Energy in the workplace: job demands, job resources, and employees’ inner resources as pathways to organizational outcomes

Abstract

In this study, we expanded upon the job demands–resources model to assess the role of employees’ vitality as an inner resource for their work engagement and job commitment. To assess vitality and related job resources, we developed an index of vitality outside of work and adapted measures of manager autonomy support and organizational support. For job demands, we measured work stress and predicted that each of these four variables would contribute independently to work-related outcomes. Then, in a preregistered study, we collected these measures from a sample of 5,280 American workers (primarily ages 18–34, 54% female). Results from multivariate regression analyses largely confirmed our hypotheses, showing that positive work-related outcomes, such as enthusiasm, enjoyment, and job satisfaction, were positively predicted by manager autonomy supports, organizational support, and individuals’ vitality, and negatively predicted by work stress. The reverse pattern was largely observed for the negative outcome of turnover intention. Exploratory analyses also suggested that individual vitality may buffer the negative effects of stress and low manager and organizational support. The results highlight the potential role of employee vitality outside of work and managerial support in bolstering work engagement and reducing turnover intentions, offering a basis for organizational strategies aimed at improving work culture and retaining talent.

Full text

Frontiers in Psychology 01 frontiersin.org
Energy in the workplace: job
demands, job resources, and
employees’ inner resources as
pathways to organizational
outcomes
CodyR.DeHaan 1, EmmaL.Bradshaw 2,
SandraDiaz-Castillo 3, ToddC.Trautman 3, C.ScottRigby
1
and RichardM.Ryan 1,2,4*
1 Immersyve, Inc., Dallas, TX, United States, 2 Institute for Positive Psychology and Education, Australian
Catholic University, North Sydney, NSW, Australia, 3 Evernorth Research Institute, St. Louis, MO, United
States, 4 Department of Education, Ewha Womans University, Seoul, Republic of Korea
In this study, weexpanded upon the job demands–resources model to assess
the role of employees’ vitality as an inner resource for their work engagement
and job commitment. To assess vitality and related job resources, wedeveloped
an index of vitality outside of work and adapted measures of manager autonomy
support and organizational support. For job demands, wemeasured work stress
and predicted that each of these four variables would contribute independently
to work-related outcomes. Then, in a preregistered study, wecollected these
measures from a sample of 5,280 American workers (primarily ages 18–34, 54%
female). Results from multivariate regression analyses largely confirmed our
hypotheses, showing that positive work-related outcomes, such as enthusiasm,
enjoyment, and job satisfaction, were positively predicted by manager autonomy
supports, organizational support, and individuals’ vitality, and negatively predicted
by work stress. The reverse pattern was largely observed for the negative outcome
of turnover intention. Exploratory analyses also suggested that individual vitality
may buer the negative eects of stress and low manager and organizational
support. The results highlight the potential role of employee vitality outside of work
and managerial support in bolstering work engagement and reducing turnover
intentions, oering a basis for organizational strategies aimed at improving work
culture and retaining talent.
KEYWORDS
wellbeing, need support, self-determination theory, job demands-resources, Work
Introduction
e energy employees have for engaging positively in their work is a growing area of
study (Bakker and Albrecht, 2018). In particular, the job demands–resources (JD-R; Bakker
and Demerouti, 2014) model has supplied a general framework for researching and
understanding engagement and burnout in the workplace. e model species that certain
job characteristics (i.e., “demands”) undermine sta engagement and retention (e.g.,
pressure and stress), while other characteristics (i.e., “resources,” like support and feedback)
enhance work engagement and job commitment. Applying the JD-R model from the
perspective of self-determination theory (SDT; Ryan and Deci, 2017) brings a focus to a
specic set of contextual resources, including manager autonomy support and organizational
OPEN ACCESS
EDITED BY
Martin Mabunda Baluku,
Makerere University, Uganda
REVIEWED BY
Sebastiaan Rothmann,
Optentia Research Unit, SouthAfrica
Prashant Mahajan,
R. C. Patel Institute of Technology, India
*CORRESPONDENCE
Richard M. Ryan
richard.ryan@acu.edu.au
RECEIVED 08 April 2024
ACCEPTED 01 October 2024
PUBLISHED
CITATION
DeHaan CR, Bradshaw EL, Diaz-Castillo S,
Trautman TC, Rigby CS and Ryan RM (2024)
Energy in the workplace: job demands, job
resources, and employees’ inner resources as
pathways to organizational outcomes.
Front. Psychol. 15:1413901.
doi: 10.3389/fpsyg.2024.1413901
COPYRIGHT
© 2024 DeHaan, Bradshaw, Diaz-Castillo,
Trautman, Rigby and Ryan. This is an
open-access article distributed under the
terms of the Creative Commons Attribution
License (CC BY). The use, distribution or
reproduction in other forums is permitted,
provided the original author(s) and the
copyright owner(s) are credited and that the
original publication in this journal is cited, in
accordance with accepted academic
practice. No use, distribution or reproduction
is permitted which does not comply with
these terms.
TYPE Original Research
PUBLISHED
DOI 10.3389/fpsyg.2024.1413901
06 November 2024
06 November 2024

DeHaan et al. 10.3389/fpsyg.2024.1413901
Frontiers in Psychology 02 frontiersin.org
support, as well as particular demands, like workplace pressure and
stress. Also relevant to workplace thriving, however, may bethe
degree of intrapsychic energy from non-work sources that one brings
to the workplace. Individual dierences in people’s general vitality,
condence, and agency may present an inner resource pathway to
optimal work outcomes. We tested these four resources and
demands in relation to indicators of work engagement and job
commitment to show each other’s unique contributions in order to
further inform the multivariate nature of complex systems like
the workplace.
Job demand and resources
e JD-R model attempts to explain both the wellbeing and
ill-health of employees via the dual pathways of job resources and job
demands (Bakker and Demerouti, 2007; Xanthopoulou etal., 2007).
Job resources are dened as the physical, psychological, social, or
organizational aspects of the work context that (1) can reduce the
depleting impact of job demands, (2) help employees achieve work
goals, and/or (3) stimulate personal growth, learning, and
development (Schaufeli and Bakker, 2004). Job resources are thus also
expected to relate positively to wellbeing. e JD-R model specically
argues that job resources (e.g., managerial supports or opportunities
for career development) are drivers of work engagement (Bakker and
Demerouti, 2007, 2014) and varied positive organizational outcomes
and key performance indicators (KPIs; Bakker etal., 2011). Indeed,
evidence suggests that job resources such as job control, participation
in decision-making, and task variety, have a positive impact on work
engagement (e.g., Korunka et al., 2009; Kühnel etal., 2012) and,
oppositely, a negative eect on burnout (e.g., Bakker etal., 2003;
Schaufeli and Bakker, 2004).
Job demands refer to aspects of a job that require sustained
physical and/or psychological eort and are therefore associated with
physiological and/or psychological costs (Bakker and Demerouti,
2017). Demands are oen represented in terms of workload, time
pressures, and attentional demands that can beenergy-depleting. In
contrast to the positive eects of job resources, excessive job demands
can lead to physical and psychological impairment and lower quality
work motivation (Van Yperen etal., 2016).
Job demands–resources and
self-determination theory
SDT (Ryan and Deci, 2000, 2017) has identied three basic
psychological needs that, when satised, enable human wellbeing and
ourishing. Specically, SDT argues that when employees experience
autonomy (i.e., agency and volition), competence (i.e., ability and
capacity), and relatedness (i.e., closeness with others) in their work,
they perform at their best. Job resources that enhance these basic
needs can help buer or protect employees from depletion and
burnout (e.g., Alarcon, 2011; Bakker etal., 2005) and enhance work
engagement (e.g., Schaufeli etal., 2009), in part, because having access
to such resources allows employees to satisfy their needs and increases
their willingness to dedicate eorts and abilities to the work task
(Bakker and Demerouti, 2007). In contrast, excessive job demands can
lead to the frustration of basic psychological needs, as employees can
feel controlled or less competent in such circumstances, potentially
diminishing job satisfaction, enthusiasm, and engagement.
Exploring this interface between SDT and JD-R, Trépanier etal.
(2015) found that job demands predicted high distress and
psychosomatic complaints, low work engagement, and lower
performance among employees. ese outcomes were, as predicted,
mediated by SDT’s basic need frustrations and by employees’
controlled (i.e., non-autonomous) motivation. In contrast, job
resources positively predicted basic psychological need satisfaction
and fostered more autonomous and less controlled employee
motivation and functioning. e JD-R model also species that
demands and resources can have joint eects on outcomes, such that
the costs associated with some work demands can bebalanced via the
provision of various job-specic resources. SDT-based research has
supported this claim from the JD-R model, showing that employees’
basic psychological need satisfaction can buer the eects of both job
demands and low resources on employee wellbeing (see Fernet etal.,
2012a; Fernet etal., 2012b; Trépanier etal., 2013).
Manager autonomy support
SDT has a long history of motivational research in organizations,
showing that basic psychological need satisfaction in one’s work
climate enhances autonomous motivation (Baard etal., 2004; Mageau
and Vallerand, 2003; Vansteenkiste etal., 2004). Among the main
facilitators of such need satisfaction is manager autonomy support. In
work settings, the interpersonal context is considered autonomy-
supportive when managers provide a meaningful rationale for doing
the tasks, emphasize choice rather than control, and acknowledge
employees’ feelings and perspectives (Deci etal., 1989; Ryan and Deci,
2017). ese behaviors are thought to foster an environment in which
people are more likely to perceive their work as meaningful and
personally relevant, making the workplace more worth investing in
over the longer term. Indeed, past research has shown that autonomy-
supportive managers foster greater autonomous motivation in their
employees, which, in turn, predicts more positive work outcomes (e.g.,
Deci etal., 2001; Gagné etal., 2000). For instance, Hardré and Reeve
(2009) showed, through an intervention-based experimental design,
that when managers displayed an autonomy-supportive managerial
style, employees were more autonomously motivated and engaged in
work more than employees supervised by control-group managers. In
a study of public sector employees, Kuvaas (2009) found that
autonomy support positively predicted autonomous motivation,
which was, in turn, related to better work performance. Recent meta-
analyses have further supported these patterns of association (see
Slemp etal., 2018; Van den Broeck etal., 2021).
Organizational support
A second source of support, a more distal one, comes from one’s
general relationship with their employer or organization. Perceived
organizational support is the degree to which employees believe that their
organization values their contributions and cares about their wellbeing
(Eisenberger etal., 1986; Eder and Eisenberger, 2008). ough the study
of perceived organizational support has received considerable attention
in the literature (see Rhoades and Eisenberger, 2002), fewer studies have
looked at the role of perceived organizational support in the prediction of
workers’ motivation, according to SDT. However, using samples from
French industries, Gillet etal. (2013) found that perceived organizational
support was associated with both more autonomous and more controlled

DeHaan et al. 10.3389/fpsyg.2024.1413901
Frontiers in Psychology 03 frontiersin.org
work motivation, whereas supervisor autonomy support predicted only
autonomous work motivation, which was, in turn, associated with lower
turnover intention.
Workplace pressure and stress
In contrast to resources and supports that bolster experiences of
need satisfaction and thus enhance work motivation and outcomes,
the demands of work pressure and stress can detract from need
satisfaction, and perhaps even actively frustrate those needs, leading
to more detrimental outcomes. For example, Desrumaux etal. (2015)
demonstrated a negative link between job demands and relatedness
satisfaction, though they did not nd a signicant link for autonomy
or competence. Job demands, conceptualized as task changes and
ambiguity, were demonstrated to relate negatively to psychological
need satisfaction in one study and positively to need satisfaction in
another (Gillet etal., 2015).
Inner resources in the workplace: vitality,
confidence, and agency outside of work
Although SDT research oen highlights the environmental factors
that impact motivation and psychological functioning, within SDT, it
has also long been argued that individual dierences inuence how
people perceive or react to their environment (Deci and Ryan, 1985).
Alongside environmental factors, dierences in motivational
orientation, goals, resilience, and energy might well inuence how
employees adapt to job stressors and respond to the resultant strains
and aordances of work life (see Frederick and Ryan, 2023; Ryan and
Frederick, 1997). In the present research, weextend previous research
combining the JD-R model and SDT, by assessing the individual
dierences in vitality, condence, and agency that employees may
possess outside of the workplace. Werefer to this as an inner resource
pathway to optimal organizational outcomes.
We dene inner resources in the workplace context as attributes
that individuals bring with them into the workplace, impacting their
ability to handle various job demands. e index used here
encompasses feelings of energy available to the self and feelings of
autonomy and competence across various spheres of life, including
social, emotional, intellectual, physical, environmental, occupational,
and nancial domains. In covering a wide variety of life domains,
we aim to be comprehensive in capturing an individual’s overall
available energy. Weexpected that these cross-domain perceptions of
energy and agency would represent a robust set of inner resources
concerning enthusiasm and engagement outside of work that, in turn,
might inuence job engagement beyond what organizational and
managerial supports might aord.
We distinguish inner resources from a variety of outcomes, such as
job satisfaction and enjoyment, as theoretical subjective experiences
across a variety of life domains that would precede and potentially
inuence outcomes at work. In other words, we expect that work
outcomes are specic to the workplace context and arise from the
interplay of inner resources and the workplace environment. By focusing
on these inner resources, weaim to demonstrate their ability to bolster
workplace outcomes beyond the eect of day-to-day workplace factors.
e present research team was commissioned by Evernorth, with
the aim of understanding the relation of job demands, job resources,
and inner resources to people’s health and wellness. To this end,
weemployed the short form version of the Evernorth Vitality Index
(EVI), referred to as the EVI-S, which assesses the domains described
above. Details of the development of this scale are described in the
Online Supplementary Materials S1, as the development of this scale
is not the primary focus of this study. Before applying the new
assessment in a formal and preregistered study, werst conducted an
exploratory study to assess its strengths and characteristics.
The current research
Across two studies—an exploratory study and a preregistered
study—we built toward our aim to test the combined JD-R and SDT
model in which job and inner resources (as operationalized by
manager autonomy support, organizational support, and vitality)
alongside demands (operationalized as workplace pressure and stress)
are tested simultaneously in relation to work engagement and job
commitment. Weconducted two studies as an initial foray into these
relations. In the rst, the exploratory study, we developed the
composites and tested the models. In the second, the preregistered
study, wetested the full preregistered models. Our hypotheses for the
second, preregistered study, as outlined in Figure1, were as follows:
Hypothesis 1: Manager autonomy support will relate positively to
work enjoyment, job satisfaction, extra mile, work enthusiasm, and
work ecacy, and negatively to turnover intention, even when
controlling for the other demands and resources in the model.
Hypothesis 2: Organizational support will positively relate to work
enjoyment, job satisfaction, extra mile, work enthusiasm, and work
ecacy, and negatively to turnover intention, even when controlling
for the other demands and resources in the model.
Hypothesis 3: Workplace pressure and stress will negatively relate to
work enjoyment, job satisfaction, extra mile, work enthusiasm, and
work ecacy, and positively to turnover intention, even when
controlling for the other demands and resources in the model.
Hypothesis 4: Inner resources, as measured by the EVI-S, will relate
positively to work enjoyment, job satisfaction, extra mile, work
enthusiasm, and work ecacy, and negatively to turnover intention,
even when controlling for the other demands and resources in
the model.
The exploratory study
Method
Participants and procedure
e data for this preliminary study were collected by Morning
Consult using a nationally representative sample in which 10,001
complete responses were collected, with the expectation that this
sample would bea relatively diverse and comprehensive demographic
broadly representative of the backgrounds and working conditions
that would generalize to other developed economies (Table 1). In this
sample, 57.5% (n= 5,755) were employed, and all analyses on the
sample were limited to this subgroup. Of these, the 45–64 age group
was the largest (37%), and most held a high school degree or greater.
In addition, a wide variety of income brackets were represented, with

DeHaan et al. 10.3389/fpsyg.2024.1413901
Frontiers in Psychology 04 frontiersin.org
most participants reporting a household income of $50,000–$74,999
(16%). Participants self-reported their gender (male, female, or prefer
not to say), with responses summarized in Table1.
Materials
Our study materials were a subset of those used for a larger study,
which were intended for separate studies. ose variables were not
used here, so they are not discussed further. As this study included a
broad range of constructs, this study employed mostly face-valid,
short measures.
Manager autonomy support
Manager autonomy support is the experience of managers
providing a meaningful rationale, acknowledging employees’
perspectives, and encouraging questions. is job resource was
assessed using ve items on a 7-point scale (1 =strongly disagree to
7 =strongly agree), including items such as “I feel understood by my
manager” and “My manager encourages me to ask questions.”
Reliabilities were good (Cronbach’s α= 0.93), with all item loadings
0.83–0.86.
Organizational support
Organizational support is the perception that an organization
values employees’ contributions and cares about their growth and
wellbeing. Perceived organizational support, another job resource,
was assessed using ve items. ree of these items, such as “I
am ____ with my chances for advancement on the job” were
assessed on a 4-point satisfaction scale (1 =very satised to 4 =not
at all satised; reversed for the composite). e remaining two
items, such as “I amkept informed about what is going on in the
company,” were assessed on a 4-point agreement scale (1 =strongly
agree to 4=strongly disagree; also reversed for the composite). e
composite showed good reliabilities (Cronbach’s α= 0.82), with all
items loading 0.66–0.74.
Workplace pressure and stress
Workplace pressure and stress are the experience of unreasonable
deadlines, stress related to the job, and other negative experiences at
the workplace. e job demand of workplace pressure and stress was
assessed using three items on a 5-point frequency scale (1 =never to
5 =very oen), including items such as “I have too many unreasonable
deadlines” and “How oen do yound your work stressful?.” e
composite showed good reliabilities (Cronbach’s α= 0.73), with all
items loading on a single factor at 0.56–0.81.
Inner resources
Inner resources are those resources individuals bring with
them into the workplace, including energy, autonomy, and
competence across various spheres of life. The short form version
of the Evernorth Vitality Index (the EVI-S), as discussed in
Online Supplementary Materials S1, was assessed using a 7-point
scale (1 =not at all true to 7 =very true). Participants were given
the instructions “Please read each statement carefully and
indicate the degree to which each statement is true for youin
general,” and items include “I feel alive and vital,” “I have all the
skills and tools necessary to live a healthy life,” and “I feel capable
of managing my emotions.” The index demonstrated good
reliability (Cronbach’s α= 0.89), with item loadings on a single
factor at 0.53–0.73.
Work enjoyment
e work enjoyment outcome was measured with a single item, “I
value and enjoy my work,” on a 7-point scale (1 = not at all true to
7 =very true). For discrete variables, single-item measures are being
increasingly considered useful due to the low participant burden they
pose and their high correlations with their multi-item versions
(Matthews etal., 2022).
Job satisfaction
e job satisfaction outcome was assessed with a single item,
“Overall, Iam____ with my job,” on a 4-point scale (1 =very satised
to 4 =not at all satised, reversed for interpretation).
Results
All analyses were conducted in R version 4.3.1 (R Core Team,
2019), using packages including dplyr (1.1.2), psych (2.3.6),
FIGURE1
An overview of regression models in preliminary and preregistered studies.

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Frontiers in Psychology 05 frontiersin.org
scipub (1.2.2), QuantPsyc (1.6), and FactoMineR (2.8).
Correlations were calculated for all variables, as shown in Table2.
The outcomes were each analyzed using multivariate regression,
in which all predictors (i.e., manager autonomy support,
organizational support, inner resources, and work stress) were
entered simultaneously. In addition, Funder and Ozer (2019)
reviewed the psychological literature and suggested the
benchmarks of r= 0.05, 0.10, 0.20, and 0.30 as indicative of very
small, small, medium, and large effect sizes, respectively. Weuse
these benchmarks in our discussion.
Intercorrelations
The correlations between the variables are displayed in
Table 2. The pattern of correlations largely conformed to our
expectations. Inner resources were broadly positively associated
with outcomes, as were manager autonomy support and
organizational support. Furthermore, workplace stress was
negatively associated with inner resources, as well as job
satisfaction and work–life balance.
Gender eects
While wedid not hypothesize any dierences in the main
study variables by gender, there were dierences in all variables
(see Table3). ese eects indicated that males, relative to females,
experienced greater manager need support, organizational
support, and inner resources, as well as greater workplace stress.
In addition, males reported greater work enjoyment and
job satisfaction.
Regressions
Work enjoyment
As shown in Table4, all four predictors (three job resources and
one job demand) were statistically signicantly associated with work
enjoyment, with manager autonomy support (β = 0.14, p < 0.001),
organizational support (β = 0.16, p < 0.001), and inner resources
(β = 0.45, p < 0.001) all positively predicting work enjoyment, and
workplace stress (β = −0.03, p < 0.01) exhibiting a small negative
relation to work enjoyment. e overall R
2
for the model, with all four
variables predicting work enjoyment, was 0.40.
Job satisfaction
All predictors were statistically signicant in their associations
with job satisfaction, with manager autonomy support (β = 0.09,
p< 0.001), organizational support (β= 0.57, p < 0.001), and inner
resources (β= 0.09 p< 0.001) all positively predicting work enjoyment,
and workplace stress (β= −0.09, p< 0.001) negatively predicting job
satisfaction. e overall R
2
for the model, with all four variables
predicting job satisfaction, was 0.50.
Discussion
Manager autonomy support, organizational support, workplace
stress, and inner resources all proved robust in explaining variance in
work enjoyment, job satisfaction, and workplace stress consistent with
our expectations. is suggests that the chosen independent variables
are important to study outcomes, encouraging us to preregister and
test with a broader array of outcomes. In addition, without
overinterpreting the relative magnitude of coecients, inner resources
appeared to beparticularly important for work enjoyment, whereas
organizational support appeared to bethe strongest predictor of job
satisfaction. Wethus felt condent in designing and preregistering a
study testing the contribution of vitality alongside other job demands
and resources in predicting an array of work outcomes, including
willingness to go above and beyond requirements, enthusiasm for
work, and turnover intention. is will serve as an extension of the
outcomes associated with these independent variables and lend
further support to the patterns revealed in the exploratory study.
TABLE1 Demographics for the exploratory and preregistered studies.
Exploratory
study
Preregistered
study
Responses 5,755 5,280
Age
18–34 1,859 (32%) 2,188 (41%)
35–44 1,403 (24%) 1,100 (21%)
45–64 2,107 (37%) 1,772 (34%)
65+ 386 (7%) 220 (4%)
Gender
Male 2,875 (50%) 2,418 (46%)
Female 2,848 (50%) 2,840 (54%)
Prefer not to say — 22 (<1%)
Employed 5,755 (100%) 5,280 (100%)
Household income
<$25,000 559 (10%) 673 (13%)
$25,000–$34,999 581 (10%) 692 (13%)
$35,000–$49,999 632 (11%) 827 (16%)
$50,000–$74,999 915 (16%) 1,037 (20%)
$75,000–$99,999 885 (15%) 758 (14%)
$100,000–$124,999 660 (11%) 418 (8%)
$125,000–$149,999 606 (11%) 361 (7%)
$150,000–$199,999 445 (8%) 278 (5%)
>$200,000 315 (5%) 144 (3%)
Prefer Not to Answer 157 (3%) 92 (2%)
Education
No Schooling 19 (<1%) 6 (<1%)
8th Grade or Less 29 (1%) 13 (<1%)
Some High School, Did Not
Graduate
124 (2%) 127 (2%)
High School/GED 957 (17%) 1,186 (22%)
Trade School/Vocational School
Graduate
231 (4%) 275 (5%)
Some College or University Study 869 (15%) 920 (17%)
Associate’s Degree 581 (10%) 638 (12%)
Bachelor’s Degree 1,664 (29%) 1,339 (25%)
Master’s Degree 1,060 (18%) 651 (12%)
Doctorate Degree 221 (4%) 125 (2%)

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The preregistered study
Method
Participants and procedure
Participants
A total of 10,000 responses were collected. Of the total sample,
5,280 were employed; further analyses were conducted only using this
subsample. Participants were collected in a similar manner to the
preliminary study. Most participants were from the 18–34 age group
(41%), and most participants had a high school degree or greater.
Participants self-reported their gender (male, female, or prefer not to
say), with results summarized in Table1.
Recruitment
Study participants were recruited by Morning Consult on behalf
of Cigna Group and its subsidiaries, including Evernorth Research
Institute. For the online survey, 10,000 adults ages 18 and over from
the continental UnitedStates., Alaska, and Hawaii were interviewed
online in English or Spanish between May and June, 2022. Recruitment
was conducted among registered Dynata and Marketing Survey panel
members using stratied sampling. To beeligible for participation,
respondents had to be a member residing in the United States,
be18 years of age or older, voluntarily consent to participation, and
beuent in either English or Spanish.
To ensure that the sample was representative of the
UnitedStates’ population, quotas were established based on Census
Data using a cross-section of age and gender, with employment
quotas based on Bureau of Labor Statistics data. To adjust for bias
in respondent characteristics and contribute to representativeness,
the sample was calibrated to the US population based on the US
Census American Community Survey benchmarks on the known
composition of the US adult population’s distribution by region,
race, ethnicity, age, and gender and employment status. e survey
had a margin of error of ±1% for the full 10,000 respondent sample.
To further ensure sample quality and eliminate human bias,
respondent quality measures were applied during the interviews.
Quality checks included bot checks, timing tests, and open-ended
questions, and to avoid missing data or implausible values,
responses were required to questions.
Consent
Consent was obtained from each respondent via a “double opt-in”
process. e panel was composed of individuals who opted to
participate in surveys in exchange for an incentive payment.
Individuals were contacted via email to participate in this specic
survey. Participants rst accepted the terms and conditions of
participation, including detailed information on what data are
collected and shared with research partners and how respondent data
may be used. Once the recruitment questionnaire is completed,
panelists receive an email and are required to click on the link from
the email to conrm they would like to participate in panel
membership (constituting the second “opt-in”).
Compensation
Compensation was oered for each participant. e form of
compensation oered varied across respondents, given that the study
leveraged several dierent sourcing mechanisms, each with its own
approach to compensation. Fair market value compensation is given to
all survey respondents. Compensation may have taken the form of cash,
gi cards, and rewards points, among others. As a quality improvement
initiative, the study did not constitute human subjects research in
accordance with the Oce of Human Research Protections guidance
on Health and Human Services regulations at 45 CFR 46.102(d). All
activities were conducted in accordance with the Marketing Research
and Intelligence Association, Marketing Research Association, and
Council of American Survey Research Organizations standards for
North America, European Society for Opinion and Market Research
(ESOMAR) and in compliance with the International Chamber of
Commerce Code of Conduct on Market, Opinion, and Social Research
and Data Analytics. is study was preregistered with the Open Science
Framework at https://osf.io/48vs9/?view_only=8455c51d242b445a931
252df8b760de5.
Materials
Our study materials were again a subset of those used for a larger
study and intended for separate and unrelated analyses.
Manager autonomy support
e same measure was used as in the exploratory study, with an
additional item included (for a total of six items) on a 7-point scale
(1 = strongly disagree to 7 = strongly agree). e additional item, “My
TABLE2 Exploratory study correlations, means, and standard deviations.
1 2 3 4 5 6
1. Inner resources -
2. MAS 0.30*** -
3. Workplace stress −0.08*** −0.18*** -
4. Org. support 0.34*** 0.58*** −0.20*** -
5. Work enjoyment 0.59*** 0.43*** −0.14*** 0.45*** -
6. Job satisfaction 0.41*** 0.49*** −0.24*** 0.69*** 0.48*** -
7. Work–life balance 0.43*** 0.58*** −0.17*** 0.48*** 0.40*** 0.43***
Mean 5.04 4.93 2.70 3.06 5.29 3.31
SD 1.12 1.08 0.68 0.51 1.53 0.74
*p < 0.05, **p < 0.01, ***p < 0.001. MAS, manager autonomy support; Org. support, organizational support; SD, standard deviation.

DeHaan et al. 10.3389/fpsyg.2024.1413901
Frontiers in Psychology 07 frontiersin.org
manager conveys condence in my ability to do well at my job,”
balanced the item set used in the exploratory study such that there
were a matched number of positively and negatively worded items.
Reliabilities were good (Cronbach’s α = 0.92), with all item loadings
0.75–0.84.
Organizational support
Perceived organizational support was assessed using four items.
One of these items, “I am____ with my chances for advancement on
the job,” was assessed on a 5-point satisfaction scale (1 =not at all
satised to 5 =very satised). An additional item, “I amkept informed
about what is going on in the company,” was assessed on a 5-point
agreement scale (1 = strongly disagree to 5 = strongly agree; also
reversed for the composite). An additional item, “I work in an
environment that is supportive of my family and personal
commitments,” was assessed on a 7-point agreement scale (1 =strongly
disagree to 7 =strongly agree). e nal item, “I receive appropriate
recognition for good performance,” was assessed on a 5-point
frequency scale (1 =never to 5 =very oen). All items were rescaled
on a 7-point scale before combining. e composite showed acceptable
reliabilities (Cronbach’s α= 0.73), with all items loading 0.60–0.70.
Workplace pressure and stress
e workplace stress composite was assessed using four items on
a 5-point frequency scale (1 =never to 5 =very oen), including items
such as “I have too many unreasonable deadlines” and “How oen do
yound your work stressful?.” e composite showed good reliabilities
(Cronbach’s α = 0.73), with all items loading on a single factor at
0.42–0.73.
Inner Resources
Inner resources, as in the exploratory study, were assessed using
the 10-item EVI-S on a 7-point scale (1 =not at all true to 7 =very
true). e items used assessed general life vitality, as well as items
assessing physical, social, intellectual, emotional, nancial, and
environmental agency. e index demonstrated good reliability
(Cronbach’s α= 0.89) and item loadings on a single factor at 0.51–0.77.
Work enjoyment
Work enjoyment was measured with a single item, “I value and
enjoy my work” on a 7-point scale (1 =not at all true to 7 =very true).
Job satisfaction
Job satisfaction was assessed with a single item, “Overall, Iam____
with my job” on a 5-point scale (1 =not at all satised to 5 =very satised).
Extra mile
Willingness to go the extra mile was assessed with a single item,
“I amwilling to work harder than Ihave to in order to help my
workplace succeed” on a 5-point agreement scale (1 =strongly agree to
5 =strongly disagree, reversed for interpretation).
Work enthusiasm
Work enthusiasm was assessed using a single item, “I
amenthusiastic about my job” on a 5-point scale (1 =strongly agree to
5 =strongly disagree, reversed for interpretation).
Work ecacy
Work ecacy was assessed using a single item, “How would
yourate your ability to carry out your duties at work in the past
month, using a scale from 1 to 7 where 7 means youwere able to carry
out your duties extremely well, and 1 means youwere not able to carry
out your work duties well at all?” Responses were on a 7-point scale
(1 =not well at all to 7 =extremely well).
Turnover intention
Turnover intention was assessed using a single item, “Taking
everything into consideration, how likely is it youwill make a genuine
eort to nd a new job with another employer within the next year?”
Responses were on a 7-point scale (1 =very likely to 5 =very unlikely).
Common method variance
As this study relied fully on self-report data, common method
variance can bea concern. Common method variance is attributable to
the method of measurement as opposed to the actual constructs of
interest (Podsako etal., 2003). It can change the nature of relations
among variables, leading to biased results. We employed Harman’s
(1976) one-factor test to check for common method variance in the
preregistered study, with an unrotated factor analysis indicating that the
single-factor solution accounted for approximately 30% of the variance,
below the recommended 50% threshold (Podsako and Organ, 1986).
is provides reassurance that common method variance is not a
critical issue here, although it is nonetheless a limitation of this work.
Results
Intercorrelations
Correlations were calculated for all variables and outcomes, as
shown in Table 5. e intercorrelations were as expected and in
similar patterns to those described in the exploratory study. e
outcomes were each analyzed using a multivariate regression in which
TABLE3 Exploratory study variable dierences by gender.
Variable Fdf pMean
(Males)
Mean
(Females)
Inner resources 118.0 1 <0.001 5.32 5.02
MAS 52.7 1 <0.001 5.02 4.75
Org. support 119.0 1 <0.001 3.20 3.01
Workplace stress 6.90 1 <0.01 2.76 2.70
Work enjoyment 21.3 1 <0.001 5.39 5.21
Job satisfaction 80.6 1 <0.001 3.40 3.23
MAS, manager autonomy support; Org. support, organizational support.
TABLE4 Exploratory study regressions with standardized coecients.
Work enjoyment Job satisfaction
Manager autonomy
support 0.14*** 0.09***
Organizational support 0.16*** 0.57***
Workplace stress −0.03** −0.09***
inner resources 0.45*** 0.09***
Overall R20.40 0.50
*p < 0.05, **p < 0.01, ***p < 0.001.

DeHaan et al. 10.3389/fpsyg.2024.1413901
Frontiers in Psychology 08 frontiersin.org
all predictors (i.e., manager autonomy support, organizational
support, inner resources, and work stress) were entered simultaneously.
Results are summarized in Table6.
Age eects
ere were age group dierences on several study variables, as
shown in Table7. In general, the youngest age group (18–34) had the
lowest availability of inner resources, experienced the lowest
organizational support, and broadly reported low work enjoyment,
enthusiasm, and ecacy. ey were also the most likely to look for
another job. In contrast, those 65+ had the greatest inner resources,
experienced the highest organizational support, and broadly enjoyed
their work. Notably, the 45–64 group reported similarly low levels of
organizational support and work enjoyment to the 18–34 group.
Gender eects
ere were also gender dierences in several study variables, as
shown in Table8. ese eects largely replicated those reported in the
preliminary study. Males, relative to females, reported greater inner
resources; the manager needs support and organizational support.
However, in contrast to the preliminary study, males reported lower
work stress. Males also reported higher on all outcomes, except for
work ecacy, for which there were no gender dierences.
Preregistered analyses
Work Enjoyment
Manager autonomy support (β= 0.09, p< 0.001), organizational
support (β= 0.18, p< 0.001), and inner resources (β= 0.47, p< 0.001)
were all statistically signicant, positive predictors of work enjoyment.
Workplace pressure and stress were not related to work enjoyment
(β= −0.01, p = 0.364). e overall R
2
for the model, with all four
variables predicting work enjoyment, was 0.40.
Job satisfaction
Manager autonomy support (β= 0.08, p< 0.001), organizational
support (β= 0.49, p< 0.001), and inner resources (β= 0.14 p< 0.001)
all statistically signicantly, positively predicted job satisfaction, and
workplace pressure and stress (β = −0.12, p < 0.001) negatively
predicted job satisfaction. e overall R2 for the model, with all four
variables predicting job satisfaction, was 0.41.
Extra mile
Manager autonomy support (β= 0.13, p< 0.001), organizational
support (β= 0.22, p< 0.001), and inner resources (β= 0.14 p< 0.001)
all statistically signicantly, positively predicted going the extra mile.
Interestingly, but unexpectedly, workplace pressure and stress
(β= 0.04, p< 0.01) were also positively related to the extra mile index.
e overall R
2
for the model with all four variables predicting an extra
mile was 0.16.
Work enthusiasm
Manager autonomy support (β= 0.13, p< 0.001), organizational
support (β= 0.27, p< 0.001), and inner resources (β= 0.22 p< 0.001)
all statistically signicantly, positively predicted enthusiasm, and
workplace pressure and stress (β= −0.11, p< 0.001) negatively related
to this variable. e overall R
2
for the model, with all four variables
predicting work enthusiasm, was 0.28.
Work ecacy
Manager autonomy support (β= 0.09, p< 0.001), organizational
support (β= 0.17, p< 0.001), and inner resources (β= 0.32 p< 0.001)
all statistically signicantly, positively predicted work ecacy.
Workplace stress was not related to work ecacy (β = −0.02,
p= 0.210). e overall R
2
for the model, with all four composites
predicting work ecacy, was 0.23.
Turnover intention
Not all predictors were statistically signicant, with manager
autonomy support unrelated to turnover intention (β = −0.01,
p =0.498). Organizational support (β= −0.20, p< 0.001) was negatively
related to turnover intention, whereas workplace stress was positively
related (β= 0.15, p< 0.001). Interestingly, inner resources also predicted
turnover intention (β= 0.09, p< 0.001), but positively. e overall R
2
for the model with all four composites predicting turnover intention
was 0.06, making it the most weakly predicted outcome.
TABLE5 Preregistered study correlations, means, and standard deviations.
1 2 2 4 5 6 7 8 9 10
1. Inner resources -
2. MAS 0.42*** -
3. Org. Support 0.48*** 0.67*** -
4. workplace stress −0.08*** −0.12*** −0.07*** -
5. Work enjoyment 0.60*** 0.41*** 0.47*** −0.07*** -
6. Job satisfaction 0.42*** 0.48*** 0.61*** −0.17*** 0.51*** -
7. Extra mile 0.30*** 0.33*** 0.37*** 00.33*** 0.34*** -
8. Work enthusiasm 0.40*** 0.41*** 0.47*** −0.13*** 0.50*** 0.54*** 0.56*** -
9. Work ecacy 0.44*** 0.34*** 0.38*** −0.06*** 0.35*** 0.34*** 0.29*** 0.35*** -
10. Turnover intention −0.03 −0.13*** −0.18*** 0.16*** −0.12*** −0.26*** −0.06*** −0.16*** −0.14*** -
Mean 5.04 4.8 4.57 3.31 5.11 2.31 2.20 2.33 5.45 3.06
SD 1.08 1.38 1.24 0.81 1.56 1.09 1.05 1.12 1.40 1.40
*p < 0.05, **p < 0.01, ***p < 0.001. MAS, manager autonomy support; Org. support, organizational support.

DeHaan et al. 10.3389/fpsyg.2024.1413901
Frontiers in Psychology 09 frontiersin.org
Exploratory analyses
In the interest of fully elucidating the dynamics present in these
data, weconducted a small set of exploratory analyses that were not
hypothesized ahead of time and thus not preregistered. All analyses
concerned moderation eects: rst, whether inner resources moderate
the impact of job resources or demands in relation to workplace
outcomes; second, whether factors such as employee age, industry, or
gender moderated the main eects observed (Table9).
Inner resources as a moderator
One question that arose aer conducting the hypothesized analyses
was whether inner resources, as measured by the EVI-S, could function
as a moderator for any of the eects of work demands or resources on
outcomes. Accordingly, using regression analysis, weexamined each of
the above-reported eects with an additional interaction eect between
each of the predictor variables and inner resources on the outcome
variable. Each model thus included four main eects and three
interaction terms. For purposes of this exploratory analysis, all outcomes
are reported in Table10, and plots of these interactions are included in
the Online Supplementary Materials S3. e results for going the extra
mile and work ecacy were not statistically signicant and are not
outlined below.
Work enjoyment
For work enjoyment, only the inner resources by organizational
support term was statistically signicant. e interaction eect was
probed using simple slopes analysis (Aiken and West, 1991). e slope
of organizational support was statistically signicantly dierent from
zero at 1 SD above the mean of inner resources (0.18, p < 0.001), as
well as −1SD, the mean of inner resources (0.28, p < 0.001). is
pattern suggests that organizational support has a stronger eect on
work enjoyment when inner resources are below average relative to
when inner resources are above average.
Job satisfaction
For job satisfaction, only the inner resources by workplace pressure
and stress term were statistically signicant. Simple slopes revealed that
the slope of workplace stress was dierent at +1SD above the mean of
inner resources (−0.10, p < 0.001), as well as −1SD, the mean of inner
resources (−0.22, p < 0.001). is pattern supports a buering eect of
inner resources, suggesting that workplace stress has a weaker negative
eect on job satisfaction when inner resources are high.
Work enthusiasm
For work enthusiasm, two interactions were statistically
signicant. e rst, inner resources by workplace pressure and stress,
indicated that the slope of workplace stress was dierent from zero at
+1SD, the mean of inner resources (−0.07, p < 0.001), as well as −1SD,
the mean of inner resources (−0.14, p < 0.001). is pattern suggests
that workplace stress has a more negative eect on work enthusiasm
when inner resources are below average relative to when inner
resources are above average. e second statistically signicant
interaction was inner resources through organizational support. e
simple slopes suggested that organizational support was dierent from
zero at +1SD, the mean of inner resources (0.22, p < 0.001), as well as
−1SD, the mean of inner resources (0.27, p < 0.001), suggesting that
organizational support had a slightly stronger impact on work
enthusiasm when inner resources are below average relative to
above average.
TABLE6 Preregistered study regressions.
Work
enjoyment
Job satisfaction Extra mile Work
enthusiasm
Work
ecacy
Turnover
intention
Manager autonomy support 0.09*** 0.08*** 0.13*** 0.13*** 0.09*** −0.01, ns
Organizational support 0.18*** 0.49*** 0.22*** 0.27*** 0.17*** −0.20***
Workplace stress −0.01, ns −0.12*** 0.04** −0.11*** −0.02, ns 0.15***
Inner resources 0.47*** 0.14*** 0.14*** 0.22*** 0.32*** 0.09***
Model R20.40 0.41 0.16 0.28 0.23 0.06
*p < 0.05, **p < 0.01, ***p < 0.001.
TABLE7 Preregistered study exploratory dierences by age.
Variable Fdf p18–34 35–44 45–64 65+
Inner resources 7.51 3 <0.001 4.99 5.07 5.05 5.33
Manager need support 1.35 3 0.255 4.78 4.87 4.78 4.80
Organizational support 3.73 3 0.011 4.53 4.65 4.55 4.71
Workplace stress 8.04 3 <0.001 3.31 3.33 3.33 3.05
Work enjoyment 8.92 3 <0.001 5.05 5.22 5.07 5.54
Job satisfaction 9.25 3 <0.001 3.70 3.70 3.63 4.04
Extra mile 8.65 3 <0.001 3.71 3.84 3.87 3.87
Work enthusiasm 6.75 3 <0.001 3.62 3.67 3.70 3.96
Work ecacy 75.82 3 <0.001 5.14 5.48 5.70 6.15
Turnover intention 126.40 3 <0.001 3.25 3.09 2.59 1.90

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Frontiers in Psychology 10 frontiersin.org
Turnover intention
For turnover intentions, two interactions were statistically
signicant. e rst was inner resources by organizational support. e
simple slopes suggested that the slope of organizational support was
dierent from zero at +1SD, the mean of inner resources (−0.15,
p < 0.001), as well as −1SD, the mean of inner resources (−0.32,
p < 0.001). is pattern suggests that a lack of organizational support has
a stronger impact on turnover intention when individuals have low
inner resources relative to high inner resources. e second signicant
interaction was inner resources, which interacted with workplace
pressure and stress. e simple slopes suggested that the eect of
workplace stress was dierent from zero at +1SD, the mean of inner
resources (0.41, p < 0.001), as well as −1SD, the mean of inner resources
(0.09, p < 0.05). is pattern indicates that workplace stress has a higher
impact on turnover intention when inner resources are high.
Discussion
Workplace wellbeing, energy, and eort are multidetermined
outcomes. In this study, our focus was on assessing how job demands
and resources impact these outcomes across a range of occupations
and industries, ndings that support the generalizability of the JD-R
model. Furthermore, weaimed to add to this picture the role that
individual dierences in vitality and agency (i.e., inner resources)
might play in relation to these outcomes. Results of the preregistered
components of these studies generally supported the four hypotheses
concerning the positive links between manager autonomy,
organizational support, and inner resources, with optimal
organizational outcomes, and negative links with workplace pressure.
Weshowed that the inner resource of vitality from non-work sources
was associated with more work engagement and job commitment,
even accounting for the other demands and resources in the models.
ese ndings support the notion that the non-work inner resources
that individuals bring to the workplace may buer the eects of job
demands or stressors. e workplace implications of these results are
that employers may benet from considering not only job resources
and demands but also the inner resources that employees bring
to work.
The eects of job demands and resources
Our evidence lends support to the proposition that manager
autonomy support is positively associated with benecial work-related
outcomes as work enjoyment, job satisfaction, and the willingness to
go beyond the call of duty. However, it may not relate to employees’
intentions to leave their positions. Meanwhile, organizational support
positively related to all benecial outcomes and, crucially, negatively
related to turnover intention. When employees perceive clear
communication about their company’s trajectory and recognize
opportunities for growth—key components of organizational
support—they are more likely to beengaged with and satised at
work. It also suggests that manager autonomy support alone may
be insucient to reduce turnover among sta if they do not also
experience support at the level of the organization.
Although workplace pressure and stress are linked to a decline in
job satisfaction and enthusiasm and an increase in turnover intention,
these factors also appeared to, perhaps counterintuitively, relate to
employees’ drive to exceed performance expectations. From an SDT
standpoint, such an eect may bea function of introjected regulation,
whereby pressure and stress result in people seeking approval from
their leaders (Deci etal., 2017), which can bemotivating in the short
term but tends not to berelated to performance outcomes (Zhang
et al., 2016). Additionally, workplace pressure and stress did not
signicantly impact work enjoyment nor work ecacy when entered
alongside manager supports and organizational supports. is was
found despite signicant zero-order correlations with these variables,
suggesting that workplace pressure and stress may beless tightly
linked to work enjoyment and ecacy than organizational and
manager supports. It seems to suggest that supports need to bepresent
at multiple levels of a workplace, and the right balance of optimal
challenge needs to bestruck to engage and retain satised sta. e
complexity of these dynamics also suggests that employee wellness
should not bean aerthought or limited to sporadic initiatives that are
too peripheral to engage with meaningfully. Rather, wellbeing should
underpin a workplace culture that addresses basic psychological
needs, provides growth opportunities, and recognizes eorts, thereby
weaving wellbeing into the fabric of daily work life.
The eects of non-work resources: inner
resources
Inner resources, as measured by the newly developed Evernorth
Vitality Index, were shown to relate benecially to workplace
outcomes. Hypothesis 4 was partially supported, with inner resources
relating to increased work enjoyment, job satisfaction, extra mile,
work enthusiasm, and work ecacy. However, contrary to the
hypotheses, inner resources were also positively related to turnover
intention in the model. Possibly, feelings of vitality, agency, and
capability in non-work domains make people more open and receptive
to other workplace opportunities. In general, however, it seems that
people’s inner resources across the physical, emotional, intellectual,
social, environmental, and nancial domains provided an indicator of
employee wellness beyond work-related indicators. Yet, it was relevant
to a variety of important workplace outcomes. Indeed, the inner
resource pathway to positive employee outcomes may prove fruitful
for human resource management because our exploratory analyses
TABLE8 Preregistered study exploratory dierences by gender (males
and females only).
Variable F df pMean
(Males)
Mean
(Females)
Inner resources 37.2 1 <0.001 5.14 4.96
Manager need support 12.7 1 <0.001 4.87 4.74
Org. support 23.9 1 <0.001 4.66 4.49
Workplace stress 5.15 1 0.023 3.28 3.33
Work enjoyment 6.40 1 0.012 5.17 5.06
Job satisfaction 25.4 1 <0.001 3.78 3.62
Extra mile 7.86 1 <0.01 3.85 3.76
Work enthusiasm 6.89 1 <0.01 3.72 3.64
Work ecacy 0.32 1 0.57 5.45 5.43
Turnover intention 18.0 1 <0.001 3.03 2.86
Org. support, organizational support.

DeHaan et al. 10.3389/fpsyg.2024.1413901
Frontiers in Psychology 11 frontiersin.org
showed that inner resources might buer against job demands and,
therefore, could bea useful target for workplace interventions. is
research suggests considering a broader spectrum of employee
experiences—and providing supports for employees outside of the
workplace—can bolster employee wellness and performance at work.
Previous studies have underscored the interconnectedness of
work and non-work aspects of people’s lives and their dual inuences
on employee wellbeing and productivity (Beauregard etal., 2011;
Sanhokwe, 2022; Sørensen etal., 2021). Our ndings support those
claims and suggest that a comprehensive approach to understanding
employee wellbeing and work outcomes that encompasses both work-
and non-work-related demands and resources may bemost benecial
to organizations and the people they employ.
Exploratory analyses
Exploratory analyses were added to this story. Inner resources not
only had main eects on outcomes but also played a buering role
when job stress was high, or organizational and manager supports
were low. In fact, the interaction results suggested that demands and
resources make more of a dierence for employees who are low in
inner resources, having more impact on their job enthusiasm, job
satisfaction, and work enjoyment. Such ndings suggest that inner
resources are a source of resilience for workers. However, these
exploratory analyses also suggested that, when overly stressed,
employees with high vitality are at risk of turnover, perhaps because
they have the agency and energy to consider alternatives. Yet wenote
that, although these moderation eects generally appear reliable and
the sample is large, they should becautiously interpreted since they
were not specied a priori in our registered hypotheses, and they need
to be tested in longitudinal studies to determine the direction
of causation.
Furthermore, industry data were collected and grouped (see
Online Supplemental Materials S2). All study variables were
compared to understand if industry categories diered on key study
variables. All comparisons were statistically signicant, with
relatively consistent patterns of results across variables. Notably, the
Service and Hospitality category reported low job resources and low
positive outcomes. In contrast, Professional and Business Services
reported greater inner resources, greater job resources, and higher
positive outcomes. ese ndings oer practical implications for
managers and organizations, by providing insights that encourage
organizations to address non-work factors. Proactively
understanding and addressing both work and non-work domains
together can contribute to creating value for both individuals
and businesses.
Limitations
One of the limitations of this study is that werelied primarily on
adapted and short-form versions of measures both to reduce
participant burden and facilitate the future use of the measures in
commercial settings, where brevity is important. e future study
would ideally replicate these results and more fully embed them in the
extant literature using validated measures where possible. In addition,
considering multiple measurement timepoints can reduce recall
TABLE9 Preregistered study exploratory dierences by industry group.
Variable Inner
resources
Manager
autonomy
Support
Organizational
support
Workplace
stress
Work
enjoyment
Job
satisfaction
Extra
mile
Work
enthusiasm
Turnover
intention
F11.35 11.32 21.90 10.03 5.53 10.15 5.21 6.13 18.86
df 5 5 5 5 5 5 5 5 5
p<0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001
Health and biotechnology 5.04 4.83 4.58 3.42 5.22 3.74 3.79 3.73 2.81
Industrial and construction 5.08 4.76 4.57 3.23 5.17 3.73 3.86 3.67 2.83
Other 4.94 4.71 4.43 3.22 4.99 3.62 3.76 3.57 2.85
Professional and business services 5.24 5.08 4.90 3.35 5.27 3.87 3.94 3.80 3.24
Public and infrastructure 5.03 4.73 4.55 3.39 5.08 3.68 3.73 3.70 2.72
Service and hospitality 4.92 4.68 4.37 3.25 4.99 3.55 3.75 3.58 3.09

DeHaan et al. 10.3389/fpsyg.2024.1413901
Frontiers in Psychology 12 frontiersin.org
biases, and continuing to ensure participant anonymity will reduce
any social desirability demands. Furthermore, a wider variety of
outcomes could beconsidered, including more objective measures of,
for example, job performance and turnover. We do believe self-
reporting will continue to bea core method of this work, given the
importance of subjective experiences in these models.
e current study also does not establish the causality of eects in
the model. While job resources (via manager autonomy support and
organizational support), job demands (via workplace stress), and
inner resources (EVI-S) were treated in the preregistered model as
simultaneous predictors of outcomes, there remains the possibility of
a deeper process model here. Future studies should build from these
cross-sectional foundations and explore the causal pattern of results
to explore if these relations hold over time, particularly if changes in
inner resources, job resources, and job demands produce meaningful
changes in outcomes at subsequent times. Additional objective
outcomes could beconsidered as well, including any reliable and
defensible measures of workplace outcomes or, across a large enough
population, actual turnover rates.
e exploratory models with inner resources serving as a
moderator of the eects the other variables have on outcomes spark
interest in considering more nuanced models of these dynamics. In
particular, future studies can explore the kinds of oerings and
interventions workplaces can provide that bolster inner resources,
leading to greater wellness and performance at work and—
presumably—outside of it.
It is also noteworthy that our samples were limited to US workers,
and generalizability to employees in other cultures is not established.
In addition, welooked at a restricted number of variables under the
JD-R categories of resources and demands. A more comprehensive
assessment of these categories would undoubtedly account for more
variance and supply comparative information on the relative strength
of predictors in the workplace.
Conclusion
In sum, wewere able to demonstrate the important role of job
climate in wellbeing and distress at work, as understood by the
JD-R framework. Both the job resources of organization support
and manager autonomy support were associated with better job
outcomes, with job demands generally being a negative predictor.
These results thus support the JD-R framework and highlight that
the inner resources of the individual matter with regard to work
outcomes as they turned out to bestrongly correlated with optimal
functioning at work. This study then contributes to both the JD-R
theory and SDT. With respect to JD-R, weexpand the scope of the
broad category of resources to include individual differences.
Although wehighlighted vitality and agency here, other inner
resources could beexamined in future research within the JD-R
framework, expanding opportunities for research on work-related
wellbeing, job satisfaction, and performance. With respect to SDT,
these results further establish the importance of vitality and
agency as inner resources that both yield positive outcomes
directly and may also help as a buffer against frustrating elements
in one’s world.
Data availability statement
e dataset was privately sourced, and remains privately managed
by Evernorth Research Institute. Requests to access the datasets should
bedirected to richard.ryan@acu.edu.au.
Ethics statement
The authors received an ethics waiver for secondary data
analysis from the Australian Catholic University’s (ACU) Human
Research Ethics Committee (HREC) under reference 2022-
2967N. The studies were conducted in accordance with the local
legislation and institutional requirements. The participants
provided their written informed consent to participate in
this study.
Author contributions
CD: Conceptualization, Data curation, Formal analysis, Investigation,
Methodology, Project administration, Writing – original dra, Writing
– review & editing. EB: Project administration, Writing – original dra,
Writing – review & editing. SD-C: Conceptualization, Data curation,
Project administration, Resources, Writing – original dra, Writing –
review & editing. TT: Project administration, Resources, Writing
TABLE10 Preregistered study exploratory regressions including interactions.
Work
enjoyment
Job
satisfaction
Extra
mile
Work
enthusiasm
Work
ecacy
Turnover
intention
MAS 0.11 −0.01 0.19*0.00 0.18*0.06
Org. support 0.36*** 0.53*** 0.23** 0.42*** 0.10 −0.56***
WP stress 0.03 −0.33*** 0.08 −0.18*** 0.02 −0.29***
Inner Resources 0.65*** −0.07 0.23** 0.13 0.36*** −0.50***
Inner resources * MAS 0.00 0.01 −0.01 0.02 −0.01 −0.01
Inner resources * Org. Support −0.04** −0.01 0.00 −0.03*0.01 0.07***
Inner resources * WP stress −0.01 0.06*** −0.01 0.03* −0.01 0.13***
Model R20.40 0.42 0.16 0.28 0.23 0.07
Org. support, organizational support; MAS, manager autonomy support; WP stress, workplace stress.

DeHaan et al. 10.3389/fpsyg.2024.1413901
Frontiers in Psychology 13 frontiersin.org
– original dra, Writing – review & editing. CR: Writing – original dra,
Writing – review & editing. RR: Conceptualization, Funding acquisition,
Investigation, Methodology, Project administration, Resources, Writing
– original dra, Writing – review & editing.
Funding
e author(s) declare that nancial support was received for the
research, authorship, and/or publication of this article. Cigna and
Evernorth nanced the data collections with which the EVI and EVI-S
were mentioned, however, that involvement did not aect the analysis
nor interpretation of the results.
Conflict of interest
CD, CR, and RR were employed by Immersyve, Inc. SD-C and TT
were employed by Evernorth Research Institute.
e remaining author declares that the research was conducted in
the absence of any commercial or nancial relationships that could
beconstrued as a potential conict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors
and do not necessarily represent those of their aliated organizations,
or those of the publisher, the editors and the reviewers. Any product
that may beevaluated in this article, or claim that may bemade by its
manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
e Supplementary material for this article can befound online
at: https://www.frontiersin.org/articles/10.3389/fpsyg.2024.1413901/
full#supplementary-material
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