Perseverance and passion to positively predict performance

Why grit requires perseverance and passion to positively predict performance
Author(s): Jon M. Jachimowicz, Andreas Wihler, Erica R. Bailey and Adam D. Galinsky
Source: Proceedings of the National Academy of Sciences of the United States of
America , October 2, 2018, Vol. 115, No. 40 (October 2, 2018), pp. 9980-9985
Published by: National Academy of Sciences
Stable URL: https://www.jstor.org/stable/10.2307/26531374
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Why grit requires perseverance and passion to
positively predict performance
Jon M. Jachimowicza,1, Andreas Wihlerb, Erica R. Baileya, and Adam D. Galinskya
aManagement Division, Columbia Business School, New York, NY 10025; and bManagement Department, Frankfurt School of Finance & Management,
60322 Frankfurt am Main, Germany
Edited by Susan T. Fiske, Princeton University, Princeton, NJ, and approved August 17, 2018 (received for review March 1, 2018)
Prior studies linking grit—defined as perseverance and passion for
long-term goals—to performance are beset by contradictory evidence.
As a result, commentators have increasingly declared that grit
has limited effects. We propose that this inconsistent evidence has
occurred because prior research has emphasized perseverance and
ignored, both theoretically and empirically, the critical role of passion,
which we define as a strong feeling toward a personally important
value/preference that motivates intentions and behaviors to express
that value/preference. We suggest that combining the grit scale—
which only captures perseverance—with a measure that assesses
whether individuals attain desired levels of passion will predict performance.
We first metaanalyzed 127 studies (n = 45,485) that used
the grit scale and assessed performance, and found that effect sizes
are larger in studies where participants were more passionate for the
performance domain. Second, in a survey of employees matched to
supervisor-rated job performance (n = 422), we found that the combination
of perseverance, measured through the grit scale, and passion
attainment, measured through a new scale, predicted higher
performance. A final study measured perseverance and passion attainment
in a sample of students (n = 248) and linked these to their
grade-point average (GPA), finding that the combination of perseverance
and passion attainment predicted higher GPAs in part through
increased immersion. The present results help resolve the mixed evidence
of grit’s relationship with performance by highlighting the
important role that passion plays in predicting performance. By adequately
measuring both perseverance and passion, the present research
uncovers grit’s true predictive power.
grit | perseverance | passion | performance | motivation
The concept of grit has captured the public imagination.
Angela Duckworth’s 2013 TED talk introduced grit to a
broad audience and described it as an important predictor of
future success; the talk clearly resonated with audiences, as it has
over 14 million views to date (1). Her subsequent 2016 book,
Grit: The Power of Passion and Perseverance, became an international
best-seller (2). Grit has also crept into educational
policy throughout the United States, influencing the design of
school curriculums to boost their future success by making students
“grittier” (3). These developments are seemingly occurring
for good reason: prior studies have found that grit relates to
several intermediaries of success, including increased deliberate
practice (4), sustained retention in difficult jobs (5, 6), and task
persistence (7).
Given the widespread attention and initial evidence, one
would expect to find copious studies showing that grit predicts
performance. Surprisingly, evidence linking grit and performance
is beset by contradictory empirical results. A recent
metaanalysis, as well as high-powered empirical studies, have
found a weak or nonsignificant relationship between grit and
various indicators of success (8–10). Because the evidence regarding
the relationship between grit and performance has been
inconclusive, several commentators have stated that grit is
“overrated,” “limited,” “hyped,” and “under attack” (11–14).
We propose that the inconsistency between grit’s initial promise
and its subsequent lack of empirical support has occurred because
grit’s measurement has not matched its definition. Duckworth
et al. (5) define grit as “perseverance and passion for long-term
goals.” Although this definition of grit contains two conceptual
components—perseverance and passion—we suggest that the grit
literature, and consequently its measurement, has focused only on
perseverance and has not adequately captured passion. The tight
link between grit and perseverance has even made its way into online
thesauruses: on https://www.thesaurus.com/, synonyms of
perseverance include grit and synonyms of grit include perseverance,
but neither includes passion.
The issue is not just conceptual but also methodological. We
propose that the current measure of grit likely reflects perseverance
alone. Indeed, studies that find effects of the grit scale
on performance-related outcomes are highly connected to perseverance
(e.g., increased deliberate practice, sustained retention,
and task persistence). We suggest that passion is key to
grit but missing in its theory and measurement, which as a result,
has produced the empirical inconsistencies found in the grit
literature.
Overall, academics and popular commentators alike frequently
equate grit with perseverance alone and neglect the
passion component. Prominent educational psychologist Mike
Rose, critiquing grit, states, “[r]ather than calling their construct
‘perseverance’ or ‘persistence,’ they chose to call it ‘grit’” (15).
Similarly, consider that a metaanalysis of the grit literature refers
to grit as “a personality trait” (8), and compares grit to
Significance
Grit has captured the public imagination and crept into educational
policy throughout the United States. However, because
prior studies linking grit and performance are beset by
contradictory evidence, commentators increasingly state that
grit is overhyped. We propose that the inconsistency between
grit’s initial promise and its subsequent lack of empirical support
has occurred because grit’s measurement has not matched
its definition. Although grit is defined as the combination of
perseverance and passion, its measurement has focused on
perseverance and has not adequately captured passion. In a
metaanalysis of 127 studies and two field studies, we show
that passion is a key component of grit. The current theory and
results suggest that perseverance without passion isn’t grit,
but merely a grind.
Author contributions: J.M.J. designed research; J.M.J. and E.R.B. performed research;
J.M.J., A.W., and E.R.B. analyzed data; and J.M.J., A.W., E.R.B., and A.D.G. wrote
the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
Published under the PNAS license.
Data deposition: Data and scripts related to this paper are available at https://osf.io/
kp7cb/.
1To whom correspondence should be addressed. Email: [email protected].
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.
1073/pnas.1803561115/-/DCSupplemental.
Published online September 17, 2018.
9980–9985 | PNAS | October 2, 2018 | vol. 115 | no. 40 www.pnas.org/cgi/doi/10.1073/pnas.1803561115
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conscientiousness in their analyses. Angela Duckworth herself
noted this shortcoming of the theory and measurement of grit,
stating that she is thinking about revising her grit scale, “specifically
the questions about passion” (16).
The neglect of passion in the measurement of grit is particularly
problematic because prior research stresses that passion
produces beneficial effects on performance through a key
mechanism: immersion. Several studies converge on the idea
that the combination of perseverance and passion may heighten
individuals’ immersion in a performance domain—that is, the
intensity of focus experienced—which may in turn promote
higher levels of performance (17–20). In fact, passion is key to
how Angela Duckworth speaks about the beneficial outcomes of
grit. In a recent interview, she noted, “I think the misunderstanding—
or, at least, one of them—is that it’s only the
perseverance part that matters [. . .] But I think that the passion
piece is at least as important. I mean, if you are really, really
tenacious and dogged about a goal that’s not meaningful to you,
and not interesting to you—then that’s just drudgery. It’s not just
determination—it’s having a direction that you care about” (as
cited in ref. 12).
The present research brings passion back into the conceptualization
and measurement of grit. We propose that only the
combination of the current grit measure, the Grit-S scale (6)—
which emphasizes perseverance—with a measure that assesses
whether individuals attain desired levels of passion will predict
higher performance. Furthermore, we hypothesize that immersion
will be a key route through which the combination of perseverance
and passion attainment will improve performance.
We test these propositions in a metaanalysis, a field study with
employees at a technology company, and a field study of
undergraduate students.
The Absence of Passion in Grit Literature and Measurement
From its inception, grit has theoretically stood on the dual pillars
of perseverance and passion. The definition of grit includes the
word passion: “perseverance and passion for long-term goals”
(5). Drawing on, integrating, and extending prior conceptualizations
of passion (21–24),* we define passion as a strong feeling
toward a personally important value/preference that motivates
intentions and behaviors to express that value/preference. We
use the words “a strong feeling” to indicate that passion is an
intense affective state, but one that is not necessarily limited to
positive emotions alone (21, 24). We use the phrase “toward a
personally important value/preference” to denote that the target
of passion reflects an attribute that has high personal value or
strong appeal to the individual (21, 23). This builds on prior
notions that passion is domain-specific, such as passion for
hobbies, relationships, or work (23, 25, 26). We use the phrase
“that motivates intentions and behaviors to express that value/
preference” to capture that passion leads individuals to consistently
desire engaging and interacting with this personally important
value/preference: that is, the target of their passion
(22, 24).
Despite the conceptual importance of passion in grit, there are
theoretical and empirical concerns about whether the grit scale
truly captures passion. The scale used to assess grit features two
components—“persistence of effort” and “consistency of interests”—
the latter of which has been suggested to measure passion
(5, 6). Theoretically, the claim that “consistency of interests”
equates to passion is not supported by research. Although
consistency of interests may be statistically correlated with personally
important values/preferences, they are conceptually distinct.
Consider this example: an academic may maintain a high
consistency in an interest (e.g., the revision of manuscripts as
part of the publication process), but the interest itself may have
little personal importance (e.g., revising a manuscript on an
unimportant topic).
Empirical results similarly cast doubt on the equivalence of
consistency of interests and passion. Consider that a recent study
finds no significant relationship between self-rated consistency of
interests and other-rated passion (27). This concern is also borne
out in a recent metaanalysis (8), which reports a corrected correlation
of ! = 0.60 between “persistence of effort” and “consistency
of interests.” This correlation size supports the presence
of a single construct (28), leading the authors of the metaanalysis
(8) to conclude that the grit scale only measures the single factor
of perseverance. This discrepancy may have occurred because
the grit literature has not connected with prior passion research.
In Duckworth et al.’s (5) paper introducing grit, the word “passion”
only appears in the manuscript title, the definition of grit,
and as a reference to a scale the authors discarded. In subsequent
publications, there is no reference to passion other than
including the word passion in the definition (4, 6, 29–31).
Taking these data together, we find that there is considerable
theoretical and empirical evidence that the scale intended to
measure both components of grit—perseverance and passion—
likely captures only perseverance. We therefore subsequently
refer to what the grit scale measures as perseverance. [The grit
scale, developed by Duckworth et al. (5) contained 12 items, but
was superseded by a shortened eight-item version of the grit
scale (termed the Grit-S scale), which has superior psychometric
qualities (6). In the studies described below, we focus on the
Grit-S scale, which has been used predominantly since its publication.]
We highlight why passion is a key component of grit’s
beneficial effects and propose that uncovering grit’s predictive
power requires adequate measurement of both perseverance
and passion.
Passion Attainment as a Key Component of Grit
We propose that passion is a key ingredient of grit and needs to
be empirically captured for a positive relationship between perseverance
and performance to emerge. We suggest that passion
is essential for perseverance to unfold its beneficial effects because
it combines with perseverance to increase immersion in an
activity, evidenced by increased focus and pursuit of activities
related to their passionate endeavor (17–19). That is, the increased
immersion produced by the combination of perseverance
and passion leads individuals to devote greater cognitive effort
and investment to their goals, as evidenced in more intense
concentration (32). This heightened immersion, in turn, provides
the energy and dedication that makes it more likely that individuals
attain their goals (33, 34). Although perseverance helps
individuals by remaining committed to their goal pursuit (5, 31),
passion provides individuals with the focus necessary to achieve
their goals (4, 29, 35). Thus, when individuals pursue goals they
are not passionate for, perseverance may not produce increased
performance. In contrast, when employees pursue goals they
are passionate for, higher perseverance may improve their
performance.
Anecdotal evidence indicates that many highly persevering
individuals achieve success only when pursuing goals they are
passionate about. Consider the Italian singer Andrea Bocelli,
who originally started his career as a lawyer, a course of study
that requires substantial persistence, particularly given his
blindness. Even while pursuing this field of study, Bocelli continued
to sing at piano bars, but it was only when Bocelli allowed
himself to be immersed in the pursuit of singing, “a passion he
couldn’t shake” (36), that he found success. This example illustrates
that the purported benefits of the combination of perseverance
and passion originally proposed by grit researchers
requires the adequate measurement of both components of grit.
*Perttula KM, Annual Meeting of the Academy of Management, August 1–6, 2003,
Seattle.
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PSYCHOLOGICAL AND
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In further understanding the role of passion, the current research
highlights the importance of passion attainment: that is,
whether people experience desired levels of passion (37). In
prior research, passion has commonly been assessed using an
adaptation of Vallerand et al.’s (23) harmonious passion scale,
which was originally developed to assess how individuals feel
about activities that are “very dear to their heart” (23). However,
individuals commonly assess whether they are experiencing desired
levels of passion (38, 39) and are guided by whether they
have met this expectation (40–42). Indeed, a recent stream of
research highlights that the experience of passion is guided by
whether an individual attains or falls short of desired levels of
passion and not by their absolute levels of harmonious passion
(37). Thus, we propose that the combination of perseverance and
passion attainment will predict performance.
Study 1: Assessing the Role of Passion in Prior Studies
To begin investigating the impact of the combination of perseverance
and passion in predicting performance, we first reviewed
prior studies in which the grit scale was used, and performance
measured. A literature search yielded 127 studies (n = 45,485)
(for more details on search and analyses, see Materials and
Methods; see SI Appendix, Table S1 for list of studies included).
Replicating prior research (8), we find a small but statistically
significant effect of perseverance, as measured by the grit scale,
on performance (estimate = 0.13, SE = 0.02, P < 0.001) (see also
SI Appendix, Fig. S1).
We hypothesized that in studies where participants were more
likely to experience passion for a particular performance domain,
the relationship between perseverance and performance
would be stronger. To assess passion in prior research, three
independent coders blind to the hypothesis of this study assessed
whether the majority of participants in the study would find the
performance domain personally important [interrater reliability
(IRR) = 0.81], in line with prior theory and the definition of
passion described above. For example, in a study of entrepreneurs
starting their own companies (43), the majority of participants
may consider the performance domain to be personally
important. In contrast, college students taking a mandatory science
class may consider the performance domain to be less
personally important (44).
Our analysis suggests that passion levels of a performance
domain moderate the relationship between perseverance and
performance. That is, we found that in studies where participants
likely experienced greater passion for a performance domain,
there was a stronger relationship between perseverance and
performance (moderator analysis of the metaanalytic effect: estimate
= 0.07, SE = 0.04, P < 0.05) (see also SI Appendix, Fig. S2
and Table S2 for further information). This analysis thus provides
preliminary support for our theory that passion moderates
the relationship between perseverance and performance.
Study 2: Performance Is Predicted by the Combination of
Perseverance and Passion Attainment
We next conducted a field study with employees at a technology
company. We predicted that perseverance, as measured by the
Grit-S scale, would only relate to increased supervisor-rated
performance when employees attained desired levels of passion.
In contrast, we predicted that for employees who did not attain
desired levels of passion, there would be no significant relationship
between perseverance and performance.
We tested this hypothesis with data from a technology company
(n = 422), where we asked employees to respond to survey
measures of perseverance (as measured by the eight-item Grit-S
scale) and passion attainment (with a previously developed
and validated three-item scale) (see also refs. 37 and 45). We
then matched employees’ survey responses to supervisor-rated
performance ratings. We subsequently ran additional analyses
including various control variables (e.g., age, gender, tenure,
motivation, and harmonious passion) (see SI Appendix for
further information and SI Appendix, Table S3 for bivariate
correlations).
Before testing our hypothesis, we assessed the distinctiveness
of the constructs by conducting confirmatory factor (confirmatory
fit index, CFI) analyses. We first loaded items of each
construct onto their respective factor, and find that the fitindices
were acceptable (46) (with the exception of the CFI): “2
(334) = 845.64, root mean square error of approximation
(RMSEA) = 0.06, CFI = 0.92, standardized root mean square
residual (SRMR) = 0.08. We then compared this model to a
model where we loaded all items from every measure on one
common factor. This model fit the data worse: “2(350) =
3110.19, RMSEA = 0.14, CFI = 0.55, SRMR = 0.12. Additionally,
the fit of the first model was significantly better: #”2 =
2264.55, #df = 16, P < 0.001. In addition, analyses reveal that the
full Grit-S scale represents a single factor, which we label perseverance,
and that this scale is distinct from the passion attainment
measure (see SI Appendix for these and additional
confirmatory factor analyses).
Our hypothesis was that the interaction between perseverance
and passion attainment predicts job performance (SI Appendix,
Table S4). Because supervisors assessed multiple employees, the
data structure is nested; we therefore centered the variables and
applied multilevel analyses (47) (SI Appendix). As shown in
model 2, the interaction effect was both positive and statistically
significant (estimate = 0.03, SE = 0.01, $ = 0.14, P = 0.02) and
accounted for an additional 2% of variance in job performance.
The highest job performance occurred when both perseverance
and passion attainment were high, as depicted in Fig. 1. This
finding was empirically supported through simple slopes analyses
(SI Appendix).
We subsequently tested whether our results remain statistically
significant when adding the control variables. As SI Appendix,
Table S4 shows, the interaction effect remains statistically significant
in all models (model 3 adding in gender, age, and organizational
tenure: estimate = 0.03, SE = 0.01, $ = 0.16, P =
0.01; model 4 adding in harmonious passion, prosocial, intrinsic,
and extrinsic motivation: estimate = 0.03, SE = 0.01, $ = 0.16,
P = 0.01; model 5 adding in the interaction between perseverance
and harmonious passion: estimate = 0.04, SE = 0.01, $ =
0.19, P < 0.001). The values of the simple slopes also remained
the same. These results provide support for our hypothesis that
the combination of perseverance and passion attainment predict
performance.
Fig. 1. Study 2: Passion attainment moderates the relationship between
perseverance and performance.
9982 | www.pnas.org/cgi/doi/10.1073/pnas.1803561115 Jachimowicz et al.
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Study 3: Immersion as One Mediator of the Relationship
Between Perseverance and Passion on Performance
Our final study explored one mechanism through which the
combination of perseverance and passion attainment would
predict performance: by promoting immersion. We recruited 248
currently enrolled students at a private university in the United
States and asked them to fill out the same measures of perseverance
and passion attainment as in the prior study. We also
asked students to upload their current grade transcript and used
their major grade point average (GPA) as a measure of their
performance (see SI Appendix for further information). In addition,
we measured our hypothesized mediator—immersion—
using three items adapted from the Utrecht Work Engagement
Scale (20). The items were, “When I am working on activities
related to my courses, I forget everything else around me,” “I get
immersed in activities related to my courses,” and “I get carried
away working on activities related to my courses” (see SI Appendix,
Table S5 for bivariate correlations).
This study replicated our earlier results (see SI Appendix for
confirmatory factor analyses and additional analyses). SI Appendix,
Table S6 shows the analyses regressing the interaction of
perseverance and passion attainment on performance. As shown
in model 2, the corresponding interaction effect was both positive
and statistically significant (estimate = 0.18, SE = 0.06, P =
0.001), such that perseverance was related to higher performance
at higher levels of passion attainment (+1 SD; estimate = 0.36,
SE = 0.08, P < 0.001) but not at lower levels of passion attainment
(−1 SD; estimate = −0.01, SE = 0.09, P = 0.91).
We next tested for the mediation through immersion. To do
so, we first regressed the interaction of perseverance and passion
attainment on immersion and find a statistically significant interaction
effect (estimate = 0.19, SE = 0.05, P < 0.001); perseverance
was related to higher immersion only at higher levels of
passion attainment (+1 SD; estimate = 0.31, SE = 0.08, P <
0.001) but not at lower levels of passion attainment (−1 SD;
estimate = −0.08, SE = 0.08, P = 0.33). Given the positive correlation
between immersion and performance (r = 0.36, P <
0.001), we next tested for mediated moderation, with perseverance
and passion attainment as the independent variables, immersion
as the mediator, and performance as the dependent
variable, using bias-corrected bootstrapping with 10,000 resamples
to construct 95% confidence intervals (CI) for the conditional
indirect effects (48). We found that the 95% CI of the
mediated moderation excludes zero (0.002; 0.086), demonstrating
a statistically significant indirect effect. Subsequent analyses
revealed that the indirect path from perseverance to performance
via immersion was statistically significant only when
passion attainment was higher [+1 SD; 95% CI (0.029; 0.173)]
but not when passion attainment was lower [−1 SD; 95% CI
(−0.084; 0.025)]. These results indicate that passion attainment
significantly moderates the indirect effect of perseverance on
performance through immersion, such that at higher levels of
passion attainment, the positive relationship between perseverance
and immersion is statistically significant, resulting in higher
performance. Given that the interaction of perseverance and
passion attainment on performance remained statistically significant
when including immersion (from estimate = 0.18, SE = 0.06,
P = 0.001 to estimate = 0.13, SE = 0.05, P = 0.016), the relationship
between the interaction of perseverance and passion
attainment on performance travels in part through immersion.
Discussion
The relationship between grit and performance has created a
firestorm of contradictory results. The current research proposed
that this inconsistency has occurred because even though the
definition of grit includes perseverance and passion, the grit
measure solely reflects perseverance and does not adequately
capture passion. Instead, we suggest that a combination of the
Grit-S scale—which we propose captures perseverance alone—
with a measure that assesses passion attainment would predict
performance. Across a metaanalysis and two field studies, we
provide support for this prediction: only the combination of
perseverance and passion attainment predicted performance. In
addition, we find that this relationship occurs in part through
increased immersion. By adequately measuring both perseverance
and passion attainment, the current research uncovers grit’s
predictive power.
The explicit connection to the passion literature is important
because grit researchers have conceptually proposed that passion
is essential for perseverance to have a positive effect on performance
(5). The interactive effect of perseverance and passion
attainment provides evidence that perseverance only propels
employees forward when they experience desired levels of passion
(24). We further advance prior literature by uncovering one
underlying mechanism: the combination of high perseverance
and high passion attainment increases performance by promoting
the intensity of focus individuals’ experience (17, 19, 20).
Finally, the present studies also address prior calls to examine
the effects of grit outside of scholastic performance (8).
The present research has limitations that provide opportunities
for future research. The study designs were cross-sectional,
which omits the possibility of investigating potential long-term
effects of grit. In addition, the cross-sectional nature of our
studies does not allow us to address concerns about reverse
causality: it is possible that individuals who performed worse also
reported lower passion attainment, changing their attitudes as a
response to negative feedback regarding their competence (49).
This concern was addressed in study 2, where supervisor-rated
performance ratings—although collected immediately before the
survey—were only disclosed to employees after the survey data
collection was completed. Nonetheless, future research should
further investigate the causal nature of the interactive effect of
perseverance and passion attainment. Furthermore, the crosssectional
nature of studies 2 and 3 does not exclude the occurrence
of common method variance for the independent variables.
However, given that we studied the moderating effect of
passion attainment on the relationship between perseverance
and performance, the presence of common method variance
should have made it more difficult to find such effects (50–53).
Finally, future research may consider adapting the grit scale to a
particular performance domain to increase its predictive capacity
in that domain (e.g., work). The present grit scale currently
assesses perseverance more generally (6), but subsequent investigations
could explore the value of assessing more specific
perseverance.
Our findings suggest that perseverance without passion attainment
is mere drudgery, but perseverance with passion attainment
propels individuals forward. By incorporating passion
into the conceptualization and measurement of grit, future research
may find that grit actually lives up to its hype.
All studies were approved by the Columbia University Institutional
Review Board and all participants provided informed
consent.
Materials and Methods
Study 1. We conducted a metaanalysis of studies that used both the grit scale
and assessed performance. We hypothesized that in contexts where participants
would find the performance domain to be personally relevant, they
would experience greater passion. In these settings, we expected to find a
moderating effect on the relationship between perseverance and performance,
such that the relationship between perseverance and performance is
stronger when participants’ passion for the performance domain is higher.
Literature search. We began our search strategy began by reviewing all of the
studies included in the most recent meta-analysis of grit (8). We then
reviewed all subsequent citations of said metaanalysis using PsychINFO, Web
of Science, and Google Scholar online databases using the search term
Jachimowicz et al. PNAS | October 2, 2018 | vol. 115 | no. 40 | 9983
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“grit.” Additionally, we sent out a call for unpublished data to two academic
listservs, the Society for Personality and Social Psychology, and the Association
for Research in Personality. This search yielded a total of 253 datasets.
We then reviewed each paper based on the inclusion criteria to develop our
final sample (see below). The search was completed in May of 2018. The
metaanalysis data and code are available via the Open Science Framework
(https://osf.io/kp7cb/).
Criteria for inclusion and exclusion. Our primary metric of interest was the
Pearson correlation coefficient between the grit scale and a measure of
performance relevant to that study’s sample. If the Pearson correlation coefficient
was not reported directly but was available through other sources,
the study was included in our final sample. In cases where the Pearson’s r
coefficient was not reported, a t-statistic, or a %-coefficient for a regression
of grit on performance was recorded and converted into r. If the correlation
was not reported directly and was not available through other sources, we
contacted the first author of the paper with a request for the correlation
coefficient. Studies were not excluded based on the location of the sample
nor were any studies excluded based on publication information. We did not
exclude papers based on the age of the participants, although subsequent
analyses were done to examine variation by age and the differences did not
qualify our findings in a meaningful way. Studies were excluded when they
did not contain measures of performance, meaning that studies that only
measured characteristics such as retention, well-being, or satisfaction were
excluded. We also excluded studies that focused on negative behavioral
characteristics (e.g., suicide, gambling). Additionally, three papers were excluded
because they used duplicate datasets to studies included in the final
sample. After thorough review of the papers based on the above qualifications,
our final sample was determined with 127 studies, and a total of
45,485 participants (ns ranging from 21 to 4,800). All analyses were conducted
in R using the statistical packages metafor (v2.0), and MAc (v1.1).
Coding procedure. All papers were coded by two authors (J.M.J. and E.R.B.) and
all disagreements were resolved through internal discussion. The following
data were collected from each study: Pearson’s r correlation between the grit
scale and performance, the type of performance metric, sample size, if the
article was published in a peer-reviewed journal, the year of the study, and
the journal type (psychology, education, other). In addition, three independent
coders were instructed to code a binary variable indicating
whether or not the majority of participants in the study would deem the
performance domain to be personally important. The coders were blind to
the hypothesis of this paper and had a high degree of interrater reliability
(IRR = 0.81). Disagreements were discussed and resolved in subsequent
coding review sessions.
Study 2.
Participants and procedure. The study was conducted with employees of a
technology company located in a Spanish-speaking country. Employees work
in teams guided by a supervisor who also provides annual evaluations of
subordinates with an organizationally developed measure of job performance.
Employees were contacted by an email sent out by J.M.J, which
contained a link to the survey hosted on https://Qualtrics.com. Employees
were guaranteed that their responses would be kept entirely confidential,
and that their employer would not have access to any of their responses. The
email was sent out to all of the firm’s 2,293 employees, and 178 emails
bounced back. In addition to the employee survey data, the company’s
Human Resources team provided performance ratings for each employee,
which were conducted in the month before the survey was sent to
employees.
Before our data collection, we conducted an a priori power analysis using
conventional values for a small to medium effect size (f2 = 0.075, & = 0.05, % =
0.95; three variables) (45), as would be expected for typical interaction effects
in social science (ranging from 3 to 10%) (46, 47). Calculations reveal
that we would need a sample of 176 participants to be able to detect an
effect of our hypothesized two-way interaction.
We received partial survey data from 1,265 employees and could match
560 employee–supervisor dyads. After dropping dyads with missing data on
our focal variables, or where we were unable to identify the corresponding
supervisors, our final sample consisted of 422 employees (response rate:
33.5%). This subset of employees did not differ in age, gender, or tenure
from partial respondents (all Ps > 0.22). Our sample included 169 female
employees, ages ranged from 18 to 63 y (mean = 30.96 y, SD = 6.99), and
employees had been working in the organization for an average of 3.69 y
(SD = 2.88). Overall, 85 supervisors provided performance ratings with an
average of five subordinate ratings per supervisor (SD = 5.25).
Measures. Given the company’s location, we used the translation procedure
outlined by Schaffer and Riordan (54) to adapt our measures to Spanish.
Where not stated otherwise, the measures used a seven-point scale ranging
from “strongly disagree” to “strongly agree.”
Perseverance. To measure perseverance, we used the Short Grit Scale (Grit-
S) (6), which has improved psychometric properties over the full Grit Scale
(6), and consists of four items each for two different factors, “perseverance
of effort” and “consistency of interests.” Sample items are “I have overcome
setbacks to conquer an important challenge (perseverance of effort)” and “I
often set a goal but later choose to pursue a different one (reversed; consistency
of interest).” Following prior research (5, 6), we computed an average
score across both subcomponents, & = 0.73.
Passion attainment. We measured the extent to which employees feel they
attained their desired level of passion for their work with three previously
developed and used items (37, 45). These items read “I am less passionate
for my work than I should be,” “I often feel as if I have to be more passionate
for my work,” and “I frequently feel obliged to be more passionate
for my work than I currently am.” We reverse-scored the items,
such that higher levels corresponded to increased passion attainment,
& = 0.82.
Harmonious passion. To highlight that the results are driven by passion
attainment, we also assessed harmonious passion with Vallerand et al.’s (23)
harmonious passion scale (& = 0.90). Sample items include “My work is in
harmony with the other activities in my life” and “My work is well integrated
in my life.”
Job performance. We used the organization-wide measure to assess performance
which supervisors use for annual performance evaluation. This
measure was conducted and provided by the Human Resources department
of the company and covers different aspects of work that are important for
the organization. The performance measure varies on a scale of 1 (very poor
performance) to 5 (very good performance). Given the average job performance
score of 4.39 (SD = 0.52), we further evaluated the skewness and
kurtosis of the performance measure. Both skewness (−0.80) and kurtosis
(0.23) were acceptable (55).
Control variables. In our analyses, we also controlled for age, gender,
tenure, and motivation. Age was included because older people tend to
receive worse performance evaluations (56) and perseverance increases with
age (6). We controlled for gender because research cannot rule out whether
female employees receive worse performance ratings (57), and for organizational
tenure because it has been shown to be related to job performance
(58). Finally, to distinguish our effects of the interaction between perseverance
and passion attainment from motivation (31), and to provide a more
rigorous test of our hypothesis, we also controlled for prosocial (& = 0.85),
intrinsic (& = 0.88), and extrinsic (& = 0.83) motivation using measures from
Grant (59). We included all control variables in subsequent steps after first
testing our predicted interaction effect separately following recommendations
by Becker (60) and Becker et al. (61) to avoid spurious results in our
hypothesis tests.
Study 3.
Participants and procedure. The study was conducted with students at a private
northeastern university. Participants were contacted by an email sent out by
the university laboratory’s recruitment mailing list, which contained a link to
the survey hosted on https://Qualtrics.com. Participants were guaranteed
that their responses would be kept entirely confidential.
Before our data collection, we conducted an a priori power analysis using
conventional values for a small to medium effect size (f2 = 0.075, & = 0.05, % =
0.95; three variables) (45), as would be expected for typical interaction effects
in social science (ranging from 3 to 10%) (46, 47). Calculations reveal
that we would need a sample of 176 participants to be able to detect an
effect of our hypothesized two-way interaction. We succeeded in obtaining
responses from 248 participants (mean age: 21.66 y, 70.56% female).
Measures. Where not stated otherwise, the measures used a seven-point scale
ranging from “strongly disagree” to “strongly agree.”
Perseverance. We measured perseverance using the same eight-item
measure as above (& = 0.73).
Passion attainment. We measured passion attainment using the same threeitem
measure as above. Same as before, we reverse-scored the items, such
that higher levels corresponded to increased passion attainment, & = 0.88.
Performance. Participants were asked to report their major GPA. For verification
purposes, we also asked students to upload their grade transcript to
the online survey. Past literature has often relied on GPA as a measure of
performance, because of its consistency across a large sample and its impact
on graduation, honors, and job-seeking (see, for example, refs. 5 and 30).
Major GPAs ranged from 2.1 (equivalent to a C average) to 4.33 (equivalent
to an A+ average). Given the average major GPA of 3.52 (SD = 0.47), we
9984 | www.pnas.org/cgi/doi/10.1073/pnas.1803561115 Jachimowicz et al.
This content downloaded from
163.238.8.158 on Mon, 26 Apr 2021 05:38:59 UTC
All use subject to https://about.jstor.org/terms
further evaluated both the skewness (−0.94) and kurtosis (0.29), which were
acceptable (55).
Control variables. Finally, we measured participants’ age and gender,
their year of study, and major.
ACKNOWLEDGMENTS. We thank Angela Duckworth, Kristen Duke, Lauren
Eskreis-Winkler, Andrea Freund, Sandra Matz, Evan Nesterak, Christopher
To, Aurora Turek, and Kristina Wald for critical feedback, which substantially
improved this paper.
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