Close
Home
Collections
Login
USC Login
Register
0
Selected
Invert selection
Deselect all
Deselect all
Click here to refresh results
Click here to refresh results
USC
/
Digital Library
/
University of Southern California Dissertations and Theses
/
College-educated older adults and information and communications technology
(USC Thesis Other)
College-educated older adults and information and communications technology
PDF
Download
Share
Open document
Flip pages
Contact Us
Contact Us
Copy asset link
Request this asset
Transcript (if available)
Content
College-Educated Older Adults and Information and Communications Technology
by
Kim Thu Nguyen
Rossier School of Education
University of Southern California
An executive dissertation submitted to the faculty
in partial fulfillment of the requirements for the degree of
Doctor of Education
December 2021
© Copyright by Kim Thu Nguyen 2021
All Rights Reserved
The Committee for Kim Thu Nguyen certifies the approval of this Executive Dissertation
Briana Hinga
Anthony Maddox
Patricia Tobey, Committee Chair
Rossier School of Education
University of Southern California
2021
iv
Abstract
The purpose of this study was to understand how adults 65 years and older use Information and
Communications Technology (ICT), the barriers and difficulties they experience when using
ICT, and how ICT could be improved for older adults. The study aimed to reveal the target
population’s lived experiences when operating their electronic devices and navigating
applications and websites. Data were gathered through 15 qualitative interviews with adults
ranging in age from 65 to 87. Interviews were conducted via phone and video conferencing
technology. A convenience sampling approach was used, and education was not part of the
participant criteria. However, all 15 individuals were college-educated, with 11 of the 15 having
earned a graduate degree. While ICT is a broad field, interview questions were limited to high-
speed internet, laptop or desktop computers, smartphones, and tablets to narrow the scope of the
study. Bronfenbrenner’s ecological systems model (1979) was the overarching conceptual
framework used to understand system influences that help explain older adults' relationship with
ICT and how this may change over time due to environmental forces and factors. Other models
and theories considered in this study were the relative deprivation theory (Crosby, 1976) and the
technology readiness and acceptance model (Davis, 1989; Parasuraman, 2000).
Keywords: Older adults, ageism, elder abuse, elder justice, equity, digital divide,
Information and Communications Technology adoption, Information and Communications
Technology competence, social connection, social isolation, Bronfenbrenner’s ecological
systems model, relative deprivation theory, technology readiness and acceptance model
v
Dedication
To all the educators who shape minds, young and old—especially my mother and father. Thank
you.
vi
Acknowledgments
I believe that when you stop learning, you stop living. Here is to learning no matter your
age and embracing knowledge through formal and informal education both inside the classroom
and outside of it.
The road to this point has been slippery and long, and I lost my footing a couple of times.
I owe a debt of gratitude to many people, especially those who stuck beside me and encouraged
me to keep writing and continue working. Sincere thanks to my chair, Dr. Patricia Tobey, and
assistant chair, Dr. Don Murphy; both served as calm and guiding forces amid the chaos. My
classmate, Dr. Ken Schow, the first in our dissertation cohort to successfully defend his study,
became an unexpected lifeline and a dear friend. My dissertation committee, Dr. Briana Hinga
and Dr. Anthony Maddox supported and challenged me to pursue this passion piece, disseminate
the findings, and promote the recommendations. Dr. Christopher Mattson provided timely and
critical feedback, pointed me to helpful resources, and ensured compliance with APA 7
requirements, a language in itself.
Much appreciation goes to Dr. Amy Alamar, Lisa Hurley, Dr. Julia Metcalf, and Julie
Vera; all audited and edited my paper when I could no longer make sense of all the words.
Tiffany Edmonds would regularly check on me and my well-being, and Angela Wentink
referenced Anne Lamott’s Bird by Bird and encouraged me to keep writing, word by word.
Thank you especially to the 15 interview participants who shared their time, perspectives, and
stories and were the heart of my study.
My friends and family all need to be acknowledged for their patience and understanding
when I was largely absent or preoccupied for several years. I also received a great deal of
vii
encouragement and support from co-workers. Needing to walk my canine companion three times
a day helped get me away from hours spent at the computer.
I salute my fellow members of Cohort 13, and especially Drs. Suzie Burns, Octavia
Davis, Jacqueline Dupont, Candace Givens, Pamela Paspa, Catherine Rice, and Diana Sanchez.
These women supported me and each other with kind gestures, encouragement, study sessions,
humor, and whatever else was needed. We all maintained the course through a global pandemic,
a divisive presidential election, civil unrest, an insurrection at the U.S. Capitol building, racial
injustices, Winter Storm Uri, and the introduction of APA 7. May we apply what we have
learned over the past few years about leadership and organizational change in our workplaces
and communities.
viii
Table of Contents
Abstract .......................................................................................................................................... iv
Dedication ....................................................................................................................................... v
Acknowledgments.......................................................................................................................... vi
List of Tables ................................................................................................................................. xi
List of Figures ............................................................................................................................... xii
Background and Importance of the Problem ...................................................................... 3
Purpose of the Study and Research Questions .................................................................... 4
Stakeholder Groups for the Study ....................................................................................... 5
Stakeholder Goals Related to Problem of Practice ............................................................. 6
Overview of Theoretical Framework and Methodology .................................................... 6
Bronfenbrenner’s Ecological Systems Model .................................................................... 7
Relative Deprivation Theory ............................................................................................. 10
Technology Readiness and Acceptance Model ................................................................ 11
Data Collection and Instrumentation ................................................................................ 12
Data Analysis .................................................................................................................... 14
Participating Stakeholders ................................................................................................ 14
Interview Sampling Strategy and Rationale ..................................................................... 15
Definitions......................................................................................................................... 15
Organization of the Dissertation ....................................................................................... 16
Literature Review.............................................................................................................. 16
Aging................................................................................................................................. 17
Ageism .............................................................................................................................. 17
Age Discrimination ........................................................................................................... 19
Artificial Intelligence ........................................................................................................ 19
ix
Elder Abuse and Elder Justice .......................................................................................... 20
Equity ................................................................................................................................ 21
The Digital Divide ............................................................................................................ 21
Digital Inequalities ............................................................................................................ 22
ICT and Older Adults........................................................................................................ 22
Benefits of Older Adults Using ICT ................................................................................. 24
Impacts of Older Adults Not Using ICT ........................................................................... 25
Older Adults and Barriers to Using ICT ........................................................................... 29
Conceptual Framework ..................................................................................................... 33
Summary ........................................................................................................................... 35
Overview of Design .......................................................................................................... 36
Data Sources ..................................................................................................................... 37
Participant Demographics ................................................................................................. 38
Research Question 1 Findings .......................................................................................... 42
Research Question 2 Findings .......................................................................................... 46
Research Question 3 Findings .......................................................................................... 55
Summary of Findings ........................................................................................................ 59
Introduction to Recommendations .................................................................................... 60
Recommendations for Improving ICT for Older Adults .................................................. 60
Bronfenbrenner’s Ecological Systems Model .................................................................. 61
Implementation and Evaluation ........................................................................................ 70
Recommendations for Future Research ............................................................................ 74
Conclusions ....................................................................................................................... 75
References ..................................................................................................................................... 77
Appendix A: Ethics ..................................................................................................................... 103
x
Appendix B: Limitations and Delimitations ............................................................................... 105
Appendix C: Credibility and Trustworthiness ............................................................................ 107
Appendix D: Participating Stakeholders, Sampling Criteria and Rationale ............................... 109
Interview Sampling (Recruitment) Strategy and Rationale ............................................ 109
Appendix E: Information Sheet for Exempt Research ............................................................... 110
Appendix F: Letter to Interview Participants .............................................................................. 112
Appendix G: Interview Protocol ................................................................................................. 113
Appendix H: Theoretical Framework Alignment Matrix ........................................................... 115
Appendix I: Interview Questions ................................................................................................ 116
Appendix J: Participant Demographics ...................................................................................... 118
Appendix K: Disabilities Affecting Use of ICT ......................................................................... 119
Appendix L: Participant Age and Employment Status ............................................................... 120
Appendix M: Types of ICT Used ............................................................................................... 121
Appendix N: How Participants Used ICT .................................................................................. 122
Appendix O: Average Hours ICT Used per Day ........................................................................ 123
Appendix P: Where ICT Skills Were Learned and Perceived Confidence ................................ 124
Appendix Q: Problems Encountered With ICT .......................................................................... 125
Appendix R: Actions Taken When Problems With ICT Are Encountered ................................ 126
Appendix S: Messages to CEOs of Technology Firms .............................................................. 127
Appendix T: Alignment Between Recommendations and Conceptual Framework ................... 130
xi
List of Tables
Appendix H: Theoretical Framework Alignment Matrix 115
Appendix J: Participant Demographics 118
Appendix K: Disabilities Affecting Use of ICT 119
Appendix L: Participant Age and Employment Status 120
Appendix M: Types of ICT Used 121
Appendix N: How Participants Used ICT 122
Appendix O: Average Hours ICT Used per Day 123
Appendix P: Where ICT Skills Were Learned and Perceived Confidence 124
Appendix Q: Problems Encountered With ICT 125
Appendix R: Actions Taken When Problems With ICT are Encountered 126
Appendix S: Messages to CEOs of Technology Firms 127
Appendix T: Alignment Between Recommendations and Conceptual
Framework Alignment
131
xii
List of Figures
Figure 1: Presentation of the Theoretical Framework 10
Figure 2: Presentation of the Conceptual Framework 35
Figure 3: High-Level Example Logic Model 71
Figure 4: Example Logic Model to Implement CEO Pledge 73
1
College-Educated Older Adults and Information and Communications Technology
The problem examined in this dissertation is the difficulty many older adults experience
using Information and Communications Technology (ICT). Selwyn (2004a) described ICT as an
umbrella term that includes computer software and hardware, digital broadcast technologies,
telecommunications technologies, and electronic information resources. For my study, ICT was
limited to high-speed internet, laptop or desktop computers, smartphones, and tablets. As the
researcher, I recognized that connectivity, networks, hardware, software, and speed are required
to make these four types of ICT operate. However, I did not examine any of these other
components to narrow my study’s scope and ensure I focused on older adults and their lived
experiences using the four types of ICT previously stated. My study also sought to understand
the target population’s lived experiences when operating their devices and navigating
applications (apps) and websites. Older adults face challenges using these technologies even if
they do not have cognitive impairments (Malinowsky et al., 2013).
Our lives are intertwined with technology from birth to death, ranging from the simplest
of tools to the most complex technical systems (MacKenzie & Wajcman, 1999). Bijker (2009)
stated that our highly developed and technological culture could not be fully understood without
considering the role of science and technology. Mick and Fournier (1998) described technology
as an enabler of freedom, control, and efficiencies in time and labor. Miller et al. (1998)
produced a forecast for 2025 with expectations from science and engineering that would
fundamentally shape and enable the next stages of the human enterprise. They identified six
areas: genetics, energy, materials, brain, information, and environmentalism.
Technology is a broad term encompassing hardware and software (Williams & Edge,
1996). Malinowsky et al. (2013) described everyday technologies (ET) as devices, machines, and
2
services used to perform everyday tasks at home and away from home. Hayre et al. (2020) listed
smartphones, smartwatches, tablets, computers, and gaming consoles as ET. In a study of 118
older adults who were interviewed and 116 who were observed using ET, Malinowsky et al.
(2013) included ET such as a dishwasher, electric kettle, microwave, radio, and stereo.
Malinowsky et al. found that past experiences with ET influenced whether an older adult chose
to use technology, as did the complexity of the technology’s design.
Ala-Mutka et al. (2008) described Information and Communications Technology (ICT)
as tools such as compact discs (CDs), computers, the internet, and mobile phones that enable
access to information. Francis et al. (2018) found that ICT use can mitigate age-related threats
such as loneliness and isolation. Difficulties in using ICT contribute to various problems,
including loneliness and social isolation (Airola et al., 2020). Research confirms that social
relationships are critical to a human’s survival, especially for older adults (Carr, 2019).
Lee et al. (2019) conducted a loneliness study of 340 community-dwelling adults in San
Diego, CA. The researchers found that self-reported loneliness was more severe in respondents
in their late 20s, mid-50s, and late 80s. A 2020 University of California, San Diego, study found
that 85% of residents living in an independent housing community for older adults reported
moderate to severe levels of loneliness. A 2010 national survey conducted by Knowledge
Networks for the American Association of Retired Persons (AARP), a nonprofit organization
empowering those 50 years and older, found that 35% of the 3,012 survey respondents indicated
they were lonely (Wilson & Moulton, 2010). Loneliness was associated with a perceived lack of
social support and a shrinking network of friends (Wilson & Moulton).
Yi and Hwang (2015) described the condition of social isolation for older adults as one in
which the microsystem surrounding them has become hollow, with a weak support system.
3
Nicholson (2009) reviewed published materials between 1983–2007 on the topic of social
isolation and found five attributes of social isolation:
1. Having a small social network or few social interactions
2. Feeling alone or having a sense of not belonging
3. Having poor or unfulfilling relationships
4. Being alone and not engaging with others
5. Lacking strong bonds and quality social networks
Baecker et al. (2014) cited clear and compelling evidence that adverse health outcomes,
such as vision impairment and incontinence, were associated with a limited social network and
social isolation in older adults. Seyfzadeh et al. (2019) concluded that social isolation is a much
greater concern for older adults than poverty or diseases. Social relationships are the greatest
source of happiness, and marriage is the relationship with the most impact (Argyle, 1987).
Background and Importance of the Problem
Life expectancy in America continues to increase. According to the Centers for Disease
Control and Prevention’s National Center for Health Statistics (2020), life expectancy at birth in
the United States in 2000 was 74.1 years for males and 79.3 for females. Life expectancy at birth
in the United States from 2010–2018 was 76.2 years for males and 81.2 for females. According
to the Federal Forum on Aging-Related Statistics (FIFARS, 2016), by 2030, more than 20% of
the U.S. population will be 65 and older, and almost 9 million will be 85 and older. It is worth
noting that while every continent is seeing life expectancy extend into the 70s, World Bank data
show that longer lifespans are primarily limited to high- and upper-middle-income countries; it is
not a global phenomenon (Hyde & Higgs, 2016).
4
As Americans’ life expectancy continues to grow, an increasing number of older adults
live in physical and social isolation (Wilson & Moulton, 2010). Evidence shows a correlation
between adverse health outcomes for older adults and feelings of social isolation (Baecker et al.,
2014). Social isolation among older adults is considered a significant public health issue and is
recognized as a key social determinant of health (Smith, 2020). Health risks associated with
social isolation are comparable to high blood pressure, obesity, physical inactivity, and smoking
nearly a pack of cigarettes a day (Holt-Lunstad, 2010). Social isolation is a significant predictor
of mortality (Lauder et al., 2004)
Boulton-Lewis et al. (2007) concluded that the quality of life of older people is
threatened by exclusion from an increasingly digital world; isolation will continue to increase as
technology becomes more pervasive. Many older adults face difficulties using ICT, contributing
to social isolation (Airola et al., 2020). The challenges older adults face in using ICT pose a
dilemma when considering how valuable ICT is in building social connections. For these
reasons, it is vital to understand the barriers to using ICT and determine how ICT can be
improved for older adults.
Purpose of the Study and Research Questions
This study examined how older Americans used Information and Communications
Technology (ICT), identified barriers to using ICT, and determined recommendations for
technology companies to improve ICT for older adults. The analysis of interview data focused on
system influences from Bronfenbrenner’s ecological systems model (1979).
The three research questions for the study were as follows:
1. How do older adults use Information and Communications Technology?
5
2. What barriers prevent older adults from using Information and Communications
Technology?
3. What are the recommended practices for technology companies to improve
Information and Communications Technology for older adults?
Stakeholder Groups for the Study
Older adults, identified here as 65 years and above, living independently and without
assistance in the United States were the primary stakeholder group for this study. The age of 65
was chosen because individuals 65 years and older are eligible to receive Medicare, the federal
health insurance program (Medicare, n.d.). Although approximately half of the single homeless
adults in the United States are 50 years or older (Culhane et al., 2013; Hahn et al., 2006), no
unhoused older adults were included in this study. Other stakeholder groups for this study are
technology companies and advocates for older adults.
Samuel (2017) coined the term “older people,” stating that “elderly” is no longer
appropriate for those in their 70s and 80s. Singh and Bajorek (2014) analyzed 20
pharmacotherapy guidelines and found three guidelines defined older adults by chronological
age, whereas the other 17 did not define older adults in any way. Of the three that defined older
adults by chronological age, two described a person 65 years or older as elderly. In contrast, the
other guideline considered a person 75 years and older to be elderly.
The population of aging adults continues to grow. Older adults are, therefore, an
important stakeholder group to study. Singh and Bajorek (2014) described an aging global
population that, according to the World Health Organization (WHO), will double with 400
million people 80 years and older by 2050. According to Kaneda et al. (2020), 21% of Western
and Southern European residents are 65 years and older, compared to only 3% in sub-Saharan
6
Africa. In the United States, the Census Bureau (2018) estimates that by 2030, one in every five
residents will be of retirement age. By 2034, older people will outnumber children for the first
time in U.S. history (U.S. Census Bureau, 2019). Coughlin (2017) predicted that by 2026, more
adult diapers or disposable undergarments would be sold in the United States than baby diapers.
Czaja et al. (2019) stated that today’s generation of older adults differs from past generations.
People are more educated and are working longer and remaining more active and independent.
Coughlin (2018a) conservatively estimated the spending power of the 50-plus group to be $8
trillion overall.
Stakeholder Goals Related to Problem of Practice
This study focused on adults 65 years and older residing independently in America
without daily living assistance. The stakeholder goals of the study were as follows:
● Share their perspectives and experiences using ICT
● Be considered in technology design
● Be included in technology concept testing
● Increase capability to use ICT
● Use ICT as a tool to supplement daily living
● Have opportunities to gain competency in ICT through training and other means
Overview of Theoretical Framework and Methodology
This study was focused on the individual and the system influences that shaped an
individual’s relationship with ICT beginning at a young age through adulthood. The three
research questions were examined through Bronfenbrenner’s ecological systems model (1979),
the relative deprivation theory (Crosby, 1976), and the technology readiness and acceptance
model (Davis, 1989; Parasuraman, 2000).
7
Bronfenbrenner’s Ecological Systems Model
Urie Bronfenbrenner was a developmental psychologist interested in child development.
Bronfenbrenner viewed humans as active participants in their development (Shelton, 2019).
Although Bronfenbrenner was keenly interested in child development, the ecological systems
model is focused on individual development and attempts to understand how the environment
shapes human development (Bronfenbrenner, 1979).
Bronfenbrenner’s ecological systems model (1979) provides a way of understanding
behavior with the individual at the center. Each circle that surrounds the individual represents a
system, and all systems impact and influence one another. The chronosystem represents time.
While Bronfenbrenner’s model was used for child development, it is viewed from birth to older
adulthood in this study.
Bronfenbrenner advocated for public policies that support child and family development,
enabling all children to have the opportunity to grow up healthy and competent. While
Bronfenbrenner is widely known for the ecological systems model, he also was the co-founder of
Project Head Start, which was launched in 1965 and continues to provide nationwide support for
low-income children and their families (Shelton, 2019).
While Bronfenbrenner’s ecological systems model (1979) is one of the most widely
recognized human development theories, the theory has critics. Vélez-Agosto et al. (2017) found
Bronfenbrenner’s view of culture too narrow because it is limited to the macrosystem. Instead,
the researchers argued that culture should be integrated with the microsystem due to its defining
and organizing role. Similarly, Markus and Kitayama (2010) stated that culture is a product of
human activity and is not separate from the individual.
8
Individual Influences
Bronfenbrenner viewed individual development as a process that occurs as the person
ages, creates an understanding of their world, and learns to operate effectively within the systems
they are participating in (Shelton, 2019). For this study, microsystem influences that occurred in
the individual’s formative years were considered. I hypothesized that these experiences
contribute to how an older adult perceives and uses ICT.
Cheeseman Day et al. (2005) found that individuals with more education or income are
more likely to have high-speed internet and a computer than the general population. An
individual’s microsystem influences, such as education and occupation, are closely tied to
technology use. Harris et al. (2013) revealed that nearly all children in affluent communities use
computers at school and home.
Microsystem Influences
A microsystem consists of the relationships, activities, and roles experienced by the
developing person in a given setting (Bronfenbrenner, 1979). Each person experiences a different
and unique microsystem, even if they live in the same household (Shelton, 2019). Backonja et al.
(2014) applied Bronfenbrenner’s theory to explore technology behaviors among older adults.
The microsystem is where the developing person learns, becomes competent, and makes
sense of their environment (Shelton, 2019). Work is part of the microsystem, and exposure to
technology generally occurs at work (Williams & Edge, 1996). Czaja et al. (2019) found that
higher levels of education are associated with higher incomes and better health outcomes and
that older adults with higher education and income levels adopt technology and use the internet
at higher rates.
9
Exosystem Influences
An exosystem affects the developing person but does not actively involve the developing
person. The exosystem influences development by establishing a causal sequence in at least two
processes (Bronfenbrenner, 1979). For this study, examples of exosystem influences are the
community, government, and technology companies. Fransman (2010) advocated for
governments to play a role in monitoring and benchmarking the performance of their new ICT
ecosystem-innovation system.
Selwyn et al. (2003) argued that technology for older people should be at the heart of
social policy and cited three reasons for this. First, technology is intergenerational and can
improve the quality of life for all people. Second, technology can help solve many traditional
problems associated with aging because every aspect of life is touched by technology. Finally,
technology facilitates communication to enable all people to participate as citizens, whether
voting, shopping, or seeking information and services. Technology is pluralistic and preventative
(Selwyn et al.).
Macrosystem/Cultural Influences
Bronfenbrenner’s largest level of the ecosystem is the macrosystem. It is the system
furthest from the individual. The macrosystem consists of societal beliefs, values, practices,
culture, consistencies, patterns, and regularities (Shelton, 2019). Figure 1 provides a visual
representation of Bronfenbrenner’s model with system influences shaping an individual’s
experience and perceptions of ICT.
10
Figure 1
Presentation of the Theoretical Framework
Relative Deprivation Theory
The relative deprivation theory (RDT) has been applied to digital inequalities studies. It
encourages researchers to examine individuals’ opinions and decision-making when interacting
with ICT at home, school, work, and elsewhere. RDT states that before individuals advocate for
access, they must first perceive deficiencies and view the void as problematic (Helsper, 2017).
Crosby’s (1976) egotistical relative deprivation theory stated that the following must occur
before somebody becomes frustrated enough to take action to change their situation:
11
● Observes that a peer possesses digital skills
● Values being able to participate in a digital environment
● Believes they also should possess the skills to participate in a digital environment
● Feels they have the ability to acquire digital skills
Helsper found that individuals will only attempt to obtain resources they are excluded
from if they are valued. Harding (2004) concluded that those most qualified to advocate for the
underserved often are socially positioned within those communities. However, because
underserved populations often lack access to positions of power and tend to be appointed to
government office rather than elected, few powerful voices advocate for resources and services
for underserved populations (Rhinehart & Geras, 2020). Bronfenbrenner’s ecological systems
model (1979) of microsystem, exosystem, and macrosystem influences support the relative
deprivation theory (Crosby, 1976). If the older adult had minimal exposure to ICT, did not have
a positive experience with ICT, or did not see the value in using ICT, they would not advocate
for access.
Technology Readiness and Acceptance Model
The technology acceptance model (TAM) explains and predicts the adoption of
information technology in work settings (Davis, 1989; Davis et al., 1989). TAM assumes that
users’ beliefs about the usefulness of a system and perceptions about the ease of using the system
determine the users’ intention to adopt new technologies (Lin et al., 2007).
Technology readiness (TR) is described as people’s inclination to embrace new
technologies to accomplish life and work goals (Parasuraman, 2000). The TR index (TRI) 1.0
was introduced in 1999 and consisted of a 36-item scale to measure technology readiness across
four dimensions (optimism, innovativeness, discomfort, and insecurity). TRI 2.0 was introduced
12
in 2012 and measured technology readiness across the five segments of skeptics, explorers,
avoiders, pioneers, and hesitators (Parasuraman & Colby, 2015).
As part of the process of developing TRI 2.0, 61 U.S. adults participated in a weeklong
discussion about the underlying motivators to adopt and use new technologies. Participants
identified age, occupation, and education as factors they believed correlated with receptiveness
to new technologies. This feedback was consistent with past technology readiness research
(Parasuraman & Colby, 2015). Age, occupation, and education are aspects of the individual that
are shaped by microsystem influences.
Data Collection and Instrumentation
This study used a convenience sampling approach, and I collected qualitative interview
data from 15 adults 65 years and older; all resided in the United States. The 15 individuals lived
independently, alone, or with others in their homes and not in a care facility. The interview
consisted of 16 open-ended questions and was conducted using Zoom phone (dial-in only) or
video conferencing technology. The University of Southern California (USC) Institutional
Review Board (IRB) restricted in-person data collection due to COVID-19 pandemic concerns.
To identify prospective study participants, I asked classmates and work colleagues to
refer me to individuals who fulfilled the study criteria. Once identified, I followed up with an
email explaining the purpose of the study and proposed possible meeting times. Upon securing a
meeting time, I sent a Google calendar invitation with the Zoom meeting link and an email
thanking the participant in advance for their time. I explained the interview’s purpose and themes
being studied. The communication included my contact information, my dissertation chair’s
email address, and a phone number and email address for USC’s IRB. A few days before the
13
meeting date, I sent a reminder email and included details about the study and the Zoom meeting
link.
Before my first interview occurred, I participated in mock interviews with a classmate via
Zoom. I posed as a study participant and answered questions while he interviewed me, and I
observed him taking field notes and coding. Then we switched roles, and I interviewed him. He
observed me taking field notes, coding, and adjusting the sequence of interview questions based
on his answers and whether he had answered subsequent questions. Additionally, I asked a
family member to test the Zoom dial-in capability for two purposes. The first was to ensure it
was a simple, straightforward process for someone manually dialing the telephone number from
their house phone, for example, rather than clicking a link on their laptop or smartphone. The
second was to confirm that a recording and transcript still were provided when an individual
manually dialed the meeting number. These mock interviews and efforts to test the technology
for various participants helped ensure the experience was smooth for both the participant and the
researcher.
As a final measure to ensure accuracy and trustworthiness, I let the participants know that
I would summarize our discussion and restate the information they had shared with me upon
completing each interview. I asked them to correct any information I may have misinterpreted or
misunderstood. After each member check or participant validation, I asked if I captured the
participant’s answers correctly. The participant responded with affirmation or clarified their
answers as needed.
At the beginning of the interview, I asked for the participant’s permission to record the
conversation. For all 15 participants, upon receiving their verbal consent to record the
conversation, I used the Zoom recording capability and a separate handheld recorder. Two
14
methods of recording were used to ensure there was backup capability in case one method failed.
I recorded memos during the interviews. After completing each interview, I allotted time to
record observations and other field notes.
Data Analysis
After conducting the 15 interviews via phone or video teleconference technology, I
followed a five-step process for analyzing the data per Creswell and Creswell (2018):
● Organized and prepared the data for analysis
● Reviewed the data
● Coded the data
● Generated descriptions and themes
● Determined how to represent the descriptions and themes
The coding process used both a priori codes from the conceptual and theoretical
frameworks and inductive codes from the transcripts. The second phase of coding combined or
related codes. The third phase of data analysis involved identifying patterns and themes related
to the conceptual and theoretical frameworks, three research questions, and 16 interview
questions. I added all 16 interview questions to a table with 15 columns created for each study
participant and used this table while conducting the interviews. Using this table enabled me to
record all field notes and codes in one document.
Participating Stakeholders
All study participants met the following criteria:
● The individual was 65 years or older, a U.S. resident, and was fluent in English
● The individual lived independently and not in a facility requiring care
● The individual was either a low, medium, or high daily user of ICT
15
Interview Sampling Strategy and Rationale
Merriam and Tisdale (2016) stated that the sample size depends on various factors,
including questions to be asked, data gathered, the analysis, and resources available to support
the study. My study employed a purposeful sampling approach targeting those 65 and older and
collected responses from 15 older adults residing in the United States. I relied on a
convenience/network recruitment approach to identify participants. This approach was
appropriate given the COVID-19 pandemic, the target audience, and the finite amount of time I
had to conduct research.
My study used a qualitative approach to gathering data. Qualitative research is “an
approach for exploring and understanding the meaning individuals or groups ascribe to a social
or human problem” (Creswell & Creswell, 2018, p. 4). Furthermore, qualitative researchers “are
interested in understanding how people interpret their experiences, how they construct their
worlds, and what meaning they attribute to their experiences” (Merriam & Tisdell, 2016, p. 6).
All 15 participants were interviewed via phone or video conferencing technology. Due to
the COVID-19 pandemic and the fact that the study investigated barriers to using ICT, I wanted
to offer a simple form of technology for those who do not consider themselves technically savvy.
Definitions
• Ageism is a highly prevalent form of discrimination against older adults that is
generally unchallenged and socially accepted (Cuddy et al., 2005; Levy & Banaji,
2002).
• Confidence is belief in one’s abilities and capabilities (Sheldrake, 2016).
• Elder abuse is harm or distress to an older person within any relationship where there
is an expectation of trust (McAlpine, 2008).
16
• Elder justice is a concern with human rights for older adults (Blancato & Whitmire,
2020).
• Equity is fairness and justice (Lambert, 2007).
• Information and Communications Technology (ICT) are tools that connect people to
resources and each other (Ala-Mutka et al., 2008).
• Motivation is the psychological construct in which individuals and groups choose
behaviors to adopt and maintain (McInerney, 2019).
• Older adults are 65 years and older and are eligible for Medicare, the federal health
insurance program (Medicare, n.d.).
• Social isolation is having few contacts and lacking a sense of belonging (Nicholson,
2009).
Organization of the Dissertation
This research study is presented in the format of an executive dissertation. An executive
dissertation is more commonly used in the business environment than academic settings, and it is
not separated into distinct chapters like a more traditional five-chapter dissertation. The body of
an executive dissertation is shorter than a five-chapter dissertation, and tables are placed in the
appendix. To easily navigate the content, the reader is encouraged to use the table of contents to
find information and corresponding tables.
Literature Review
This literature review examines aging, ageism, artificial intelligence, elder abuse, elder
justice, and equity. Next, the digital divide and digital inequalities are explored. Benefits to using
ICT are explored, as are impacts to older adults not using ICT. Difficulties exacerbated by the
17
COVID-19 pandemic are reviewed. Next, barriers to older adults using ICT and motivations to
use ICT are examined.
Aging
Torres and Hammarstrom (2009) found no consensus on defining, measuring, and
operationalizing successful aging. However, the literature indicates that aging is feared. Fear
stems from beliefs that aging is associated with diminished mental and physical capacity,
disease, and sickness (Samuel, 2017). Unfavorable stereotypes about older adults negatively
affect their physical, psychological, and cognitive health and have been demonstrated in a
decreased will to live, increased reaction to stress, impaired memory, and disinterest in engaging
in healthy, preventive behaviors (Nelson, 2016). Older adults who believed that aging means
getting sick had double the mortality rate as their peers who did not hold those negative
expectations about their health (Stewart et al., 2012). A longitudinal study examining data over
38 years found that older adults who endorsed negative age stereotypes suffered a 30.2% greater
memory decline than their peers who did not believe those age stereotypes (Levy et al., 2012).
Ageism
Ageism is a highly prevalent form of discrimination, and unlike sexism and racism,
ageism is generally unchallenged and socially accepted because of its implicit and subconscious
nature (Cuddy et al., 2005; Levy & Banaji, 2002). The problem of ageism is not a new one, as
Curtin (1972) described an American culture that worships youth and discards the aged,
regardless of their past contributions. America’s disposable and mobile society exacerbates the
problem of ageism. Nancy Gustafson, an aging consultant, explained that the problem is more
social than biological when older people no longer have a recognizable role (Samuel, 2017).
Ageist views are held mainly by young people and result in a bias in the development and design
18
of technology (Ivan & Cutler, 2021). However, some of these ageist views are also held by older
people and result in a reluctance to adopt new technologies and underestimating their
performance and ability to learn technology skills (Beckers et al., 2006). Choi et al. (2020)
analyzed 2016 data from the Health and Retirement Study (HRS) and Research and
Development (RAND) HRS data files, which consisted of 5,914 respondents aged 50 and older.
Responses indicated that greater exposure to ageism is generally related to less use of the
internet.
Visual ageism is a concept introduced by Loos and Ivan (2018). It is a social practice that
visually represents older adults in a prejudiced manner and manifests in underrepresentation or
misinterpretation of older adults in stereotypical or peripheral roles. Ivan et al. (2020) described
visual ageism as a type of institutional discrimination. Ivan et al. advocated for older people to
have visual communication rights and a voice about how they are portrayed.
A 2019 report released by the American Association for Retired Persons (AARP)
Foundation, an advocacy organization focused on Americans 50 years and older, revealed that
80% of people 50 and older believe they are portrayed negatively in the media by marketers and
product developers. Additionally, 62% of those surveyed said they would consider switching to a
brand representing people their age (AARP, n.d.).
Many images of older adults in the media are based on stereotypes and show older adults
as dependent, socially isolated, and a burden to society. To address this, AARP partnered with
Getty Images to launch The Disrupt Aging Collection, a library of more than 1,400 curated
images. According to AARP, the photos were selected to more accurately portray how people
age in today’s society (AARP, 2019).
19
Age Discrimination
Older workers are underrepresented in the tech industry, and this has been attributed to a
combination of age discrimination and a need to reskill older workers. According to a study of
18 technology firms (Payscale, 2020), only IBM, Oracle, and Hewlett Packard had a median
employee age over 33. The median age in seven of the 18 companies was 30 years or younger.
These numbers compare to other industries in the United States, where the median age is 42.3
years (Dilven, 2021). In 2020, BCS, The Chartered Institute for IT, reported that in the United
Kingdom, only 22% of people working in IT roles are older than 50 (Hughes, 2021).
Additionally, there were 13,000 unemployed IT specialists in the United Kingdom over
age 50. This number equates to an unemployment rate of 3.4%, much higher than the 2.2%
unemployment rate for IT specialists between 16–49 years (Hughes). McNamara and Williamson
(2019) found that age discrimination poses further hardships because older adults lack retirement
readiness. Several studies found that up to one-third of workers approaching retirement age
would live in poverty or near poverty if they relied only on retirement savings and other assets
(Ellis et al., 2014; Ghilarducci & Saad-Lessler, 2015).
Artificial Intelligence
Artificial intelligence (AI) uses technology to act and think humanly and to think and act
rationally (Mueller & Massaron, 2018). AI also has been used to study natural language patterns
and emotions in speech to detect loneliness in older adults (Talking alone, 2020). Home
technologies using apps, robots, and sensors support independent living among the older
population (National Science and Technology Council, 2019). AI machinery is built through a
combination of logic, mathematics, and computer science (Brighton & Selina, 2012). Marvin
Minsky, considered a founding father of AI, described the AI problem as one of the most
20
complex science has undertaken because it has one foot in science and the other in engineering
(Brighton & Selina). AI will increasingly be a technology solution in the years to come, and
Hans Moravec, a roboticist, predicted in detail the next four generations of robots and said that
robot intelligence will exceed human intelligence well before 2050 (Brighton & Selina). “The
new machines are exceeding human performance…as they merge with us more intimately and
we combine our brain power with computer capacity to deliberate, analyse, deduce,
communicate and invent” (Sanders & Gegove, 2013, p. 191).
The MIT AgeLab’s AI & Longevity study collected insights from 911 adults and
revealed a general belief that AI is beneficial, especially in healthcare and caregiving
applications. The same participant group also viewed AI as risky in specific domains. These
varying opinions emphasize the importance of greater public education on AI and its potential
benefits (MIT Age Lab, n.d.).
Verizon and Google Cloud announced a pilot program in July 2020 using conversational
AI to help customer service agents and consumers. The program eliminates menu prompts and
option trees and relies on natural language recognition technologies. Millions of Verizon’s
anonymized historical support logs power their machine learning model (Verizon, 2020).
Elder Abuse and Elder Justice
The World Health Organization (WHO) defined elder abuse as harm or distress caused to
an older person in any relationship where there is an expectation of trust (McAlpine, 2008). The
harm or distress may be through a single or repeated act or lack of appropriate action
(McAlpine). Elder abuse, neglect, and exploitation (e.g., financial, sexual, and psychological) are
nondiscriminatory and occur in all socioeconomic groups, including the wealthy (Alford, 2011).
Brinig et al. (2004) cited increasing levels of elder abuse in the United States over 20 years, with
21
47 states reporting 242,430 investigations of domestic elder abuse. Brinig et al. predicted that by
2020, with 18% of the population 65 years and older, the cases of elder abuse incidents would
continue to rise. Blancato and Whitmire (2020) described elder justice as a human rights issue
for older adults. The researchers found that 10 years after the passage of the 2010 Elder Justice
Act, elder abuse, neglect, and exploitation still lack the necessary political support to prioritize
action.
Equity
Equity is described as fairness and justice (Lambert, 2007). Vertical equity refers to
treating those with varying needs differently and appropriately (Lambert). Where there are
resources, benefits, or services to be received, there are inequities, including access to these
resources. Generational equity refers to the concept that the elderly may be receiving more of
their share and depriving children and younger adults (McNamara & Williamson, 2019).
Achieving health equity among older adults requires looking at clinical care and the medical
system and the influences of societal, political, economic, social, behavioral, and biological
determinants of health inequities (Lincoln, 2016).
The Digital Divide
The term digital divide first became widely known when used in a 1995 U.S. Department
of Commerce report titled Falling through the Net: A Survey of the Have Nots in Rural and
Urban America (Lu, 2001). The digital divide describes the gap between Americans who have
access to information technology and those who do not (Eubanks, 2012). Czaja et al. (2007)
revealed an age-based digital divide in which the lowest number of internet users were those 65
and older. The digital divide also represents inequalities between those with and without access
to the internet (Hoffman et al., 2000). Studies from the past two decades have shown that uneven
22
access to digital resources reflects a more significant issue of societal inequalities;
socioeconomic status determines access to many resources, including technology (Dijk, 2005;
Hargittai & Walejko, 2008).
Digital Inequalities
Most digital inequalities research focuses on absolute deprivation, with fixed levels of
internet connection speed, skill, and engagement as digital inclusion indicators. Helsper (2017)
argues that relative deprivation must be considered; focusing only on absolute deprivation is a
mistake given technology’s rapidly changing pace. According to Eubanks (2012), technology
policymakers have wrongly focused on the fair distribution of high-tech tools and incorrect
assumptions. These myths include the following:
1. Low-income earners lack technology tools
2. Technology training results in sustainable employment
3. Women, in comparison with men, are reluctant to engage with complex technological
systems
Eubanks (2012) argues that access is only one component of the high-tech equity puzzle and that
combatting inequalities of the information age requires consideration of matters such as
institutional discrimination, health and safety issues, environmental injustice, and privacy rights.
Excluding older adults from information technology has been identified as an issue in many
studies (Cameron et al., 2001; Scott, 1999a, 1999b; Steinberg et al., 1999; Tay, 2001).
ICT and Older Adults
Information and Communications Technology are tools that connect people to resources
and each other. Ala-Mutka et al. (2008) described ICT as the tools that enable access to
organized courses and informal learning, including CDs, computers, the internet, and mobile
23
phones. ICT is used to access, manage, create, and communicate information and includes
technologies not yet developed and those already in existence, such as computers, networking
systems, handheld digital devices, digital cameras, and camcorders (National Assessment
Governing Board, 2014).
Over the past 20 years, many analysts and governments have offered compelling
evidence of ICT’s role in transforming countries into knowledge economies and network
societies (Castells, 1996a, 1996b, 1996c). Friedman (2009) believed that humans working in
partnership with technology were better off than those who did not. Senkbeil (2017) stated that
ICT literacy or competency is necessary to participate in society successfully.
Ogozalek (1991) cited numerous studies that show older adults generally have positive
attitudes toward computer technology and that these adults are capable users of this technology.
Culen (2015) conducted six in-depth interviews with older adults and found that none feared or
disliked new technology. However, two participants expressed a desire to live a life with as little
technology as possible. Nygård (2006) provided a different perspective and concluded that
technology might be a hindrance and a hazard for older adults. Birkland (2019) identified five
ICT user types among older adults ranging from those excited to use ICT to those fearful of ICT.
The five types are as follows:
1. Enthusiasts who view ICT as fun and toys.
2. Practicalists who consider ICT to be functional tools.
3. Socializers who see ICT as a connector to others.
4. Traditionalists who yearn for tradition and prefer ICT from the past.
5. Guardians view ICT as potentially negative.
24
Benefits of Older Adults Using ICT
Convenience
Backonja et al. (2014) proposed that technology use can promote a healthier world for
older adults by addressing significant health promotion changes, disparities, and natural
disasters. Telephones and computers can, in many cases, take the place of in-person
appointments (Greenberger & Puffer, 1989; Vaughn et al., 1984). Technology is considered an
essential solution to reducing health care costs and improving older adults’ quality of life
(Ogozalek, 1991).
Social Connections
Fuss et al. (2019) found that older adults who use computer-mediated communication
benefit through a sense of social connectedness and perceived social support. Holt-Lunstad et al.
(2010) observed that the quality and quantity of individuals’ social relationships were linked to
mental health, morbidity, and mortality. Across 148 studies involving 308,849 participants, there
was a 50% increased chance of survival for individuals with stronger social relationships.
Rokach (2019) concluded that technology and relationships could enhance life experiences,
whereas when technology replaces relationships, the result may be physical and emotional
suffering. Phones enabled connections across countries, although they also distracted people who
were focused on their phones when in others’ presence (Culen, 2015) and were associated with
low self-confidence and poor social skills among those who used their phones excessively
(Dayapoglu et al., 2016).
Tools to Participate in Society
Ample evidence exists that excessive internet and technology use can be problematic and
lead to addiction and other long-term adverse effects (Caplan, 2005; Dayapoglu et al., 2016;
25
Kardaras, 2016; Mok et al., 2014). High internet use was associated with a small but statistically
significant increase in depression and loneliness and decreased social engagement (Clay, 2000).
Conversely, findings also show that using the internet, especially social network sites, is strongly
associated with increased community engagement, access to political information, and
heightened public activity (Hampton, 2011; Hampton et al., 2011). Barnett and Adkins (2001)
found that older adults want to be recognized, included, and competent in information
technology; these attributes contribute to their feelings of self-esteem and inclusion.
Impacts of Older Adults Not Using ICT
Exclusion From Activities
The inability to manage technologies in everyday life can be a risk for older adults by
excluding them from home and social activities (Malinowsky, 2010). An international literature
review of old-age social exclusion uncovered under-developed research in six domains:
neighborhood and community services; amenities and mobility; social relations; material and
financial resources; civic participation; and socio-cultural aspects (Walsh et al., 2017). Exclusion
also occurs if a person’s digital skills remain static rather than continue to develop along with
new technology (Helpser, 2017).
Inability to Access Resources
As everyday life becomes increasingly dependent on the internet, people who do not use
the internet likely will become more disadvantaged and disenfranchised (McDonough, 2016).
The Medicare Prescription Drug, Improvement, and Modernization Act of 2003 encouraged
older adults to use the internet to manage their account information online. Instead, the act
excluded many Americans from accessing vital health information (Wright & Hill, 2009).
Additionally, difficulties in using technologies such as ATMs may prohibit older adults from
26
living independently (Rogers & Fisk, 2000). Lam et al. (2020) estimated that among the 13
million older adults in the United States, 38% of them are not ready for telemedicine or video
visits, mainly due to inexperience with technology. The COVID-19 global pandemic accelerated
digital connections with Mayo Clinic patients in Phoenix, AZ (Mayo Clinic, 2021). Before the
COVID-19 pandemic, telemedicine was primarily used in rural areas in AZ and numbered less
than 500 digital connections a day. That number rose as high as 8,000 telemedicine visits per
day, with highly favorable survey feedback from patients and providers (Mayo Clinic).
Social Isolation
Nicholson (2009) defined social isolation as having few contacts, not having a sense of
belonging, lacking fulfilling relationships, and an inability to engage with others and establish
fulfilling relationships. Hawkley and Cacioppo (2010) described loneliness as distress resulting
from discrepancies between desired and actual social relationships. Compared to those with
strong social networks, those who live alone are prone to higher physical and mental illness
(Argyle, 1987; Cacioppo et al., 2003; Kiecolt-Glaser et al., 1984; Lynch, 1979; Myers, 1992). In
every U.S. census from 1970 to 2000, 73–77% of single-person households were occupied by
females aged 65 and over (Hobbs & Stoops, 2002).
It cannot be assumed that living alone results in social isolation. In a study of 13
European countries, Banks et al. (2009) found that overall, individuals living in single-person
households were no more likely to experience severe isolation such as combined social and
familial isolation than those living with others. Furthermore, age was positively associated with
the frequency of socializing, religious participation, and volunteering (Cornwell et al., 2008).
Adams and Blieszner (1995) found that gerontological literature assumes that having friends and
family relationships is better than not having them. For some individuals, social isolation is a
27
choice that protects them from emotional pain that may have come from being interpersonally
rejected (DeWall et al., 2006). While social isolation may be better for some older adults,
significant evidence shows that social isolation and loneliness are harmful. Worldwide, suicide is
a severe social and public health concern (Ra & Cho, 2013). In 2014, one-third of South Korea’s
suicides were among individuals 60 years and older (Yoon & Cummings, 2019).
Seyfzadeh et al. (2019) concluded that older adults’ social isolation is a much greater
concern than poverty or diseases. Baecker et al. (2014) cited clear and compelling evidence that
limited social networks and social isolation led to adverse health outcomes such as vision
impairment and incontinence in older adults. U.S. Surgeon General Vivek Murthy said that
loneliness reduces a lifespan comparable to the damage caused by smoking 15 cigarettes a day
(Finnegan, 2017).
Difficulties During a Global Pandemic
Stay-at-home orders implemented to protect people during the COVID-19 pandemic have
had a particularly harmful impact on older adults due to social isolation (Ory & Smith, 2020).
Krendl & Perry (2021) found that the pandemic caused immediate negative impacts on older
adults’ mental health and social well-being. Smith (2020) introduced the COVID-19 Social
Connectivity Paradox, which suggests that the same measures that protect older adults from
contracting COVID-19 may be causing social isolation and harming them. Before the COVID-19
global pandemic, national studies revealed that nearly 25% of older Americans were socially
isolated and about 33% of middle-aged and older adults experienced loneliness (Ory & Smith).
The University of Exeter and King’s College London studied more than 3,000 people aged 50
years and older and found increased feelings of loneliness and depression during lockdown
(University of Exeter, 2021). The University College London conducted a COVID-19 social
28
study in which more than 70,000 U.K. adults (18 years and older) were surveyed weekly and
then monthly, beginning in March 2020. The study revealed that those who had higher quality or
more frequent face-to-face or video calls reported fewer symptoms of depression (Sommerlad et
al., 2021).
Efforts have been organized across the United States to promote social interaction with
older adults during the pandemic. Examples include biweekly Senior Care Calls in Plano, TX,
and volunteers who helped older adults by making social calls, running errands, and helping with
technology questions through the Mon Ami app (Padilla, 2020). To facilitate video conferencing
and chat capabilities between nursing home residents with restricted visitation and loved ones,
New Mexico’s Aging and Long-Term Services Department purchased 350 tablets and distributed
them to licensed nursing facilities across the state. The New Mexico Health Care Association
purchased and distributed an additional 140 tablets to nursing home facilities (The State of New
Mexico, 2020).
Even though older adults were among the first to be eligible to receive COVID-19
vaccines, accessing appointments was problematic for many people 65 years and older. A
significant reason for the challenges was that the rollout primarily was dependent on technology.
“You can’t have the vaccine distribution be a race between elderly people typing and younger
people typing. That’s not a race; that’s just cruel,” said Jeremy Novich, a clinical psychologist
based in New York City who launched an effort to help older adults navigate the technology to
schedule vaccine appointments (Stone, 2021). Bill Johnston-Walsh, the state director of AARP
Pennsylvania, referenced a survey sent to their members. Within 24 hours, they heard from
thousands of upset respondents who expressed confusion and frustration about the sign-up
process. He explained that of those 65-plus, their time on computers is focused on making video
29
calls with their grandchildren or playing games. They are not online navigating the internet and
cannot easily access services (Chinn & Yu, 2021).
Victoria, an 81-year-old living in Montgomery County, PA, called WHYY-FM’s Health
Desk Help Desk and left a message describing her difficulty signing up for a vaccine
appointment because she did not have a computer. She said, “I’ve been trying for a month, and I
never found a place to register. I wish it was a little simpler to do. I don’t think I’m senile. I can
follow instructions” (Chinn & Yu).
Older Adults and Barriers to Using ICT
With many proven benefits to ICT, it is essential to examine barriers to access and use.
Selwyn (2004b) reported that age is highly significant in determining whether individuals can
access and use ICT. Ala-Mutka et al. (2008) found that ICT tools may not be user-friendly for
older adults with physical limitations or low ICT skills. These difficulties may discourage older
adults from learning how to use ICT.
Access and Exposure
Survey data from a randomized sample of 1,001 adults showed that age is highly
significant in determining ICT use and access (Selwyn et al., 2003). In terms of exposure to
technology, many of today’s older adults left school and the workplace before IT was widely
used (Irizarry & Downing, 1997; Rosen & Weil, 1995). The workplace was the first setting to
see a widespread societal application of information technologies (Williams & Edge, 1996).
Affordability
Inequalities in socioeconomic status are a factor that limits access to ICT. This finding is
accurate for the general population and older adults (Hunsaker & Hargittai, 2018). Couldry et al.
(2018) concluded that the distribution of media resources is skewed toward wealthy nations and
30
regions and that poor, marginalized groups are largely excluded from accessing these resources.
Anderson et al. (1997) stated that information elitism still exists. Unless concerted efforts are
taken to provide all citizens with access to technology and knowledge about computers and
email, information “have-nots” will be left further and further behind.
Poverty among older adults is prevalent, especially among ethnic minorities, with about
25% of African Americans, Hispanics, and Native Americans living below the poverty line
(Dychtwald & Flower, 1989). Vogels (2021) found that high-speed internet affordability is a
prohibitive factor for Americans earning less than $30,000 annually. Of survey respondents in
this low-income bracket, 43% did not have home broadband services, and 41% did not own a
computer. This finding contrasted with households earning more than $100,000 annually; 63% of
adults indicated having both home broadband services and multiple devices with which to
connect to the internet.
One foundational concept of occupational justice is inclusivity; people are appropriately
supported to participate in occupation (Hocking, 2017; Townsend & Wilcock, 2004).
Occupational justice theory has highlighted systematic injustices that impact older adults’ access
to ICT, namely those with cognitive impairments. Occupations that require the use of everyday
technology may exclude older adults with cognitive impairments (Kottorp et al., 2016).
ICT Design for Older Adults
Coughlin (2018a) referred to the 65-plus population as the longevity economy; generally,
a wealthier, more highly educated, and more discerning group than the same group in previous
generations. The Administration on Aging funding the Education in Aging for Scientists and
Engineers (EASE) Program concluded that older consumers must be considered in the design of
technology products (Holstein, 1987). When developing new products, technology companies
31
must factor in the changing cognitive capabilities of older adults (Holt & Morrell, 2002; Rogers
& Fisk, 2000). When an individual’s capabilities change and technology changes, there may be
undesirable product interactions (Czaja et al., 2019). Conditions such as arthritis may make using
a computer mouse or a trackball difficult for older adults (Czaja & Lee, 2002). Changes in visual
and auditory perceptions, motor skills, and cognitive abilities also must be considered in
interface design (Culen & Bratteteig, 2013).
While many older adults experience a decline in physical and cognitive abilities,
designers must resist the temptation to view them in a stereotypically negative way, for example,
frail and confused. Mitzner et al. (2010) conducted 18 focus groups, each comprising four to nine
older adults ranging in age from 65–85. The majority of participants expressed significantly
more likes than dislikes when asked about technology and perceived the benefits to outweigh the
costs. Older adults are not a problem to be solved. Instead, technology companies must solve
older adults’ problems from a consumer perspective (Coughlin, 2018b).
Lack of Training
Sheldrake (2016) defined confidence as beliefs in one’s abilities and capabilities. Age-
related impairments can result in a loss of confidence (Zajicek, 2004). Studies have shown that
older adults experience difficulties mastering new technology due to low confidence in their
abilities rather than memory difficulties (Marquie et al., 2002).
Barnett and Adkins (2001) conducted a qualitative case study over a six-month period
that involved 17 participants between 61–82; all were computer club members who lived
independently and were in good health. A tutor showed the club members—including some
individuals with arthritic fingers—how to use a mouse, navigate search engines, browse the
internet, mark sites as favorites, and create an email account. The tutor calmly repeated processes
32
that had been forgotten and reassured computer club members when necessary. Club members
responded well to repetition and patience.
Older Adults’ Motivation to Use ICT
Culen (2015) and McInerney (2019) defined motivation as the psychological construct in
which individuals and groups choose behaviors to adopt and maintain. Reeve (2016) described
motivation as wanting change based on prior experience and learning and forward-looking
exploration. There are three components of motivational outcomes—the direction, intensity, and
persistence of effort (Kanfer, 1990). Emotions impact learning and motivation (Münchow &
Bannert, 2019). Czaja et al. (2006) found that older adults’ use of ICT is primarily motivated by
their experience and that motivation amongst older adults differs in comparison to other age
groups.
In a study of 352 adults 60 years and older, Selwyn et al. (2003) found that using a
computer was an activity highly stratified by gender, age, marital status, and education. The
researchers also found that the non-use of computers was due to perceptions of low relevance
and relative advantage. Szabo et al. (2019) discovered in a longitudinal study that older adults
participate online for three primary reasons: social (e.g., connecting with family and friends),
instrumental (e.g., banking), and information (e.g., accessing health information and conducting
research).
Davis’s (1989) technology acceptance model (TAM) suggests that individuals use
technology based on perceived usefulness and ease of use (Porter & Donthu, 2006). In a
qualitative study involving six active older adults who lived alone and had no significant health
challenges, four participants had smartphones. All either owned a desktop or laptop computer or
33
a tablet. None had strong positive or negative feelings about technology, but most preferred face-
to-face connections
Conceptual Framework
The theoretical foundations for this study's conceptual framework were Bronfenbrenner’s
ecological systems model (1979), relative deprivation theory (Crosby, 1976), and the technology
readiness and acceptance model (Davis, 1989; Parasuraman, 2000). Bronfenbrenner viewed
humans as active participants in a world in which reciprocal relationships exist between five
interrelated systems (Shelton, 2019):
• Microsystem
• Mesosystem
• Ecosystem
• Macrosystem
• Chronosystem
The relative deprivation theory (Crosby, 1976) and the technology readiness acceptance model
(Davis, 1989; Parasuraman, 2000) are used to explain the relationship older adults have with
ICT, whether they are active users or see limited value in becoming fluent in ICT.
The ecological systems model is considered a viable framework for research and
dissemination in qualitative, quantitative, and mixed-methods studies (Onwuegbuzie et al.,
2013). U.S. health-related organizations such as the Centers for Disease Control (2021, January
28) and the Pediatric Policy Council (Cheng et al., 2020) have used the ecological systems model
for research and interventions. Eriksson et al. (2018) found that published papers within the field
of mental health that considered the interactions between Bronfenbrenner’s systems resulted in
the most useful recommendations to guide public policy and practice.
34
A conceptual framework presents ideas, variables, and key factors and presumes
relationships (Miles & Huberman, 1994). Jabareen (2009) described a conceptual framework as
interlinked concepts that comprehensively explain a phenomenon. In the conceptual framework
for this study, the individual is shown at the center. The placement of the individual at the center
is consistent with Bronfenbrenner’s ecological systems model (1979). The text in the white
circles surrounds the three research questions, which are shown in the gray circles. The text
appearing in the white circles represents possible microsystem, exosystem, and macrosystem
influences. These influences might explain why older adults use ICT, the ICT barriers they
encounter, and recommended practices for improving it. The diagram also indicates the factors
correlated with the relative deprivation theory (Crosby, 1976) and the technology readiness
acceptance model (Davis, 1989; Parasuraman, 2000). Figure 2 presents the conceptual
framework for this study.
35
Figure 2
Presentation of the Conceptual Framework
Summary
The literature provided ample evidence of the importance of the problem and the need to
understand the relationship between older adults and ICT. Americans are living longer, and an
increasing number of older adults are living alone, some in physical and social isolation (Wilson
& Moulton, 2010). Baecker et al. (2014) reported a correlation between adverse health outcomes
for older adults and feelings of social isolation. Smith (2020) indicated that social isolation
36
among older adults is a significant public health issue and is a key social determinant of health.
The evidence validates the importance of this study.
Overview of Design
This qualitative field study aimed to understand system influences and environmental
forces that explain older adults’ relationship with ICT. The theoretical foundations for the
study’s conceptual framework were Bronfenbrenner’s ecological systems model (1979), the
relative deprivation theory (Crosby, 1976), and the technology readiness and acceptance model
(Davis, 1989; Parasuraman, 2000). This study explored how these systems influence older
adults’ perceived value and utility of ICT and their willingness to learn and adopt new
technology. To gather data, I conducted interviews with 15 adults ranging in age from 65 to 87.
The following three research questions guided this study:
1. How do older adults use Information and Communications Technology (ICT)?
2. What barriers prevent older adults from using ICT?
3. What are the recommended practices for technology companies to improve ICT for
older adults?
I used a convenience sampling approach to identify 15 study participants who were 65
and older and lived independently and not in a care facility. I sought a diverse participant pool
relative to age, gender, race, geography, and varying experience levels of using ICT. In addition
to answering the three research questions, I wanted to understand and share the experiences and
life histories of these 15 individuals.
Between June 25 and July 2, 2021, I conducted 15 interviews. Twelve of 15 interviews
used Zoom videoconferencing technology with video and audio; one interview used Zoom
technology without the camera because the participant could not turn it on. Two of the 15
37
interviews were completed by phone using the Zoom dial-in number due to difficulties accessing
the Zoom meeting link. The interviews varied in length from 25 minutes to 60 minutes; the
average length of the interviews was 30 minutes.
The interviews consisted of 16 open-ended questions (Appendix I). Seven questions
asked personal demographic information; six pertained to ICT use and barriers, and two focused
on recommended practices for improving ICT. A final closing question asked the participants if
there was anything else they wanted to cover.
Data Sources
Upon completing the 15 interviews, I followed Creswell and Creswell’s (2018) five-step
process for analyzing the data. I referred to field notes and the Zoom interview transcripts and
then took the following steps:
● Organized and prepared the data for analysis
● Reviewed the data
● Coded the data
● Generated descriptions and themes
● Determined how to represent the descriptions and themes
The coding process used both a priori codes from the conceptual and theoretical
frameworks and inductive codes from the transcripts. The second phase of coding combined or
related codes. The third phase of data analysis involved identifying patterns and themes related
to the conceptual and theoretical frameworks, three research questions, and 16 interview
questions.
38
Participant Demographics
All participants were assigned a pseudonym to protect their confidentiality. Ten of the
participants identified as female and ranged in age from 65 to 85. Five of the participants
identified as male and ranged in age between 67 and 87. Ten of the participants were white, and
five were people of color. Of the people of color, one participant was Asian, two were Black, and
two were Hispanic. Although education was not part of the participant criteria, these 15
individuals all were college-educated. Four of the participants received bachelor’s degrees, eight
held master’s degrees, and three earned doctoral degrees. Appendix J shows the demographic
information for all 15 study participants.
Despite most of the interview participants being fully retired, all remained very active,
whether they were helping to care for parents or grandchildren, exercising, working on their
hobbies and passion projects, or taking online and in-person classes. Grace, who earned a
bachelor’s degree in English literature and African American studies, recently finished her first
novel, a 261-page story based on tales from her grandfather working on the railroad and his
journey from Mississippi to California. Michael co-founded an organization in the early 2000s
and remained involved as a member of the organization’s board of directors. Additionally, he
served on another board and took classes at the Osher Lifelong Learning Institute, something he
has done for some time.
Of the 15 participants, 13 were retired. The two individuals who worked were Petra and
Rae. Petra held a part-time job, and Rae worked full-time. Appendix L shows the age and
employment status of the interview participants.
Following is a brief description of each interview participant. The information provides
pertinent information on each person, including age, race, gender identity, work status, state of
39
residency, education, disability status, types of ICT used, and self-assessed confidence level
using ICT.
Ava
Ava was a retired 76-year-old white female who resided in Texas. She earned two
master’s degrees and lived with others. She did not have any disabilities that affected her use of
ICT. Ava used a laptop computer, the internet, and a smartphone; she did not use a tablet. When
it comes to technology, Ava said, “I am confident with the tools I know, but I am not very
confident in general. I don’t try new things.”
Belle
Belle was a retired 75-year-old white female who resided in Texas. She earned a master’s
degree and lived with others. Belle indicated that she had dyslexia and attention deficit disorder
(ADD), and that the learning difference and condition affected her use of ICT. Belle said that due
to ADD, she could not recall more than three instructions at a time. She used a laptop computer,
the internet, and a smartphone. Belle said she was not confident when it came to using ICT.
Corinne
Corinne was a retired 85-year-old Asian female who resided in California. She earned a
bachelor’s degree and lived alone. She stated that eye strain and hearing difficulties affected her
use of ICT. Corinne used a laptop computer, the internet, a smartphone, and a tablet. She said she
was not confident in using ICT.
David
David was a retired 84-year-old white male who resided in Texas. He earned a doctorate,
lived with others, and had a hearing disability. David used a desktop computer, the internet, and
a smartphone. He reported confidence with ICT and “no difficulties.”
40
Emmett
Emmett was a retired 75-year-old white male who resided in Texas. He earned a
bachelor’s degree and lived with others. He did not have any disabilities that affected his use of
ICT. Emmett used a desktop computer, the internet, and a smartphone. He described himself as
confident in using ICT.
Grace
Grace was a retired 77-year-old Black female who resided in California. She earned a
bachelor’s degree and lived alone. She did not have any disabilities that affected her use of ICT.
Grace used a desktop computer, the internet, a smartphone, and a tablet. She indicated that when
she interacted with ICT, she was “confident with familiar tasks.”
Griffon
Griffon was a retired 67-year-old white male who resided in Texas. He earned a
bachelor’s degree and lived alone. He did not have any disabilities that affected his use of ICT.
Griffon used a desktop computer, the internet, and a smartphone. He described himself as
confident with ICT.
Kelly
Kelly was a retired 69-year-old white female who resided in California. She earned a
master’s degree and lived with others. She did not have any disabilities that affected her use of
ICT. Kelly used a desktop computer, the internet, a smartphone, and when traveling, a tablet. She
was confident with ICT until something unplanned happened. Kelly said, “When something goes
wrong, it throws me for a curve because I don’t understand how it works. I problem-solve other
issues, but not technology.”
41
Margot
Margot was a retired 74-year-old white female who resided in the District of Columbia.
She earned a Juris Doctor degree and lived with others. She did not have any disabilities that
affected her use of ICT. Margot used a desktop and laptop computer, the internet, and a
smartphone. Her confidence level with ICT was varied. When Margot worked on Microsoft
Word documents, she was very confident. The same was true when “things go well. When
unexpected things happen,” said Margot, “I’m not confident.”
Mia
Mia was a recently retired 69-year-old Black female who resided in California. She
earned a master’s degree and lived with others. She did not have any disabilities that affected her
use of ICT. Mia used a laptop computer, the internet, and a smartphone. In describing her
confidence with ICT, she said, “I am confident in those things when I know what I’m doing,
which is very little.”
Michael
Michael was a retired 87-year-old white male who resided in the District of Columbia.
He earned a Juris Doctor degree and lived with others. His hearing disability affected his use of
ICT. Michael used a laptop computer, the internet, and a smartphone. He described his
confidence with ICT as “somewhere between not confident and confident.”
Petra
Petra was a 66-year-old white female who worked part-time and resided in Utah. She
earned a master’s degree and lived with others. She was diagnosed with attention deficit
hyperactivity disorder but said it did not interfere with her ability to use ICT. Petra used a laptop
42
computer, the internet, a smartphone, and a tablet. She described herself as very confident with
ICT.
Rae
Rae was a 73-year-old white female who worked full-time and resided in the District of
Columbia. She earned a master’s degree and lived alone. Rae did not have any disabilities that
affected her use of ICT. She used a laptop computer, the internet, a tablet, an Apple smartphone
for work, and an Android smartphone for personal use. Rae described herself as very confident
in using ICT.
Ryan
Ryan was a retired 81-year-old Hispanic male who resided in Texas. He earned two
master’s degrees and lived with others. He did not have any disabilities that affected his use of
ICT. Ryan used the internet, a smartphone, and a tablet; he rarely used his laptop computer. He
described himself as confident with ICT.
Umi
Umi was a retired 65-year-old Hispanic female who resided in California. She earned a
master’s degree and lived with others. Umi said she had glaucoma, which affected her ability to
use ICT. She used a laptop computer, the internet, a smartphone, and a tablet. Umi described
herself as very confident on the phone, confident on her tablet, and not very confident on her
laptop, although she knew how to accomplish what she needed to do.
Research Question 1 Findings
Research Question 1 asked how participants used ICT, specifically desktop or laptop
computers, the internet, smartphones, and tablets. These four types of ICT were studied because
they were everyday tools when this study was conducted. I intentionally excluded the vital
43
components that support ICT, such as connectivity, networks, hardware, software, and speed.
While these components are essential to understanding technology, this study was focused on
older adults and their lived experiences using these four types of ICT. In analyzing the data
associated with Research Question 1, three themes emerged:
1. Older adults use multiple types of ICT.
2. ICT connects older adults to others and information.
3. Older adults are becoming dependent upon ICT.
Older Adults Use Multiple Types of ICT
Six of 15 participants used all four ICT types examined in this study. All participants
used more than one type of ICT, all had broadband internet in their homes, and all owned a
smartphone. Fourteen of 15 used a computer, and seven of 15 used a tablet. Griffon mentioned
he bought a tablet when they first were introduced to consumers but “didn’t see the usefulness
for it because phones kind of caught up with tablets.” Petra used all the ICT devices featured in
this study and said she primarily used her mobile phone for texting, checking the news, and
email. Emmett said, “I use a desktop computer and my iPhone. I prefer the desktop [computer] if
I’m really doing some serious stuff.” Umi explained:
I use my laptop for Zoom meetings, classes, and to print important paperwork. I use my
iPad in bed to read CNN articles and the Chronicle [online newspaper]. For everyday
social communication, just keeping in touch and texting people, I use my phone.
The data indicated that all 15 participants used multiple types of ICT. They used a
minimum of three of the four ICT types studied in this research project. Appendix M shows
participant usage of desktop or laptop computers, the internet, smartphones, and tablets.
44
ICT Connects Older Adults to Others and Information
All 15 participants used ICT to connect to others and access information. The participants
all used smartphones to make calls and connect to others. Fourteen of the 15 said they used their
smartphones for texting. Eleven of the 15 used their ICT for videoconferencing, for example,
Apple FaceTime and Zoom. Eleven of the 15 said they used ICT to read and send emails. Ryan
said:
My iPhone is to try to maintain communication, you know, to check my emails, etc.
Every day I send my pictures to my wife and four kids from my iPad. We have a group
chat set up, and I select pictures from today’s date and send them pictures taken on the
same day from years back. Everyone comments on the photos, and that keeps us together.
Nine of the 15 participants said they relied on ICT to connect to financial information
such as banking, checking stock market performance, and paying bills. “I monitor my checking
account online and pay certain bills through the credit union,” said Grace. Using search engines
and software applications were actions cited by eight and six participants, respectively. “I use my
phone to google a fair amount, and I order food and Uber rides,” said Margot. Griffon said, “I
have about 200 apps on my phone. I’ve got Life 360 and can track my daughter’s every
movement. I use apps around the house, and I use several GPS apps religiously if I’m in the car.”
Not using ICT can exclude older adults from connecting to others and accessing
information. Umi explained:
I’m thinking of the seniors at the senior center where my mom goes. During the
pandemic in the shutdown, there were so many seniors who didn’t have any form of
communication. They couldn’t get services or find out about free meals. There’s some
45
advertisement on TV…but it’s not enough unless you have children who can help you
out. There’s a huge population being left out.
All 15 participants said they used their smartphones to make telephone calls. Participants
also used ICT for recreation and entertainment, including playing games, streaming movies,
listening to music, and reading. Appendix N reflects the 16 different ways the study participants
used ICT.
Older Adults Are Becoming Dependent Upon ICT
Seven of the 15 participants used ICT three to five hours per day. Six used ICT up to two
hours per day, and two participants used ICT six to eight hours per day. Even Kelly, whose
husband described her as a Luddite, a person who is opposed to technology, said:
My iPhone has become such a part of me that if I leave the house and forget it, I gotta
[sic] go back and get it. Because God forbid somebody would call me, and I wouldn’t
have my phone with me, or I’d need to look something up.
She also described the importance of ICT when traveling in her RV and used two
smartphones and one tablet simultaneously, each for different purposes:
I have my phone set up for Google directions, my husband’s phone going for something
else, and then I have the tablet running looking for places to go like the nearest Costco.
Technology has been great in assisting in planning. I feel so confident now when I’m
going someplace, and I haven’t been there before. I can look something up and get
guided instructions. ‘At the next stop sign, make a left.’ How do they know there’s a stop
sign here in the middle of nowhere? It’s amazing.
David said he used his cell phone and personal computer every day. He described his
digital approach to managing files and financials. “I don’t have any paper files and try to opt out
46
of all paper. I use Microsoft Access for our files and Microsoft Excel for our financials. All bill-
paying is electronic and through my bank,” he said. Rae described her tablet and said, “I love it.
It’s just delightful. You know it has Wi-Fi, and I can take it with me and do everything.”
Seven participants reported using ICT between three and five hours per day, and six cited
using ICT up to two hours per day. Of the two who said they used ICT six to eight hours per day,
one person worked full-time, and the other was retired. There was not a single participant who
said there were days when they did not use ICT. Appendix O shows the average number of hours
participants actively used ICT per day.
Research Question 2 Findings
Research Question 2 asked what barriers prevented older adults from using ICT. The
findings revealed 14 obstacles, including cognitive or physical disabilities, confidence,
insufficient training, technical readiness, and perceived value or utility. Additional barriers not
mentioned by anyone in this study include affordability and access to ICT. Costs and annual
contracts could be prohibitive for some older adults, especially those unhoused and those living
on a fixed income and caring for family members, for example. In analyzing the data for
Research Question 2, six themes emerged:
1. Disabilities result in strain or difficulty for older adults when using ICT.
2. ICT problems are technical, and user interfaces are unintuitive.
3. Older adults appreciate the power of ICT and feel excluded from it.
4. Older adults do not have sufficient ICT training.
5. Older adults do not have sufficient access to ICT help resources.
6. A lack of confidence prevents some older adults from using ICT.
47
Disabilities Result in Strain or Difficulty for Older Adults When Using ICT
Of the 15 participants, five identified disabilities, physical, language-based, and learning,
impacting their ICT use. None of the disabilities, however, were significant enough to prevent
the participants from using ICT altogether. Instead, the disabilities resulted in strain or difficulty.
Hearing impairments affected three of the study participants. Vision was a challenge for
Corinne and Umi, who had cataracts and glaucoma, respectively. “My eyes get tired when I’m
on the computer for a long time. I have eye strain from the blue light,” said Corinne. “My
glaucoma is managed,” said Umi, “But I sometimes notice with the smaller print I have to rest
my eyes. After a while, things start getting blurry, so then I know it’s time to stop.”
Belle had attention deficit disorder (ADD) and dyslexia. She described her difficulty
recalling more than three moves or instructions due to ADD:
It absolutely makes me frantically crazy to listen to somebody on the phone, particularly
overseas [when English is the speaker’s second language], trying to help me put
something together. I can’t do it. When you’re trying to do something on the computer,
frequently, it’s lots more [steps] than that. It’s gone [my recollection of the instructions]
after three [steps].
Age was not a determinant of disabilities. The youngest participant had glaucoma, and
the oldest had hearing issues. Appendix K shows the five participants and self-reported
disabilities affecting their use of ICT; some participants revealed multiple disabilities.
ICT Problems Are Technical, and User Interfaces Are Unintuitive
Participants were asked to describe problems they encountered when using ICT. The top
three concerns shared were software updates, an unintuitive interface, and technical language or
instructions. “You know you’ve got to do the Ctrl Alt Delete; stick your finger in your ear to get
48
somewhere. No, stop all that. That’s a computer language,” said Griffon. “Sometimes the
language they [technology companies] use is a computer-based language that I’m not familiar
with. I’m not sure what they are talking about,” said Umi.
Six of the 15 participants stated they often did not understand the ICT problems they
encountered. “There are a lot of problems that I don’t even know how to explain because I don’t
understand them to begin with,” said Belle. “People who don’t know anything about technology
don’t know the questions to ask,” said Corinne. “We’re a very large and growing portion of the
population, and there’s sometimes too much of an assumption of what we know. There needs to
be an effort to go to where the customer is in their knowledge,” said Margot. “So many times,
directions are given or written by a computer nerd, someone who doesn’t understand old ladies’
minds. I need really simple directions,” said Ava. “What tech companies need to do is put a great
big goddamn help button on the screen and just hit help, and somebody will pop up on the screen
and tell you what to do to make the font bigger, or something as simple as that,” said Griffon.
Software updates were identified as problematic for seven of the 15 participants. “On
both my phone and laptop, I tend to ignore updates, and that gets me in a lot of trouble. When
I’m on the computer, I don’t want to be bothered with stopping for a software update,” added
Belle. “I’m not doing updates. I hate updates,” said Kelly. David had a YouTube channel of
travelogues that combined narration with photos, videos, music, historical facts, and route details
using Google Earth satellite images. Even with his technical fluency, David found software
updates to be unintuitive. He said, “Almost every time there is a Microsoft update, you have to
start all over to figure out what the update has done.”
Software updates were cited more than any other problem. While software updates do not
require user knowledge, the unintuitive user interface and unfamiliar technical instructions create
49
barriers. Appendix Q lists the 14 ICT problems reported by the 15 participants; some mentioned
multiple ICT issues.
Older Adults Appreciate the Power of ICT and Feel Excluded From It
Many participants expressed appreciation and value for ICT; they see how powerful
technology is. “Every day, I am in awe of what the world is capable of showing me, and that’s
amazing about technology!” said Kelly. She added:
When we grew up in the ‘50s, we had a set of encyclopedias. We were the only family on
the block that had them. All the kids in the neighborhood used to come over when they
had a report due, borrowing our encyclopedias, so they didn’t have to go to the library. I
think of the place of honor they [the encyclopedias] held in our family home, and now all
you have to do is pick up a little phone and get much more information. It’s great!
Ava said, “I think computers and technology are wonderful. I just wish it [technology]
were simpler, so I can understand it more…and that they wouldn’t have so many ads on the
computer.”
Despite valuing and appreciating technology, many of the older adults in this study
struggled with their relationship to ICT. They observed a world heavily dependent on ICT, and
they questioned if they had the skills to navigate that world. “They [technology companies] are
making a huge mistake in ignoring the aging population, the baby boomers. There are programs
and products to help kids learn how to use technology, but they don’t have anything for seniors,”
said Belle. “It’s like they’ve [technology companies] just written us off. It’s like everything is for
the young people,” said Grace.
Ageism in American society and subsequently technology firms also contribute to older
adults and their feelings about ICT. “When I see advertisements for technology that are geared
50
toward older adults, a lot of it seems very condescending. To me, that’s offensive. I think there
has to be a way to assist people without looking down on them,” said Rae.
Older Adults Do Not Have Sufficient ICT Training
When asked when and how they learned to use ICT, the participants responded with a
wide range of answers. Five said they learned exclusively through work. Another five also
referenced work, but either learned through work and training, learned through work but did not
receive training, or were exposed to ICT through work and family. Two indicated they were
exposed to ICT through school, two took classes, and one learned through family members. “I
was fortunate to have been an early adopter of technology,” said David. “Many people [in my
age group] don’t realize the value of these tools.”
In 1964, Ryan studied engineering at General Motors Institute (now called Kettering
University). Working for General Motors, he returned to Mexico and was assigned to automate
many areas within manufacturing. Shortly after that, the IBM System/360 Model 40, the second-
largest computer in Mexico, was installed in his shop. Ryan said:
I learned how to use computers in school and at work, so I think I am an exception in my
age group. But a lot of people, you know, are really afraid. And they don’t even touch
things [technology]. My wife has a lot of issues [with technology], but she goes to me,
and then I help to solve them [the technology issues], and then that’s it.
Emmett said, “As a manager in business, you sink or swim, and you needed to figure it
out, or you were going to be gone. There was no training per se.” Michael echoed the theme of
needing training when he said, “I think it would be helpful if they [technology companies]
provided some training at the outset…they kind of give you the device and leave you on your
51
own.” Mia added, “Technology companies should go to schools to train teachers and computer
teachers. There should be training from companies if they want their products to be in schools.”
While there was roughly a 20-year range from the youngest to the oldest study
participant, their responses did not identify a standard way older adults learned to use ICT. For
example, the youngest participant, Umi, said she learned ICT through work. The oldest
participant, Michael, reported learning ICT through work and training. Ava, 76, said she took
some classes but was largely self-taught. Mia described an early career as a computer analyst,
typing on large cards and stacking the cards in an area where large printouts were made. She
said:
Life isn’t like that anymore. The computer language itself has changed, and the older you
get, if it’s not something you are doing every day, you have lost that bit. You are like a
kid starting over again.
Appendix P shows where and how the participants learned to use ICT and their perceived
confidence.
Older Adults Do Not Have Sufficient Access to ICT Help Resources
Having reliable, trusted sources to help with ICT issues was something most participants
said they lacked. “I get frustrated with technology sometimes because now that I’m outside the
work sector, I don’t have my IT help,” said Griffon. Although he was retired, Michael
maintained his relationship with his previous company, in part, to continue getting technical
support. He explained, “When I’m having problems, I will dial up tech support, and I do that
with some frequency. They’re great. They always seem able to solve the problem.”
Participants stated that finding help resources was difficult. “When I try to get help
[online], I can rarely find anything that actually helps. Providing quick, clear help would be
52
good. It would also be great to be able to talk to a person,” said Margot. “The older generation
needs very basic, very simple instructions hopefully developed by another old person who
understands it and can teach someone who doesn’t,” said Ava. Making help accessible in other
languages also is needed. “Language is an issue if you’re not a native English speaker. It
becomes even more complex and more intimidating for you to reach out and ask for help,” said
Umi.
A lack of confidence in using ICT also prevents users from seeking help from IT experts.
“I think if they [technology companies] would make it less intimidating to ask for help…if there
was a more user-friendly space for people 65 and older who did not grow up with technology,”
said Umi. Two participants brought up the importance of learning or getting help from someone
patient. “I need someone to help me. Patiently,” said Corinne. Kelly added, “I need to sit with a
patient person who can walk me through technology.”
Two participants discussed concerns about phishing and spam. “There’s so much stuff
that comes out on the internet that hurts people. They’re reading something, and it sounds great,
and just by doing that, their personal information is stolen, and it hurts them economically,” said
Ryan. Corinne complained about junk emails and spam calls to her smartphone:
I wrote down 12 numbers that need to be blocked. Somebody told me to punch number
two, and then you could stop the calls, but it didn’t help. I tried to block them, but I
couldn’t block anything. So, now I have a list and need to wait for my children to come
here and help me…I need people to help me solve my problems [with technology]
because I cannot do it.
Ten of 15 participants said they asked family or friends for help when they encountered
ICT problems. Eight of the 10 individuals said they reached out to relatives for help. “I call my
53
children for help almost every day. Especially my son,” said Corinne. “My daughter and son are
my tech support,” said Margot. “I depend upon my granddaughter and my youngest daughter to
show me how to navigate through everything,” said Mia.
Almost all 15 participants described a willingness to troubleshoot and solve whatever
issue they were having. Rae said:
Usually, the first thing I do is turn it [the device] off and turn it on. That was like the first
piece of advice I got from a technology friend. I would say that is very, very often the
way to fix whatever the problem is.
David relied on technology through Google searches and YouTube to solve ICT
problems. He said, “I have found on the internet that I’ve never been the first one to have a
problem. Somebody has already queried about it and figured it out; I’ve never had to hire an IT
expert to help me.” Griffon said, “Since I no longer have IT support, I go online and fix it
myself. When I’m looking on YouTube, I’m looking for the videos with the greatest number of
hits and the shortest length.”
Three of the 15 respondents stated they would likely abandon whatever task they were
trying to complete using ICT if they could not quickly solve the problem themselves. “I would
ignore the problem for as long as I could and would pick up a book and start reading instead,”
said Kelly. “If my games don’t load, or there are too many ads, I’ll just turn it off,” said Grace.
“Between my son and my neighbor, if they don’t know how to do it, I tend to say, ‘to hell with
it’ and quit,” said Ava.
Based on the findings, asking family or friends for help is generally attributed to
convenience, a lack of confidence in ICT abilities, distrust, and a lack of awareness or
54
availability of help resources. Appendix R shows the seven actions participants took when
encountering ICT problems. Some participants cited multiple actions taken.
A Lack of Confidence Prevents Some Older Adults From Using ICT
When asked their confidence levels in using ICT, nine of the 15 participants described
themselves as confident. However, they qualified their answer by saying that their confidence
was limited to familiar tasks and diminished when problems occurred. Two of the 15 participants
said they were not confident, and two reported being somewhat confident. The two participants
who said they learned how to use ICT through school were also the only two who described
themselves as very confident in using ICT. Petra started college at 38 as a single mother and
said:
It was right when WordPerfect was hitting, so I had to teach myself how to type using
WordPerfect…and then I got remarried to a software engineer, so now I’m surrounded by
people who have the expertise. So, I think it helped a lot that I started that [learning how
to use technology] much later in life.
Rae described her love of reading and libraries and said, “I always wanted to be a
librarian and went to library school…and law and medicine were two of the areas where
technology was applied very early on.”
Michael, who is somewhat confident with ICT, said, “I wish I were more adroit in using
some of this, but I’m not very patient about trying to figure out how all of these things work.”
Corinne, who is not confident using ICT, said, “I should learn how to do more, like shop and
order things online, but I can’t do it. It takes time to learn these things, and I’d like to have more
time for other things that are more fun.” Simplifying ICT and focusing on the benefits of using
ICT could encourage confidence. “Make devices and products easier to use for people who are
55
not interested in technology and show the value of technology by demonstrating how to get
something done,” recommended Rae.
Participant responses showed a relationship between a lack of confidence in using ICT
and learning to use technology through friends and family. Learning how to use ICT in a setting,
such as a school, where tasks were used and repeated, helped with ICT mastery. Appendix P
shows the participants’ self-reported confidence levels with ICT.
Research Question 3 Findings
Research Question 3 asked participants how technology companies could improve ICT
for older adults. Participants were also asked to imagine delivering a message to CEOs of major
technology firms about ICT, either personally or on behalf of others. Recommendations ranged
from simplifying the user experience to providing training when new products roll out. Several
participants complained about the all-consuming role technology plays in the younger
generations’ lives. Others questioned the role technology companies have played in the political
landscape; I excluded those comments from this study to focus on older adults and their use of
ICT.
Regardless of how competent or confident the interview participants were in using ICT, all
shared their ideas of how ICT could be improved for older adults. In analyzing the interview data
for Research Question 3, the recommendations fell into four major themes. The
recommendations section, supported by literature, explores these four themes for improving ICT
for older adults:
• Simplify and create an intuitive, user-friendly experience
• Involve older adults in product design and solutions
• Be proactive in training users and non-users
56
• Make getting help easy and accessible
Simplify and Create an Intuitive, User-Friendly Experience
Ample feedback was provided about the unintuitive nature of ICT. Mia said she retired
from teaching early due to increased and immediate demands to use new technology in the
classroom during the COVID-19 pandemic. Despite her youngest daughter and granddaughter
being reliable resources to help her navigate technology, she felt the demands [to use new
technology] were too great. Mia described her school’s principal telling the teachers to set up
Google Classroom, on a Friday, for the following Monday due to COVID-19 stay-at-home
orders. The teachers gathered for cupcakes, conversation, and laughter. “There wasn’t any
training going on.” She continued:
I could not have my first meeting with the kids [on Monday] because I didn’t know how
to send them links and do all of that. I couldn’t set up the classes. I didn’t know anything,
and then, unfortunately, we had quite a few teachers that were 60 and above, and all of us
just cried. Tears were coming down because our principal felt we should have been able
to go into the computer and find out how to do everything. My principal actually got
upset and said that I should know how to make it [Google Classroom and related
technology] work.
“I am not familiar with my iPhone,” said Corinne. “There are certain things on that phone
I don’t know how to use, so I use my laptop more. Although that is not reliable, either.
Sometimes it takes me a long time to type something, and then it disappears.”
Involve Older Adults in Product Design and Solutions
Three of the 15 participants felt their current knowledge of ICT was sufficient. “At this
time in my life, I don’t have the desire anymore to interact with these technologies or do new
57
things on the computer or the phone. What I’m doing now is fine,” said Mia. “I could do some
training,” said Michael, “But right now, given my needs, I’m quite satisfied.”
Five participants advocated for older adults to be involved in ICT product design and
solutions citing benefits for the older consumer. Ava said, “ask older people to provide
instructions for their peer group!” David, who was very comfortable with ICT, said, “In
designing and building things, those who are smart gather information from users.” He
mentioned the additional benefit of using ICT, “Many people don’t realize the enjoyment and the
benefit. I’m probably a little sharper than if I weren’t using these things [ICT].”
Be Proactive in Training Users and Non-users
While this study is focused on older adults, David mentioned the importance of ensuring
that young people have access to ICT and know how to use it. He said, “Google and Microsoft
have the opportunity to assist schools so that all kids can be exposed [to technology].” He added,
“Ask kids for their ideas.” This idea is essential since many older adults rely on younger family
members, including grandchildren, to provide technical support.
Michael recommended that technology firms provide help at the outset. “They kind of
give you the device and leave you on your own. It would be helpful if they had instruction
manuals.” Once training is received, whether through peers or an instructor, the participants were
able to adopt the new technology. Mia, who taught math, said:
Once I learned how to use Google classroom, I was determined that these kids were
going to be ready to go to the next level. I said my eighth graders cannot leave me and
not know algebra. So, I taught them as though we were in the classroom, and I learned
how to use the whiteboard, and everyone was checking everyone else’s work.
58
Make Getting Help Easy and Accessible
To compensate for the unintuitive nature of ICT, participants described needing better
help tools. With inadequate resources for help, participants leaned heavily upon family and
friends for help. Umi described friends in her age group who were intimidated to get on the
phone and ask technical support for help. “A while back, when the NextDoor app came out,
friends would just give me their phone and say, ‘Could you set it up for me?’ It’s a network of
friends helping each other.” Umi recommended “a more user-friendly space for 65 and older
people who did not grow up with technology.”
“I think they [technology companies] should be more friendly and teaching [consumers]
in better and easier ways. Don’t complicate it so that people can’t take advantage of all the things
available on the internet and everywhere else,” said Ryan. Participants also asked that
assumptions not be made about their knowledge. Margot said, “There needs to be an effort to go
to where the customer is in their knowledge.”
The study participants identified four themes to improve ICT for older adults:
• Simplify and create an intuitive, user-friendly experience
• Involve older adults in product design and solutions
• Be proactive in training users and non-users
• Make getting help easy and accessible
Participants were asked what they would like to convey to CEOs of technology firms.
The messages to CEOs are consistent with the four themes for improvement. Appendix S
highlights participant messages to CEOs.
59
Summary of Findings
Participant interviews answered all three research questions and revealed other valuable
insights about ICT use among older adults. For example, the group of participants had 20 years
between the youngest and the oldest participant. The youngest participant, Umi, while confident
with ICT, was not the most confident user. David, the third-oldest participant, described himself
as confident. He had a YouTube channel in which he uploaded travelogues shot on his
smartphone, maintained a digital household with very little paper, and said he never went
through a checkout line at grocery stores or membership warehouses. “I scan everything [using
my smartphone], and then there’s a kiosk that calculates my bill, and then I scan the barcode, and
I’m gone!” These wide ranges of experience demonstrate that a one-size-fits-all approach to
solving ICT needs would not be practical for older adults, especially if assumptions are made
about age and ability.
This study’s findings support the literature that older adults are a heterogeneous group in
their use of digital technology (Hanninen et al., 2020). Haddon et al. (2012) concluded that
generations are often viewed as homogenous entities. In actuality, there are significant
differences and similarities across all generations (Haddon et al.). In this study, all 15
participants held college degrees, with 11 of the 15 earning advanced degrees. Even with this
similarity, there was significant variation between the 15 participants in how they learned to use
ICT and their confidence levels. There were similarities, however. The group of participants all
said they valued ICT, including the least-confident users. While many expressed concerns about
phishing, spam, and excessive use of ICT by the younger generations, none of the participants
said they were fundamentally opposed to ICT, did not want to use it, or elected not to use ICT. In
contrast, all participants recognized the power of ICT, and if they were not already proficient,
60
they expressed a desire to become more fluent using ICT. Many felt they did not know how to
achieve fluency or did not want to spend the time learning how to achieve or enhance their ICT
knowledge and abilities.
Introduction to Recommendations
The purpose of this study was to understand the difficulty many older adults experience
when using ICT. The following research questions guided this study:
1. How do older adults use ICT?
2. What barriers prevent older adults from using ICT?
3. What are the recommended practices for technology companies to improve ICT for
older adults?
The research questions were asked through the lens of a conceptual framework which consisted
of Bronfenbrenner’s ecological systems model (1979), the relative deprivation theory (Crosby,
1976), and the technology readiness and acceptance model (Davis, 1989; Parasuraman, 2000). A
literature review examined numerous studies on aging, ageism, elder justice, equity, the digital
divide, digital inequalities, and ICT benefits, impacts, and barriers for older adults. Data were
gathered through 15 qualitative interviews with participants ranging in age from 65 to 87. These
interviews provided answers to the three research questions and offered a glimpse into the
participants’ lived experiences relative to ICT use. All interviews consisted of 16 questions. The
literature supported recommended practices for improving ICT for older adults. A sample
implementation and evaluation plan, using Kellogg’s Logic Model (2004), follows.
Recommendations for Improving ICT for Older Adults
The following are recommended practices technology companies should implement to
improve ICT for older adults. The recommendations fall into four major themes:
61
• Simplify and create an intuitive, user-friendly experience
• Involve older adults in product design and solutions
• Be proactive in training users and non-users
• Make getting help easy and accessible
Bronfenbrenner’s Ecological Systems Model
This study’s recommendations were viewed through Bronfenbrenner’s ecological
systems model (1979), which attempts to understand how the environment shapes human
development. While the individual is at the center of Bronfenbrenner’s model, this study’s
recommendations are directed toward technology companies operating at the exosystem level in
developing, producing, and manufacturing the four types of ICT identified in this study.
Ageism, which occurs at the macrosystem level through societal beliefs, practices, and
values, also must be considered because cultural norms permeate all systems. As the World
Health Organization shared in its Decade of Healthy Ageing: Plan of Action, improving healthy
aging will require involvement from many sectors, including health, finance, education, housing,
transportation, long-term care, social protection, civil society, the private sector, advocates for
older people, older people, and their friends and families (World Health Organization, 2020).
Integration of these areas is necessary, and “ageism should be addressed in all policies,
programmes, and practice. Together, they should promote and foster healthy ageing and improve
the well-being of older people” (World Health Organization, 2020, p. 6).
Equity and elder justice also must be considered when examining the problem of practice.
Concepts such as fairness and rights for older adults reflect the values of a society. Similarly, the
absence of fairness and rights for older adults is also representative of a culture. Yuen et al.
(2017) explored the ICT experience of 22 Hong Kong students and found that Confucian values
62
affected microsystem relationships and influenced parenting practices and the distribution of ICT
resources. Whether the parents distributed or withheld ICT resources potentially affected ICT
proficiency and could result in digital inequities (Yuen et al.)
The problems of ageism and digital inequities are global (Cuddy et al., 2005; Dijk, 2005;
Hargittai & Walejko, 2008; Levy & Banaji, 2002). As the older population continues to grow
worldwide, there is increased interest and attention on how societies across the globe will view,
treat, and accommodate their older adults (North & Fiske, 2015). To be an advocate for age
justice and elder rights intersects with the fight for racial justice. Raven (2021) stressed the
importance of intersectionality and seeing the whole person and their needs and not just one part
of a person. Intersectionality refers to the interconnected nature of social categories such as
gender, race, disability, and class (Swartz et al., 2019). These social categories can be applied to
individuals or groups and create overlapping and interdependent systems of disadvantage or
discrimination (Swartz et al.).
Bronfenbrenner (1979) described the components of the macrosystem as consistencies
and similarities across settings and systems and the beliefs attached to those similarities. Beliefs
include what is valued and considered good or bad. Laws and policies often support those beliefs
and influence behavior and development (Bronfenbrenner). As a result, changing cultural values
at the macrosystem level about youthfulness and aging will take time.
Simplify and Create an Intuitive, User-Friendly Experience
In conducting technology training sessions in retirement communities, Cotten et al.
(2016) found that older adults responded to simplified language in the training manual, detailed
instructions, and repetitive practice for even the simplest of tasks. The trainers found that tasks
such as moving the mouse or clicking to open a program sometimes took more than one class to
63
master. In a comparison study of 42 older adults (M = 68.6 years) and 49 young adults (M = 22.6
years), Marquie et al. (2002) concluded that low confidence in their abilities is one reason older
adults have difficulty mastering new computer technologies. Cotten et al. (2016, p. 142) advised:
The important thing for those working with older adults and technology to remember is
that the simpler the interface can be made, whether by design or through the way the
instructor explains and teaches it, and the less removed from actual physical experience
(e.g., touch, rather than point and click), the easier it will be for those unfamiliar with it to
grasp and master. Therefore, no matter the interface or how technology advances, the
main goal of design should be naturalization and simplification, both of which take a
great deal of thought and time to effectively implement in training…the necessity for a
simple and natural interface will continue for at least the next decade.
The data from this study’s interviews matched with the technology readiness acceptance
model (Davis, 1989; Parasuraman, 2000) suggests that simplifying and creating an intuitive,
user-friendly experience is necessary for older adults to adopt ICT. Applying Universal Design
for Learning (UDL) guidelines also could improve users’ ICT experience regardless of age
(CAST, n.d.). UDL guidelines are based on scientific insights into human learning (CAST).
Incorporating more use of artificial intelligence in products for older adults will be an important
solution in the future. Another recommendation is to create tools and products that fit the user
rather than designing one product intended for use by all consumers. For example, if Apple or
Dell were to build a laptop, perhaps there could be three different versions or models of the same
laptop. One laptop could be for children with smaller hands. A second laptop could be developed
for adults. A third could be developed for older adults who might have disabilities or limited
mobility. These three laptops could come in three different categories such as novice,
64
intermediate, and expert. As the individual’s experience level improves, the user could turn in
their laptop and upgrade to the next version. Rather than requiring multiple keystrokes such as
Ctrl Alt Del Fn Esc for commands, technology companies could replace them with simple keys
such as Open, Close, Send, and Help.
Koscher et al. (2017) reported on the findings of a 2016 study conducted in Switzerland
and the Netherlands with inexperienced ICT users 70 years and older. The study showed that the
primary motivation for the test group to use ICT is to stay in touch with family and friends.
Willingness to try out a new technological device occurs only when older adults believe they
need a new technical device. This finding, matched with the relative deprivation theory (Crosby,
1976), suggests that a compelling argument must be made to convince non-ICT users to invest
the time, resources, and energy to learn to use ICT.
When beginning any ICT outreach program to older adults, it is recommended that
trainers immediately show the benefits of ICT and focus on the value to the individual. Trainers
could demonstrate how ICT enables contact with those who live in other countries, for example.
Describing the technical aspects before highlighting the benefits of ICT may discourage some
less-confident users who lack technical skills and abilities. The trainer should also reinforce that
mastery is not a prerequisite to using ICT, whereas repetition and patience are highly
encouraged.
Involve Older Adults in Product Design and Solutions
Studies about older adults and the use of digital technology support the notion that older
adults are a very heterogeneous group compared to other age groups (Hanninen et al., 2020).
Cotten et al. (2016) found different ICT usage and adoption patterns within older adults, with
variations in their devices used to access the internet and how often they used ICT. This study’s
65
findings align with the conclusion that older adults are a very heterogeneous group. There was
roughly a 20-year difference between the youngest participant, 65, and the oldest, 87. All study
participants had varying experiences ranging from where and how they learned to use ICT and
their confidence associated with ICT.
Involving older adults in technology design, product testing, and solutions should not be
merely an exercise to fulfill brand and reputation goals for the technology company. Therefore,
the recommendation is for technology firms to understand ageism, identify the ways ageism
permeates technology firms—from hiring decisions to product design—and find meaningful
ways to tap into the insights and experiences of older adults. Technology firms should seek to
understand older adults, both novices and fluent ICT users.
Thielke et al. (2011) found general inattention to user needs in the development process
of technologies geared at older adults. Technology developers often did not understand or
address user needs. Thielke et al. recommended using Maslow’s model and hierarchy of five
levels of human needs—physiological needs, safety, love and belonging, esteem, and self-
actualization—to predict how older adults and their caregivers would benefit from and consider
adopting technology. Mannheim et al. (2019) were unable to determine if gerontology studies on
digital technology involved older adults or if the technologies met the needs and desires of older
adults.
Given the heterogeneous nature of older adults, technology firms must be more diverse
and inclusive. Diversity in Tech (n.d.), an online resource dedicated to helping close the diversity
gap in the technology sector, identified four ways to increase diversity in tech:
• Address unconscious bias
• Support returners, including women and older workers
66
• Support apprenticeships
• Ensure equal pay
After the amplified focus on the Black Lives Matter movement in 2020, Google and
Facebook pledged to increase underrepresented leadership by more than 30% within five years
(Sor, 2021). Sor cited a 2020 study conducted by Blendoor, a corporate analytics firm, that
revealed technology firms pledged more than $4.5 billion to diversity efforts. The numbers do
not yet match the promise, however. Blendoor reported that Black and Hispanic workers
comprised 4.7% and 6.8%, respectively, of the technology industry in 2021. Google announced a
program designed to bring more workers with autism into its cloud workforce (Heasley, 2021,
August 9). The program will rely on experts from Stanford University’s Neurodiversity Project
to train Google staff to work with candidates who have autism and coach job applicants with
autism. The support continues if the candidates are hired (Heasley).
Leaders from firms such as Pricewaterhouse Coopers, Accenture, Deloitte, and Boston
Consulting Group launched CEO Act!on for Diversity and Inclusion in June 2017. Since the
program began, nearly 2,000 CEOs have signed a pledge that commits the signatories to
implement programs, share information, and support open dialogues in their respective
companies. These CEOs represent more than 85 industries and about 13 million employees
across the United States (CEO Act!on for Diversity and Inclusion, n.d.). An advocacy
organization for older adults such as AARP could partner with technology leaders to launch an
awareness and action campaign to invite friendly competition in a highly competitive industry.
Technology company CEOs could pledge to do the following:
• Bring attention to the problems of ageism, an absence of older workers in the
technology industry, the digital divide, and digital ageism
67
• Amplify user-centered design efforts and resources to understand what older adults
want and need in ICT and to involve older adults in testing product design
• Commit to taking measurable steps to address the problems of ageism, an absence of
older workers in the technology industry, the digital divide, and digital ageism
• Hire older technology workers and upskill them as necessary
• Form an advisory or steering committee comprising older adults of different levels of
technological fluency
The data matched with the technology readiness acceptance model (Davis, 1989;
Parasuraman, 2000) reinforce the importance of involving older adults in product design and
solutions. Involving this underserved population will identify strategies to teach older adults how
to use ICT or increase their ICT fluency. A growing concern is that older adults must learn to use
ICT to avoid further disadvantages in contemporary society (Selwyn, 2004b). Mannheim et al.
(2019) concluded that there is a mismatch between the promise of digital technology in
improving the lives of older adults and the actual use of digital technology; partnering with older
adults in design and research would help overcome barriers. By involving older adults, solutions
may be more representative of the interests, abilities, and needs of those 65 and older. In
describing Apple and Uber’s success in designing products for the user, Varma (2015) said:
One common thread that unites these examples is how well these products and services
are designed—not just the bright and shiny wrapper, but as a well-designed product in the
truest sense. These companies aim to deliver superior experiences through their deep
understanding of target group users rather than mindlessly stuffing features into the
product. They strive to learn about their pain points and address them through evolving
innovating solutions and by increasing the number of cases through “co-creation.” They
68
don’t proceed with a “we-know-everything” attitude, but actually listen to their
prospective users and aim to deliver solutions through a process of continuous feedback,
adaptation, and improvement.
The 15 participants in this study all used ICT in manners that reflected their abilities
ranging from novice to advanced user. If technology companies asked a similar sample of older
adults for their ideas and opinions, the feedback would likely represent a wide range of
complaints and ideas for improvement. This input should be used to inform product design, and
as prototypes are built, older adults should test the devices before they go to market. The process
of gathering feedback, designing, and evaluating should be repeated regularly as users and their
needs change. By involving older adults in product design and solutions, technology companies
could customize ICT for older adults and reap the benefits of a lucrative and relatively untapped
market. According to AARP’s Longevity Economy Outlook (2021), anticipated spending on
technology by older Americans will grow from $140 billion in 2018 to $645 billion in 2050.
Be Proactive in Training Users and Non-users
Individual development is an ongoing process. It occurs as a person ages, creates an
understanding of their world, and learns to operate effectively within the systems they participate
in (Shelton, 2019). When it comes to learning new technologies, older adults are motivated if
they consider the technologies helpful, useable, and time-savers (González et al., 2012).
Bronfenbrenner (1979) concluded that other than the family home, children’s institutions
such as daycare and preschool were the only setting that served as a comprehensive context for
human development from the early years onward. Family, friends, school, and work all represent
microsystem influences. How an older adult perceives and uses ICT is influenced by
microsystem influences, such as education and occupation. Unlike other age groups, older
69
adults’ use of ICT is primarily motivated by experience (Czaja et al., 2006). This study’s
findings revealed that participants who learned to use ICT through work and school were more
confident than those who learned independently or through family and friends.
Bakardjieva (2005) introduced the concept of using “warm experts” and described them
as those who have a close personal relationship with a novice user and serve as the mediator
between technology and the needs and background of the novice user. Caceres and Chaparro
(2019) found that warm experts could be other adults or spouses. The literature supports the
technology readiness acceptance model (Davis, 1989; Parasuraman, 2000) and suggests that
engaging warm experts to teach older adults ICT is an effective way to approach novice users.
Hunsaker et al. (2019) found that older adults generally seek technical support from informal
sources such as family and friends. Additionally, Leedahl et al. (2020) found that addressing and
improving age stereotypes among young adults effectively decreases ageist attitudes and
improves the treatment of older adults.
The interview data matched with the technology readiness acceptance model (Davis,
1989; Parasuraman, 2000) suggest that technology companies should proactively train users and
non-users. The recommendation is to assess the level of existing knowledge and comfort with
ICT and create a judgment-free, fun learning environment customized to the older adult. Trainers
should, ideally, have experience working with older adults. Technology firms should also
consider hiring older adults proficient in ICT and provide them with training; they can serve as
role models for their peers.
Make Getting Help Easy and Accessible
The recommendation is to bring flexible ICT training programs to places older adults
congregate and live, such as community centers and retirement homes. As mobility and
70
transportation become more challenging for older adults, having training programs and
technology help that are easily accessible and come to users will likely make using ICT more
appealing. Receiving positive feedback and rewards and gaining a sense of competence during
action can enhance intrinsic motivation for that action (Ryan & Deci, 2000). Cotten et al. (2016)
found that technology can be a valuable tool in helping older adults maintain their identity when
moving from home and into a retirement community.
The recommendation, therefore, is for technology companies to make getting help easy
and accessible. Simple step-by-step help videos could be prominently displayed on manufacturer
sites and offered in different languages and for those who may be visually impaired.
Additionally, technology companies should minimize the use of technology to solve technology
problems. A low-tech approach is recommended, such as providing a 24/7 helpline that can be
accessed by dialing a toll-free telephone number. The person who answers the telephone can
help route the call to the correct department or resource rather than relying on the caller to
respond to prompts to push or say something. A study by Schecter et al. (2021) found that when
customer service agents are experts or know how to handle complex calls, they can quickly,
efficiently, and effectively resolve customer issues.
Implementation and Evaluation
This study used the Kellogg Logic Model (2004) to illustrate an implementation and
evaluation plan. A logic model provides a systematic and visual way to depict the relationships
between the program resources, planned activities, and desired changes or results. Logic models
can be as simple or complex as the programs they represent. In their simplest form, they contain
five essential components (Kellogg):
• Resources/Inputs
71
• Activities
• Outputs
• Outcomes
• Impacts
Resources are sometimes referred to as inputs and reflect what the program intends to
contribute. Program activities reflect what will be done with the resources. Outputs refer to the
products of the program activities. Outcomes reflect the specific, measurable changes that will
occur. According to Kellogg (2004), short-term outcomes should be achieved within one to three
years, while longer-term outcomes should be attained within four to six years. Impact refers to
the intended change that will occur as a result of program activities. A foundational principle
from Kirkpatrick and Kirkpatrick (2016) is that the end is the beginning. Applying Kirkpatrick’s
philosophy means that desired results should be examined and identified first rather than last.
A logic model captures the sequence of activities and the linkage between the various
components. The first two boxes—resources/inputs and activities—represent planned work.
Next, the following three boxes—outputs, outcomes, and impact—are desired or intended
results. Figure 3 shows a high-level example logic model.
Figure 3
High-Level Example Logic Model
72
Implementation Using a Logic Model
In practice, a logic model for a program or project would need to be much more specific
and detailed than Figure 3 shows. Developing a logic model begins with the project team and
sponsor answering a series of thoughtful questions (Kellogg, 2004):
• Resources/Inputs: What is needed to accomplish the desired results?
• Activities: Using the resources provided, what steps or actions will be taken to
address the problem?
• Outputs: What are the expected and measurable results of planned activities?
• Outcomes: What are the short- (one to three years) and long-term (four to six years)
measurable results anticipated?
• Impacts: What are the long-term desired and measurable results of actions taken?
The details listed in the example logic model are elements a technology company could include
to launch a CEO-led campaign pledging to involve older adults in product design and solutions.
Assumptions, such as those that exist in the exosystem, refer to beliefs held to be accurate that
will support program success. External factors are other elements to be considered and
potentially mitigated. External factors exist in the macrosystem and can include cultural values
and norms. Figure 4 presents a logic model with example elements.
73
Figure 4
Example Logic Model to Implement CEO Pledge
Evaluation Using a Logic Model
There are two types of evaluation questions in Kellogg’s (2004) evaluation plan. The
purpose of formative evaluation is to improve the program as it is executed. Summative
evaluation occurs at the end of the program, and its purpose is to prove whether the program met
74
its implementation goals. Regardless of the evaluation type chosen, Kellogg identified three
areas to evaluate:
1. Context (relationships and capacity): How did the program function?
2. Implementation (quality and quantity): Were activities executed as planned?
3. Outcomes (effectiveness, magnitude, and satisfaction): What changed as a result of
the program?
Kellogg recommended keeping the evaluation process simple, manageable, and
beginning with the types of data needed and designing methods to gather the data. The project
team also should think about their key stakeholders and questions they would want to be
answered. For example, funders would want to know how their resources were used and whether
targets were achieved.
Recommendations for Future Research
While this study had no participation criteria for education, only highly educated people
were involved in the study. A future study could explore whether less-educated individuals
identified the same barriers to ICT as these 15 study participants. Another future research study
could compare the six barrier themes identified in this study with other underrepresented groups
to determine if the recommendations cited in this study are applicable for other underrepresented
populations.
The dearth of older adults working in the technology industry provides many ideas for
future research. One study could explore hiring practices within the industry and how ageism and
age discrimination practices are addressed to promote greater inclusion. Many technology
companies have established accessibility and customer inclusion functions. A related study could
investigate how findings and recommendations are dispersed through the rest of the company for
75
implementation. Another study could examine the consequences for marginalized groups, such
as older adults, when there is a lack of representation and involvement during the product design
process.
Conclusions
According to the AARP’s Longevity Economy Analysis (The Longevity Economy
Outlook, 2021), Americans 50 and older are an “economic powerhouse.” The economic power of
people in this age group was $8.3 trillion in annual economic activity in 2018. Economic activity
is “the total of GDP generated by all industries as a result of the 50-plus population’s existence
and participation in market activities, i.e., it spends money, pays taxes, and provides labor.”
Additionally, older adults’ anticipated spending on technology is forecast to grow from $140
billion in 2018 to $645 billion in 2050 (The Longevity Economy Outlook). Technology
companies have the potential to tap into a largely untapped revenue stream and, at the same time,
to better serve a population that often feels excluded from technology—this seems to be an
obvious win-win.
However, whether technology companies will address ageism and adopt practices to
serve older adults better is yet to be determined. Upon completing my research project, I reached
out to a leading multinational technology corporation to share the findings and recommendations
of my study. I was told, through a professional contact, that a critical decisionmaker in the
company’s customer inclusion practice “does not have time to speak with you.” The head of user
experience research at a different multinational technology corporation has shown more interest;
hopefully, a meeting will follow. I will continue exploring different avenues to disseminate my
study findings and identify other technology companies that will welcome the opportunity to
understand more about the needs and wants of this important group of people.
76
The aging population is growing and living longer. The world is increasingly relying on
technology for essential needs, whether to sign up for the COVID-19 immunizations, book
airline tickets, or do banking. Ensuring that older adults can use ICT to supplement their lives is
a venture worth pursuing; it will help ensure this growing population continues to participate and
thrive in society, add value, and feel included.
77
References
Adams, R. G., & Blieszner, R. (1995). Aging well with friends and family. American Behavioral
Scientist, 39(2), 209–224. https://doi.org/10.1177/0002764295039002008
Airola, E., Rasi, P., & Outila, M. (2020). Older people as users and non-users of a video
conferencing service for promoting social connectedness and well-being - a case study
from Finnish Lapland. Educational Gerontology, 46(5), 258–269.
https://doi.org/10.1080/03601277.2020.1743008
Ala-Mutka, K., Malanowski, N., Punie, Y., & Cabrera, M. (2008). Active ageing and the
potential of ICT for learning. Joint Research Centre—Institute for Prospective
Technological Studies. JRC Scientific and Technical Reports.
https://tinyurl.com/ea4mvz2e
Alford, D. M. (2011). The elder justice act. Journal of Gerontological Nursing, 37(8), 14–16.
https://journals.healio.com/doi/10.3928/00989134-20110603-01
American Association of Retired Persons. (2019). AARP wants to disrupt the image of aging.
https://www.aarp.org/about-aarp/info-2019/disrupt-aging-collection.html
American Association of Retired Persons. (n.d.). The economic impact of age discrimination.
https://doi.org/10.26419/int.00042.003
American Association of Retired Persons. (2021). The longevity economy outlook.
https://doi.org/10.26419/int.00042.005
Anderson, R., Bikson, T., Law, S., & Mitchell, B. (1997). Universal access to email: Feasibility
and societal implications. Educational Media International, 34(2), 86–87.
Argyle, M. (1987). The psychology of happiness. Methuen.
78
Backonja, U., Hall, A., & Thielke, S. (2014). Older adults’ current and potential uses of
information technologies in a changing world: A theoretical perspective. The
International Journal of Aging and Human Development, 80(1), 41–63.
https://doi.org/10.1177/0091415015591109
Baecker, R., Sellen, K., Crosskey, S., Boscart, V., & Neves, B. (2014, October 20). Technology
to reduce social isolation and loneliness. [Paper presentation]. 16
th
international ACM
SIGACCESS conference on computers & accessibility, Rochester, NY.
Bakardjieva, M. (2005). Internet society: The internet in everyday life. SAGE.
Banks, L., Haynes, P., & Hill, M. (2009). Living in single person households and the risk of
isolation in later life. International Journal of Ageing and Later Life, 4(1), 55–86.
Barnett, K., & Adkins, B. (2001, Dec.13–15). Social inclusion: Computer practices enabling
older people’s ‘virtual mobility’ between and communities [Paper presentation]. TASA
2001 conference, Sydney, Australia.
Beckers, J. J., Rikers, R. M., & Schmidt, H. G. (2006). The influence of computer anxiety on
experienced computer users while performing complex computer tasks. Computers in
Human Behavior, 22(3), 456–466. https://doi.org/10.1016/j.chb.2004.09.011.
Bijker, W. (2009). How is technology made? That is the question! Cambridge Journal of
Economics., 34(1), 63–76. https://doi-org.libproxy2.usc.edu/10.1093/cje/bep068
Birkland, J. (2019). Gerontechnology: Understanding older adult information and
communication technology use. Emerald Publishing.
Blancato, R., & Whitmire, W. (2020). Elder justice policy: Where we are now and where do we
go next? Generations, 44(1), 106–110.
79
Boulton-Lewis, G., Buys, L., Lovie-Kitchin, J., Barnett, K., & David, L. N. (2007). Ageing,
learning, and computer technology in Australia. Educational Gerontology, 33(3), 253–
270. http://dx.doi.org.libproxy1.usc.edu/10.1080/03601270601161249
Brighton, H., & Selina, H. (2012). Introducing artificial intelligence: A graphic guide. In
Introducing Artificial Intelligence. Icon Books Ltd.
Brinig, M., Jogerst, G., Daly, J., Schmuch, G., & Dawson, J. (2004). The public choice of elder
abuse law. The Journal of Legal Studies, 33(2), 517–549. https://doi.org/info:doi/
Bronfenbrenner, U. (1979). The ecology of human development: Experiments by nature and
design. Harvard University Press.
Caceres, B., & Chaparro, C. (2019). Age for learning, age for teaching: The role of inter-
generational, intra-household learning in internet use by older adults in Latin America.
Information, Communication & Society, 22(2), 250–266.
Cacioppo, J. T., Hawkley, L. C., & Berntson, G. G. (2003). The anatomy of loneliness. Current
Directions in Psychological Science, 12, 71–74.
Cameron, D., Marquis, R., & Webster, B. (2001). Older adults’ perceptions, experiences and
anxieties with emerging technologies. Australasian Journal on Ageing, 20(s2), 50–56.
https://doi.org/10.1111/j.1741-6612.2001.tb00399.x
Caplan, S. (2005). A social skill account of problematic internet use. Journal of Communication,
55(4), 721–736.
Carr, D. (2019). Golden years? Social inequality in later life. Russell Sage Foundation.
CAST. (n.d.). The UDL guidelines. Universal Design for Learning Guidelines.
https://tinyurl.com/22ay8b62
80
Castells, M. (1996a). The information age: Economy, society and culture. Volume I—the rise of
the network society. Blackwell.
Castells, M. (1996b). The information age: Economy, society and culture. Volume II—the power
of identity. Blackwell.
Castells, M. (1996c). The information age: Economy, society and culture. Volume III—end of
millennium. Blackwell.
Centers for Disease Control National Center for Health Statistics (2020, January). Changes in
life expectancy at birth, 2010–2018. https://www.cdc.gov/nchs/data/hestat/life-
expectancy/lifeexpectancy-H.pdf
Centers for Disease Control and Prevention. (2021, January 28). The social-ecological model: A
framework for prevention Violence Prevention Injury Center CDC.
https://www.cdc.gov/violenceprevention/about/social-ecologicalmodel.html
CEO Act!on for Diversity and Inclusion. (n.d.). FAQs. https://www.ceoaction.com/faqs/
Cheeseman Day, J., Janus, A., & Davis, J. (2005). Computer and internet use in the United
States: 2003. U.S. Census Bureau Current Population Reports, 1–14.
Cheng, T. L., Moon, M., & Artman, M. (2020). Shoring up the safety net for children in the
COVID-19 pandemic. Pediatric Research, 88, 349–351. https://doi.org/10.1038/s41390-
020-1071-7
Chinn, H., & Yu, A. (2021, March 1). I’m trying to sign up for the COVID vaccine, but I’m not
good with computers. Help! WHYY.org. https://whyy.org/articles/im-trying-to-sign-up-
for-the-covid-vaccine-but-im-not-good-with-computers-help/
81
Choi, E., Kim, Y., Chipalo, E., & Lee, H. (2020). Does perceived ageism widen the digital
divide? And does it vary by gender? The Gerontologist, 60(7), 1213–1223.
https://doi.org/10.1093/geront/gnaa066
Clay, R. A. (2000). Linking up online. Monitor on Psychology, 31(4), 20–23.
Cornwell, B., Laumann, E., & Schumm, L. (2008). The social connectedness of older adults: A
national profile. American Sociological Review, 73(2), 185–203.
Cotten, S., Yost, E., Berkowsky, R., Winstead, V., & Anderson, W. (2016). Designing
technology training for older adults in continuing care retirement communities. CRC
Press.
Coughlin, J. (2017). The longevity economy: Unlocking the world’s fastest-growing, most
misunderstood market. Hachette Book Group.
Coughlin, J. (2018a). The longevity economy: Why seniors are a fast-growing emerging market.
Barron’s. https://www.barrons.com/articles/seniors-have-spending-power-especially-as-
life-spans-lengthen-1544226021
Coughlin, J. (2018b). The rise of the longevity economy. Barron’s, 98(50), 38. https://www-
proquest-com.libproxy2.usc.edu/docview/2153597660?accountid=14749
Couldry, N., Rodriguez, C., Bolin, G., Cohen, J., Volkmer, I., Goggin, G., & Lee, K. (2018).
Media, communication and the struggle for social progress. Global Media and
Communication, 14(2), 173–191.
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed
methods approaches. Sage Publications.
Crosby, F. (1976). Model of egotistical relative deprivation. Psychological Review, 83(2), 85–
113.
82
Cuddy, A., Norton, M., & Fiske, S. (2005). This old stereotype: The pervasiveness and
persistence of the elderly stereotype. Journal of Social Issues, 61(2), 267–85.
Culen, A. (2015, August 2–7). Later life: Living alone, social connectedness and ICT. [Paper
presentation]. Digital Human Modeling 2015. Applications in Health, Safety,
Ergonomics and Risk Management: Ergonomics and Health. Los Angeles, CA.
https://doi.org/10.1007/978-3-319-21070-4_40
Culen, A., & Bratteteig, T. (2013, February 24–March 1). Touch-screens and elderly users: A
perfect match? [Paper presentation]. ACHI 2013: The Sixth International Conference on
Advances in Computer-Human Interactions, Nice, France. https://tinyurl.com/2bpmpvev
Culhane, D. P., Metraux, S., Byrne, T., Stino, M., & Bainbridge, J. (2013). The age structure of
contemporary homelessness: Evidence and implications for public policy. Analyses of
Social Issues and Public Policy, 13(1), 228-244. https://doi.org/10.1111/asap.12004
Curtin, S. (1972). Nobody ever died of old age. Pleasant Street Books.
Czaja, S., Boot, W., Charness, N., & Rogers, W. (2019). Designing for older adults: Principles
and creative human factors approaches (3rd ed.). CRC Press.
https://doi.org/10.1201/b22189
Czaja, S., & Lee, C. (2007). The impact of aging on access to technology. Universal Access in
the Information Society, 5(4), 341–349.
Czaja, S. J., Charness, N., Fisk, A., Hertzog, C., Nair, S., Rogers, W., & Shari, J. (2006). Factors
predicting the use of technology: Findings from the Center for Research and Education
on Aging and Technology Enhancement (CREATE). Psychology and Aging, 21, 333–
352.
83
Czaja, S., & Lee, C. (2002). Designing computer systems for older adults. In J. Jacko & A.
Sears, (Eds.), Handbook of human-computer interaction. Lawrence Erlbaum.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of
information technology. MIS Quarterly, 13, 319–340.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of
computer technology: A comparison of two theoretical models. Management
Science, 35, 982–1003.
Dayapoglu, N., Kavurmaci, M., & Karaman, S. (2016). The relationship between the problematic
mobile phone use and life satisfaction, loneliness, and academic performance in nursing
students. International Journal of Caring Sciences, 9(2), 647–652.
DeWall, N., Baumeister, R., & Judd, C. (2006). Alone but feeling no pain: Effects of social
exclusion on physical pain tolerance and pain threshold, affective forecasting, and
interpersonal empathy. Journal of Personality and Social Psychology, 91(1), 1–15.
https://doi.org/10.1037/0022-3514.91.1.1
Dijk, J. A. G. M. van. (2005). The deepening divide: Inequality in the information society. Sage
Publications.
Dilven, M. (2021, September 23). The future of Work: 7 industries where ageism is most
rampant. Ladders. https://tinyurl.com/dys4m8nc
Diversity in Tech. (n.d.). How to increase diversity in tech. https://www.diversityintech.co.uk/
Dychtwald, K., & Flower, J. (1989). Age wave: The challenges and opportunities of an aging
America. Jeremy P. Tarcher.
84
Ellis, C. D., Munnell, A. H., & Eschtruth, A. D. (2014). Falling short: The coming retirement
crisis and what to do about it. Oxford University Press.
https://doi.org/10.1093/acprof:oso/9780190218898.001.0001
Eriksson, M., Ghazinour, M., & Hammarström, A. (2018). Different uses of Bronfenbrenner’s
ecological theory in public mental health research: What is their value for guiding public
mental health policy and practice? Social Theory & Health, 16(4), 414–433.
https://doi.org/10.1057/s41285-018-0065-6
Eubanks, V. (2012). Digital dead end: Fighting for social justice in the information age. MIT
Press.
Federal Interagency Forum on Aging-Related Statistics (FIFARS). (2016). 2016 Older
Americans Key indicators of well-being. https://agingstats.gov/docs/LatestReport/Older-
Americans-2016-Key-Indicators-of-WellBeing.pdf
Finnegan, J. (2017, October 5). Vivek Murthy offers 4 steps to help end the nation’s loneliness
epidemic. https://www.fiercehealthcare.com/practices/vivek-murthy-former-surgeon-
general-loneliness-epidemic
Francis, J., Kadylak, T., Makki, T., Rikard, R., & Cotten, S. (2018). Catalyst to connection:
When technical difficulties lead to social support for older adults. The American
Behavioral Scientist, 62(9), 1167–1185. https://doi.org/10.1177/0002764218773829
Fransman, M. (2010). The new ICT ecosystem: Implications for policy and regulation.
Cambridge University Press. https://doi.org/10.1017/CBO9780511676130
Friedman, C. P. (2009) A fundamental theorem of biomedical informatics. Journal of American
Medical Informatics Association, 16(2), 169.
85
Fuss, B., Dorstyn, D., & Ward, L. (2019). Computer‐mediated communication and social support
among community‐dwelling older adults: A systematic review of cross‐sectional data.
Australasian Journal on Ageing, 38(4), e103–e113. https://doi.org/10.1111/ajag.12703
Ghilarducci, T., & Saad-Lessler, J. (2015). Explaining the decline in the offer rate of employer
retirement plans between 2003 and 2012. Industrial & Labor Relations Review, 68(4),
807–832. https://doi.org/10.1177/0019793915586383
Gibbs, G. (2018). Analyzing qualitative data. Sage.
González, A., Ramírez, M. P., & Viadel, V. (2012). Attitudes of the elderly toward information
and communications technologies. Educational Gerontology, 38(9), 585–594.
https://doi.org/10.1080/03601277.2011.595314
Greenberger, M., & Puffer, J. (1989). Facilitating health communication for the older person.
International Journal of Technology and Aging 2(2), 153–70.
Haddon, L., Mante-Meijer, E., & Loos, E. (2012). Generational use of new media. Taylor and
Francis. https://doi.org/10.4324/9781315584270
Hahn, J. A., Kushel, M. B., Bangsberg, D. R., Riley, E., & Moss, A. R. (2006). Brief report: The
aging of the homeless population—Fourteen-year trends in San Francisco. Journal of
General Internal Medicine, 21(7), 775–778. https://doi.org/10.1111/j.1525-
1497.2006.00493.x
Hampton, K. (2011). Comparing bonding and bridging ties for democratic engagement:
Everyday use of communication technologies within social networks for civic and civil
behaviors. Information, Communication & Society, (14), 510–528.
86
Hampton, K., Lee, C., & Her, E. J. (2011). How new media affords network diversity: Direct and
mediated access to social capital through participation in local social settings. New Media
& Society, (13), 1031–1049.
Hanninen, R., Taipale, S., & Luostari, R. (2020). Exploring heterogeneous ICT use among
adults: The warm experts’ perspective, New Media & Society, 23(6), 1584–1601.
Harding, S. G. (2004). The feminist standpoint theory reader: Intellectual and political
controversies. Psychology Press.
Hargittai, E., & Walejko, G. (2008). The participation divide: Content creation and sharing in the
digital age. Information, Communication & Society, 11(2), 239–256.
https://doi.org/10.1080/13691180801946150
Harris, C., Straker, L., & Pollock, C. (2013). The influence of age, gender and other information
technology use on young people’s computer use at school and home. Work, 44(1), S61–
S71. https://doi.org/10.3233/WOR-121494
Hawkley, L. C., & Cacioppo, J. T. (2010). Loneliness matters: A theoretical and empirical
review of consequences and mechanisms. Annals of Behavioral Medicine, 40, 218–227.
Hayre, C., Mü ller, D., & Scherer, M. (2020). Everyday technologies in healthcare. CRC Press.
https://doi.org/10.1201/9781351032186
Heasley, S. (2021, August 9). Google launches program to hire more people with autism.
https://www.disabilityscoop.com/2021/08/09/google-launches-program-to-hire-more-
people-with-autism/29435/
Helsper, E. (2017). The social relativity of digital exclusion: Applying relative deprivation
theory to digital inequalities. Communication Theory, 27(3), 223–242.
https://doi.org/10.1111/comt.12110
87
Hobbs, F., & Stoops, N. (2002). Demographic trends in the 20
th
century: Census 2000 special
reports. https://www.census.gov/prod/2002pubs/censr-4.pdf
Hocking, C. (2017). Occupational justice as social justice: The moral claim for inclusion.
Journal of Occupational Science, 24(1), 29–42.
https://doi.org/10.1080/14427591.2017.1294016
Hoffman, D. L., Novak, T. P., & Schlosser, A. (2000). The evolution of the digital divide: How
gaps in internet access may impact electronic commerce. Journal of Computer-Mediated
Communication, 5(3). https://doi.org/10.1111/j.1083-6101.2000.tb00341.x
Holstein, M. (1987). The EASE project brings together scientists and engineers. The Aging
Connection (June–July): 1.
Holt, B. J., & Morrell, R. W. (2002). Guidelines for website design for older adults: The ultimate
influence of cognitive factors. In Morrell, R. W. (Ed.), Older Adults, Health Information
and the World Wide Web (pp. 109–129). Erlbaum.
Holt-Lunstad, S. (2010). Social relationships and mortality risk: A meta-analytic review. PLOS
Medicine, 7(7), e1000316–e1000316. https://doi.org/10.1371/journal.pmed.1000316
Hughes, O. (2021, July 14). Older workers are missing from tech. That's a big problem for
everyone. ZDNet. https://tinyurl.com/88jv53nu
Hunsaker, A., & Hargittai, E. (2018). A review of Internet use among older adults. New Media &
Society, 20(10), 3937–3954. https://doi.org/10.1177/1461444818787348
Hunsaker, A., Nguyen, M., Fuchs, J., Djukaric, T., Hugentobler, L., & Hargittai, E. (2019). He
explained it to me and I also did it myself: How older adults get support with their
technology uses. Socius: Sociological Research for a Dynamic World, 5.
https://doi.org/10.1177/2378023119887866
88
Hyde, M., & Higgs, P. (2016). Ageing, populations and health. In Ageing and globalization (pp.
55–80). Bristol University Press.
Ioannidis, J. (2007). Limitations are not properly acknowledged in the scientific literature.
Journal of Clinical Epidemiology, (60), 324–329.
Irizarry, C., & Downing, A. (1997). Computers enhancing the lives of older people. Australian
Journal on Ageing, 16(4), 161–165.
Ivan, L., & Cutler, S. J. (2021). Ageism and technology: The role of internalized stereotypes.
University of Toronto Quarterly, 90(2), 127–139. https://doi.org/10.3138/utq.90.2.05
Ivan, L., Loos, E., & Tudorie, G. (2020). Mitigating visual ageism in digital media: Designing
for dynamic diversity to enhance communication rights for senior citizens. Societies,
10(4), 76. https://doi.org/10.3390/soc10040076
Jabareen, Y. (2009). Building a conceptual framework: Philosophy, definitions, and procedure.
International Journal of Qualitative Methods, 8(4), 49–62.
https://doi.org/10.1177%2F160940690900800406
Kaneda, T., Greenbaum, C., & Kline, K. (2020, April 13). 2020 World Population Data Sheet
Shows Older Populations Growing, Total Fertility Rates Declining. Population Reference
Bureau. https://www.prb.org/2020-world-population-data-sheet/
Kanfer, R. (1990). Motivation theory and industrial and organizational psychology. In M. D.
Dunnette & L. Hough (Eds.), Handbook of industrial and organizational psychology.
Volume 1. Theory in industrial and organizational psychology. Consulting Psychologists
Press.
Kardaras, N. (2016). Glow kids: How screen addiction is hijacking our kids—and how to break
the trance. St. Martin’s Press.
89
W.K. Kellogg Foundation. (2004, January 1). Logic model development guide.
https://www.wkkf.org/resource-directory/resources/2004/01/logic-model-development-
guide
Kiecolt-Glaser, J. K., Ricker, D., George, J., Messick, G., Speicher, C. E., Garner, W., & Glaser,
R. (1984). Urinary cortisol levels, cellular immunocompetency, and loneliness in
psychiatric inpatients. Psychosomatic Medicine, 46, 15–24.
Kirkpatrick, D., & Kirkpatrick, W. (2016). Kirkpatrick’s Four Levels of Training Evaluation.
ATD Press.
Koscher, A., Dittenberger, S., & Stainer-Hochgatterer, A. (2017). Harnessing the power of
technology to improve lives. IOS Press.
Kottorp, A., Nygård, L., Hedman, A., Ohman, A., Malinowsky, C., Rosenberg, L., Lindqvist, E.,
& Ryd, C. (2016). Access to and use of everyday technology among older people: An
occupational justice issue—but for whom? Journal of Occupational Science, (23)3, 382–
388. https://doi.org/10.1080/14427591.2016.1151457
Krendl, A. C., & Perry, B. L. (2021). The impact of sheltering in place during the COVID-19
pandemic on older adults’ social and mental well-being. The Journals of Gerontology.
Series B, Psychological Sciences and Social Sciences, 76(2), e53–e58.
https://doi.org/10.1093/geronb/gbaa110
Lam, K., Lu, A., Shi, Y., & Covinsky, K. (2020). Assessing telemedicine unreadiness among
older adults in the United States during the COVID-19 pandemic. JAMA Internal
Medicine, 180(10), 1389–1391. https://doi.org/10.1001/jamainternmed.2020.2671
Lambert, P. J. (2007). Equity (1st ed.). Elsevier JAI.
90
Lauder, W., Sharkey, S., & Mummery, K. (2004). A community survey of loneliness. Journal of
Advanced Nursing, 46(1), 88–94.
Lee, E., Depp, C., Palmer, B., Glorioso, D., Daly, R., Liu, J., Tu, X., Kim, H., Tarr, P., Yamada,
Y., & Jeste, D. (2019). High prevalence and adverse health effects of loneliness in
community-dwelling adults across the lifespan: Role of wisdom as a protective factor.
International Psychogeriatrics, 31(10), 1447–1462.
https://doi.org/10.1017/S1041610218002120
Leedahl, S. N., Brasher, M. S., LoBuono, D. L., Wood, B. M., & Estus, E. L. (2020). Reducing
ageism: Changes in students’ attitudes after participation in an intergenerational reverse
mentoring program. Sustainability, 12(17), 6870.
http://dx.doi.org.libproxy2.usc.edu/10.3390/su12176870
Levy, B., & Banaji, M. (2002). Implicit ageism. In: Ageism: stereotyping and prejudice against
older persons. MIT Press.
Levy, B., Zonderman, A., Slade, M., & Ferrucci, L. (2012). Memory shaped by age stereotypes
over time. The Journals of Gerontology Series B, Psychological Sciences and Social
Sciences, 67, 432–436. http://dx.doi.org/10.1093/geronb/gbr120
Lin, C., Shih, H., & Sher, P. (2007). Integrating technology readiness into technology
acceptance: The TRAM model. Psychology & Marketing, 24(7), 641–657.
https://doi.org/10.1002/mar.20177
Lincoln, K. (2016). Achieving health equity among older adults. The Gerontologist, 56(3), 488.
Loos, E. & Ivan, L. (2018). Visual ageism in the media. In L. Ayalon & C. Tesch-Roemer,
(Eds.), Contemporary aspects on ageism. Springer.
91
Lu, M. (2001). Digital divide in developing countries. Journal of Global Information Technology
Management, 4(3), 1–4.
Lynch, J. J. (1979). The broken heart: The medical consequences of loneliness. Basic Books.
MacKenzie, D., & Wajcman, J. (1999). The social shaping of technology (2
nd
ed.). Open
University Press.
Malinowsky, C., Kottorp, A., & Nygård, L. (2013). Everyday technologies’ levels of difficulty
when used by older adults with and without cognitive impairment—Comparison of self-
perceived versus observed difficulty estimates. Technology and Disability, 25(3), 167–
176. https://doi.org/10.3233/TAD-130380
Malinowsky, A. (2010). Ability to manage everyday technology: A comparison of persons with
dementia or mild cognitive impairment and older adults without cognitive impairment.
Disability and Rehabilitation: Assistive Technology, 5(6), 462–469.
Mannheim, I., Schwartz, E., Xi, W., Buttigieg, S., McDonnell-Naughton, M., Wouters, E., & van
Zaalen, Y. (2019). Inclusion of older adults in the research and design of digital
technology. International Journal of Environmental Research and Public Health, 16(19),
3718. https://doi.org/10.3390/ijerph16193718
Markus, H., & Kitayama, S. (2010). Cultures and selves: A cycle of mutual constitution.
Perspectives on Psychological Science, 5(4), 420–430.
https://doi.org/10.1177/1745691610375557
Marquie, J.C., Jourdan-Boddaert, L., & Huet, N. (2002). Do older adults underestimate their
actual computer knowledge? Behaviour & Information Technology, 21(4), 273–280.
Maxwell, J.A. (2013). Qualitative research design: An interactive approach (3
rd
ed.). SAGE
Publications.
92
Mayo Clinic. (2021, January 23). Telemedicine offers benefits in the COVID-19 era and beyond.
https://www.mayoclinic.org/medical-professionals/neurology-
neurosurgery/news/telemedicine-offers-benefits-in-the-covid-19-era-and-beyond/mac-
20506813
McAlpine, C. (2008). Elder abuse and neglect. Age and Ageing., 37(2), 132–133.
https://doi.org/10.1093/ageing/afn008
McDonough, C. C. (2016). The effect of ageism on the digital divide among older adults.
Gerontology & Geriatric Medicine, 2(1), 1–7. https://doi.org/10.24966/ggm-
8662/100008
McInerney, D. (2019). Motivation. Educational Psychology, 39(4), 427–429.
McNamara, T. K., & Williamson, J. B. (2019). Ageism: Past, present, and future. Routledge,
Taylor & Francis Group.
Medicare. (n.d.). What’s Medicare. https://www.medicare.gov/what-medicare-covers/your-
medicare-coverage-choices/whats-medicare
Merriam, S., & Tisdell, E. (2016). Qualitative research. Jossey-Bass.
Mick, D.G., & Fournier, S. (1998). Paradoxes of technology: Consumer cognizance, emotions,
and coping strategies. The Journal of Consumer Research, 25(2), 123–143.
https://doi.org/10.1086/209531
Miles, M.B., & Huberman, A.M. (1994). Qualitative data analysis: An expanded source book
(2
nd
ed.). Sage.
Miller, R., Michaelski, W., & Stevens, B. (1998). 21st century technologies: Promises and perils
of a dynamic future. OECD Publishing. https://doi.org/10.1787/9789264163539-en
93
MIT Age Lab. (n.d.). Consumer attitudes toward the implementation of AI into life, work and
care. https://agelab.mit.edu/artificial-intelligence-and-longevity
https://agelab.mit.edu/system/files/2020-11/Issue%20brief%20part%201%20-
%20consumer%20attitudes_FINAL_0.pdf
Mitzner, T., Boron, J., Fausset, C., Adams, A., Charness, N., Czaja, S., Dijkstra, K., Fisk, A.,
Rogers, W., & Sharit, J. (2010). Older adults talk technology: Technology usage and
attitudes. Computers in Human Behavior, 26(6), 1710–1721.
https://doi.org/10.1016/j.chb.2010.06.020
Mok, J., Choi, S., Kim, D., Choi, J., Lee, J., Ahn, H., & Song, W. (2014). Latent class analysis
on internet and smartphone addiction in college students. Neuropsychiatric Disease and
Treatment, 10, 817–828.
Mueller, J. P., & Massaron, L. (2018). Artificial intelligence for dummies. Wiley.
Münchow, H., & Bannert, M. (2019). Feeling good, learning better? Effectivity of an emotional
design procedure in multimedia learning, Educational Psychology, 39(4), 530–549.
Myers, D. (1992). The pursuit of happiness. Morrow.
National Assessment Governing Board. (2014). Information and communication technology
(ICT). https://www.nagb.gov/naep-frameworks/technology-and-engineering-
literacy/2014-technology-framework/toc/ch_2/ict.html
National Science and Technology Council. (2019, March). Emerging technologies to support an
aging population. https://tinyurl.com/twsr9a8
Nelson, T. D. (2016). Promoting healthy aging by confronting ageism. American Psychologist,
71(4), 276–282. http://dx.doi.org.libproxy2.usc.edu/10.1037/a0040221
94
Nicholson, Jr., N. (2009). Social isolation in older adults: An evolutionary concept analysis.
Journal of Advanced Nursing, 65(6), 1342–1352.
North, M. S., & Fiske, S. T. (2015). Modern attitudes toward older adults in the aging world: A
cross-cultural meta-analysis. Psychological Bulletin, 141(5), 993–1021.
https://doi.org/10.1037/a0039469
Nygård, L. (2006). Management of everyday technology assessment, META. Karolinska
Institutet. https://ki.se/en/nvs/management-of-everyday-technology-assessment-meta
Ogozalek, V. (1991). The social impacts of computing: Computer technology and the graying of
America. Social Science Computer Review, 9(4), 655–666.
Onwuegbuzie, A., Collins, K., & Frels, R. (2013). Foreword: Using Bronfenbrenner’s ecological
systems theory to frame quantitative, qualitative, and mixed research. International
Journal of Multiple Research Approaches, 7(1), 2–8.
http://libproxy.usc.edu/login?url=https://search-proquest-
com.libproxy1.usc.edu/docview/1470898076?accountid=14749
Ory, M. G., & Smith, M. L. (2020, July 7). Social isolation during COVID-19 pandemic has
hidden health risks—especially for seniors. Chicago Tribune. https://www-proquest-
com.libproxy2.usc.edu/docview/2420528522?accountid=14749
Padilla, M. (2020, June 10). Isolated older adults find a lifeline on the phone. New York Times,
A4(L). https://tinyurl.com/djabypsy
Parasuraman, A. (2000). Technology readiness index (TRI) a multiple-S use scale to measure
readiness to embrace new technologies. Journal of Service Research, 2(4), 307–320.
95
Parasuraman, A., & Colby, C. (2015). An updated and streamlined technology readiness index:
TRI 2.0. Journal of Service Research: JSR, 18(1), 59–74.
https://doi.org/10.1177/1094670514539730
Patton, M. Q. (2015). Qualitative research and evaluation methods (4
th
ed.). Sage.
Payscale. (2020). By the numbers: Comparing tech employee salary, age, stress and more.
https://www.payscale.com/data-packages/top-tech-companies-compared/tech-salaries
Porter, C., & Donthu, N. (2006). Using the technology acceptance model to explain how
attitudes determine Internet usage: The role of perceived access barriers and
demographics. Journal of Business Research, 59(9), 999–1007.
https://doi.org/10.1016/j.jbusres.2006.06.003
Price, J., & Murnan, J. (2004). Research limitations and the necessity of reporting them.
American Journal of Health Education, 35(2), 66–67.
https://doi.org/10.1080/19325037.2004.10603611
Ra, C. K., & Cho, Y. (2013). Differentiated effects of social participation components on
suicidal ideation across age groups in South Korea. BMC Public Health, 13(1), 890.
Raven, S. (2021). Why does this matter? The value of intersectionality. Cultural Studies of
Science Education. https://doi.org/10.1007/s11422-020-10007-7
Reeve, J. (2016). A grand theory of motivation: Why not? Motivation and Emotion, 40(1), 31–
35. https://doi.org/10.1007/s11031-015-9538-2
Rhinehart, S., & Geras, M. (2020). Diversity and power: Selection method and its impacts on
state executive descriptive representation. State Politics & Policy Quarterly, 20(2), 213–
233. https://doi-org.libproxy1.usc.edu/10.1177%2F1532440019891982
96
Rogers, W. A., & Fisk, A. D. (2000). Human factors, applied cognition and aging. In F. I. Craik
& T. A. Salthouse (Eds.), Handbook of Aging and Cognition (pp. 559–591). Erlbaum.
Rokach, A. (2019). The psychological journey to and from loneliness: Development, causes, and
effects of social and emotional isolation. Elsevier Science & Technology.
Rosen, I., & Weil, M. (1995). Adult and teenage use of consumer, business, and entertainment
technology: Potholes on the information superhighway. Journal of Consumer Affairs,
29(1), 55–84.
Ryan, R., & Deci, E. (2000). Self-determination theory and the facilitation of intrinsic
motivation, social development, and well-being. American Psychologist., 55(1), 68–78.
https://doi.org/info:doi/
Salkind, N. J. (2014). Chapter 6: Just the truth. In Statistics for people who (think they) hate
statistics. (pp. 105–128). Sage.
Samuel, L. (2017). Aging in America: A cultural history. University of Pennsylvania Press.
Sanders, D. & Gegov, A. (2013). AI tools for use in assembly automation and some examples of
recent applications. Assembly Automation, 33(2), 184–194.
https://doi.org/10.1108/01445151311306717
Schecter, A., Wowak, K., Berente, N., Ye, H., & Mukherjee, U. (2021). A behavioral perspective
on service center routing: The role of inertia. Journal of Operations Management.
https://doi.org/10.1002/joom.1156
Scott, H. (1999a, August 22–26). Information and older people—present and future [Paper
presentation].STRAIT to the Future: The 8th Asia-Pacific Specials, Health and Law
Librarians’ Conference, Hobart, Tasmania, Australia.
97
Scott, H. (1999b). Seniors in cyberspace: Older people and information, Strategic Ageing, 99(8),
47.
Selwyn, N. (2004a). Reconsidering political and popular understandings of the digital divide.
New Media & Society, 6(3), 341–362. https://doi.org/10.1177/1461444804042519
Selwyn, N., Gorard, S., Furlong, J., & Madden, L. (2003). Older adults’ use of information and
communications technology in everyday life. Ageing and Society, 23, 561–582.
http://dx.doi.org.libproxy1.usc.edu/10.1017/S0144686X03001302
Selwyn, N. (2004b). The information aged: A qualitative study of older adults’ use of
information and communications technology. Journal of Aging Studies, 18(4), 369–384.
https://doi.org/10.1016/j.jaging.2004.06.008
Senkbeil, M. (2017). Motivational factors predicting ICT literacy: First evidence on the structure
of an ICT motivation inventory. Computers & Education, 108, 145–158.
Seyfzadeh, A., Haghighatian, M., & Mohajerani, A. (2019). Social isolation in the elderly: The
neglected issue. Iranian Journal of Public Health, 48(2), 365–366.
https://doi.org/10.18502/ijph.v48i2.844
Sheldrake, R. (2016). Confidence as motivational expressions of interest, utility, and other
influences: Exploring under-confidence and over-confidence in science students at
secondary school. International Journal of Educational Research, 76, 50–65.
Shelton, L. (2019). The Bronfenbrenner primer. Routledge.
Singh, S., & Bajorek, B. (2014). Defining elderly in clinical practice guidelines for
pharmacotherapy. Pharmacy Practice, 12(4), 489.
98
Smith, S. (2020). Combatting social isolation among older adults in a time of physical
distancing: The COVID-19 social connectivity paradox. Frontiers in Public Health, 8,
403–403. https://doi.org/10.3389/fpubh.2020.00403
Sommerlad, A., Marston, L., Huntley, J., Livingston, G., Lewis, G., Steptoe, A., & Fancourt, D.
(2021). Social relationships and depression during the COVID-19 lockdown:
Longitudinal analysis of the COVID-19 Social Study. Psychological Medicine, 1–10.
https://doi.org/10.1017/S0033291721000039
Sor, J. (2021, August 30). Tech firms move slowly after pledge to boost diversity. San Francisco
Chronicle. https://tinyurl.com/j26mmj49
Steinberg, M., Walley, L., Najman, J., & Donald, K. (1999, July 13–16). Connected or
disconnected? Are older people being marginalized through modern communication
technologies? [Paper presentation]. Fourth International Conference on Communication,
Ageing and Health: Communication for All Ages, Gold Coast, Queensland, Australia.
Stewart, T., Chipperfield, J., Perry, R., & Weiner, B. (2012). Attributing illness to “old age”:
Consequences of a self-directed stereotype for health and mortality. Psychology &
Health, 27, 881–897. http://dx.doi.org/10.1080/08870446.2011.630735
Stone, W. (2021, February 4). “Just cruel”: Digital race for COVID-19 vaccines leaves many
seniors behind. National Public Radio. https://www.npr.org/sections/health-
shots/2021/02/04/963758458/digital-race-for-covid-19-vaccines-leaves-many-seniors-
behind
Swartz, T. H., Palermo, A.-G. S., Masur, S. K., & Aberg, J. A. (2019). The science and value of
diversity: Closing the gaps in our understanding of inclusion and diversity. The Journal
99
of Infectious Diseases, 220 (Supplement 2), S33–S41.
https://doi.org/10.1093/infdis/jiz174
Szabo, A., Allen, J., Stephens, C., & Alpass, F. (2019). Longitudinal analysis of the relationship
between purposes of internet use and well-being among older adults. The Gerontologist,
59(1), 58–68.
Talking alone: Researchers use artificial intelligence tools to predict loneliness. (2020, October
17). Psychology & Psychiatry Journal, 2173. Retrieved July 4, 2021, from
https://link.gale.com/apps/doc/A638063518/HWRC?u=usocal_main&sid=HWRC&xid=
4c5a1ac1
Tay, A. (2001). Is there a slow lane on the information superhighway? Issues of exclusion and
discrimination confronting older people in the information age. Australasian Journal on
Ageing, 20.3 (Supplement 2), 42–49.
The State of New Mexico. (2020, March 31). 350 tablets distributed to nursing facilities across
the state to improve communications for residents and their loved one.
https://www.newmexico.gov/2020/03/31/350-tablets-distributed-to-nursing-facilities-
across-the-state-to-improve-communications-for-residents-and-their-loved-one/
Thielke, S., Harniss, M., Thompson, H., Patel, S., Demiris, G., & Johnson, K. (2011). Maslow’s
hierarchy of human needs and the adoption of health-related technologies for older
adults. Ageing International, 37(4), 470–488. https://doi.org/10.1007/s12126-011-9121-4
Torres, S., & Hammarstrom, G. (2009). Successful aging as an oxymoron: Older people—with
and without home-help care—talk about what aging well means to them. International
Journal of Ageing and Later Life, 4(1), 23–54.
100
Townsend, E. A., & Wilcock, A. A. (2004). Occupational justice. In C. H. Christiansen & E. A.
Townsend (Eds.), Introduction to occupation: The art and science of living (pp. 243–
273). Prentice Hall.
University of Exeter. (2021, January 22). Covid lockdown loneliness linked to more depressive
symptoms in older adults. Science Daily.
https://www.sciencedaily.com/releases/2021/01/210122084936.htm
U.S. Census Bureau. (2018, September 6). Older people projected to outnumber children.
https://www.census.gov/newsroom/press-releases/2018/cb18-41-population-
projections.html
U.S. Census Bureau. (2019, December 10). 2020 census will help policymakers prepare for the
incoming wave of aging boomers. https://www.census.gov/library/stories/2019/12/by-
2030-all-baby-boomers-will-be-age-65-or-older.html
Varma, T. (2015). Agile product development: How to design innovative products that create
customer value. Apress.
Vaughn, G., Faucett, R., & Lightfoot, R. (1984). Communication outreach: Delivery systems and
devices. In R. Dunkle, M. Haug, & M. Rosenberg (Eds.), Communication technology and
the elderly (pp. 107–22). Springer.
Vélez-Agosto, N., Soto-Crespo, J., Vizcarrondo-Oppenheimer, M., Vega-Molina, S., & García
Coll, C. (2017). Bronfenbrenner’s bioecological theory revision: Moving culture from the
macro into the micro. Perspectives on Psychological Science, 12(5), 900–910.
https://doi.org/10.1177/1745691617704397
Verizon. (2020, July 13).Verizon powers intuitive customer experiences with Google Cloud.
Verizon. https://www.verizon.com/about/news/verizon-customer-google-cloud
101
Vogels, E. (2021, June 22). Digital divide persists even as Americans with lower incomes make
gains in tech adoption. Pew Research Center. https://www.pewresearch.org/fact-
tank/2021/06/22/digital-divide-persists-even-as-americans-with-lower-incomes-make-
gains-in-tech-adoption/
Walsh, K., Scarf, T., & Keating, N. (2017). Social exclusion of older persons: A scoping review
and conceptual framework. European Journal of Ageing, 14, 81–98.
Williams, R., & Edge, D. (1996). The social shaping of technology. Research Policy, 25(6),
865–899. https://doi.org/10.1016/0048-7333(96)00885-2
Wilson, C., & Moulton, B. (2010). Loneliness among older adults: A national survey of adults
45+. Prepared by Knowledge Networks and Insight Policy Research. American
Association of Retired Persons. https://tinyurl.com/yemnj2cn
World Health Organization. (2020, December 14). Decade of healthy ageing: Plan of action.
https://www.who.int/publications/m/item/decade-of-healthy-ageing-plan-of-action
Wright, D., & Hill, T. (2009). Prescription for trouble: Medicare part D and patterns of computer
and internet access among the elderly. Journal of Aging & Social Policy, 21(2), 172–186.
Yi, E., & Hwang, H. (2015). A study on the social behavior and social isolation of the elderly
Korea. Journal of Exercise and Rehabilitation, 11(3), 125–132. https://www.e-
jer.org/journal/view.php?number=2013600195
Yoon, S., & Cummings, S. (2019). Factors protecting against suicidal ideation in South Korean
community-dwelling older adults: A systematic literature review. Journal of
Gerontological Social Work, 62(3), 279–305.
https://doi.org/10.1080/01634372.2018.1557310
102
Yuen, A. H. K., Park, J. H., Chen, L., & Cheng, M. (2017). Digital equity in cultural context:
Exploring the influence of Confucian heritage culture on Hong Kong families.
Educational Technology Research and Development, 65(2), 481–501.
https://doi.org/10.1007/s11423-017-9515-4
Zajicek, M. (2004). Successful and available: Interface design exemplars for older users.
Interacting with Computers, 16, 411–430. https://www-sciencedirect-
com.libproxy2.usc.edu/science/article/pii/S0953543804000402
103
Appendix A: Ethics
To mitigate any concerns from study participants regarding confidentiality, consent, and
compensation/incentives, the researcher emailed a one-page document to all 15 interview
participants. The document covered the following points:
1. The purpose of this interview is to gain valuable insights about older adults and their
interactions with Information and Communications Technology.
2. The interview helps satisfy the requirements related to Kim Nguyen pursuing a
doctorate through the University of Southern California Rossier School of Education.
3. The individual participating in the interview is doing so of their free will.
4. The individual is not compensated for their time and is not receiving any gifts or
benefits in exchange for their participation.
5. At any time, the individual can choose to stop participating in the interview.
6. While information will be used to understand the issue better, the study participants’
names will not be shared or published.
7. To avoid misquoting the participant, the researcher requests permission to record the
conversation.
8. After the study and upon request, study findings can be shared at an aggregate level.
9. Confirmation of date and time of the interview.
10. Zoom meeting details for the participant.
These steps were completed before the interview process began. Additionally, at the
beginning of each interview, I summarized the objectives of my study, asked participants if they
had any questions, and requested oral consent before the interview and recording began.
104
The research conducted in my study gave older adults a voice and provided insights into
their needs, preferences, relationships to ICT, and barriers to ICT. The research findings will be
shared with technology companies to encourage their design, software, and product development
teams to create tools with older adults in mind.
105
Appendix B: Limitations and Delimitations
Study limitations are described as systematic bias that the researcher did not or could not
control. Study delimitations are intentionally introduced to the study design or instrument by the
researcher (Price & Murnan, 2004).
Knowledge and discussion of limitations are essential for genuine scientific progress:
they are useful for understanding a research finding, translating the importance of the
potential errors involved, placing the current work in context, and ascribing a credibility
level to it. Limitations are also likely to reveal how the current research work may be
improved in future experiments and what caveats should be considered in trying to
incorporate this new information in the evolving body of scientific evidence (Ioannidis,
2007, p. 324).
Limitations of my study include the following:
● As the researcher, I have inherent biases. While I attempted to mitigate these
biases and include other perspectives obtained in literature reviews, my
positionality must be considered.
● The study assumed that older adults want to live life in a socially connected
manner and have access to resources that improve their quality of life.
● The study focused on older adults living in the United States. Some of the
literature cited references studies outside the United States. Given microsystem,
exosystem, and macrosystem influences, findings in another country will likely be
different from the experience of older adults living in the United States.
● The study relied on convenience sampling. Sampling based on convenience alone
could result in poor data quality (Merriam & Tisdale, 2016).
106
● Only 15 older adults living in the United States were interviewed. While
plausible, the findings cannot be extrapolated and assumed to be true of all older
adults living in America.
● All 15 interview participants were college-educated; 11 held advanced degrees.
● The study assumed participant honesty.
● My study focused on ICT, i.e., high-speed internet, desktop and laptop
computers, tablets, and smartphones; all other technologies were excluded.
● The technology manufacturers’ perspective is not reflected in my study. The
limited number of products geared toward older adults would suggest that ICT is
not designed for older adults. My study will not validate or disprove this
assumption.
107
Appendix C: Credibility and Trustworthiness
I employed several strategies to maximize the credibility and trustworthiness of the
qualitative data. Interview instructions were standardized, and the same process was followed
before each of the 15 interviews. I sent each participant an email outlining the purpose of the
study. The letter included my contact information, my dissertation chair’s information, and a
phone number and email for USC’s Office for the Protection of Research Subjects. Additionally,
upon the conclusion of each interview, I conducted participant validation or member checks.
Member checks are “the single most important way of ruling out the possibility of
misinterpreting the meaning of what participants say and do...as well as being an important way
of identifying your own biases and misunderstanding of what you observed” (Maxwell, 2013, pp.
126–127).
Merriam and Tisdell (2016) described triangulation as one of the best strategies to
improve a study’s internal validity. Maxwell (2013) defined triangulation as using various data
collection methods to reach the same conclusion. I used multiple theories to understand the
barriers that prevent older adults from using everyday technologies. Additionally, I conducted an
extensive literature review and gained perspectives from 15 interview participants. I observed
participants who chose to use video conferencing for their interviews; this enabled me to gain
additional insights. Field notes from interviews were recorded and reviewed.
Salkind (2014) stated that lowering mistakes and errors increases reliability. Internal
reliability was expected because the same interview process was used and followed for all phone
or video conference interviews. The sampling strategy should meet credibility criteria due to the
number of interviews that were completed.
108
The researcher’s positionality includes the fact that I am the youngest daughter of a
couple married for nearly 62 years. My father was an electrical and computer engineering
professor. Given his education and training, he was very comfortable with technology, used
many forms of technology throughout his life, and continued until he died in 2018. He handled
financial matters, including filing tax returns, paying bills, and writing email correspondence to
family and friends. My mother was an English as a Second Language teacher and only a
moderate technology user, both professionally and personally.
After my father died, my mother needed to handle the duties my father previously
managed. In many cases, these matters involved the use of technology, apps, and passwords. I
saw how challenging technology was for my mother and how difficult it was to help her log in to
devices and use them from afar. It was these experiences that motivated me to study the problem
of practice.
Given these biases, I attempted to mitigate potential assumptions and biases by asking
several classmates to review the interview questions and the raw survey data. Peer review will
help determine if the findings and conclusions are plausible (Merriam & Tisdale, 2016).
…although a wide variety of interpretations and descriptions presented by researchers
may be possible, some of these will be clearly biased or partial, and some may even be
downright silly or wrong. There may be no absolute truth, but there can still be error
(Gibbs, 2018, p. 129).
Patton (2015) stated that qualitative analysts do not have a statistical test to determine
significant observation or pattern. Researchers must rely on their sense-making, judgment, and
understandings. The researcher must provide substantive details and documentation that support
conclusions (Merriam & Tisdale, 2016).
109
Appendix D: Participating Stakeholders, Sampling Criteria and Rationale
There were criteria for selecting interview participants:
• The individual must be 65 years or older, reside in the United States, and be
conversant in English.
• The individual must live independently (not in a facility requiring care), alone, or
with others.
Interview Sampling (Recruitment) Strategy and Rationale
Merriam and Tisdale (2016) stated that the sample size depends on various factors,
including questions to be asked, data gathered, the analysis, and resources available to support
the study. I looked to my dissertation committee to guide the target sample size.
For my study, I used a qualitative approach to gather data from adults ages 65 and older. I
interviewed 15 participants via either phone or videoconferencing technology and strived to
develop a complex, holistic view of the problem. The participants were interviewed in their
natural settings.
I employed a convenience/network recruitment approach to identify study participants.
This approach was appropriate given COVID-19, the target audience, and the short amount of
time I had to conduct research.
110
Appendix E: Information Sheet for Exempt Research
University of Southern California
Rossier School of Education
3470 Trousdale Parkway, Los Angeles, CA 90089
STUDY TITLE: Older Adults and Barriers to Information and Communications Technology
PRINCIPAL INVESTIGATOR: Kim Nguyen
FACULTY ADVISOR: Patricia Tobey, Ph.D.
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
a. This study aims to understand how adults 65 and older use Information and
Communications Technology (ICT). ICT in this study will be limited to
desktop/laptop computers, the internet, smartphones, and tablets.
b. We hope to learn about the:
i. system influences that shape the perceptions and behaviors of adults 65 and
older as related to ICT;
ii. experience older adults have in using the internet and how they receive
help when needed;
iii. perceptions, behaviors, and physical barriers that prevent older adults from
using ICT.
You are invited as a possible participant because you meet the criteria of being 65 years or older
and do not live in an assisted living facility.
PARTICIPANT INVOLVEMENT
The interview will use Zoom, with a dial-in function for telephone only or a link with full audio
and video capability. Upon participant consent, the conversation will be recorded. The interview
will take approximately 45 minutes. If at any time you wish to stop the interview, it is your
choice to do so. Similarly, you can decline to be recorded and continue your participation in this
study.
If you decide to participate, you will be asked to confirm your interest and call or join the
meeting link on the date and time we schedule.
111
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.
To protect the confidentiality of participants, the following steps will be taken:
i. The laptop used for the interviews is password protected and uses facial recognition to
unlock the laptop
ii. The researcher is the only user of the laptop; nobody else knows the password
iii. All transcripts will contain no personally identifiable information (e.g., name, age,
locations, etc.)
iv. You have the right to review/edit the audio/video recording or transcript. Please let me
know if this is something you are interested in doing.
v. Once the transcripts are verified, the researcher will delete any video files from the
Zoom portal
vi. The recorded transcripts will be downloaded from Zoom and saved to the researcher’s
USC Google Drive account, which is a private strong password account and is not
shared
vii. Pseudonyms will be used for all interview participants to further ensure confidentiality
viii. Identifiable information will be deleted from the transcripts
ix. Upon a successful final defense and dissertation publication, all interview files and
correspondence will be deleted no later than December 31, 2021.
INVESTIGATOR CONTACT INFORMATION
If you have any questions about this study, please contact Kim Nguyen, ktn@usc.edu, or Patricia
Tobey, Ph.D., faculty advisor, tobey@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.
112
Appendix F: Letter to Interview Participants
Date
Dear [insert participant name]:
Thank you for your willingness to meet with me, help me with my research study, and share your
perspectives on using technology. As agreed, we will be meeting at [insert date and time]. Please
call this number [insert phone number].
I estimate that our conversation will take between 45 and 60 minutes. I will be asking you
questions about how you use technology, what prevents you from using it, and if you have any
recommendations for improving your interactions and experiences with technology. To ensure I
accurately capture your comments, I would like to record our conversation. You will not be
identified in my research study, and your thoughts and statements will remain anonymous and
will not be attributed to you.
Your participation in my study is entirely voluntary. I will not be compensating you for your
time. If you want to end the meeting during our conversation, for whatever reason, that is your
choice.
If you need to reach me before we meet, please call me [insert cell number] or email me [insert
email address].
For your information, I’m including contact information for my dissertation chair [insert email
address] and USC’s Office for the Protection of Research Subjects, 323-442-0114, irb@usc.edu.
Also, upon completion of my research study, I am happy to share the findings with you.
Thank you for your time, and I look forward to speaking with you!
Sincerely,
Kim Nguyen
[insert cell number and email address]
113
Appendix G: Interview Protocol
Background and Purpose
● You should have received a letter from me with all the information about today’s
interview. Let me quickly review the main points again.
● My school coursework requires that I conduct an original research project. My study
focuses on older adults and their experiences with technology and the internet.
● My goal is to understand three things:
• How do you use technology?
• What barriers prevent you from using these devices and the internet?
• How can your interactions with technology be improved?
● There are no right or wrong answers and no good or bad answers. I want to hear about
your experiences. Everything you share with me will remain confidential. I will not
publish your name or anything that identifies you when analyzing your interview or
writing about my findings.
Interview Logistics
● I will record our conversation with your permission so that I am sure I don’t misquote
you.
● Is that okay with you? May I begin recording?
● I estimate that our interview will take between 45 and 60 minutes. If you need a break
during our conversation, we can take one.
Participant Rights and Agreement
● If at any time you wish to end this interview, you are free to do so.
● Similarly, if at any time you want to take a break, please let me know.
114
● If you’d like to follow up with me later about my findings after I’ve concluded all my
interviews, you are welcome to do so.
● Do you have any questions for me about everything that I just covered?
● Okay, are you ready to get started?
115
Appendix H: Theoretical Framework Alignment Matrix
Research question Theoretical framework Interview questions
How do older adults use
Information and
Communications
Technology (ICT)?
Ecological systems model
Relative deprivation theory
Technology readiness and
acceptance model
2–11
8, 10
6–11
What barriers prevent older
adults from using
Information and
Communications
Technology?
Ecological systems model
Relative deprivation theory
Technology readiness and
acceptance model
1–14
8–11
8–14
What are the recommended
practices for technology
companies to improve
Information and
Communications
Technology for older
adults?
Ecological systems model
Relative deprivation theory
Technology readiness and
acceptance model
5–14
8–10
8–14
Demographic Questions NA 1–6
116
Appendix I: Interview Questions
Personal Demographics
1. What’s your preferred gender identity? (male, female, non-binary)
2. Do you live alone or with others?
3. Please tell me your age?
4. What is your race?
5. In general terms, please describe any disabilities you have that impact your ability to
use the following forms of technology, i.e., desktop/laptop computer, internet,
smartphone, and tablet?
6. What is the highest level of education you completed?
7. Can you tell me about your employment, volunteer work, or how you spend most of
your time?
Technology Use and Barriers
8. Consider the following forms of technology, i.e., desktop/laptop computer, internet,
smartphone, and tablet. Which of these do you use, and how do you use them?
9. Tell me how you use any of the following technologies, i.e., desktop/laptop computer,
internet, smartphone, and tablet, to stay connected with others?
10. How confident do you feel when using these technologies, i.e., desktop/laptop
computer, internet, smartphone, and tablet?
11. When and how did you learn to use these various forms of technology, i.e.,
desktop/laptop computer, internet, smartphone, and tablet?
12. Of the ICT technologies you don’t own, what barriers prevent you from using them?
117
13. Tell me about problems you may encounter when using any of the technologies
we’ve discussed, i.e., desktop/laptop computer, internet, smartphone, and tablet, and
what you do when you experience them?
Recommended Practices for Improving ICT
14. Referring to a desktop/laptop computer, internet, smartphone, and tablet, what would
improve your experience or interactions with these tools?
15. With you and your peers in mind, what would you like to say to the CEOs of tech
companies about designing new technology?
Closing Question
16. Is there anything else we didn’t cover that you’d like to share?
118
Appendix J: Participant Demographics
Pseudonym
Gender
identity
Age Race
Highest level of
education
Ava Female 76 White Master’s Degree
Belle Female 75 White Master’s Degree
Corinne Female 85 Asian Bachelor’s Degree
David Male 84 White Ph.D.
Emmett Male 75 White Bachelor’s Degree
Grace Female 77 Black Bachelor’s Degree
Griffon Male 67 White Bachelor’s Degree
Kelly Female 69 White Master’s Degree
Margot Female 74 White Juris Doctor
Mia Female 69 Black Master’s Degree
Michael Male 87 White Juris Doctor
Petra Female 66 White Master’s Degree
Rae Female 73 White Master’s Degree
Ryan Male 81 Hispanic Master’s Degree
Umi Female 65 Hispanic Master’s Degree
119
Appendix K: Disabilities Affecting Use of ICT
Participant Disability(ies)
Gender
identity
Age
Belle Attention Deficit Disorder, Dyslexia Female 75
Corinne Cataracts, Hearing Female 85
David Hearing Male 84
Michael Hearing Male 87
Umi Glaucoma Female 65
Note. Age was not a determinant of disability status; Umi was the youngest participant.
120
Appendix L: Participant Age and Employment Status
Participant Age Employment status
Ava 76 Retired
Belle 75 Retired
Corinne 85 Retired
David 84 Retired
Emmett 75 Retired
Grace 77 Retired
Griffon 67 Retired
Kelly 69 Retired
Margot 74 Retired
Mia 69 Retired
Michael 87 Retired
Petra 66 Working
Rae 73 Working
Ryan 81 Retired
Umi 65 Retired
Note. Petra worked part-time, and Rae worked full-time.
121
Appendix M: Types of ICT Used
ICT type Participants
Internet 15
Smartphone 15
Computer 14
Tablet 7
Note. All 15 participants used multiple types of ICT. All had broadband internet and used a
smartphone.
122
Appendix N: How Participants Used ICT
Use Frequency
Calls 15
Texting 14
Email 11
Videoconferencing, e.g., FaceTime, Zoom 11
Finances, e.g., banking, paying bills 9
Search engine 8
Apps, e.g., music, navigation 6
Information, e.g., news, sports, weather 5
Entertainment, e.g., games 4
Taking photos and/or videos 3
Shopping 2
Work 2
Education, e.g., taking classes 1
Reading, e.g., downloading books 1
Social media, e.g., Facebook 1
Writing 1
Note. All 15 participants cited multiple ways in which they used ICT. Most participants used ICT
to connect with others and to access information.
123
Appendix O: Average Hours ICT Used per Day
Hours Number of participants
3–5 7
1–2 6
6–8 2
Note. Of the two participants who used ICT 6–8 hours per day, one worked full-time.
124
Appendix P: Where ICT Skills Were Learned and Perceived Confidence
Participant
Gender
identity
Age How/where learned Confidence with ICT
Ava Female 76 Classes, Self-Taught Confident
Belle Female 75 Class, Friends Not Confident
Corinne Female 85 Family Not Confident
David Male 84 Work Confident
Emmett Male 75 Work, No Training Confident
Grace Female 77 Work Confident
Griffon Male 67 Classes, Work Confident
Kelly Female 69 Work, No Training Confident
Margot Female 74 Work, Family Somewhat Confident
Mia Female 69 Work Confident
Michael Male 87 Work, Training Somewhat Confident
Petra Female 66 School, Family Very Confident
Rae Female 73 School, Work Very Confident
Ryan Male 81 Work Confident
Umi Female 65 Work Confident
Note. Most participants who described themselves as confident said their confidence was limited
to familiar tasks and diminished when problems occurred.
125
Appendix Q: Problems Encountered With ICT
Problem Frequency
Software updates 7
Unintuitive interface 5
Technical language or instructions 3
Apps 2
Connectivity to the internet, printers, etc. 2
Help difficult to obtain 2
Navigation 2
Passwords 2
Processing time 2
Retrieving files 2
Advertisements 1
Device incompatibility, e.g., between Apple and PC 1
Spam 1
Syncing 1
Note. Some participants cited multiple problems encountered with ICT, including not
understanding the problem or why it was occurring.
126
Appendix R: Actions Taken When Problems With ICT Are Encountered
Action Frequency
Ask family or friends 10
Contact manufacturer tech support 4
Use a search engine to find a solution 4
Abandon task 2
Hire tech support 2
Restart device 2
Search YouTube for a solution 2
Note. Participants cited multiple actions they take when encountering problems with ICT. Even
the least confident users attempted to solve the problems on their own before asking others for
help.
127
Appendix S: Messages to CEOs of Technology Firms
Theme Participant example quote
Simplify and create an
intuitive, user-
friendly experience.
“Advertising is everywhere. It’s very interruptive. I’ll be reading a
story, and all of a sudden an ad pops up right between each
paragraph.” (Grace, age 77)
“I don’t like the ads. I understand the need for them, but they are a
turnoff for me. I use an ad blocker. I’ve never bought anything on a
whim as a result of seeing an advertisement.” (David, age 85)
“When changes are made, they seem to be motivated by sales and
encouraging consumers to spend money. Phone chargers used to be
round, and now they’re flat. They just want you to keep spending
money for more equipment.” (Grace, age 77)
“Minimize the complexity of some steps and consider physical
issues…ensure continuity so every time you want to open it, it’s
going to be right here, and every time you want to close it, it’s going
to be right here.” (Petra, age 66)
“Make your products and services more user-friendly to the non-tech
population. Apple and Microsoft don’t work together as well as they
should. Even the functionality between Microsoft Office for Mac is
different [than the version for a PC].” (Griffon, age 67)
128
Theme Participant example quote
Involve older adults in product design and
solutions.
“Older adults have been forgotten. So many
older people who don’t know anything [about
technology] have been left out.” (Ryan, age 81)
“Older adults are a group that I now identify
with, and we need some attention.” (Kelly, age
69)
“In designing and building things, be smart and
get information from users…U.S. designers say
this is what you need whereas Japanese
designers ask what is it you need?” (Ryan, age
81)
“My biggest complaint is that I feel there’s no
interaction with software programmers. They
think they know better and know what we want,
and they don’t.” (Petra, age 66)
“Ask an older person to provide instructions for
older people.” (Ava, age 76)
129
Theme Participant example quote
Be proactive in training
users and non-users.
“Show me how to safely use technology.” (Ryan, age 81)
“I feel uneasy about some apps such as Facebook and PayPal. I’m
not sure if this is reality-based, but it stands in the way of my use of
other apps.” (Rae, age 73)
“Many older adults say, ‘I’ve lived without it [technology] I don’t
need it.’ But it’s a valuable resource.” (Umi, age 65)
Make getting help easy
and accessible.
“Consider doing outreach in various languages and promoting free
[technology help] services.” (Umi, age 65)
“Churches can play a role. School districts can offer classes. Family
members and kids can help.” (David, age 85)
130
Appendix T: Alignment Between Recommendations and Conceptual Framework
Recommendation System influence Theory(ies) and model
Simplify and create an
intuitive, user-friendly
experience
Exosystem,
Macrosystem
Bronfenbrenner’s ecological systems
theory, technology readiness acceptance
model, relative deprivation theory
Involve older adults in
product design and
solutions
Exosystem,
Macrosystem
Bronfenbrenner’s ecological systems
theory, technology readiness acceptance
model
Be proactive in training
users and non-users
Exosystem,
Macrosystem
Bronfenbrenner’s ecological systems
theory, technology readiness acceptance
model
Make getting help easy and
accessible
Exosystem,
Macrosystem
Bronfenbrenner’s ecological systems
theory, technology readiness acceptance
model
Abstract (if available)
Linked assets
University of Southern California Dissertations and Theses
Conceptually similar
PDF
COACH: Connecting Older Adults to Community for Health - an evidence-based program to address older adult social isolation and loneliness
PDF
Leveraging the principalship for instructional technology equity and access in two urban elementary schools
PDF
Improving graduation equity in community colleges: a study on California Assembly Bill 705 policy implementation
PDF
Financial inequity and the impact of acquiring technology competency within the emergency medical service community
PDF
Palliative care: breaking the knowledge barrier among community-based older adults
PDF
An examination of soft skills in the virtual workplace
PDF
Training qualified rural area teachers in Malawi using synchronous virtual learning (SVL) information and communication technologies (ICTs) platforms
PDF
Food insecurity and the impact on community college students
PDF
Educational technology integration: a search for best practices
PDF
Indonesian teachers' adoption of technology in the K-12 classroom: a TAM-based quantitative study
PDF
My Life, My Wishes, a death education program for community-dwelling Chinese older adults: development and pilot testing
PDF
Using technology to drive high academic achievement
PDF
How are teachers being prepared to integrate technology into their lessons?
PDF
And still we rise: examining the strengths of first-generation college students
PDF
Forensic markers of physical elder abuse in medical and community contexts: implications for criminal justice interventions
PDF
What university equity and diversity leaders are doing to deal with issues of equity, access, and inclusion
PDF
Black and [mis]educated: the Black American adult’s perspective of the U.S. K–12 public school system
PDF
Equity and access for veteran's students in the California community colleges
PDF
Collective impact addressing social isolation for older adults living independently in the community; a capstone innovation project
PDF
Addressing systemic challenges in elementary-school teacher preparation in science, technology, engineering, and mathematics
Asset Metadata
Creator
Nguyen, Kim Thu
(author)
Core Title
College-educated older adults and information and communications technology
School
Rossier School of Education
Degree
Doctor of Education
Degree Program
Organizational Change and Leadership (On Line)
Degree Conferral Date
2021-12
Publication Date
10/19/2021
Defense Date
08/31/2021
Publisher
University of Southern California
(original),
University of Southern California. Libraries
(digital)
Tag
Ageism,Bronfenbrenner’s ecological systems model,digital divide,elder abuse,elder justice,equity,information and communications technology adoption,information and communications technology competence,OAI-PMH Harvest,older adults,relative deprivation theory,social connection,social isolation,technology readiness and acceptance model
Format
application/pdf
(imt)
Language
English
Contributor
Electronically uploaded by the author
(provenance)
Advisor
Tobey, Patricia (
committee chair
), Hinga, Briana (
committee member
), Maddox, Anthony (
committee member
)
Creator Email
ktn@usc.edu,sfkim2@gmail.com
Permanent Link (DOI)
https://doi.org/10.25549/usctheses-oUC16251441
Unique identifier
UC16251441
Legacy Identifier
etd-NguyenKimT-10173
Document Type
Dissertation
Format
application/pdf (imt)
Rights
Nguyen, Kim Thu
Type
texts
Source
University of Southern California
(contributing entity),
University of Southern California Dissertations and Theses
(collection)
Access Conditions
The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright. The original signature page accompanying the original submission of the work to the USC Libraries is retained by the USC Libraries and a copy of it may be obtained by authorized requesters contacting the repository e-mail address given.
Repository Name
University of Southern California Digital Library
Repository Location
USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA
Repository Email
cisadmin@lib.usc.edu
Tags
Bronfenbrenner’s ecological systems model
digital divide
elder abuse
elder justice
equity
information and communications technology adoption
information and communications technology competence
older adults
relative deprivation theory
social connection
social isolation
technology readiness and acceptance model