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The antecedents and consequences of believing that difficulties are character-building
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Content
THE ANTECEDENTS AND CONSEQUENCES OF BELIEVING THAT
DIFFICULTIES ARE CHARACTER-BUILDING
by
Gülnaz Kiper
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(PSYCHOLOGY)
August 2023
Copyright 2023 Gülnaz Kiper
0
Acknowledgments
We gratefully acknowledge the John Templeton Foundation grant #61083 to Oyserman and Yan
which supported our work.
1
Table of Contents
Acknowledgments ......................................................................................................................... ii
List of Tables ................................................................................................................................ iv
List Figures .................................................................................................................................... v
Abstract ......................................................................................................................................... vi
Introduction .................................................................................................................................... 1
Chapter 1: The Upside: How People Make Sense of Difficulty Matters During a Crisis ............. 5
Abstract .............................................................................................................................. 5
Current Studies ................................................................................................................. 12
Method ............................................................................................................................. 14
Results .............................................................................................................................. 20
Discussion ........................................................................................................................ 28
Chapter 2: I’ll Take the High Road: Paths to Goal Pursuit and Identity-based Interpretations
of Difficulty .......................................................................................................................... 34
Abstract ............................................................................................................................ 34
Current Studies ................................................................................................................. 38
Results .............................................................................................................................. 45
Discussion ........................................................................................................................ 57
Chapter 3: Believing That Difficulties are Character-building Supports Wellbeing and
Positively Frames Daily Life ................................................................................................ 63
Abstract ............................................................................................................................ 63
Current Studies ................................................................................................................. 69
Method ............................................................................................................................ 72
Results .............................................................................................................................. 83
Discussion ........................................................................................................................ 95
Chapter 4: General Discussion ................................................................................................... 100
Limitations and Future Directions ................................................................................. 100
Conclusion ..................................................................................................................... 101
References .................................................................................................................................. 102
Appendix A: Measures for Chapter 1 ........................................................................................ 113
2
List of Tables
Chapter 1 Tables
Table 1: Demographic Information of Samples by Study ............................................... 15
Table 2: Study 1: Means, Standard Deviations, Cronbach’s α, and Correlations
With 95% Confidence Intervals ........................................................................... 22
Table 3: Study 2: Means, Standard Deviations, Cronbach’s α, and Correlations
With 95% Confidence Intervals ........................................................................... 23
Table 4: Study 3: Means, Standard Deviations, Cronbach’s α, and Correlations
With 95% Confidence Intervals ........................................................................... 24
Table 5: Model 1: Direct, Indirect, and Total Effects of Difficulty Mindsets on
Taking Action [95% Confidence Intervals] ......................................................... 25
Chapter 2 Tables
Table 1: Studies 1 to 3: Working on Goals, More and Less Effortful Means .................. 41
Table 2: Studies 1-3: Dependent Variables ..................................................................... 42
Table 3: Studies 1 to 3: Difficulty-Mindset Scale Statements and Descriptives ............. 43
Table 4: Testing H1 and Examining RQ1 with Less Effortful Means: Difficulty
Mindset Regression Results ..................................................................................50
Table 5: Testing H2 and Examining RQ1 with More Effortful Means: Difficulty
Mindset Regression Results ..................................................................................53
Table 6: Study 3: The Association Between Difficulty Mindsets and DVs for
Students’ Study Method ........................................................................................56
Chapter 3 Tables
Table 1: Hypotheses and Studies Testing Them .............................................................. 72
Table 2: Difficulty-as-Improvement Religious Version ................................................... 75
Table 3: Difficulty-as-Improvement Secular Version ...................................................... 76
Table 4: Meaning in Life .................................................................................................. 76
Table 5: Coherence .......................................................................................................... 77
Table 6: Self-Esteem ........................................................................................................ 78
Table 7: Life Satisfaction ................................................................................................. 79
Table 8: Effortful Engagement ......................................................................................... 79
Table 9: Success ............................................................................................................... 80
Appendix A Tables
Table A1: Difficulty Mindset Scale Items ..................................................................... 113
Table A2: Silver Linings and Actions Scale Items ........................................................ 113
Table A3: Experiences of Adversity (8 items) ............................................................... 114
Table A4: Silver Linings for Community (7-items) and Additional Actions That
Would Not Load On Onto a One- or Two-Factor Structure (Study 3) ............... 115
3
List of Figures
Chapter 1 Figures
Figure 1: Study Times Contextualized with New U.S. COVID-19 Cases
and Noteworthy Events ........................................................................................ 16
Figure 2: Hypothesized Structural Equations Model (Model 1) ...................................... 20
Figure 3: Model 1: Difficulty Mindsets Predict Taking Action via Seeing
Silver Linings for Oneself .................................................................................... 25
Figure 4: Model 2: Structural Equations Model (Unconstrained) for Democrats
(Left) and Republicans (Right) With Standardized Estimates ............................. 27
Chapter 2 Figures
Figure 1: Testing H1 and Examining RQ1 with Less Effortful Means: Difficulty
Mindset Meta-Analytic Regression Results for DV1 to DV3 ............................. 49
Figure 2: Testing H2 and Examining RQ1 with More Effortful Means: Difficulty
Mindset Meta-Analytic Regression Results for DV1 to DV3 ............................. 52
Figure 3: Study 3: Difficulty Mindsets and Likelihood of Using, Effectiveness,
and Effort Matters in Using Students’ Own Study Method ................................. 56
Chapter 3 Figures
Figure 1: Trait Difficulty-as-Improvement is Correlated With Trait Wellbeing .............. 85
Figure 2: Trait Difficulty-as-Improvement Predicts Daily Wellbeing ............................. 87
Figure 3: Trait Difficulty-as-Improvement Predicts Daily Experiences .......................... 88
Figure 4: Daily Difficulty-as-Improvement Predicts Daily Wellbeing ............................ 90
Figure 5: Daily Difficulty-as-Improvement Predicts Daily Experiences ........................ 91
Figure 6: Yesterday’s Difficulty-as-Improvement Predicts Current Day’s
Meaning in Life and Self-Esteem ........................................................................ 93
Figure 7: Yesterday’s Difficulty-as-Improvement Predicts Current Day’s
Wellbeing (With Controls) ................................................................................... 94
Appendix A Figures
Figure A1: Difficulty Mindsets Predict Taking Action via Silver Linings:
Detailed Structural Equations Model with Correlations, Regression
Paths, and Factor Loadings (Unconstrained Model) .......................................... 116
4
Abstract
Life often presents people with unchosen difficulties and how people respond to these difficulties
matters. Both religious and non-religious cultural frameworks draw attention to difficult
experiences as opportunities for building character and becoming a better version of oneself. We
term the belief that difficulties are character-building the “difficulty-as-improvement mindset.”
Throughout my PhD, I investigated the sources and consequences of endorsing this belief, being
specifically interested in how this belief can confer value. The three papers comprising my
dissertation each investigate the value of holding belief in a different context, using various
methodologies. We find that overall, people who more strongly endorse the
difficulty-as-improvement mindset are better off, seeing silver linings in difficult life
circumstances, positively evaluating ethical but effortful goal pursuit strategies, and experiencing
life as meaningful and themselves as people of worth.
5
Introduction
The three papers that are part of my dissertation are (1) “The upside: How people make
sense of difficulty matters during a crisis,” Kiper et al., 2022, published in Self and Identity; (2)
“I’ll take the high road: Paths to goal pursuit and identity-based interpretations of difficulty,”
Kiper et al., 2023a, manuscript submitted for publication to Self and Identity; and (3) “Believing
That Difficulties are Character-building Supports Wellbeing and Positively Frames Daily Life,”
Kiper et al., 2023b, manuscript in preparation, which we plan on submitting to Social
Psychological and Personality Science.
The common thread across our studies is the difficulty-as-improvement mindset; the
belief that difficulties are character-building and self-strengthening experiences. I started this
project with my advisor Dr. Daphna Oyserman and Dr. Veronica Yan under a grant from the John
Templeton foundation (grant #61083 awarded to Oyserman and Yan). One of our motivations for
starting this project was to understand if there was a mindset that could help people garner moral
muscle in the face of difficulty. If difficulty is something that makes one a better person and
brings one closer to God, enduring difficulty can be of moral concern. Thus, a
difficulty-as-improvement mindset can create encouragement to endure and lean into difficulty
when such difficulties are necessary. For example, in the context of learning, people find it hard
to believe that certain strategies, which require more effort, lead to better learning and
performance outcomes than strategies requiring less effort (Yan et al., 2016). If people can come
to embrace the notion that experiencing difficulty is in and of itself valuable and necessary for
self-improvement, they may come to see the effortful way as the right way, finding
encouragement and resilience to persist when they need to do so.
1
We looked to religious (e.g., the Bible) as well as non-religious narratives (e.g., the
Hero’s Journey, Campbell, 1949) from cultures to come up with an understanding of the
ecological prevalence of the difficulty-as-improvement mindset. Drawing from these sources, we
created a set of face-valid items aimed at capturing the difficulty-as-improvement belief, which
we initially conceptualized as a sanctified experience (e.g., “Every difficulty you overcome
makes your spirit and soul grow stronger.”). Based on feedback from our colleagues that this
version may not resonate with non-religious people, we created the secular version of our
measure (e.g., “Experiencing difficulty makes me grow stronger.”).
We believed that having this mindset should matter. People who hold this mindset should
see the unbidden difficulties of their lives as necessary experiences for their growth, and hence
should experience more meaning in their lives. Moreover, we hypothesized that this belief should
resonate from people across different cultures. In one set of studies, we found support for these
ideas: People who more strongly endorsed this belief scored higher on meaning in life and
optimism, and both people from Western and non-Western societies endorsed this belief (Yan et
al., 2023).
We predicted and found that this belief also helps people make sense of difficult life
circumstances: people who more strongly endorse this belief were more likely to see silver
linings in the COVID-19 pandemic for themselves and their communities (Kiper et al., 2022).
Next, we asked, once people have this frame for thinking about the hardships in their
lives, does it also carry over to thinking about effortful vs. easy strategies for goal pursuit? In the
goal pursuit paper (Kiper et al., 2023a), we found that people who more strongly endorse
difficulty-as-improvement are more likely to prefer ethical, effortful, “right” ways of engaging
2
with goal pursuit strategies, even controlling for endorsement of the two IBM difficulty
mindsets, difficulty-as-importance and difficulty-as-impossibility (Fisher & Oyserman, 2017).
In all studies leading up to the daily diary study (Kiper et al., 2023b), we treated
difficulty-as-improvement as an individual difference variable, measured at a single timepoint. In
the daily diary studies, we tested to what extent this is truly the case—how much the
difficulty-as-improvement can be considered trait vs. state-like. We found that about two-thirds
of the variation in daily scores were due to between-person differences; hence,
difficulty-as-improvement is more trait than state-like. We also asked how much trait
endorsement matters, as well as how much within-person daily fluctuations matter. Specifically,
we asked how much the variation at these two levels matters for experiencing life as meaningful
and coherent, and experiencing oneself and one’s life as worthy. Lastly we asked if variation
carries over to engagement in effortful strategies and experiencing success in daily life. We
found that both trait and daily variation in difficulty-as-improvement scores matter for these
outcomes, generally predicting higher scores.
The effect sizes across the studies are as follows. In the silver linings paper (Kiper et al.,
2022), the standardized SEM path from difficulty-as-improvement to seeing silver linings for
oneself in a model that simultaneously considered all our main variables (three difficulty
mindsets, silver linings, taking action, conservatism, sample) was .30, which can be considered a
medium-size effect, using the guidelines of Cohen (1988). For effortful goal pursuit strategies
(Kiper et al., 2023a), meta-analytic R
2
values from models that simultaneously tested the effects
of difficulty-as-impossibility, difficulty-as-importance, and difficulty-as-improvement on seeing
one’s effort as valuable was .20 (medium to large); perceived effectiveness was .11 (small to
medium); and likelihood of using the method was .18 (medium to large).
3
In the daily diary studies (Kiper et al., 2023b) we used Rights & Sterba’s (2019, 2021)
recommendations to calculate level-specific effect sizes of difficulty-as-improvement. For
example, in models testing within-person relationships, we report R
w
f1v
(defined as the square
root of the proportion of variance explained by within-person predictors via fixed slopes and
random slope variation/covariation; akin to a correlation). The R
w
f1v
in meta-analytic models
testing same-day effects of endorsing difficulty-as-improvement on meaning in life was .34
(medium to large); coherence .40 (medium to large); self-esteem .35 (medium to large);
satisfaction .34 (medium to large); effortful engagement .21 (small to medium); and successes
.20 (small to medium).
4
Chapter 1
The Upside: How People Make Sense of Difficulty Matters During A Crisis
Gülnaz Kiper
1
Mohammad Atari
1
Veronica X. Yan
2
Daphna Oyserman
1
1
Department of Psychology, University of Southern California, CA, USA
2
Department of Educational Psychology, The University of Texas at Austin, TX, USA
Abstract
We tested the prediction that how people respond to all-encompassing life difficulties that may
require taking on novel difficult tasks or goals is a function of what they infer about their
identities from these experiences of difficulty. We focused on the COVID-19 pandemic and
identity-based motivation theory to test our predictions (N=698 U.S. adults, three datasets).
People were more likely to see silver linings if they endorsed difficulty-as-importance
(experienced difficulties with a task/goal as implying its importance) and
difficulty-as-improvement (experienced life difficulties as possibly making them better people).
Our structural equation models revealed that people who endorsed difficulty-as-importance were
more likely to mask, distance, and wash hands in large part because they saw a silver lining for
themselves in the pandemic; for difficulty-as-improvement, effects on action were fully mediated
by seeing silver linings. Taken together, our results suggest that people apply their
difficulty-as-importance and difficulty-as-improvement mindsets to cope with novel life
difficulties.
Keywords: Difficulty mindsets; Identity-based motivation; COVID-19 pandemic; social
identities; Silver linings in a crisis
5
The Upside: How People Make Sense of Difficulty Matters During A Crisis
Experiencing difficulty is part of life. People can experience difficulty while working on
or imagining working on tasks and goals as well as due to an array of personal, community- and
national-level difficulties such as job loss and illness, floods and fires, and wars and pandemics.
In the current paper, we build on Identity-based Motivation theory (Oyserman, 2007) to predict
that how people respond to difficulties emerging in times of crisis depends in part on how they
interpret their experiences of difficulty and hence the identities they form. We use as our concrete
example the COVID-19 pandemic and focus on the relationship among people’s interpretations
of their experiences of difficulty, novel identity construction, and engaging in pandemic-relevant
action. Before detailing our predictions and describing our studies, we outline what
Identity-based Motivation Theory is and provide a brief summary of relevant empirical evidence
to date.
Identity-Based Motivation
IBM theory is a social psychological theory of goal pursuit and self-regulation that
describes how identities, meaning making, and behaviors are interrelated (Oyserman, 2007;
2009; Oyserman et al., 2017). IBM theory predicts that people are motivated to act and make
sense of their experiences in identity-congruent ways—in ways that fit their identities. How
much certainty people have that they hold an identity affects how people interpret their
experiences of difficulty when engaging or considering identity-relevant tasks and goals. Of
particular relevance for this paper, IBM theory also predicts that the reverse is true --people often
interpret their experiences of difficulty as having implications for who they are (or might
become) and what actions they should take. In doing so, people are guided by a set of three
“difficulty mindsets”, two of which focus on what they believe their experiences of difficulty
6
engaging with a task or goal implies for who they are and might become and one of which
focuses on what they believe their experiences of difficulty in life imply for who one is and
might become. The task-focused difficulty mindsets are termed difficulty-as-importance and
difficulty-as-impossibility, and the life-focused difficulty mindset is termed
difficulty-as-improvement. Each is detailed next.
When working on or imagining a task or goal feels difficult, people can interpret their
difficulty as implying that the task or goal is self-relevant, important to who they are or might
become (a “difficulty-as-importance” mindset). This difficulty mindset can be reliably measured
with a brief scale (Fisher & Oyserman, 2017). Scale items reflect the focus on the self-defining
aspects of difficulty working on tasks and goals (e.g., Sometimes if a task feels difficult to me
my gut says that it really matters for me. If a goal feels difficult to work on, I often think it might
be a critical one for me. When a task feels difficult, the experience of difficulty sometimes
informs me that succeeding in the task is important for me. Often when a goal feels difficult to
attain it turns out to be worth my effort).
However, when working on a task or goal feels difficult, people can also interpret their
difficulty as implying that the task or goal is not self-relevant, a waste of their time. This
difficulty-as-impossibility mindset can be reliably measured with a brief scale as well (Fisher &
Oyserman, 2017). Scale items reflect the focus on the self-defining aspects of difficulty working
on tasks and goals (e.g., Sometimes if a task feels difficult, my gut says it is impossible for me.
If a goal feels difficult to work on, I often think it might not be for me. When a task feels
difficult, the experience of difficulty sometimes informs me that succeeding in the task is just
not possible for me. Often when a goal feels difficult to attain it turns out to be out of my reach).
In contrast to experiences of difficulty linked to tasks or goals, when people experience
7
life difficulties such as economic downturns, job loss or community-level or personal tragedies,
they can interpret these difficulties as an opportunity for building character and for self-growth.
This “difficulty-as-improvement” mindset can be reliably assessed with a brief scale (Yan et al.,
2021). Scale items reflect the focus on the self-defining aspects of life difficulties (e.g., In a way,
the struggles I have today are strengthening my character to meet tomorrow's challenges.
Experiencing difficulty makes me grow stronger. Experiencing difficulty is the strongest of
teachers; I may temporarily feel broken but in the long run, I will be better. Life is not complete
without difficulty, hardship, and suffering). As these scale items concretize,
difficulty-as-improvement is not about responding to difficulties with discrete tasks or goals, it is
about responding to difficulties, struggles, and hardships more generally.
IBM theory predicts that the more people endorse difficulty-as-importance and
difficulty-as-improvement, the more likely they will be to endorse connected identities and take
relevant action (Oyserman, 2007, 2009). IBM theory also predicts that the reverse is true. The
more people endorse difficulty-as-impossibility, the more likely they will be to reject connected
identities (see these identities as untrue for them) and reject related actions (see these actions as
not for them). In sum, IBM theory highlights the bi-directional paths by which interpretations of
difficulty with tasks and goals and life circumstances shape identities and behavior.
In the current paper, we consider the COVID-19 pandemic because the pandemic reflects
both a life difficulty and a difficult novel task or goal (following the CDC guidelines). While
COVID-19 is a pandemic, it is not unique. Climate-induced environmental tragedies that
devastate communities have a similar quality of including both a life difficulty and novel tasks or
goals that people can find identity congruent or not, with likely implications for the meaning that
they make of their difficulties and what they do. Hence, we use identity-based motivation theory
8
to predict that people’s responses will be a function of their interpretations of difficulty.
In response to the COVID-19 pandemic, the CDC asked people to perform an array of
novel and challenging behaviors in the hopes of reducing spread. In addition to cleaning and
disinfecting surfaces, the CDC recommended staying home, wearing a mask, and keeping
physical distance from others. Wearing a mask impedes both breathing freely and ease of
communication, as does keeping physical distance from others. Though initial messaging from
the CDC did not present these behaviors as difficult or requiring a new identity, taking these
actions is difficult in part because they are socially isolating. People are inherently social beings
(Van Bavel et al., 2020), so social isolation takes a toll on mental health (Hawryluck et al., 2004,
increasing people’s risk of feeling detached, angry, and frustrated, Brooks et al., 2020).
Identity-based motivation theory implies that people would be more likely to engage in
these novel and difficult pandemic-relevant behaviors if they create a novel identity of a person
who can take appropriate action during the pandemic. One way to operationalize a
pandemic-relevant novel identity is being the kind of person who can see a silver lining for
themselves in the difficult situation of the pandemic. Prior studies document that finding silver
linings can be beneficial: people who report finding silver linings in disasters report more
well-being (Taylor, 1983), seek more support, and pray and meditate more (Lechner et al., 2006;
Mohr et al., 1999). We did not find prior studies showing that taking on a silver lining identity is
associated with taking action to mitigate the risk of infection and spread of disease. However, the
identity-to-action link is central to identity-based motivation theory. Hence, in our studies, we
focus on how endorsing each difficulty mindset can predict taking on this new identity and the
downstream consequences of difficulty mindsets and identity for taking action. The new identity
we focus on is a silver lining identity of a person who has gained positive attributes in the wake
9
of the pandemic.
We predict that the more people interpret difficulties working on or imagining working
on their tasks and goals as implying importance, the more they should take on a silver lining
identity and the more they should engage in difficult but necessary action. We also predict that
the more people interpret their experiences of difficulty in life as implying that these difficulties
can build their character and improve them, the better positioned they will be to take on a silver
lining identity. Given that IBM theory predicts that people prefer to act in identity-congruent
ways (Oyserman, 2007), endorsing this new silver lining identity should increase the likelihood
that people take the difficult, but relevant, pandemic-appropriate actions. The silver lining
identity of becoming a better person through the pandemic may give people the stamina and
strength to take on and persist in the difficult and novel pandemic-relevant behaviors. In contrast,
difficulty-as-impossibility is less clearly related to novel tasks and identities. People who
interpret their experiences of difficulty as implying impossibility may simply shift to something
else when faced with novel difficulties or they may reject the novel identities and actions as not
for them.
We make our predictions based on the assumption that people have access to and endorse
each difficulty mindset (difficulty-as-importance, difficulty-as-improvement, and
difficulty-as-impossibility) to differing degrees, deploying them in ways shaped by their
identities. Though researchers have mostly focused on the situated nature of difficulty mindset
accessibility (e.g., Aelenei et al., 2016; Oyserman et al., 2015; Oyserman et al., 2018; Smith &
Oyserman, 2015), several studies examine the effects of differential endorsement of each
mindset (e.g., Fisher & Oyserman, 2017; Yan et al., 2021). Situated studies entail making a
single difficulty mindset differentially accessible. This method provides causal evidence that an
10
accessible difficulty mindset matters for meaning making and action. For example, students
guided to think of difficulty-as-importance are more likely to see academics as identity-central
(Smith & Oyserman, 2015) and report greater confidence that they can attain their academic
possible future selves (Aelenei et al., 2016). They persist longer and perform better on academic
tasks than students guided to think of difficulty-as-impossibility (Oyserman et al., 2018; Smith &
Oyserman, 2015).
While invaluable in documenting causality, this methodology does not address how each
mindset can matter in the real world. Real-world processes require measuring the consequences
of endorsing each difficulty mindset for meaning making and action. Some emerging research
addresses this gap. For example, how much students endorsed difficulty-as-importance and
difficulty-as-impossibility mediated the effect of a classroom intervention on students’ academic
trajectory measured over a school year (Oyserman et al., 2021). In addition, people reported
more meaning in life and conscientiousness, and other virtuous character traits when they
endorsed difficulty-as-importance and difficulty-as-improvement more and
difficulty-as-impossibility less (Yan, et al., 2021 using samples from eight countries).
Taken together, these studies imply that how much people endorse
difficulty-as-importance, difficulty-as-improvement, and difficulty-as-impossibility is
meaningfully associated with identity-relevant traits and behavioral responses. The process is
multidirectional. Thus, the extent to which people endorse each difficulty mindset shapes their
identities and behaviors, and their identities can shape which difficulty mindset is used and
which behaviors are adopted. At the same time, identity-based motivation theory describes the
consequences of both personal and social identities on taking action (Oyserman, 20007, 2009).
Hence, while we focus in particular on the pandemic-induced possibility of taking on a novel
11
identity and novel behavior, we also explore the possibility that the likelihood of taking up this
identity and set of behaviors was moderated in part by another identity, party affiliation.
We focus on party affiliation because identities as conservative and liberal and
Republican and Democrat emerged as particularly relevant during the COVID-19 pandemic
(Howard, 2021). Republican politicians and media outlets responded to the challenges of the
pandemic quite differently from Democrats and there is some evidence that which judgments and
behaviors feel congruent with political identities depends on social contexts (e.g., Oyserman &
Schwarz, 2017). Consider, for example, wearing a mask, social distancing, and washing hands.
These behaviors could be identity-congruent for conservatives. After all, each of these behaviors
entails taking personal responsibility and none entails a government program or spending tax
dollars. But, in part due to statements from former President Trump and other leading
Republicans, people with Republican identities came to see COVID-19 itself as not a serious
problem (The Economist/YouGov poll July 10 to 13, 2021) and each of these actions as
antithetical to holding a Republican identity (see, for example, Calvillo et al., 2020; Gollwitzer et
al., 2020; Kerr et al., 2021). This reframing of a set of beliefs and behaviors as incongruent with
Republican identity had behavioral consequences. Compared to Democrats, Republicans report
being less likely to wear masks (Capraro & Barcelo, 2020; Chan, 2021; Howard, 2021; Xu &
Cheng, 2021), maintain distance (Allcott et al., 2020; de Bruin et al., 2020; Painter & Qiu, 2021:
van Holm et al., 2020), and wash their hands (van Holm et al., 2020).
Current Studies
Predictions
We focus on how identity-based difficulty mindsets matter during a crisis. We make two
12
predictions (H1, H3) regarding the positive effects of difficulty-as-improvement and two parallel
ones (H2, H4) regarding difficulty-as-importance.
H1: The more people endorse a difficulty-as-improvement mindset, the more likely they
will be to find a silver lining positive effect of the COVID-19 pandemic for themselves and their
communities. We make this prediction because people who endorse difficulty-as-improvement
see life’s difficulties as character-building opportunities and should be more likely to see the
pandemic as a specific chance to become better in various ways and assume others do as well.
H2: The more people endorse a difficulty-as-importance mindset, the more likely they
will be to report a silver lining positive effect of the COVID-19 pandemic for themselves. We
make this prediction because people who endorse difficulty-as-importance believe that
experiences of difficulty imply the value of their goals; hence, they should be more likely to see
the pandemic as making them better by pushing them to work on challenging goals.
H3: The effects of difficulty-as-improvement and difficulty-as-importance are robust.
That is, H1 and H2 will remain significant when we take each difficulty mindset simultaneously
into account as predictors and include political identity (Democrat, Republican) and date of data
collection as controls. We make this prediction because each mindset should have unique effects
and the mindset-silver-lining-action linkage should be stable even though people with a
Republican identity report that they are less likely to take the CDC-recommended actions we are
studying.
H4: People who endorse difficulty-as-improvement and difficulty-as-importance will be
more likely to wear masks, social distance, and handwash partly due to their propensity to see a
pandemic-related silver lining. People who endorse difficulty-as-improvement believe that they
can grow from life’s difficulties so should be willing to weather the unpleasant and isolating
13
aspects of pandemic-related restrictions and guidelines. People who endorse
difficulty-as-importance believe that experiences of difficulty imply that a goal is worth their
effort so should be willing to engage in difficult actions like wearing masks and social
distancing. People who find silver linings should be more likely to take difficult but necessary
preventive action.
Exploratory questions: We also examined two exploratory questions. First, we asked if
people who endorse difficulty-as-impossibility would be less likely to find a silver lining and
take relevant action. Second, we asked whether our model was stable across party affiliation or if
party affiliation (or being a conservative) moderated our model.
Method
Open Practices and Data Availability
We collected data at three points in time in three studies. We provide the full scales in the
Appendix, data files and analysis scripts for each study and Study 3’s pre-registration at:
https://osf.io/enz37/?view_only=7cbf9b5a8f60433a834471eb70cb3209
Samples and Procedure
Our participants were U.S. adults (see Table 1 for demographics) recruited on Prolific.
They completed predictor (difficulty mindsets) and outcome (silver linings, taking action)
measures, indicated location, demographics, and political orientation, in that order. Procedures
across studies were identical except as noted below.
14
Table 1
Demographic Information of Samples by Study
Demographics Study
Study 1 Study 2 Study 3
Sample size (n) 196 200 302
% Women 51% 57% 48%
% White 83% 68% 75%
% Republican, Republican Leaning 36% 27% 24%
Mean age (SD) 36.77 (12.01) 32.98 (11.45) 34.16 (12.00)
Mean education (SD) (1-9 scale) 5.11 (1.81) 4.83 (1.92) 5.00 (1.86)
Mean income (SD) (1-11 scale) 5.62 (3.41) 5.09 (3.38) 5.21 (3.22)
Mean conservatism (SD) (1-7
scale)
3.23 (1.69) 3.19 (1.72) 3.01 (1.60)
Note. Education: 1 = < High school diploma, 2 = High school diploma or GED, 3 = Some
college, no degree, 4 = V ocational/ technical degree, 5 = Associate degree, 6 = Bachelor’s
degree, 7 = Master’s Degree, 8 = Professional Degree (M.D., D.D.S., J.D.), 9 = PhD. Income: 1
=< $10,000, 2=$10,000 to $19,999, 3=$20,000 to $29,999, 4 = $30,000 to $39,999, 5 = $40,000
to $49,999, 6 = $50,000 to $59,999, 7 = $60,000 to $69,999, 8=$70,000 to $79,999, 9=$80,000
to $89,999, 10=$90,000 to $99,999, 11= > $100,000.
In Figure 1, we situate our studies in the context of U.S. daily COVID-19 cases and
events from March 2020 to 2021. We recruited in May 2020 as the first U.S. COVID-19
infection wave stabilized (Study 1), in July 2020 as the second U.S. wave neared its peak (Study
2), and in February 2021 after the third U.S. wave peaked and 8% of American adults were
vaccinated (study 3). We based Study 3 sample size on Tabachnick & Fidell’s (2013) SEM
recommendation of n=300, recruiting 325 to account for potential exclusions. We excluded
people failing an attention check (Study 1 n=5, Study 2 n=2, Study 3 n=23).
15
Figure 1
Study Times Contextualized with New U.S. COVID-19 Cases and Noteworthy Events
Note. The black smoothed line represents the 7-day average of new COVID-19 cases. WHO =
World Health Organization; CDC = U.S. Centers for Disease Control and Prevention; BLM =
Black Lives Matter; Real GDP = Real (inflation-adjusted) Gross Domestic Product; FDA = Food
and Drug Administration. We created this graph using CDC (2021) data.
Measures
Preliminary analyses
We conducted a 5-factor confirmatory factor analysis (CFA), verifying that our three
difficulty mindset scales, silver lining, and taking action scales are distinct (see Tables S1 and
S2, Supplementary Materials).
Predictors: Difficulty Mindset Scales
Participants indicated their agreement (6 = strongly agree) or disagreement (1 = strongly
disagree) with twelve statements which were presented in a randomized order provided in the
Appendix, Table A1). The statements included the 4-item difficulty-as-improvement (Yan et al.,
2021), the 4-item difficulty-as-importance (modified from Fisher & Oyserman, 2017), and the
4-item difficulty-as-impossibility (modified from Fisher & Oyserman, 2017) scales. Each scale
16
was reliable (Tables 2-4).
1
Experiencing a Pandemic-Related Silver Lining
We adapted the 38-item Silver Lining Questionnaire (Sodergren & Hyland, 2000;
Sodergren et al., 2002) to focus on the COVID-19 pandemic. Two-thirds of the original items
focused on personal growth (e.g., “My illness gave me more confidence”), a third on other
positive consequences (e.g., “People can be more open with me since my illness”). We replaced
the word “illness” with “pandemic” in the seven personal growth items most relevant to the
pandemic. We presented these items to participants in a single block in the order we show in
Table A2 (Appendix, left panel) and again as a single block with items slightly modified to be
about community (e.g., “This pandemic is making society face up to problem areas,” Table A4,
Appendix). Participants rated how much they agreed (5=strongly agree) or disagreed (1=strongly
disagree) with each item, yielding a reliable scale, as reflected in the Cronbach reliabilities we
present by Study in Tables 2-4.
Taking Action
Participants responded to seven statements about COVID-relevant action (presented in
the order shown on the right panel of Table A2). Our statements reflect CDC’s recommendations
as brief phrases that could be answered on a 5-point Likert scale (1 = Never, 5 = Always). In
Study 1, we asked: “Which of the following steps have you taken to protect yourself from
contracting the virus?” Given the ongoing nature of the pandemic, in Study 2, we asked,
“Looking forward, how often do you plan on taking each of the following steps to protect
yourself from contracting the virus in the coming weeks?”. In Study 3, we asked, “How certain
are you that you will engage in each of the following steps to protect yourself so that you reduce
1
We present McDonald’s omega (ω) reliabilities in Table S2 in Supplemental Materials.
17
your chances of contracting COVID-19 or suffering from serious symptoms?”. The scale was
reliable in each study, as we detail in Tables 2-4.
In Study 3, we also asked people explicitly about actions to protect their community (see
Appendix). We do not include these new items in our analyses because our pre-registered CFAs
suggested that these items do not form a coherent latent construct or set of constructs (as detailed
in the Supplemental Materials).
Party Identity and Conservative Identities
Participants reported how politically conservative they were (single item, 1=Very liberal,
7=Very conservative) and their party affiliation (Democrat, Republican, or Independent). We
asked people who chose ‘Independent’ which party they leaned toward and treated people who
leaned toward Democrats as Democrats and those who leaned Republican as Republicans
following research on political behavior (e.g., Pappi, 1996). We used our political conservatism
item in our main SEM analysis and our party affiliation item as part of our robustness check.
Description of Pandemic Experience and Demographic Information
We asked participants whether they had experienced adversity in finances, health, and
other obligations due to the pandemic (measure in Appendix) and to report their age, sex,
education, income, and U.S. state of residence. We also obtained current state-wide COVID-19
mandates (see Supplemental Materials for measures). In Table 1 we provide descriptive statistics
for demographics. We provide other descriptive information (location and mandates, Table S3;
correlations among all variables, are Table S4) in Supplemental Materials.
Analytic Strategy
We used the psych (v. 2.1; Revelle, 2021) and lavaan (v. 0.6; Rosseel, 2012) packages in
the R (v. 4.1) programming language (R Core Team, 2020).
18
H1 and H2. We created scale scores from item means in each sample and tested H1 and
H2 using Pearson correlations with 95% Confidence Intervals (CI).
H3 and H4. In Figure 2 we display our hypothesized process model which we tested by
pooling our three datasets to conduct a structural equations model (SEM, Model 1). SEM is the
appropriate analytic strategy given that people’s difficulty mindset scores were correlated as we
previously showed in Tables 4, 5, and 6. In Model 1 we included factor loadings of each item on
their respective latent variables, direct paths from difficulty mindsets to silver linings and action,
and indirect paths from difficulty mindsets to actions via silver linings. We accounted for the
possible effect of conservatism on silver linings and taking action. We used two dummy-coded
variables (July vs. May 2020, February 2021 vs. May 2020) to account for possible sample
effects on taking action. We checked for model fit adequacy using chi-square (χ
2
) with degrees of
freedom (df), Comparative Fit Index (CFI), Tucker Lewis Index (TLI), and Root Mean Square
Error of Approximation (RMSEA) following Hu and Bentler (1999, CFI > .90 and RMSEA <
.08 show a good fit of the hypothesized model to data). We show this model in our results
2
. We
applied a Bonferroni-type correction, dividing our .05 p-value threshold by the five latent
variables (.05/5=0.1) to account for multiple comparisons and thus reduce Type I error risk. We
use the resultant .01 p-value threshold to claim significance in our SEM analyses.
2
After fitting the model, we followed SEM guidelines and checked for Modification Indices
(MI) and added covariance paths for error terms of items belonging to the same construct if an
MI was >10.83, indicating model fit would significantly improve at p < .01. We added the
highest error covariance, checking for MIs again until we found no more within-construct error
covariances with MIs of >10.83. We provide all the modified models in Supplemental Materials.
Modifications do not change the process model or the significance of our theorized pathways.
19
Exploratory Analyses. We examined our exploratory difficulty-as-impossibility question
by examining bivariate correlations and our Model 1 direct and indirect paths. We examined our
exploratory political affiliation question in Model 2 by conducting the Model 1 SEM separately
for Democrats and Republicans.
Figure 2
Hypothesized Structural Equations Model (Model 1)
Results
H1 and H2
People who endorsed difficulty-as-improvement were more likely to report experiencing a
pandemic-related silver lining for themselves (Studies 1 to 3 rs = .42, .36, .46, ps < .001) and
their community (rs = .21, .14,.30, Studies 1, 3 ps < .004, Study 2 p = .056). People who
20
endorsed difficulty-as-importance were more likely to report a pandemic-related silver lining for
themselves (rs = .42, .42, .47, ps < .001) and their community (rs = .19, .07, .21, Studies 1, 3 ps
< .006, Study 2 p = .339). Tables 4 to 6 detail these results by Study.
H3 and H4: Difficulty Mindsets, Experiencing Silver Linings, Taking Action
To test H3 and H4, we use SEM. Our SEM Model 1 analysis supports our predictions
--Model 1, estimated with unconstrained error terms, variances, and covariances, adequately fit
the data (Hu & Bentler, 1999), χ
2
=1255.128, df =363, χ
2
/df =3.458, CFI =.883, TLI =.870,
RMSEA =.059. As our Figure 3 process model depicts, the positive relationships between
difficulty-as-improvement, difficulty-as-importance, and silver linings for self remain when
accounting for difficulty-as-impossibility, conservatism, and date of data collection
3
. People who
endorsed difficulty-as-importance and difficulty-as-improvement were more likely to see a silver
lining. As we show in Table 5, this and not having a conservative identity predicted that they
would take CDC-recommended action. Consistent with H4, difficulty-as-importance had a
significant total effect on taking action. Both difficulty-as-improvement and
difficulty-as-importance had significant indirect effects on taking action via silver linings.
3
People were more likely to act in July 2020 than May 2020, p (β =.12, p =.010); this effect was
less strong by February 2021 (β =.07, p =.137). We present item loadings on each construct and
correlations among the three difficulty mindsets in Figure A1 (Appendix) and the modified
model in Figure S1 (Supplemental Materials).
21
Table 2
Study 1: Means, Standard Deviations, Cronbach’ s α, and Correlations With 95% Confidence
Intervals
Variable M SD α 1 2 3 4 5
1.
Difficulty-as-
Improvement
4.56 0.90
.81
[.77, .86]
2.
Difficulty-as-
Importance
4.17 0.77
.74
[.68, 79]
.55***
[.45, .64]
3.
Difficulty-as-
Impossibility
3.01 1.02
.85
[.82, .88]
-.38***
[-.50,
-.26]
-.29**
*
[-.41,
-.16]
4. Silver
Linings
3.26 0.89
.87
[.84, .90]
.42***
[.30, .53]
.42***
[.29,
.52]
-.19**
[-.32,
-.05]
5. Taking
Action
3.94 0.81
.81
[.77, .85]
.15*
[.01, .29]
.27***
[.14,
.40]
-.04
[-.18,
.10]
.46***
[.34, .57]
6.
Conservatism
3.23 1.69
--
.22**
[.08, .35]
.06
[-.08,
.20]
-.20**
[-.33,
-.06]
.10
[-.04,
.24]
-.24*
**
[-.36,
-.10]
Note. * p < .05; ** p < .01; *** p < .001.
22
Table 3
Study 2: Means, Standard Deviations, Cronbach’ s α, and Correlations With 95% Confidence
Intervals
Variable M SD α 1 2 3 4 5
1.
Difficulty-as-
Improvement
4.75 0.85 .79
[.74,
.84]
2.
Difficulty-as-
Importance
4.31 0.81 .77
[.72,
.82]
.50***
[.38, .59]
3.
Difficulty-as-
Impossibility
3.00 0.95 .79
[.74,
.84]
-.25***
[-.37,
-.11]
-.13
[-.27,
.00]
4. Silver
Linings
3.53 0.85 .86
[.83,
.89]
.36***
[.24, .48]
.42***
[.30,
.53]
-.20**
[-.33,
-.06]
5. Taking
Action
4.22 0.59 .77
[.72,
.82]
.08
[-.06,
.22]
.16*
[.02,
.29]
-.07
[-.21,
.07]
.22**
[.09,
.35]
6.
Conservatism
3.19 1.72 -- .17*
[.03, .30]
.07
[-.07,
.21]
-.11
[-.24,
.03]
-.02
[-.16,
.12]
-.31***
[-.43,
-.18]
Note. * p < .05; ** p < .01; *** p < .001.
23
Table 4
Study 3: Means, Standard Deviations, Cronbach’ s α, and Correlations With 95% Confidence
Intervals
Variable M SD
α
1 2 3 4 5
1. Difficulty-as-
Improvement
4.46 0.92
.84
[.81, .87]
2. Difficulty-as-
Importance
4.05 0.86
.81
[.77, .84]
.68***
[.62, .74]
3. Difficulty-as-
Impossibility
3.01 1.04
.85
[.82, .88]
-.15**
[-.26,
-.04]
-.19***
[-.30,
-.08]
4. Silver Linings 3.33 0.88
.86
[.84, .89]
.46***
[.37, .55]
.47***
[.38, .55]
-.11*
[-.22,
-.00]
5. Taking Action 4.11 0.68
.82
[.79, .85]
.06
[-.05,
.18]
.17**
[.06, .28]
-.03
[-.14,
.09]
.34***
[.24, .44]
6. Conservatism 3.01 1.60
--
.09
[-.02,
.20]
.02
[-.10, .13]
-.05
[-.17,
.06]
-.11
[-.22,
.01]
-.34***
[-.44,
-.24]
Note. * p < .05; ** p < .01; *** p < .001.
24
Figure 3
Model 1: Difficulty Mindsets Predict Taking Action via Seeing Silver Linings for Oneself
Note. Coefficients are standardized estimates. Ovals are latent and rectangles are manifest
variables. Solid lines are significant paths, dashed lines are non-significant paths. ** p < .01; ***
p < .001.
Table 5
Model 1: Direct, Indirect, and Total Effects of Difficulty Mindsets on Taking Action [95%
Confidence Intervals]
Difficulty Mindset Direct Effect Indirect Effect via Silver
Linings
Total Effect
Difficulty-as-Improvement -.13 [-.33 .08] .11 [.03, .19] -.02 [-.22, .19]
25
Difficulty-as-Importance .17 [-.04, .38] .12 [.04, .20] .29 [.08, .51]
Difficulty-as-Impossibility -.02 [-.09, .12] -.01 [-.05, .03] .01 [-.10, .11]
Note. ** p < .01, *** p < .001. Effects from the unconstrained model. Table S5 in Supplemental
Materials details effects in the modified model.
Testing Predictions Regarding Silver Linings for Community
Our SEM Model including silver linings for community and for oneself as mediators
adequately fit the data (χ
2
= 1890.943, df = 541, χ
2
/df = 3.495, CFI= .859, TLI= .846, RMSEA=
.060) as detailed in Figure S2 in Supplemental Materials which also details our analyses. The
more people endorsed difficulty-as-improvement the more they found silver linings for their
community (β =.32, p < .001). However, people who found silver linings for their community
were no more likely to take CDC-recommended action (β =.06, p = .160)
Exploratory Analyses
Does Difficulty-as-Impossibility Matter for Silver Linings or Taking Action?
People who endorsed difficulty-as-impossibility were less likely to report experiencing a
silver lining (rs = -.19, -.20, -.11, ps < .046) but no more or less likely to take
CDC-recommended action (ps > .307), as detailed in Tables 4 to 6. But as detailed in Figure 3
and Table 5, neither relationship was significant once difficulty-as-importance and
difficulty-as-improvement were included.
Political Conservatism and Party Affiliation
Conservatism matters; as displayed in Figure 3, people who rated themselves as more
politically conservative were less likely to take CDC-recommended action (β = -.32, p < .001),
but not necessarily less likely to find a pandemic-related silver lining (β = -.08, p = .018, above
our corrected threshold of p = .01). We also conducted an unconstrained exploratory multigroup
SEM (Model 2) with binary political party affiliation (Democrat vs. Republican) as our grouping
26
variable. We present this SEM in Figure 4 for Democrats (left) and Republicans (right)
4
. We
freely estimated a unique model for each, not constraining the models to be equal on any
parameters. Our initial model adequately fit the data (χ
2
=1634.499, df =678, χ
2
/df =2.411, CFI
=.872, TLI =.858, RMSEA =.064). Democrats and Republicans who found a COVID-related
silver lining were more likely to act. They were more likely to find one if they agreed that
difficulty implies improvement and importance. These patterns were more robust for Democrats
than Republicans.
Figure 4
Model 2: Structural Equations Model (Unconstrained) for Democrats (Left) and Republicans
(Right) With Standardized Estimates
Democrats (n = 498) Republicans (n = 196)
Note. **p <.01, ***p < .001
4
Supplemental Materials Figure S3 (Democrats) and S4 (Republicans) present item loading on
each factor and correlations among factors for interested readers. Covarying error terms of items
belonging to the same construct based on modification indices that exceeded 10.83
(χ
2
=1237.187, df =702, χ
2
/df =1.762, CFI =.929, TLI =.919, RMSEA =.047) improves fit.
27
Discussion
We collected data during three unique periods in the COVID-19 pandemic in the U.S.
Building on identity-based motivation theory (Oyserman, 2007; 2009; Oyserman et al., 2017),
we predicted and showed that people’s difficulty mindsets mattered for their identities and
actions. People were more likely to create a new identity of being the kind of person who finds a
silver lining for themselves in the pandemic if they endorsed a difficulty-as-importance mindset
for tasks and goals and a difficulty-as-improvement mindset for life’s difficulties. People were
more likely to follow pandemic-related recommended behavioral guidelines (wear a mask,
distance, wash hands) if they endorsed difficulty-as-importance and difficulty-as-improvement
mindsets.
The extent to which people endorsed each mindset was associated with their endorsement
of other mindsets. People who endorsed difficulty-as-importance were more likely to endorse
difficulty-as-improvement and less likely to endorse difficulty-as-impossibility. Yet, as revealed
in our structural equations model, each difficulty mindset had a unique and distinguishable effect
on identity construction: the likelihood that people found a pandemic-related silver lining for
themselves. We also predicted and found that people who endorsed difficulty-as-improvement
would create a social identity of silver linings for their communities. We predicted but did not
find that people who found a silver lining for their community would be more likely to take
CDC-recommended action. Our results imply a unique benefit of creating a new personal
identity of seeing a silver lining for oneself, at least in our American sample. Our data were
collected during the COVID-19 pandemic, but we assume that our results are applicable to other
kinds of community-level life difficulties such as fires, floods, wars, and other situations in
which people face both a life difficulty and a set of new challenging tasks and goals which they
28
may or may not find identity-congruent.
We explored the effect of difficulty-as-impossibility, the belief that difficulty engaging
with a task or goal implies that succeeding is unlikely, perhaps even impossible for the self. We
did not find an additive positive or negative effect of difficulty-as-impossibility, after accounting
for difficulty-as-improvement and difficulty-as-importance mindsets. We infer from our results
that during a crisis, interpretations of difficulty as chances for self-improvement and as signals of
the importance of engaging in relevant tasks help people find a silver lining and take necessary
action. We did not have a clear prediction for difficulty-as-impossibility because prior research
has focused on difficulty engaging in tasks and goals that have already been associated with an
identity while our research focused on creation of a new identity.
We also explored the role of political identity (being a conservative, a Republican, or
Republican-leaning versus a Democrat or Democratic-leaning) in seeing a silver lining and
taking action. People with conservative identities were less likely to take action. These results are
congruent with other reports that Republicans have come to identify taking CDC-recommended
preventive action as identity-incongruent (Grossman et al., 2020; Niemi et al., 2021) and are
more likely to believe that government sources exaggerate the danger of COVID-19 (The
Economist/YouGov Poll, July 10 to 13, 2021). However, we also found that the relationships
among endorsing each difficulty mindset, silver linings, and action were the same across political
identities. These results support our identity-based motivation prediction that
difficulty-as-importance and difficulty-as-improvement mindsets help people cope in a crisis by
scaffolding identities of growth and positive meaning-making. People who experience
difficulties as signals of importance and as opportunities for self-improvement are more likely to
see crisis-related silver linings for themselves. Seeing these silver linings for oneself in turn may
29
motivate people to take on novel behaviors in times of crisis. As our results show, the particular
course of action people take depends on the extent that these actions feel identity congruent,
something that is dependent on the context.
Limitations and Future Directions
Any study is limited, and here we focus on four limitations of the present research (focus
on COVID-19, panel design, online panel, U.S. only sample). First, we studied responses during
a particular national and worldwide crisis, COVID-19, rather than sampling across personal,
community, and other crises. Understanding how identity-based motivation might matter during
COVID-19 is important because the pandemic was and continues to be devastating to
populations worldwide. At the same time, COVID-19 might be unique. In addition to its death
toll, its novelty, and the never prior experienced national response in the form of shutdowns of
public spaces and workplaces created massive uncertainty. People could no longer be certain
about every aspect of their lives, their finances, work, and what to do generally, experienced
physical illness and its longer-term consequences, as well as other life difficulties including
social isolation and loss of daily structure (Keeter, 2021; Van Kessel et al., 2021). Though we
believe that our results may generalize to other times of crisis, future research is needed to test
our predictions in other crisis situations.
Second, regarding our design choice, we collected data at three points fitting the first
three waves of COVID-19 in the U.S., but our panel design means that our data are
cross-sectional. We cannot study causal processes, even in interpreting our mediation analysis.
Mediation analysis allows us to test the significance of a hypothetical mediator (finding a silver
lining), but mediation cannot help us infer whether that mediator is the true mediator (Fiedler et
al., 2011). We focused on taking action as our outcome and finding a silver lining as our
30
mediator but taking action may affect the subsequent likelihood of finding a silver lining (e.g., a
reciprocal relationship). Our analyses suggest total and indirect effects of endorsing
difficulty-as-importance and an indirect effect of endorsing difficulty-as-improvement on
behavior via finding a silver lining. People who endorse difficulty-as-importance and
difficulty-as-improvement may find silver linings in part because they are adopting necessary
preventive behaviors. It may be that finding a silver lining and taking necessary action are two
separate consequences of endorsing difficulty-as-importance and difficulty-as-improvement.
What we can show is that our theorized process could matter. Future research using COVID-19
or other kinds of personal, community-level, and nation-level life difficulties could take the next
step by using a longitudinal, rather than a panel design, to better understand causal and reciprocal
processes.
Regarding our choice of an online panel, we recruited adults. These adults are more
representative than a sample of college students; at the same time, as we found in our exploratory
analyses, our participants on average reported relatively few difficulties in various life domains
(health, financial, and other obligations). In our exploratory analyses, we found that people who
reported experiencing more pandemic-related hardships were higher in their endorsement of
difficulty-as-importance, more likely to experience a pandemic-related silver lining, and more
likely to take action. However, our data could not capture the full range of experienced
difficulties. Our results might have been stronger, or we might have found effects of endorsing
difficulty-as-impossibility had we sampled healthcare workers or people whose lives were
upended through loss of job, home, loved ones, or personal health. The pandemic might have
affected people of different ages and at different life phases differently and age and economic
circumstance might matter for endorsement of difficulty mindsets and silver linings. Though our
31
data might reflect the modal experience of the pandemic, future research should focus on the
most negatively impacted populations.
Finally, our focus on the U.S. allowed us to document that the pattern of relationships that
we found remained stable across three panels. At the same time, it may be that some of our
findings may not be fully generalizable to other countries and societies. We focused on a creation
of a particular novel identity of being a person who finds silver linings for themselves. In other
countries, other novel identities or adding novel aspects to existing identities may have parallel
effects. For example, in times of crisis, people who endorse difficulty-as-importance and
difficulty-as-improvement mindsets might be more likely to expand their conscientious person
identities to include following health- or other guidelines. Similarly, we found that endorsing
difficulty-as-improvement was associated with finding silver linings for one’s community but
was not associated with taking action. These relationships may be culture-bound. It is possible
that when collectivistic or honor mindsets are salient, people who find a silver lining for their
community would be more likely to take preventive action (e.g., Wang et al., 2021). These are
questions for future research.
Conclusion
We demonstrated that in a time of crisis, how people interpret difficulty matters. People
are more likely to construct an identity as someone who finds crisis-related silver linings if they
interpret difficulties thinking about or engaging in tasks as signals of the importance of the task
for them (termed difficulty-as-importance). The same is true for people who interpret life
difficulties as opportunities for self-improvement (termed difficulty-as-improvement). People
who endorse difficulty-as-importance are more likely to take crisis-relevant difficult but
necessary actions. The same is true for people who take on silver linings identities. Our results
32
provide new insights into how identity-based motivation can support or undermine identity
construction and relevant action during a crisis.
33
Chapter 2
I’ll take the high road: Paths to goal pursuit and identity-based interpretations of difficulty
Gülnaz Kiper
1
and Daphna Oyserman
1
, Veronica X. Yan
2
1
Department of Psychology, University of Southern California
2
Department of Educational Psychology, The University of Texas at Austin
Abstract
When people imagine their futures, they can prioritize getting there the easy way, prefer more
demanding paths, or be indifferent to means and focus only on making progress. Identity-based
motivation theory predicts that difficulty mindsets—what people infer about themselves from
experiencing difficulty thinking about or working on tasks or goals and facing life
difficulties—shape action. When thinking or doing feels hard, people vary in how much they
infer that the hard thing is not for them (difficulty-as-impossibility) or valuable for them
(difficulty-as-importance). When life feels hard, people vary in how much they infer that
enduring difficulty can be character-building (difficulty-as-improvement). We predict, and mixed
effect regression equations reveal, that difficulty mindsets shape the means people prefer to reach
their goals (N = 537 undergraduates, three studies). People who endorse
difficulty-as-impossibility choose ease --people who endorse difficulty-as-improvement disdain
it. In contrast, high difficulty-as-importance and high difficulty-as-improvement scorers prefer
the hard way.
Keywords: Difficulty mindsets; means-ends; identity-based motivation theory; academic goals;
health goals; possible selves
34
I’ll take the high road: Paths to goal pursuit and identity-based interpretations of difficulty
Say you want to get fit. You hear that electrical pulses can strengthen your abdominal
muscles. Would you go for that, or would the thought that no effort is required sour you on this?
Would you instead prefer taking the high road and sweating to progress through floor exercises?
Say you have a school-focused possible self. What seems like a more effective means to make
progress, a means of studying that feels easy to do or one that feels harder? Students often pursue
both health and academically-focused possible selves (e.g., Benau et al., 2019; Lowry et al.,
2000; VanOra, 2019), and making progress requires taking action (for a review, O’Donnell &
Oyserman, 2022). But, as our opening examples attest, they can choose from more and less
effortful means to get there (and a booming market offers various aids, Whitney & Viswanath,
2004). In the current studies, we consider individual differences in how much people prefer
easier and harder means to progress toward attaining their possible selves. At first pass, it might
seem to go without saying that easy is better. After all, when considering a product, no one
prefers spending more to attain a product available for less elsewhere. However, as highlighted
in the so-called IKEA effect (Norton et al., 2012), sometimes people like products more if they
expend effort on obtaining them (e.g., Inzlicht et al., 2018).
We build on identity-based motivation theory to predict that preferring easy or more
effortful means is identity-based (Oyserman, 2007; Oyserman & Dawson, 2021). The inferences
people draw about themselves when they experience difficulty shape their preference for easy or
more effortful means toward goal attainment. Our predictions address a “means gap” in the goal
literature (King et al., 1998, including health interventions, e.g., Cugelman et al., 2011; learning,
e.g., Bereiter & Scardamalia, 2018; and achievement goals, e.g., Dweck, 1986; Hulleman et al.,
2010). This literature does not consider individual differences in preference for effortful or easy
35
means. For example, the achievement orientation literature highlights differences in how students
perceive their academic goals—as standards or as skills and proficiencies to attain or avoid
failing to get (termed performance and mastery goals, Dweck, 1986; Hulleman et al., 2010). But
it does not examine differences in preference for easier or harder means to achieve these desired
ends. Before proceeding, we describe the Identity-based motivation theory (IBM) and articulate
the bases for our predictions.
Identity-based Motivation Theory (IBM)
IBM is a social psychological theory of self-regulation, goal pursuit, and motivation
(Oyserman, 2007; 2009; Oyserman et al., 2017; Yan et al., 2022). IBM describes a recursive
relationship between what people do, how they make sense of themselves, and how they interpret
their experiences of ease and difficulty while thinking about or working on tasks and goals. IBM
theory posits that people prefer to act in identity-congruent ways (termed action-readiness), but
which identities come to mind and what they imply for action and for interpretation of
experience (termed procedural-readiness) is dynamically constructed in context. People can
interpret their experiences of difficulty working on or thinking about tasks and goals in two ways
--task importance (difficulty-as-importance mindset) and low odds of task success
(difficulty-as-impossibility mindset). When tasks feel important, they may feel
identity-congruent, “me” or “us” things to do. When the odds of success are very low, engaging
may feel identity irrelevant or even incongruent, not “me” or “us” things to do. IBM theory also
describes inferences people can make regarding their experiences of life difficulties—they can
infer from these unbidden difficulties that they may become better, improved versions of
themselves (a difficulty-as-improvement mindset).
Difficulty Mindsets and Action-Readiness
36
IBM theory predicts that accessible difficulty mindsets shape whether and how people
pursue their goals for their future selves (Oyserman & Horowitz, 2022) and how they face life’s
challenges (Yan et al., 2022). Specifically, applying a difficulty-as-importance rather than a
difficulty-as-impossibility mindset can increase the likelihood of taking goal-focused action, and
endorsing difficulty-as-improvement can increase the chances of accepting setbacks without
losing hope. Indeed, students spend more time on (Elmore et al., 2016; Smith & Oyserman,
2015), perform better on (Oyserman et al., 2018), and value (Aelenei et al., 2017) school tasks
more when led to consider difficulty-as-importance rather than difficulty-as-impossibility.
Similarly, people report that proactive health measures are less likely to work for them after
experiencing difficulty imagining similarities between their in-group and the people they believe
do take these measures (Oyserman et al., 2007). Dieters report less temptation to overeat and eat
less in a taste test if researchers lead them to view difficulties with dieting as signaling the
importance and necessity of engagement rather than the impossibility of success (Lewis & Earl,
2018). Moreover, people who endorse difficulty-as-improvement are more likely to see silver
linings for themselves and their communities during the COVID-19 pandemic (Kiper et al.,
2022). They are more likely to see themselves as optimistic, virtuous, and conscientious people
who live lives of meaning—traits that predict resilience when faced with challenges (Yan et al.,
2022).
Difficulty-Mindsets and Means to Goal Attainment
Though documenting that difficulty mindsets matter for action-readiness, prior studies do
not address whether they also direct attention toward a particular means of goal pursuit. In the
current studies, we address this gap. We predicted that difficulty-as-impossibility and
difficulty-as-improvement direct attention to particular kinds of means and explored the possible
37
role of difficulty-as-importance.
Specifically, IBM theory implies that people who score high in difficulty-as-impossibility
should prefer the easy way. After all, this mindset highlights the odds of success. If easy means
do not exist, it might be better to shift rather than fruitlessly persist. Regarding
difficulty-as-improvement, people who score high on difficulty-as-improvement should prefer
effortful means for two reasons. First, people may carry over their inference that unbidden life
difficulties can have a positive character-building effect, resulting in a sense that the hard way is
the better way to work on their possible selves. Second, difficulty-as-improvement emerges from
culture-based explanations for suffering, including religious and spiritual explanations that link
being moral to doing things the hard way—restricting, fasting, and abstaining (Yan et al., 2022).
People higher in difficulty-as-improvement might see virtue in taking the high road, the effortful
route to a goal.
Current Studies
We conducted three studies. Each specified a goal common for students. We started with
health (exercise, Study 1; weight, Study 2) and broadened to being a successful student (Study
3). We offered more and less effortful goal-pursuit means and had students rate them on three
dependent variables (DV1 to DV3). DV1 was the value of putting in effort when using this
means. DV2 was the perceived effectiveness of the means. DV was the person’s reported
likelihood of use. We also obtained ratings of how hard the means was to use as a control.
Building on the literature, we made two predictions about difficulty-as-impossibility and
difficulty-as-improvement (H1, H2) and explored one research question (RQ1) about
difficulty-as-importance. H1: People higher in difficulty-as-impossibility prefer less effortful
goal-pursuit means (pre-registered Studies 2, 3), not more effortful ones (pre-registered Study 2).
38
H2: People higher in difficulty-as-improvement prefer more effortful goal-pursuit means
(pre-registered Studies 2, 3). RQ1: Do people higher in difficulty-as-importance prefer more
effortful goal-pursuit means (pre-registered as a prediction in Study 2, as exploratory in Study
3)?
In Study 2, we pre-registered two exploratory analyses involving gender and weight goal
relevance, asking if having experience with weight goals or being a woman moderates effects.
We also pre-registered a secondary prediction: people believe that weight strategies they find
hard are more effective and require more of their effort.
In Study 3, we pre-registered three exploratory analyses: We explored the
difficulty-mindset-to-DV association in the context of (1) students’ preferred study method and
(2) the goal attainment methods we used as filler items. (3) We explored each
difficulty-mindset-to-achievement-orientation association.
Open Science and Stop Rules
We provide the measures, data, R scripts, Supplemental Materials for Studies 1 to 3, and
the pre-registrations for Studies 2 and 3 on the Open Science Framework
at https://osf.io/u7dbm/?view_only=235c171b61a842ff989f292bfcb995c0. Supplemental
Materials provide detailed descriptives of race-ethnicity, the questionnaires, measurement
construction, and additional analyses. In Studies 1 and 3, we aimed to recruit 200 people. In
Study 2, we aimed for 330 with at least 200 women for exploratory sex analyses, but the
semester ended before we could. We included all participants except the eight who failed the
attention check in Study 2—the only study with an attention check.
Samples
Undergraduates signed up through The University of Texas at Austin (UT) or the
39
University of Southern California (USC) subject pool to participate in a 10-15 minute study for
course credit. Study 1, N = 197, n = 22 UT, n = 175 USC, 131 females, Mage = 19.95, SDage =
3.09; Study 2, N = 136 USC, 89 females, Mage = 20.06, SDage = 1.35; Study 3 N = 204 USC,
130 females, Mage = 20.17, SDage = 2.06). We detail in Supplemental Materials our full
distribution by race/ethnicity. Our samples were diverse --the groups representing at least 10% of
a sample were: Study 1, 42% white, 25% Asian, 13% Hispanic; Study 2, 44% white, 22% Asian,
12% Hispanic; and Study 3, 41% white, 28% Asian, 13% Hispanic.
Procedure
We programmed and administered our surveys through Qualtrics. After consenting,
students imagined they had a goal—core and abdominal muscles (Study 1), an ideal weight
(Study 2), or being a good student with good grades (Study 3). Then they saw one of six (more
or less effortful) ways to attain the goal (the order of presentation was randomized). They rated
how hard it would be to use (control variable), how much of their effort they would need to
expend to be successful (DV1), how effective they thought the means would be (DV2), and their
likelihood of using it (DV3). They repeated this process six times, once for each means (in Study
3, they then wrote in the study method they most commonly used, rated it as just described, and
responded to the mastery and performance orientation items presented in a randomized block).
Next, students rated how much they agreed or disagreed with the 4-items
difficulty-mindset scales, presented as 12 statements in randomized order. Finally, students
provided demographics. In Study 2, they also reported if they currently or previously had a
weight goal. We detail the strategies students rated and our dependent measures next.
Measures
Pilot Study Measure Development
40
To develop Study 1 and Study 2 materials, we piloted ways to assess preferred means
(Study S1 in Supplemental Materials; N = 195, 132 females, Mage = 20.12). Our final dependent
variables entailed rating some common more- and less-effortful ways college students can work
on exercise and weight goals (Table 1). For Study 3, we piloted a list of 24 means to develop our
materials (Study S2 in Supplemental Materials; N=196; 91 females; Mage = 20.34). We used
student responses to choose nine means: three high-effort (Table 1), three low-effort (Table 1),
and three mid-range effort fillers (Talk through and explain important concepts [whether to
yourself or someone else]; create flashcards; write a summary of key points at the end of each
paper or while I am reading).
Table 1
Studies 1 to 3: Working on Goals, More and Less Effortful Means
Means
Type Study
Study 1: Core and
Abdominal Strength
Study 2: Attain and
Maintain Ideal Weight
Study 3: Attain Good Grades
Higher
Effort
(1) Ab roller
(2) Ab bench
(3) Floor mat
(4) Exercise ball
(1) Fasting
(2) Weight loss program
(3) Calorie tracking
(4) Restriction
(1) Study 4-5 hours a day
(2) Re-read chapters
(3) Re-watch lectures
Lower
Effort
(1) Surgery
(2) Ab stimulator
(1) Surgery
(2) Liposuction
(1) Paraphrase
(2) Find assignments online
(3) Get answers
Dependent Variables
We present the specific wording for DVs 1, 2, and 3 in Table 2. We used multilevel
Exploratory Factor Analysis (EFA) to test our assumption that they would load onto a single
factor. Surprisingly, these analyses revealed that each is distinct at the within and the between
41
levels (see Dependent Measure Construction in Supplemental Materials). Hence, we conducted
separate regressions for each DV even though we did not have a theoretical reason to expect
different patterns of results.
Table 2
Studies 1-3: Dependent Variables
DV Study 1 Study 2 Study 3
DV1: Own Effort
Matters
If you use [means], how
much does success
depend on your own
efforts?
How much effort would
[means] require of you?
If you used [means],
how much of your
own effort would you
need to expend to
attain your goal?
If you were to
[means], how much
would success
depend on your own
efforts?
DV2: Effective
Means
How effective do you
think [means] would be
for you?
How effective do you
think [means] would
be for you?
How effective
would it be for you
to [means]?
DV3: Likelihood of
Use
Putting aside concerns
about cost or access,
how likely would you
be to use [means] to
reach your goal?
How likely is it that
you will use [means]
to reach your goal?
How likely are you
to [means] as a way
of getting good
grades?
Note. DV=Dependent Variable. In Study 1, we assessed the Own Effort DV with two items.
Difficulty-Mindsets
We assessed difficulty-as-importance, difficulty-as-impossibility (Fisher & Oyserman,
2017), and difficulty-as-improvement (Kiper et al., 2022) in a single block in randomized order
with a response scale of 1 = strongly disagree to 6 = strongly agree. We present item wording,
scale means, standard deviations, and Cronbach’s α reliability in Table 3. Each mindset was
distinct but correlated. Thus, endorsing difficulty-as-impossibility correlated negatively, though
not necessarily significantly, with endorsing difficulty-as-importance in the range of -.22 < r <
-.08 (Study 1 r = -.21, p = .003; Study 2 r =-.22, p = .010; Study 3 r=-.08, p = .228). The same
42
pattern of negative correlation held for difficulty-as-improvement, with the range being -.26 < r
< -.22 (Study 1 r = -.26 p <.001; Study 2 r =-.22, Study 3 r=p = .009; -.22, p = .002). Endorsing
difficulty-as-importance was positively correlated with endorsing difficulty-as-improvement
(Study 1 r = .48, p <.001; Study 2 r =.55, p <.001; Study 3 r=.58, p <.001).
Table 3
Studies 1 to 3: Difficulty-Mindset Scale Statements and Descriptives
Scale Name
Item Difficulty-as- Impossibility Difficulty-as- Importance Difficulty-as- Improvement
1 Sometimes if a task feels
difficult, my gut says it is
impossible for me.
Sometimes if a task feels
difficult to me my gut
says that it really matters
for me.
In a way, the struggles I
have today are
strengthening my character
to meet tomorrow's
challenges.
2 If a goal feels difficult to
work on, I often think it
might not be for me.
If a goal feels difficult to
work on, I often think it
might be a critical one for
me.
Experiencing difficulty
makes me grow stronger.
3 When a task feels difficult,
the experience of difficulty
sometimes informs me that
succeeding in the task is
just not possible for me.
When a task feels
difficult, the experience
of difficulty sometimes
informs me that
succeeding in the task is
important for me.
Experiencing difficulty is
the strongest of teachers; I
may temporarily feel
broken but in the long run,
I will be better.
4 Often when a goal feels
difficult to attain it turns
out to be out of my reach.
Often when a goal feels
difficult to attain it turns
out to be worth my effort.
Life is not complete
without difficulty, hardship,
and suffering.
Scale Descriptives
Study M SD α M SD α M SD α
1 2.55 1.01 0.89 4.28 0.93 0.89 4.97 0.89 0.88
43
2 2.67 1.04 0.91 4.3 0.92 0.9 4.97 0.86 0.88
3 3.09 1.18 0.83 4.44 0.92 0.83 4.87 0.94 0.84
Control Variable
We controlled for individual differences in how hard students thought a particular way of
making progress would be in our analyses. We did this as there is no way to calibrate a priori the
relative difficulty of each means compared to each of the other means and because experienced
difficulty can differ by person. In Study 1, we averaged two responses (“How difficult would
[means] be to use for you?” and “How much discomfort would you feel while using [means]?”).
In Studies 2 and 3, we obtained a single response (Study 2: “How difficult is it for you to use or
imagine using [means]?”, Study 3: “How difficult would it be for you to [means]?”).
Exploratory Variables
Weight Salience. In Study 2, we asked four questions about experiences with weight
goals. Q1 “Are you currently trying to lose weight?” (67% were), Q2 “Are you currently trying
to maintain your weight?” (77% were); Q3 “Have you gained or lost weight recently due to
Covid-19?” (63% had) and Q4 “Have you previously ever pursued a method to lose weight?”
(65% had). Following our pre-registration, we created a sum score from the four questions. Due
to researcher error, we did not use a yes/no response option in Q1, Q2, or Q3, so we re-coded
responses to no=0 or yes=1 dichotomies before summing to create a composite “weight salience”
score. Q1 and Q2, original: 1 = not at all, 2 = slightly, 3 = actively; Q1 and Q2 became: no=1
yes=2, 3. Q3 original: 1 = Lost weight, 2 = Lost weight slightly, 3 = weight has stayed the same,
4 = Gained weight slightly, 5 = Gained weight; became no=1, 2, 3 yes=4, 5. Weight salience
scores could range from 0 = no to 4 = yes across all four questions (M=2.48, SD=1.15).
44
Gender. We explored whether being a woman moderates the association between weight
goals and difficulty mindsets in Study 2.
Students’ Study Means. In Study 3, students rated their way of studying on our DVs.
They read: “Finally, we want to ask you about the method you most often use when you try to
get good grades from classes. In the box below, type in the strategy you most often use:”
Students wrote things like “I rewatch lecture videos” and “I make flashcards” (Supplemental
Materials provides more examples).
Filler Strategies. Our Study 3 filler items were rated as mid-range effortful, as described
above in our Pilot Studies Section (talking through and explaining important concepts, creating
flashcards, and writing summaries of key points). Our predictions focused on high- and
low-effort strategies; hence analyses were exploratory.
Performance and Mastery Orientation. We used 12 face-valid statements (six each for
performance and mastery, half of each focused on approaching success and half on avoiding
failure, 1 = strongly disagree to 6 = strongly agree, based on Hulleman et al., 2010). Example
items: (mastery) “learning as much as I can” and (performance) “getting a good GPA”
(Supplemental Materials, Study 3 Measure Construction provides all items and the EFA). The
EFA suggested two constructs: performance (M = 5.09, SD = .86, α = .89) and mastery (M =
4.76, SD = .74, α = .79). Performance and mastery scores are distinct but correlated (r = 0.22, p =
.002).
Results
Analytic Strategy for Regressions
We performed multilevel EFAs using Mplus (Muthén & Muthén, 1998-2017) and all
other analyses using the psych (v. 2.1; Revelle, 2021) and lme4 (v. 1.1-23; Bates et al., 2015)
45
packages in R programming language (R Core Team, 2020). To test H1 and RQ1, we examined
participants' ratings (DV1, DV2, DV3) for the less effortful means by running a linear mixed
effects model for each DV with the three difficulty mindsets as predictors. To test H2 and RQ1,
we examined participants' ratings for the more effortful means using the same analytic strategy
we just described. In each model, we included as controls the specific way of exercising or
working on a weight goal or studying, and level-1 and level-2 student-reported perceived
hardness of working toward that goal in that way.
Figure 1 displays regression results by DV for H1 and RQ1 with the unstandardized
regression coefficient of each difficulty mindset with 95% Confidence Interval whiskers as a
meta-analytic summary across studies. Figure 2 does the same for H2 and RQ1. Tables 4 and 5
detail these results, adding the p-values and model R2 for each DV for each study (and the
meta-analytics summary presented in Figures 1 and 2). To avoid over-interpreting fluctuations
that may not be stable, we focus on a meta-analytic summary in our description of our results.
We detail model development in the Supplemental Materials.
Testing H1 and RQ1: Preference for Less Effortful Means to Attain Goals
H1 predicts that people higher in difficulty-as-impossibility prefer less effortful means.
Indeed, difficulty-as-impossibility adds to the explained variance for two of our three DVS
(perceived effectiveness and likelihood of using). Effects are stable after controlling for the other
mindsets, the specific ways of exercising, maintaining weight, or studying, and how hard people
found each way of exercising or maintaining weight or studying.
RQ1 asks if people higher in difficulty-as-importance prefer or disdain less effortful
means. As depicted in Figure 1 and specified in Table 4, we find no significant effect of
difficulty-as-importance on our three DVs, implying that people higher in
46
difficulty-as-importance are indifferent to these less effortful means of goal attainment.
We did not have a prediction for whether people who are higher in
difficulty-as-improvement prefer or disdain less effortful means. As depicted in Figure 1 and
specified in Table 4, we found a positive association with two of three DVs (own effort matters
and likelihood of using). People higher in difficulty-as-improvement were less likely to perceive
their effort as mattering for these means and were less likely to use them.
Testing H2 and RQ1: Preference for More Effortful Means to Attain Goals
H2 predicts that people higher in difficulty-as-improvement prefer more effortful means.
Indeed, our analyses reveal that difficulty-as-improvement adds to the variance explained in each
of our three DVS. RQ1 asks if people higher in difficulty-as-importance prefer or disdain more
effortful means. We find that they find these means more effective and are likely to use them.
We explored whether people who are higher in difficulty-as-impossibility prefer or
disdain more effortful means. Unexpectedly, people who endorsed difficulty-as-impossibility
also reported a higher likelihood of using effortful means.
Summary
We did not expect our three DVs to be distinct, but they were, forcing us to analyze more
associations than initially planned. In this section, we consider the findings separately for each
DV .
Does your effort matter if you take this path? Regarding whether one’s effort matters,
our results suggest that this is relevant to difficulty-as-improvement and not to the other
difficulty mindsets. People who endorsed difficulty-as-improvement believed their efforts
mattered for means that were more effortful and not for less effortful ones. People’s
47
difficulty-as-importance and difficulty-as-impossibility scores were not associated with this DV .
These results are not compatible with H1 and are compatible with H2.
Is this path an effective way to get to your goal? Our results suggest that responses
depended on the means in question. People who endorsed difficulty-as-impossibility found less
effortful means to be effective. People who endorsed difficulty-as-improvement and
difficulty-as-importance found more effortful means to be effective. These results are compatible
with H1 and H2.
Will I do this? People with higher difficulty-as-impossibility scores reported they were
likely to use more and less effortful means (the latter score was influenced by responses to the
exercise study). Difficulty-as-importance was associated with using effortful means.
Difficulty-as-improvement was associated with a lower likelihood of using low-effort means and
a higher likelihood of using high-effort means. While compatible with H1 and H2, the
high-effort finding for people who endorse difficulty-as-impossibility was unexpected. Current
data could not support further exploration.
48
Figure 1
Testing H1 and Examining RQ1 with Less Effortful Means: Difficulty Mindset Meta-Analytic
Regression Results for DV1 to DV3
49
Note. Circles represent the unstandardized regression coefficient estimates associated with each
difficulty mindset by study, and triangles represent the meta-analytic regression coefficient
associated with each difficulty mindset. Whiskers represent 95% Confidence Intervals of the
estimates.
Table 4
Testing H1 and Examining RQ1 with Less Effortful Means: Difficulty Mindset Regression Results
DV Predictor Estimate 95% CI p Marginal R
2
Own Effort Matters
Study 1 Impossibility 0.16
**
[0.06, 0.26] .003 .48
Importance -0.02 [-0.15, 0.10] .701
Improvement -0.01 [-0.14, 0.12] .883
Study 2 Impossibility 0.05 [-0.18, 0.29] .657 .04
Importance 0.24 [-0.06, 0.54] .122
Improvement -0.35
*
[-0.67, -0.02] .041
Study 3 Impossibility -0.02 [-0.13, 0.09] .758 .11
Importance -0.03 [-0.19, 0.13] .730
Improvement -0.17
*
[-0.34, -0.01] .044
Meta-analysis Impossibility 0.04 [-0.02, 0.11] .220 .21
Importance 0.03 [-0.06, 0.12] .482
Improvement -0.16
**
[-0.25, -0.06] .001
Effective Means
Study 1 Impossibility 0.32
***
[0.16, 0.48] <.001 .05
Importance 0.11 [-0.08, 0.29] .263
Improvement -0.04 [-0.24, 0.16] .709
Study 2 Impossibility 0.10 [-0.12, 0.32] .377 .17
Importance -0.31
*
[-0.59, -0.03] .035
Improvement 0.11 [-0.20, 0.41] .506
Study 3 Impossibility 0.08 [-0.05, 0.21] .254 .12
Importance -0.05 [-0.25, 0.15] .619
Improvement -0.06 [-0.26, 0.13] .530
Meta-analysis Impossibility 0.19
***
[0.12, 0.27] <.001 .07
Importance -0.07 [-0.18, 0.03] .181
Improvement -0.02 [-0.13, 0.09] .660
50
Likelihood of Using
Study 1 Impossibility 0.39
***
[0.24, 0.54] <.001 .16
Importance 0.04 [-0.14, 0.22] .695
Improvement -0.09 [-0.28, 0.11] .378
Study 2 Impossibility 0.16
*
[0.02, 0.31] .034 .25
Importance -0.02 [-0.20, 0.17] .852
Improvement -0.03 [-0.23, 0.17] .780
Study 3 Impossibility 0.12 [0.00, 0.24] .051 .08
Importance -0.08 [-0.26, 0.10] .408
Improvement -0.19
*
[-0.37, -0.01] .043
Meta-analyses Impossibility 0.23
***
[0.17, 0.30] <.001 .12
Importance -0.03 [-0.12, 0.06] .527
Improvement -0.14
**
[-0.24, -0.05] .004
Note. *p < .05, **p < .01, ***p < .001
51
Figure 2
Testing H2 and Examining RQ1 with More Effortful Means: Difficulty Mindset Meta-Analytic
Regression Results for DV1 to DV3
52
Note. Circles represent the unstandardized regression coefficient estimates associated with each
difficulty mindset by study, and triangles represent the meta-analytic regression coefficient
associated with each difficulty mindset. Whiskers represent 95% Confidence Intervals of the
estimates.
Table 5
Testing H2 and Examining RQ1 with More Effortful Means: Difficulty Mindset Regression
Results
DV Difficulty Mindset Estimate 95% CI p Marginal R
2
Own Effort Matters
Study 1 Impossibility -0.02 [-0.13, 0.09] .695
Importance -0.06 [-0.19, 0.08] .419 .25
Improvement 0.22
**
[0.08, 0.36] .002
Study 2 Impossibility 0.11 [-0.04, 0.26] .147 .17
Importance -0.15 [-0.34, 0.05] .139
Improvement 0.28
*
[0.07, 0.49] .012
Study 3 Impossibility -0.13
*
[-0.23, -0.03] .012 .24
Importance 0.16
*
[0.01, 0.31] .043
Improvement 0.20
**
[0.05, 0.35] .009
Meta-analysis Impossibility -0.01 [-0.06, 0.04] .692 .20
Importance -0.02 [-0.09, 0.05] .535
Improvement 0.23
***
[0.16, 0.30] <.001
Effective Means
Study 1 Impossibility 0.01 [-0.11, 0.13] .833 .12
Importance 0.06 [-0.08, 0.20] .406
Improvement 0.23
**
[-0.08, 0.20] .003
Study 2 Impossibility 0.04 [-0.10, 0.18] .601 .17
Importance -0.01 [-0.19, 0.18] .920
Improvement 0.25
*
[0.06, 0.45] .015
53
Study 3 Impossibility 0.02 [-0.09, 0.12] .742 .11
Importance 0.21
*
[0.05, 0.37] .012
Improvement 0.16 [-0.01, 0.32] .062
Meta-analysis Impossibility 0.03 [-0.03, 0.09] .327 .11
Importance 0.09
*
[0.01, 0.17] .022
Improvement 0.22
***
[0.13, 0.30] <.001
Likelihood of Use
Study 1 Impossibility 0.02 [-0.11, 0.15] .778 .15
Importance -0.07 [-0.23, 0.09] .378
Improvement 0.40
***
[0.24, 0.57] <.001
Study 2 Impossibility 0.04 [-0.11, 0.19] .592 .34
Importance 0.08 [-0.12, 0.27] .442
Improvement 0.21 [0.00, 0.43] .051
Study 3 Impossibility 0.10 [-0.02, 0.22] .095 .15
Importance 0.21
*
[0.03, 0.39] .027
Improvement 0.06 [-0.13, 0.24] .539
Meta-analysis Impossibility 0.08
*
[0.02, 0.15] .016 .18
Importance 0.09
*
[0.00, 0.18] .039
Improvement 0.22
***
[0.13, 0.31] <.001
Note. *p < .05, **p < .01, ***p < .001
Study 2 and Study 3 Pre-registered Exploratory Analyses
Study 2: Moderating Effect of Gender and Goal Relevance. We planned to explore
whether being a woman and weight goal relevance moderate the association between
difficulty-mindsets and our DVs. Weight was a relevant goal for most participants, but our
weight goal score did not significantly moderate results. Given the ubiquity of weight goals, it
might be accurate to say that our results come from a sample of participants with personal
54
experiences with weight goals. Regarding gender, only one of the 18 possible
difficulty-mindset-by-way-of-maintaining-weight interactions was significant without a
Bonferroni correction (none were once we added it). At the same time, we are underpowered to
examine if being a woman moderated effects because we had only 47 men in the sample. We also
predicted that if a means felt hard to do, people would believe their effort mattered and that it
would feel effective. As detailed in Supplemental Materials, results support our mattering
prediction for more-effortful means --fasting, weight loss program, calorie tracking, restriction,
not less-effortful ones --surgery, liposuction) and did not support our effectiveness prediction.
Study 3: Students’ Study Method. In terms of perceived hardness, students rated their
way of studying as about as effortful (M = 2.77, SD =1.26) as they rated less effortful ways (M =
2.42, SD = 1.37). We explored the relationship between difficulty mindsets and our DVs for
students’ way of studying using the regression models (one for each DV) we used for our H1 and
H2. As detailed in Figure 3 and Table 6, people who scored higher in difficulty-as-improvement
rated their way of studying as one in which their effort mattered and said they were likely to use
it. No other relationships were significant, though the pattern of results for perceived
effectiveness suggests that people higher in difficulty-as-improvement found their way of
studying effective while people higher in difficulty-as-impossibility did not.
55
Figure 3
Study 3: Difficulty Mindsets and Likelihood of Using, Effectiveness, and Effort Matters in Using
Students’ Own Study Method
Note. Circles represent the unstandardized regression coefficient estimates associated with each
difficulty mindset and whiskers represent 95% Confidence Intervals of the estimates.
Table 6
Study 3: The Association Between Difficulty Mindsets and DVs for Students’ Study Method
DV Difficulty Mindset Estimate 95% CI p
Adjusted
R2
Own Effort
Matters
Impossibility -0.05 [-0.16, 0.06] .394
0.05 Importance 0.05 [-0.12, 0.22] .536
Improvement 0.20
*
[0.03, 0.37] .021
Effective
Means
Impossibility -0.10 [-0.20, 0.00] .057
0.08 Importance 0.13 [-0.03, 0.29] .100
Improvement 0.15 [-0.01, 0.30] .071
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Likelihood of
Using
Impossibility -0.08 [-0.18, 0.03] .140
0.12 Importance 0.04 [-0.11, 0.20] .579
Improvement 0.25
**
[0.09, 0.41] .002
Note. *p < .05, **p < .01,
Study 3: Midrange Effortful Means. We found a significant positive association
between difficulty-as-improvement (not difficulty-as-importance or difficulty-as-impossibility)
and each of our three DVs. We detailed the results of this exploratory regression in Figure S1 in
Supplemental Materials (Study 3 Additional Analyses).
Study 3: Association Between Difficulty Mindsets and Achievement
Orientation. Exploratory analyses suggest that our difficulty mindsets are not redundant with
performance or mastery orientation. Bivariate correlations suggest that difficulty-as-impossibility
was not associated with either mastery (r = -.05, p = .510) or performance (r = .00, p = .987)
orientation while difficulty-as-importance and difficulty-as-improvement were only associated
with mastery (difficulty-as-importance: mastery r = .23, p = .001, performance r =.08, p = .249;
difficulty-as-improvement: mastery r = .26 p < .001, performance r = .08, p = .284). These null
results replicated in a linear regression analysis with the mindsets entered simultaneously as
predictors and performance orientation as the outcome. For mastery orientation, our linear
regression yielded a significant effect of difficulty-as-improvement (b = .15, p = .026) but not
difficulty-as-importance or difficulty-as-impossibility. We detail the results of these regression
equations in Supplemental Materials (Study 3 Additional Analyses).
Discussion
An old saying about procedural flexibility admonishes that there are many ways to skin a
cat. Our studies shift attention from having strategies to predictors of individual differences in
57
preference for taking the high road --choosing effortful mean. In three studies, we tested the
prediction that whether people prefer the easier or harder ways of attaining their goals depends,
in part, on what they infer about themselves from the difficulty that comes when thinking about
or working on something is hard or life throws them a curveball. We considered common goals
among students—fitness (Study 1), weight (Study 2), and academics (Study 3). We assessed
beliefs (effort matters, this way is effective, and they will use it) regarding six ways of making
progress toward a future self. Building on identity-based motivation theory, we focused on
individual differences in the extent students endorse each of three distinct inferences about
experienced difficulty. Difficulty-as-impossibility is the inference that finding a task or goal hard
to think about or work on signals that it is not for you. Difficulty-as-improvement entails
inferring chances for becoming a better person from life difficulties. And
difficulty-as-importance is the inference that difficulty signals that a task or goal is valuable for
you). We predicted and found that people who endorse difficulty-as-impossibility find the easy
way more effective and prefer it. People who scored higher in difficulty-as-impossibility were
indifferent to the hard way. We predicted and found that people who endorse
difficulty-as-improvement find the hard way more effective and prefer it; they do not want to go
the easy route. We explored the possibility that difficulty-as-importance might yield indifference
as to which means to use or carry over to a preference for effortful means, finding the latter to be
the case. People who endorse difficulty-as-importance find the hard way more effective and
prefer it. They are indifferent to easy means.
Contributions
Our results address a gap in the goal pursuit, identity-based motivation, goal orientation,
and means-ends literature, which is that prior research documents effects on goal progress but
58
has not considered how preference for means comes about. Our results add to this literature in
four ways, which we outline next.
Our results suggest that endorsing difficulty-as-impossibility does not imply that people
will not pursue goals but that they will if an easy way is available. Second, people who score
higher in difficulty-as-improvement prefer the more effortful route to goal attainment and disdain
the easy way. Third, people who endorse difficulty-as-importance prefer the effortful way. Of
course, the more effortful way can sometimes be more effective. At the same time, the general
preference people who scored high in difficulty-as-improvement have for the hard way may be a
spillover from the belief that enduring difficulty can be morally uplifting—a way of taking the
high road. Similarly, the easy way may or may not be effective, but disdaining ease may make
pursuing a possible self unnecessarily complicated.
Fourth, our results add to prior research on the relationship between effort and perceived
value (for a review, Inzlicht et al., 2018). After exerting effort, people find a
product less hedonically valuable and like it less (e.g., Marcowski et al., 2022) but see them as
having a higher monetary valuation. The latter occurs when people value products they had to
work hard for more than identical ones obtained without effort—the origami swan they created
themselves, the lego house, or the IKEA dresser they built themselves (the so-called
IKEA-effect, Norton, et al. 2012). Similarly, people may value group membership more if the
group is hard to get into (e.g., hazing, costly admissions, Aronson & Mills, 1959). This research
has not examined the circumstances in which people prefer easier or harder means to attain their
goals. Our results suggest that people may be more prone to find effort intrinsically valuable if
they endorse difficulty-as-improvement or difficulty-as-importance and less likely to do so if
they score higher on difficulty-as-impossibility.
59
Limitations, Future Directions, and Concluding Comments
Like any research, ours has limitations. We focus on three: design, sample, and dependent
variables. To our knowledge, ours are the first studies documenting that difficulty mindsets --the
ways people make sense of their difficulties with tasks and in life carry-- carry over to a
preference for means, but our designs were cross-sectional. We focused on how difficulty
mindsets predict preferring more and less effortful paths toward goals. The reverse might also be
the case. We cannot tell if people prefer easier versus harder means because of their difficulty
mindsets or the reverse (maybe they endorse difficulty mindsets because of their prior preference
for easier versus harder ways to attain their goals). Moreover, our design allowed us to focus on
individual differences. It might equally be the case that people vary across time and situations
such that accessible difficulty mindset shapes preference for means. Future studies using priming
procedures, diaries, and EMA (ecological-momentary-assessment) techniques could test these
possibilities.
Second, regarding the sample, we showed effects with common goals among students in
the U.S. who were diverse as to self-reported racial-ethnic background. However, there is some
evidence that how much people endorse difficulty-mindsets varies across cultures (O’Donnell et
al., 2021; Yan et al., 2022). These studies suggest that non-college student adults in the U.S.
score higher in difficulty-as-impossibility and lower in difficulty-as-improvement than
non-college student adults in other, more collectivistic cultures. These differences might imply
that in these societies, people have less preference for the easy way and a stronger preference for
the hard way than in the U.S. Future studies could test this possibility.
Third, regarding dependent variables, we showed effects for two dependent variables:
how effective students believed a method would be and how likely they would be to use it. We
60
thought our dependent measures would be related, but they were not. Given the number of
analyses, we focused on our meta-analytic summaries of effects across studies to reduce
over-reliance on single effects. Future research is needed to unpack why effectiveness and
likelihood of use were distinct. Moreover, we used self-report dependent variables and contrasted
more and less effortful means as a first step. It is tricky to obtain behavioral data on what people
do to work toward possible selves that require repeated engagement over time. Hence researchers
typically measure outcomes (grades) rather than means (what people do when they study) over
time. However, future research could use more within-subjects ecological data obtained via
methods such as a daily diary approach to explore within and between-person variation in the
means people use over time.
Our results support the prediction that the inferences people draw about themselves from
their experiences of difficulty matter, in part, by shaping the extent to which they prefer the easy
or the hard way—the means they use when pursuing common goals. Each difficulty mindset
adds to each individual’s profile of preference for easier or harder means to goal attainment. We
do not yet have enough studies to consider the extent that profiles differ for different possible
selves. Focusing on ease can be beneficial --easier means may preserve energy to pursue other
goals. Focusing on the hard way can also be beneficial --if it is the more effective way to
progress. Since how much people endorse difficulty-as-impossibility, difficulty-as-importance,
and difficulty-as-improvement are relatively independent, whether people choose the easy or
hard way at a particular moment may depend in part on which mindset is momentarily
accessible. At the same time, given differences in mean endorsement of difficulty mindsets
across societies, it might also be the case that social structural factors shape which difficulty
mindsets are chronically on the mind. Our results suggest that people are more likely to prefer
61
the hard way when they also prefer the high road or the morally right way and that people may
prefer the easy way when they also don’t want to waste efforts on what they deem to be lost
causes.
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Chapter 3
Believing That Difficulties are Character-building Supports Wellbeing and Positively
Frames Daily Life
Gülnaz Kiper
1
, David Newman
2
, and Daphna Oyserman
1
1
Department of Psychology, University of Southern California
2
Department of Psychiatry and Behavioral Sciences, University of California, San Francisco
Abstract
People vary in how much they believe that enduring hard times can support self-improvement.
This variation matters, people who endorse this difficulty-as-improvement mindset are more
likely to see silver linings from suffering (e.g., during the COVID-19 pandemic), see life as
meaningful, and see themselves as conscientious, virtuous, and optimistic about life. These
results imply that difficulty-as-improvement is trait-like and consequential. We test these
predictions in four daily diary studies (N = 382). Multilevel modeling results suggest that
difficulty-as-improvement is more trait-like than state-like. Both between-person differences and
daily fluctuations matter, predicting well-being (meaning, coherence, self-esteem, life
satisfaction) generally and in daily assessments as well as daily effortful engagement and
attainment of successes. Yesterday’s difficulty-as-improvement predicts today’s meaning in life
and self-esteem, controlling for yesterday’s experience meaning in life or self-esteem.
Difficulty-as-improvement mindset provides meaning (difficulties happen for a reason) and
feelings of worth (you are good enough).
Keywords: Difficulty-as-improvement, daily diary, wellbeing, meaning in life, self-esteem
63
Believing That Difficulties are Character-building Supports Wellbeing and Positively
Frames Daily Life
Societies provide people with implicit culture-based blueprints for how to make sense of
their experiences (Oyserman & Yan, 2019). An important role of these culture-based blueprints
is to guide people on how to make sense of unbidden life difficulties (Yan et al., 2023). This
guidance is based in part on the religious, spiritual, political, and secular beliefs a society has
about what experiencing difficulty implies about a person. Many of these beliefs center on the
concept of deservingness—that people suffer because they deserve to. For example, many
religions with origins in India such as Hinduism and Buddhism endorse the notion of karma:
people who enjoy positive circumstances do so because of past good behavior, while people who
suffer do so because of past bad deeds (White & Norenzayan, 2019; White et al., 2019). Not only
religions, but also political or secular beliefs about society provide meaning frames: People with
conservative beliefs (e.g. traditional values and ideas) espouse the idea that the world is a fair
place where people are responsible for themselves (Carney et al., 2008); people get what they
deserve (Furnham & Gunter, 1984); and difficulties occur due to people’s laziness or
shortcomings (Feather, 1984; Furnham & Bland, 1983).
Deservingness-based frames imply that whatever people are suffering through is a
reflection of their character. Difficulties in life are self-made and due to people’s faults.
However, an alternative meaning frame exists that shifts the focus away from people’s
shortcomings and emphasizes the positive instead: People do not have to infer from their
difficulties that they are a bad person or have done bad things. Instead, people can see difficulties
as experiences that help them grow and become better versions of themselves—they can
interpret life difficulties as paths to self-betterment. This idea can be traced back to many
religious beliefs, where enduring pain and suffering is viewed as a means of sanctification,
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elevation, and bringing oneself closer to God (e.g., Jewish scholars believe that God inflicts pain
and suffering on the righteous to improve them (Schwartz, 1983); St. Paul describes Christians as
glorying in their sufferings because suffering produces perseverance and perseverance improves
the character and creates hope (New International Version Bible, 2011, Romans 5:3-4); the
Muslim poet Rūmī describes pain and suffering as antecedents to spiritual growth and
redemption (Chittick, 1983)).
The perspective that unbidden difficulties serve a sanctifying or self-improvement
purpose is a cross-cultural belief that is shared by individuals across both Western and
non-Western societies (Yan et al., 2023). Notably, this belief is more strongly endorsed by people
who identify as politically conservative, religious, and believers of karma and a just world, as
well as those from less-WEIRD societies (Yan et al., 2023). Identity-based Motivation theory
(Oyserman, 2007, 2009) terms this perspective the “difficulty-as-sanctifying” mindset, which has
been secularized as the “difficulty-as-improvement” mindset (Kiper et al., 2022).
A difficulty-as-improvement mindset is not antagonistic to the idea of deservingness, but
instead emphasizes the positive aspects of suffering—that through enduring difficulty, people can
become better versions of themselves and more deserving of good (Yan et al., 2023). Adopting
this perspective should facilitate a greater sense of meaning and coherence in one’s life; a greater
sense of self-worth and satisfaction; and the ability to persist in the face of challenge. We
elaborate on each of these potential outcomes next.
Finding Meaning
The difficulty-as-improvement mindset posits that challenges in life are an essential
component for personal growth and development. By embracing this perspective, individuals can
find greater meaning and coherence in their lives. In a set of studies conducted with participants
65
from four Western and four non-Western countries, Yan and colleagues (2023) found that people
who endorse this mindset indeed report higher meaning in life and more strongly believe that
they are the kind of person for whom things will turn out alright.
Meaning in life is experienced when one’s life feels purposeful, significant, and coherent
(King et al., 2006), with coherence often being conceptualized as a core facet of meaning in life
(e.g., Martela & Steger, 2016; King & Hicks, 2021). Experiencing meaning in life entails
pursuing personally valued and important life goals (purpose), feeling like one’s existence and
contributions matter (significance), and feeling like one’s experiences make sense (coherence),
and each of these experiences support adaptive coping (Ward et al., 2023). Perceiving one’s life
as meaningful positively relates to psychological wellbeing (e.g., Zika & Chamberlain, 1992)
and predicts positive emotions (e.g., Miao et al., 2017). As one of the facets of meaning in life,
experiencing coherence entails being able to consolidate one’s experiences into a sensible story
(Ward et al., 2023) and is also related to wellbeing (e.g., Baerger & McAdams, 1999). If
comprehension is a central feature of meaning in life, when experiences make sense, life should
feel more meaningful (King & Hicks, 2021). The difficulty-as-improvement mindset suggests
that hardships in life are not mere fate or punishment; they serve a purpose. By weaving these
challenges into a cohesive narrative, this mindset can support the facets of meaning in life:
finding purpose, significance, and coherence in one’s struggles.
This perspective not only imbues life with meaning, but also encourages people to find
meaning in and persevere through difficult life circumstances. In a series of studies conducted
during the height of the COVID-19 pandemic, Kiper and colleagues (2022) found that people
who embraced difficulty-as-improvement were more likely to see silver linings in the COVID-19
pandemic for themselves and their communities. Importantly, people with a stronger
66
difficulty-as-improvement mindset were more likely to take up COVID-19 preventative
behaviors (e.g. mask-wearing) to the extent that this mindset allowed them to see silver linings
for themselves. By painting the hardship of the pandemic as an opportunity for growth and
improvement, the difficulty-as-improvement belief likely helped people take up difficult but
necessary actions in the face of adversity.
Self-Esteem and Life Satisfaction
Making sense of one’s life may be a prerequisite for valuing one’s life: in situations
where life doesn’t make sense, it may be difficult to uphold a sense of life’s worthiness (Martela
& Steger, 2016). Therefore, establishing meaning and coherence in life may precede feelings of
self-esteem and life satisfaction. Self-esteem is defined as the amount of value people place on
themselves, and is the evaluative component of self-knowledge (Baumeister et al., 2003). In a
similar vein, life satisfaction represents a cognitive and global evaluation of the quality of one’s
life as a whole (Pavot & Diener, 1993). People who feel satisfied with themselves (self-esteem)
tend to also be satisfied with their lives (e.g., Kwan et al., 1997). Furthermore, experiences of
meaning and coherence not only precede but also tend to go hand in hand with feelings of
self-esteem and life satisfaction (Chamberlain & Zika, 1988; Steger et al., 2006). Hence, it is
plausible that the difficulty-as-improvement mindset is also positively associated with
self-esteem and life satisfaction.
Difficulty-as-improvement should support self-esteem and life satisfaction in two ways.
First, deservingness frames focus on the faults of one’s character and point to the self as the
culprit for one’s suffering. In these ways, these perspectives can harm self-esteem. A
difficulty-as-improvement frame redirects attention from deservingness to potential for personal
growth. In this way, this perspective may foster a sense of worth and positive self-perception.
67
Second, difficulty-as-improvement can support feelings of one’s worth and quality of life
by encouraging socially desirable behaviors. Self-esteem can act as a sociometer, providing
feedback on one’s social standing, monitoring the quality of interpersonal relationships, and
motivating behaviors that maintain inclusion and acceptance by others (Leary, 1990; Leary &
Baumeister, 2000). Behaviors that signal competence, responsibility, and morality are essential
for maintaining acceptance and inclusion by others (Leary & Baumeister, 2000), and
difficulty-as-improvement can play a positive role in this regard. Individuals who expend more
effort are viewed as more competent and cooperative (Celniker et al., 2023), while being
described as hardworking leads to perceptions of greater honesty and diligence (Amos et al.,
2019). People who are able to exercise self-control are perceived to be more moral, especially by
those who endorse group-focused moral values (Mooijman et al., 2018). Conversely, individuals
who contribute less to collective actions yet still seek to benefit from them are seen as less moral
(Delton et al., 2012). People who embrace a difficulty-as-improvement mindset should be more
likely to have the moral fortitude needed to tackle challenges that have significance for their
group. By doing so, people with this mindset should demonstrate their competence, virtue, and
worthiness as cooperative partners. Consequently, difficulty-as-improvement has the potential to
increase feelings of self-esteem and contribute to life satisfaction.
Engaging in Effortful Strategies and Experiencing Success
Difficulty-as-improvement helps people experience meaning in life and feelings of
self-worth, and can also carry over to moral fortitude and resilient behaviors: people who
endorse this mindset report higher conscientiousness and character virtues (Yan et al., 2023).
Students with this mindset prefer goal pursuit strategies that are ethical, difficult, and deemed the
68
“right way,” despite the higher effort requirement; and do not prefer passive, shortcut, and
cheating strategies (Kiper et al., 2023).
Difficulty-as-improvement can lead people to experience the difficult way as the right
way. However, effort is often perceived as aversive and costly (Inzlicht et al., 2018). For
example, within the context of learning, learners interpret effort as a motivational cost (Feldon et
al., 2019) and are less likely to believe that they have learned something if learning feels effortful
and difficult (Baars et al., 2020). Yet, certain learning strategies that feel effortful often lead to
better long-term learning (“desirable difficulties,” Bjork, 1994). This creates a need to address
people’s erroneous beliefs about experiencing difficulty in contexts where it matters (de Bruin et
al., 2023). In such contexts, adopting a difficulty-as-improvement mindset can help people
recognize the value of effort as a necessary component of self-development. By doing so, this
mindset can encourage individuals to persist, engage more effortfully in daily life, and attain
greater success through their perseverance.
Current Studies
Previous research suggests that adopting a difficulty-as-improvement mindset can have
positive effects on various aspects of life. Building on this, our studies aim to explore how this
mindset relates to six outcomes of interest: meaning in life, coherence, self-esteem, life
satisfaction, effortful engagement, and success. Past studies have primarily assessed
difficulty-as-improvement as a between-person measure using secular wording. In our current
studies, we first hypothesize that the secular and sanctified between-person measures of
difficulty-as-improvement will be positively correlated (H1, Table 1). Finding this correlation
will allow us to use the prior work as the basis for our current studies and also to assume that
69
whether people answer the religious or the secular version of the scale does not change the
pattern of results.
To the extent that a culture dictates ideals and rituals centered around the notion of
difficulty-as-improvement, this idea should be experienced as fluent and natural by the people in
this culture, and the more fluent this idea feels due to cultural literacy, the more it should operate
as an individual difference rather than a situated state. All prior studies have assumed
difficulty-as-improvement to be an individual difference, yet none have tested to what extent this
is truly the case. In the current studies, we address this gap and test to what extent the daily
measure of difficulty-as-improvement functions as a between-person trait vs. a within-person
state, predicting it to be more trait-like (H2, Table 1).
We next predict that the preliminary between-person findings for
difficulty-as-improvement are stable, replicating for meaning in life, and that they carry over to
experiencing more life coherence, self-esteem, and life satisfaction (H3, Table 1).
Next, we predict that the between-person measure of difficulty-as-improvement predicts
greater daily wellbeing (meaning in life, coherence, self-esteem, and life satisfaction), effortful
engagement, and successes (H4, Table 1).
We turn to within-person relationships next. We predict that although the daily measure
of difficulty-as-improvement is more trait-like, there will be sufficient within-person variability
to explain daily fluctuations in outcomes. We predict that daily fluctuations in
difficulty-as-improvement are associated with daily fluctuations in wellbeing, effortful
engagement, and success (H5, Table 1). We also predict that there will be lagged effects of daily
difficulty-as-improvement on these outcomes (H6, Table 1) and explore reverse lagged
relationships as well.
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Finally we explore the relationships between trait or daily difficulty-as-improvement and
religiosity, religious experiences, engagement in ease, and failures.
Our studies fill three gaps in the literature. First, the literature has not considered the
amount of between vs. within-person variability that exists with regards to the
difficulty-as-improvement mindset. Second, it is not known to what extent the two sources of
variance in difficulty-as-improvement predict between vs. within-person variance in wellbeing
and daily experiences. To the extent that difficulty-as-improvement is trait-like, it should predict
between-person variability in our DVs. To the extent that difficulty-as-improvement is state-like,
it should predict within-person variability in our DVs. Finally, prior studies have not looked at
the extent to which yesterday’s difficulty-as-improvement can predict today’s outcome,
controlling for how much the individual experienced that outcome yesterday
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Method
Table 1
Hypotheses and Studies Testing Them
Hypothesis Study
Number Content
H1 Endorsement of the secular and sanctified versions of the
difficulty-as-improvement (trait) scale are positively correlated.
4
H2 Difficulty-as-improvement is more trait-like than state-like—it varies more
between-persons than it fluctuates by day within-persons.
1 to 4
H3 Trait difficulty-as-improvement is related to trait wellbeing. 1 to 4
H3a-d People who endorse difficulty-as-improvement (trait) are more likely to see
themselves as people whose lives have (a) meaning and (b) coherence. They are
more likely to (c) believe that they are people of worth (self-esteem) and (d) feel
satisfied with their lives.
H4 Trait difficulty-as-improvement predicts daily wellbeing and daily
experiences.
1 to 4
H4a-f People who are higher in trait-level difficulty-as-improvement will on average be
more likely to report greater daily (a) meaning in life, (b) coherence, (c) feelings
of self-worth (self-esteem), and (d) life satisfaction, as well as that they (e)
engaged in effortful strategies and (f) experienced successes.
H5 Today’s difficulty-as-improvement predicts today’s wellbeing and daily
experiences.
1 to 4
H5a-f On days on which a person endorses difficulty-as-improvement more compared
to their two-week average, the more likely they will be to report that they
experienced (a) meaning in life, (b) coherence, (c) feelings of self-worth
(self-esteem), and (d) life satisfaction, as well as that they (e) engaged in
effortful strategies and (f) experienced successes.
H6 Yesterday’s difficulty-as-improvement predicts today’s wellbeing and daily
experiences.
1 to 4
H6a-f On days following higher difficulty-as-improvement endorsement, people will
experience more (a) meaning in life, (b) coherence, (c) feelings of self-worth
(self-esteem), and (d) life satisfaction, as well as (e) effortful engagement and (f)
success.
Note. H6 is tested with models that control for yesterday’s experience of the DV in question.
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Open Science Framework
We pre-registered Studies 2-4. All of our pre-registrations, measures, data, and R script
can be found on our OSF page:
https://osf.io/qs8dn/?view_only=4a49254028824cbb89b11b4a579a7ad2
Data Exclusions
We followed the methodology outlined by Nezlek (2012) to prepare data for analysis.
Multiple entries completed on the same day, entries completed after 10:00 a.m. the following
morning, and entries that did not have a correct answer to an instructed response item were
dropped from final analyses, as recommended by Meade & Craig (2012). Participants who
completed less than five daily entries were eliminated as well. In total, 246 of 4880 daily entries
were deleted (final n = 4634; 94.96%); details of study-specific deletions can be found in
Supplemental Materials.
Samples
We conducted four daily diary studies (total final N =382) with University of Southern
California undergraduates (Study 1 during spring 2019, n = 96, 76% female, M
age
= 20.17; Study
2 during fall 2019, n = 147, 79% female, M
age
= 19.91; Study 3 during spring 2020, n = 59, 66%
female, M
age
= 20.47; Study 4 during spring 2022, n = 80, 68% female, M
age
= 20.71). The
race-ethnicity breakdown of participants by study can be seen in Table S1 in Supplemental
Materials. Our final sample yielded a total of 4,634 daily reports (with an average of 12.33
reports per participant). In each study, we collected data from as many participants as possible
within the constraints of the participant pool. Because each study had a small sample size on its
73
own, we aggregated the datasets of the four studies and ran meta-analyses on this combined
dataset. A G*Power analysis showed that this combined dataset was adequately powered at .80
to detect medium size correlations. Moreover, the combined dataset was well above the
minimum daily diary sample size recommendation by Nezlek (2012) of two weeks of daily data
from 100 participants, as well as the level-2 sample size recommendation by Maas & Hox
(2005).
Procedure
Students signed up for the study via the university subject pool and received credit upon
completion of the study. They first watched an instructional video and completed a trait
questionnaire either before or after completing 14 days of daily questionnaires. As explained in
the video, students were instructed to do their best to complete each daily survey for 14
consecutive days. They were told to complete the daily survey as close to bedtime as possible,
and to complete it before 10 am the next day. Any survey that was completed after 10 am the
next day would be discarded.
Measures
All measures along with descriptive information can be seen in Tables 2-9. We report
stuy-specific descriptive information as well as information from the combined dataset under the
“meta” column or in the Table note. We took trait measures from the sources mentioned in table
notes and created day measures based on trait-level items unless otherwise noted. We measured
difficulty-as-improvement using the religious version in Studies 1-3, and the secular version in
Study 4. In Study 4, we assessed both the religious and secular versions of trait
difficulty-as-improvement in order to look at their correlation: one of our predictions for Study 4
74
was that the religious and secular versions of the difficulty-as-improvement measure would be
highly correlated.
Table 2
Difficulty-as-Improvement Religious Version
Difficulty-as-Improvement Religious Version: Items and Scale Descriptives
Trait Measure Items Scale Information by Study
Study 1 Study 2 Study 3 Study 4 Meta
1. In a way, the struggles you have
today purify your character to meet
tomorrow's challenges.
Cronbach's Alpha Reliability
2. Every difficulty you overcome makes
your spirit and soul grow stronger.
.89 .84 .84 .85 .86
3. Difficulty is the strongest of teachers;
difficulty might bend or break you
temporarily, but it can purify you in
the long run.
M (SD)
4. Your spiritual journey through life
cannot be complete without adversity,
hardship, and overcoming suffering.
4.50
(1.00)
4.75
(0.87)
4.72
(0.99)
4.83
(0.79)
4.70
(0.91)
Day Measure Items Reliability
1. In a way, the struggles I had today
will purify my character to meet
tomorrow's challenges.
.82 .81 .74 -- .80
2. Every difficulty I overcame today
will make my spirit and soul grow
stronger.
M (SD)
3. The difficulties I experienced today
might bend or break me temporarily,
but they can purify me in the long
run.
4.15
(1.34)
4.36
(1.23)
4.49
(1.10)
--
4.30
(1.20)
Day measure ICCs: .68, .60, .59; meta: .63
Note. Measures developed by our team. Response scale for trait measure: 1 = Strongly disagree
to 6 = Strongly agree. Response scale for day measure: 1 = Strongly disagree to 6 = Strongly
agree, 7 = I did not experience any difficulties today. To create the day measure of
difficulty-as-improvement, we followed the following procedure: if and only if the participant
selected a response option other than 7 (“I did not experience any difficulties today”) for all three
daily items did we take the mean of the three items to create the person’s daily mean score. If 7
was selected for any one of the three items, the person’s daily score was coded as NA.
75
Table 3
Difficulty-as-Improvement Secular Version
Difficulty-as-Improvement Secular Version: Items and Scale Descriptives
Trait Measure Items Scale Information by Study
Study 4
1. In a way, the struggles I have today are strengthening
my character to meet tomorrow's challenges.
Cronbach's Alpha Reliability
2. Experiencing difficulty makes me grow stronger. .88
3. Experiencing difficulty is the strongest of teachers; I
may temporarily feel broken but in the long run, I
will be better.
M (SD)
4. Life is not complete without difficulty, hardship, and
suffering.
4.90 (0.74)
Day Measure Items Reliability
1. In a way, the struggles I had today will strengthen my
character to meet tomorrow's challenges.
.87
2. The difficulties I experienced today will make me
grow stronger. M (SD)
3. The difficulties I experienced today might bend or
break me temporarily, but they will make me better
in the long run.
4.71 (1.13)
Day measure ICC: .58
Note. Trait measure from Kiper et al. (2022); daily measure developed by our team. Response
scale for trait measure: 1 = Strongly disagree to 6 = Strongly agree. Response scale for day
measure: 1 = Strongly disagree to 6 = Strongly agree, 7 = I did not experience any difficulties
today. To create the day measure of difficulty-as-improvement, we followed the following
procedure: if and only if the participant selected a response option other than 7 (“I did not
experience any difficulties today”) for all three daily items did we take the mean of the three
items to create the person’s daily mean score. If 7 was selected for any one of the three items, the
person’s daily score was coded as NA.
Table 4
Meaning in Life
Meaning in Life: Items and Scale Descriptives
Trait Measure Items Scale Information by Study
Study 1 Study 2 Study 3 Study 4 Meta
76
1. I understand my life's meaning. Cronbach's Alpha Reliability
2. My life has a clear sense of purpose. .90 .87 .88 .90 .89
3. I have a good sense of what makes
my life meaningful.
M (SD)
4. I have discovered a satisfying life
purpose.
4.51
(1.35)
4.57
(1.23)
4.92
(1.19)
4.89
(1.25)
4.70
(1.27)
5. My life has no clear purpose. (R)
Day Measure Items Reliability
1. How meaningful did you feel your
life was today?
.87 .87 .86 .88 .87
2. How much did you feel your life had
purpose today?
M (SD)
4.19
(1.67)
4.15
(1.66)
4.16
(1.66)
4.57
(1.53)
4.20
(1.60)
Day measure ICCs: .50, .54, .56, .57; meta: .54
Note. Trait measure from Steger et al. (2006); daily measure from Kashdan & Steger (2007);
Kashdan & Nezlek (2012). Response scale for trait measure: 1 = Absolutely untrue, 2 = Mostly
untrue, 3 = Somewhat untrue, 4 = Can't say true or false, 5 = Somewhat true, 6 = Mostly true, 7 =
Absolutely true. Response scale for day measure: 1=Not at all to 7=Very much.
Table 5
Coherence
Coherence: Items and Scale Descriptives
Trait Measure Items Scale Information by Study
Study 1 Study 2 Study 3 Study 4 Meta
1. I can make sense of the things that
happen in my life.
Cronbach's Alpha Reliability
2. Looking at my life as a whole, things
seem clear to me.
.80 .72 .68 .88 .88
b
3. I can understand why the events of
my life have occurred.
M (SD)
4. My life feels like a sequence of
unconnected events. (R)
a
4.89
(1.10)
4.98
(1.02)
5.31
(1.00)
4.93
(1.28)
5.00
(1.10)
Day Measure Items Reliability
1. I can make sense of the things that
happened in my life today.
.79 .82 .74 .82 .80
2. Looking at my life today, things seem
clear to me. M (SD)
3. I can understand why the events of
my day occurred.
4.74
(1.40)
4.79
(1.38)
4.90
(1.29)
5.05
(1.37)
4.80
(1.40)
77
Day measure ICCs: .44, .51, .50, .60; meta: .51
Note.
a
Item not included in Study 4.
b
Alpha reliability shown is computed using the 4-item
measure from Studies 1-3. Coherence trait measure adapted from Costin & Vignoles (2020);
daily measure created by our team based on trait measure. Response scale for both measures: 1 =
Strongly disagree to 7 = Strongly agree.
Table 6
Self-Esteem
Self-Esteem: Items and Scale Descriptives
Trait Measure Items Scale Information by Study
Study 1 Study 2 Study 3 Study 4 Meta
1. I feel that I am a person of worth, at
least on an equal plane with others.
Cronbach's Alpha Reliability
2. I feel that I have a number of good
qualities.
.91 .90 .87 .86 .89
3. All in all, I am inclined to feel that I am
a failure. (R)
M (SD)
4. I am able to do things as well as most
other people.
2.88
(0.59)
2.88
(0.54)
3.00
(0.49)
2.84
(0.48)
2.90
(0.53)
5. I feel I do not have much to be proud
of. (R)
6. I take a positive attitude toward myself.
7. On the whole, I am satisfied with
myself.
8. I wish I could have more respect for
myself. (R)
9. I certainly feel useless at times. (R)
10. At times I think I am no good at all. (R)
Day Measure Items Reliability
1. Today, I felt like a failure. (R) .57 .60 .55 .65 .59
2. Today, I felt that I had many good
qualities. M (SD)
3. Today, I thought I was no good at all.
(R) 4.92
(1.42)
4.98
(1.42)
5.10
(1.33)
5.00
(1.42)
5.00
(1.40) 4. Today, on the whole, I was satisfied
with myself.
Day measure ICCs: .47, .48, .48, .55
Note. Trait measure from Rosenberg (1965); daily measure from Nezlek (2005). Response scale
for trait measure: 1=Strongly disagree, 2=Disagree, 3=Agree, 4=Strongly agree. Response scale
for day measure: 1=Very uncharacteristic of me to 7= Very characteristic of me.
78
Table 7
Life Satisfaction
Life Satisfaction: Items and Scale Descriptives
Trait Measure Items Scale Information by Study
Study 1 Study 2 Study 3 Study 4 Meta
1. In most ways my life is close to my
ideal.
Cronbach's Alpha Reliability
2. The conditions of my life are
excellent.
.87 .89 .88 .85 .88
3. I am satisfied with my life. M (SD)
4. So far I have gotten the important
things I want in life.
4.45
(1.33)
4.43
(1.44)
4.73
(1.41)
4.72
(1.19)
4.50
(1.36)
5. If I could live my life over, I would
change almost nothing.
Day Measure Items
M (SD)
1. How satisfied were you with your life
today? 4.67
(1.63)
4.65
(1.59)
4.69
(1.56)
4.61
(1.59)
4.70
(1.60)
Day measure ICCs: .43, .47, .42, .51; meta: .46
Note. Trait measure from Diener et al. (1985); daily measure from Busseri & Newman (2022).
Response scale for trait measure: 1 = Strongly disagree to 7 = Strongly agree. Response scale for
day measure: 1 = Not at all to 7 = Very satisfied. Reliabilities can not be calculated for
single-item measures (Nezlek, 2012), hence we do not report reliability for the daily measure of
life satisfaction.
Table 8
Effortful Engagement
Effortful Engagement in Studies 2 & 3: Items and Scale Descriptives
Scale Information by Study
Study 2 Study 3
1. Engaged in a difficult social interaction (e.g. with a
stranger, with someone I feel awkward around, or on a
topic that was difficult to discuss).
M (SD)
2. Engaged with difficult schoolwork or homework or
went to a difficult class.
0.94
(0.72)
1.02
(0.78)
3. Engaged with a difficult health or fitness routine or did
strenuous exercise.
4. Engaged in another type of difficult activity (not listed
79
above) in a domain that I care about.
5. Did schoolwork the hard way (e.g., I took notes, I read
the assignments before class).
6. Took the high road to engage in a health or fitness goal
(e.g. figuring out a way to have balanced nutrition even
if it slowed down progress on my health and fitness
goals).
ICCs: .42, .50
Effortful Engagement in Study 4: Items and Scale Descriptives
Scale Information for Study 4
1. Engaged in a difficult social interaction (e.g. on a topic
that was difficult but necessary to discuss, had to call
someone out on their behavior).
M (SD)
2. Engaged with difficult schoolwork or homework or
went to a difficult class.
1.11 (0.92)
3. Engaged with a difficult health or fitness routine or did
strenuous exercise.
4. Engaged in another type of difficult activity (not listed
above) in a domain that I care about.
5. Did schoolwork the hard way (e.g., I took notes, I read
the assignments before class).
6. Took the high road to engage in a health or fitness goal
(e.g. figuring out a way to have balanced nutrition even
if it slowed down progress on my health and fitness
goals).
7. Started a necessary conversation that I was intimidated
to have.
ICC: .43
Note. Measures developed by our team. Response Scale: 0= did not occur, 1 = occurred and not
important, 2 = occurred and somewhat important, 3 = occurred and pretty important, 4=
occurred and extremely important. There is no reason to expect event checklists to be internally
consistent (Stone et al., 1991), hence we do not report alpha reliabilities for daily event
measures. Combined dataset M (SD) = 1.00 (0.79); ICC = .45.
Table 9
Success
Success in Study 1: Items and Scale Descriptives
1. Completed work on an interesting project or
assignment.
Scale Information for
Study 1
2. Met a daily fitness goal.
3. Performed well (sports, music, speaking, drama,
etc.).
M (SD)
0.97 (0.89)
80
4. Got caught up (or ahead) in coursework or work
duties.
5. Did well on a school or work task (e.g. test,
assignment, job duty).
ICC: .43
Success in Studies 2 and 3: Items and Scale Descriptives
Scale Information by
Study
Study 2 Study 3
1. Succeeded in a social goal (e.g. making new friends,
making a good impression).
M (SD)
2. Succeeded at a work or school task.
1.19
(0.96)
1.33
(0.98)
3. Succeeded in a health or fitness goal.
ICCs: .43, .46
Success in Study 4: Items and Scale Descriptives
Scale Information for
Study 4
1. Succeeded in a social goal (e.g. making new friends,
making a good impression).
M (SD)
2. Succeeded at a work or school task. 1.48 (1.05)
3. Succeeded in a health or fitness goal.
4. Succeeded in another type of task or goal (not listed
above) in a domain that I care about.
ICC: .45
Note. Measures adapted from Butler et al. (1994) and Nezlek & Plesko (2001). Response Scale:
0= did not occur, 1 = occurred and not important, 2 = occurred and somewhat important, 3 =
occurred and pretty important, 4= occurred and extremely important. There is no reason to
expect event checklists to be internally consistent (Stone et al., 1991), hence we do not report
alpha reliabilities for daily event measures. Combined dataset M (SD) = 1.20 (0.98); ICC = .45.
Data Preparation
To create day-level difficulty-as-improvement, we took the average of the three day items
only for days on which the participant selected a response other than 7 (“I did not experience any
difficulties today”) for all three items. If the participant selected 7 for any of the three items, their
daily difficulty-as-improvement was coded as NA. To create the aggregated datafile, we
combined the merged datafiles.
81
Analysis Plan
We used the R packages psych (R Core Team, 2021) for descriptive statistics and lme4 (v.
1.1-23; Bates et al., 2015) to run multilevel models. To compute reliabilities of day measures, we
used the method outlined by Nezlek (2012). Items of each scale were nested within days, which
were nested within persons in a three-level model. The intercept of a null model provides the
estimate of true variance over total variance. To examine the primary questions of interest, we
created two-level multilevel models in which days were nested within persons. We attempted to
include random intercepts and random slopes in all models. However, we trimmed the error term
whenever the model failed to converge because there was not enough variation in the random
effects, a practice recommended by Nezlek (2012). We followed recommendations by Rights and
Sterba (2019; 2021) to calculate effect sizes using the r2mlm function. For models examining
between-person relationships, we report R
b
f2
(defined as the square root of the proportion of
variance explained by between-person predictors via fixed slopes); for models examining
within-person relationships, we report R
w
f1v
(defined as the square root of the proportion of
variance explained by within-person predictors via fixed slopes and random slope
variation/covariation). These measures are similar to a measure of the square root of the
proportion reduction in variance, akin to a correlation (Hox, 2002; Kreft & de Leeuw, 1998;
Raudenbush & Bryk, 2002). We interpret the size of these effects using Cohen’s (1988) rule of
thumb for interpreting Pearson's r (.10 as small; .30 as moderate; .50 or larger as large).
We ran all analyses on each individual dataset as well as the aggregated dataset. In all
aggregated models, we added three dummy-coded study variables as controls. We present a
summary of each individual study’s results as well as the meta-analytic result in the figures of
82
this paper, but for parsimony’s sake we focus mostly on discussing the meta-analytic results.
Detailed results pertaining to the individual studies can be found in Supplemental Materials.
Results
H1: Endorsement of the secular and sanctified versions of the difficulty-as-improvement
(trait) scale are positively correlated.
We ran a correlation between the two trait measures of difficulty-as-improvement in
Study 4 and found support for H1. There are different ways to consider whether two constructs
are redundant: one way is Kline’s (2011) discriminant validity cutoff rule of .85. Another way is
to examine whether different measures of the same underlying construct follow similar
correlation patterns with other constructs (Campbell & Fiske, 1959). We found that the secular
and religious/sanctified versions of the trait difficulty-as-improvement measure were sufficiently
highly correlated that they could be considered redundant using Kline’s (2011) discriminant
validity cutoff of .85—the upper bound of the correlation confidence interval surpassed this
cutoff (r = .82, 95% CI [.73, .88], p < .001). We also found that they follow similar correlation
patterns with the outcome variables (Table S2, Supplemental Materials). Hence, we consider the
measures to be the same. Going forward, we use the term difficulty-as-improvement to refer to
the religious/sanctified version (Studies 1 to 3) as well as the secular (Study 4) version.
83
H2: Difficulty-as-improvement is more trait-like than state-like—it varies more
between-persons than it fluctuates by day within-persons.
To examine the amount of between-person and within-person variation of
difficulty-as-improvement (H2) as well as all other daily measures, we ran fully unconditional
multilevel models separately on each day-level dataset with days nested within persons using
package lme4 (v. 1.1-23; Bates et al., 2015). We found support for H2. About two-thirds of the
variance in daily difficulty-as-improvement scores was attributable to between-person
differences in each study: the ICCs for the day-level difficulty-as-improvement measure were
.68, .60, .59, and .58, for Studies 1-4, respectively (.63 in the aggregated dataset). In addition, the
ICCs of the outcome variables were between .42 and .60 across the studies, suggesting that there
is a good amount of variance to be explained at both the within and between-person levels. The
ICCs of the outcomes are similar to what has previously been reported in the literature: .56
(Ward et al., 2023) and .61 (Newman & Sachs, 2022) for meaning in life; .42 (Teneva & Lemay,
2020) and .47 (Newman & Sachs, 2022) for self-esteem; and .40 (Busseri & Newman, 2022) and
.50 (Newman & Sachs, 2022) for life satisfaction.
H3: Trait difficulty-as-improvement is related to trait wellbeing.
To test H3, we ran correlations on individual datasets. Next, we ran linear regressions on
the Studies 1-4 aggregated dataset using package stats (R Core Team, 2021): the standardized
trait-level wellbeing variable was treated as the outcome variable and the standardized trait-level
difficulty-as-improvement variable was treated as the predictor, while three dummy-coded study
variables were included as controls. We found support for H3. As represented by the blue
triangles in each of the four plots of Figure 1 (with whiskers representing 95% Confidence
Intervals), in the aggregated dataset, people who were higher in trait-difficulty-as-improvement
84
were also higher in trait meaning in life (H3a; r = .35, 95% CI [.25, .44], p < .001), life
coherence (H3b; r = .23, 95% CI [.13, .33], p < .001), self-esteem (H3c; r = .19, 95% CI [.09,
.29], p < .001), and satisfaction with life (H3d; r = .17, 95% CI [.07, .27], p = .001). The green
circles in each plot represent the correlation of difficulty-as-improvement with each wellbeing
variable by study. The study-specific correlations differed from study to study and can be seen in
Supplemental Materials, Table S2.
Figure 1
Trait Difficulty-as-Improvement is Correlated With Trait Wellbeing
Note. In each graph, the x-axis represents the magnitude of the correlation between trait
difficulty-as-improvement and the given trait variable. The y-axis represents the Study number
with the bottommost y-axis tick representing the meta-analytic result. Meaning in life,
85
coherence, and satisfaction measures were rated on a 7-point scale whereas self-esteem was rated
on a 4-point scale. For numeric representations of confidence intervals, see Table S2 in
Supplemental Materials.
H4: Trait difficulty-as-improvement predicts greater daily wellbeing and daily experiences.
To examine H4 hypotheses, we created two-level means-as-outcomes models with either
the daily well-being or daily experience variable as the outcome variable in each separate model.
Trait difficulty-as-improvement was entered as a level-2 predictor:
Day level: y
ij
(outcome variable) = β
0j
+ r
ij
Person level: β
0j
= γ
00
+ γ
01
(trait difficulty-as-improvement)
j
+ u
0j
In these models, y
ij
is the ‘j’th person’s score on the outcome variable on the ‘i’th day; β
0j
is the jth person's 2-week average outcome score; and r
ij
is the level-1 random error term. γ
00
is
the grand mean for the outcome score; γ
10
is the regression coefficient of trait
difficulty-as-improvement; and u
0j
is the deviation of the mean outcome score of the jth person
from the grand mean.
We found support for H4. As represented by the blue triangles in each plot in Figure 2
(with whiskers representing 95% Confidence Intervals), aggregated analyses revealed that people
higher in trait difficulty-as-improvement were on average more likely to experience greater daily
meaning in life (H4a; b = .34, t = 4.98, p < .001), life coherence (H4b; b = .25, t = 4.52, p <
.001), self-esteem (H4c; b = .17, t = 2.88, p = .004), and life satisfaction (H4d; b = .17, t = 2.65,
p = .009). As seen in Figure 3, they were on average also more likely to engage in effortful
strategies (H4e; b = .92, t = 3.86, p < .001) and experience successes (H4f; b = .61, t = 4.22, p <
.001). Of note, effortful engagement was assessed in Studies 2-4, not in Study 1. Green circles
represent regression coefficients for each individual study; numeric representations of these can
86
be seen in Table S3. The meta-analytic effect sizes were as follows: meaning in life .29
(moderate); coherence .27 (small to moderate); self-esteem .16 (small to moderate); life
satisfaction .14 (small to moderate); effortful engagement .27 (small to moderate); and success
.34 (moderate to large).
Figure 2
Trait Difficulty-as-Improvement Predicts Daily Wellbeing
Note. In each graph, the x-axis represents the magnitude of the unstandardized regression
coefficient of trait difficulty-as-improvement for the given DV . The y-axis represents the Study
number with the bottommost y-axis tick representing the meta-analytic result. In Studies 1-3, we
used the sanctified/ religious version of the trait difficulty-as-improvement measure; in Study 4
we used the secular version. For numeric representations of confidence intervals, see Table S3 in
Supplemental Materials.
87
Figure 3
Trait Difficulty-as-Improvement Predicts Daily Experiences
Note. In each graph, the x-axis represents the magnitude of the unstandardized regression
coefficient of trait difficulty-as-improvement for the given DV . The y-axis represents the Study
number with the bottommost y-axis tick representing the meta-analytic result. For numeric
representations of confidence intervals, see Table S3 in Supplemental Materials.
H5: Today’s difficulty-as-improvement predicts today’s wellbeing and daily experiences.
To examine the H5 within-person relationships, we created two-level models with either
the daily well-being or daily experience variable as the outcome variable in each separate model.
Daily difficulty-as-improvement was entered as the level-1 predictor, centered around each
individual’s mean as follows:
Day level: y
ij
(outcome variable) = β
0j
+ β
1j
(difficulty-as-improvement)
ij
+ r
ij
Person level: β
0j
= γ
00
+ u
0j
β
1j
= γ
10
+ u
1j
88
We found support for H5. As seen from the blue triangles representing aggregated
analyses in Figure 4, on days when people more strongly endorsed difficulty-as-improvement
compared to their two-week average endorsement, they were more likely to experience greater
meaning in life (H5a; b = .41, t = 12.98, p < .001), life coherence (H5b; b = .36, t = 11.75, p <
.001), self-esteem (H5c; b = .32, t = 9.96, p < .001), and life satisfaction (H5d; b = .39, t =
10.85, p < .001). Similarly, as represented by the blue triangles in Figure 5, on days when people
more strongly endorsed difficulty-as-improvement compared to their two-week average, they
were more likely to engage in effortful strategies (H5e; b = .13, t = 7.80, p < .001) and
experience successes (H5f; b = .15, t = 8.19, p < .001). Of note, effortful engagement was
assessed in Studies 2-4, not in Study 1. Green circles represent regression coefficients by study;
numeric representations can be found in Table S4 in Supplemental Materials. The meta-analytic
effect sizes were as follows: meaning in life .34 (moderate to large); coherence .40 (moderate to
large); self-esteem .35 (moderate to large); life satisfaction .34 (moderate to large); effortful
engagement .21 (small to moderate); and success .20 (small to moderate).
Interested readers can turn to Table S5 in Supplemental Materials for results of H5
models in which we did not model random slope variability. Whether we modeled random slope
variability or not, the fixed effects that are of interest to us remained similar.
89
Figure 4
Daily Difficulty-as-Improvement Predicts Daily Wellbeing
Note. In each graph, the x-axis represents the magnitude of the unstandardized regression
coefficient of the person-mean-centered daily difficulty-as-improvement variable. The y-axis
represents the Study number with the bottommost y-axis tick representing the meta-analytic
result. For numeric representations of confidence intervals, see Table S4 in Supplemental
Materials.
90
Figure 5
Daily Difficulty-as-Improvement Predicts Daily Experiences
Note. In each graph, the x-axis represents the magnitude of the unstandardized regression
coefficient of the person-mean-centered daily difficulty-as-improvement variable. The y-axis
represents the Study number with the bottommost y-axis tick representing the meta-analytic
result. For numeric representations of confidence intervals, see Table S4 in Supplemental
Materials.
H6: Yesterday’s difficulty-as-improvement predicts today’s wellbeing and experiences.
To test H6 and examine the directionality of the within-person relationships between
difficulty-as-improvement and well-being and experiences, we ran lagged analyses. In the first
set of models, we examined the relationship between yesterday’s difficulty-as-improvement and
today’s well-being, controlling for yesterday’s well-being. In the second set of models, we
examined the relationships in the opposite direction. All level-1 predictors were centered around
each individual’s mean as follows and no predictors were included at the person level:
Lagged relationship from difficulty-as-improvement to well-being/experience
Day level: y
ij
(well-being/experience day n) = β
0j
+ β
1j
(difficulty-as-improvement day
91
n-1)
ij
+ β
2j
(well-being/experience day n-1)
ij
+ r
ij
Lagged relationship from well-being/experience to difficulty-as-improvement
Day level: y
ij
(difficulty-as-improvement day n) = β
0j
+ β
1j
(difficulty-as-improvement day
n-1)
ij
+ β
2j
(well-being/experience day n-1)
ij
+ r
ij
We found partial support for H6. As can be seen from the blue triangles in Figure 6
representing aggregated analyses, following days on which people endorsed
difficulty-as-improvement more strongly compared to their two-week average, people were more
likely to experience greater meaning in life (H6a; b = 07, t = 2.32, p = .021), not more likely to
experience greater life coherence (H6b; b = .04, t = 1.70, p = .091), more likely to experience
greater self-esteem (H6c; b = .06, t = 2.32, p = .021), and not more likely to experience greater
life satisfaction (H6d; b = .05, t = 1.60, p = .112). Moreover, as seen from the blue triangles in
Figure 7, people were not more likely to engage in effortful strategies (H6e; b = .02, t = 1.31, p =
.191) or experience successes (H6f; b = .02, t = 0.87, p < .385). Detailed by-study results can be
found in Table S6, and results from models where we did not model random slope variability can
be found in Table S7 in Supplemental Materials. We do not report effect sizes for these models,
however, interested readers can turn to Tables S8-S9 in Supplemental Materials to see results of
models that test H6 without daily lag controls, where they can find the R
w
f1v
effect size associated
with the daily lag difficulty-as-improvement variable. In the models without daily lag controls,
the meta-analytic effect sizes were as follows: .16 (small to moderate); coherence .13 (small to
moderate); self-esteem .17 (small to moderate); life satisfaction .13 (small to moderate); effortful
engagement .07 (small); and success .14 (small to moderate).
92
To provide a complete picture (as a sanity check), we also tested lagged relationships in
the opposite direction. In these analyses, the only significant meta-analytic relationship was that
between yesterday’s coherence and today’s difficulty-as-improvement, controlling for
yesterday’s difficulty-as-improvement (b = .05, t = 2.71, p = .007). The other lagged wellbeing
and daily experience variables did not have a significant relationship with today’s
difficulty-as-improvement (Table S10 in Supplemental Materials).
Figure 6
Yesterday’ s Difficulty-as-Improvement Predicts Current Day’ s Meaning in Life and Self-Esteem
93
Note. In each graph, the x-axis represents the magnitude of the unstandardized regression
coefficient of the person-mean-centered daily lag difficulty-as-improvement variable. The y-axis
represents the Study number with the bottommost y-axis tick representing the meta-analytic
result. For numeric representations of confidence intervals, see Table S6 in Supplemental
Materials.
Figure 7
Yesterday’ s Difficulty-as-Improvement Predicts Current Day’ s Wellbeing (With Controls)
Note. In each graph, the x-axis represents the magnitude of the unstandardized regression
coefficient of the person-mean-centered daily lag difficulty-as-improvement variable. The y-axis
represents the Study number with the bottommost y-axis tick representing the meta-analytic
result. For numeric representations of confidence intervals, see Table S6 in Supplemental
Materials.
Exploratory Analyses
We pre-registered a set of exploratory analyses pertaining to religiosity and daily
religious experiences (Supplemental Materials Table S11), daily engagement in ease (Table S12),
and daily failures (Table S13). Results of these analyses can be found in Tables S14-S23 in
94
Supplemental Materials. For brevity’s sake, we only briefly describe general results here. Trait
religiosity is correlated with trait difficulty-as-improvement (meta-analytic r = .17, t = 3.35, p <
.001). People endorse difficulty-as-improvement more on days on which they engage in religious
activity (meta-analytic b = 0.08, t = 2.37, p = .019). Trait difficulty-as-improvement does not
predict daily religious activity (meta-analytic b = 0.05, t = 1.26, p = .210), daily easy
engagement (meta-analytic b = 0.05, t = 1.54, p = .124), or daily failures (meta-analytic b =
-0.03, t = -1.21, p = .228). Same-day difficulty-as-improvement is associated with same-day
easy engagement (meta-analytic b = 0.08, t = 4.94, p < .001) and failures (meta-analytic b =
-0.07, t = -4.39,p < .001). The interactions we explored were for the most part non-significant;
Supplemental Materials provide details of these analyses.
Discussion
Across four daily diary studies, we investigated the effects of having a
difficulty-as-improvement mindset—the belief that difficulties are character-building and
self-improving—on wellbeing and daily experiences. Our findings are as follows. First, the
secular and sanctified ways of measuring trait difficulty-as-improvement can be considered
redundant. Second, about two-thirds of the variance in daily difficulty-as-improvement scores
were attributable to between-person differences and one-third to within-person fluctuations. It is
reasonable to conceptualize difficulty-as-improvement as an individual difference, but the
amount of within-person variation also allows for examination of within-person relationships.
Thus, we examined relationships at each level of analysis as they address distinct questions.
Third, trait level endorsement of difficulty-as-improvement was associated with people’s
trait level experience of their lives as meaningful and coherent and themselves as people with
95
high self-worth and life satisfaction. Fourth, trait-level endorsement carried over to daily
experiences of these outcomes and to daily effortful engagement and experiences of success.
Fifth, not only was trait difficulty-as-improvement associated with higher trait and daily levels of
these outcomes, but also, there were same-day effects of experiencing difficulty as
self-improving: On days when they endorsed difficulty-as-improvement more compared to their
two-week average, people reported higher meaning in life, coherence, self-esteem, and life
satisfaction, were more likely to engage in effortful strategies, and more likely to experience
success. Sixth, following days when they endorsed difficulty-as-improvement more compared to
their two-week average endorsement, people reported higher meaning in life (controlling for the
prior day’s experience of meaning in life), and higher self-esteem (controlling for the prior day’s
experience of self-esteem). Whereas yesterday’s difficulty-as-improvement only had a
trend-level effect on today’s coherence (b = .04, t = 1.70, p = .091), the effect of yesterday’s
coherence on today’s difficulty-as-improvement was more robust (b = .05, t = 2.71, p = .007).
Our findings imply that daily fluctuations in difficulty-as-improvement may have a lasting effect
on experiencing life as meaningful and oneself as a person of worth, while fluctuations in
coherence may have a lasting effect on people’s sense that difficulty is self-improving. We
discuss the contributions of our findings next.
We add to the literature on Identity-based motivation and difficulty-as-improvement by
replicating prior findings on the relationship between trait difficulty-as-improvement and
meaning in life, and by expanding this to other outcomes. Furthermore, prior work tested the
effects of endorsing this mindset on people’s perceptions of difficult strategies (Kiper et al.,
2023); we expand on this work and document the effects of difficulty-as-improvement on how
much people report engaging in effortful strategies in their daily lives.
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Through its links to our outcomes, the difficulty-as-improvement mindset has the
potential to support wellbeing, health, and daily functioning. Meaning and coherence have been
linked to various positive outcomes: meaning in life to physical health (Czekierda et al., 2017);
meaning and coherence to lowered distress (Winger et al., 2016); and coherence to reduced
PTSD symptoms (Schäfer et al., 2019). In a similar vein, self-esteem has been linked to lower
levels of depression and anxiety (Sowislo & Orth, 2013), higher levels of happiness (Cheng &
Furnham, 2004), and higher positive affect and lower negative affect (Orth et al., 2012); and life
satisfaction to lower levels of depression (Lewinsohn et al., 1991), better adaptation, and optimal
mental health (Park, 2004). Given these associations, a difficulty-as-improvement mindset
should be a beneficial tool that allows people to experience improved wellbeing and health.
The difficulty-as-improvement mindset may also support wellbeing by helping people
construct life narratives centered around redemption (McAdams, 2013) and being the hero of
one’s journey (Campbell, 1949). A highly American ideal (McAdams, 2006), redemption
narratives are stories that include negative experiences giving way to positive outcomes
(McAdams, 2013; McAdams et al., 2001). People who display more redemptive sequences
report greater concurrent and long-term well-being (e.g., Adler et al., 2015; McAdams et al.,
2001) and people who hold a redemptive mindset towards life (e.g., “If I receive bad news, it
tends to work out in the long run”) report higher life satisfaction, optimism, and
conscientiousness (Dunlop et al., 2020). Similarly, people who more strongly endorse the idea
that their own life is a Hero’s Journey (e.g., “I will have a lasting impact on others”) report
higher meaning in life (Rogers et al., 2023), and people who are led to write their life stories
from the perspective of the Hero’s Journey subsequently experience higher meaning in life and
resilience (Rogers et al., 2023). As it specifically concerns the self and one’s growth, a life
97
narrative focused on the difficulty-as-improvement mindset has the potential to increase the
benefits of constructing redemption narratives or having a redemptive identity. Furthermore, the
difficulty-as-improvement mindset may be a critical part of perceiving oneself as a hero on a
journey: overcoming trials and tribulations is the prerequisite to being transformed from
someone unexceptional into a hero in the Hero’s Journey story template (Campbell, 1949). By
embracing this mindset, people can come to view their life difficulties as necessary steps on the
path to becoming an exceptional person, rather than seeing these as insurmountable obstacles.
Individuals can thus begin to see their lives as heroic journeys and gain motivation and resilience
to achieve positive outcomes.
Limitations and Future Directions
Three limitations are worth mentioning. First, our sample consisted of USC
undergraduates who were for the most part between the ages of 18 and 23. This was a
predominantly Western sample who was most likely not experiencing extreme financial hardship
or health problems, and so our results may not be generalizable to populations who are
experiencing extreme hardship or traumas. Future studies may consider a more diverse sample
that includes people from non-Western populations and a wider age range. There is some
preliminary evidence that when people are experiencing financial hardship, they endorse
difficulty-as-improvement less (Karimi-Malekabadi & Oyserman, 2023) but it is not yet clear
whether the relationship between endorsing difficulty-as-improvement and wellbeing and
engagement would change or remain the same in these circumstances. Furthermore, we do not
know from our current studies to what extent the proportion of between-person variability in
difficulty-as-improvement is culturally-specific. Future samples that comprise multiple cultures
can address this question.
98
The second limitation pertains to our measures. All measures were based on self-report,
and did not include direct observation of people. Future studies could incorporate direct
observations of behavior or physiology throughout the day (e.g., using Ecological Momentary
Assessment to measure blood pressure and heart rate, Newman et al., 2023) as more objective
measures.
Finally, although lagged analyses reveal that difficulty-as-improvement is a precursor to
experiencing meaning in life and self-esteem, temporal precedence does not establish causality
(West & Hepworth, 1991). There is some evidence that difficulty mindsets are causally linked to
outcomes. For example, students spend more time on (Elmore et al., 2016; Smith & Oyserman,
2015), perform better on (Oyserman et al., 2018), and place more value on (Aelenei et al., 2017)
school tasks when led to view difficulties as signals of importance (a “difficulty-as-importance”
mindset) rather than signals of impossibility (a “difficulty-as-impossibility” mindset). However,
to our knowledge, there is not yet any experimental evidence that causally links the
difficulty-as-improvement mindset to outcomes. Hence, future studies can investigate whether
adopting a difficulty-as-improvement mindset may increase subsequent experiences of meaning
and self-worth.
Conclusion
In conclusion, we found that having a difficulty-as-improvement mindset is beneficial.
The more people endorse this idea, the more favorably they experience themselves and their
lives, the more likely they become to engage in effortful but necessary strategies, and the more
likely they become to succeed. The more people experience meaning in their lives, coherence,
self-esteem, and life satisfaction, the more they may be able to combat mental illness and
experience psychological and physical wellbeing.
99
Chapter 4: General Discussion
Overall, our studies point to the value of embracing a difficulty-as-improvement mindset.
The strengths in our studies is variability in the methods (e.g., structural equation modeling,
multilevel modeling) and variability in the DVs (e.g., perceptions of one’s life, daily successes).
We discuss limitations and future directions next.
Limitations and Future Directions
Three limitations of this work are worth mentioning. First, we have not yet successfully
developed materials to causally manipulate endorsement of the difficulty-as-improvement
mindset to test subsequent effects on our outcomes of interest. We tried autobiographical
memory primes in several studies but did not successfully attain effects of this prime on DVs
(i.e., meaning in life, optimism, self-compassion). Second, undergraduate students are the
subjects of two of the three studies comprising my dissertation and Study 1 of Yan et al. (2023).
These younger populations may not be experiencing hardship to the same degree as older and
more diverse populations do, and hence may be thinking of a different category of experiences
when asked to think about difficulty-as-improvement. A final limitation worth mentioning is that
we haven’t yet answered when it might be inadvisable to hold a difficulty-as-improvement
mindset. Not all difficulties are desirable—sometimes it is better to simply quit and take oneself
out of the situation instead of persisting (e.g., in cases such as abuse). Future work can test more
primes to construct a successful method of inducing difficulty-as-improvement; look into how
age affects how people respond to difficulty-as-improvement; and test the situations in which
people might be better off not holding a difficulty-as-improvement mindset.
One exciting direction that this work is taking is analyses on the English language to
determine the extent to which life difficulties lead to an increase in improvement discourse.
100
Using a pre-trained BERT language model on 68 countries from 1989 to 2022,
Karimi-Malekabadi & Oyserman (2023) found that individual-level life difficulties predict the
difficulty-as-improvement mindset after controlling for country-level covariates, thus providing
evidence for ecological validity. Moreover, they found that experiencing financial hardship is
negatively associated with endorsement of difficulty-as-improvement. My plan for the future is
to continue to support my colleagues’ work on this topic as I find the topic to be fascinating and
important, and hope that we continue to evidence ecological validity in addition to shedding
better light on causal links and limitations pertaining to the difficulty-as-improvement mindset.
Conclusion
As Viktor Frankl said,“In some ways, suffering ceases to be suffering at the moment it
finds a meaning.” (1985) Ultimately, I believe that people have the power to choose how they
respond to their life difficulties, and interpreting difficulties from a self-improvement lens can
help ease suffering and create hope. This work has given me valuable insight and shown support
for this notion. I have learned that seeing difficulties as parts of one’s journey that are necessary
for growth and transformation gives people meaning, self-esteem, courage, and resilience.
Moreover, there are both religious and non-religious cultural antecedents of the
difficulty-as-improvement mindset, and although there are some cultural differences, this belief
tends to be cross-culturally endorsed. Overall, those who embrace the notion that difficulties
serve a character-building purpose stand to benefit in numerous ways.
101
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Appendix A: Measures for Chapter 1
Table A1
Difficulty Mindset Scale Items
Scale
Difficulty-as-Improvement
Difficulty-as-Importance
Difficulty-as- Impossibility
1. In a way, the struggles I
have today are
strengthening my
character to meet
tomorrow's challenges.
2. Experiencing difficulty
makes me grow stronger.
3. Experiencing difficulty
is the strongest of
teachers; I may
temporarily feel broken
but in the long run, I will
be better.
4. Life is not complete
without difficulty,
hardship, and suffering.
1. Sometimes if a task
feels difficult to me my
gut says that it really
matters for me.
2. If a goal feels difficult
to work on, I often think
it might be a critical one
for me.
3. When a task feels
difficult, the experience
of difficulty sometimes
informs me that
succeeding in the task is
important for me.
4. Often when a goal feels
difficult to attain it turns
out to be worth my
effort.
1. Sometimes if a task feels
difficult, my gut says it
is impossible for me.
2. If a goal feels difficult to
work on, I often think it
might not be for me.
3. When a task feels
difficult, the experience
of difficulty sometimes
informs me that
succeeding in the task is
just not possible for me.
4. Often when a goal feels
difficult to attain it turns
out to be out of my
reach.
Note. Participants indicated how much they agreed or disagreed (1 = strongly disagree, 6 =
strongly agree).
Table A2
Silver Linings and Actions Scale Items
Scale
Silver Linings Taking Action
1. This pandemic has made me a better person.
2. This pandemic made me face up to problem
areas of my life.
1. Frequent handwashing.
2. Disinfecting surfaces at home
frequently.
113
3. This pandemic made me more mature.
4. This pandemic made me a more tolerant person.
5. This pandemic made me a more determined
person.
6. This pandemic made me more aware of my
strengths.
7. Because of this pandemic I find it easier to
accept what life has in store.
3. Use hand sanitizer when outside.
4. Wear a mask when outside.
5. Practice social distancing.
6. Stay at home as much as possible.
7. Use delivery or curbside pickup
services to avoid going into
establishments.
Note. Participants indicated their response on a 5-point Likert scale (1 = disagree/never, 5 =
agree/always).
Table A3
Experiences of Adversity (8 items)
These are questions about your …
Income Health Other obligations
My income has … My other obligations have…
become more uncertain
because of COVID-19.
I have had symptoms of
COVID-19.
increased because of
COVID-19.
dropped because of
COVID-19.
My physical health has
suffered due to COVID-19.
become more difficult to
manage because of
COVID-19.
I have not been able to keep
up my regular physical health
maintenance because of
COVID-19.
become more stressful
because of COVID-19.
Note: Instructions and Response Scale by Study: Study 1 Please rate the extent to which you
agree or disagree with each of the following statements regarding your own experiences during
the COVID-19 pandemic (1= disagree, 2= disagree a little, 3= neutral, 4= agree a little, 5=
agree). Studies 2 and 3 Please tell us whether you’ve experienced any of the following during the
COVID-19 pandemic (1= No, 2 = Yes). Other obligations were detailed as schooling for your
children, parenting, caring for family members, household responsibilities.
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Table A4
Silver Linings for Community (7-items) and Additional Actions That Would Not Load On Onto a
One- or Two-Factor Structure (Study 3)
Scale Name and Items
Silver Linings For Community Taking Action
1. This pandemic is making society
better.
2. This pandemic is making society face
up to problem areas.
3. This pandemic is making elected local
officials more mature.
4. This pandemic is making society more
tolerant.
5. This pandemic is making society more
determined to do the right thing (e.g.,
volunteering, providing financial
assistance to the needy).
6. This pandemic is making a stronger,
less divided society.
7. This pandemic is making society more
accepting of future uncertainties.
1. Take supplements like vitamin D.
2. Get the COVID-19 vaccine as soon
as one is available for people in my
category.
3. Get my flu vaccine.
4. Be cautious with my finances
5. Time grocery trips.
6. Limit socializing.
7. Tip more generously than usual.
8. Donate my time or money (e.g., food
drives, delivering meals, volunteering
for organizations like Red Cross).
9. Support local businesses rather than
buying from the big box stores (e.g.,
Amazon).
Note: Instructions and Response Scales: Please rate the extent to which you agree or disagree
with each of the following statements regarding society’s experiences with the COVID-19
pandemic (1= disagree, 2= disagree a little, 3= neutral, 4= agree a little, 5= agree). For Actions,
We attempted to expand the list and focus of actions but we could not create a reliable one- or
two-factor scale and hence used only the 7-item taking actions scale assessed in all three studies.
In addition to asking about actions performed to protect oneself, we asked how likely people
were to take each of these actions to protect one’s community: How certain are you that you will
engage in each of the following steps to protect your community so that you help to reduce the
community spread of COVID-19 and do not add to the burden of the health care system?
115
Figure A1
Difficulty Mindsets Predict Taking Action via Silver Linings: Detailed Structural Equations
Model with Correlations, Regression Paths, and Factor Loadings (Unconstrained Model)
Note. Coefficients are standardized estimates. Factor indicators are numbered consistent with
their numbering in Tables 2 and 3. All factor loadings were significant at p<.001. Bolded lines
represent significant paths; dashed lines represent non-significant paths. ** p < .01, *** p < .001.
116
Abstract (if available)
Abstract
Life often presents people with unchosen difficulties and how people respond to these difficulties matters. Both religious and non-religious cultural frameworks draw attention to difficult experiences as opportunities for building character and becoming a better version of oneself. We term the belief that difficulties are character-building the “difficulty-as-improvement mindset.” Throughout my PhD, I investigated the sources and consequences of endorsing this belief, being specifically interested in how this belief can confer value. The three papers comprising my dissertation each investigate the value of holding belief in a different context, using various methodologies. We find that overall, people who more strongly endorse the difficulty-as-improvement mindset are better off, seeing silver linings in difficult life circumstances, positively evaluating ethical but effortful goal pursuit strategies, and experiencing life as meaningful and themselves as people of worth.
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A path to K-12 educational equity: the practice of adaptive leadership, culture, and mindset
Asset Metadata
Creator
Kiper, Gülnaz
(author)
Core Title
The antecedents and consequences of believing that difficulties are character-building
School
College of Letters, Arts and Sciences
Degree
Doctor of Philosophy
Degree Program
Psychology
Degree Conferral Date
2023-08
Publication Date
05/22/2023
Defense Date
05/02/2023
Publisher
University of Southern California
(original),
University of Southern California. Libraries
(digital)
Tag
culture,difficulty mindsets,difficulty-as-improvement,identity-based motivation theory,OAI-PMH Harvest,wellbeing
Format
theses
(aat)
Language
English
Contributor
Electronically uploaded by the author
(provenance)
Advisor
Oyserman, Daphna (
committee chair
), Monterosso, John (
committee member
), Schwarz, Norbert (
committee member
), Wakslak, Cheryl (
committee member
)
Creator Email
gkiper@usc.edu,gulnazkiper@gmail.com
Permanent Link (DOI)
https://doi.org/10.25549/usctheses-oUC113134840
Unique identifier
UC113134840
Identifier
etd-KiperGulna-11883.pdf (filename)
Legacy Identifier
etd-KiperGulna-11883
Document Type
Dissertation
Format
theses (aat)
Rights
Kiper, Gulnaz
Internet Media Type
application/pdf
Type
texts
Source
20230524-usctheses-batch-1048
(batch),
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.
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
culture
difficulty mindsets
difficulty-as-improvement
identity-based motivation theory
wellbeing