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Which Daily Experiences Can Foster Well-Being at Work? A Diary Study on the Interplay Between Flow Experiences, Affective Commitment, and Self-Control Demands

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Previous research has provided strong evidence for affective commitment as a direct predictor of employees' psychological well-being and as a resource that buffers the adverse effects of self-control demands as a stressor. However, the mechanisms that underlie the beneficial effects of affective commitment have not been examined yet. Drawing on the self-determination theory, we propose day-specific flow experiences as the mechanism that underlies the beneficial effects of affective commitment, because flow experiences as peaks of intrinsic motivation constitute manifestations of autonomous regulation. In a diary study covering 10 working days with N = 90 employees, we examine day-specific flow experiences as a mediator of the beneficial effects of interindividual affective commitment and a buffering moderator of the adverse day-specific effects of self-control demands on indicators of well-being (ego depletion, need for recovery, work engagement, and subjective vitality). Our results provide strong support for our predictions that day-specific flow experiences a) mediate the beneficial effects of affective commitment on employees' day-specific well-being and b) moderate (buffer) the adverse day-specific effects of self-control demands on well-being. That is, on days with high levels of flow experiences, employees were better able to cope with self-control demands whereas self-control demands translated into impaired well-being when employees experienced lower levels of day-specific flow experiences. We then discuss our findings and suggest practical implications. (PsycINFO Database Record
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Journal of Occupational Health Psychology
Which Daily Experiences Can Foster Well-Being at Work? A
Diary Study on the Interplay Between Flow Experiences,
Affective Commitment, and Self-Control Demands
Wladislaw Rivkin, Stefan Diestel, and Klaus-Helmut Schmidt
Online First Publication, April 21, 2016. http://dx.doi.org/10.1037/ocp0000039
CITATION
Rivkin, W., Diestel, S., & Schmidt, K.-H. (2016, April 21). Which Daily Experiences Can Foster
Well-Being at Work? A Diary Study on the Interplay Between Flow Experiences, Affective
Commitment, and Self-Control Demands. Journal of Occupational Health Psychology. Advance
online publication. http://dx.doi.org/10.1037/ocp0000039
Which Daily Experiences Can Foster Well-Being at Work? A Diary Study
on the Interplay Between Flow Experiences, Affective Commitment, and
Self-Control Demands
Wladislaw Rivkin
Leibniz Research Centre for Working Environment and Human
Factors at the Technical University of Dortmund
Stefan Diestel
International School of Management–Dortmund
Klaus-Helmut Schmidt
Leibniz Research Centre for Working Environment and Human Factors at the Technical University of Dortmund
Previous research has provided strong evidence for affective commitment as a direct predictor of
employees’ psychological well-being and as a resource that buffers the adverse effects of self-control
demands as a stressor. However, the mechanisms that underlie the beneficial effects of affective
commitment have not been examined yet. Drawing on the self-determination theory, we propose
day-specific flow experiences as the mechanism that underlies the beneficial effects of affective
commitment, because flow experiences as peaks of intrinsic motivation constitute manifestations of
autonomous regulation. In a diary study covering 10 working days with N90 employees, we examine
day-specific flow experiences as a mediator of the beneficial effects of interindividual affective com-
mitment and a buffering moderator of the adverse day-specific effects of self-control demands on
indicators of well-being (ego depletion, need for recovery, work engagement, and subjective vitality).
Our results provide strong support for our predictions that day-specific flow experiences a) mediate the
beneficial effects of affective commitment on employees’ day-specific well-being and b) moderate
(buffer) the adverse day-specific effects of self-control demands on well-being. That is, on days with high
levels of flow experiences, employees were better able to cope with self-control demands whereas
self-control demands translated into impaired well-being when employees experienced lower levels of
day-specific flow experiences. We then discuss our findings and suggest practical implications.
Keywords: commitment, flow experiences, self-control demands, self-determination theory, well-being
Positive psychology (Seligman & Csikszentmihalyi, 2000) has
promoted research on employees’ psychological well-being (sim-
ply referred to as well-being throughout the article), which has
become a major research topic in the field of personnel psychol-
ogy. Thus, recent research on stress and work-related psycholog-
ical health, instead of exclusively focusing on negative work-
related outcomes (e.g., burnout or depression; Alarcon, 2011), has
also focused on positive outcomes at work (e.g., positive mood and
creativity; Davis, 2009). Consequently, this line of research has
identified multiple stressors (e.g., self-control demands [SCDs];
Schmidt & Diestel, 2015) that impair well-being as well as re-
sources that help to foster psychological well-being (Hobfoll,
2002). In particular, there is strong empirical evidence for the
direct beneficial effects of organizational commitment on well-
being and for the buffering effects of commitment on the adverse
relations between stressors and well-being (for a review, see
Meyer & Maltin, 2010). To account for these effects, Meyer and
Maltin (2010) proposed a theoretical framework drawing on the
self-determination theory (SDT). This framework suggests that
basic psychological needs satisfaction (autonomy, competence,
and relatedness) at work constitutes the basis for the experience of
both commitment and autonomous (in contrast to controlled) ac-
tion regulation or intrinsic motivation, which in turn facilitate
well-being (Deci & Ryan, 1985; Ryan & Deci, 2000). More
specifically, the authors suggest that affective commitment and
autonomous regulation are reciprocally related (cf., Meyer &
Maltin, 2010, p. 330). That is, basic needs satisfaction may pro-
mote autonomous regulation at work, which facilitates the initial
emergence of employees’ commitment. In turn, once commitment
is established it may reinforce autonomous regulation, which can
be expected to buffer the adverse effects of job stressors such as
SCDs (e.g., by reducing depletion of regulatory resources and by
recovering regulatory resources after depletion; Muraven, 2008;
Muraven, Gagné, & Rosman, 2008; Rivkin, Diestel, & Schmidt,
2015). Drawing on these arguments, we propose flow experiences,
which constitute manifestations of autonomous regulation as a
Wladislaw Rivkin, Leibniz Research Centre for Working Environment
and Human Factors at the Technical University of Dortmund; Stefan
Diestel, International School of Management–Dortmund; Klaus-Helmut
Schmidt, Leibniz Research Centre for Working Environment and Human
Factors at the Technical University of Dortmund.
Correspondence concerning this article should be addressed to Wladis-
law Rivkin, Leibniz Research Centre for Working Environment and Hu-
man Factors at the Technical University of Dortmund, Ardeystr. 67,
Dortmund D-44139, Germany. E-mail: rivkin@ifado.de
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Journal of Occupational Health Psychology © 2016 American Psychological Association
2016, Vol. 21, No. 4, 000 1076-8998/16/$12.00 http://dx.doi.org/10.1037/ocp0000039
1
mediator of the beneficial effects of stable affective commitment
on well-being.
Furthermore, in the field of self-control, cross sectional and
diary studies have demonstrated buffering effects of commitment
on the adverse effects of SCDs on well-being (Schmidt, 2007;
Rivkin et al., 2015). SCDs at work require employees to engage in
self-control, which involves the inhibition, modification, or over-
ride of spontaneous and automatic reactions, urges, emotions, and
desires that would otherwise interfere with goal-directed behavior
and impede goal achievement at work (Baumeister, Heatherton, &
Tice, 1994). Muraven and Baumeister (2000) delineated the
strength model of self-control according to which different self-
control processes tax on a common limited regulatory resource and
that depletion of this resource can impair well-being. Integrating
SDT and research on the effects of autonomous regulation on
regulatory resource depletion (Muraven, 2008; Muraven et al.,
2008), Rivkin et al. (2015) proposed that the buffering effects of
commitment on the negative day-specific relations between SCDs
and well-being are provided by autonomous regulation and asso-
ciated positive experiences that have the potential to replenish
regulatory resources.
However, despite the large body of evidence on the beneficial
effects of commitment and the adverse effects of SCDs on
well-being, scholarly knowledge suffers from at least three
limitations. First, although the strength model of self-control
implies day-specific adverse effects of SCDs, to our knowledge,
only a few studies have examined such day-specific relations
(exceptions are: Muraven, Collins, Shiffman, & Paty, 2005;
Rivkin et al., 2015). Thus, research on self-control could benefit
from examining day-specific mechanisms and processes that
underlie the proposed relations. Second, despite the theoretical
arguments that predict the beneficial effects of commitment on
well-being, to our knowledge, there are no empirical studies
that have examined the mechanisms proposed by Meyer and
Maltin (2010). And third, for multiple occupations, particularly
in the services sector, SCDs constitute an integral part of the
work role. Hence, to protect employees from impairments in
well-being that result from high SCDs, research needs to iden-
tify further resources that have the potential to buffer the
adverse effects of SCDs.
In the present study, we address these drawbacks by integrat-
ing theories and findings from research on self-control, com-
mitment and flow experiences. Csikszentmihalyi (1990) defined
flow experiences as states of consciousness occasionally expe-
rienced by individuals who are deeply involved in an enjoyable
activity. Therefore, flow experiences reflect pleasant states that
are highly intrinsically motivating and during which employees
experience high levels of autonomous regulation. On the basis
of Meyer and Maltin’s (2010) theoretical framework, we pro-
pose that strongly committed employees are more likely than
less committed employees to experience autonomous regulation
or intrinsic motivation at work, which manifests as day-specific
flow experiences. Thus, we predict that flow experiences me-
diate the direct effects of already established levels of employ-
ees’ commitment on well-being. Additionally, experimental
research in the field of self-control has demonstrated that in
contrast to controlled or enforced self-control, autonomous
forms of self-control, also referred to as self-regulation, help to
restore limited regulatory resources (Muraven, 2008; Muraven
et al., 2008). Because autonomous self-regulation or intrinsic
motivation constitutes an integral component of flow experi-
ences, we propose that day-specific flow experiences also mod-
erate (buffer) the adverse effects of SCDs on well-being.
Figure 1 depicts the hypothesized model of the present
study.
In the following, we first elaborate on the concept of affec-
tive commitment and the theoretical model proposed by Meyer
and Maltin (2010), which form the basis for our prediction on
mediating effects of day-specific flow experiences. Then, we
review research on SCDs to derive arguments for the moderat-
ing effects of flow experiences on the day-specific adverse
relations between SCDs and well-being. Finally, we test our
predictions in a diary study.
Figure 1. Theoretical model.
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2RIVKIN, DIESTEL, AND SCHMIDT
Beneficial Effects of Affective Commitment on
Well-Being: Flow Experiences as a Mediator
Organizational commitment refers to “a force that binds an
individual to the target and to a course of action of relevance to
that target” (Van Dick, Becker, & Meyer, 2006). Whereas Allen
and Meyer (1990) originally proposed three components (affec-
tive, normative, and continuance commitment), most scholars
agree that affective commitment constitutes the conceptual core of
organizational commitment. This notion was grounded in the large
body of empirical evidence that inevitably demonstrates that af-
fective commitment exerts the strongest beneficial effects on job
performance and psychological well-being (Meyer & Maltin,
2010). Previous research has proposed commitment as an inter-
mediate variable, which on the one hand predicts job outcomes
such as performance, turnover, and well-being and on the other
hand can be determined by multiple factors such as personal
characteristics (e.g., age and tenure), job characteristics (e.g., skill
variety and task autonomy), leadership (e.g., consideration; Ma-
thieu & Zajac, 1990), and not least through satisfaction of basic
psychological needs and associated forms of autonomous regula-
tion (cf., Meyer & Maltin, 2010). Thus, studies emphasizing the
emergence of commitment have examined it as an outcome vari-
able (for an overview see Meyer, Stanley, Herscovitch, & Topol-
nytsky, 2002), while research focusing on the consequences of
established forms of commitment have considered it as a predictor
of work-related outcomes (e.g., Leong, Furnham, & Cooper, 1996;
Ng & Feldman, 2011; Schmidt & Diestel, 2012; Rivkin et al.,
2015). Furthermore, studies on commitment have demonstrated
that once employees have established a certain level of commit-
ment to their organization—for example, through basic needs
satisfaction and autonomous regulation—this level remains rela-
tively stable over time. For example, in a sample of experienced
nursing employees, Bateman and Strasser (1984) found that over a
time lag of five months the correlation of Time 1 and Time 2
commitment was .65 (p.01). In addition, analyses of the
temporal stability of affective commitment indicate that those with
high tenure tend to experience more stable levels of commitment.
Consistent with this finding, only meaningful changes in job or
organizational characteristics and perceptions have the potential to
influence the level of employee commitment (Johnston, Parasura-
man, Futrell, & Black, 1990). In light of these findings, Meyer and
Allen (1997, p. 120) concluded that after a state of flux, commit-
ment rapidly begins to stabilize. Drawing on these arguments in
the present study, we examine established levels of affective
commitment as a predictor, which is expected to be stable over the
time frame covered by our study.
The theoretical focus on affective commitment is also consistent
with the SDT, which suggests that the satisfaction of employees’
basic psychological needs promotes autonomous regulation at
work and thereby particularly fosters affective commitment. In
turn, once employees have established a certain level of work-
related commitment, it is expected to be strongly reciprocally
related to autonomous regulation or intrinsic motivation (Meyer &
Maltin, 2010). In contrast to controlled regulation, which is nec-
essary when aiming for external rewards or avoiding punishment,
autonomous regulation implies that activities are freely chosen and
consistent with one’s core values. Consistently, research in orga-
nizational contexts has repeatedly demonstrated that states of
autonomous regulation are positively related to work outcomes
such as work engagement, performance, and well-being (e.g.,
Baard, Deci, & Ryan, 2004; Gagné, Koestner, & Zuckerman,
2000). Thus, drawing on Meyer and Maltin’s (2010) theoretical
framework, we propose that autonomous regulation is thought to
constitute the mechanism that underlies the beneficial effects of
established affective commitment on well-being.
In the present study, we propose flow experiences as a mani-
festation of autonomous regulation and thus as a mediator of the
positive effects of stable affective commitment on day-specific
indicators of well-being. According to Csikszentmihalyi (1990), flow
experiences comprise nine interrelated components: challenge-skill
balance, action-awareness merging, clear goals, unambiguous
feedback, concentration on the task at hand, a sense of control, loss
of self-consciousness, time transformation, and autotelic experi-
ence. These components reflect states in which individuals are
completely immersed in an activity and draw their motivation from
performing this specific activity rather than from external rewards
that may be associated with the activity. Consequently, flow ex-
periences reflect peaks of intrinsic motivation, which are expected
to be positively related to day-specific indicators of well-being.
Rheinberg, Vollmeyer, and Engeser (2003) conceptualized a scale
to measure flow that consists of two correlated but distinct dimen-
sions. The first dimension reflects the fluency of performance
during an activity, while the second dimension describes the ab-
sorption into an activity. Consistent with the proposition that the
beneficial effects of flow on well-being result from intrinsic mo-
tivation, which occurs during states of total immersion into a task,
in the present study we use the absorption dimension to operation-
alize flow. Conceptualized as absorption into a task, flow experi-
ences are likely to reflect day-specific states rather than traits that
are constant across different days. Hence, experience sampling has
been proposed as an appropriate method to measure flow experi-
ences (Csikszentmihalyi & Rathunde, 1993). In line with this
argument, we use day-specific measurements of flow experiences
to capture the anticipated fluctuations of flow experiences across
days.
From a theoretical perspective, two central propositions strongly
suggest that flow experiences mediate the positive relations be-
tween established commitment and day-specific well-being. First,
we propose a positive relation between stable levels of affective
commitment and flow. As suggested by the challenge–skill bal-
ance component, flow experiences are facilitated by activities,
which are challenging for a specific individual. Thus, research
suggests that the investment of personal energetic resources con-
stitutes a psychological precondition to experience flow (Naka-
mura & Csikszentmihalyi, 2002). Accordingly, studies have dem-
onstrated that task (e.g., appropriate task difficulty, Nakamura &
Csikszentmihalyi, 2002) as well as personal characteristics (e.g.,
state of recovery, Debus, Sonnentag, Deutsch, & Nussbeck, 2014)
facilitate flow experiences. Consistent with this argument, we
propose affective commitment as another externally influenced
characteristic that promotes flow experiences. We argue that em-
ployees with low levels of affective commitment tend to invest
lower amounts of energetic resources at work because they are
more likely to perform according to “work to rule.” In contrast,
highly committed employees tend to invest larger amounts of
resources at work because, for example, they are more likely to
engage in extrarole behavior (Organ & Ryan, 1995), which neces-
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3
DAY-SPECIFIC FLOW EXPERIENCES AND WELL-BEING
sitates the investment of regulatory energetic resources (Son-
nentag, Mojza, Demerouti, & Bakker, 2012). Consequently, we
expect strongly committed employees to experience higher levels
of day-specific flow at work.
Second, we argue that flow experiences are positively related to
well-being. The autotelic component of flow implies that flow
experiences are highly intrinsically motivating and thus reflect
high levels of autonomous regulation because activities are per-
formed for their own sake rather than for gaining external reward
(Csikszentmihalyi & Rathunde, 1993; Ellis, Voelkl, & Morris,
1994). SDT in turn states that basic needs satisfaction at work
fosters autonomous regulation, which in turn predicts well-being
(Ryan & Deci, 2000). Kowal and Fortier (1999) demonstrated
positive relations between basic needs satisfaction and flow expe-
riences as manifestations of autonomous regulation, which in turn
are expected to predict employees’ psychological well-being. In-
tegrating both arguments, we propose:
Hypothesis 1: Day-specific levels of flow experiences mediate
the positive relations between affective commitment at the
person level and indicators of day-specific psychological well-
being (Hypothesis 1a: low ego-depletion; Hypothesis 1b: low
need for recovery; Hypothesis 1c: high work engagement;
Hypothesis 1d: high subjective vitality).
However, because Meyer and Maltin’s (2010) theoretical frame-
work proposes a reciprocal relationship of affective commitment
and autonomous regulation, and because commitment may be
studied as a predictor as well as an outcome (Mathieu & Zajac,
1990), one may also assume alternative models for the interplay of
SCDs, flow experiences, and commitment. For example, the
above-mentioned arguments may also lead to the prediction that
affective commitment is an outcome of flow experiences and
SCDs. Thus, we conduct additional analyses to test this prediction.
Demonstrating that empirical data provides only limited support
for such a model is supposed to strengthen the evidence for our
proposed Hypothesis 1.
As indicators of well-being, we focus on ego depletion, need for
recovery, work engagement, and subjective vitality. According to
previous research, these outcomes constitute short-term indicators
of well-being that correspond with day-specific fluctuations of
stressors and resources (Rivkin, Diestel, & Schmidt, 2014; Diestel,
Rivkin, & Schmidt, 2015). Ego depletion refers to a state of
regulatory resource depletion and an inner experience of exhaus-
tion (Baumeister, Bratslavsky, Muraven, & Tice, 1998). Need for
recovery reflects the requirement to recuperate from work tasks
that is strongest in the last hours of work and directly after work
(Van Veldhoven & Broersen, 2003). These indicators represent
cognitive and behavioral manifestations of regulatory resource
depletion (Diestel et al., 2015).
Work engagement is a fulfilling and motivational state of mind
reflected by perceived energy, vitality and mental resilience
(vigor), strong work-related involvement (dedication), and being
positively engrossed in and focused on work (absorption; Bakker,
2011). Subjective vitality is a positive feeling of aliveness and
energy (Ryan & Frederick, 1997). While subjective vitality may
directly reflect the availability of regulatory resources, Sonnentag
et al. (2012) proposed that work engagement may be largely
influenced by the perceived availability of regulatory resources.
Particularly when perceived regulatory resource availability is low,
employees attempt to conserve regulatory resources by reducing
work engagement (Ryan & Deci, 2008).
Adverse Effects of SCDs on Well-Being:
Flow Experiences as a Moderator
A growing body of research indicates that frequent acts of
self-control are associated with psychological costs, which can
manifest in impairments of cognitive and behavioral control (Hag-
ger, Wood, Stiff, & Chatzisarantis, 2010). In a series of experi-
mental studies that demanded two successive acts of self-control
(e.g., the suppression of emotions or thoughts and attention con-
trol), self-control performance on the second act was consistently
impaired, even in apparently unrelated spheres of activity (see
Hagger et al., 2010, for a meta-analysis).
In addition, recent research in occupational health psychology
has also demonstrated that SCDs constitute a major stressor at
work. Neubach and Schmidt (2007) identified three forms of SCDs
at work. First, impulse control refers to the demand to inhibit
spontaneous, impulsive response tendencies and associated affec-
tive states, which manifest, for example, in injudicious expres-
sions. Second, resisting distractions involves the requirement to
ignore or resist distractions evoked by task-irrelevant stimuli.
Third, overcoming inner resistances relates to the requirement to
overcome motivational deficits that result from unappealing tasks.
Multiple studies have demonstrated adverse effects of these SCDs
on indicators of well-being (e.g., burnout and depression) and a
decrease in productivity (e.g., absenteeism; Diestel & Schmidt,
2011). The strength model of self-control (Muraven & Baumeister,
2000) accounts for these findings by proposing that SCDs cause
employees to engage in self-control, which, in turn, depletes lim-
ited regulatory resources and thereby impairs psychological well-
being.
In addition to the broad empirical evidence from cross-sectional
studies suggesting that SCDs impair well-being (Schmidt & Dies-
tel, 2015), initial research has demonstrated that work-related
SCDs exhibit high day-specific variation, which indicates that
SCDs are not constant over time but are subject to day-specific
change and that high day-specific SCDs impair psychological
well-being (Rivkin et al., 2015). To protect employees from the
adverse effects of SCDs, research has also identified resources
(e.g., sleep quality and trait self-control; Diestel et al., 2015) that
have the potential to buffer the adverse effects of SCDs on well-
being. Accordingly, in the present study, we examine day-specific
flow experiences as yet another resource that may buffer the
adverse effects of day-specific SCDs on day-specific well-being.
Our proposition draws from findings on recovery of regulatory
resources (Muraven, 2008; Muraven et al., 2008; Tice, Baumeister,
Shmueli, & Muraven, 2007), suggesting that in contrast to con-
trolled regulation, which is performed for the sake of extrinsic
motives (e.g., gaining rewards or avoiding punishments), autono-
mous regulation requires less effort and thus is less depleting.
Multiple studies have demonstrated that participants were less
depleted and performed better on subsequent self-control tasks
when they engaged in self-regulation (autonomous self-control)
instead of forced or pressured self-control (Muraven, 2008; Mu-
raven et al., 2008). Consistent with the idea that pleasant experi-
ences during self-control-related tasks facilitate recovery of lim-
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4RIVKIN, DIESTEL, AND SCHMIDT
ited resources, Muraven et al. (2008) argued that autonomous
regulation and associated positive affective states facilitate and
accelerate recovery of limited regulatory resources. In line with
this argument, we propose that flow experiences as a manifestation
of autonomous regulation buffer the negative day-specific rela-
tions between SCDs and indicators of well-being by facilitating
recovery of regulatory resources after depletion. Thus, we derive
the following Hypothesis:
Hypothesis 2: Day-specific flow experiences moderate the
negative relations between day-specific SCDs and indicators
of day-specific psychological well-being (Hypothesis 2a: low
ego-depletion; Hypothesis 2b: low need for recovery, Hypoth-
esis 2c: high work engagement; Hypothesis 2d: high subjec-
tive vitality): The negative relations are attenuated as a func-
tion of day-specific flow experiences.
Method
Participants
We conducted a diary study to test our hypotheses. The method
of data collection was adopted by Rivkin et al. (2015). However,
the present data sample was collected exclusively for the present
study, and thus has not been previously published. The present
study was conducted in Germany and focused on employees from
the services sector who had regular contact with clients, patients,
customers, or other individuals. Overall, participants held different
occupations; a large part of the sample worked as consultants,
followed by salespersons. Furthermore, some participants worked
in care institutions, as kindergarten teachers and in elder care. For
these participants, SCDs constitute a predominant stressor at work.
For example, to promote customer satisfaction, employees must
inhibit affective states or behavioral tendencies that may displease
customers (Schmidt & Diestel, 2015). This description of SCDs
may resemble emotional labor in general and emotional disso-
nance in particular because both job demands are thought to rely
on a common limited regulatory resource (e.g., Diestel & Schmidt,
2011). However, there are also conceptual differences between
these both job demands. For example, while emotional dissonance
largely involves the display of emotions, which are not felt at that
particular moment, SCDs also include the inhibition of impulsive
reactions and behavioral tendencies, resisting distractions and
completing unattractive assignments. These conceptual differences
are also supported by confirmatory factor analyses (cf., Diestel &
Schmidt, 2011).
We recruited participants by announcements via e-mail. There-
fore, over the course of the last years, we collected contact infor-
mation from individuals who expressed their willingness to par-
ticipate in a scientific study. Additionally, we invited personal
contacts to participate in our electronic diary study. Individuals did
not receive any compensation for participating in our study. A final
sample of 90 participants was included in our study. Of the partici-
pants, 79% were female, 26% worked part-time, and the mean age
was 39.51 (SD 14.08) years. In advance of the day-specific mea-
surements, the participants responded to a general questionnaire
that assessed demographic variables and person-level constructs
(e.g., affective commitment). Over 10 consecutive work days,
three times per day (morning, noon, and evening), participants
received e-mails reminding them to complete day-specific ques-
tionnaires. However, only two measurement points (noon and
evening) were relevant for the present study. At noon, participants
rated SCDs and flow experiences; in the evening after work, ego
depletion, need for recovery, work engagement, and subjective
vitality were assessed. On weekends or public holidays, the diary
study was suspended and continued on the next regular work day.
Overall, response rate to our daily questionnaires was 76%, result-
ing in 648 daily measurement points, which were included into our
analyses.
Measures and Control Variables
The general questionnaire included age, gender, work-time, and
affective commitment. In the day-specific questionnaires, we ex-
plained that the items of the SCD scale, flow experiences and all
items of psychological well-being refer to recent experience.
Affective commitment. To measure affective commitment,
four items from the German translation (Schmidt, Hollmann, &
Sodenkamp, 1998) of Allen and Meyer’s (1990) affective com-
mitment scale were used. The scale reflects the affective attach-
ment to and involvement in the organization. A typical item is
“This organization has a great deal of personal meaning for me.”
All items were rated on a 7-point intensity-rating scale (1 not at
all;7a great deal).
Flow experiences absorption (noon). Our measure of flow
experiences is comprised of four items that reflect the absorption
dimension of flow (Rheinberg et al., 2003; for the English version,
see Rheinberg, 2008; for studies published in English using this
measure, see Engeser & Rheinberg, 2008; Schüler & Brunner,
2009). On a 7-point intensity-rating scale (1 not at all;7a
great deal) participants rated how absorbed they were into the task
they performed before responding to our survey. An example is “I
did not realize that time is going by.”
SCDs (noon). We assessed day-specific SCDs with the 15-
item scale developed by Neubach and Schmidt (2007). On a
5-point intensity-rating scale (1 not at all;5a great deal), the
participants rated the degree to which they had to control their
impulses in “the last hours” of work. An example of an item is “In
the last hours, my job required me not to lose my temper.”
Ego depletion (evening). Day-specific ego depletion was as-
sessed using five items related to the participants’ current experi-
ences with resource depletion and low willpower (e.g., “At the
moment, I feel increasingly less able to focus on anything.”). The
scale was developed and validated by Bertrams, Unger, and Dick-
häuser (2011), who intended to assess the psychological state of
ego depletion proposed by Muraven and Baumeister (2000). All
items were scored using a 4-point intensity-rating format (1 not
at all;4a great deal).
Need for recovery (evening). We assessed the day-specific
need for recovery using five items from Van Veldhoven and
Broersen’s (2003) scale (e.g., “Today, I cannot really show any
interest in other people when I have just come home myself.”). In
essence, this scale indicates the extent to which employees are
incapable of expressing interest in other things and perceive a
strong need for a rest period to recover from stressful activities. All
items were scored using a 4-point intensity-rating format (1 not
at all;4a great deal).
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5
DAY-SPECIFIC FLOW EXPERIENCES AND WELL-BEING
Work engagement (evening). The assessment of day-specific
work engagement was based on the nine-item version of the
Utrecht Work Engagement Scale (Breevaart, Bakker, Demerouti,
& Hetland, 2012; Schaufeli, Bakker, & Salanova, 2006), which
was adapted for day-specific assessment and involves three facets:
vigor (e.g., “Today, I felt strong and vigorous at my work.”),
dedication (e.g., “Today, I was enthusiastic about my job.”), and
absorption (e.g., “Today, I was immersed in my work.”). The
response format ranges from 0 (strongly disagree)to6(strongly
agree). As suggested by Xanthopoulou, Bakker, Demerouti, and
Schaufeli (2009), we incorporated vigor, dedication and absorption
into a general work engagement factor that was computed as the
mean of the three facets of work engagement.
Subjective vitality (evening). Day-specific subjective vitality
was assessed with four items from Ryan and Frederick’s (1997)
subjective vitality scale. The scale was conceptualized to measure
the feeling of being alive and alert. An example of an item is
“Right now I feel alive and vital”. The response format ranges
from 1 (not at all)to7(a great deal).
Construct Validity
We conducted multilevel confirmatory factor analyses
(MCFAs) to assess the psychometrical distinctiveness of our day-
level measures. First, MCFAs for SCDs and state flow experiences
as different predictors indicated a satisfactory fit: 2 (38) 84.01,
p.01, root-mean square error of approximation (RMSEA)
.043, comparative fit index (CFI) .979, standardized root-mean-
square residual within-person/between-person (SRMRw/SRMRb)
.037/.056; however, a model with SCDs and flow experiences as
one factor performed worse (2 (40) 355.85, p.01,
RMSEA .110, CFI .856, SRMRw/b .104/.232). Second,
the construct validity of the outcomes ego depletion, need for
recovery, work engagement, and subjective vitality was tested in a
4-factor model. The 4-factor model (2 (42) 98.96, p.01,
RMSEA .046, CFI .986, SRMRw/b .034/.085) performed
better compared to other models that integrated all variables into
one factor (2 (54) 2185.26, p.01, RMSEA .247, CFI
.463, SRMRw/b .195/.347) or a 2-factor model with ego deple-
tion and need for recovery as one factor and work engagement and
subjective vitality as another factor(2 (47) 174.87, p.01,
RMSEA .065, CFI .968, SRMRw/b .038/.172). MCFAs
thus suggest distinguishing among all four outcomes in our anal-
yses.
Analytical Procedure
Even though the present study lasted for 10 working days, mean
participation was 7.20 days (SD 2.45) resulting in 252 missing
data points. As outlined by Reise and Duan (2003) missing data
does not pose a problem for multilevel analysis provided that data
are missing completely at random and thus missing data is not
related to predictor or outcome variables under examination. To
examine whether missing data was random in our data sample we
introduced a dummy variable for missing data (0 missing data,
1no missing data) and correlated it with all relevant variables
in our study (age, sex, work-time, affective commitment, SCDs,
flow experience, ego depletion, need for recovery, work engage-
ment, and subjective vitality). All correlations except for age (r
.21 p.01) were below .10 and did not reach significance.
However, because participants’ age was not a core variable in our
study, our analyses provide strong support for the proposition that
missing data were completely at random in our data sample. Thus,
missing data were excluded in the subsequent analyses.
To test our hypotheses, we used the multilevel modeling soft-
ware MLWin (Rasbash, Steele, Browne, & Goldstein, 2012) be-
cause the day-level data (Level 1: SCDs, flow experiences, ego
depletion, need for recovery, work engagement, and subjective
vitality) were nested within the person-level data (Level 2: affec-
tive commitment) and MLWin considers the interdependence of
both levels. To analyze the mediating effects of flow experiences
in the relations between affective commitment and all four out-
comes, we applied a stepwise procedure to test for a 2–1–1
mediation as recommended by Zhang, Zyphur, and Preacher
(2009). First, the null model only included the intercept and was
used to estimate the between-subjects variance of flow experiences
and all outcomes (Intra-Class-Coefficient). In Model 1, we added
the person-level variables gender, age, working time, and affective
commitment at Level 2 to predict flow experiences. Model 2
included identical predictors as Model 1 (gender, age, working
time, and affective commitment) that were specified to predict
each of the four indicators of day-specific well-being (ego-
depletion, need for recovery, work-engagement and subjective
vitality). According to Zhang et al. (2009; p. 700) Model 1 esti-
mates the a-path from affective commitment to flow experiences
whereas the c-paths from affective commitment to all four out-
comes were ascertained on the basis of Model 2 (cf., Figure 1). In
Model 3, we included day-specific SCDs and flow experiences at
Level 1. Both predictors were centered around their person-mean
to reduce the risk of confounding effects (Enders & Tofighi, 2007).
This procedure allowed us to determine the b-paths from flow
experiences to all four outcomes. In addition, we aggregated and
added flow experiences at the person-level (Level 2) to examine
the indirect effects (c-c’; cf., Figure 1). These effects are a measure
for the reduction of the direct effect of affective commitment on all
outcomes resulting from integrating the aggregated measure of
flow experiences into the model. Thus, a large indirect effect
indicates that flow experiences mediate the relations between
affective commitment and employees’ well-being. Consistent with
the recommendations of Zhang et al. (2009), we used Sobel tests
to determine the significance of indirect effects. In Model 4, we
analyzed the proposed interaction of SCDs and flow experiences
on all outcomes by including a cross-product term of both predic-
tors. To avoid the biasing effects of multicollinearity when testing
interaction effects (Aiken, West, & Reno, 1991), we centered the
predictors before calculating the interaction term (Dollard,
Tuckey, & Dormann, 2012). Consistent with Hofmann and Gavin
(1998), Level 2 variables were centered on their grand mean.
Results
Table 1 displays the descriptive statistics, internal consistencies,
and correlations among the study variables. Before testing our
hypotheses, we examined the within- and between-person varia-
tions in all outcomes (state flow experiences, ego depletion, need
for recovery, work engagement, and subjective vitality). Flow
experiences exhibited a within-person variation of 42.5%. For ego
depletion, need for recovery, work engagement, and subjective
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6RIVKIN, DIESTEL, AND SCHMIDT
vitality, the proportions of within-person (Level 1) variance were,
respectively: 71.7%, 66.7%, 41.4%, and 65.6%. The high amounts
of within-person variance in the outcomes justify the application of
multilevel models.
Test of Hypothesis 1: Mediating Effects of State Flow
Experiences
Hypothesis 1 (a– d) predicted that state flow experiences medi-
ate the positive relations between affective commitment and all
four indicators of day-specific well-being. Model 1 in Table 2
indicates that affective commitment is positively related to state
flow experiences (a-path: ␥⫽.35; p.01). Furthermore, Model
2 for all outcomes in Tables 2 and 3 demonstrates that affective
commitment is related to all four day-specific indicators of well-
being with signs corresponding to expectations: Ego depletion
(c-path: ␥⫽⫺.09; p.01), need for recovery (c-path: ␥⫽⫺.10;
p.05), work engagement (c-path: ␥⫽.42; p.01), and
subjective vitality (c-path: ␥⫽.20; p.01). Additionally, as
predicted, interindividual flow experiences (aggregated) predicted
all four outcomes (b-paths [Model 3]: ego-depletion: ␥⫽⫺.10;
need for recovery: ␥⫽⫺.14; work engagement: ␥⫽.71; subjec-
tive vitality: ␥⫽.42; all ps .01). We conducted Sobel tests to
demonstrate that the indirect effects of affective commitment on
all four outcomes were significant. These tests provided strong
support for Hypothesis 1 (a– d) (ego-depletion:
IND
.03; need
for recovery:
IND
.05; work engagement:
IND
⫽⫺.25; sub-
jective vitality:
IND
⫽⫺.15; all ps.05).
Test of Hypothesis 2: Moderating Effects of State
Flow Experiences
Hypothesis 2 (a– d) predicted that state flow experiences mod-
erate (buffer) the adverse effects of SCDs on all day-specific
indicators of well-being. All Model 3s demonstrate significant
relations between SCDs and all outcomes with signs according to
Table 1
Means, Standard Deviations, Internal Consistencies (Cronbach’s Alpha), and Intercorrelations
Variable 12345678910
1. SCDs—noon (.88) .04 .14 .23 .05 .07
2. Flow experiences—noon .07 (.75) .15 .20 .60 .30
3. Ego depletion—evening .18 .33 (.86) .71 .27 .64
4. Need for recovery—evening .29 .45 .74 (.84) .27 .61
5. Work engagement—evening .03 .68 .37 .30 (.94) .44
6. Subjective vitality—evening .09 .55 .62 .70 .49 (.89)
7. Affective commitment .05 .28 .13 .08 .39 .16 (.79)
8. Gender
a
.07 .09 .22 .11 .02 .10 .06 —
9. Work time
b
.15 .09 .10 .18 .03 .03 .20 .39
10. Age .04 .29 .09 .01 .14 .17 .25 .29 .23
M2.53 5.02 1.89 1.85 4.36 4.36 4.55 1.31 1.74 39.51
SD .60 .87 .42 .45 .92 .86 1.22 .47 .44 14.08
Note. Cronbach’s alpha for day-level variables is mean internal consistencies averaged over all measurement days. Correlations below the diagonal are
person-level correlations (N90). Correlations above the diagonal are day-level correlations (N648). Numbers in bold p.05.
a
Gender (1 female, 2 male)
b
Work time (1 part-time, 2 full-time).
Table 2
Multilevel Estimates for Predicting Flow Experience, Ego-Depletion, and Need for Recovery
Flow experiences Ego depletion Need for recovery
Null model Model 1 Null model Model 2 Model 3 Model 4 Null model Model 2 Model 3 Model 4
Parameter SE SE SE SE SE SE SE SE SE SE
Fixed effects
00
Intercept 4.79
ⴱⴱ
(.10) 4.87
ⴱⴱ
(.40) 1.87
ⴱⴱ
(.04) 2.24
ⴱⴱ
(.19) 2.27
ⴱⴱ
(.18) 2.24
ⴱⴱ
(.18) 1.82
ⴱⴱ
(.04) 2.31
ⴱⴱ
(.19) 2.35
ⴱⴱ
(.17) 2.33
ⴱⴱ
(.17)
01
Gender .03 (.24) .17 (.11) .00 (.05) .00 (.05) .04 (.11) .02 (.05) .01 (.05)
02
Age .20 (.11) .02 (.05) .17 (.11) .16 (.11) .02 (.05) .04 (.10) .02 (.10)
03
Work time .05 (.25) .08 (.12) .08 (.11) .08 (.11) .25
(.12) .25
(.11) .27
(.11)
04
Affective commitment .35
ⴱⴱ
(.09) .09
(.05) .05 (.05) .06 (.05) .10
(.05) .04 (.05) .05 (.05)
05
Flow experiences (aggregated) .12
ⴱⴱ
(.05) .10
(.05) .16
ⴱⴱ
(.05) .14
ⴱⴱ
(.05)
10
SCDs .11
(.06) .17
ⴱⴱ
(.06) .18
ⴱⴱ
(.05) .22
ⴱⴱ
(.05)
20
Flow experiences (FE) .12
(.04) .11
(.04) .11
ⴱⴱ
(.03) .10
ⴱⴱ
(.03)
30
SCDs FE .23
ⴱⴱ
(.08) .19
ⴱⴱ
(.07)
Random effects
Level 1 intercept variance .59 .59 .33 .33 .30 .29 .26 .26 .24 .24
Level 2 intercept variance .80 .65 .13 .11 .10 .10 .13 .12 .10 .10
2
log (lh) 1700.44 1680.61 1231.10 1220.98 1194.72 1184.38 1100.84 1089.88 1045.34 1035.64
Note. Gender, age, work time, affective commitment, and flow experiences (aggregated) are person-level (Level 2) variables; all other predictor variables
are day-level (Level 1) variables.
p.05.
ⴱⴱ
p.01.
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7
DAY-SPECIFIC FLOW EXPERIENCES AND WELL-BEING
expectations (cf., Tables 2 and 3). Additionally, and theoretically
more important, the day-level interaction effects of SCDs and flow
experiences on all four outcomes were also significant (ego-deple-
tion: ␥⫽⫺.23; need for recovery: ␥⫽⫺.19; work engagement:
␥⫽.25; subjective vitality: ␥⫽.25; all ps.05).
To facilitate the interpretation of the interaction effects, we
depicted the interactions and performed simple slope tests, as
recommended by Preacher, Curran, and Bauer (2006). As shown in
Figure 2, the interactions are consistent with our Hypothesis 2
(a– d). In particular, on days with low levels of state flow experi-
ences, subjects reported an increase in day-specific ego-depletion
and need for recovery as a result of increased day-specific SCDs,
whereas on days with high levels of state flow experiences, the
positive relations between SCDs and both indicators of well-being
were weaker. For day-specific work-engagement and subjective
vitality, we identified similar interaction patterns: the negative
relations between SCDs and both outcomes were attenuated as a
function of state flow experiences. Thus, state flow experiences
buffered the day-specific adverse relations of SCDs with ego
depletion, need for recovery, work engagement, and subjective
vitality.
Additional Analyses
We conducted additional analyses to test whether affective
commitment may also be regarded as an outcome. Consequently,
Table 3
Multilevel Estimates for Predicting Work Engagement and Subjective Vitality
Work engagement Subjective vitality
Null model Model 2 Model 3 Model 4 Null model Model 2 Model 3 Model 4
Parameter SE SE SE SE SE SE SE SE
Fixed effects
00
Intercept 4.37
ⴱⴱ
(.10) 4.25
ⴱⴱ
(.40) 4.13
ⴱⴱ
(.28) 4.14
ⴱⴱ
(.28) 4.42
ⴱⴱ
(.09) 4.08
ⴱⴱ
(.38) 3.99
ⴱⴱ
(.33) 4.02
ⴱⴱ
(.34)
01
Gender .16 (.23) .05 (.08) .05 (.08) .12 (.22) .03 (.09) .03 (.09)
02
Age .09 (.10) .15 (.16) .17 (.17) .11 (.10) .10 (.20) .09 (.20)
03
Work time .18 (.25) .17 (.17) .19 (.17) .09 (.24) .11 (.21) .11 (.21)
04
Affective commitment .42
ⴱⴱ
(.10) .16
(.07) .17
(.07) .20
(.09) .05 (.09) .05 (.09)
05
Flow experiences (aggregated) .72
ⴱⴱ
(.07) .71
ⴱⴱ
(.07) .44
ⴱⴱ
(.09) .42
ⴱⴱ
(.09)
10
SCDs .15
(.08) .22
(.09) .18
(.10) .25
(.10)
20
Flow experiences (FE) .36
ⴱⴱ
(.05) .33
ⴱⴱ
(.05) .29
ⴱⴱ
(.07) .26
ⴱⴱ
(.07)
30
SCDs FE .25
ⴱⴱ
(.12) .25
(.13)
Random effects
Level 1 intercept variance .55 .55 .40 .38 1.03 1.03 .92 .91
Level 2 intercept variance .78 .63 .28 .28 .54 .51 .35 .36
2
log (lh) 1664.23 1644.01 1465.97 1453.73 1992.35 1983.68 1927.81 1924.03
Note. Gender, age, work time, affective commitment, and flow experiences (aggregated) are person-level (Level 2) variables; all other predictor variables
are day-level (Level 1) variables.
p.10
p.05.
ⴱⴱ
p.01.
Figure 2. Interaction effects of SCDs and flow experiences on ego depletion, need for recovery, work
engagement, and subjective vitality.
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8RIVKIN, DIESTEL, AND SCHMIDT
we examined whether SCDs and flow experiences may also pre-
dict affective commitment. Because affective commitment was a
Level 2 variable, which cannot be included as an outcome in
multilevel analysis, we aggregated SCDs and flow experiences to
the person level (Level 2) by computing the mean value of the
Level 1 values for each individual across all days. Afterward, we
specified hierarchical linear regression models. In the first step, we
entered demographic variables into the regressions. In the second
step, we added the main predictors SCDs and flow experiences. In
the third step, the interaction term between SCDs and flow expe-
riences was included into the regressions. To avoid biased estima-
tions due to multicollinearity, we centered both predictors prior to
calculating the cross-product term (cf., Aiken et al., 1991).
The results of our analyses demonstrated that flow experiences
were positively related to affective commitment (␤⫽0.41; p
.01). However, both SCDs (␤⫽⫺0.02; p[ns]) as well as the
interaction of SCDs and flow experiences (␤⫽0.06; p[ns]) had
no effect on affective commitment. The overall variance explained
by the model was R
2
.154, p.05. Consequently, our additional
analyses provide further support for our hypothesized model by
demonstrating that the SCDs and their interaction with flow ex-
periences did not predict affective commitment.
Discussion
Previous research has demonstrated convincing evidence for
affective commitment as a predictor of employees’ psychological
well-being (Meyer & Maltin, 2010). Thus, not only researchers but
also practitioners have focused on how organizations may help
foster employees’ affective commitment (Mathieu & Zajac, 1990).
However, today’s dynamic working environment is characterized
by continuous organizational change (e.g., mergers or acquisi-
tions), which can be associated with layoffs and thus may prevent
employees from developing strong affective commitment. Addi-
tionally, to effectively adapt to organizational change, employees
cannot rely on rigid, automatic, and habitual behavioral patterns
but rather must exert volitional self-control (e.g., Schmidt & Di-
estel, 2012). Our research sought to help employees preserve and
even enhance psychological well-being in such dynamic and
changing working environments. Hence, we examined flow expe-
riences as a mechanism that underlies the beneficial effects of
already established affective commitment and simultaneously
helps to protect employees’ well-being, particularly against the
adverse consequences of SCDs. On the basis of Meyer and Malt-
in’s (2010) theoretical framework, which suggests that the bene-
ficial effects of stable levels of employees’ commitment on well-
being are provided by autonomous regulation, we proposed that
flow experiences constitute peaks of intrinsic motivation during
which employees experience a high degree of autonomous regu-
lation. We further argued that highly committed employees are
more likely to experience flow at work because during work-
related tasks these employees are more willing and thus more
likely to invest energetic resources and in turn experience flow at
work more frequently. Furthermore, consistent with the notions a)
that SCDs impair psychological well-being by depleting regulatory
resources (Schmidt & Diestel, 2015) and b) that autonomous
regulation facilitates the recovery of regulatory resources (Mu-
raven, 2008; Muraven et al., 2008), we proposed that flow expe-
riences as states of high autonomous regulation, foster coping with
high job-related SCDs and prevent impaired well-being. Thus, we
predicted buffering effects of flow experiences on the adverse
day-specific effects of SCDs on well-being.
The results of our diary study provide strong support for both
propositions: First, state flow experiences mediate the beneficial
relations between affective commitment and indicators of well-
being. Thus, the beneficial effects of intraindividual affective
commitment are mediated by day-specific flow experienced during
work-related tasks. Second, flow experiences also buffer the neg-
ative day-level relation between SCDs and well-being. That is, on
days with high levels of flow experiences, employees were better
able to cope with SCDs whereas SCDs translated themselves into
impaired well-being when employees reported low levels of day-
specific flow experiences.
Theoretical Implications
Our research offers several contributions to the literature and
complements previous studies (such as Schmidt & Diestel, 2012;
Rivkin et al., 2015). First, we demonstrated how affective com-
mitment, state flow experiences and daily SCDs correspond with
indicators of psychological well-being at the day-level. Most stud-
ies on the beneficial effects of affective commitment were based
on cross-sectional samples and demonstrated that affective com-
mitment predicts interindividual differences in psychological well-
being (cf., Meyer & Maltin, 2010). Consequently, these studies did
not allow inferences regarding the underlying causal structure of
these relations. The present study further disentangles the positive
effects of commitment on well-being by demonstrating that highly
committed employees report higher levels of psychological
well-being over the course of 10 working days compared to
employees with low commitment. In addition, the present study
provides further support for Rivkin et al.’s (2015) initial results on
the beneficial effects of commitment on day-level indicators of
well-being by replicating these results in another sample and by
examining subjective vitality as an additional indicator of day-
specific well-being. Thus, in line with previous research our study
strongly supports the notion that affective commitment predicts
employees’ day-specific psychological well-being. Furthermore,
our research provides further evidence for the adverse day-specific
effects of SCDs on indicators of well-being as proposed by
Schmidt and Diestel (2015). Finally, our study demonstrates day-
specific flow as a strong predictor of employees’ psychological
well-being, even after controlling for SCDs as a stressor. Thus,
flow experiences function as another personal resource (Hobfoll,
2002) that contributes to employees’ well-being over and above
day-specific SCDs.
Second, past research on affective commitment has primarily
focused on the direct or interactive effects of commitment on
well-being (cf., Meyer & Maltin, 2010). For example, scholars
have hypothesized that employees with strong commitment are
either less likely to experience workplace stressors or have greater
access to resources (e.g., social support) to help them cope with
stressors (Meyer & Maltin, 2010). Drawing on the SDT (Deci &
Ryan, 1985; Ryan & Deci, 2000), Meyer and Maltin (2010)
proposed a well-founded theoretical framework in which they
disentangle the mechanisms that underlie the beneficial effects of
commitment. These authors argued that the relation between al-
ready established affective commitment and autonomous regula-
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9
DAY-SPECIFIC FLOW EXPERIENCES AND WELL-BEING
tion provides the beneficial effects of affective commitment on
well-being. However, we know of no empirical studies that have
examined this theoretical proposition. To our knowledge, the pres-
ent study is the first to examine and provide empirical evidence for
the underlying mechanisms that determine the beneficial effects of
commitment on employees’ psychological well-being. We inte-
grated literature on commitment, flow experiences, and well-
being, and examined flow experiences as the day-specific mani-
festation of autonomous regulation mediating the beneficial effects
of affective commitment as proposed by Meyer and Maltin (2010).
Thus, our research provides strong evidence for flow experiences
as the mechanism that underlies the beneficial effects of affective
commitment.
Finally, experimental findings in the field of self-control have
demonstrated that autonomous forms of regulation are less deplet-
ing than controlled forms of regulation (Muraven, 2008; Muraven
et al., 2008). Conceptualizing flow experiences as states of auton-
omous regulation, the results of our study provide evidence for
flow experiences as a buffering moderator of the adverse effects of
SCDs on well-being and thus support the results of these experi-
mental findings in an occupational setting. Furthermore, our study
supports central arguments of the SDT (Deci & Ryan, 1985; Ryan
& Deci, 2000) by demonstrating that flow experiences as day-
specific manifestations of autonomous regulation counteract the
depleting effects of SCDs. The results of our research thus dem-
onstrate that flow experiences can help employees to cope with
high day-specific SCDs.
Limitations and Suggestions for Further Research
Our research is subject to several limitations that must be
discussed. First, because we operationalized our study variables as
self-report measures, common method variance may have biased
the analyses in our research (Podsakoff, MacKenzie, Podsakoff, &
Lee, 2003). However, because of the temporal separation of the
measures and adequate construct validity, as demonstrated by
MCFAs, mutual contamination of the constructs appears unlikely.
Nevertheless, future research on the combined effects of SCDs and
flow experiences may benefit from using the experience sampling
method with multiple random measurement points across days to
measure flow (Csikszentmihalyi & Larson, 1987) because this
method may be more appropriate for identifying day-specific
fluctuations in flow experiences.
Second, although our research design separated two measure-
ment occasions by day, strong causal conclusions cannot be de-
rived from such correlational data structures. For example, a
general low level of psychological well-being may have influenced
the experience of SCDs during the course of a day. In addition,
Meyer and Maltin’s (2010) theoretical framework may also pro-
pose commitment as an outcome of flow experiences as a conse-
quence of basic needs satisfaction and their interaction with SCDs.
Although we are not able to completely rule out these possibilities,
previous research strongly suggests that SCDs predict psycholog-
ical well-being and not vice versa (e.g., Diestel et al., 2015).
Moreover, experimental research on SCDs and associated states of
ego depletion provides strong evidence for the causal directions
hypothesized in our research (Robinson & Demaree, 2007). Fi-
nally, demonstrating that a model with commitment as an outcome
receives only limited support by our data further strengthens the
validity of the model proposed in the present study. However,
further research could benefit from examining the development of
commitment over time to disentangle the potential reciprocal re-
lationship of autonomous regulation and commitment proposed by
Meyer and Maltin (2010).
Practical Implications
From a practical point of view, to promote employees’ psycho-
logical well-being at work and particularly to protect employees
from the adverse effects of day-specific SCDs our research sug-
gests fostering affective commitment, which in turn helps provide
day-specific flow experiences. In line with SDT and Meyer and
Maltin’s (2010) theoretical framework, satisfaction of basic psy-
chological needs is expected to facilitate commitment as well as
flow experiences. Thus, to enhance well-being, organizations
should satisfy employees’ needs for autonomy, competence, and
relatedness. For example, need for autonomy can be satisfied by
reducing the number of rules and formal procedures and giving
employees the opportunity to decide when and how they perform
tasks (Van den Broeck, Vansteenkiste, De Witte, & Lens, 2008).
Furthermore, need for competence may be satisfied by stimulating
the utilization of various skills and thereby enhance employees’
skills levels and distribute tasks, which correspond with employ-
ees’ skill levels (Van den Broeck et al., 2008). Finally, need for
relatedness can be satisfied by organizing corporative events and
establishing a culture of acceptance and support in the organization
(Fernet, Austin, Trépanier, & Dussault, 2013). In turn, satisfaction
of basic psychological needs is expected to facilitate commitment
and associated flow experiences, which in turn help to promote
psychological well-being. Furthermore, previous research has
demonstrated that leadership can have a strong influence on com-
mitment (Mowday, Porter, & Steers, 1982). Servant leadership is
a leadership style, which focuses on integrating the interests of
different organizational stakeholders and in particular on the em-
powerment of employees to release their full potential (Greenleaf,
2002). Previous research has demonstrated that among other out-
comes, servant leadership predicts commitment (Walumbwa, Hart-
nell, & Oke, 2010). Consequently, a leadership training based on
the principles of servant leadership (e.g., Bröker, Rivkin, & Gün-
newig, 2015) may help leaders to enhance employees’ well-being
by increasing commitment and associated flow experiences.
From an employee’s perspective, because states of flow expe-
riences are difficult to initiate and very fragile, it is also necessary
to maintain such states to enhance job performance and well-being.
Interruptions of work such as distractions or intrusions can impair
flow experiences (Jett & George, 2003) or even prevent individ-
uals from experiencing flow at all. Additionally, because flow is
such a pleasant state (cf., Nakamura & Csikszentmihalyi, 2002),
interrupting flow experiences is likely to be associated with neg-
ative outcomes such as distress or a decrease in mood. Currently,
by means of electronic communication (e-mails, phone calls, mes-
sages), most employees are subject to numerous sources of inter-
ruptions at work (e.g., by coworkers, customers, or even family
members). Thus, to facilitate flow experiences, employees must
reduce possible sources of interruption, particularly when perform-
ing solitary work. This can be achieved, for example, by turning
off electronic communication devices such as phones or determin-
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This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
10 RIVKIN, DIESTEL, AND SCHMIDT
ing specific time slots for checking e-mails and messages (Jett &
George, 2003).
Thus, to foster psychological well-being, it is necessary for
organizations and employees themselves to promote affective
commitment at work and thereby help employees get into and
maintain states of flow experiences.
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Received August 27, 2015
Revision received March 22, 2016
Accepted March 23, 2016
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13
DAY-SPECIFIC FLOW EXPERIENCES AND WELL-BEING
... Similarly, job satisfaction and organizational commitment have been shown to be directly affected by work stress levels in military personnel (Dobreva-Martinova, 2002). In a meta-analysis, however, affective organizational commitment turned out to be a crucial factor for lower stress levels and absenteeism, and higher performance and work engagement (Meyer et al., 2002; see also Rivkin et al., 2018). Job satisfaction and loneliness were negatively related before the pandemic (Tabancali, 2016;Bakır and Aslan, 2017). ...
... Cross-sectional direct analyses: How are individual and organizational soldier student factors related to loneliness, life satisfaction, and COVID-19 stress at the same time point? Specifically, we anticipated relations in accordance with prior research during the pandemic (for personality traits; see Carvalho et al., 2020;Anglim and Horwood, 2021;Gubler et al., 2021;Modersitzki et al., 2021;Nikčević et al., 2021;Shokrkon and Nicoladis, 2021;Zacher and Rudolph, 2021a) or before the pandemic, respectively (for organizational factors; see Dobreva-Martinova, 2002;Meyer et al., 2002;Moon and Jonson, 2012;Rivkin et al., 2018;Lambert et al., 2021). All expected relations are displayed in Table 1. ...
... Further, commitment was unrelated to either of the coping strategies. Although the positive effect of commitment on psychological health is well established, the underlying mechanisms are hardly examined (Rivkin et al., 2018). In our study, we found no evidence for coping strategies as mechanisms of commitment's effect on psychological health. ...
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... Moreover, Kuhnle et al. (2012) pointed that self-control is a good predictor of flow experiences in eighth graders. This being the case, Rivkin et al. (2018) found that higher levels of flow experiences would enhance self-control demands and would ultimately result in higher well-being. The authors also claimed that the experience of flow revealed higher levels of intrinsic motivation (Rivkin et al., 2018). ...
... This being the case, Rivkin et al. (2018) found that higher levels of flow experiences would enhance self-control demands and would ultimately result in higher well-being. The authors also claimed that the experience of flow revealed higher levels of intrinsic motivation (Rivkin et al., 2018). Finally, as for social skills, Walker (2010) examined whether the social flow was preferred to solitary flow and the results of his survey study revealed that social flow was more enjoyable than solitary flow. ...
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Given the fundamental role of emotional intelligence (EI) in learning, especially in virtual learning contexts where individuals experience more stress and anxiety, the need to understand and recognize one’s own feelings and the mutual feelings of peers has gained more importance. Flow as the ultimate state in harnessing emotions in the service of performance and learning has been introduced as the main reason for one’s willingness to perform activities which are connected to no external motivation. In this regard, the present study was conducted to first introduce a new educational program to enhance the EI level in the English as a foreign language (EFL) online education environment and next to investigate the possibility of raising EFL learners’ perceived flow. To achieve these goals, the study recruited a sample of 67 EFL learners who were next divided into experimental (n = 32) and control (n = 35) groups. The experimental group received the EI intervention over ten weeks and the control group received the ordinary online EFL instruction. Data were collected through EI and flow questionnaires and semi-structured interviews which focused on learners’ perception of the EI intervention and signs of enhanced flow. Statistical analysis of the data showed a positive effect of the program on the learners’ EI and their perceived flow. The study emphasizes the role of applying positive emotions in making language learners more engaged in online classroom tasks.
... In theory, people who possess characteristics of high investment, intense involvement, and personal commitment are more likely to experience flow than those who do not (Csikszentmihalyi, 1997). Commitment appears to correlate positively with flow (Rivkin et al., 2018). Therefore, examining a possible relationship between singing commitment and flow, concurrently while determining effects of the two predictors on MIL, is theoretically important to achieve a more comprehensive understanding of MIL formation. ...
... There are two possible explanations for these results. First, since singing commitment requires consistently focused behavior associated with willingness (Lamont et al., 2018), it predicts flow that often occurs by focusing on the activity (Csikszentmihalyi, 1997;Rivkin et al., 2018). Second, singing commitment commonly correlates with participants receiving positive feedback from the activity (Page-Shipp et al., 2018). ...
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Identifying predictors of meaning in life (MIL) among older adults is important to promote their well-being. Therefore, to provide practitioners with information to help older adults enhance well-being, we examined a mediated model in which singing commitment is predictive of flow, and flow is predictive of MIL. A total of 305 older adults participated in our study. Participants completed an in-person survey including singing commitment, flow, and MIL scales. We analysed data using structural equation modeling. Results indicated that high levels of singing commitment predicted high levels of flow, and high levels of flow predicted high levels of MIL. The relationship between singing commitment and MIL was fully mediated by flow, and there were no residual direct effects. We discuss implications of these results in terms of increasing meaning in later life, in particular, facilitating flow through singing commitment among older adults who do not have high levels of singing skills.
... First, in order to maintain focused on tasks, impulses to process tasks in a shallow way or to even omit important subtasks have to be controlled, this is especially true when tasks are aversive (Schmidt & Diestel, 2015). Several studies indicate that dealing with such demands to control impulses positively relates to depletion (Gombert et al., 2020;Rivkin et al., 2018). ...
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When conceptualizing work performance as requiring self-control, scholars often employ a resource-depletion perspective. However, this perspective neglects the role of self-control motivation and self-regulation strategies. In this diary study, we examine self-control motivation (viz. motivation to control impulses) and depletion at the beginning of work and at midday as predictors of afternoon task performance. Additionally, we investigate morning aversive tasks as an antecedent of increased depletion and decreased self-control motivation. Further, we examine the role of self-regulation strategies (organizing, meaning-related strategies, self-reward) for maintaining and improving performance when depleted or low in self-control motivation. Data from a 2-week diary study with 3 daily measurements (N = 135 employees; n = 991 days) was analyzed. Multilevel path modeling showed that self-control motivation at the beginning of work and depletion at midday predicted afternoon task performance. We found that self-reward in the afternoon counteracts the negative relationship between depletion and task performance. Further, we found an indirect effect from morning aversive tasks on task performance via depletion at noon buffered by afternoon self-reward. Organizing and meaning in the afternoon were positively related to afternoon task performance. Findings suggest that self-control motivation is important for task performance, in addition to low depletion. Moreover, results highlight that self-regulation strategies are beneficial for task performance.
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Abstract: The performance of an activity can have positive incentives per se and individuals may engage in an activity purely for the enjoyment of it. The engagement due to the enjoyment of an activity is often called intrinsic motivation. Beside this understanding of intrinsic motivation other conceptions are presented (self-determination, experience of competence, interest and involvement, mean-end-correspondence, learning-goal orientation). In doing so, the problem became evident, that the term intrinsic motivation refers to different, even conflicting conceptions. With the “Extended Cognitive Model of Motivation” different aspects of motivation are theoretically integrated. Instead of using the term intrinsic motivation, we use the term activity-related motivation. Qualitative and quantitative ways to measure activity-related incentives are outlined. Finally we present an intensively studied activity-related incentive, i.e. the experience of flow.
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Book
I: Background.- 1. An Introduction.- 2. Conceptualizations of Intrinsic Motivation and Self-Determination.- II: Self-Determination Theory.- 3. Cognitive Evaluation Theory: Perceived Causality and Perceived Competence.- 4. Cognitive Evaluation Theory: Interpersonal Communication and Intrapersonal Regulation.- 5. Toward an Organismic Integration Theory: Motivation and Development.- 6. Causality Orientations Theory: Personality Influences on Motivation.- III: Alternative Approaches.- 7. Operant and Attributional Theories.- 8. Information-Processing Theories.- IV: Applications and Implications.- 9. Education.- 10. Psychotherapy.- 11. Work.- 12. Sports.- References.- Author Index.
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Chapter
Introduction DEFINITION Motivation can be defined as the “activating orientation of current life pursuits toward a positively evaluated goal state”. (Rheinberg, 2004a, p. 17) The purpose of a definition of this kind is to describe the essential qualities of a term as succinctly as possible. Finer points have to be considered separately. In the present case, at least two points need further elaboration: The “positively evaluated goal state” may be to avoid or prevent undesired events. The qualities of avoidance motivation may differ from those of approach motivation (Chapters 4–9). The second point is rather more complicated, and is the focus of the present chapter. When, as here, the definition of motivation focuses on a goal state, there is a risk of premature conclusions being drawn about where the incentives motivating behavior are located. It is easy to assume that the goal state has incentive value, and that the pursuit of the goal-directed activity is purely instrumental to bringing about that goal state, i.e., that the appeal of an activity resides solely in its intended outcomes. This is the approach taken by scholars such as Heckhausen (1977b) and Vroom (1964). Unfortunately, this rather rash conclusion sometimes holds and sometimes does not. It is beyond question that people often engage in activities simply because they want to achieve or modify a particular goal state.
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Objectives: This research aimed to shed light on the relationship between flow experience and performance in sports using a marathon race as an example. We hypothesized that flow influences the marathon race performance by an indirect rewarding effect.We assumed that the positive quality of flow experience rewards the pre-race running activity and thereby enhances training behavior which again leads to high race performance. A methodological issue of the this was to compare the retrospective with the experience-sampling measure of flow. Design: Three studies with marathon runners (Ns ¼ 109, 112, 65 for Studies 1, 2, and 3, respectively) were conducted. Method: They measured flow experience four times during a marathon race either retrospectively (Studies 1 and 2) or using an experience-sampling method during the race (Study 3). Additionally race performance and future running motivation (Studies 1, 2, and 3), pre-race training behavior (Studies 2 and 3) and flow experience in training (Study 3) were measured. Results: The results confirmed the hypothesis showing that flow during a marathon race is related to future running motivation, but is not directly linked to race performance. Instead, race performance was predicted by pre-race training behavior (Studies 2 and 3) which again was fostered by flow during the training (Study 3). The descriptive flow courses of the retrospective and the experience-sampling flow measures were comparable but also showed important differences. Conclusions: We critically discuss the practical implications of the rewarding effect of flow on performance and the advantages of the retrospective and experience-sampling measure of flow.