Flow Stress & Health

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RESEARCH ARTICLE
How is Flow Experienced and by Whom? Testing Flow
among Occupations
Susana Llorens
*†
, Marisa Salanova & Alma Mª Rodríguez
WONT Research Team, Universitat Jaume I, Spain
Abstract
The aims of this paper are to test (1) the factorial structure of the frequency of flow experience at work; (2) the flow
analysis model in work settings by differentiating the frequency of flow and the frequency of its prerequisites; and
(3) whether there are significant differences in the frequency of flow experience depending on the occupation. A
retrospective study among 957 employees (474 tile workers and 483 secondary school teachers) using multigroup
confirmatory factorial analyses and multiple analyses of variance suggested that on the basis of the flow analysis
model in work settings, (1) the frequency of flow experience has a two-factor structure (enjoyment and absorption);
(2) the frequency of flow experience at work is produced when both challenge and skills are high and balanced;
and (3) secondary school teachers experience flow more frequently than tile workers. Copyright © 2012 John Wiley
& Sons, Ltd.
Received 20 September 2010; Revised 15 April 2012; Accepted 18 April 2012
Keywords
frequency of flow experience; work setting; prerequisites; occupation
*Correspondence
Susana Llorens, Department of Social Psychology, Universitat Jaume I, Avenida Sos Baynat, s/n. 12071, Castellón, Spain.
†
Email: llorgum@uji.es
Published online in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/smi.2436
The study of human strengths and optimal functioning
has drawn a growing amount of attention in modern
organizations, and following the premises of Positive
Psychology, they have become increasingly more inter-
ested in optimizing positive psychosocial emotions and
experiences. One of the positive phenomena that is
receiving attention is flow, which is an optimal experi-
ence that is common to a wide range of activities.
Different scholars have described the experience of
flow not only in daily and entertainment activities
(e.g. Csikszentmihalyi, 2003; Delle Fave & Massimini,
2005) but also in work settings (e.g. Bakker, 2005;
Salanova, Bakker, & Llorens, 2006).
Despite the advances in the study of flow at work,
more empirical research is needed in order to (1) identify
the dimensionality of the flow experience at work; (2)
differentiate the frequency of flow experience at work
from its prerequisites; and (3) test for significant differ-
ences in the frequency of flow experience among different
occupations. In the present study, we contribute to
previous research questions by testing (1) the factorial
structure of the frequency of flow experience (i.e. enjoy-
ment, absorption and intrinsic interest) at work in two
samples (tile workers and secondary school teachers);
(2) the flow analysis model in work settings by differenti-
ating the frequency of flow experience at work and the
frequency of its prerequisites (i.e. challenge and skills);
and (3) whether there are significant differences in the
frequency of flow experiences depending on the occupa-
tion (tile workers and secondary school teachers) on the
basis of the flow analysis model in work settings.
Flow experiences at work: The concept and
its measurement
The study of flow constitutes one of the new trends that
have emerged in Positive Psychology. Originally, this
concept was studied by means of interviews with
artists, athletes, composers, dancers, scientists and so
on (see Csikszentmihalyi, 1975, 1990, 1997, 2003).
These particular samples described flow as an experi-
ence in their activities that made them feel good and
motivated because they were doing something worth-
while for its own sake. The study of the experience of
flow has been extended to different contexts such as
daily activities (Delle Fave & Massimini, 2005), leisure
(Csikszentmihalyi & LeFevre, 1989), study (Delle Fave
& Bassi, 2000) and work settings (Salanova et al., 2006).
On the basis of the concept of flow, and according to
Csikszentmihalyi (1997; p. 30), the flow experience
‘tends to occur when a person’s skills are fully involved
Stress Health (2012) © 2012 John Wiley & Sons, Ltd.

in overcoming a challenge that is just about manage-
able. Optimal experiences usually involve a fine balance
between one’s ability to act and the available opportu-
nities for action’. Different authors (e.g. Bakker, 2005;
Salanova et al., 2006) have developed the concept of
flow specifically for work activities. Three of the
advances in the study of the flow experience at work
are the following: (1) flow at work is considered a
short-term peak experience; (2) it is assessed by single
administration retrospective instruments; and (3) flow
experience (and its prerequisites) is tested by frequency
and not by intensity (see Bakker, 2001, 2008). Thus,
considering the nature of work context, flow at work
refers to a short period, i.e. the preceding days of weeks
while working (Bakker, 2001, 2005, 2008). Conse-
quently, the most useful procedure to capture the essence
of flow at work is through a single retrospective instru-
ment administration (e.g. Bakker, 2008; Salanova et al.,
2006; Mäkikangas, Bakker, Aunola, & Demerouti,
2010). Moreover, the flow at work concept (as well as
its prerequisites) is usually tested not by intensity but
by frequency. Specifically, different scholars test flow
experience at work in terms of frequency as the way to
assess how often employees experience flow at work
(e.g. Bakker, 2005 and 2008; Demerouti, 2006; Jackson
& Eklund, 2002, 2004; Mäkikangas et al., 2010; Salanova
et al., 2006). Indeed, and according to Bakker (2008; pp.
400, 401, 409, 411), flow is tested by frequency and not
by intensity for different reasons: (1) the dimensions of
flow experience at work are enjoyment, absorption and
intrinsic interest, which have been traditionally tested
by frequency; (2) this method of research (frequency) is
applied on several studies related to different forms of
subjectivewell-being, including work engagement, burn-
out, depression and psychosomatic health; and finally,
(3) testing flow experience (and prerequisites) by
frequency (instead of intensity) is not a casualty but
instead a practical approach implemented by Human
Resources Development Company for promoting context
variables that can increase flow experiences at work.
Taking into consideration all of these features, Bakker
(2001) developed the WOrk-reLated Flow scale (WOLF;
Bakker, 2001, 2008). This is one of the most popular
single administration instruments for testing flow experi-
ence at work. Despite being a single administration retro-
spective instrument, it is a scientific, reliable and valid
scale to test flow at work (Bakker, 2001, 2008). Items
referred to flow at work as a momentary experience
related with a specific activity rather than a general
behaviour during work. Basically, they defined flow at
work as an optimal experience that is characterized by
high frequency in enjoyment (i.e. the emotional compo-
nent), high frequency in absorption (i.e. the cognitive
component) and high frequency in intrinsic interest
(i.e. the motivation component) at work. Enjoyment
refers to a particular feeling of happiness that is the
outcome of cognitive and affective evaluations of the
flow experience (cf. Diener, 2000; Diener & Diener,
1999). The state of being fully concentrated and
engrossed in one’s work, whereby time passes quickly
and one has difficulties detaching oneself from work,
characterizes absorption (Ghani & Deshpande, 1994;
Lutz & Guiry, 1994; Moneta & Csikszentmihalyi, 1996;
Novak & Hoffman, 1997). Intrinsic interest refers to
the need to perform a certain work-related activity with
the aim of experiencing inherent pleasure and satisfac-
tion in the activity (cf. Deci & Ryan, 1985; Moneta &
Csikszentmihalyi, 1996; Novak & Hoffman, 1997;
Trevino & Webster, 1992). Intrinsically motivated
employees are continuously interested in the work they
are involved in (Harackiewicz & Elliot, 1998), and they
want to continue their work and are fascinated by the tasks
they perform (Csikszentmihalyi, 1997).
The elements that make up this three-dimensional
structure (i.e. enjoyment, absorption and intrinsic inter-
est) have been proposed as the main components of the
frequency of flow experience at work in a vast amount
of research. For example, high correlations have been
obtained in music teachers and students (Bakker,
2005), in secondary school teachers (Salanova et al.,
2006), in workers from small and medium-sized compa-
nies (Demerouti, 2006) and in line managers (Nielsen &
Cleal, 2010). On the basis of Information and Commu-
nication Technology users (students and workers),
Rodríguez, Schaufeli, Salanova, and Cifre (2008) used
confirmatory factor analyses (CFA) to show that the
flow experience is composed of the expected three
independent but related dimensions, i.e. enjoyment,
absorption and intrinsic interest. Yet, the bidimen-
sionality of flow (enjoyment and absorption) has also
been noted in other studies (Ghani & Deshpande,
1994; Skadberg & Kimmel, 2004). Recently, Rodríguez,
Cifre, Salanova and Åborg (2008) used CFA to provide
evidence of the genuine core dimensions of frequency of
flow experience: enjoyment and absorption in Spanish
and Swedish university students. Thus, it seems that
the role played by intrinsic interest is that of an anteced-
ent of the frequency of flow experience rather than one
of its components. This basic confusion regarding the
structure of the flow experience needs further studies
in order to clarify the structure of the frequency of flow
experience, specifically in work contexts. Consequently,
one of the aims of the current study is to use multigroup
CFA to investigate the factorial structure of frequency of
flow at work in order to test the invariance of the
frequency of flow structure in work settings (tile work-
ers and secondary school teachers). More particularly,
we expect that:
Hypothesis 1 A traditional three-factor model including
enjoyment, absorption and intrinsic interest (tested by
frequency) will fit the data better than a two-factor model
(in which items are assumed to be loaded in enjoyment
and absorption) or a one-dimensional model (all items
are assumed to be loaded on one underlying undifferenti-
ated flow dimension).
FLOW EXPERIENCE S. Llorens, M. Salanova and A. M. Rodríguez
Stress Health (2012) © 2012 John Wiley & Sons, Ltd.

What makes a job allow to experience flow
more frequently?
The frequency of flow experience is a complex concept
not only because of the difficulty involved in operationa-
lizing it but also because the experience itself is often
confounded with its prerequisites. This confusion has
been common in research even as far back as the original
description by Csikszentmihalyi (1975, 1990, 1997).
This author defined the flow experience by means of
nine characteristics: (1) clear goals; (2) immediate and
unambiguous feedback; (3) personal skills well suited
to given challenges; (4) merger of action and awareness;
(5) concentration on the tasks at hand; (6) a sense of
potential control; (7) a loss of self-consciousness; (8) an
altered sense of time; and (9) experience that becomes
autotelic. Consequently, the flow experience itself and it
prerequisites are mixed up in his definition. However,
it is generally accepted that flow prerequisites, the flow
experience itself and flow consequences are aspects of
flow that are closely related but should nevertheless be
distinguished (Chen, Wigand, & Nilan, 1999; Ghani &
Deshpande, 1994; Trevino & Webster, 1992). Recent
research attends to the differentiation among flow prere-
quisites and the flow experience itself in different con-
texts such as public and private schools, web users,
online shopping and physical activity (i.e. Bassi & Delle
Fave, 2011; Chen et al., 1999; Guo & Poole 2009;
Kawabata & Mallett, 2011; Keller & Bless 2008; Keller
& Blomann 2008; Mesurado 2009; Pearce, Ainley, &
Howard, 2005). Despite this advance, it seems that more
research is needed to clarify this distinction in work
settings where the confusion still remains. For example,
in Nielsen and Cleal (2010), flow experience consists of
nine items measuring (1) control of the situation; (2)
enjoyment; (3) activity; (4) clarity; (5) skills; (6) chal-
lenge; (7) performance; (8) absorption; and (9) involve-
ment. Again, the flow experience and its prerequisites are
mixed together.
In order to determine what makes a job allow to
experience flow and to differentiate it from the experience
of flow itself, Csikszentmihalyi (1975) developed the
Channel Model. Originally, he considered the flow
experience as a situation in which challenges match
people’s skills. Subsequently, the Experience Fluctuation
Model (EFM; Massimini & Carli, 1988) proposed that
flow would occur when there is a balance between high
levels of both challenges and skills. Specifically, ‘when
both challenge and skills are high, the person is not only
enjoying the moment, but is also stretching his or her
capabilities with the likelihood of learning new skills and
of increasing self-esteem and personal complexity’
(Csikszentmihalyi & LeFevre, 1989; p. 816). Despite of
the empirical evidence of the EFM in different contexts,
i.e. educational, technological, and competitive and recre-
ational sports (e.g. Catley & Duda, 1997; Chen et al.,
1999; Csikszentmihalyi & Rathunde, 1993; Moneta &
Csikszentmihalyi, 1996), any study has tested this model
in work settings using questionnaires. Actually, EFM
was designed to tackle the experience fluctuation in terms
of intensity (instead of frequency) and based on a
repeated data collection (instead of single administration
questionnaire) (e.g. Csikszentmihalyi, Larson, & Prescott,
1977; Hektner, Schmidt, & Csikszentmihalyi, 2007).
Consequently, this model is inadequate to test flow at
work since this experience has been traditionally tested
in terms of frequency and on a single administration ques-
tionnaire (e.g. Bakker, 2005, 2008; Salanova et al., 2006;
Mäkikangas et al., 2010). Concretely, Bakker (2008; p.
411) posted that, considering the nature of work, ‘it is
technically not possible (yet) to measure real-time flow
(while it happens), and this makes it difficult to map the
precise prevalence of peak experiences at work’.
Notwithstanding the relevance of previous models, it
is necessary to develop a specific model of analyses of
flow in work settings. On the basis of the premises of
previous models of flow, this model of flow at work
should take into account the following: (1) previous
research on flow experience; (2) the distinction between
flow experience and its prerequisites; and (3) the charac-
teristics of the measure of flow experience at work, which
is tested by frequency (instead of intensity) and using
single administration questionnaires. More specifically,
and on the basis of previous research (e.g. Delespaul, Reis
& de Vries, 2004; Eisenberger et al., 2005), our flow
analysis model in work settings assumes that employees
would experience flow more frequently when their job
demands are perceived as highly challenging but they
also believe that they have the skills to cope with
the demands.
Similar to predecessor models of flow (Csikszentmihalyi
& Csikszentmihalyi, 1988; Delle Fave & Bassi, 2000; Delle
Fave & Massimini, 2005; Massimini & Carli, 1988), our
flow analysis model in work settings also proposes eight
areas, called channels, which represent the following
experiences: Channel 1 (high frequency challenge and
medium frequency skills are perceived) corresponds to
arousal; Channel 2 (high frequency challenge and high
frequency skills) corresponds to flow; Channel 3 (medium
frequency challenge and high frequency skills), control is
experienced; Channel 4 (low frequency challenge and high
frequency skills) characterized by relaxation; Channel 5
(low frequency challenge and medium frequency skills),
boredom is experienced; Channel 6 (low frequency
challenge and frequency skills), a state of disengagement
and physical disorganization is produced, corresponding
to apathy; Channel 7 (medium frequency challenge and
low frequency skills), worry is experienced; and finally,
Channel 8 (high frequency challenge and low frequency
skills) corresponds to anxiety.
The second relevant point of our flow analysis model
in work settings is that the balance among high frequency
challenge and high frequency skills is not necessarily
objective but depends on employees’perceptions or
beliefs, since the flow experience at work is a subjective
experience (see Massimini, Csikszentmihalyi, & Carli,
S. Llorens, M. Salanova and A. M. Rodríguez FLOW EXPERIENCE
Stress Health (2012) © 2012 John Wiley & Sons, Ltd.

1987, for an original version of measure of flow as inten-
sity). Different scholars have shown that flow experiences
at work are enhanced by the quality of the work experi-
ences rather than the objective complexity of the tasks.
In particular, studies in work settings (Salanova et al.,
2006) found that those people with high beliefs in their
skills experienced flow more frequently than those with
low beliefs in their skills. Thus, high perceived skills,
which are well matched with high perceived challenges,
are necessary prerequisites to experience flow (Salanova
et al., 2006).
Despite the empirical evidence of flow experience at
work, there is a lack of research in which the frequency
of flow experience (i.e. enjoyment, absorption and
intrinsic interest) and the frequency of its prerequisites
(i.e. high balanced perceptions of challenges and skills)
are tested together, but at the same time differentiated,
in the same study. In order to solve these tricky questions
about the distinction of the frequency of flow experience
and its prerequisites, more studies need to be conducted
specifically in work contexts. Hence, the second aim of
the current study is to test, in the same study, the
frequency of the flow experience and its prerequisites
(i.e. challenge and skills) at work (tile workers and
secondary school teachers) on the basis of the flow anal-
ysis model in work settings. We expect that:
Hypothesis 2 Workers, independently of occupation, who
perceive balanced high frequency of challenge and skills
in their jobs will experience flow more frequently than
others who perceive different combinations between
challenge and skills.
Looking for the jobs in which flow is most
frequently experienced?
Different scholars have tested the frequency of flow
experience in different work settings, e.g. music teachers
(Bakker, 2005), secondary school teachers (Salanova
et al., 2006), Information and Communication Tech-
nology users (Rodríguez, Schaufeli et al., 2008), line
managers (Nielsen & Cleal, 2010), employment agency
workers (Mäkikangas et al., 2010) and workers from
different occupations (Demerouti, 2006; Salanova,
Martínez, Cifre, & Schaufeli, 2005). This research pro-
vides evidence that the frequency of flow experience
can be felt not only by artists or athletes but also by
workers. However, none of these studies explore the
differences in the frequency of the flow experience and
its prerequisites across different kinds of jobs on the
basis of a flow analysis model in work settings.
According to previous research on intensity of flow
(Csikszentmihalyi, 1975; Delle Fave & Bassi, 2000;
Massimini & Carli, 1988), and by extending this
evidence to the flow analysis model in work settings,
it is plausible to expect that workers in any occupation
may experience flow frequently while doing the tasks
their job involves. In particular, this frequency of flow
experience should be produced when prerequisites of
frequency of challenge and skills are both high and
balanced. Employees (regardless of the occupation)
could experience flow more frequently when the tasks
in their jobs are perceived as challenging and they also
perceive themselves as having high frequencies in skills
that enable them to cope with those challenging tasks
(e.g. Salanova et al., 2006). Despite the experience of
the frequency of flow regardless of the type of occupa-
tion, previous results (Salanova et al., 2005) from a study
on 770 workers in different jobs (i.e. office workers,
university lecturers, technical staff, laboratory workers,
sales staff, tile workers and managers) showed significant
differences in the frequency of flow experience. More
specifically, managers and university lecturers (i.e. both
employees working with ‘people’)experiencedflow more
frequently than the other occupational workers, particu-
larly more than office and tile workers (i.e. employees
working with ‘data and things’). It seems that, as expected,
more challenging occupations increase the possibilities
of experiencing flow at work more frequently if workers
believe that they have the skills needed to cope with the
challenges of their job. The authors proposed that the
frequency of the flow experience does not depend on
ageorgenderbutonthetypeofoccupation.Workersin
intrinsically more motivating jobs (e.g. managers, supervi-
sors and university lecturers) could experience flow at
work more frequently than those in other intrinsically less
motivating professions (e.g. production workers). Fur-
thermore,theynotedthatthemorecreativejobs,i.e.work
settings in which job resources are higher (e.g. autonomy,
feedback and variety) (Warr, 1990, 2007), allowed
employees to experience flow at work more frequently.
In these positive contexts, workers may become engrossed
in carrying out the activity and not only in the results of
the task. Consequently, they could experience internally
motivating activities more frequently than other workers
in more routine and less creative jobs, e.g. production
workers.
Although these previous results from Salanova et al.
(2005) are relevant, only the differences in the frequency
of flow experience itself were tested among occupations.
Moreover, in this study the frequency of flow experience
was tested according to a different conceptualization,
i.e. absorption, intrinsic satisfaction and skills, which
confounds the experience with the prerequisites. More
research is needed in work settings in order to test in
which jobs flow more frequently is experienced than
others by taking into account the flow experience itself
and its prerequisites. With this aim in mind, the third
objective in this study is to explore whether there are
significant differences in the frequency of the flow expe-
rience and in its prerequisites according to the occupa-
tion. Two specific types of occupations that are
characterized by working with different elements/users
(see Fine & Cronshaw, 1999) were tested: production
workers (tile workers) and human-services employees
(secondary school teachers). These specificsampleswere
selected for two main reasons: (1) the theoretical one is
FLOW EXPERIENCE S. Llorens, M. Salanova and A. M. Rodríguez
Stress Health (2012) © 2012 John Wiley & Sons, Ltd.

that there is evidence in favour of the idea that jobs char-
acterized by frequent challenge, and thus more creative
jobs (in our case, secondary school teachers), enhance
the probability of employees experiencing flow more
frequently than employees in less frequent challenging,
less creative and less complex jobs (in our case, tile work-
ers); and (2) the empirical reason is that the only study on
the frequency of flow experience and different occupa-
tions that we know of, i.e. Salanova et al. (2005), provided
evidence to show that flow experience was more frequent
for managers and university lecturers than for office and
tile workers. Hence, we expect to find that:
Hypothesis 3 Therewillbesignificant differences in the
frequency of the flow experience between workers from
two different occupations: tile workers (i.e. production
workers) and secondary school teachers (i.e. human-
services employees). More specifically, we expect second-
ary school teachers to experience flow more frequently
than tile workers.
Method
Sample and procedure
The present study used a cross-sectional design involving
a total sample of 957 Spanish employees (53% women).
Self-report questionnaires were distributed among two
samples: (1) Sample 1 consisted of 474 (83% response
rate) employees from the tile industry (i.e. production
workers; 51% of the total sample) from three private
ceramic industries; and (2) Sample 2 consisted of 483
(81% response rate) secondary school teachers (i.e.
human-services employees; 49% of the total sample)
from 34 schools (83% of them public). The mean age
of the sample as a whole was 36 years and 8 months
(SD = 9 years) with ages ranging from 18 to 62 years. In
Sample 1 (i.e. employees from the tile industry,
N= 474), 52% were men, ages ranged from 18 to 62 years
(M= 33; SD = 8 years) and 83% had permanent con-
tracts. As regards professional category, tile workers
occupied a variety of jobs: 98% were blue-collar operators
who were under the direct influence of the rate of produc-
tion and of the tile machinery (e.g. people working on
presses or kilns and in maintenance), and 2% were sales
agents. In Sample 2 (i.e. secondary school teachers,
N= 483), 56% were women and age s ranged from 23 to
60 years (M= 40; SD = 8 years). As regards the profes-
sional category, 87% were graduates and 62% had perma-
nent contracts at their school (85% were public schools).
Researchers distributed self-report questionnaires in
envelopes (2004 and 2005) together with a cover letter
explaining the purpose of the study. Participants were
asked to fill out the questionnaires as a part of an occu-
pational health and safety audit. This audit project was
backed by different public organisms with the main
aim of generating healthy organizations and raising
the quality of working life. Participation was voluntary
with guaranteed confidentiality. Respondents returned
the completed questionnaires in a sealed envelope
either to the person who had distributed them or
directly to the research team.
In order to test whether the sociodemographic
variables differed between the two samples, we compared
them in relation to the background variables (i.e. fre-
quency of flow experience, challenge and perceived skills)
of both samples. The following sociodemographic vari-
ables were tested: (1) age and gender in both samples;
(2) company, type of jobs and contract (permanent
versus temporary) in tile workers; and (3) educational
level (graduates versus teachers), type of contract (perma-
nent versus temporary) and type of school (private versus
public) in secondary school teachers. Analyses of variance
and chi-square showed non-significant differences in the
background variables as regards the sociodemographic
variables in both samples.
Measures
Frequency of flow experience
We measured the ‘frequency of the flow experience at
work’using a Spanish adaptation (Salanova et al., 2006)
of the WOLF (WOrk-reLated Flow; Bakker, 2001) to
assess three dimensions: enjoyment (four items; e.g.
‘When I am working, I feel happy’), absorption (six
items; e.g. ‘When I’m working, I forget everything
around me’) and intrinsic interest (six items; e.g. ‘Iget
my motivation from the work itself, and not from the
rewards for it’). Participants had to answer how often
(i.e. the frequency) they had had these experiences at
work in the last 6 months on a seven-point scale (0
‘never’to 6 ‘every day’).
Frequency of flow prerequisites
We measured the frequency of ‘flow prerequisites’by
assessing two dimensions: perceived challenge and per-
ceived skills. Challenge was measured by two items from
the dedication scale of the Spanish version (Salanova
et al., 2000) of the Utrecht Work Engagement Scale
(UWES; Schaufeli, Salanova, González-Romá, & Bakker,
2002). The two items (0 ‘never’and 6 ‘always’)were‘My
job is stimulating and inspires me’and ‘My job gives me
new challenges’.Secondly,perceived skills was measured
by six items (0 ‘never’and 6 ‘always’) of the professional
competence scale from the Spanish version (Salanova
et al., 2000) of the Maslach Burnout Inventory—
General Survey (MBI-GS; Schaufeli, Leiter, Maslach, &
Jackson, 1996). An example of the items used is ‘Ican
effectively solve the problems that arise in my work’.
Cronbach’s alpha and the intercorrelations of each scale
in each sample are shown in Table I.
Data analyses
Firstly, we calculated internal consistencies (Cronbach’s
a), descriptive analyses and intercorrelations among the
variables in the study using SPSS Statistics 19.0 (IBM
Company, New York, USA). Secondly, we computed a
S. Llorens, M. Salanova and A. M. Rodríguez FLOW EXPERIENCE
Stress Health (2012) © 2012 John Wiley & Sons, Ltd.

procedure to test for bias due to common method vari-
ance. Different methods to test for common factor bias
are shown in Podsakoff, MacKenzie, Lee and Podsakoff
(2003). Since all of them display potential problems, we
used the simplest and one of the most widely utilized
techniques: Harman’s single factor test (Iverson &
Maguire 2000; cf. Podsakoff et al., 2003) with CFA using
the Analysis of MOment Structures (AMOS) software
package (v. 19.0). The most important limitation is that
Harman’s single factor test is a diagnostic technique for
assessing the extent to which common method variance
may be a problem, but it does not actually control for
method effects statistically. In order to get round this
limitation, we also computed an alternative multiple
factor test with CFA, and finally, we checked for signifi-
cant differences between this multiple factor model and
Harman’ssinglefactormodel.
Thirdly, the AMOS 19.0 software program was used
to implement different second-order CFA in order to
confirm the factorial structure of the frequency of flow
experience scale. Four plausible models were com-
pared: M1, the three-factor model, in which the 16
items load in the original specific dimensions of the flow
experience: enjoyment, absorption and intrinsic interest;
M2, the first-order factor, in which the original 16 items
load in a single latent factor; M3, a second-order two-
factor model, in which items load in two specificdimen-
sions of flow experience: enjoyment and absorption; and
finally, M4, the one-factor reduced model, in which the
10 items (from enjoyment and absorption scales) load in
a single latent factor. Different goodness-of-fit indices
were tested: the w
2
goodness-of-fitstatistic,RootMean
Square Error of Approximation (RMSEA), Comparative
Fit Index (CFI), Normed Fit Index (NFI), Tucker–Lewis
Index (TLI, also called the Non-normed Fit Index),
Incremental Fit Index (IFI) and Expected Cross-Validation
Index (ECVI). Values below 0.08 for the RMSEA, the
lowest for ECVI and above 0.90 for the rest of the
indices indicate an acceptable fit (Byrne, 2001).
Fourthly, we computed different multiple analyses of
variance (MANOVA) with the SPSS program (v. 19.0)
to test for (1) significant differences in the frequency of
the flow experience (as the dependent variable) accord-
ing to the ‘group’(established on the prerequisites of
flow as an independent variable), taking tile workers
and secondary teachers into account simultaneously
following the hypothesis of the flow analysis model in
work settings; and (2) significant differences in the
frequency of the flow experience (as the dependent var-
iable) across occupations (i.e. tile workers and secondary
school teachers as independent variables). In order to
interpret the relationship among the frequency of
prerequisites of flow (i.e. challenge and skills) and the
frequency of the flow experience itself, we took 1SD
with respect to the mean in each variable (i.e. challenge
and skills). Specifically, a high value in a variable corre-
sponds to scores one standard deviation higher than
the mean, whereas a low value corresponds to scores
one standard deviation below the mean. This procedure
allows us to select the participants with extreme values in
these variables (high scores, +1SD; low scores, 1SD),
as recommended by previous research (i.e. Cohen &
Cohen, 1983; Jaccard, Turrisi, & Wan, 1990).
Results
Descriptive analyses
Table I displays the means, standard deviations, internal
consistencies (Cronbach’s alpha) and intercorrelations
of the variables for each sample separately. All the alpha
values meet the 0.70 criterion (Nunnally & Bernstein,
1994), as they range from 0.78 to 0.91. The pattern of
correlations shows that, as expected, frequency of enjoy-
ment, absorption and intrinsic interest (i.e. the
frequency of flow experience itself) are positively and
significantly related in both samples. The prerequisites
of flow also show positive and significant intercorrela-
tions with one another: frequency of challenge shows a
significant and positive relationship to frequency of skills
in both samples. Additionally, frequency of challenge as
well as skill shows higher positive correlations with the
frequency of the flow experience (i.e. enjoyment,
absorption and intrinsic interest) in tile workers and in
secondary school teachers.
Furthermore, the results of Harman’s single factor
test with CFA for the frequency of the flow experience
and the frequency of flow prerequisites reveal a poor
fit to the data for the variables in the study,
Table I. Means (M), standard deviations (SD), correlations (tile workers below the diagonal), t-test and Cronbach’s alpha (tile workers/
secondary school teachers) on the diagonal (N = 957)
Variables
Tile (N= 474) Teachers (N= 483)
df FŊ
2
12 3 4Mean SD Mean SD
1. Flow: enjoyment 4.03 1.33 4.48 1.10 1,955 31.02*** 0.038 0.89/.91 0.53*** 0.58*** 0.64***
2. Flow: absorption 3.09 1.24 3.56 1.05 1,955 38.65*** 0.206 0.55*** 0.82/0.79 0.51*** 0.44***
3. Challenge 3.30 1.67 3.83 1.28 ———0.55*** 0.65*** r= 0.66***/0.66***
,†
0.58***
4. Skills 4.40 0.95 4.27 0.81 ———0.41*** 0.43*** 0.48*** 0.78/0.82
Notes. df: degrees of freedom.
†
This is a correlation between the two items that compose the ‘challenge’variable.
***p<0.001.
FLOW EXPERIENCE S. Llorens, M. Salanova and A. M. Rodríguez
Stress Health (2012) © 2012 John Wiley & Sons, Ltd.

w
2
(7) = 841.85, RMSEA = 0.35, CFI = 0.63, NFI = 0.61,
TLI = 0.47, IFI = 0.63, AIC = 857.85. To avoid the pro-
blems related to the use of Harman’s single factor test
(see Podsakoff et al., 2003), we compared the results
with an alternative model that included multiple
latent factors. Results show a significantly lower fitof
the model with one single factor when compared
with the model with multiple latent factors, Delta
w
2
(3) = 703.67, p<0.001. Hence, one single factor could
not account for the variance in the data. Consequently,
we may consider common method variance not to be
a serious deficiency in this dataset.
Confirmatory factor analyses for the
frequency of flow experience scale
Table II shows the results of the second-order CFA
conducted to confirm the structure of the frequency
of the flow experience at work by multigroup analyses
(Byrne, 2001). The findings indicate that the original
three-factor model of the frequency of the flow expe-
rience (M1) does not show adequate goodness-of-fit
indices in either the tile or the teacher samples. Similar
poor findings are observed when M2, the one-factor
original model, is tested. None of these models
showed adequate goodness-of-fit indices and thereby
did not lend support to consider either three-factor
or one-factor validity for this scale to measure the fre-
quency of flow experience at work. A review of Table II
shows that M3,
1
a second-order two-factor model
composed of enjoyment and absorption, fits the data
better than the previous models: M1, the original
three-factor model, Delta w
2
(136) = 1970.95, p<0.001;
M2, the one-factor model, Delta w
2
(212) = 1285.30,
p<0.001; and M4, the 10-item one latent factor
model, Delta w
2
(2) = 578.3, p<0.001. According to
the Modification Index, the fit of the hypothesized
M3 model could be significantly improved, Delta
w
2
(2) = 196.42, p<0.001, by constraining one pair of
errors (absorption4–absorption5, which refer to the
difficulty involved in detaching oneself from the activ-
ity). Again, this revised M3 fits significantly better than
previous models: M1, the original three-factor model,
Delta w
2
(138) = 2167.37, p<0.001; M2, the original
one-factor model, Delta w
2
(214) = 1481.72, p<0.001;
and M4, the 10-item one-factor model, Delta
w
2
(4) = 774.72, p<0.001.
In sum, the revised M3—in which the frequency of
the flow experience is composed of 10 items distributed
in two latent factors (enjoyment and absorption)—is
the best model, with all fit indices satisfying the criteria.
Results show significant first-factor weights higher than
0.72 and 0.79 and second-factor weights higher than
0.44 and 0.23 for tiles and teachers, respectively. Based
on these previous empirical analyses, in the following
analyses, the frequency of the flow experience will be
computed on the basis of just its two core dimensions:
enjoyment and absorption. On the basis of these
results, and regarding Hypothesis 1, statistical analyses
do not reject the null hypothesis.
Testing the flow analyses model in work
settings: Frequency of flow experience and
flow prerequisites
Table III shows the descriptive analyses for the
frequency of the flow experience (i.e. enjoyment and
absorption) of four groups of workers: tile workers
and secondary school teachers being taken into account
simultaneously. According to the flow analysis model
Table II. Fit indices of the confirmatory factor analyses for the frequency of flow experience scale (N= 957)
Model w
2
df RMSEA CFI IFI TLI ECVI w
2
diff RMSEA CFI IFI TLI ECVI
M1. Three-factor model 2630.25 204 0.112 0.73 0.74 0.68 2.897
M2. One-factor model (16 items) 1944.60 280 0.09 0.81 0.81 0.78 2.170
Difference between M2 and M1 685.65 0.02 0.08 0.07 0.10 0.727
M3. Two-factor model 659.30 68 0.07 0.88 0.88 0.84 0.778
Difference between M3 and M1 1970.95 0.04 0.01 0.07 0.16 2896.22
Difference between M3 and M2 1285.30 0.06 0.07 0.07 0.06 1.392
M4. One-factor model (10 items) 1237.60 70 0.13 0.77 0.77 0.70 1.380
Difference between M4 and M1 1392.65 0.02 0.04 0.03 0.02 1.517
Difference between M4 and M2 707.00 0.04 0.04 0.04 0.08 0.790
Difference between M4 and M3 578.30 0.06 0.11 0.11 0.14 0.602
M3 revised. Two-factor model revised 462.88 66 0.07 0.92 0.92 0.90 0.577
Difference between M3r and M1 2167.37 0.04 0.19 0.18 0.22 2.32
Difference between M3r and M2 1481.72 0.02 0.11 0.11 0.12 1.593
Difference between M3r and M3 196.42 0.00 0.04 0.04 0.06 0.201
Difference between M3r and M4 774.72 0.06 0.15 0.15 0.20 0.803
Notes.w
2
: Chi-square; df: degrees of freedom; RMSEA: Root Mean Square Error of Approximation; CFI: Comparative Fit Index; IFI: Incremental
Fit Index; TLI: Tucker–Lewis Index; ECVI: Expected Cross-Validation Index.
1
The error variance of enjoyment indicator was constrained by using
the formula [(1 α)*σ
2
] in order to avoid error misrepresenting
relationships between variables (Stephenson & Holbert, 2003).
S. Llorens, M. Salanova and A. M. Rodríguez FLOW EXPERIENCE
Stress Health (2012) © 2012 John Wiley & Sons, Ltd.

in work settings, these four groups are characterized by
a combination of high/low frequencies on challenge
and skills (the prerequisites of flow). We selected parti-
cipants with high (+1SD) and low (1SD) frequencies
on flow prerequisites, i.e. with high (+1SD) and low
(1SD) frequencies on challenge and with high
(+1SD) and low (1SD) frequencies on skills in both
samples analysed together (N= 957). Following this
process (Cohen & Cohen, 1983; Jaccard et al., 1990),
participants with extreme conditions in the two sam-
ples simultaneously analysed (i.e. high/low frequencies
on challenge and high/low frequencies on skills) were
selected (N= 149; 15%). This resulted in the four
groups of frequency of challenge and skills combina-
tions proposed by the different channels. Workers in
jobs characterized by low frequency of challenge plus
high skills made up Group 1 (n= 12; 8%); Group 2
included workers in jobs characterized by a balance
between high frequency of challenge and high
frequency of skills (n= 64; 43%); Group 3 included
workers in jobs characterized by a balance between
low frequency of challenge and low frequency of skills
(n= 71; 48%); and, finally, Group 4 comprised workers
with a perception of high frequency of challenge plus
low frequency of skills (n= 2; 1%). Chi-square analyses
revealed that the distribution of the sample in the four
quadrants is statistically significant, w
2
(3) = 100.26,
p<0.001.
Results in Table III also show that only 43% (n=64)
of the workers in our ‘extreme’sample (n= 149) (6% of
the whole sample of 957) are classified in Group 2 (high
frequency of challenge plus high frequency of skills), in
which the prerequisites of the frequency of flow experi-
ence are present in balanced high frequencies. According
to the flow analysis model in work settings, this Group 2
will experience flow at work more frequently. Results of
aMANOVAtakingthe‘group’(established on the basis
of the combinations of frequency of flow prerequisites)
into account as the independent variable and the
frequency of the flow experience (i.e. enjoyment and
absorption) as dependent variables show consistent
statistically significant differences among the four
groups in the frequency of the flow experience itself,
F(6,288) = 46.23, p<0.001. More specifically, these
significant differences were shown in both dimensions
of the frequency of flow experience: enjoyment,
F(3, 145) = 80.79, p<0.001, Ŋ
2
= 0.59, and absorption,
F(3,145) = 71.92, p<0.001, Ŋ
2
= 0.62. According to
Cohen (1988), these significant differences are consid-
ered to be ‘large’effects based on the effect size
d=2.73 and d= 2.53 for enjoyment and absorption,
respectively.
We employed Tukey’s HSD follow-up tests for pair-
wise comparisons among the four groups that were
corrected for experiment-wise error rates. As expected,
Group 2 (workers with a perceived balance between
high frequency of challenge and high frequency of
skills) had significantly higher scores in the frequency
Table III. Means (M) and standard deviations (SD) for frequency of flow experience (i.e. enjoyment and absorption) by ‘groups’based on the frequency of flow prerequisite combinations (N= 149)
Frequency
of flow
experience
Group 1 Group 2 Group 3 Group 4
df FŊ
2
Tukey’s HSD
Low challenge + high skills High challenge + high skills Low challenge + low skills High challenge + low skills
(n= 12; 8%) (n= 64; 43%) (n= 71; 48%) (n=2; 1%)
MSD MSD MSD MSD
Enjoyment 5.21 1.12 5.53 0.57 2.89 1.28 5.00 0.00 3,145 80.79*** .59 2 >3***; 3 <1,4***
Absorption 2.97 1.00 4.52 0.98 2.04 0.97 3.67 0.23 3,145 71.92*** .62 2 >3,1***; 3 <1***
Notes. Results are significant at ***p<0.001. Challenge and skills are tested by frequency. df: degrees of freedom.
FLOW EXPERIENCE S. Llorens, M. Salanova and A. M. Rodríguez
Stress Health (2012) © 2012 John Wiley & Sons, Ltd.

of both flow experience dimensions (i.e. enjoyment
and absorption) than the rest of the groups—above
all Group 1 (low frequency of challenge and high fre-
quency of skills) and Group 3 (workers with balanced
low frequency of challenge and low frequency of skills).
On the other hand, Group 3 (balance between low fre-
quency of challenge and low frequency of skills) shows
significantly lower scores in the frequency of flow
experiences; that is to say, they experience enjoyment
and absorption less frequently than the other groups.
In accordance with the predictions based on the flow
analysis model in work settings, only Group 2 experi-
ences flow (i.e. enjoyment and absorption) since it is
located in Channel 2, which is characterized by a bal-
ance between high frequency of challenge and high fre-
quency of skills. A deeper analysis of this group (n= 64;
43%) who experiences flow reveals that it is made up of
35 tile employees (55%) and 29 secondary school
teachers (45%) (Table IV). Following the flow analysis
model in work settings, the rest of the groups describe
other experiences that are opposite of flow. Firstly,
Group 3 (n= 71; 48%) corresponds to Channel 6
(balance between low frequency of challenge and low
frequency of skills), in which workers experience
apathy. Specifically, this group is made up of 43 tile
employees (61%) and 28 secondary school teachers
(39%). Secondly, Group 1 (n= 12; 8%) corresponds
to Channel 4 (low frequency of challenge plus high
frequency of skills), in which workers experience
relaxation. This group is basically made up of 11 tile
employees (92%) and only 1 secondary school teacher
(8%). Finally, Group 4 (n= 2; 1%) corresponds to
Channel 8 (high frequency of challenge plus low fre-
quency of skills), in which workers experience anxiety
at work. This group is made up exclusively of second-
ary school teachers (n= 2, 100%) (Table IV). On the
basis of these results, and with regard to Hypothesis 2,
the statistical analyses rejected the null hypothesis.
Frequency of flow experience across
occupations
In order to test whether there are significant differences
in the frequency of the flow experience at work be-
tween different types of occupations (i.e. production
and human-services employees), MANOVAs were
calculated taking into account the ‘occupation’as the
independent variable and the frequency of the flow
experience (i.e. enjoyment and absorption) as the
dependent variable (Huberty & Morris, 1989).
Results showed consistent statistically significant
differences between tile workers and secondary school
teachers in the frequency of the flow experience,
F(2,954) = 22.74, p<0.001. As expected, secondary
school teachers experienced flow more frequently
than tile workers, i.e. absorption, F(1,955) = 38.65;
p<0.001; d= 0.86, ‘large’effect, and enjoyment,
F(1,955) = 31.02; p<0.001; d= 0.96, ‘large effect’
(Table I). Despite the fact that, as Hypothesis 2 has
confirmed, both of the occupations (tile workers and
secondary school teachers) could work in contexts in
which the conditions to experience flow (high fre-
quency of challenges and high frequency of skills)
could be presented (55% in tile workers and 45% in
secondary school teachers), secondary school teachers
experience the phenomenon of flow more frequently
than tile workers. Further analyses based on the distri-
bution among groups per occupation (tile workers and
secondary school teachers) reveal similar results. In
fact, the distribution shows that when considering the
type of occupation, secondary school teachers are
mainly classified in Group 2 (flow; 48%), whereas tile
workers are mainly classified in Group 3 (apathy;
43%) (Table IV). Consequently, and with regard to
Hypothesis 3, statistical analyses rejected the null
hypothesis.
Discussion
The aims of the current study was to test (1) the facto-
rial structure of the frequency of flow experience at
work in two samples (tile workers and secondary
school teachers); (2) the flow analysis model in work
settings by differentiating the frequency of the flow
experience at work and the frequency of its prerequi-
sites (i.e. challenge and skills); and (3) whether there
are significant differences in the frequency of flow
experiences depending on the occupation (tile workers
and secondary school teachers) on the basis of the flow
analysis model in work settings.
With regard to the first objective, we expected a
traditional three-factor model of frequency of flow
Table IV. Classification of workers per group and per number of occupation considering the prerequisites of flow experience
Group Characteristics
Ntotal per
group (%)
Per group Per occupation
Tile workers Teachers Tile workers (n= 99) Teachers (n= 60)
n(%) n(%) n(%) n(%)
Group 1 ‘Relaxation’12 (8) 11 (92) 1 (8) 11 (11) 1 (2)
Group 2 ‘Flow’64 (43) 35 (55) 29 (45) 35 (35) 29 (48)
Group 3 ‘Apathy’71 (48) 43 (61) 28 (39) 43 (43) 28 (47)
Group 4 ‘Anxiety’2 (1) —2 (100) —2 (3)
S. Llorens, M. Salanova and A. M. Rodríguez FLOW EXPERIENCE
Stress Health (2012) © 2012 John Wiley & Sons, Ltd.

experience in work settings that included enjoyment,
absorption and intrinsic interest to fit the data better
than a two-factor model (in which items are assumed
to be loaded in enjoyment and absorption) or a one-
dimensional model (all items are assumed to be loaded
on one underlying undifferentiated flow dimension)
(Hypothesis 1). The multigroup confirmatory factorial
analyses conducted among both tile workers and
secondary school teachers showed the two-factor struc-
ture of the frequency of flow experience when tested by
the WOLF Inventory (Bakker, 2001). Thus, statistical
analyses accepted the null hypothesis (Hypothesis 1).
Contrary to previous research (Bakker, 2005;
Demerouti, 2006; Nielsen & Cleal, 2010; Salanova
et al., 2006), the frequency of flow experience at work
(i.e. among tile workers and secondary school teachers)
is not made up of one or three dimensions. Results
from the latest research on the measurement of the
frequency of flow experience at work (Rodríguez, Cifre
et al., 2008; Rodríguez, Schaufeli et al., 2008) offer
evidence in favour of the core dimensions of the
frequency of flow experience at work: enjoyment (e.g.
Ghani & Deshpande, 1994; Moneta & Csikszentmihalyi,
1996) and absorption (e.g. the central characteristics of
flow; Csikszentmihalyi, 1975). It seems that the particu-
lar feeling of happiness (enjoyment; cf. Diener, 2000)
and the state of being fully concentrated and engrossed
in one’s work, whereby time passes quickly (absorption;
cf. Novak & Hoffman, 1997), constitute the real essence
of the flow experience in work settings. On the other
hand, it seems that intrinsic interest (cf. Deci & Ryan,
1985; Moneta & Csikszentmihalyi, 1996) may play
another role in the flow experience, since it is not a con-
stituent dimension but possibly an antecedent (Ghani &
Deshpande, 1994; Skadberg & Kimmel, 2004). In fact,
some authors have shown a positive relation among
intrinsic interest, the core dimensions of flow experience
(enjoyment and absorption) and satisfaction at work
(e.g. Finneran & Zhang, 2003). However, more research
in terms of the antecedents of the flow experience in
work settings needs to be conducted in order to give
an accurate answer.
On the basis of the premises of the flow analysis
model in work settings, we also expected that only
workers, independently of occupation, who perceive
balanced high frequency of challenge and skills in their
jobs would experience flow more frequently, than
others who perceive different combinations between
challenge and skills (Hypothesis 2). MANOVA showed
that, as expected, employees (tile workers and second-
ary school teachers simultaneously analysed) perceiving
a balance between high frequencies of challenge and
skills at work (Group 2; 6% of the total sample) expe-
rienced flow more frequently compared with others
who had a different combination of frequencies of
challenge and skills. Thus, statistical analyses rejected
the null hypothesis (Hypothesis 2). More specifically,
evidence in favour of Channel 2 is also obtained using
the frequency of the flow experience itself (i.e. enjoy-
ment and absorption) and its prerequisites (i.e. the
perception of a balance between high frequency of
challenge and high frequency of skills) in work settings,
independently of the type of occupation. These findings
are consistent with suggestions from previous research
in different areas, such as public and private schools,
web users, online shopping and physical activity (i.e.
Bassi & Delle Fave, 2011; Chen et al., 1999; Guo &
Poole 2009; Kawabata & Mallett, 2011; Keller & Bless
2008; Keller & Blomann 2008; Mesurado 2009; Pearce
et al. 2005), and in work settings (Salanova et al.,
2006) that assume that (1) challenge and skills are pre-
requisites of flow and (2) a balance between high
challenge and high skills creates an optimal subjective
experience relative to other combinations of skills and
challenge independently of occupation [tile workers
and secondary school teachers (Channel 2)]. These
results also allow us to distinguish between the flow
experiences itself and its prerequisites independently
in two occupations: tile workers and secondary school
teachers. This represents an advance in the research
on flow at work since it reduces the confusion about
the frequency of flow experience and the conditions
that make a job more probably to allow people experi-
ence flow more frequently. As suggested by previous
scholars, it seems that the frequency of flow prerequi-
sites and the frequency of flow experience in the work
setting are also closely related aspects of flow but should
be distinguished (Chen et al., 1999; Ghani & Deshpande,
1994;Trevino&Webster,1992).Differentexperiences
at work were also obtained on the basis of other combi-
nations of challenge and skills, i.e. apathy (Group 3;
Channel 6), relaxation (Group 1; Channel 4) and anxiety
(Group 4; Channel 8), as proposed by previous flow
literature (Csikszentmihalyi & Csikszentmihalyi, 1988;
Delle Fave & Bassi, 2000; Delle Fave & Massimini,
2005; Massimini & Carli, 1988; Salanova et al.,
2006). It must be noted that a particular result was
found in Group 4, characterized by high challenge plus
low skills. According to the model of flow in work
settings, this group is characterized by being more
prone to anxiety. However, it is odd to note that,
according to Table III, this group shows scores in
enjoyment and absorption that are not significantly
different from those of Group 2 (the group who expe-
rience flow more frequently). The values of enjoyment
in this Group 4 are especially high, and this could be
produced as a consequence of the high frequency of
challenge scores that workers perceived. It is important
to note that only an increase in frequency of skill
perception is needed in this group to change from
Channel 8 to Channel 2, i.e. the flow channel. All in
all, we could also explain this interesting finding in
terms of the artefactual result, since only two workers
are included in this group. A deeper analysis reveals
that, in fact, the workers in this group are exclusively
secondary school teachers (100%) working in public
FLOW EXPERIENCE S. Llorens, M. Salanova and A. M. Rodríguez
Stress Health (2012) © 2012 John Wiley & Sons, Ltd.

schools with fixed contracts, which may explain at
least the challenge frequencies in this group.
Finally, according to the third objective of the
current study, and on the basis of previous studies on
flow experience at work from different occupations
(Demerouti, 2006; Salanova et al., 2005), we expected
significant differences in the frequency of the flow
experience between workers from two different occu-
pations: tile workers (i.e. production workers) and
secondary school teachers (i.e. human-services
employees) on the basis of the flow analysis model in
work settings. More specifically, we expected secondary
school teachers to experience flow more frequently
than tile workers (Hypothesis 3). Again, MANOVA
showed that secondary school teachers indeed experi-
enced flow more frequently than tile workers. That is
to say, school teachers felt enjoyment and absorption
more frequently than tile workers. This means that
although both samples may experience the prerequi-
sites of flow (50% approximately), secondary school
teachers (i.e. human-services employees) experience
flow more frequently than tile workers (i.e. production
workers who depend on the pace of the machinery). In
fact, it seems that secondary school teachers are mainly
classified in the flow group (Group 2), compared with
tile workers who are mainly classified in ‘apathy’group
(Group 3). Thus, statistical analyses rejected the null
hypothesis (Hypothesis 3). These results are in line with
the study of flow in different occupations conducted by
Salanova et al. (2005). Despite both types of workers in
the study perceive that their jobs are challenging and
that they have the skills to cope with these job
demands, it seems that secondary school teachers per-
ceive that they experience flow more frequently than
tile workers. There is evidence that human-services
employees (and specifically teachers) experience flow
more frequently than production workers (particularly
office and tile workers). It seems that when employees
works with people, in intrinsically motivating and
creative occupations (e.g. the settings in secondary
school teachers), and with more resources (i.e. auton-
omy, feedback and variety) (Warr, 1990, 2007), they
are more likely to report higher perception of flow
experience at work (Gold & Roth, 1993; Salanova
et al., 2005). If the work conditions are relevant to
increase the probability to experience flow, it seems
that the perception of workers about the experience
of flow itself increases when workers work with
‘people’(Salanova et al., 2005).
Limitations and strengths
One of the limitations of this study is that the results
must be interpreted with caution because of its non-
experimental nature. However, this limitation has been
reduced by considering a broad sample including
different occupations (i.e. tile workers and secondary
school teachers) from different enterprises belonging
to two different economic sectors (i.e. tile companies
and public and private secondary schools). Another
limitation is that the data were obtained by self-report
measures. However, we followed the Harman test
(Podsakoff et al., 2003) and checked for common
method variance in our data. Although we cannot
completely rule out the possibility that method
variance may play a role, results show that this is not
a serious problem in the present study. Thirdly, this
study is limited to the context of tile workers and
secondary school teachers, and consequently, findings
cannot be generalized. Thus, a wide range of occupa-
tions as well as multigroup comparisons and cross-
cultural studies need to be accounted for in future
studies. Finally, although the sample size is quite large,
the subsamples in each channel are still rather small,
particularly in Group 4. Finally, a retrospective cross-
sectional design was used. Further research with
longitudinal analyses will be useful to test the antece-
dents (i.e. working conditions) and consequences (i.e.
individual, group and organizational outcomes) of the
frequency of flow experience. Since 6% of secondary
school teachers and 7% of tile workers experience flow,
there is a special need for research to test the role of job
resources (e.g. autonomy, feedback and variety) and
personal resources (e.g. efficacy beliefs and intrinsic
motivation) in the development of the frequency of
flow experience at work.
Conversely, our study also has the following main
strengths. Firstly, the current study integrates the liter-
ature on flow experience and its prerequisites in work
settings by using frequency and single administration
questionnaire. Secondly, it establishes that the flow
experience at work is composed of two core dimensions,
i.e. enjoyment and absorption. Thirdly, it attempts to
test our flow analysis model in work settings by distin-
guishing the core dimensions of the flow experience
(i.e. enjoyment and absorption) and its prerequisites
(a balance of high challenges and skills) in the same
study in work settings on the basis of frequency (instead
intensity) and by using a single questionnaire adminis-
tration. Fourthly, this study investigates the differences
in the frequency of flow experiences across two occupa-
tions, i.e. tile workers and secondary school teachers.
Theoretical and practical implications
The present results may have some important implica-
tions for future flow research and practice at work.
Firstly, the current study corroborates the two-factor
structure of flow experience (i.e. enjoyment and
absorption) tested by the frequency of flow in two
different occupations: tile workers and secondary school
teachers. This offers evidence of the bidimensionality of
the frequency of flow experience, which leads to a more
parsimonious understanding of the flow experience at
work by testing its essence: frequency of enjoyment
and absorption. The second implication is that the flow
experience at work (measured by frequency instead of
intensity) has been related with but, at the same time,
S. Llorens, M. Salanova and A. M. Rodríguez FLOW EXPERIENCE
Stress Health (2012) © 2012 John Wiley & Sons, Ltd.

distinguished from the prerequisites of flow. This result
provides support for the flow analysis model in work
settings, since it analyses the impact of a balance of high
challenge and skills being the real predictors of the flow
experience at work. Also, these results give evidence of
the accuracy to test the flow analysis model in work
settings by using a single administration retrospective
instrument in terms of frequency. Thirdly, the current
study has demonstrated that there are significant differ-
ences in the frequency of the flow experience based on
the type of occupation (but not in the perception about
their prerequisites).
With regard to the practical implications, the results
obtained in this study can be used as recommendations.
Thus, the findings warn organizations of the need to take
care of frequency of challenge and skills if they want
their employees to obtain flow experiences more fre-
quently. Specifically, results show the significance of
organizations promoting job (e.g. autonomy, feedback
and variety) and personal characteristics (e.g. creative
and intrinsic motivation) in order to generate more
challenging settings and more highly skilled employees,
which in turn enhance the frequency of flow experience
at work. In this sense, job (re)design plays a key role in
being able to increase the frequency of one of the prere-
quisites of flow experience, i.e. workers’perceptions of
challenge at work. Results also suggest that training plays
a pivotal role in generating flow at work more fre-
quently. This training should focus on promoting the
development of skills that can help people to perceive
themselves as being more skilful and as being capable
of meeting the challenge that their work offers. Further-
more, another practical implication is related to the fre-
quency of flow experience itself in work settings. Because
it only has two dimensions (enjoyment and absorption),
practitioners can measure the frequency of flow experi-
ence at work quickly and easily by using just a single
questionnaire. Some research works have criticized the
use of questionnaires because they do not yield good
quality data for eliciting phenomenological perceptions,
since subjects are not used to putting these perceptions
into words (Massimini et al., 1987). Nevertheless, other
works have shown them to be a strategy that can be used
not only to collect retrospective data of past flow experi-
ences but also to obtain a descriptive picture of these
positive experiences (e.g. Bakker, 2008; Chen et al.,
1999; Mäkikangas et al., 2010).
Final note
The current study shows that the frequency of flow
experience and its prerequisites are not specificto
athletes and artists, but also exist in work settings.
Contrary to the claims of some traditional scholars,
the frequency of flow experience at work is composed
of two genuine dimensions: enjoyment and absorption.
Although flow could be experienced in any occupation
characterized by a perception of a balance of high
frequency of challenges and high frequency of skills,
secondary school teachers perceive that they experience
flow more frequently than tile workers, especially when
they are working at the machines’pace. Thus, this
study has led to at least a tentative understanding of
the frequency of flow experience and its prerequisites
in work settings, that is to say, a clearer view of the
dimensions of flow experience, what makes flow and
who it is experienced by. We hope that our study will
allow scientists and practitioners to go a step forward
in measuring and promoting the experience of flow in
work domains, above all in this time of social, occupa-
tional and economic crisis.
Acknowledgements
This study was supported by a grant from the Spanish
Ministry of Science and Technology (#SEJ2004-
02755/PSIC) and the Spanish Ministry of Science and
Innovation (#PSI2011-22400).
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