boundaries, consulting healthcare professionals, and
leaning on social support—highlight the need for a holistic approach to health information
seeking. Recognizing and addressing the emotional dimensions of this process is important for
supporting individuals in making informed and emotionally sustainable health decisions.
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The Role of Healthcare Professionals
The interaction with healthcare professionals played a significant role in the health
decision-making process for participants, acting as a primary source of authoritative information
and reassurance. Despite the numerous information available through various channels,
healthcare professionals remained a trusted reference point for clarifying doubts and making
informed health decisions. Participants often sought the counsel of healthcare professionals to
verify the information they had found independently. "After reading a lot online, I still felt like I
needed to check with my doctor to get a professional perspective," shared one interviewee.
The quality of the interaction with healthcare providers significantly influenced
participants' satisfaction and trust in the health information received. Positive experiences were
characterized by open communication, empathy, and the healthcare professional's willingness to
engage with the information the patient brought to the table. "My doctor was really open to
discussing the articles I found and helped me understand them in the context of my own health,"
described another participant.
Conversely, experiences where healthcare professionals dismissed concerns or were not
open to discussing externally sourced information lead to frustration and increased reliance on
other information sources. "I felt brushed off when my doctor dismissed the concerns I had based
on my research without much discussion," an interviewee recounted, expressing a sentiment that
could drive individuals to seek validation and answers elsewhere.
The role of healthcare professionals extended beyond just providing information; their
guidance was valuable in helping participants handle the emotional aspects of health decisionmaking. "My doctor's reassurance was key in helping me manage my anxiety about the choices I
was making," one participant reflected.
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In conclusion, healthcare professionals occupy an important role in the health information
system, with their expertise and approach to patient engagement guiding individuals’ health
knowledge and decision-making. However, not all participants had positive interactions with
traditional healthcare providers, leading some to seek alternative healthcare professionals who
could offer a different perspective or were more aligned with their health beliefs and preferences.
The quality of this relationship, whether with traditional or alternative practitioners, can
significantly affect individuals' perceptions of their health choices and their confidence in the
decisions they make.
Distrust in Government Agencies, Traditional Medicine, and Science
A notable theme that emerged from the interviews was a discernible level of distrust
toward government health agencies, traditional medicine, and certain aspects of the scientific
community. This skepticism often stemmed from personal experiences, controversial health
policies, or perceived conflicts of interest within the healthcare and pharmaceutical industries.
Several participants expressed concerns over the recommendations and guidelines issued
by government health agencies, questioning the influence of pharmaceutical companies and
political agendas on these directives. "I find it hard to take everything at face value when I know
there's so much money in healthcare," one interviewee stated, highlighting the perceived impact
of profit motives on health recommendations.
The reliance on traditional medicine was also met with caution by some participants, who
felt that the one-size-fits-all approach did not adequately address individual health needs or
preferences. "After a few negative experiences with prescription medications, I started to
question if there were better, more natural ways to manage my health," shared another
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participant, demonstrating the shift towards alternative health solutions due to dissatisfaction
with conventional treatments.
A segment of the participants exhibited skepticism towards certain scientific studies,
especially those that seemed to contradict their personal beliefs or experiences. This skepticism
was often fueled by stories of past scientific missteps, retracted studies, or research funded by
entities with vested interests. "How can I trust a study that says one thing when I've experienced
the complete opposite?" questioned one interviewee, voicing a common sentiment of mistrust
when personal experiences clash with scientific findings.
While not all participants rejected traditional healthcare and scientific evidence outright,
many advocated for a more informed and critical approach to health information. They
emphasized the importance of doing personal research, seeking multiple sources of information,
and considering alternative perspectives before forming health beliefs and making decisions.
The distrust in traditional health authorities and science highlights a broader desire
among participants for transparency, autonomy, and personalized approaches to health. It also
reflects an engagement with the sources of health information and a call for greater
accountability and standards within the healthcare and scientific communities.
In conclusion, while healthcare professionals and scientific evidence played a role in
some participants' health decision-making, there was a clear call for scrutiny of government
health agencies, the pharmaceutical industry, and the traditional medical establishment. This
perspective advocates for a more individualized, holistic approach to health that values personal
experience and autonomy alongside scientific evidence.
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Openness to New Information
Throughout the interviews, a strong theme of openness to new information emerged,
although with cautious optimism and a strong scrutiny process. Participants indicated that while
they were open to revising their health beliefs and practices, any new information that
contradicted their current understanding required substantial evidence and credibility to be
considered.
One interviewee noted the need for compelling evidence to change an established belief,
stating, "I'm open to new information, but it has to be backed by solid research and make logical
sense compared to what I already know." This statement captures the participants' approach to
new information—balancing openness with a critical evaluation of the evidence's strength and
relevance.
The ever-changing nature of health information and the continuous advancement in
medical research mean that individuals recognize the importance of staying informed about the
latest findings. However, they also expressed a degree of skepticism towards new information,
especially when it appears to conflict with established knowledge or their personal experiences.
"When I come across new health information, I take it with a grain of salt and do my due
diligence in researching before I consider changing anything," shared another participant.
Furthermore, the influence of personal and social networks in disseminating new
information was noted, with participants often engaging in discussions with peers who share
similar health interests. These conversations can serve as a catalyst for researching new health
concepts, as one participant noted, "Hearing about a new health approach from someone in my
friend circle or social media often prompts me to look into it further."
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Overall, participants exhibited an openness to new health information, recognizing the
potential benefits of staying up to date with the latest research and developments. However, this
openness is mitigated by an evaluation process, where the credibility of the information, its
alignment with existing beliefs and practices, and the advice of trusted healthcare professionals
are all carefully considered. This approach reflects a proactive and engaged stance towards
health management, where new information is accepted but scrutinized before being
implemented into personal health decisions.
Discussion
This study examined the reported motivations, strategies, and experiences of individuals
conducting their own health research, highlighting the individualized nature of health
information-seeking behaviors. The findings reveal that personal health research is influenced by
a variety of factors including family upbringing, significant life events, and personal health
experiences. These reported motivations indicate a desire for enhanced well-being and reflect a
broader trend toward proactive health management and skepticism toward traditional health
narratives.
One notable theme that emerged was the significant role of family/friend influence and
life transitions, such as becoming a parent, in catalyzing health information-seeking behaviors.
This highlights the impact of personal life contexts in shaping health priorities and the search for
information that matches individuals’ values and experiences. Additionally, the COVID-19
pandemic served as a catalyst for many, emphasizing the importance of timely and credible
health information during global health crises.
Participants' approaches to sourcing and verifying information highlight an engagement
with both traditional and digital information sources. While peer-reviewed scientific literature
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and consultations with healthcare professionals remain valued sources of information, social
media and personal networks also play an important role in the initial stages of information
gathering. However, this reliance on digital platforms raises concerns about the credibility and
reliability of information, emphasizing the need for literacy skills in evaluating health
information.
The study also highlighted the complexities of handling conflicting information and
making health-related decisions. Participants used various strategies to reconcile discrepancies,
including weighing risks and benefits, consulting with trusted healthcare providers, and relying
on personal judgment. This decision-making process reflects a delicate balance between
empirical evidence, personal experiences, and the perspectives of healthcare professionals.
Conclusion
The findings from this study highlight the complex relationships between personal
experiences, social influences, and decision habits in the pursuit of health information.
Participants' approaches to health research were characterized by a reliance on both personal
networks and validated scientific sources, demonstrating a balance between experiential
knowledge and empirical evidence.
These results provide valuable insights into the factors that motivate individuals to
engage in personal health research and the strategies they employ to understand the available
information. The study also reveals the significant role of different literacies in enabling
individuals to make informed health decisions despite conflicting information.
As this study represents Part I of a larger investigation, it sets the stage for Part II, which
will examine the specific behaviors and attitudes captured through a survey. The subsequent
42
section will build upon the themes identified here, providing a clear understanding of the health
research process among individuals today.
The knowledge gained from both parts of this study will contribute to a more thorough
understanding of contemporary health information-seeking behaviors, with potential implications
for health communication strategies and educational interventions aimed at enhancing health
literacy.
Part II: Online Survey
The exploration of how individuals approach their health decisions—a concept referred
to as Health Decision Habits (HDH) in this study—is at the core of Study 1, Part II. This
research segment builds on the foundational understanding collected from the qualitative
interviews conducted in Part I and progresses to a quantitative examination of the factors
influencing HDH.
HDH encompasses the reported motivations prompting individuals to self-research health
topics and the methodologies they employ in their efforts. Given the various factors that can
shape HDH—ranging from life events and personal health status to various literacies and
biases—this study aims to identify the potential demographic and cognitive functioning variables
that may predispose individuals to specific health decision habits.
Considering the diverse influences on health decision-making, this part of the study seeks
to answer a pressing question: Are there identifiable risk factors, embedded in demographics or
cognitive functioning, that correlate with HDH? This investigation hypothesizes that variables
such as age, education level, income, race/ethnicity, and political ideology may serve as
demographic predictors, while aspects of cognitive functioning—specifically numeracy, critical
thinking, and open-mindedness—could offer further insight into individuals' HDH.
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The evaluation of these potential risk factors is operationalized through validated
cognitive assessments, including the Berlin Numeracy Test (Cokely et al., 2012), which gauges
numeracy; the Cognitive Reflection Test (CRT) by Thomson & Oppenheimer (Thomson &
Oppenheimer, 2016), which assesses critical thinking; and the Actively Open-Minded Thinking
(AOT) scale which measures the extent to which individuals are willing to revise their beliefs in
light of new evidence (Baron et al., 2022).
Figure 1-1 presents a path model illustrating the hypothesized relationships between these
risk factors and HDH, offering a visual guide to the anticipated interactions and influences that
will be examined in this study.
Figure 1-1.
Study 1 path model identifying risk factors for poor health decision habits.
Methods
Following the qualitative insights from Part I of Study 1, Part II's objective was to
quantitatively assess health research behaviors and attitudes among a broader sample of women
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aged 18-45. This phase employed an online survey to collect numerical data that would
complement the qualitative data gathered previously.
Recruitment and Participants
The survey was distributed to two distinct samples (N=498). The first sample consisted
of psychology undergraduate students from the University of Southern California's subject pool
(N=196). The second sample was obtained from Prolific.com (N=302), ensuring a varied
demographic not limited to the university community. Eligibility was confined to female U.S.
residents, between 18 to 45 years of age, and who reported having actively engaged in healthrelated research. The survey was hosted, and the data was collected through Qualtrics.com.
Prolific participants received $2 for their involvement, while subject pool participants were
awarded course credit. Demographic data for the sample is provided in Table 1-1.
Table 1-1.
Demographic table for Study 1 Part II.
Demographics Prolific
(N=302) %
Subject Pool
(N=196) %
Total
(N=496) %
Age
Mean 30 (7.0) 20 (2.2) 26 (7.5)
Median 30 20 23
Education
Less than high school 3 1% 0 0% 3 1%
High school graduate 35 12% 0 0% 72 15%
Some college 70 23% 154 79% 187 39%
2-year degree 38 13% 2 1% 40 8%
4-year degree 104 34% 27 14% 131 27%
Professional Degree 46 14% 1 1% 47 10%
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Hispanic 35 12% 33 17% 68 14%
Race
White 241 79% 97 51% 338 68%
Black/African American 33 11% 20 10% 53 11%
American Indian/Alaska
Native 8 3% 1 1% 9 2%
Asian 33 11% 68 35% 101 20%
Native Hawaiian/Pacific
Islander 1 1% 3 2% 4 1%
Other 5 2% 10 5% 15 3%
Income
Less than $29,999 81 27% 39 20% 120 10%
$30,000 to $59,999 82 28% 11 6% 93 6%
$60,000 to $99,999 69 23% 25 13% 94 7%
$100,000 to $149,999 38 13% 21 11% 59 12%
$150,000 or more 18 6% 54 28% 72 15%
Prefer not to say 9 3% 34 17% 43 9%
Political Ideology
1 (Liberal) 83 28% 25 26% 108 23%
2 83 28% 63 66% 146 30%
3 43 15% 53 55% 96 20%
4 54 18% 29 30% 83 17%
5 13 4% 10 10% 23 5%
6 14 5% 3 3% 17 4%
7 (Conservative) 7 2% 0 0% 7 2%
Children 85 28% 4 2% 89 19%
Single / Never Married 208 68% 180 94% 388 81%
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Note: Since demographic variables are optional percentages may not sum to 100%.
Health Research Behavior Survey
The survey was administrated through the Qualtrics platform (Qualtrics.com), designed
to be a one-time, anonymous questionnaire. The study was classified as exempt by the USC IRB,
and informed consent was collected from each participant before the survey data collection.
The health research behavior survey consisted of 13 survey questions followed by
cognitive assessments and demographic questions. Survey items were presented in multiplechoice, 'select all that apply,' and Likert scale formats. The median completion time for the
survey was 7 minutes and 50 seconds. The full health research behavior survey is provided in
Appendix B.
Cognitive Measures
As part of the comprehensive assessment participants completed additional cognitive
tests alongside the health research behavior survey. These tests included the Berlin Numeracy
Test, the Cognitive Reflection Test, and the Actively Open-Minded Thinking (AOT) Test, each
chosen for their relevance and validated contributions to understanding critical thinking and
decision-making in health contexts.
The Berlin Numeracy Test, developed by Cokely et al. (2012), is a robust measure of risk
literacy and numeracy, recognized for its efficacy in diverse populations, including online
samples. This test is particularly concise and effectively measures an individual's ability to
understand and apply statistical and probability information relevant to everyday risks, thereby
providing a foundation for understanding participants' abilities to engage with numerical health
information. Due to survey time constraints, the single-item version of the test was implemented.
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The Cognitive Reflection Test -2 (CRT-2), as updated by Thomson & Oppenheimer
(2016), is designed to measure participants' capacity for critical thinking. It has been shown to
correlate with the propensity to discern misinformation, a key factor in evaluating health
information (Bronstein et al., 2019; Byrd & John, 2021; Pennycook & Rand, 2019). The CRT-2's
relevance to this study lies in its ability to provide insight into the participants' evaluation of
health information and decision-making processes.
The revised AOT measure (Baron et al., 2022) assesses the extent to which individuals
engage in open-minded thinking. It evaluates the willingness to consider new information and
adjust existing beliefs when confronted with credible evidence (Baron, 2018, 2019). The AOT is
instrumental in gauging how individuals assess arguments and construct evidence-based beliefs.
Its association with CRT (Thoma et al., 2021) and its relevance to discerning misinformation
(Martel et al., 2021), as well as its implications in important issues such as climate change,
medical decisions, and political beliefs (Pennycook & Rand, 2019), make it especially relevant to
this study.
By incorporating these established cognitive tests into the survey, the study seeks to
understand the behaviors and attitudes of individuals engaged in health research and the
cognitive factors that contribute to their ability to manage health information. This
comprehensive approach ensures a thorough analysis of the factors contributing to health
literacy.
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Results
Motivations for Conducting Health Research
The survey provided insights into the various reasons that individuals are motivated to
conduct their own health research. Most participants, 79%, cited unresolved health issues, such
as undiagnosed medical conditions, fertility concerns, or complications from treatments, as their
primary motivators. This suggests a significant reliance on self-directed research when
confronted with health uncertainties or dissatisfaction with conventional medical advice.
Furthermore, a substantial 63% of participants were prompted by external influences,
including recommendations from friends, information on social media, documentaries, news
articles, podcasts, or events such as the COVID-19 pandemic. This indicates the substantial
impact of societal and social network factors on individuals' decisions to seek health information
independently.
Distrust in traditional medicine or science was a motivator for 19% of the respondents,
reflecting a notable skepticism towards conventional healthcare systems and scientific
authorities. This group may represent a segment of the population turning to self-research to
validate or supplement the information provided by traditional sources.
The reported motivations identified suggest that while some individuals are drawn to selfresearch due to direct health-related challenges, others may be influenced by a broader context of
influences, including social, cultural, and systemic factors. These findings emphasize the
importance of understanding the relationship of internal and external factors that shape health
information-seeking behaviors. Results are displayed in Figure 1-2.
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Figure 1-2.
Participants' reported motivations for conducting their own health research.
Note: Values may add up to more than 100% considering participants could select more than one option.
Life Events Influencing Health Research
The participants reported a variety of life events that motivated their pursuit of health
research. The majority, 79%, indicated a general desire to be healthier as their reason for
conducting health research, demonstrating a proactive approach to health and wellness among
the survey participants.
A large percentage of participants began their research when they started experiencing
health problems without a diagnosis (69%), or after receiving a health diagnosis (44%). Thus, the
role of personal health experiences is a significant catalyst for many seeking additional
information.
The COVID-19 pandemic was cited by 46% of the participants as a motivating factor,
reflecting the impact of global health crises on individual health information-seeking behavior. A
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considerable portion of the sample reported that the onset of health problems in a child, partner,
or family member (36%) prompted them to do research. This suggests that the health challenges
of close relations can be a strong motivator for individuals to seek additional health information.
Financial concerns or lack of insurance were reported by 18% of the participants as a
reason for conducting their own health research, indicating that economic factors and
accessibility to healthcare can influence the decision to seek information independently. The
influence of social networks was also evident, with 17% of participants motivated by a friend,
partner, or family member who shared their own findings from health research.
Less common were life-changing events such as recently becoming a parent (7%) or
trying to conceive or becoming pregnant (6%), although these low values could be due to the age
and demographics of the subject pool sample. A small proportion of participants indicated that
no specific life event was occurring when they decided to conduct health research (4%), or they
specified other unique motivations (5%).
These results illustrate that both personal and situational factors can significantly
influence individuals’ decisions to engage in health research, highlighting the interaction
between an individual’s health context and their information-seeking behavior. Values are shown
in Figure 1-3.
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Figure 1-3
Participants reported life events when they did their own research.
Note: Values may add up to more than 100% considering participants could select more than one option.
Health Research Topics
The survey examined the range of topics participants had researched concerning their
health. The majority indicated that they had researched issues surrounding nutrition, diet, and
food, with 84% of participants engaging with this topic. This was closely followed by medication
and exercise, with 80% and 78% of the participants researching these topics respectively.
Medical diagnoses were also a common subject of research, cited by 75% of the
respondents. A significant portion of the sample, 70%, looked into beauty products, which can be
indicative of the broader interests encompassing health and well-being.
Vaccines and supplements were researched by more than half of the participants, with
56% and 55% respectively. These findings could reflect the growing public discourse and
concern about vaccinations and the rising interest in dietary supplements.
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Research into specific medical treatments and surgeries was noted by 54% of the
participants, suggesting a proactive approach to understanding and potentially deciding on
medical procedures. Household products were another notable subject, with nearly half of the
respondents (47%) seeking information on them, possibly due to increasing awareness of the
health impacts of everyday products.
Less commonly researched topics included alternative/complementary medicine and
organic products, with 30% and 29% respectively, indicating a smaller yet significant interest in
these topics. These results paint a comprehensive picture of the subjects that individuals are
interested in and choose to research, providing insights into the various aspects of health and
wellness that concern the modern health-conscious individual. Details are displayed in Figure 1-
4.
Figure 1-4.
Counts and percentages of participants who selected that they had researched a topic.
Note: Values may add up to more than 100% considering participants could select more than one option.
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Utilization and Trustworthiness of Health Research Sources
The survey responses identified a compelling disparity between the health information
sources used by participants and those they considered reliable1
. Health websites such as
WebMD and Healthline were widely utilized (82% of participants), yet there was a disconnect
between usage and trust, as 55% found them reliable and 14% did not. This suggests that while
these sites are convenient and frequently accessed, there's an underlying skepticism about their
reliability.
In contrast, medical agency websites from organizations such as the American Heart
Association and the American Cancer Society were both widely used (54%) and highly trusted
(79%). This demonstrates a strong alignment between usage and trust, with participants favoring
established medical entities for reliable information.
Federal and global agency websites, including those of the CDC and WHO, showed a
similar trend, with 55% of participants consulting them and 69% considering them trustworthy,
reinforcing the authority of official health organizations.
While academic articles were less frequently used (45%), they received a relatively high
trust rating (66%), pointing to the respect for scientific research despite it being less commonly
consulted, likely due to accessibility barriers.
Traditional medical professionals were trusted by a substantial 74% of participants but
were consulted by only 44%. This discrepancy may reflect the perceived inaccessibility or time
constraints associated with consulting professionals directly.
1 Note: While search engines were the most used source for health research, used by 95% of participants, this survey
did not assess their perceived reliability, since these platforms are intermediaries that lead to other information
sources rather than being direct sources themselves.
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Social media's role was particularly striking, with 36% of participants using these
platforms for health research yet an overwhelming 85% deeming them unreliable. This paradox
indicates that despite recognizing the potential unreliability of health information on social
media, its ease of access continues to make it a commonly used resource.
Friends and family were consulted by 38% of respondents, but only 33% found these
personal interactions reliable, with nearly half (46%) considering them unreliable. This
discrepancy reflects the complex nature of weighing personal relationships against the need for
accurate health information.
Internet blogs and books, though utilized by a minority (32% and 20%, respectively),
demonstrated a mismatch between usage and perceived reliability, suggesting that while certain
resources may be part of participants' research process, they do not necessarily consider them
trustworthy.
Complementary/alternative healthcare providers, while only used by 11%, were
considered reliable by nearly 19%. This indicates a select group of participants place significant
trust in alternative health approaches despite their overall lower usage rate.
These findings highlight a dichotomy in health information-seeking behavior, with
participants often resorting to sources they do not fully trust, such as social media and health
websites. It reveals a decision-making process where convenience, accessibility, and existing
habits may influence the choice of health information sources more than their perceived
trustworthiness. Full results of the utilization, reliability, and unreliability values for each source
are presented in Figure 1-5.
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Figure 1-5
Sources participants used, viewed as reliable, and viewed as unreliable.
Note: Values may add up to more than 100% considering participants could select more than one option.
Assessing Source Trustworthiness in Health Decision Habits
When asked if they usually “fact check” their sources the participants' responses varied.
Only a small percentage (2%) reported never assessing source trustworthiness, suggesting a
possible oversight or a high level of trust in the sources they tend to choose. A segment of the
sample (15%) acknowledged that they sometimes consider the trustworthiness of their sources.
This intermittent scrutiny could indicate a reliance on familiar sources or possibly an assumption
of credibility based on past experiences.
Approximately 12% of participants indicated that they assess the trustworthiness of their
sources about half the time. This selective approach might be influenced by the nature of the
information being sought or by the perceived credibility of the source based on context.
The largest group, making up 42% of respondents, stated they attempt to determine the
trustworthiness of sources most of the time. This suggests a conscious effort to validate
information.
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Lastly, 28% of the sample claimed they always check the reliability of their sources,
highlighting a group of participants who consistently apply due diligence when seeking health
information. This level of consistent scrutiny represents a commitment to informed health
decision-making and suggests a higher level of health literacy and engagement.
These results indicate a spectrum of behaviors related to trustworthiness assessment, with
a significant number (70%) of participants showing an understanding of the importance of
verifying the credibility of health information sources. However, the data also suggest that there
is room for improvement in the consistency of such practices, which could be addressed through
health literacy education and the promotion of best practices for health information validation.
Values are displayed in Figure 1-6.
Figure 1-6
Participants' response to verifying source trustworthiness.
Depth of Research Sources in Health Decision-Making
When participants engaged in health research, the majority demonstrated a thorough
approach: 57% usually sought out three or more sources. A smaller segment, representing 39%
of respondents, preferred to consult two sources before concluding their research. Only a
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minimal 5% of the sample indicated that they typically stopped their research after finding one
source.
These findings reflect a strong inclination towards comprehensive research among
participants, suggesting a strong desire to obtain a well-rounded understanding of health-related
topics. The preference for consulting multiple sources may also indicate an awareness of the
complexities present in online health information.
Approaches to Reconciling Conflicting Health Information
Confronted with conflicting health information, a significant majority of participants
actively engaged in further research, with 76% reading additional sources to determine the most
agreed-upon viewpoint. A substantial 65% of participants habitually fact-checked their sources,
while 61% took a more analytical approach, comparing the quality of research and information
presented on both sides of an argument.
A smaller percentage of participants chose less proactive strategies. About 18% preferred
to move on without reaching a definitive conclusion on what information to trust, indicating a
level of indecision or acceptance of ambiguity in their health research process.
Only a minority, 10%, reported that they typically believe information that confirms their
pre-existing beliefs, showing a confirmation bias that can impact the objectivity of their health
decision-making.
These findings suggest that while most individuals are diligent and methodical when
faced with conflicting health information, a portion of the population may still fall back on
personal beliefs or avoid engaging with conflicting data, potentially affecting the quality of their
health decisions. Results are shown in Figure 1-7.
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Figure 1-7
Participants' responses to handling conflicting information.
Note: Values may add up to more than 100% considering participants could select more than one option.
Openness to Revising Health Conclusions
A vast majority of participants indicated a high degree of openness to reassessing their
health decisions when confronted with new information. As depicted in the survey responses, an
overwhelming 93% stated that they would investigate the reliability of the new information
before considering any changes to their previous conclusions. This suggests a commitment to
due diligence before altering their health beliefs or behaviors.
A small portion, 5%, expressed readiness to accept new information outright and change
their conclusions accordingly, showing a level of adaptability to evolving evidence. Only a
minimal 2% reported that they would disregard new, conflicting information and maintain their
original conclusions, reflecting a degree of resistance to changing established beliefs or practices.
These findings indicate that most participants report being engaged in their health
decision-making process and exhibit a thoughtful and analytical approach when encountering
new information that challenges their existing health conclusions.
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Predictive Factors of Health Decision Motivations
Multiple binary generalized linear models (GLMs) were run for participants' reported
motivations for conducting their own health research. These models aimed to identify potential
demographic and cognitive functioning variables that could act as risk factors for health decision
habits.
Three key motivational factors were examined: unresolved health issues, distrust in
traditional science/medicine, and being motivated by someone/something. Each motivational
category was assessed against various predictors, including cognitive tests (AOT, BNT, CRT)
and demographic variables (education, race, income, political ideology).
For the reported motivation rooted in Unresolved Health Issues, the likelihood of
engaging in health research increased as Actively Open-Minded Thinking (AOT) scores
increased (OR = 1.44, CI [1.11, 1.88], p = 0.007) and Cognitive Reflection Test (CRT) scores
increased (OR = 1.57, CI [1.13, 2.21], p = 0.008). Conversely, higher numeracy skills as
assessed by the Berlin Numeracy Test (BNT) were associated with a decreased likelihood (OR =
0.57, CI [0.34, 0.95], p = 0.031). This suggests that those with greater open-mindedness and
critical thinking propensity are more inclined to engage in health research due to unresolved
health issues, while those with higher numeracy may rely on their ability to interpret quantitative
data, possibly reducing the need for further research.
In terms of Distrust in Traditional Science/Medicine, higher CRT scores significantly
decreased the odds of being motivated by distrust (OR = 0.61, CI [0.43, 0.86], p = 0.005). The
results indicated that those with higher CRT scores were less likely to be motivated by distrust in
traditional science/medicine. Furthermore, political ideology had a significant relationship with
this reported motivation. Participants with more self-reported conservative political views were
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more likely to report distrust in traditional science/medicine as a motivator for their health
research. Specifically, a conservative political ideology increased the odds of participants being
motivated by distrust in traditional science/medicine (OR = 1.52, CI [1.05, 2.18], p = 0.024).
In the context of being Motivated by Someone/Something, the CRT score was once again
a significant predictor. Higher CRT scores suggested a decreased likelihood of being motivated
by external influences (OR = 1.33, CI [1.00, 1.77], p = 0.050). Race was also a significant factor,
with non-white participants being less likely to be influenced by external motivators (OR = 0.53,
CI [0.33,0.85], p < 0.05).
Overall, these models highlight the factors that drive individuals to seek health
information and suggest that both cognitive abilities and demographic factors such as political
ideology play a role in shaping health decision habits. The models are displayed in Table 1-2.
Table 1-2.
Binary Generalized Linear Models for participants' reported motivations.
Note: AOT is standardized. BNT is binary. CRT is measured on a scale from 0-3. Education is measured using a
dichotomous variable where less than a 4-year college degree is 0 and a 4-year college degree or greater is 1.
Income is measured on a four-point scale where “Less than $50,000” = 0, “$50,000 to $99,999” = 1, “$100,000 to
$149,999” = 2, “$150,000 or more” = 3. Political ideology was measured on a 7-point scale from 1 to 7 where 1 is
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extremely liberal and 7 is extremely conservative. The political values were then recoded into -1 for values 1-3, 0 for
4, and 1 for values 5-7.
Predictive Factors of Health Information Source Utilization
The utilization of various health information sources was examined through binary
generalized linear models (GLMs), each predicting the likelihood of participants using a
particular source based on cognitive tests and demographic variables.
Federal/Global Agency Websites: AOT scores were positively associated with the use of
federal and global agency websites (OR = 2.08, p < 0.001). Political ideology had a negative
relationship, with more conservative views being associated with less use (OR = 0.68, p =
0.026).
Medical Agency Websites: Participants with higher open-mindedness (AOT) were more
inclined to use medical agency websites (OR = 1.16, p = 0.001).
Academic Articles: Participants with higher AOT scores were more likely to use
academic articles (OR = 1.67, p < 0.001), with education level also playing a significant role,
where those with higher education were more likely to refer to academic literature (OR = 1.67, p
= 0.016).
Health Websites: Open-mindedness was again a significant predictor, with participants
with higher AOT scores more likely to refer to health websites (OR = 1.69, p < 0.001).
Internet Search Engines: The results indicated a strong association between Actively
Open-Minded Thinking (AOT) and the use of Internet search engines for health information.
Participants with higher AOT scores were significantly more likely to use search engines (OR =
2.46, p < 0.001).
Social Media: Both the Berlin Numeracy Test (BNT) and AOT scores were significant
predictors for using social media as a health information source. Higher numeracy skills
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increased the likelihood of using social media (OR = 1.68, p = 0.017), whereas higher AOT
scores decreased the likelihood of using social media (OR = 0.68, p = 0.001).
Blogs: There were no significant predictors for using blogs as a source of information.
Books: Critical thinking, as measured by the Cognitive Reflection Test (CRT), was a
significant predictor for referring to books. Higher CRT scores increased the likelihood of using
books as a source (OR = 1.50, p = 0.039).
Traditional Medical Professionals: Higher AOT scores and CRT scores were associated
with an increased likelihood of using traditional medical professionals as information sources
(OR = 1.36, p = 0.007 and OR=1.44, p=0.018 respectively). Race was a significant predictor,
with non-white participants more likely to use these professionals (OR = 2.22, p = 0.001).
Alternative Healthcare Providers: There were no significant cognitive or demographic
predictors identified for the use of alternative healthcare providers.
Friends or Family: Higher AOT scores were associated with a decreased likelihood of
using friends and family as information sources (OR=0.78, p=0.024)
These results illustrate that cognitive factors, particularly open-mindedness, are
significant predictors of using various health information sources. Additionally, demographic
factors such as race and political ideology also influence the likelihood of using these sources.
The findings suggest that individuals' values and cognitive abilities play an important role in how
they seek and use health information. Full model details are presented in Table 1-3.
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Table 1-3.
Binary Generalized Linear Models for participants' choice of sources.
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Note: AOT is standardized. BNT is binary. CRT is measured on a scale from 0-3. Education is measured using a
dichotomous variable where less than a 4-year college degree is 0 and a 4-year college degree or greater is 1.
Income is measured on a four-point scale where “Less than $50,000” = 0, “$50,000 to $99,999” = 1, “$100,000 to
$149,999” = 2, “$150,000 or more” = 3. Political ideology was measured on a 7-point scale from 1 to 7 where 1 is
extremely liberal and 7 is extremely conservative. The political values were then recoded into -1 for values 1-3, 0 for
4, and 1 for values 5-7.
Discussion
Study 1 Part II examined the Health Decision Habits (HDH) of women aged 18-45 in the
United States, to identify the reported motivations, processes, and cognitive factors influencing
their health research behaviors. The survey identified the diversity in health topics of interest,
with a substantial focus on nutrition/diet/food, medication, and exercise. This broad range of
topics highlights the comprehensive nature of health concerns that prompt individual research
efforts.
Reported motivations for engaging in health research were predominantly driven by
unresolved health issues and a desire to be healthier, reflecting a proactive stance toward
personal health management. The COVID-19 pandemic acted as a significant catalyst,
highlighting how global health crises can accelerate health information-seeking behaviors.
An important finding was the relationship between the sources participants used for
health information and their perceptions of these sources' reliability. While internet search
engines and health websites were the most frequently used, there was a notable "social media
paradox" where over one-third of participants continued to use social media for health
information despite overwhelmingly viewing it as unreliable. This paradox suggests that ease of
access to information and habitual social media use may override concerns about information
quality. An alternative explanation could be that while participants may generally view social
media as unreliable, they might believe that certain parts of it are still trustworthy and feel
capable of distinguishing between reliable and unreliable information. As a result, they may
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continue to use social media as a source, confident in their ability to find credible information
even when unreliable information is present.
The study further examined the process of assessing source trustworthiness, revealing
that most participants strive to verify the credibility of their information sources, although not
consistently. This indicates an awareness of the importance of source reliability, though practices
vary in thoroughness. Additionally, participants often integrate information from multiple
sources such as the internet, doctors, friends, and family to form a more comprehensive
understanding of health-related topics.
Predictive models for reported motivations behind health research highlighted the
influence of cognitive factors such as open-mindedness and critical thinking, as measured by
AOT and CRT scores, respectively. These cognitive abilities were associated with a higher
likelihood of engaging in health research driven by unresolved health issues, whereas higher
CRT scores were linked to reduced reported motivation by distrust in traditional
science/medicine.
Regarding source utilization, cognitive factors, particularly AOT scores, were significant
predictors for the use of various health information sources. Suggesting that individuals with
higher levels of open-minded thinking are more inclined to engage with a wider range of
information sources, potentially enhancing their ability to make informed health decisions.
This research offers significant practical implications across various domains concerned
with health literacy and decision-making. For health practitioners, understanding the motivations
and cognitive processes behind individuals' health information-seeking behaviors can inform
more effective patient communication strategies. Recognizing the specific needs and preferences
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identified in this study can help practitioners guide patients toward reliable information sources
and engage in more meaningful discussions about health decisions.
Policymakers and public health officials can use these insights to design targeted health
communication campaigns. By acknowledging the influence of personal motivations, life events,
and the role of cognitive factors in health information processing, campaigns can be designed to
address the specific needs of different demographic groups, enhancing the overall impact of
public health messaging.
Due to the association between political orientation and distrust of traditional medicine, it
is important to highlight the limits of doing your own research. Individuals must be made aware
of the importance of consulting healthcare professionals and relying on scientifically verified
information. Educational efforts should emphasize critical thinking while also recognizing the
boundaries of personal health research to avoid misinformation and ensure safe health practices.
Educators in the field of health literacy have an important role to play in bridging the gap
identified between the use of and trust in various health information sources, particularly social
media. Curriculum development that focuses on necessary health literacy skills, including
evaluating source credibility and handling conflicting information, is essential. These programs
should aim to empower individuals with the tools necessary to make informed health decisions in
the current digital society.
Conclusion
The findings from Study 1 Part II offer insights into Health Decision Habits, emphasizing
the nature of health information-seeking behaviors. The paradox of social media use, despite its
perceived unreliability, and the variations in how individuals assess source trustworthiness,
highlight the necessity for improved health literacy education to effectively manage health
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information. Furthermore, the cognitive and demographic predictors identified as reported
motivations in health research and source utilization suggest important avenues for future
interventions designed to promote informed health decision-making.
An understanding of the detailed approaches individuals take toward their health
research, including the relationship between reported motivations, life events, source utilization,
and cognitive abilities, enables a more supportive environment for individuals to access reliable
health information and make decisions that reflect their health and wellness objectives. Moving
onto Study 2, these insights provide foundational knowledge for further investigation into the
factors affecting health research behaviors present today.
Limitations, Future Research, and Conclusion
The findings from Study 1 offer significant insights into the reported motivations,
processes, and cognitive factors influencing health research behaviors among women aged 18-
45. However, this investigation is not without its limitations, which pave the way for future
research directions.
One limitation is the reliance on self-reported data, which may introduce recall or social
desirability biases, potentially affecting the accuracy of reported health research behaviors.
Future studies could benefit from incorporating objective measures, such as web browsing
histories, to corroborate self-reported data and provide a better understanding of health
information-seeking patterns.
The study's sample, while diverse, was limited to women within a specific age range
from the United States, which may limit the generalizability of the findings to other
demographics and cultural contexts. Moreover, the sample had a liberal skew, potentially
impacting the applicability of the results to people with diverse political perspectives.
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Expanding the scope of future research to include a wider range of ages, genders, political
ideologies, and international perspectives would enhance our understanding of health decisionmaking behaviors across different populations.
Furthermore, the cross-sectional design of this study limits the ability to draw causal
inferences regarding the relationships between cognitive factors, demographics, and health
decision habits. Longitudinal studies or experimental designs that involve interventions aimed at
enhancing health literacy and decision-making processes could provide insights into causal
mechanisms and the effectiveness of such interventions.
Considering the identified predictors of health decision habits, future research should also
examine the development and evaluation of targeted interventions to improve health literacy and
decision-making skills. Study 2 will build on the findings from Study 1 by designing,
implementing, and assessing the impact of an intervention designed to address the specific needs
and preferences identified in this study.
Chapter 3: Study 2
Abstract:
Study 2 (N=300) presents a dual-phase approach: initially, it details the creation and
validation of the Health Decision Literacy (HDL) Scale (N=200). Following this, the study
introduces a podcast-based intervention titled "Fact Check Your Health," which aims to enhance
HDL. This intervention, spread across five educational episodes, covers topics such as health
research methodologies, commonly misunderstood terms, and health information evaluation
techniques. Through a three-group variant of the Solomon four-group design, the experiment
(N=100) demonstrates a significant increase in Health Decision Literacy scores, with participants
exposed to the intervention experiencing an average improvement of 28.6% compared to a
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7.61% improvement in the control group. This significant finding demonstrates the effectiveness
of the "Fact Check Your Health" podcast in improving participants' ability to evaluate and use
health information.
Introduction:
Access to the internet and the growth of social media have granted unprecedented access
to health information, significantly changing health decision-making. While the digital space
offers numerous opportunities, it also introduces significant challenges, particularly in discerning
credible sources amongst widespread misinformation. Recognizing the role of health decision
literacy (HDL)—the capacity to find, understand, and utilize online health information for
informed decision-making—is necessary in this context. As the reliance on digital platforms
grows, so does the necessity for interventions aimed at enhancing critical thinking, various
literacies, and the identification of trustworthy health information.
Responding to these challenges, Study 2 introduces "Fact Check Your Health," a podcastbased intervention designed to boost HDL among women aged 18-45. This demographic often
finds itself at the center point of health decision-making necessitating targeted support. Using the
accessible and engaging nature of podcasts, the intervention aims to equip listeners with the
skills needed to assess health research methodologies, risk assessments, and the credibility of
health information.
Insights from Study 1—such as the paradox between the frequent use and the perceived
trustworthiness of digital health information sources—highlight the need for the intervention.
Study 1’s findings on the significant roles of open-mindedness and critical thinking in health
information-seeking behavior further justify the focus of this intervention. By addressing the
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gaps and challenges identified in Study 1, Study 2 seeks to provide a practical, accessible
solution aimed at empowering women with the essential skills for making informed health
decisions in an increasingly digital society.
Previous Research on Literacies and Literacy Interventions
Understanding the complexity of health decision-making in a digital media society
requires a comprehensive approach that incorporates various literacies. These literacies — health
literacy, media literacy, information literacy, risk literacy, statistical literacy, and critical thinking
— are fundamental to analyzing, interpreting, and applying online health information.
Health Literacy
Health literacy is the foundation of informed health decision-making in healthcare. This
skill set involves accessing, understanding, and effectively using health information and is
increasingly important as digital media becomes integral to health communication and
information (Nutbeam, 2013; Xie, 2012).
Recent educational programs and training initiatives, such as those conducted by Xie
(2012), have made strides in improving e-health literacy through computer training using online
NIH resources. These programs have been particularly beneficial for older adults, providing
them with the tools necessary to use online health environments effectively. Whitley et al.
(Whitley et al., 2018) have addressed mental health literacy among educators, showcasing the
importance of literacy training that is specific to certain domains, such as mental health, within
the educational setting.
The outcomes of these health literacy interventions generally suggest improvements in
knowledge and an increased capacity for personal health management. Watkins and Xie (2014)
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demonstrate that interventions can significantly empower individuals, especially older adults,
enhancing their ability to engage with e-health resources and make more informed decisions
regarding their health.
Despite the progress, there remain gaps in the reach and inclusivity of these interventions.
Challenges such as unequal access to digital resources and content that lacks cultural relevance
continue to be obstacles in health literacy improvement efforts. As a response to these
challenges, recent interventions are adopting more personalized approaches that consider
individual differences in culture, language, and access to technology, striving to make health
literacy resources more accessible and effective across diverse populations (Kim & Xie, 2017).
Moreover, recent literature continues to emphasize the significance of health literacy in
health outcomes and its status as a social determinant of health. Research by Yuen et al. (2024),
Nutbeam and Lloyd (2021), Ayre et al. (2023), Stormacq et al. (2019), Paakkari & Okan (2020),
Visscher et al. (2018), Geboers et al. (2018), Walters et al. (2020), and C. Liu et al. (2020) offers
a further understanding of health literacy interventions, their outcomes, and the potential to
enhance health literacy across different social demographics and world events, including public
health crises such as the COVID-19 pandemic.
The comprehensive approach to health literacy interventions proposed by Geboers et al.
(2018) highlights the need for initiatives that include the development of personal skills and the
improvement of healthcare services and information accessibility. Additionally, the systematic
reviews conducted by Visscher et al. (2018) and Walters et al. (2020) provide evidence of the
effectiveness of these interventions, further supporting their significance in public health
promotion. 'Fact Check Your Health' aims to enhance e-health literacy by providing listeners
with strategies to effectively use online health environments, thus providing them with the tools
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to make informed health decisions in a digital media society. In conclusion, health literacy
remains a construct influenced by a variety of social, economic, and cultural factors. As digital
information evolves, interventions must also adapt, employing innovative and inclusive
strategies to enhance health literacy.
Media Literacy, Information Literacy, and Misinformation
Within the framework of health literacy, information literacy and media literacy play
important roles in equipping individuals with the skills necessary for understanding health
information. These literacies are particularly essential considering misinformation can easily
proliferate, complicating the task of making informed health decisions.
Information literacy provides the foundation for evaluating the credibility of information
sources, a skill that becomes increasingly important as misinformation becomes more
sophisticated. Efforts such as the game "Fakey" by Micallef et al. (2021) and the digital media
literacy intervention by Guess et al. (2020) highlight innovative approaches to enhancing news
literacy and thoughtful engagement with social media content. These interventions demonstrate
the potential of media literacy programs to influence media consumption habits positively,
suggesting a broader impact on public health literacy.
Jones-Jang et al. (2021) and Hameleers (2022) further demonstrate the effectiveness of
literacy interventions in identifying misinformation and enhancing media consumption skills.
Their findings suggest that equipping individuals with the skills to thoughtfully analyze media
content can be more sustainable and impactful than reactive measures such as fact-checking.
However, the challenges in media literacy education persist, with interventions such as
those discussed by Badrinathan (2021) and Byrd & John (2021) highlighting the difficulties of
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digital media. These challenges emphasize the need for adaptive and flexible media literacy
interventions that can respond to the evolving digital environment.
Pangrazio et al. (2020) call for a thorough understanding of digital literacy, indicating
that media literacy education must adapt to the diverse contexts and rapidly changing digital
platforms. This approach is important for ensuring that literacy interventions remain effective in
enabling individuals to discern credible information.
As media and information literacy continue to play a role in public health, the integration
of these literacies into health literacy initiatives is important. By supporting an understanding of
media content and enhancing the ability to identify credible information, these literacies
contribute significantly to the overall goal of improving health decision-making in a digital
society. The intervention in this study aims to improve these literacies by equipping listeners
with evaluation skills to discern the reliability of health information sources and understand
digital health information.
Critical Thinking Interventions
Critical thinking is an essential literacy in health decision-making, enabling individuals to
analyze and evaluate information methodically. This skill set is fundamental for evaluating and
synthesizing health information in an environment with both information overload and
misinformation.
Studies such as those by Lutzke et al. (2019) have shown that simple critical thinking
prompts can reduce the influence of fake news on social media. Similarly, Bensley et al. (2010)
found that structured critical thinking instruction could enhance argument analysis skills,
highlighting the potential for such skills to be transferred across different domains of knowledge.
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Halpern's (1998) "structural component" model has been influential in designing
interventions that encourage the transfer of critical thinking skills across contexts. The
effectiveness of these interventions in various educational settings suggests that the skills
acquired can be applied to health literacy and beyond. While the positive outcomes of these
interventions are clear, challenges remain in ensuring that such skills are adopted widely and
retained over time. As Nieto and Saiz (2008) note, the continuous evolution of information
sources calls for adaptable strategies that can address new forms of misinformation and biases.
By incorporating critical thinking into health literacy interventions, individuals are better
equipped to make informed health decisions and evaluate digital information. The podcast in this
study incorporates structured discussions and critical thinking prompts designed to refine
listeners' evaluative skills.
Statistical and Risk Literacy
Understanding statistical data and risk is another necessary component of health decisionmaking. These literacies enable individuals to interpret and apply statistical information, assess
risks, and make informed choices about topics such as health interventions, lifestyle changes, and
medical treatments.
Statistical literacy interventions have been instrumental in enhancing the ability to
comprehend and use statistics (Dani & Joan, 2004; Gal, 2002, 2004; Garfield & Ben-Zvi, 2007;
Gigerenzer et al., 2007). For example, initiatives have focused on educating individuals about
statistical concepts, enabling them to understand the probabilities and outcomes reported in
medical research (Gigerenzer, 2015).
Risk literacy, closely related to statistical literacy, pertains to the comprehension of the
probabilities of potential outcomes and the ability to make decisions based on these risks. It's an
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essential skill for managing everyday health choices, understanding medical advice, and
consenting to treatments. The work of Gigerenzer has been instrumental in this field,
highlighting the necessity of risk literacy in society. His research suggests that improving
people's risk literacy could lead to better health outcomes by enabling more informed decisions
(Gigerenzer, 2015, 2022; Gigerenzer et al., 2007).
However, despite the availability of such educational resources, a gap remains in the
general public's understanding of statistical concepts and risk. This gap can lead to
misconceptions about health risks, potentially resulting in suboptimal health decisions.
Recent interventions have provided valuable insights into effective educational strategies.
Nawabi et al. (2021) highlights the importance of health literacy in pregnant women, which
includes the comprehension of statistical data relevant to prenatal care decisions. Similarly,
interventions aimed at enhancing health professionals' understanding of statistics, as examined
by Friederichs et al. (2020), demonstrate that even clinicians benefit from targeted education in
statistical reasoning—a skill vital for interpreting research findings and communicating risks to
patients.
To bridge the gap between professional expertise and patient understanding, van Weert et
al. (2021) have examined the role of visual aids in conveying health risks. Their work suggests
that age, health literacy, and numeracy significantly impact how patients interpret graphical data,
thus influencing their health-related decisions.
Furthermore, Aven (2023) addresses the foundational aspects of risk literacy, linking it to
the broader field of risk science, which has implications for public health policy. Regarding
shared decision-making, particularly with patients who have limited health literacy, Richter et al.
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(2023) have examined the effectiveness of various risk communication strategies, highlighting
the need for clear and accessible information.
The interventions and strategies documented in these studies form the basis for
implementing effective statistical and risk literacy programs. They illustrate the diverse needs
across different populations—be it enhancing the competencies of healthcare professionals or
empowering patients with the knowledge to make informed choices. As such, these literacies are
integral to the overarching goal of improving health decision-making competencies. To improve
these literacies the podcast intervention explains statistical concepts and risk assessments
through clear explanations and relatable examples, making these aspects of health research
accessible to listeners. This approach aims to improve listeners' capacity to interpret research
findings and make informed decisions based on statistical evidence.
Boosting Interventions
Boosting interventions offer a promising strategy within behavioral sciences for
enhancing decision-making competence. Unlike nudges, which subtly guide decisions, boosting
interventions aim to fundamentally enhance individuals' ability to make informed choices
independently. This is achieved through targeted education and training that improves cognitive
abilities and decision-making skills, drawing on principles that short, targeted sessions or
exposure to specific types of information can significantly enhance cognitive capacities and
decision-making abilities (Gigerenzer et al., 2007; Hertwig, 2017).
Such interventions are designed to provide practical strategies and analytical skills,
enabling individuals to sort through information-rich environments. By focusing on education
and skill development, boosting interventions aim to nurture lasting, transferable competencies
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for a wide range of decision-making scenarios, promoting greater autonomy and efficacy
(Lorenz-Spreen et al., 2021).
The positive impact of boosting interventions on public health outcomes and decisionmaking has been documented, with researchers Hertwig & Grüne-Yanoff (2017) highlighting
their benefits for supporting informed and autonomous decision-making capabilities. These
interventions have been shown to contribute significantly to individual and societal well-being,
by empowering people with the knowledge and tools to make better health-related decisions
(Gigerenzer, 2022).
Given the advantages of boosting interventions and their alignment with this study's aims,
the podcast-based intervention "Fact Check Your Health" is designed as a boosting intervention.
The podcast series addresses key aspects of health decision literacy, aiming to provide listeners
with the knowledge and skills to make health decisions with confidence. This approach uses the
empowering potential of boosting, ensuring the intervention educates and enhances individuals'
decision-making capabilities related to health literacy.
Podcasts
The growth of podcasts as a primary medium for information dissemination and
education marks a significant shift in media, paralleling the rise in online audio consumption. As
of early 2023, three-quarters of Americans aged 12 and older report having listened to online
audio in the past month, demonstrating a broad cultural adoption of digital media, with podcasts
at the forefront of this movement (Gray, 2024). As of February 2024, there are an estimated 3.2
million active podcasts, with almost 30 million episodes published in just 2023 (Howarth, 2024).
As of 2023, 64% of Americans (183 million) had listened to a podcast, with podcasts being
utilized by 42% (120 million) of Americans each month (Edison Research, 2023). Further, 31%
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of Americans (89 million) listened to podcasts weekly, with an average listening rate of 9
podcast episodes a week (Edison Research, 2023).
Smartphones, the preferred device for podcast listening for 79% of U.S. listeners,
highlight the medium's accessibility and integration into daily life, allowing for consumption
during commutes, workouts, or household chores. This accessibility, combined with the
platforms' reach—where YouTube and Spotify dominate the podcast scene in the U.S., capturing
significant portions of podcast listeners—highlights the widespread appeal and potential reach of
podcast-based interventions (Nguyen, 2023). In addition, educational podcasts are the second
most popular podcast category at 12.5% behind only society & culture podcasts at 13.8%
(Howarth, 2024).
The versatility of podcasts extends beyond consumption patterns to encompass a variety
of podcast formats, including interviews, storytelling, and discussions, making intricate subjects
more comprehensible and relatable. This versatility, along with the cost-effectiveness of
producing high-quality audio content compared to video, presents a significant opportunity for
content creators to engage with diverse audiences across demographic and geographic
boundaries.
Given the nature of podcast consumption, content creators are encouraged to distribute
their podcasts across multiple channels to maximize engagement. This strategic distribution,
coupled with the unique advantages of podcasts, makes them an ideal tool for educational and
health interventions, aiming to integrate educational content seamlessly into listeners' daily
routines.
By embracing the podcast format, creators can use its educational potential to address a
range of topics, including health decision literacy. The statistics and trends surrounding podcast
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usage validate the medium's relevance and highlight the importance of designing content to meet
the preferences and habits of a specific listener base.
Advantages of podcasts
Podcasts stand as a valuable educational resource, seamlessly integrating into the patterns
of daily life. Their unique format enables listeners to absorb new information while engaged in
other activities, such as commuting, exercising, or performing household tasks, thus representing
the epitome of learning flexibility. This adaptability ensures that education can occur beyond
traditional settings, catering to the modern individual's busy lifestyle.
The personal nature of podcasting creates a sense of intimacy between the host and the
listener and supports a personal connection that enhances the learning experience. This
relationship encourages engagement and can make the content more memorable and impactful.
Additionally, podcasts offer various types of content that can appeal to various learning
preferences and styles. Through storytelling, interviews, and discussions, they provide
comprehensive insights into topics, presenting information in a unique and accessible manner.
The diversity of podcast formats—from narrative explorations to structured episodes—ensures
that auditory learners and those seeking depth and context can find content that matches their
specific learning needs.
Moreover, the capacity of podcasts to summarize complex subjects in relatable and
understandable terms is particularly advantageous. By breaking down intricate ideas into
digestible segments, podcasts can transform abstract concepts into tangible knowledge, providing
a better understanding and retention of information. The serialized nature of many podcasts also
allows for the exploration of subjects in greater depth over multiple episodes, building a layered
understanding of the topic at hand.
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Incorporating podcasts into educational strategies offers a unique opportunity to address
the various needs of learners today. Their blend of accessibility, personal connection, and
adaptability to various learning styles makes podcasts an invaluable tool for educational
resources, capable of enhancing engagement, understanding, and the overall learning experience.
Challenges in Podcast Development
Creating a successful podcast involves several challenges. One of the primary concerns is
maintaining listener interest over time. With the vast number of podcasts available, creators must
produce compelling, relevant, and consistently high-quality content to keep their audience
engaged. This requires an understanding of the target audience's preferences and the ability to
adapt content based on feedback and changing trends.
Ensuring content accuracy and reliability is another challenge, particularly for podcasts
focusing on health and science. Misinformation can easily spread if not carefully checked, which
could have serious implications for listener health and safety. Podcast creators must thoroughly
research their topics, consult with experts, and cite reputable sources to maintain the trust of their
audience.
Reaching the intended audience is also a key consideration. With so many platforms and
distribution channels available, podcasters must strategically promote their series to stand out in
a crowded marketplace. This may involve leveraging social media, engaging in community
discussions, and collaborating with other content creators to increase visibility and listener
numbers.
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Considerations for Podcast Development
In addition to these challenges, there are several important considerations for those
developing podcasts, especially in educational contexts. Understanding the technical aspects of
podcasting, such as audio quality, editing, and distribution, is fundamental. Creators must invest
in good recording equipment, learn editing software, and choose the right platforms for hosting
and sharing their podcasts.
Another consideration is the format and structure of the podcast. Podcasts can feature
interviews, narrative storytelling, Q&A sessions, or a mix of these elements. The format should
align with the content's goals and the preferences of the target audience. Further, determining the
optimal length and release schedule for episodes can impact listener engagement and retention.
Podcast Interventions
As researchers investigate the use of podcasts in educational settings, it becomes apparent
that they represent a rapidly expanding avenue for the delivery of knowledge and information.
The efficacy of podcasts as a learning tool is increasingly recognized, with various studies
confirming their positive impact on educational outcomes in a wide range of fields.
For instance, research led by White et al. (2011) focused on the utilization of podcasts
within surgical training, revealing that this modern learning aid could effectively complement
traditional educational methods. Similarly, Vogt et al. (2010) examined how podcasting affected
the learning experience and satisfaction of nursing students, highlighting the medium's
contribution to enhancing academic life. Regarding health education, Strickland et al. (2012)
highlight how podcasts can facilitate the connection between academic research and teaching,
illustrating their capacity to bridge the gap between theory and practice.
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Further research, such as that by Porter et al. (2022), points to the role of podcasts in
elevating health literacy among adolescents and adults, while Shaw et al. (2013) have
demonstrated their supportive role in medical recovery processes.
Collectively, these studies illustrate the emerging importance of podcasts as an
educational platform. They offer valuable insights into the ways podcasts can be strategically
used to enhance health literacy and amplify the learning process. This sets the stage for podcasts
to be viewed as effective channels for boosting interventions, which disseminate information and
actively enhance listeners' ability to make informed health choices and engage with educational
material more accurately. Using the insights from previous research, the following section
explains the creation process of the intervention podcast series developed for this study, detailing
the considerations and strategic approaches employed to maximize its educational impact and
accessibility.
Fact Check Your Health Podcast
"Fact Check Your Health" is a podcast specifically designed to enhance health decision
literacy among women aged 18-45. This intervention matches the broader goal of enhancing
individuals' ability to find, understand, and apply health information in making informed
decisions.
Content Development
The development of content for "Fact Check Your Health" involved a detailed process
aimed at creating an informative and engaging educational experience. This process began with
the selection of topics that are necessary for understanding health decision literacy. Topics were
carefully chosen to cover a wide range of subjects including misinformation, evaluating the
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reliability of sources, understanding academic studies, explaining commonly confused terms,
analyzing risk perspectives, and comparing competing hypotheses among others.
The purpose of the podcast was not to encourage people to conduct their own health
research on these topics. Instead, it was designed to provide individuals with the tools to perform
their own research correctly if they were already doing so or if they wished to start. This
approach ensures that listeners can navigate health information accurately and make informed
decisions.
The scripts were designed to be conversational and accessible, breaking down complex
concepts into understandable segments without oversimplifying the content. Relatable examples
of the concepts were inserted throughout the episodes to reemphasize the topics and retain the
listener’s attention. Feedback from pilot listeners played an important role in refining the
content. This feedback helped identify areas that needed clarification, topics that were relevant to
most listeners, and aspects of the podcast format that enhanced learning. Based on this feedback,
adjustments were made to the script and presentation style, ensuring the final product was both
educational and engaging.
Podcast Hosts
The "Fact Check Your Health" podcast has two cohosts, Katie Byrd and Sydney Miller,
Ph.D., who together create an engaging and educational listening experience. Katie Byrd leads
the episodes as a quantitative psychology researcher with a focus on understanding and
improving human decision-making under conditions of uncertainty and risk. As a Ph.D.
candidate in Psychology at the University of Southern California, Katie's analytical skills provide
listeners with a clear framework for handling health decisions.
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The other cohost, Sydney Miller, Ph.D., is a public health scientist with a research
emphasis on the intricate social and structural factors affecting nutrition and nutrition-related
health disparities. Holding a Ph.D. in Health Behavior Research from the University of Southern
California and serving as a Research Associate at Drexel University, Sydney contributes a strong
understanding of public health challenges and solutions.
Following a conversational style, the cohosts take turns asking questions, providing
answers, and sharing insights. This collaborative approach allows for an engaging and
informative discussion that invites listeners into an educational conversation. Katie and Sydney's
rapport, characterized by their informative yet approachable dialogue, demonstrated the podcast's
mission to enhance health decision literacy in a way that is both accessible and engaging for a
diverse audience.
Episode Content
The podcast series, "Fact Check Your Health," addresses the essential aspects of health
decision literacy through five episodes. Each episode covers specific topics, offering listeners a
comprehensive guide to understanding online health information. Each episode is between 14-19
minutes in length, with the total series containing ~85 minutes of content. The episode titles,
topics, and lengths are presented in Table 2-1.
Table 2-1.
Episode outlines for the intervention podcast ‘Fact Check Your Health’.
Episode # Episode Title Episode Topics Episode Length
in Minutes
Ep. 1 Who can you
trust?
Misinformation
How to find accurate information 17:02
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Ep. 2 Let’s talk
basics
Overview of academic articles (e.g.,
abstract, citations, journals, etc.) 16:39
Ep. 3
The good, the
bad, and the in
between
Study design
Confounding factors 17:38
Ep. 4 You’re reading
it all wrong
Statistical significance & clinical
significance
Headlines
Causation vs. correlation
Risk perspective
19:10
Ep. 5
Make a
decision
already
Confirmation bias
Conflicting information
Analysis of Competing Hypotheses
(ACH)
14:17
Episode one begins the series by teaching listeners how to discern accurate health
information from misinformation and introducing them to resources such as PubMed and Google
Scholar. This foundational episode sets the stage for critical thinking and informed decisionmaking.
The second episode goes through the structure and content of academic articles,
describing the essential components such as abstracts, citations, and conflicts of interest. This
episode explains the details of academic literature, making it more accessible to a lay audience.
In episode three, the focus shifts to study design and confounding factors, key elements in
understanding research validity. Listeners are introduced to the details and differences of study
methodologies, providing them with the knowledge to evaluate research credibility.
Statistical significance, clinical significance, headlines, causation versus correlation, and
risk perspective are covered in episode four. This episode bridges the gap between statistical data
and its real-world implications, providing a more thorough understanding of research results.
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The final episode, episode five, explains confirmation bias, conflicting information, and
the Analysis of Competing Hypotheses (ACH). It encourages listeners to critically assess health
information, even when it challenges their preconceived notions2
.
Recording, Production, and Distribution
Technical considerations played a significant role in the creation of the podcast. Highquality audio equipment, specifically Audio-Technica ATR2100x microphones, was used to
ensure clarity and professionalism in the production. The recording environment was optimized
to minimize background noise and echo, providing a clean and clear listening experience. The
podcast was edited using the program Descript (www.descript.com). The editing process focused
on maintaining a natural flow of conversation while ensuring the content remained engaging and
informative. Attention to these details was important in producing a podcast that is not just
educational but also enjoyable to listen to. For the intervention, participants received direct links
to access the episode audio files. Accessibility features, such as transcripts for each episode,
were also provided to cater to individuals with various needs and learning preferences.
Health Decision Literacy (HDL) Scale
The Health Decision Literacy (HDL) Scale was developed to address the need for an
assessment tool designed to the specifics of health decision-making within digital information
contexts. Traditional health literacy measures were insufficient in capturing the depth of skills
2 Study 2 episode audio files and transcripts can be found at the following links:
Episode 1- https://share.descript.com/view/D66SMGPnngC
Episode 2 - https://share.descript.com/view/Mx1i6jaF4x3
Episode 3- https://share.descript.com/view/xdRkN3dCjJy
Episode 4- https://share.descript.com/view/gX6pU2AGllF
Episode 5- https://share.descript.com/view/gEi3qahjG6Q
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required to find, comprehend, and utilize health information in decision-making processes
effectively. To bridge this measurement gap, the HDL Scale was crafted to more accurately
reflect the competencies essential for evaluating the credibility of sources, understanding health
information, and applying this understanding in real-world contexts.
Initiated by a thorough review of the literature on health literacy and decision-making
frameworks, the scale's creation sought to pinpoint the fundamental competencies integral to
health decision literacy. Subsequently, a study was conducted using the online platform
Prolific.com, where 200 participants were recruited and completed the survey, contributing to the
scale's development and validation. This process ensured that the HDL Scale was grounded in
both theoretical knowledge and practical application, positioning it as a reliable tool for
contemporary health literacy assessment.
Item Generation and Selection
When developing the Health Decision Literacy (HDL) Scale, a unique approach was
adopted for item generation and selection, emphasizing the practical application of knowledge
through vignette-style questions. This methodological choice was informed by the recognition
that health decision-making often involves more than just the recall of facts or information.
Instead, it requires individuals to apply knowledge and critical thinking skills to real-life
scenarios.
To capture these competencies, the scale's items were designed around short vignettes
that present participants with hypothetical health-related situations or dilemmas. These vignettes
were carefully constructed to reflect a range of common health decision-making contexts, from
evaluating the credibility of different health information sources to making choices based on
understanding risk assessments and statistical data.
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Participants respond to each vignette by choosing actions or interpretations that best
demonstrate their ability to apply important health decision-making skills. This approach
matches the scale's aim to measure applied knowledge and enhances its relevance and validity by
situating questions in realistic and relatable contexts.
This focus on vignette-style questions represents a significant departure from traditional
health literacy measures, which often rely on direct questions about health facts or terminologies.
It reflects a stronger understanding of health literacy as a varying and context-dependent ability,
highlighting the importance of equipping individuals with the skills to understand and apply
health information. The item generation and selection process culminated in an initial set of 44
vignette-based multiple-choice questions (22 items for Test A and 22 items for Test B).
Participants
Once the pool of items was established, two versions of the test (Test A and Test B) were
created, each containing 22 multiple-choice items. These versions along with the question order
and answer choice order were randomized. For the pilot testing and scale refinement of the
Health Decision Literacy (HDL) Scale, participants (N=200) were recruited through
Prolific.com. The survey was hosted, and the data was collected through Qualtrics.com. The
sample exclusively comprised women aged 18-45, aligning with the demographic focus of the
broader study. By focusing on this demographic, the study aimed to refine the HDL Scale with
insights from individuals who are within the targeted age group. The demographic profiles of
participants were broadly similar between the groups, with minor variations observed in certain
categories, namely political ideology. The USC IRB board approved the study as exempt, and
participants were compensated $3 for completing the survey. A comprehensive breakdown of the
sample's demographics is detailed in Table 2-2.
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Table 2-2.
Demographic table for the scale development survey.
Demographics
Test A Test B
N % N %
Sample Size 99 49% 101 51%
Age
Mean 31 (6.68) 31 (6.59)
Median 32 31
Education
Some high school or less 3 3% 0 0%
High school diploma or GED 13 13% 12 12%
Some college, but no degree 20 20% 21 21%
Associates or technical degree 12 12% 13 13%
Bachelor’s degree 39 39% 37 37%
Graduate or professional degree 12 12% 18 18%
Hispanic 8 8% 14 14%
Race
White 72 73% 70 69%
Black/African American 12 12% 14 14%
American Indian/Alaska Native 4 4% 3 3%
Asian 16 16% 19 19%
Native Hawaiian/Pacific Islander 0 0% 1 1%
Other 3 3% 4 4%
Income
Less than $24,999 13 13% 16 16%
$25,000 to $49,999 19 19% 25 25%
$50,000 to $74,999 21 21% 19 19%
$75,000 to $99,999 19 19% 22 22%
$100,000 to $124,999 9 9% 3 3%
$125,000 to $149,999 5 5% 3 3%
$150,000 or more 10 10% 12 12%
Prefer not to say 3 3% 1 1%
Political Ideology
1 (Liberal) 18 18% 31 31%
2 29 29% 22 22%
3 21 21% 11 11%
4 17 17% 29 29%
5 6 6% 3 3%
90
6 5 5% 4 4%
7 (Conservative) 3 3% 1 1%
Are a parent/guardian 32 32% 36 36%
Single / Never Married 50 51% 45 45%
Note: Since demographic variables are optional percentages may not sum to 100%.
Results
The pilot testing of the Health Decision Literacy (HDL) Scale yielded insightful findings
that were instrumental in refining the scale for improved measurement accuracy and relevance.
This section details the results derived from the pilot testing, focusing on the overall performance
of Test A and Test B, the significant differences observed, and the implications of these findings
on the scale's content and format.
Average Scores and Differences
The pilot test was conducted with two versions of the scale: Test A and Test B, each
containing 22 scored items. The analysis of the pilot test scores revealed the mean number of
items correct to be 15.3 (SD = 3.2) for Test A and 16.0 (SD = 3.4) for Test B. A bootstrap
independent samples t-test revealed no significant difference between the overall scores of Test
A and Test B (t(198) = -1.571, p = .118), suggesting that the two versions of the test were
comparable in difficulty.
Regression Analysis
A preliminary linear regression analysis, incorporating variables such as test version, age,
education level, ethnicity, presence of children, and political ideology, showed that the test
version was not a significant predictor of performance. This result highlights the equitable design
of both versions of the scale. However, other predictors such as age, education, ethnicity, having
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children, and political ideology were found to be significant predictors of overall performance,
highlighting the influence of these demographic factors on health decision literacy.
Item-Level Analysis Using Item Response Theory
An IRT analysis was run in R using a 2-parameter model and Item Response Theory
(IRT). The IRT analysis played a significant role in further refining the scale by assessing items
for discriminability and difficulty. Items that exhibited discriminability below 0.3 or difficulty
levels beyond the range of -3.5 to 3.5 were deemed problematic and were subsequently removed.
This initial IRT step resulted in the exclusion of eight items classified as inadequate for the
scale's objectives. After the eight items were removed bootstrapped independent t-tests were run
for each of the remaining 14 items. These tests revealed significant differences between Test A
and Test B for two items. Due to the inherent variability in responses to those two risk and
benefit assessment items, they were also removed, bringing the scale down to 12 questions3
.
This revised 12-item version of the scale underwent a new IRT analysis to ensure the
comparability, reliability, and validity of the 12 items. The results from this final set showed no
significant difference in the mean number of correct answers between the two groups (Test A =
6.71(2.12); Test B = 6.85(2.28)), and similar mean discriminability (Test A= 1.24; Test B= 1.23)
and difficulty values (Test A= -1.23; Test B= -1.22) confirming the scale's uniformity in
measuring health decision literacy across the targeted demographic.
In addition, an item-by-item improvement analysis from pre- to post-intervention was
conducted. This analysis revealed that the item-to-item improvement varied significantly
between participants, reflecting a highly individualized pattern of response improvement. No
3 The full 12-item Health Decision Literacy (HDL) scale is displayed Appendix C.
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consistent patterns emerged among the items, indicating that improvements were specific to
individual participants' interactions rather than reflecting broader trends across the sample.
The outcomes of the pilot testing and scale refinement highlight the methodical approach
taken to ensure that the HDL Scale is a robust tool for assessing health decision literacy. The
item characteristic curves (ICCs) for the 12-item tests, graphically representing the probability of
a correct answer at various levels of health decision literacy for Test A and Test B, are detailed
in Figure 2-1. The final 12-item scale had a Cronbach's alpha of 0.70.
Figure 2-1
ICC curves and Test Information Functions for the final 12 Health Decision Literacy (HDL)
Scale items.
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Intervention Experiment
Following the development of the 'Fact Check Your Health' podcast and the
establishment of the 12-item Health Decision Literacy (HDL) Scale, the next phase of the
research aimed to evaluate the impact of the podcast on enhancing HDL among participants. An
experimental study was designed to assess the efficacy of the podcast intervention and to
determine the potential effects of pretesting on participants' learning outcomes. A total of 100
participants completed the study, which employed a modified Solomon four-group design
adapted into a three-group variant for efficiency and clarity. The methods employed in executing
the experiment and the results obtained are detailed in the following section, providing insight
into the intervention's effectiveness in improving HDL scores among participants.
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Methods
Overview of the Experiment Design
The experiment was structured using a modified Solomon four-group design, which, was
condensed into a three-group variant for this study. This design is particularly robust, allowing
researchers to isolate the effects of the intervention from the effects of pretesting. Participants in
the study were randomly assigned to one of the three groups.
The first group underwent a pretest, followed by the podcast intervention, and then a
posttest. The second group participated in the intervention and the posttest without a pretest,
which provided insights into the intervention's effectiveness without the potential priming effects
of the pretest. The third group completed only the pretest and posttest, with no exposure to the
intervention, serving as a control for pretest sensitization. By using this design, the study aimed
to answer whether the intervention could stand alone in boosting HDL without the need for
pretest priming, as well as whether the pretest itself had any impact on the participants' posttest
performance. Table 2-3 displays a table of the study design.
Table 2-3.
Study 2 research design using a three-group variant of the Solomon four-group design.
Pretest Intervention
(Five podcast episodes) Posttest
Group 1 ✓ ✓ ✓
Group 2 ✓ ✓
Group 3 ✓ ✓
Design and Procedure
Participants were randomly assigned to one of three conditions to examine various facets
of the intervention and its effects:
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Group 1 - Pretest-Intervention-Posttest (PIP): Participants in this group (N=38)
underwent a sequence starting with the pretest (12-item HDL test, either Test A or Test
B), followed by the intervention (listening to the podcast series and completing the
attention check questions), and concluded with the posttest (12-item HDL test featuring
the opposite version of their pretest, alongside demographic questions and cognitive
assessments).
Group 2 - Intervention-Posttest (IP): Participants in this condition (N= 29) experienced
the intervention first and then proceeded to the posttest, offering insights into the
intervention's effect without pretesting influence.
Group 3 - Pretest-Posttest (PP): This group (N=33) allowed for the analysis of pretesting
effects by having participants complete both the pretest and posttest without the
intervention phase.
To counterbalance and mitigate order effects, the two test versions were counterbalanced
within each condition and participants were randomly allocated to the two test versions (Test A
and Test B). Similarly, to mitigate response bias the answer choices for each question were
randomized. The pretest involved the 12-item HDL scale, and the posttest included the
alternative version of the HDL test, followed by demographic questions, and three cognitive
questionnaires: specifically the full 4-item version of the Berlin Numeracy Test (Cokely et al.,
2012), the Actively Open-Minded Thinking (AOT) scale (Baron, 2019), and the Cognitive
Reflection Test -2 (CRT) (Thomson & Oppenheimer, 2016).
The intervention phase was marked by participants listening to all five episodes of the
podcast series, complemented by three multiple-choice attention check questions for each
episode, summing to a total of 15 attention check questions. Participants who missed more than
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five attention check questions were disqualified from the study to ensure engagement and
comprehension. The study's procedure, exclusion criteria, hypotheses, and analyses were
preregistered on aspredicted.org before data collection.
Participants
The participant pool for this study was recruited through Prolific.com, an online platform
frequently used for academic research. This study was limited to women aged 18 to 45 years
who reside in the United States and are fluent in English.
Initial recruitment targeted 120 participants across the experimental conditions.
Participant retention, however, faced several challenges leading to attrition at different stages of
the experiment. The final retention rate was 83% (N=100). The following details the distribution
and nature of participant dropout and removal:
- Incomplete participation: One participant completed both the pretest and the
intervention but did not proceed to complete the posttest.
- Dropouts in the no-pretest intervention group: A total of six participants engaged
with the intervention but did not finalize the study by completing the posttest.
- Pretest only participation: Eight individuals completed only the pretest portion
and did not engage with the subsequent parts of the study. Notably, the average
pretest score among these participants was 8.4, aligning closely with the average
score of those who completed the posttest, suggesting that the dropout was not
correlated with lower or higher pretest performance.
- Removal due to attention check failures: The study's design included attention
check questions following each podcast episode to ensure that participants were
engaging with the content. Five participants were removed from the study due to
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failing more than 5 attention check questions, indicating insufficient engagement
with the intervention material.
The attrition observed across these different stages highlights the challenges inherent in
maintaining participant engagement in studies requiring active and sustained interaction. The
unequal group sizes, in the final analysis, are a consequence of this attrition, impacting the
distribution of participants across the experimental conditions.
In total, 100 participants completed the study. They were compensated $2.50 for the
pretest, $4 for the posttest, and $20 for the intervention. The study was approved as exempt by
the Institutional Review Board (IRB) of the University of Southern California. Detailed
demographic information of the sample is available in Table 2-4.
Table 2-4.
Demographic table for the Study 2 experiment.
Demographics
Group 1: PIP
(N=38)
Group 2: IP
(N=29)
Group 3: PP
(N=33)
Total
(N=100)
N % N % N % N %
Age
Mean 34 (6.12) 33 (6.50) 34 (6.53 33 (6.39)
Median 35 33 35 34
Education
Less than high school 0 0% 1 3% 0 0% 1 1%
High school graduate 3 8% 3 10% 2 6% 8 8%
Some college 3 8% 5 17% 9 27% 17 17%
2-year degree 8 21% 3 10% 2 6% 13 13%
4-year degree 18 47% 14 48% 12 36% 44 44%
More than a 4-year
Degree 6 16% 3 10% 8 24% 17 17%
Hispanic 3 8% 3 10% 3 9% 9 9%
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Race
White 32 84% 26 90% 27 82% 85 85%
Black/African American 3 8% 1 3% 4 12% 8 8%
American Indian/Alaska
Native 0 0% 1 3% 1 3% 2 2%
Asian 2 5% 3 10% 3 9% 8 8%
Native Hawaiian/Pacific
Islander 0 0% 0 0% 0 0% 0 0%
Other 1 3% 1 3% 1 3% 3 3%
Income
Less than $24,999 8 21% 4 14% 5 15% 17 17%
$25,000 to $49,999 8 21% 10 35% 5 15% 23 23%
$50,000 to $74,999 7 18% 11 38% 5 15% 23 23%
$75,000 to $99,999 7 18% 3 10% 5 15% 15 15%
$100,000 to $124,999 3 8% 0 0% 4 12% 7 7%
$125,000 to $149,999 1 3% 1 3% 3 9% 5 5%
$150,000 or more 4 11% 0 0% 3 9% 7 7%
Prefer not to say 0 0% 0 0% 3 9% 3 3%
Political Ideology
1 (Liberal) 9 24% 6 21% 9 27% 24 24%
2 9 24% 9 31% 6 18% 24 24%
3 5 13% 6 21% 9 27% 20 20%
4 10 26% 6 21% 6 18% 22 22%
5 2 5% 1 3% 1 3% 4 4%
6 1 3% 1 3% 1 3% 3 3%
7 (Conservative) 2 5% 0 0% 1 3% 3 3%
Have Children 18 47% 11 38% 10 30% 39 39%
Single / Never Married 11 29% 9 31% 14 42% 34 34%
BNT 1.61 (1.22) 1.62 (1.47) 1.47 (1.19) 1.56 (1.28)
CRT 1.82 (0.80) 2.00 (0.72) 2.12 (0.59) 1.97 (0.72)
AOT 56.05 (6.40) 54.65 (6.96) 55.53 (6.78) 55.49 (6.63)
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Note: Since demographic variables are optional percentages may not sum to 100%.
Results
This section presents the comprehensive findings from the study, aimed at evaluating the
effectiveness of the "Fact Check Your Health" podcast intervention on improving health decision
literacy among participants. By comparing participant performance across different groups and
implementing various statistical analyses, this section seeks to examine the extent to which the
podcast intervention boosted participants' HDL. The analysis includes mean scores across
distinct groups, regressions predicting baseline predictors of HDL, and interactions between
various factors, offering a comprehensive view of the intervention's impact.
Participant Performance by Group
Group 1, i.e. Pretest-Intervention-Posttest (PIP), (N=38) participants showed an
improvement from a mean pretest score of 7.55 (SD=2.14) to a mean posttest score of 9.71
(SD=2.22), with an average improvement of 2.16 (SD=1.84). Group 2, i.e. Intervention-Posttest
(IP) (N=29), achieved a mean posttest score of 9.90 (SD=2.01). Group 3, i.e. Pretest-Posttest
(PP): (N=33) went from a mean pretest score of 7.88 (SD=2.23) to a mean posttest score of 8.48
(SD=2.15), with a mean improvement score of 0.61 (SD=1.90).
Overall, the experiment group (Group 1) saw an increase of 28.6% in posttest HDL
scores, whereas the control group (Group 3) improved only 7.6%. This stark difference
highlights the significant effect of the "Fact Check Your Health" podcast intervention on HDL.
The mean pretest and posttest scores for each group are displayed in Figure 2-2.
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Figure 2-2
Plot of the mean pretest and posttest scores for all three experiment conditions in Study 2.
An analysis of variance (ANOVA) was conducted to compare the mean scores across
three groups—Experiment Group, No Pretest Group, and Control Group—with a focus on the
mean pretest, posttest, and improvement scores as the dependent variables.
The pretest ANOVA did not demonstrate a significant difference in pretest scores based
on condition (F(1, 69) = 0.39, p = 0.532), confirming that the experiment group (Group 1) and
control group (Group 3) had comparable levels of HDL when the experiment began.
Conversely, the ANOVA results for the posttest scores between groups showed
significant differences (F(2, 97) = 4.20, p = 0.018), particularly between the experiment groups
(Groups 1 and 2) compared to the control group (Group 3). This difference highlights the
beneficial impact of the intervention on participant performance. Additionally, there was not a
significant difference in posttest scores between the two experimental groups (Groups 1 and 2),
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as indicated by a non-significant t-value (t = -0.35, p = 0.924), confirming that the intervention is
effective even without the pretesting effect.
Furthermore, the analysis demonstrated significant variation in improvement scores
among the groups (F(1, 69) = 12.18, p = 0.001), with the experiment group (Group 1) showing
substantially better improvement compared to the control group (Group 3). This evidence
strongly supports the efficacy of the "Fact Check Your Health" podcast intervention in enhancing
health decision literacy.
Additionally, the 2x2 Mixed Model ANOVA revealed a significant interaction between
time (pretest vs. posttest) and experimental conditions (F(1, 69) = 10.75, p = 0.002), indicating
that score improvements from pretest to posttest varied significantly across groups. This suggests
that the podcast intervention, particularly for the experiment groups (Group 1), played a
significant role in boosting participants' health decision literacy over time.
These analyses collectively affirm that engagement with the podcast intervention led to
significant enhancements in participants' HDL. The standout performance of Group 2 further
validates the intervention's standalone effectiveness, independent of any pretesting effects.
Effect Size
Before conducting the study, a power analysis was carried out using G*Power to estimate
the required sample size to detect the effect of the intervention. For an ANOVA with repeated
measures and within-between interactions, assuming a small to medium effect size (f = 0.2), an
alpha error probability of 0.05, and a power of 0.95, the analysis suggested a total sample size of
56 participants was necessary. The actual sample size for this study exceeded this requirement,
ensuring this study was adequately powered to detect the intended effects.
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Cohen's d was used to quantify the difference between the experiment group (Group 1)
and the control group (Group 3) in posttest scores and improvement scores, offering insight into
the practical significance of the results. The analysis revealed a Cohen's d of 0.56 for the posttest
scores between the two groups. This medium effect size indicates a moderate, practically
significant difference in the health decision literacy levels achieved by participants who engaged
with the podcast intervention compared to those who did not. It suggests that the intervention had
a substantial impact on participants' ability to understand and use health information effectively.
Baseline Health Decision Literacy Predictors in Study 2
A regression analysis was performed to determine potential predictors of participants'
baseline Health Decision Literacy (HDL) scores, aiming to identify any initial cognitive or
demographic influences on HDL. The model incorporated a range of demographic (age,
education, race, income, marital status) and cognitive variables, including the Berlin Numeracy
Test [BNT], Cognitive Reflection Test [CRT], and Actively Open-minded Thinking [AOT]
scale.
From the cognitive perspective, none of the predictors reached statistical significance in
forecasting baseline HDL scores. This suggests that these cognitive skills, as assessed by the
tests included in the study, do not have a discernible impact on initial HDL scores among
participants, which is contradictory to the proposed hypothesis and the results from Study 1.
Regarding demographic factors, the analysis revealed that being a parent/guardian had a
significant negative association with baseline HDL scores, with an estimate of -1.55 (p = 0.030).
This may suggest that parental responsibilities could detract from the cognitive resources
available for health decision-making. All other demographic variables, including age, education,
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race, income, and marital status, did not significantly predict baseline HDL. The results of this
analysis are detailed in Table 2-5.
Table 2-5.
Linear regression predicting participants' pretest correct scores in Experiment 1 based on
cognitive and demographic variables.
Note: AOT is standardized. BNT is measured on a scale from 0-4. CRT is measured on a scale from 0-3. Age is
standardized. Education is measured using a dichotomous variable where less than a 4-year college degree is 0 and
a 4-year college degree or greater is 1. Race is dichotomized where white/Caucasian is 0 and all other races are 1.
Hispanic is dichotomized where non-Hispanic is 0 Hispanic is 1. Income is measured on a four-point scale where
“Less than $50,000” = 0, “$50,000 to $99,999” = 1, “$100,000 to $149,999” = 2, “$150,000 or more” = 3.
Children is dichotomized where no children is 0 and 1 or more children is 1. Single/Never Married is dichotomized
where single/never married is 0 and all other options are 1. Political ideology was measured on a 7-point scale
from 1 to 7 where 1 is extremely liberal and 7 is extremely conservative. The political values were then recoded into
-1 for values 1-3, 0 for 4, and 1 for values 5-7.
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Regression Analyses
Linear regression analyses were conducted to investigate the factors influencing posttest
health decision literacy (HDL) scores among the study participants. To gauge the effectiveness
of the podcast intervention, regression models predicting posttest scores included the
experimental condition as a variable. The condition was coded to reflect participation in the
intervention (Group 1) versus the control (Group 3).
The intervention condition was a significant predictor (Estimate = 1.26, p=0.012) of
posttest HDL scores, further affirming the positive impact of the podcast in enhancing
participants' health decision-making capabilities. This remained true even after controlling for
pretest HDL scores (Estimate = 0.50, p < .001) and other covariates, highlighting the robust
influence of the intervention.
Surprisingly, age and marital status were the only cognitive and demographic variables
that predicted posttest values. Age was negatively related to performance (Estimate = -0.74, p =
0.011), suggesting that as participants' age increases, there is a tendency for the posttest HDL
scores to decrease slightly. This could imply that younger participants may have had more
benefit from the intervention or were better able to improve their HDL scores. On the other hand,
being single or never married (compared to being married or in a partnership) is associated with
a decrease in posttest HDL scores (Estimate = -1.32, p = 0.044). This finding suggests marital
status is a notable factor in the variation of posttest HDL scores among participants, with those
who are single or never married showing lower scores on average than those who are not. The
remaining demographic variables (i.e. education, race, ethnicity, income, and children) did not
significantly predict posttest HDL scores.
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The cognitive variables, namely Numeracy (BNT), Cognitive Reflection (CRT), and
Actively Open-minded Thinking (AOT) were hypothesized to predict the impact of the
intervention represented through posttest HDL scores. Surprisingly, none of these cognitive
variables were significant predictors, challenging the hypotheses about the role of cognitive
skills, as measured by this study, in health decision literacy. This result emphasizes the potential
for a broader variation of factors at play in influencing individuals' ability to use and understand
health-related information. The results of the regression are displayed in Table 2-6.
Table 2-6.
Linear regression predicting participants' posttest HDL scores.
Note: AOT is standardized. BNT is measured on a scale from 0-4. CRT is measured on a scale from 0-3. Age is
standardized. Education is measured using a dichotomous variable where less than a 4-year college degree is 0 and
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a 4-year college degree or greater is 1. Race is dichotomized where white/Caucasian is 0 and all other races are 1.
Hispanic is dichotomized where non-Hispanic is 0 Hispanic is 1. Income is measured on a four-point scale where
“Less than $50,000” = 0, “$50,000 to $99,999” = 1, “$100,000 to $149,999” = 2, “$150,000 or more” = 3.
Children is dichotomized where no children is 0 and 1 or more children is 1. Single/Never Married is dichotomized
where single/never married is 0 and all other options are 1. Political ideology was measured on a 7-point scale
from 1 to 7 where 1 is extremely liberal and 7 is extremely conservative. The political values were then recoded into
-1 for values 1-3, 0 for 4, and 1 for values 5-7.
Podcast Feedback
The "Fact Check Your Health" podcast received diverse feedback, providing valuable
insights into participant engagement and learning. Several listeners appreciated the real-world
examples, noting that they effectively illustrated the podcast's concepts and provided
understanding. While some participants expressed that the information was a refresher on
familiar topics, others gained new knowledge, particularly valuing the breakdown of abstract
concepts into layperson terms. The length of the podcast episodes was generally well-received,
with many listeners affirming the shorter format as being more digestible and conducive to
maintaining attention. However, there were numerous suggestions to reduce redundancy in some
sections to decrease the overall length of the podcast series.
Feedback regarding the podcast's practicality varied. While some participants felt that the
average listener might not research health research as severely the podcast suggested, others
disagreed and appreciated the in-depth approach, stating that it empowered them with tools for
better health decision-making. Participants also remarked on the helpfulness of the podcast in
understanding digital health information. Participants with existing health conditions found the
podcast particularly relevant, as it aligned with their experiences of seeking credible health
information. The educational value of the podcast was recognized, with many expressing a
willingness to recommend it to others seeking to improve their health literacy.
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Overall, the "Fact Check Your Health" podcast was deemed a helpful and engaging
resource by the study's participants, suggesting that such interventions can play a significant role
in enhancing public health literacy.
Limitations
Examining the limitations of this study, several factors should be acknowledged. First,
the study was confined to a specific demographic: women aged 18 to 45 residing in the United
States and fluent in English. This focus, while beneficial for the depth of analysis within this
group, limits the generalizability of the findings to a broader population. The intricacies of health
decision literacy, influenced by cultural, socio-economic, and educational backgrounds, suggest
that future studies should consider including a more diverse participant base to evaluate the
intervention's effectiveness across different demographics. Additionally, the sample exhibited a
liberal skew, which may influence the generalizability of the findings to individuals with
differing political orientations.
Another limitation arises from the length of the podcast intervention. The cumulative
duration of approximately 85 minutes represents a significant time commitment, which may not
be feasible for all listeners in real-world contexts. Shorter interventions or segmented content
delivery could enhance accessibility and willingness to engage, potentially increasing the
intervention's impact.
Furthermore, the compensation provided to participants for their time and engagement
raises questions about the intervention's appeal and effectiveness outside of a controlled,
incentivized setting. This aspect of the study design might not accurately reflect natural
engagement levels with the podcast, highlighting the need for research into the consumption of
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educational podcasts and their efficacy in improving health decision literacy in the wild without
external incentives.
The study may also be subject to the Hawthorne effect, where participants' behavior
could change simply because they are aware they are being studied (Jones, 1992). This
awareness might lead to higher engagement or more positive responses than would be seen in a
naturalistic setting, potentially skewing the results.
Lastly, the study's experimental design, the modified Solomon three-group format,
effectively differentiated the effects of the podcast intervention from pretesting but also led to
unequal group sizes due to participant attrition. This attrition could potentially affect the
statistical power of comparisons between groups. Developing strategies to minimize dropout
rates is essential for ensuring the reliability of outcomes in similar studies moving forward.
Addressing these limitations in subsequent research will be valuable for refining the
approach to podcast-based health literacy interventions, ensuring they are accessible, engaging,
and effective for a wide audience in the wild.
Discussion
The findings of Study 2 highlight the significant potential of the "Fact Check Your
Health" podcast as a tool for enhancing health decision literacy (HDL) among women aged 18-
45. This research supports previous studies highlighting the effectiveness of digital interventions
in improving health literacy and advances our understanding of podcasts' role in this context. The
study's outcomes correspond with the evolving consumption of digital health information,
emphasizing podcasts' capacity to serve as an engaging and accessible medium for health
education.
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The improvement in HDL scores among participants who engaged with the "Fact Check
Your Health" podcast, particularly when compared to the control group, highlights the
intervention's efficacy. This improvement matches the overarching goal of boosting
interventions, which seek to enhance individuals' decision-making competencies through
targeted education and skill development. The significant increase in posttest scores for the
experiment group compared to the control group reflects the podcast's ability to convey complex
health information effectively, thereby facilitating a better understanding and application of
health decision-making principles.
The analysis revealed age and marital status as significant predictors of posttest HDL
scores, suggesting relationships between demographic factors and health decision literacy. The
negative correlation between age and posttest scores invites further investigation into how
generational differences influence engagement with digital health interventions. Similarly, the
observed impact of marital status on HDL scores highlights the relationship of social and
relational factors in health decision-making processes. These findings contribute to a growing
body of literature that examines the varying nature of health literacy, advocating for more
personalized and inclusive health education strategies.
The promising results of the "Fact Check Your Health" podcast intervention open several
avenues for future research, including expanding the scope and impact of such educational tools.
A direction for future studies involves experimenting with the length of the intervention. Given
the significant time commitment required by the current format, developing a shorter, more
concise version of the podcast could potentially increase accessibility and engagement, making it
more feasible for individuals with time constraints. This modification could help determine the
minimum amount of content necessary to achieve measurable improvements in HDL.
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Another area for future research is the public launch of the podcast intervention on
widely accessible platforms. Evaluating the podcast's performance 'in the wild'—without the
structure of a controlled study environment or the incentive of compensation—would provide
valuable insights into its natural appeal and effectiveness. Such a study could identify listener
engagement patterns, voluntary uptake rates, and the sustainability of HDL improvements over
time when participants self-select into the intervention. This approach would also allow for the
collection of qualitative feedback from a broader audience, enhancing the development of future
iterations of the podcast with diverse listener experiences and preferences.
Furthermore, investigating the intervention across a broader demographic spectrum
would provide insight on its generalizability and potential for widespread impact. Long-term
studies focusing on the retention of HDL improvements and the application of learned concepts
in real-life health decision-making scenarios are essential. These studies should continue to
examine the influence of cognitive and demographic variables on the effectiveness of health
literacy interventions, aiming to design content to meet the needs of diverse populations more
effectively.
Conclusion
The "Fact Check Your Health" podcast has proven to be a powerful tool for enhancing
health decision literacy (HDL) among women aged 18-45, showcasing the potential of podcasts
as educational tools. This study reinforces the value of digital interventions in elevating health
literacy and positions podcasts as a valuable medium for disseminating complex health
information in an accessible and engaging manner. The notable improvements in HDL scores
following the podcast intervention affirm the strategic application of boosting interventions in
encouraging more informed and competent health decision-making.
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The study contributes to the broader discussion on health literacy, emphasizing the
importance of innovative educational interventions designed for modern information
consumption habits. The findings from this research advocate for a customizable approach to
health literacy interventions, considering the diversity of demographic factors and their impact
on health decision-making. It reinforces the importance of developing targeted, inclusive, and
adaptable health education content that can address the unique needs and preferences of different
populations.
Creating a more concise version of the podcast and evaluating its effectiveness in noncontrolled environments would point to a commitment to making health education more
accessible and relevant to a broader audience. These future directions would increase the
understanding of how digital interventions can be optimized to enhance health decision literacy
across diverse communities.
Chapter 4: Study 3
Abstract
Building on the success of the "Fact Check Your Health" podcast intervention in Study 2,
Study 3 introduces a streamlined version of the intervention, condensed to less than 60 minutes,
aimed at further enhancing its accessibility and practicality. This study (N=127) maintained the
identical methodological framework and analytical approaches as Study 2 to evaluate the
effectiveness of the condensed intervention in improving Health Decision Literacy (HDL)
among women aged 18-45. A total of 127 participants completed the study to assess the
intervention's impact through a three-group variant of the Solomon four-group design. Results
indicated a significant improvement in HDL scores among those exposed to the condensed
podcast version, paralleling the findings of Study 2. Subsequently, the podcast was launched
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publicly across all major podcast platforms. This phase aimed to examine its broader appeal and
impact in a real-world setting, marking a step towards disseminating evidence-based health
literacy interventions to a wider audience. The launch included the collection of qualitative
feedback and engagement metrics, providing insights into listener experiences and the
sustainability of HDL improvements outside a controlled study environment. Study 3 validates
the efficacy of the condensed "Fact Check Your Health" podcast as an educational tool and
illustrates its potential to reach and benefit a diverse group of listeners globally.
Introduction
Within the ever-changing space of health education and promotion, the scalability,
implementation, and public reception of interventions have become central to their success and
sustainability. Following the promising results of the "Fact Check Your Health" podcast
intervention aimed at enhancing Health Decision Literacy (HDL) in Study 2, Study 3 seeks to
address these aspects by presenting a condensed version of the intervention, examining its
effectiveness through an experimental design, and then determining its scalability and reception
in the public domain.
The concept of scalability is necessary for transforming good ideas into impactful, widereaching interventions. In the book, The Voltage Effect: How to make good ideas great and great
ideas scale, List (2022) emphasizes the importance of identifying factors that allow interventions
to grow successfully without losing their effectiveness, a concept central to this study's aim of
creating a shorter, more accessible version of the "Fact Check Your Health" podcast. Similarly,
Peters (2020) highlights the challenges of numeracy and information literacy in the general
population, reinforcing the need for interventions such as "Fact Check Your Health" that make
complex health information more digestible and actionable to a lay audience.
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Zamboni et al. (2019), Milat et al. (2013), and Gupta et al. (2022) provide frameworks for
assessing the scalability of health interventions, focusing on factors such as adaptability, costeffectiveness, and potential barriers to widespread implementation. These considerations
informed the development of the condensed podcast version, aiming to maintain its educational
efficacy while making it more feasible for broader public consumption.
The transition from controlled experimental settings to real-world applications poses
unique challenges, as indicated by Zullig et al. (2015) and Huang et al. (2011), who examined
the sustainability and reach of health interventions. This study uses these insights, aiming to
understand how "Fact Check Your Health” is received and engaged with by a diverse audience
when launched on public platforms.
Furthermore, Attanasio et al. (2022) and Koch et al. (2021) provide evidence of the
positive impacts and feasibility of scaling early-stage interventions. Their work supports the
premise that well-designed health literacy interventions, when carefully adapted and scaled, can
significantly impact public health outcomes.
Ultimately, Study 3 tests the efficacy of a condensed version of the "Fact Check Your
Health" podcast (Part I) and examines its scalability and real-world application (Part II). By
examining the intervention's performance in a controlled experimental setup and its subsequent
public launch, this study contributes to the growing body of literature on scalable health
interventions and their potential to improve health decision literacy across diverse populations.
Part I: Condensed Intervention
Part I of this study focuses on the design, development, and evaluation of a condensed
version of the "Fact Check Your Health" podcast. This effort seeks to maintain the intervention's
educational content while significantly reducing its duration to under 60 minutes, thereby
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addressing potential barriers to engagement and accessibility identified in previous research. The
adaptation of the podcast into a more accessible format represents an important step towards
achieving scalability and wider reach, setting the stage for Part II's examination of the
intervention's public launch and its implications for health decision literacy on a global scale.
Methods
Following the same methodological framework as Study 2, Part I of Study 3 (N=127)
evaluates the efficacy of a condensed version of the "Fact Check Your Health" podcast. The
intervention was designed to maintain the educational content of the original while making it
more accessible through reduced duration.
Intervention Design
The intervention in Study 3 involved the creation of a condensed podcast series,
strategically shortened to less than 60 minutes4
. This process was informed by an analysis of
content from Study 2, focusing on retaining key educational elements that directly contribute to
improved Health Decision Literacy (HDL). Essential topics were repackaged into shorter
segments, using feedback from previous participants to highlight the most impactful content.
This version aimed to provide a comprehensive overview of health decision-making principles
4 Podcast episodes for Study 3
Episode 1: https://www.buzzsprout.com/2325329/episodes/14639623
Episode 2: https://www.buzzsprout.com/2325329/episodes/14639800
Episode 3: https://www.buzzsprout.com/2325329/episodes/14640083
Episode 4: https://www.buzzsprout.com/2325329/episodes/14641001
Episode 5: https://www.buzzsprout.com/2325329/episodes/14641005
*The links provided above are live links to the publicly available “Fact Check Your Health” podcast. Therefore
slight variations in the length of the series might exist due to nominal adaptations of aspects such as introductions
and recaps, however the content of each episode remains the same.
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within a more manageable timeframe for listeners. The titles, topics, and order of the episodes
remained the same as in Study 2 and are detailed in Table 2-1.
Experimental Design
Following the experimental design outlined in Study 2, this study employed a three-group
variant of the Solomon four-group design to assess the intervention's impact on HDL scores
among participants. This design was chosen for its robustness in evaluating both the effect of the
intervention and the potential influence of pretesting on outcomes.
- Group 1 (Pretest-Intervention-Posttest): Participants (N=43) completed the HDL pretest,
received the podcast intervention, and then completed the HDL posttest.
- Group 2 (Intervention-Posttest): Participants (N=44) received the podcast intervention
and then completed the HDL posttest.
- Group 3 (Pretest-Posttest): Participants (N=40) took both the pretest and posttest without
the intervention, acting as a control.
Measures and Procedures
The same pretest and posttest, including the Health Decision Literacy (HDL) scale
developed and validated in Study 2 was used in Study 3. The condensed podcast was made
available to participants in the intervention groups through direct links, with engagement verified
through a series of attention check questions. Data collection included pretest and posttest HDL
scores, alongside demographics, cognitive measures, and feedback on the podcast experience.
Participants
The study initially recruited 144 (N=48 per group) women aged 18 to 45 residing in the
United States through Prolific.com. The survey was hosted, and the data was collected through
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Qualtrics.com. Participants were randomly assigned to one of the three experiment groups.
Participants failing five or more of the 15 attention check questions were removed from the
sample. After attrition and the attention check questions the final sample was 127 participants,
representing a retention rate of 88.2%. The mean pretest scores for the participants that attrited
were comparable to the pretest scores of the retention group (8.32 and 8.35 respectively).
Inclusion and exclusion criteria were preregistered before data collection on aspredicted.org.
Participants received $2 for completing the pretest, $15 for engaging with the
intervention (listening to the condensed podcast series and completing the attention check
questions), and $3 for completing the posttest. The USC IRB approved the study as exempt. A
demographic breakdown of the final sample is provided in Table 3-1.
Table 3-1.
Demographic table for Study 3.
Demographics
Group 1: PIP
(N=43)
Group 2: IP
(N=44)
Group 3: PP
(N=40)
Total
(N=127)
N % N % N % N %
Age
Mean 32 (6.78) 32 (7.20) 29 (7.49) 31 (7.26)
Median 32 33 26 31
Education
Less than high school 0 0% 1 2% 0 0% 1 1%
High school graduate 3 7% 7 16% 8 20% 18 14%
Some college 7 16% 3 7% 5 13% 15 12%
2-year degree 4 9% 5 11% 5 13% 14 11%
4-year degree 25 58% 14 32% 18 45% 57 45%
More than a 4-year Degree 4 9% 13 30% 4 10% 21 17%
Hispanic 7 16% 6 14% 5 13% 18 14%
Race
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White 28 65% 24 55% 28 70% 80 63%
Black/African American 10 23% 11 25% 4 10% 25 20%
American Indian/Alaska
Native
2 5% 1 2% 2 5% 5 4%
Asian 6 14% 6 14% 11 28% 23 18%
Native Hawaiian/Pacific
Islander 1 2% 0 0% 0 0% 1 1%
Other 1 2% 1 2% 0 0% 3 2%
Income
Less than $24,999 4 9% 6 14% 3 8% 13 10%
$25,000 to $49,999 14 33% 9 21% 11 28% 34 27%
$50,000 to $74,999 4 9% 9 21% 6 15% 19 15%
$75,000 to $99,999 9 21% 10 23% 8 20% 27 21%
$100,000 to $124,999 7 16% 3 7% 5 13% 15 12%
$125,000 to $149,999 2 5% 1 2% 2 5% 5 4%
$150,000 or more 3 7% 3 7% 3 8% 9 7%
Prefer not to say 0 0% 2 5% 2 5% 4 3%
Political Ideology
1 (Liberal) 9 21% 8 18% 9 23% 26 21%
2 11 26% 13 30% 12 30% 36 28%
3 11 26% 6 14% 5 13% 22 17%
4 7 16% 12 27% 9 23% 28 22%
5 5 12% 3 7% 2 5% 10 8%
6 0 0% 0 0% 2 5% 2 2%
7 (Conservative) 0 0% 1 2% 1 3% 2 2%
Have Children 17 39% 17 39% 8 20% 42 33%
Single / Never Married 20 47% 22 50% 22 55% 65 50%
BNT 1.89 (1.38) 1.49 (1.22) 1.03 (1.00) 1.48 (1.26)
CRT 1.65 (0.84) 1.63 (0.69) 1.85 (0.80) 1.71 (0.78)
AOT 53.65 (5.94) 56.58 (6.56) 53.48 (6.54) 54.58 (6.46)
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Note: Since demographic variables are optional percentages may not sum to 100%.
Results
The following result sections detail the findings from various analyses conducted to
assess the impact of the condensed "Fact Check Your Health" podcast intervention on
participants' HDL. The analyses include an examination of baseline HDL predictors, participants'
performance by group, effect size, a regression analysis, and feedback from participants. These
results offer comprehensive insights into how the podcast has influenced health decision-making
skills.
Participant Performance by Group
In Study 3, the efficacy of the condensed "Fact Check Your Health" podcast intervention
was evaluated using a similar methodology to Study 2. Group 1, the Pretest-Intervention-Posttest
(PIP) group, with 43 participants, started with a mean pretest score of 8.19 (SD=2.12) and saw an
increase to a mean posttest score of 10.07 (SD=1.62). This represents a mean improvement of
1.88 or 23.0%, highlighting a significant enhancement in Health Decision Literacy (HDL)
following the podcast intervention. Group 2, the Intervention-Posttest (IP) group, consisting of
44 participants who did not undergo a pretest, achieved a mean posttest score of 9.91 (SD=1.93),
indicating a strong performance comparable to Group 1. Group 3, the control group, with 40
participants, did not participate in the intervention and had mean scores that stayed the same
between the pretest 8.53 (SD=2.30) and posttest 8.53 (SD=2.49). The observed improvement in
Group 1 and performance for Group 2, as compared to the control group, highlight the positive
impact of the "Fact Check Your Health" podcast in promoting health decision literacy among
participants. The mean pretest and posttest scores for each group are displayed in Figure 3-1.
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Figure 3-1
Plot of the mean pretest and posttest scores for Study 3.
An analysis of variance (ANOVA) was conducted to examine the differences in mean
pretest, posttest, and improvement scores across the three groups in Study 3: the experiment
group (Group 1), the no-pretest group (Group 2), and the control group (Group 3).
The ANOVA comparing pretest scores across the groups indicated no significant
differences in initial HDL levels (F(1, 81) = 0.49, p = 0.486), which suggests that both the
experiment group (Group 1) and the control group (Group 3) started with a comparable baseline
of health decision literacy. This result supports the notion that any subsequent differences found
in posttest scores can be attributed to the intervention rather than initial group disparities.
In contrast, the posttest ANOVA revealed a significant difference in scores between the
groups (F(2, 125) = 5.16, p = 0.024 ), with both experimental groups (Groups 1 and 2) showing
superior performance compared to the Control Group (Group 3). This indicates a positive effect
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of the condensed podcast intervention on participants' health decision literacy. Moreover, no
significant difference was detected between the two experimental groups (Group 1 and 2)
posttest scores (t = 0.37, p = 0.917), suggesting that the absence of a pretest did not affect the
intervention's effectiveness.
The results also showed a significant difference in improvement scores between the
groups (F(1, 81) = 15.66, p<0.001), with Group 1 (Pretest-Intervention-Posttest) exhibiting a
more pronounced increase in HDL scores compared to the control group (Group 3). This finding
supports the efficacy of the "Fact Check Your Health" podcast in enhancing health decision
literacy.
Furthermore, a 2x2 Mixed Model ANOVA indicated a significant interaction effect
between time (pretest vs. posttest) and group condition (F(1, 81) = 8.70, p=0.004), signifying
that the improvement in HDL scores from pretest to posttest varied notably across groups. This
interaction effect further supports that the podcast intervention played a significant role in
increasing health decision literacy for the participants who received it.
These findings confirm the effectiveness of the podcast intervention, with Group 2's
performance in particular validating the standalone impact of the intervention without the
influence of pretesting. Overall, Study 3 demonstrated that the condensed "Fact Check Your
Health" podcast successfully improved participants' health decision literacy in a significant
manner.
Effect Size
For Study 3, Cohen's d was calculated to measure the effect size of the intervention,
specifically looking at the differences in posttest scores between the experimental and control
groups. The Cohen's d value obtained was 0.72, which falls into the range commonly interpreted
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as a medium to large effect size. This suggests that the "Fact Check Your Health" podcast had a
substantial impact on the HDL of participants who engaged with the condensed intervention, as
compared to those in the control group who did not receive the intervention.
This effect size highlights the practical significance of the podcast intervention. It is
indicative of a robust intervention that has statistical validation and a meaningful effect on
individuals' ability to discern and use health information. Given the challenges in health literacy
and decision-making in today's society, such an effect size is both relevant and significant,
pointing to the potential of the "Fact Check Your Health" podcast to contribute positively to
public health outcomes when disseminated at scale.
Baseline Health Decision Literacy Predictors
In Study 3, a regression analysis was conducted to examine whether various demographic
and cognitive variables were predictive of participants’ baseline Health Decision Literacy (HDL)
scores. This analysis sought to understand if any underlying factors could be influencing initial
HDL performance before the intervention.
The regression model included both demographic (such as age, education, race, income,
and marital status) and cognitive predictors (such as scores on the Berlin Numeracy Test [BNT]
(Cokely et al., 2012), Cognitive Reflection Test [CRT] (Thomson & Oppenheimer, 2016), and
Actively Open-minded Thinking [AOT] scale (Baron, 2019).
The results of the regression analysis provided insights into the factors influencing
baseline Health Decision Literacy (HDL). Cognitive abilities measured by the Cognitive
Reflection Test (CRT) significantly predicted HDL, with an estimate of 0.65 (p = 0.019). This
implies a meaningful relationship where higher CRT scores, representing greater reflection and
analytical capacity, were associated with stronger initial HDL. This finding supports the premise
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that individuals with a propensity for reflective thought have a foundational advantage in making
informed health decisions. Similarly, Actively Open-minded Thinking (AOT) was another
significant cognitive predictor with an estimate of 0.85 (p =0.001), affirming the link between an
open-minded thinking style and the ability to use health information effectively.
Contrastingly, the Berlin Numeracy Test (BNT) did not exhibit a significant relationship
with baseline HDL scores, suggesting numeracy, as measured by BNT, doesn't notably impact
HDL at the outset.
From a demographic standpoint, education level was a significant factor, specifically
individuals with higher educational attainment had better initial HDL scores (Estimate = 0.96, p
= 0.037). This highlights the role of education in equipping individuals with the skills to make
health-related decisions. On the other hand, having children was inversely related to baseline
HDL (Estimate = -1.11, p = 0.039), possibly indicating the challenging balance parents must
strike between family responsibilities and maintaining their own health literacy. The remaining
demographic variables (i.e. age, income, race, and marital status) were not significant predictors
of baselines HDL. The regression results are displayed in Table 3-2.
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Table 3-2.
Linear regression predicting participants' pretest correct scores in Study 3.
Note: AOT is standardized. BNT is measured on a scale from 0-4. CRT is measured on a scale from 0-3. Age is
standardized. Education is measured using a dichotomous variable where less than a 4-year college degree is 0 and
a 4-year college degree or greater is 1. Race is dichotomized where white/Caucasian is 0 and all other races are 1.
Hispanic is dichotomized where non-Hispanic is 0 Hispanic is 1. Income is measured on a four-point scale where
“Less than $50,000” = 0, “$50,000 to $99,999” = 1, “$100,000 to $149,999” = 2, “$150,000 or more” = 3.
Children is dichotomized where no children is 0 and 1 or more children is 1. Single/Never Married is dichotomized
where single/never married is 0 and all other options are 1. Political ideology was measured on a 7-point scale
from 1 to 7 where 1 is extremely liberal and 7 is extremely conservative. The political values were then recoded into
-1 for values 1-3, 0 for 4, and 1 for values 5-7.
Regression Analysis
A linear regression was run to further investigate the various factors that may influence
Health Decision Literacy (HDL) scores following the intervention. As with Study 2, the
intervention condition, distinguishing participants in the intervention group from those in the
control group, was once again a significant predictor (Estimate = 1.50, CI [0.60, 2.39], p =
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0.001), affirming the substantial role the podcast played in improving HDL. This finding
remained robust even when controlling for pretest scores and other covariates, reinforcing the
intervention's influence.
In contrast to the findings from Study 2, age did not significantly predict posttest HDL
scores in this sample; however, education was a significant predictor (Estimate = 1.05, CI [0.17,
1.94], p = 0.021), indicating that higher educational levels were associated with better posttest
HDL outcomes. This matches the intuitive concept that individuals with higher educational
backgrounds may possess or develop better health literacy skills.
Further, cognitive ability as measured by CRT, was a significant predictor (Estimate =
0.56, CI [0.02, 1.09], p = 0.042), suggesting that higher cognitive ability correlates with an
increase in HDL scores post-intervention. The regression results are presented in Table 3-3.
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Table 3-3.
Linear regression predicting participants' improvement between the pretest and posttest in Study
3.
Note: AOT is standardized. BNT is measured on a scale from 0-4. CRT is measured on a scale from 0-3. Age is
standardized. Education is measured using a dichotomous variable where less than a 4-year college degree is 0 and
a 4-year college degree or greater is 1. Race is dichotomized where white/Caucasian is 0 and all other races are 1.
Hispanic is dichotomized where non-Hispanic is 0 Hispanic is 1. Income is measured on a four-point scale where
“Less than $50,000” = 0, “$50,000 to $99,999” = 1, “$100,000 to $149,999” = 2, “$150,000 or more” = 3.
Children is dichotomized where no children is 0 and 1 or more children is 1. Single/Never Married is dichotomized
where single/never married is 0 and all other options are 1. Political ideology was measured on a 7-point scale
from 1 to 7 where 1 is extremely liberal and 7 is extremely conservative. The political values were then recoded into
-1 for values 1-3, 0 for 4, and 1 for values 5-7.
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Podcast Feedback
Participants in Study 3 were asked to provide feedback on their experience with the "Fact
Check Your Health" podcast. The responses were overwhelmingly positive, indicating a strong
appreciation for the content, length, and delivery of the podcast.
Many participants expressed that the podcast was informative and insightful, noting that
it was easy to follow and provided valuable information concisely. The real-world examples
were particularly well-received, as listeners appreciated how they illustrated the discussed
concepts, making the material relatable and easier to grasp. Moreover, the conversational style of
the hosts was highlighted as engaging, making complex topics more approachable.
Some listeners, already familiar with research methods and health literacy, found the
content to be a helpful refresher, while others gained new insights, especially regarding clinical
versus statistical significance. The length of the episodes was frequently mentioned as "just
right," keeping listeners engaged without being overwhelming.
However, feedback also included constructive criticism. A few participants found certain
parts of the podcast slightly repetitive and suggested that more diverse examples could enhance
the listening experience. Others mentioned that while the content was very informative, it could
sometimes be too information-heavy, suggesting the potential benefit of a lighter approach or the
inclusion of more personal anecdotes to increase relatability and maintain interest. The hosts'
delivery was generally well-regarded, with their clear and easy-to-understand explanations being
praised.
In conclusion, the feedback from Study 3 participants suggests that the "Fact Check Your
Health" podcast successfully met its educational objectives, providing accessible and engaging
content that enhanced listeners' health decision literacy. The insights gathered will be valuable
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for refining potential future iterations of the podcast and ensuring that it continues to meet the
needs of the audience.
Discussion and Limitations of Study 3 Part I
The findings from Part I of Study 3 reinforce the potential of the "Fact Check Your
Health" podcast as an effective tool for improving Health Decision Literacy (HDL). The
observed improvements in HDL among participants who engaged with the podcast demonstrate
its educational value. Moreover, the regression analysis suggests that certain cognitive abilities,
notably reflective thinking, are beneficial in maximizing the improvements from such health
literacy interventions.
However, these results must be interpreted within the context of certain limitations. First, the
self-selected nature of the study sample may limit the generalizability of the findings to a broader
population. Participants who are inclined to participate in health literacy studies may already
possess a higher baseline level of health knowledge or motivation to learn, which could influence
the observed efficacy of the intervention. Additionally, the sample had a liberal bias, potentially
affecting the generalizability of the findings to individuals with different political orientations.
Second, the assessment of HDL was based solely on quantitative measures. Qualitative
data, such as in-depth interviews or focus groups, might provide better insights into the
participants' experiences and the various ways the podcast affected their understanding and
decision-making.
Lastly, while the condensed format of the podcast was intended to enhance accessibility,
it is important to consider the trade-offs between conciseness and depth of content. Future
research should investigate the optimal balance to ensure that the necessary information is
conveyed efficiently and understood by a variety of listeners. As the transition to Part II of Study
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3 occurs, the focus shifts to determining the scalability of the podcast and its reception in a
public launch.
Part II: Public Intervention Dissemination
In Part II of Study 3, "Fact Check Your Health" transitioned from a tested intervention to
a publicly available resource with its launch across multiple podcast platforms and the creation
of additional digital resources in March 2024. The podcast aimed to engage the same
demographic targeted in the study, with the number of downloads serving as the primary metric
for success. Supplemental to the number of downloads were listener interactions, such as ratings
and comments. Using Buzzsprout’s comprehensive podcast launch guide, the podcast positioned
itself as an educational tool within the 'how to' category, expanding its reach and impact on
health literacy to the general public.
Methods
Podcast Dissemination
The "Fact Check Your Health" podcast was simultaneously released for free on all major
podcast platforms (e.g. Apple Podcast, Spotify, Amazon Music, YouTube)56
to enable
widespread accessibility. Accompanying the audio content, a dedicated website was established,
https://factcheckyourhealth.squarespace.com. The website offers episode transcripts, resources
specific to each episode's themes and topics, and additional information along with contact
5Apple Podcast: https://podcasts.apple.com/us/podcast/fact-check-your-health/id1735219472
Spotify: https://open.spotify.com/show/5pNGqOnwXLZ9YZbQv0kTCG?si=11fc795850e54b45
Amazon: https://music.amazon.com/podcasts/ec86b0b1-e907-48a6-b47b-c6b6c707aef7/fact-check-your-health
6 Full list of podcast platforms where “Fact Check Your Health” is available for streaming: Apple Podcast, Spotify,
Amazon Music, Podcast Index, Youtube, Google Podcast, iHeartRadio, Podcast Addict, Podchaser, Pocket Casts,
Deezer, Listen Notes, Player FM, Overcast, Castro, Castbox, Podfriend, Goodpods, TrueFans
130
information. Additionally, an Instagram account7
, @factcheckyourhealth, was created to develop
an online community and encourage dialogue among listeners. Screenshots of the website,
Instagram account, and Apple Podcast listing are provided in Appendix D.
Engagement Metrics
The primary metric for evaluating the podcast's success was the number of downloads,
providing a quantitative measure of reach and listener interest. Supplementary metrics included
listener ratings and written feedback on podcast platforms, as well as responses to feedback
forms available on the podcast's website. These provided both quantitative and qualitative data
on listener engagement and content reception.
Launch Date and Launch Strategy
The podcast, website, and social media account were officially made available to the
public on March 11, 2024, targeting the demographic of women aged 18-45, consistent with the
study's participant profile. The hosting service, Buzzsprout.com, was used for podcast
distribution. The public RSS feed is https://feeds.buzzsprout.com/2325329.rss. The podcast
series is listed under the "How To" subsection within the "Education" category on Apple
Podcasts.
In preparation for the launch, the strategy outlined in Buzzsprout's "How to Start a
Podcast: Complete Step-by-Step Guide [2024]" was employed. This encompassed promotional
tactics, search optimization within podcast platforms, and leveraging social media for outreach.
7
Instagram Account: https://www.instagram.com/factcheckyourhealth
131
The intention was to maximize discoverability and listener engagement through strategic content
placement and community interaction.
Scope of Launch Activities
Due to time and resource constraints, the scope of launch activities was carefully
considered. While additional promotional tactics such as cross-promotion with influencers and
other podcasts, the creation of teaser content, trailers, and extensive social media and traditional
marketing campaigns would typically enhance a podcast's launch, these were not viable within
the project's parameters. The chosen launch strategy was therefore designed to capitalize on the
most accessible and impactful tools available, including organic growth through platform
optimization, community engagement via social media, and word-of-mouth promotion driven by
early listeners. This focused approach aimed to establish a solid listener base upon which future
marketing efforts could be built and reflects a strategic prioritization that sets the stage for
possible sustainable growth.
Results
The podcast's initial release saw promising engagement from the public. Within the first
week of availability, the podcast received approximately 250 individual downloads across
various platforms, and in the first month over 300. Comparatively, half of all podcast episodes
receive less than 29 downloads in the first week after publishing (Howarth, 2024). This early
interest in the podcast indicated a strong initial reception and suggested a potential for growth
and broader reach with sustained promotion, marketing strategy, and content delivery.
Listener feedback, particularly through the Apple Podcast platform, was highly positive,
with 20 five-star reviews accumulated in the first two weeks. Reviews emphasized the podcast's
132
informativeness and clarity, with listeners appreciating the easily digestible format and the
practicality of the content. Comments highlighted the podcast's help in managing the
complexities of health information, with specific comments on the clear explanations and
applicability to everyday decision-making.
The reviews reflected the successful communication of key concepts and indicated that
the podcast was achieving its educational goals. The positive listener responses also suggested
the potential for the podcast to serve as a valuable resource for individuals looking to improve
their health literacy in an environment saturated with diverse and often conflicting health
information.
As the podcast continues to reach listeners, these early indicators of success will serve as
a foundation for ongoing assessment and adjustments to the dissemination strategy, ensuring that
"Fact Check Your Health" remains an accessible and valuable resource for its target audience.
Limitations & Future Research
While the "Fact Check Your Health" podcast demonstrated promising initial engagement,
there are inherent limitations that future research could address to improve the impact and reach
of this educational tool.
One of the primary limitations was the absence of an extensive marketing and
promotional strategy. The initial launch lacked the support of cross-promotion with influencers,
teaser trailers, and other comprehensive marketing campaigns, mainly due to time and resource
constraints. Additionally, the podcast was only promoted during the first three days of the
launch, and all of the episodes were released at once. Future studies could examine the effects of
a robust marketing approach on the dissemination and uptake of the podcast, which could
133
provide valuable insights into methods to enhance the visibility and appeal of educational
content in health literacy.
Furthermore, the study's reliance on surface measures, such as downloads and reviews,
provides a limited scope of listener engagement. Future research may benefit from employing
more detailed data collection methods such as surveys, interviews, and in-depth usage analytics
to gain a better understanding of the podcast's influence on listener behavior and health decision
literacy. Future studies could also measure actual behavioral changes in listeners, such as their
ability to make informed health decisions and apply critical thinking skills in real-life scenarios,
rather than relying solely on self-reported data. This could be achieved through longitudinal
studies or by tracking changes in participants' health-related actions and outcomes over time.
Additionally, it is important to consider the Hawthorne effect, where individuals alter their
behavior due to the awareness of being observed, which may influence the results.
Moreover, the current approach also targeted a specific demographic profile, which
suggests the potential to expand the reach. Future research could examine the podcast's reception
across varied demographic groups, leading to more general content strategies and possibly a
wider audience base.
In addition, the study did not incorporate the recording of the podcast episodes in video
format, which could be an asset for promotional activities on platforms favoring short-form
video content, such as TikTok and YouTube. Future research could investigate the effectiveness
of such formats in conjunction with current social media trends to enhance engagement.
Lastly, the development of additional episodes that cover a broader range of health
topics, the incorporation of guest experts, and the exploration of collaborations with related
content creators could significantly improve the content and appeal of the podcast. By expanding
134
its scope and maximizing the strengths of social media and collaborative opportunities, future
research could build on the initial success and optimize the podcast's contribution to public
health education.
In conclusion, while the initial results of the "Fact Check Your Health" podcast are
encouraging, there are various avenues for future research to expand on. Through more
comprehensive promotional strategies, detailed metrics of engagement, broadened demographic
reach, and enhanced content development, there is significant potential to maximize the
educational impact of the podcast and its role in promoting informed health decisions.
Conclusion
Study 3 represents a significant advancement in health decision literacy interventions,
with the "Fact Check Your Health" podcast providing evidence to the power of accessible and
engaging health education. The condensed podcast, evaluated in Part I, showcased a clear and
significant improvement in HDL among participants, confirming that the streamlined content
retained its efficacy. This phase of the study highlighted the importance of adaptability and
conciseness in health communication, particularly within the context of busy modern lifestyles.
Transitioning to Part II, the public launch of the podcast offered an opportunity to
translate these findings into real-world impact. The positive reception, indicated by download
figures and listener feedback, demonstrates the podcast's appeal to the public and its potential to
serve as a sustainable resource for individuals seeking to enhance their health decision-making
capabilities.
Despite facing limitations in marketing and promotional efforts, the initial engagement
metrics present a strong foundation for the podcast's future growth. The limitations identified
provide opportunities for future research to further improve the reach and effectiveness of the
135
"Fact Check Your Health" podcast. Looking to the future, the goal is to continue refining and
expanding the podcast's content and dissemination strategies, ensuring that it can adapt to
changing media trends and listener preferences.
The insights gained from Study 3’s dual-phase approach, encompassing both
experimental evaluation and real-world application, contribute valuable knowledge to the field of
health education. They confirm that with strategic design and thoughtful implementation,
educational interventions such as the "Fact Check Your Health" podcast can achieve substantial
reach and positively influence public health outcomes.
Study 3 bridges the gap between research and practice, setting a precedent for the
development, evaluation, and dissemination of health literacy interventions. It paves the way for
future initiatives to build upon its success, continuing the mission to empower individuals with
the knowledge and skills necessary to make informed health decisions in a digital society.
Chapter 5: General Discussion
The sequence of Studies 1 through 3 provides a comprehensive narrative intending to
enhance Health Decision Literacy (HDL) within the digital space, using a podcast intervention.
This series of studies highlights the role of HDL in understanding online health information and
demonstrates the efficacy of a novel, podcast-based intervention in enhancing improvements in
health literacy.
Study 1 established a foundation by examining aspects such as individuals' reported
motivations for seeking health information and their source preferences. It identified various
health information-seeking behaviors, linked to desires for autonomy in health decision-making
and a pursuit for reliable information. Importantly, Study 1 identified significant correlations
136
between health literacy habits and cognitive/demographic variables, offering insights into the
factors in engagement with health information. The insights from Study 1 were important in
identifying gaps and opportunities for HDL enhancement.
Study 2 involved the creation of a targeted intervention to boost HDL. This effort
included two integral developments: formulating and validating the HDL Scale and creating the
"Fact Check Your Health" podcast. The HDL Scale proved essential for assessing individuals'
ability to make informed health decisions. In response to the identified needs, the podcast was
designed to be an innovative tool for health literacy education, prioritizing engagement,
accessibility, and the improvement of the various literacy skills necessary for evaluating health
information. The intervention in Study 2 was successful in significantly improving participant’s
HDL.
Progressing to Study 3, the focus shifted to refining the podcast into a condensed, more
accessible format, without sacrificing its educational content. Subsequent improvements in HDL
scores among participants confirmed the condensed podcast's effectiveness as an educational
tool. Moreover, the public launch of the podcast marked a transition from controlled
experimental settings to broader audience engagement. This stage determined the podcast's
appeal and impact in a real-world context, with early public engagement metrics signaling the
successful transformation of research insights into a practical health literacy resource.
This dissertation showcases the importance of digital interventions, such as podcasts, in
health education and demonstrates the necessity for adaptability, feedback, and real-world testing
in developing effective and sustainable health literacy solutions. By systematically addressing
identified needs, engaging with the target demographic, and refining the intervention based on
feedback and real-world outcomes, this series of studies highlights a comprehensive approach to
137
enhancing health decision-making capabilities. As such, it sets a precedent for future health
literacy efforts, emphasizing the power of innovative methods, thorough evaluation, and strategic
use of digital platforms to empower individuals with the skills and knowledge necessary for
informed health decision-making and improve public health outcomes.
138
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Appendix A: Study 1 Guided Interview Script
Introduction Prompt:
Thank you for agreeing to participate in this interview. I am going to be recording today’s
conversation. I do this so I can focus on our discussion instead of trying to take notes. I am going
to start the recorder now.
There are no right or wrong answers to the questions I am going to ask you, so please don’t
hesitate to share anything that is on your mind. Remember, your responses will be completely
confidential – which means that nobody will know that it’s you who said the things we discussed.
Today, we’re going to be talking about your experiences with doing your own research to gather
health information. “Doing your own research” can include things like listening to podcasts,
watching videos on the internet, reading blogs or scientific articles, or gathering information
from any other type of source.
I am going to start by asking you a couple of questions about what type of topics you’ve
researched in the past and what motivated you to do the research. Then we will ask you a series
of questions about what your research process typically looks like.
Interview Questions
Qualifying Question: Must report having wanted to do their own research on at least one topic
1. Have you ever wanted to do your own research on a health-related topic? (ex. Nutrition,
food, exercise, vaccines, medications, medical treatments. etc.). If so, which topics in
particular?
Motivation Questions:
First, I’d like to talk to you about what motivates you when you are trying to do your own
research on health-related topics.
1. Thinking back to some of the times that you did your own research on health, what
motivated you to do this? (Potential motivations: Unresolved health problems, distrust in
science/traditional medicine, social media, the news, podcast, book, documentary, friend,
partner, etc.)
a. IF RELEVANT, Can you tell me a bit more about a time when you had a health
issue that motivated you to do research?
i. How did you become aware of this health issue? (e.g., did a doctor
diagnose you, social media, etc)
2. IF NOT ANSWERED - When you were motivated to do this research, what was
happening in your life at the time? (Potential answers: Started having health problems,
got a health diagnosis, was trying to conceive or got pregnant, had a baby, got married,
life change, COVID, when my friends/partner became interested in it, etc.)
Process Questions:
148
1. When you decide that you want to do research on a topic, what is an overview of the
process that you take?
2. How long does it normally take you to research a topic? (Do you do it all at once or over
a period of time)
3. Where do you look to find your information? (Ex. Google, blogs, websites, social media,
books, PubMed, etc.)
a. If they say Internet or Google - Are there any specific websites or organizations
that you usually look at?
4. When doing your own research, you might try to figure out whether your source is
trustworthy and reliable.
a. Do you usually try to figure out how trustworthy your source is? If so, what things
do you look for?
i. Are there any examples of the types of sources you usually consider to be
reliable?
ii. Is there anything that automatically makes you think a source is not
reliable? If so, can you describe it?
b. Do you usually “fact-check” your sources? This can include things like looking
up a study, article, or other information mentioned by your source.
i. If yes, can you describe the methods you usually use to fact-check?
c. Are there certain types of sources that you fact-check more often? If so, what are
they?
5. Some people might look at one resource and feel that they have enough information on a
topic, while others may want to look at multiple sources.
a. How much information do you try to find on a topic?
b. What makes you feel satisfied that you’ve gathered enough information?
6. If you have done research by reading multiple sources, have you ever found conflicting
information?
a. How did you handle this?
b. When you come across conflicting information, are there certain types of sources
you usually decide are more trustworthy? Can you describe these sources, and
why you value them more than others?
7. Once you have done all of your research, how do you normally come to an ultimate
decision about the topic you’re researching?
8. You might come to a conclusion about a topic, and then later you hear or see some
information that is contrary to your conclusion. If this has ever happened to you, how did
you handle this new information?
a. For example, did you look more into the source to see if it was trustworthy or did
you ignore the information?
i. Has there ever been a time that this led you to change your conclusion,
and if so, can you describe it?
Demographics:
1. Age
2. Sex
3. Race
4. Education
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5. Income
6. Occupation
7. Children
8. Zip Code
9. Thoughts/Questions
150
Appendix B. Health Decisions Behaviors Survey
University of Southern California
Department of Psychology
INFORMATION/FACTS SHEET FOR EXEMPT NON-MEDICAL RESEARCH You are
invited to participate in a research study. Your participation is voluntary. This document explains
information about this study. You should ask questions about anything that is unclear to you.
PURPOSE
The purpose of this study is to understand how individuals currently do their own research on a
topic. You must be 18 or older to participate, and your participation is voluntary.
PARTICIPANT INVOLVEMENT
You will be asked to provide information about how you would do your own research on a topic
that you wanted to know more about. You will also be asked to indicate your sex, age, race, and
income as background factors. In addition, you will answer a few reasoning questions and other
questions about yourself. This survey is anticipated to take no more than 10 minutes to complete.
However, we expect that most people will finish it more quickly.
PAYMENT/COMPENSATION FOR PARTICIPATION
You will be compensated $2 for your time.
CONFIDENTIALITY
The members of the research team and the University of Southern California Institutional
Review Board (IRB) may access the data. The IRB reviews and monitors research studies to
protect the rights and welfare of research subjects. When the results of the research are published
or discussed in conferences, no identifiable information will be used. There will be no
information obtained in connection with this survey that can identify you. Your name, address or
other information that may identify you will not be linked to your responses. Only the members
of the research team and the University of Southern California’s Human Subjects Protection
Program (HSPP) may access the data. The HSPP reviews and monitors research studies to
protect the rights and welfare of research subjects. The anonymous data may be used for future
research. If you do not want your data used in future studies, you should not participate.
INVESTIGATOR CONTACT INFORMATION
If you have any questions about this study, please contact Katie Byrd via email at
ksippel@usc.edu or Richard John at richardj@usc.edu
IRB CONTACT INFORMATION
If you have any questions about your rights as a research participant, please contact the
University of Southern California Institutional Review Board at (323) 442-0114 or email
irb@usc.edu.
In this survey you will be asked questions about your experiences with doing your own research
to gather health information. For the purpose of this survey, “Doing your own research” on a
topic might include things like: searching for information on the internet, listening to podcasts,
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watching videos on the internet, reading blogs/books/scientific articles, viewing information on
social media, or gathering information from any other type of source. The survey will begin by
asking a couple of questions about what type of topics you’ve researched in the past and what
motivated you to do the research. Then you will be asked a series of questions about what your
research process typically looks like.
1. Have you ever done your own research on a health related topic? (ex. Nutrition, food,
exercise, vaccines, medications, medical treatments. etc.).
o Yes
o No
o Unsure
2. Which topics in particular have you done research on? (Select all that apply)
▢ Medication
▢ Vaccines
▢ Medical Diagnosis
▢ Medical Treatment/Surgery
▢ Nutrition/Diet/Food
▢ Beauty Products
▢ Household Products
▢ Organic Products
▢ Exercise
▢ Supplements
▢ Alternative/Complementary Medicine (ex. Acupuncture, Chiropractor, Functional
Medicine)
▢ Other: Please Specify
__________________________________________________
3. Thinking back to some of the times that you did your own research on a health related
topic, what motivated you to do this? Select all the apply.
▢ Unresolved health problems (ex. undiagnosed medical problems, fertility,
complications from medicine or procedure, etc.)
▢ Distrust in traditional medicine/science
▢ Motivated by someone/something (ex. friend, social media, documentary, news,
podcast, COVID-19)
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▢ Curiosity
▢ Other: Please specify
__________________________________________________
4. When you were motivated to do this research, what was happening in your life at the
time?
▢ Started having health problems but did not have a diagnosis
▢ Got a health diagnosis
▢ Was trying to conceive or became pregnant
▢ Recently became a parent
▢ Child, partner, or family member started having health problems
▢ A friend, partner, or family member became interested in doing their own
research and told me about it
▢ Wanted to be healthier
▢ Financial concerns/Lack of insurance
▢ COVID-19 pandemic
▢ Other: Please specify
__________________________________________________
▢ Does Not Apply / Nothing in particular was happening in my life
Now you will be asked a series of questions about what your research process typically looks
like. There are no right or wrong answers to the questions you will be asked, so please answer
truthfully.
5. When you decide that you want to do research on a health related topic, where do you
look to find your information? Select all that apply.
▢ Internet Search Engines (ex. Google, Yahoo, etc.)
▢ Social Media (ex. Instagram, Twitter, Facebook, TikTok)
▢ Internet Blogs (ex. Health blogs, mom blogs, fitness blogs, personal blogs, etc.)
▢ Health Websites (ex. WebMD, Healthline)
▢ Federal/Global agency websites (ex. CDC.gov, WHO.int, FDA.gov, etc.)
▢ Medical agency websites (ex. American Heart Association, American Cancer
Society, American Diabetes Association, etc.)
▢ Academic Articles (ex. PubMed, Google Scholar, etc.)
▢ Friends or Family
▢ Books
153
▢ Traditional Medical Professionals (ex. Medical Doctor, Physicians Assistant,
Nurse Practitioner)
▢ Complementary/Alternative Healthcare Providers (ex. Doula, Acupuncturist,
Chiropractor, Functional Medicine Doctor)
▢ Other: Please specify
__________________________________________________
6. Please arrange the sources based on how much you use each of them.
Start with the source that you use the most, followed by the source that you use second most
often, followed by the source that you use the next most often, etc. The source that you use the
least often should be ranked last.
______ Internet Search Engines (ex. Google, Yahoo, etc.)
______ Social Media (ex. Instagram, Twitter, Facebook, TikTok)
______ Internet Blogs (ex. Health blogs, mom blogs, fitness blogs, personal blogs, etc.)
______ Health Websites (ex. WebMD, Healthline)
______ Federal/Global agency websites (ex. CDC.gov, WHO.int, FDA.gov, etc.)
______ Medical agency websites (ex. American Heart Association, American Cancer Society,
American Diabetes Association, etc.)
______ Academic Articles (ex. PubMed, Google Scholar, etc.)
______ Friends or Family
______ Books
______ Traditional Medical Professionals (ex. Medical Doctor, Physicians Assistant, Nurse
Practitioner)
______ Complementary/Alternative Healthcare Providers (ex. Doula, Acupuncturist,
Chiropractor, Functional Medicine Doctor)
______ Other: Please specify
7. When doing your own research, you might try to figure out whether a source is trustworthy
and reliable before deciding what you want to do with the information. Do you usually try to
figure out how trustworthy your source is? This can include things like: verifying the
qualifications of the author/organization making sure the source is legitimate checking if the
source is satire
o Never
o Sometimes
o About half the time
o Most of the time
o Always
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8. Are there any types of sources that you usually consider to be reliable? Select all that apply.
▢ Someone's personal experience (ex. friend, family member, social media story)
▢ Federal/Global agencies (ex. WHO, CDC, FDA, etc.)
▢ Medical agencies (ex. American Heart Association, American Cancer Society,
American Diabetes Association, etc.)
▢ Traditional Healthcare providers (ex. Medical Doctors/MDs/DOs, Physicians
Assistants, Nurse Practitioners, etc.)
▢ Complementary/Alternative Healthcare providers (ex. Doulas, Acupuncturist,
Chiropractors, Functional Medicine Doctors/NDs, etc.)
▢ Academic Articles (ex. PubMed, Google Scholar, etc.)
▢ Social Media Accounts (ex. Instagram, TikTok, Facebook, etc.)
▢ Books
▢ Internet Blogs (ex. Health blogs, mom blogs, fitness blogs, personal blogs, etc.)
▢ Health Websites (ex. WebMD, HealthLine, etc.)
9. Are there any types of sources that you usually consider to be unreliable? Select all that
apply.
▢ Someone's personal experience (ex. friend, family member, social media story)
▢ Federal/Global agencies (ex. WHO, CDC, FDA, etc.)
▢ Medical agencies (ex. American Heart Association, American Cancer Society,
American Diabetes Association, etc.)
▢ Traditional Healthcare providers (ex. Medical Doctors/MDs/DOs, Physicians
Assistants, Nurse Practitioners, etc.)
▢ Complementary/Alternative Healthcare providers (ex. Doulas, Acupuncturist,
Chiropractors, Functional Medicine Doctors/NDs, etc.)
▢ Academic Articles (ex. PubMed, Google Scholar, etc.)
▢ Social Media Accounts (ex. Instagram, TikTok, Facebook, etc.)
▢ Books
▢ Internet Blogs (ex. Health blogs, mom blogs, fitness blogs, personal blogs, etc.)
▢ Health Websites (ex. WebMD, HealthLine, etc.)
10. Do you usually “fact check” your sources? This can include things like: looking up a study,
article, or other information mentioned by your source checking the source's credibility checking
to see if multiple sources confirm the same information.
o Never
155
o Sometimes
o About half the time
o Most of the time
o Always
o It depends on the source
11. Some people might look at one resource and feel that they have enough information on a
topic, while others may want to look at multiple sources. How much information do you try to
find on a topic?
o Once I find one source I usually stop looking
o I usually find two sources than stop looking
o I usually try to find three or more sources
12. When researching health related topics it is common to come across opposing and conflicting
opinions. For example one source might claim that a medication is good for you while a different
source might claim that the same medication is bad for you. When you come across conflicting
information how have you typically handled it? Select all that apply.
▢ Fact check the sources to see if they are reliable
▢ Believe the information that matches my prior opinion/beliefs and ignore
opposing information
▢ Read additional sources to see which viewpoint most sources agree with
▢ Compare the quality of the research/information on both sides
▢ Move on and decide you aren’t sure what information is correct
▢ Does Not Apply / I have never found conflicting information
13. You might come to a conclusion about a topic, and then later hear or see some new
information that is contrary to your original conclusion. For example, imagine you did your own
research on different types of diets/eating patterns and decided that one specific diet was best for
your health. Then, at a later point you come across new information that the diet you've been
following might actually be harmful.
If this happened to you, how would you handle this new information?
o I would ignore the new information and stick with my original conclusion
o I would believe the new information and change my previous conclusion
156
o I would look into the source of the new information to see if it was reliable, then consider
changing my previous conclusion
Cognitive Measures
1. Please indicate your agreement level with the following statements.
Strongly
Disagree
Disagree Somewhat
Disagree
Somewhat
Agree
Agree Strongly
Agree
True experts
are willing to
admit to
themselves
and others
that they are
uncertain or
that they
don't know
the answer.
o o o o o o
People
should take
into
consideration
evidence that
goes against
conclusions
they favor.
o o o o o o
Being
undecided or
unsure is the
result of
muddled
thinking.
o o o o o o
People
should revise
their
conclusions
in response
to relevant
new
information.
o o o o o o
157
Changing
your mind is
a sign of
weakness.
o o o o o o
People
should search
actively for
reasons why
they might be
wrong.
o o o o o o
It is OK to
ignore
evidence
against your
established
opinions.
o o o o o o
It is
important to
be loyal to
your
opinions
even when
evidence is
brought to
bear against
them.
o o o o o o
There is
nothing
wrong with
being
undecided
about many
issues.
o o o o o o
158
When faced
with a
puzzling
question, we
should try to
consider
more than
one possible
answer
before
reaching a
conclusion.
o o o o o o
It is best to
be confident
in a
conclusion
even when
we have
good reasons
to question it.
o o o o o o
2. Out of 1,000 people in a small town 500 are members of a choir. Out of these 500
members in a choir, 100 are men. Out of the 500 inhabitants that are not in a choir 300
are men. What is the probability that a randomly drawn man is a member of the choir?
Please indicate the probability in percent.
________________________________________________________________
3. Emily’s father has three daughters. The first two are named April and May. What is the
third daughter’s name?
________________________________________________________________
4. How many cubic feet of dirt are there in a hole that is 3’ deep x 3’ wide x 3’ long?
________________________________________________________________
159
5. A farmer had 15 sheep and all but 8 died. How many are left?
________________________________________________________________
Demographics
1. How old are you?
18 21 23 26 29 32 34 37 40 42 45
Age in years
2. What is your highest level of education
o Less than high school
o High school graduate
o Some college
o 2 year degree
o 4 year degree
o Professional degree
o Doctorate
o Prefer not to say
3. Information about income is very important to understand. Would you please give your
best guess? Please indicate the answer that includes your entire household income in
(previous year) before taxes.
o Less than $10,000
o $10,000 to $19,999
o $20,000 to $29,999
o $30,000 to $39,999
o $40,000 to $49,999
o $50,000 to $59,999
o $60,000 to $69,999
o $70,000 to $79,999
o $80,000 to $89,999
o $90,000 to $99,999
160
o $100,000 to $149,999
o $150,000 or more
o Prefer not to say
4. What is your sex?
o Male
o Female
o Other / Prefer not to say
5. Are you Spanish, Hispanic, or Latino or none of these?
o Yes
o None of these
6. Choose one or more races that you consider yourself to be:
▢ White
▢ Black or African American
▢ American Indian or Alaska Native
▢ Asian
▢ Native Hawaiian or Pacific Islander
▢ Other __________________________________________________
7. Are you currently married, widowed, divorced, separated or single/never married?
o Married
o Widowed
o Divorced
o Separated
o Single / Never Married
8. If you are a parent or guardian, how many children do you currently have under the age
of 18?
o 1
o 2
o 3
o 4
o 5 or more
161
o 0 / Not Applicable
9. Here is a 7-point scale on which the political views that people might hold are arranged
from extremely liberal (left) to extremely conservative (right). Where would you place
yourself on this scale?
Extremely
liberal 1
2 3 4 5 6 Extremely
conservative
7
Political
Ideology o o o o o o o
10. In which state do you currently reside?
▼ Alabama ... I do not reside in the United States
11. What is your ZIP code?
________________________________________________________________
162
Appendix C. Health Decision Literacy Scale
Question 1a:
Let's say you want to know if turmeric can help reduce inflammation in the body. Where would
you look for information? (select all that apply)
a. Social Media
b. Internet search engines (e.g., Google, Yahoo, etc.)
c. Academic search engines (e.g., PubMed, Google Scholar)
d. Friends & Family
e. Traditional Medical Professionals (e.g., Medical Doctor, Physicians Assistant, Nurse
Practitioner)
f. Complementary/Alternative Healthcare Providers (e.g., Herbalist, Naturopath,
Homeopath, Ayurvedic Practitioner)
Scoring: 1 point if they select “Academic search engine”
Question 1b:
Let's say you've heard that consuming flaxseed oil can boost brain health. Where would you look
for information? (select all that apply)
a. Social Media
b. Internet search engines (e.g., Google, Yahoo, etc.)
c. Academic search engines (e.g., PubMed, Google Scholar)
d. Friends & Family
e. Traditional Medical Professionals (e.g., Medical Doctor, Physicians Assistant, Nurse
Practitioner)
f. Complementary/Alternative Healthcare Providers (e.g., Nutritionist, Herbalist,
Naturopathic Doctor)
Scoring: 1 point if they select “Academic search engine”
Question 2a:
Headline: Coffee lowers risk of heart problems and early death, study says, especially ground
and caffeinated.
Study abstract:
This study analyzed observational data from a large database to investigate the relationship
between coffee intake and cardiovascular outcomes over a 12-year period. The study included
400,000 participants who reported their daily coffee intake and heart problems once a year
through an online survey. The results showed that ground coffee consumption was associated
with significantly lower odds of having a heart problem over the study period. Furthermore,
decaffeinated, ground, and instant coffee, particularly when consumed at 2-3 cups per day, were
linked to significant reductions in incident cardiovascular disease and mortality. Ground and
163
instant coffee were also associated with reduced arrhythmia, whereas decaffeinated coffee was
not.
Does the news headline accurately reflect the findings of this study?
a. Yes, because the study found that coffee caused an improvement in heart problems
b. No, because the headline implies that coffee caused heart problems to improve, but this
study design can’t prove causation, it only proves correlation
c. I’m not sure
Scoring: 1 point if they select “B”
Question 2b:
Headline: Drinking green tea reduces the risk of breast cancer, especially when consumed daily,
according to a recent study.
Study abstract:
This study analyzed observational data from a large database to investigate the relationship
between green tea intake and the incidence of breast cancer over a 10-year period. The study
included 350,000 participants who reported their daily green tea intake and any breast cancer
diagnosis once a year through an online survey. The results showed that daily green tea
consumption was associated with significantly lower odds of being diagnosed with breast cancer
over the study period. Furthermore, drinking 1-2 cups daily was linked to significant reductions
in incident breast cancer cases. Participants who consumed green tea extracts also showed a
reduced risk, but the impact was less pronounced than for those drinking the brewed tea.
Does the news headline accurately reflect the findings of this study?
a. Yes, because the study found that green tea caused a reduction in breast cancer diagnoses.
b. No, because the headline implies that green tea caused the reduction in breast cancer
diagnoses, but this study design can’t prove causation, it only proves correlation.
c. I’m not sure
Scoring: 1 point if they select “B”
Question 3a:
Headline: Diet soda and other sugar-free sweeteners are harming your gut
Study Abstract:
The consumption of sugar-free foods is growing because of their low-calorie content and the
health concerns about products with high sugar content. Although sugar-free sweeteners are
considered safe and well tolerated, alterations to gut microbiota composition are controversial.
This review critically discusses high-quality experimental studies and clinical trials that evaluate
the effects of sugar-free sweeteners on the composition of microbiota in the human gut. So far,
only three sugar-free sweeteners change the composition of the gut microbiota, by increasing the
numbers of bifidobacteria in humans. Further research on the effects of sweeteners on the
164
composition of the human gut microbiome is necessary, and further research is needed to
understand the effects of increased bifidobacteria in humans.
Does the news headline accurately reflect the findings of this study?
a. Yes, because the study found that sugar-free sweeteners increased bacteria in the gut
b. No, because the study found that sugar-free sweeteners increased bacteria in the gut, but
didn’t establish whether the bacteria was good or bad
c. I’m not sure
Scoring: 1 point if they select “B”
Question 3b:
Headline: Consumption of probiotics leads to improved mental health, new research indicates.
Study Abstract:
The use of probiotics has become popular due to their potential benefits on gut health. These live
bacteria, often found in fermented foods, are consumed to enhance the variety and number of
beneficial microbes in the gut. Although probiotics are deemed safe and beneficial for digestion,
their effects on mental health remain debated. This review systematically examines high-quality
studies and clinical trials evaluating the effects of probiotics on the mental well-being of
individuals. The current evidence suggests that certain strains of probiotics lead to an increase in
the levels of Lactobacillus in humans. However, the implications of increased Lactobacillus on
mental health are not fully understood, necessitating more extensive research on the topic.
Does the news headline accurately reflect the findings of this study?
a. Yes, because the study found that probiotics increased levels of Lactobacillus in the gut.
b. No, because the study found that probiotics increased levels of Lactobacillus in the gut,
but didn’t establish a direct link between Lactobacillus and improved mental health.
c. I’m not sure.
Scoring: 1 point if they select “B”
Question 4a:
Headline: Eating dark chocolate regularly is one answer to enhanced brain function.
Study Abstract:
Dark chocolate, like nuts and green tea, contains high levels of flavonoids. Previous
observational studies have suggested that flavonoids may have positive effects on cognitive
function. Using data from a community sample (N=850), this study aimed to determine the
relationship between dark chocolate consumption and cognitive performance. Participants selfreported their dark chocolate intake, and their cognitive function was assessed through
standardized tests. A higher intake of flavonoids, particularly from dark chocolate, was
associated with better scores on cognitive tests. However, the relationship between the intake of
nuts and green tea and cognitive function did not appear to be significant. Although dark
165
chocolate was associated with enhanced cognitive performance, the direct cause of this
relationship requires further investigation.
Does the news headline accurately reflect the findings of this study?
a. Yes, because the study found that dark chocolate was associated with better cognitive
performance.
b. No, because the headline implies that dark chocolate directly enhances brain function, but
this study design can’t prove causation, it only proves correlation.
c. I’m not sure.
Scoring: 1 point if they select “B”
Question 4b:
Headline: Regular intake of blueberries is your ticket to a sharper memory.
Study Abstract:
Blueberries, similar to fish and whole grains, are rich in antioxidants. Some observational studies
have indicated that antioxidants may bolster memory function. In this study, which used data
from N=1,000 participants, the association between blueberry consumption and memory
enhancement was examined. Participants were asked about their blueberry consumption habits
and subsequently underwent memory assessment tests. Results showed that those who consumed
blueberries frequently had marginally better scores on memory tests compared to those who did
not. However, the consumption of fish and whole grains did not show any significant correlation
with memory performance. Although there was an observed relationship between blueberry
consumption and better memory scores, further research is required to determine the exact nature
of this association.
Does the news headline accurately reflect the findings of this study?
a. Yes, because the study found that frequent blueberry consumption was related to better
memory scores.
b. No, because the headline suggests that blueberries directly improve memory, but this
study design can’t prove causation, it only shows a correlation.
c. I’m not sure.
Scoring: 1 point if they select “B”
Question 5a:
You saw a post on social media about a product called NailBoost that claims to enhance nail
growth. Before trying it, you want more information. Which of the following should you NOT
type into the search bar if you want to avoid confirmation bias?
a. Pros and cons of NailBoost for nail growth
b. Does NailBoost promote nail growth?
c. Best products for nail growth.
166
d. Studies on the effectiveness of nail growth products.
Scoring: 1 point if they select “B”
Question 5b:
You recently watched a video on social media that praises a hair product named HairFlare for
promoting faster hair growth. Intrigued, you're considering giving it a shot but want to be
informed. Which of the following should you NOT type into the search bar if you want to avoid
confirmation bias?
a. Benefits and drawbacks of HairFlare for hair growth.
b. Does HairFlare really speed up hair growth?
c. Top hair growth products on the market.
d. Research findings on products that claim to boost hair growth speed.
Scoring: 1 point if they select “B”
Question 6a:
You have been experiencing mild anxiety lately and are considering trying a herbal supplement
named CalmEase that you read about on social media. CalmEase is marketed as a natural remedy
for anxiety and claims to have no side effects. Before giving it a try, you want to gather more
details. Which of the following should you NOT type into the search bar if you want to avoid
confirmation bias?
a. Benefits and drawbacks of CalmEase for anxiety relief.
b. Does CalmEase genuinely help with anxiety symptoms?
c. Most recommended natural supplements for anxiety.
d. Scientific research on the effectiveness of herbal supplements like CalmEase for anxiety.
Scoring: 1 point if they select “B”
Question 6b:
You've been having difficulty falling asleep recently and stumbled upon an advertisement for a
herbal tea called SleepTonic that claims to promote better sleep. SleepTonic is marketed as an
all-natural sleep aid that can help you fall asleep faster and enjoy deeper sleep. Intrigued but
skeptical, you decide to look into it further. Which of the following should you NOT type into
the search bar if you want to avoid confirmation bias?
a. Advantages and potential risks of SleepTonic for sleep enhancement.
b. Can SleepTonic truly aid in better sleep quality?
c. Top herbal teas known to improve sleep.
d. Clinical studies evaluating the efficacy of teas like SleepTonic for sleep.
Scoring: 1 point if they select “B”
Question 7a:
167
You recently heard about a new herbal supplement that claims to improve bloating and gut
function. You want to quickly understand the research on this supplement. What should you
focus on reading first?
a. Abstract
b. Introduction
c. Methods
d. Results
Scoring: 1 point if they select “A”
Question 7b:
You recently heard about a supplement that claims to improve menstruation and fertility. You
want to quickly understand the research on this supplement. What should you focus on reading
first?
e. Abstract
f. Introduction
g. Methods
h. Results
Scoring: 1 point if they select “A”
Question 8a:
For this example, let's say you currently weigh 200 pounds. You were recently diagnosed with a
condition, and weight loss is one of the potential treatment options. Your doctor recently told
you that if you could reduce your weight by 10%, it would be considered a clinically significant
weight loss. This means you would need to lose 20 pounds. You found a study comparing the
effects of a new diet (Diet A) with a control group that was not following any specific diet, and it
reported a statistically significant difference of one pound of weight loss for people who
followed the diet. You are trying to decide if you should try Diet A. Which of the following
would be true for you based on the study?
a. Diet A is potentially beneficial for my condition because it is connected with weight loss.
b. While Diet A is associated with a statistically significant weight loss, the actual weight
loss of 1 pound isn't clinically significant for me, as it's far from the 20 pounds or 10% of
my current weight.
c. Following Diet A would lead to a weight loss that's both statistically and clinically
significant for me.
d. Trying Diet A wouldn't lead to a weight loss that is clinically or statistically significant
for my condition.
Scoring: 1 point if they select “B”
Question 9a:
168
For this example, let's say you currently weigh 200 pounds and have been advised to lose weight
to improve your overall health. In researching potential diets, you come across a new diet called
Diet B. A published study on Diet B reports a statistically significant weight loss of 15 pounds
on average over six months compared to a control group. The study, however, had a high
dropout rate, with 40% of the participants not completing the six-month duration. You are
considering whether to adopt Diet B. Which of the following statements is most accurate based
on the study?
a. Diet B is guaranteed to make me lose 15 pounds if I follow it for six months.
b. Diet B has shown promising results, but the high dropout rate may suggest that the diet
could be difficult to adhere to or there could be other issues.
c. The dropout rate is not important; the only thing that matters is the average weight loss of
those who completed the study.
d. Since Diet B showed statistically significant weight loss, it means it's the best diet
available for weight loss.
Scoring: 1 point if they select “B”
Question 8b:
For this example, let's say you currently weigh 200 pounds. You were recently diagnosed with a
condition, and weight loss is one of the potential treatment options. Your doctor recently told
you that if you could reduce your weight by 10%, it would be considered a clinically significant
weight loss. This means you would need to lose 20 pounds. You found a study comparing the
effects of a new fitness program (Fitness Program A) with a control group that was not following
any fitness program, and it reported a statistically significant difference of one pound of weight
loss for people who followed the fitness program. You are trying to decide if you should try
Fitness Program A. Which of the following would be true for you based on the study?
e. Fitness Program A is potentially beneficial for my condition because it is connected with
weight loss.
f. While Fitness Program A is associated with a statistically significant weight loss, the
actual weight loss of 1 pound isn't clinically significant for me, as it's far from the 20
pounds or 10% of my current weight.
g. Following Fitness Program A would lead to a weight loss that's both statistically and
clinically significant for me.
h. Trying Fitness Program A wouldn't lead to a weight loss that is clinically or statistically
significant for my condition.
Scoring: 1 point if they select “B”
Question 9b:
For this example, let's say you currently weigh 200 pounds and have been advised to lose weight
to improve your overall health. In researching potential fitness programs, you come across a new
fitness program called Fitness Program B. A published study on Fitness Program B reports a
169
statistically significant weight loss of 15 pounds on average over six months compared to a
control group. The study, however, had a high dropout rate, with 40% of the participants not
completing the six-month duration. You are considering whether to adopt Fitness Program B.
Which of the following statements is most accurate based on the study?
e. Fitness Program B is guaranteed to make me lose 15 pounds if I follow it for six months.
f. Fitness Program B has shown promising results, but the high dropout rate may suggest
that the program could be difficult to adhere to or there could be other issues.
g. The dropout rate is not important; the only thing that matters is the average weight loss of
those who completed the study.
h. Since Fitness Program B showed statistically significant weight loss, it means it's the best
fitness program available for weight loss.
Scoring: 1 point if they select “B”
Question 10a:
You have two different medications to choose from for a health condition:
Medication A triples your risk of a rare side effect, increasing it from one in a million to three in
a million.
Medication B doubles your risk of a common side effect, increasing it from one in a hundred to
two in a hundred.
Which medication would you choose to minimize the absolute risk of side effects?
a. Medication A
b. Medication B
c. It doesn't matter which medication I choose; the risk increases in both cases.
d. I’m unsure
Scoring: 1 point if they select “A”
Question 10b:
You're considering two different surgeries to treat a medical condition. Each surgery has its own
set of potential complications:
Surgery A: It triples your risk of a rare complication, increasing it from one in a thousand to
three in a thousand.
Surgery B: It doubles your risk of a common complication, increasing it from one in ten to two
in ten.
Which surgery would you choose to minimize the absolute risk of complications?
a. Surgery A
b. Surgery B
c. It doesn't matter which surgery I choose; the risk increases in both cases.
170
d. I’m unsure.
Scoring: 1 point if they select “A”
Question 11a:
A skincare company wants to determine how effective their new product is at reducing acne.
They recruited 20 participants and measured the amount of acne present after using the product
for one month. Based on the amount of acne that participants had at the end of the month, they
concluded that the skin care product is effective in reducing acne.
What is(are) the major weakness(es) of this study?
a. The study did not measure the participants' acne before starting the product
b. The study did not use a placebo control group.
c. The sample size is too small to draw meaningful conclusions.
d. All the above
e. None of the above, the study adequately assessed the effectiveness of the product.
Scoring: 1 point if they select “D”
Question 11b:
A haircare company wants to determine how effective their new shampoo is at reducing hair fall.
They recruited 25 participants and measured the amount of hair fall after using the shampoo for
two weeks. Based on the amount of hair that participants lost at the end of the two weeks, they
concluded that the shampoo is effective in reducing hair fall.
What is(are) the major weakness(es) of this study?
a. The study did not measure the participants' hair fall rate before starting the shampoo.
b. The study did not use a placebo control group.
c. The sample size is too small to draw meaningful conclusions.
d. All the above
e. None of the above, the study adequately assessed the effectiveness of the product.
Scoring: 1 point if they select “D”
Question 12a:
A research study aimed to assess the effectiveness of a new fitness weight loss program. They
enrolled 400 participants with similar fitness levels with the goal of evaluating weight loss after
1 year. The participants were randomly assigned to two groups: one group followed the new
fitness weight loss program, while the other group followed their usual exercise routines. The
study found that the program group had a significantly greater weight loss compared to the
control group.
171
What is(are) a major weakness(es) of this study?
a. The study did not properly monitor participants' dietary habits which could be a
confounding factor of weight loss.
b. The study did not have a control group.
c. The study was too short.
d. All the above
e. None of the above, the study adequately assessed the effectiveness of the program.
Scoring: 1 point if they select “A”
Question 12b:
A research study aimed to assess the effectiveness of a new diet program. They enrolled 400
participants with a similar current weight with the goal of evaluating weight loss after 1 year.
The participants were randomly assigned to two groups: one group followed the new diet
program, while the other group followed their usual eating patterns. The study found that the diet
program group had a significantly greater weight loss compared to the control group.
What is(are) a major weakness(es) of this study?
a. The study did not properly monitor participants' fitness levels which could be a
confounding factor in diet weight loss.
b. The study did not have a control group.
c. The study was too short.
d. All the above
e. None of the above, the study adequately assessed the effectiveness of the program.
Scoring: 1 point if they select “A”
172
Appendix D. Fact Check Your Health Website and Social Media Accounts
Social Media Account: Instagram
173
Home Page:
174
175
176
Example Episode Page:
177
178
179
About Page:
180
181
182
Subscribe Page:
183
184
185
Apple Podcast Listing:
Abstract (if available)
Abstract
This dissertation presents a comprehensive examination of Health Decision Literacy (HDL) within the current digital information space, focusing specifically on women aged 18-45. Spanning three studies (N=933), this research examines how individuals seek, perceive, and use online health information, and evaluates an innovative educational intervention aimed at improving HDL. Study 1 establishes the foundation by determining motivations behind health information-seeking behaviors and preferences for specific sources, revealing a relationship of trust, autonomy, and the influence of cognitive and demographic variables on health literacy practices. Building on these insights, Study 2 introduces the "Fact Check Your Health" podcast as a novel boosting intervention designed to enhance HDL. This study details the creation and validation of an HDL Scale, followed by an assessment of the podcast's efficacy through a randomized control trial demonstrating significant improvements in HDL among participants. Study 3 develops a condensed version of the podcast. The effectiveness of this revised format is also confirmed through a RCT, followed by a public launch demonstrating a step towards evaluating the podcast's real-world impact. Early engagement metrics and positive audience feedback from the public launch highlight the intervention's potential for broad application and its effectiveness in enhancing informed health decision-making. Collectively, these studies offer a novel perspective on boosting HDL through digital interventions, emphasizing the importance of understanding target audiences, using innovative media such as podcasts, and the necessity of adaptability and feedback in educational content creation.
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Early literacy intervention
Asset Metadata
Creator
Byrd, Katie E. S.
(author)
Core Title
Improving health decision literacy: enhancing informed health decisions through podcast interventions
School
College of Letters, Arts and Sciences
Degree
Doctor of Philosophy
Degree Program
Psychology
Degree Conferral Date
2024-08
Publication Date
07/26/2024
Defense Date
05/06/2024
Publisher
Los Angeles, California
(original),
University of Southern California
(original),
University of Southern California. Libraries
(digital)
Tag
health literacy, podcast intervention, women's health, decision making, randomized control trial
Format
theses
(aat)
Language
English
Contributor
Electronically uploaded by the author
(provenance)
Advisor
John, Richard S. (
committee chair
)
Creator Email
katie.e.sippel@gmail.com,ksippel@usc.edu
Permanent Link (DOI)
https://doi.org/10.25549/usctheses-oUC113998G0U
Unique identifier
UC113998G0U
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Byrd, Katie E. S.
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Tags
health literacy, podcast intervention, women's health, decision making, randomized control trial