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Recovery experiences as moderatorsbetween psychosocial workcharacteristics and occupational well-beingMarjo Siltaloppi a , Ulla Kinnunen a & Taru Feldt ba Department of Psychology, University of Tampere, Tampere,Finlandb Department of Psychology, University of Jyväskylä, Jyväskylä,FinlandPublished online: 09 Dec 2009.

To cite this article: Marjo Siltaloppi , Ulla Kinnunen & Taru Feldt (2009) Recovery experiencesas moderators between psychosocial work characteristics and occupational well-being, Work& Stress: An International Journal of Work, Health & Organisations, 23:4, 330-348, DOI:10.1080/02678370903415572

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Recovery experiences as moderators between psychosocial workcharacteristics and occupational well-being

Marjo Siltaloppia*, Ulla Kinnunena and Taru Feldtb

aDepartment of Psychology, University of Tampere, Tampere, Finland;bDepartment of Psychology, University of Jyvaskyla, Jyvaskyla, Finland

This study examined the direct and moderator roles of recovery experiences (psychological

detachment from work, relaxation, mastery, and control) in the relationship between

psychosocial work characteristics (i.e. time demands, job control, and justice of the supervisor)

and occupational well-being (need for recovery, job exhaustion, and work engagement). The

study was conducted among 527 Finnish employees from several occupational sectors who

were employed in a variety of different jobs. Of the employees, 53% were women and the

average age was 42.4 years. The moderated hierarchical regression analyses showed that

psychological detachment and mastery were protective mechanisms against increased need for

recovery in a situation of lack of job control. Also, relaxation protected against increased job

exhaustion under high time demands. In addition, recovery experiences � psychological

detachment and mastery in particular � had direct links to occupational well-being.

Altogether, the study findings suggest that recovery experiences play a significant role in

maintaining well-being at work.

Keywords: recovery; job demands; job resources; burnout; job engagement; work-related stress

Introduction

Employees’ recovery from job strain � a process that allows individuals to replenish

their resources � is threatened in many ways in today’s working life. For example,

technological advances have made it possible to work almost anywhere and anytime:

at home or even when travelling. This also means that traditional office hours are in

the process of changing to a 24-hours work society, which has resulted in an increase

of non-standard work schedules (i.e. evening, night and weekend work; see Harma,

2006, for a review). It has been argued that in the modern society the lack of recovery

could have even more impact on an individual’s well-being and health than the strain

itself (Lundberg, 2005; Zijlstra & Sonnentag, 2006).

The process of recovery from job strain has not received as much scientific

attention as the strain process itself. Therefore, the recovery process is not yet well

understood. Lack of recovery has been referred to when explaining why job

stressors may produce poor well-being and health problems (e.g. Geurts &

Sonnentag, 2006; Lundberg, 2005). When recovery is insufficient an individual

has to put in some extra effort at work to get through normal tasks, which may

*Corresponding author. Email: marjo.siltaloppi@uta.fi

ISSN 0267-8373 print/ISSN 1464-5335 online

# 2009 Taylor & Francis

DOI: 10.1080/02678370903415572

http://www.informaworld.com

Work & Stress

Vol. 23, No. 4, October�December 2009, 330�348

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inflict strain and in the long run lead to health deterioration and sickness absence

(Meijman & Mulder, 1998).

Although individuals may recover in many ways, for example, by doing different

activities such as reading a book or going for a walk; according to Sonnentag and

Fritz (2007), it is not a specific activity per se that helps to recover from job strain.

The question is rather about the mechanisms behind those activities, such asrelaxation or psychological distance from job-related issues, which help people to

recover. In this study, we focus on these mechanisms; more specifically, on four

recovery experiences that have been recently presented by Sonnentag and Fritz

(2007). These are psychological detachment from work, relaxation, mastery, and

control. We examine their direct links to occupational well-being as well as their

moderator role in the relation between psychosocial work characteristics and

occupational well-being.

Altogether, this study extends the existing recovery research in several ways. First,

it takes into account all those recovery experiences identified by Sonnentag and Fritz

(2007). So far, most studies have focused only one or two of the experiences and most

often only psychological detachment has been the focus (e.g. Sonnentag & Bayer,

2005; Sonnentag, Binnewies, & Mojza, 2008; Sonnentag, Mojza, Binnewies, &

Scholl, 2008). Second, we examine both negative (need for recovery, job exhaustion)

and positive (work engagement) aspects of occupational well-being, which adds to

our knowledge about the role of recovery experiences in both the health impairment

and the motivational processes (Demerouti, Bakker, Nachreiner, & Schaufeli, 2001).

Third, the moderating role of recovery experiences in the work characteristics�well-being outcomes relationship has not previously been examined, and for this reason it

is unknown whether recovery experiences buffer against the adverse well-being

effects of job stressors. Consequently, our study contributes to the recovery literature

by broadening the empirical basis concerning the relationships between work

characteristics, recovery experiences, and well-being.

Theoretical models of recovery from job strain

Recovery is a psycho-physiological revival process, in which an individual returns

to his or her pre-stressor level after a stressful experience (Meijman & Mulder,

1998). Thus, recovery is a process of unwinding, that is, the opposite of the

psycho-physiological activation that occurs under stressful conditions (Geurts &

Sonnentag, 2006). From a psychological perspective, an individual feels capableand ready to continue with his or her current demands or to meet new demands

(Zijlstra & Sonnentag, 2006). Recovery is also seen as a decrease in physiological

strain indicators (e.g. the excretion of adrenaline and cortisol or elevated heart

rate; for example, Geurts & Sonnentag, 2006). Recovery is important for an

individual’s health and well-being, because continuous or frequent exposure to

high workload with insufficient recovery may lead to cumulative health deteriora-

tion (McEwen, 1998).

There are only few theories that deal with recovery. Meijman and Mulder’s

(1998) Effort-Recovery Model states that expending effort at work leads to load

reactions including physiological, behavioural, and subjective responses. When an

individual is no longer confronted with work or similar demands, load reactions

(e.g. fatigue) are released and recovery occurs. Accordingly, it is important that the

Work & Stress 331

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psycho-physiological systems taxed during work are not called upon after work. If

an individual does not recover from load reactions, the recovery process is

incomplete and he or she has to invest compensatory effort to perform adequately

at work. Consequently, an accumulation of load reactions may be started, which

may result in impaired well-being (Meijman & Mulder, 1998).

The Conservation of Resources Theory (Hobfoll, 1998) assumes that peoplestrive to obtain, retain, and protect their resources. Resources refer to heterogeneous

categories of which personal characteristics and energy resources are most important

in relation to recovery. According to this theory, stress occurs when an individual’s

valued resources are threatened or lost or when no resources are gained after

resource investment. Applied to the context of work, an unfavourable work situation

expends or threatens an individual’s resources (e.g. vigour, self-esteem), which

produces stress. Thus, to recover from that stress an individual has to gain new

resources or restore threatened or lost resources in off-job time. This can be done, for

example, by engaging in leisure activities that may charge an individual’s batteries

(restore energy) or positively contribute to his or her self-esteem.

The Effort-Recovery Model and the Conservation of Resources Theory suggest

how the recovery process occurs, and they complement each other (Sonnentag &

Fritz, 2007). First, according to the former theory, it is essential to refrain from work

demands and to avoid activities that require the same functional systems or internal

resources as those required at work. Second, according to the latter theory, gaining

new internal resources such as energy, self-efficacy, or positive mood will help to

restore threatened resources.

Recovery experiences and occupational well-being

The mechanisms helping recovery are called recovery experiences by Sonnentag and

Fritz (2007), and they consist of psychological detachment from work, relaxation,

mastery (mastery-related off-job activities that offer an individual challenges or

opportunities to learn new skills), and control (ability to choose which activity to

pursue during leisure time, as well as when and how to pursue this activity). The

first two experiences have their roots in the Effort-Recovery Model, and the last

two in the Conservation of Resources Theory. According to the Effort-Recovery

Model, psychological detachment and relaxation may be helpful, because they

imply that no further demands are made on the functional systems called upon

during work. Mastery-oriented strategies � mastery and control � may aid recoverybecause they build up new and restore threatened internal resources. In addition,

control is crucial because it provides the opportunity to gain internal resources

(Hobfoll, 1998).

Psychological detachment implies disengaging mentally from work during off-job

time (Sonnentag & Fritz, 2007). That means not doing work-related tasks such as

receiving job-related phone calls or reading e-mails at home, because such activities

will make psychological detachment impossible. An individual also needs to stop

thinking about his or her job-related affairs. In every-day terms, psychological

detachment is often experienced as ‘‘switching off ’’ during off-job time (Sonnentag &

Bayer, 2005). Empirical evidence suggests that psychological detachment is helpful in

recovering from job strain. Diary studies (Sonnentag & Bayer, 2005; Sonnentag,

Binnewies et al., 2008) suggest that psychological detachment from work during

332 M. Siltaloppi et al.

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leisure time is associated with positive mood and low fatigue in the evening at

bedtime and the next morning. Further, Sonnentag and Fritz (2007) showed that

psychological detachment was negatively related to health complaints, emotional

exhaustion, depressive symptoms, need for recovery, and sleep problems. Also,

vacations may help to recover by promoting a sense of detachment through giving

relief from daily routines (e.g. Westman & Etzion, 2001).

Relaxation is characterized by a low activation and increased positive affect

(Stone, Kennedy-Moore, & Neale, 1995). This state may be either a result of

deliberately chosen strategies aimed at the relaxation of body and mind, like

meditation or progressive muscle relaxation, or relaxation may occur less deliber-

ately, for example, while performing such activities as reading a book, taking a walk,

or listening to music. As relaxation experience reduces activation and increases

positive affect, it is important for recovery (see Sonnentag & Fritz, 2007 for details).

In the study by Sonnentag and Fritz (2007), relaxation had negative relations with

health problems, emotional exhaustion, need for recovery, and sleep problems.

Further, the one-week diary study by Sonnentag, Binnewies et al. (2008) showed that

relaxation in the evening was related to morning serenity.

The mastery experience refers to pursuing mastery-related off-job activities (e.g.

taking a language class, or learning new sports) that offer an individual challenges or

opportunities to learn new skills (Fritz & Sonnentag, 2006; Sonnentag & Fritz,

2007). However, mastery experiences should challenge the individual without

overtaxing his or her capabilities. Although mastery experiences may put extra

demands on the individual, these experiences are expected to enhance recovery

because they help to build up new internal resources, such as skills, competencies,

self-efficacy, and positive mood (see Sonnentag & Fritz, 2007 for more details). The

empirical evidence available so far suggests that mastery experiences are related to

recovery. First, Fritz and Sonnentag (2006) demonstrated that higher levels of

mastery experiences during a vacation were related to lower levels of exhaustion on

the employee’s return to work. Second, mastery was negatively related to emotional

exhaustion, depressive symptoms, and need for recovery (Sonnentag & Fritz, 2007),

and mastery in the evening was related to morning positive activation (Sonnentag,

Binnewies et al., 2008).Control can be described as a person’s ability to choose an action from two or

more options. When applied to leisure time, it refers to control over such decisions

as which activity to pursue, and when and how to pursue this chosen activity.

According to Sonnentag and Fritz (2007), the experience of control during leisure

time may increase self-efficacy and feelings of competence; therefore it may be an

external resource that promotes recovery from job strain. As with control at work

(e.g. Karasek & Theorell, 1990), control in off-job time is also considered a factor

that promotes well-being. This view has received some support. First, Griffin,

Fuhrer, Stansfeld, and Marmot (2002) reported that women and men experiencing

low control at home (e.g. they did not feel that they had control over what happens

at home) showed higher levels of depression five years later than those women and

men with high control at home. Second, Sonnentag and Fritz (2007) found that

control was negatively related to health complaints, emotional exhaustion,

depressive symptoms, need for recovery, and sleep problems, and positively related

to life satisfaction.

Work & Stress 333

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Altogether, there seems to be some evidence that the four recovery experiences

are related to such well-being indicators as need for recovery, burnout, and health

complaints. Psychological detachment has received most research attention so far,

whereas mastery and control especially have been examined in only few studies.

In fact, there is only one study in which all the four recovery experiences have

been simultaneously examined (Sonnentag & Fritz, 2007). Therefore, the evidence

of their joint contribution to occupational well-being can be considered quite

limited.

In the present study, we examine all the four recovery experiences and their

relationships with three occupational well-being indicators, which are need for

recovery, job exhaustion, and work engagement. Need for recovery refers to the

desire to be temporarily relieved of demands in order to replenish internal resources

(Sluiter, van der Beek, & Frings-Dresen, 1999). Thus, a break from the demands may

be felt to be necessary in order to be willing and able to confront the demands again.

Need for recovery refers to a very early stage of a long-term strain process (Jansen,

Kant, & van den Brandt, 2002).Job exhaustion is the core symptom of burnout (Maslach, Schaufeli, & Leiter,

2001). It refers to feelings of overstrain, tiredness, and fatigue resulting from long-

term involvement in an over-demanding work situation. The state of exhaustion is

chronic and not relieved by daily or weekly rest (Maslach et al., 2001; Schaufeli &

Enzmann, 1998). Thus, the depletion of an individual’s overall energy due to

prolonged work stress is the core in the concept of job exhaustion. Therefore, job

exhaustion can be considered a more serious sign of the long-term strain process

than need for recovery.

Work engagement is considered a positive antipode of burnout (Bakker,

Schaufeli, Leiter, & Taris, 2008; Gonzalez-Roma, Schaufeli, Bakker, & Lloret,

2006; Schaufeli, Salanova, Gonzalez-Roma, & Bakker, 2002); specifically, Schaufeli

and his colleagues (p. 74) define work engagement ‘‘as a positive, fulfilling, work-

related state of mind that is characterized by vigor, dedication, and absorption.’’ In

this study, we focus on vigour and dedication, because they are considered the core

dimensions of engagement (Gonzalez-Roma et al., 2006). Vigour refers to high levels

of energy and mental resilience while working, the willingness to invest effort in one’s

work, and persistence in the face of difficulties. Dedication is considered a sense of

significance, enthusiasm, inspiration, pride, and challenge. In the diary study by

Sonnentag (2003), which extended over a period of five consecutive working days, a

positive relation between day-level recovery (level of recovery before starting to

work) and day-level work engagement (work engagement before leaving the

workplace) was detected (see also Sonnentag, Mojza et al., 2008).

In terms of the Job Demands-Resources (JD-R) Model (e.g. Demerouti et al.,

2001), need for recovery and job exhaustion represent indicators of the health

impairment process, whereas work engagement is an indicator of the motivational

process. Therefore, elevated levels of need for recovery or exhaustion can be seen as

consequences of lack of recovery, that is, in that case recovery experiences have not

helped to recover. On the contrary, work engagement � as a positive antipode of

burnout and a marker of a positive motivational state � signals adequate recovery.

This may signify that an individual’s well-functioning recovery experiences have

helped him or her to stay engaged (e.g. Sonnentag, Mojza et al., 2008).

334 M. Siltaloppi et al.

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Altogether, the previous study results and the reasoning in the light of the JD-R

model led to our first hypothesis:

Hypothesis 1: The four recovery experiences, namely psychological detachment from

work, relaxation, mastery, and control, are negatively related to need for recovery and

job exhaustion and positively related to work engagement.

Recovery experiences as potential moderators

It is well established that psychosocial job characteristics can have a profound impact

on employee well-being (see e.g. van der Doef & Maes, 1999; van Vegchel, de Jonge,

Bosma, & Schaufeli, 2005 for reviews). Therefore, such factors (e.g. social support)

which may buffer against these harmful effects on well-being have been intensively

examined. To the best of our knowledge, earlier research has not yet paid attention

to the question of whether recovery experiences may alter the effects of psychosocial

job characteristics on well-being � with one exception. Etzion, Eden, and Lapidot

(1998) examined the effect of detachment on the stressor�burnout relationship

during active reserve service. They showed that greater psychological detachment

intensified the positive off-job experience; those who felt most detached transferred

more of their respite relief back to their jobs in terms of diminished burnout.

Sonnentag and Fritz (2007) have assumed that all the four recovery experiences may

be conceptualized as moderators in the relationship between job stressors and

occupational well-being. In the present study, our aim is to shed further light on this

issue of moderation.

In our study, we focused on three psychosocial work characteristics, namely time

demands, job control, and justice of the immediate supervisor. These three

characteristics were chosen for the following reasons: First, time demands and

(lack of) job control represent the core elements at work that predict strain and

illness, according to the Job Demand-Control Model (Karasek & Theorell, 1990),

which has gained considerable support especially in cross-sectional studies (e.g. van

der Doef & Maes, 1999). Second, interactional lack of justice � of which lack of

justice of a supervisor is one type � has turned out to be a major source of

psychosocial strain at work, amounting to a health risk, whereas perceived justice is

a psychosocial resource that predicts employees’ well-being and health (Elovainio,

Kivimaki, Vahtera, Virtanen, & Keltikangas-Jarvinen, 2003; Kivimaki, Elovainio,

Vahtera, & Ferrie, 2003). This interactional component of organizational justice

refers to the perceived quality of treatment (e.g. honesty, equality) that people

experience in organizations by their supervisors.

According to the JD-R Model (e.g. Demerouti et al., 2001) and the categoriza-

tion of job demands and resources presented by Bakker and Demerouti (2007), of

the chosen work characteristics, time demands can be conceptualized as job

demands and job control and perceived justice in leadership as job resources. Job

demands refer to aspects of the job that require sustained physical and/or mental

(cognitive and emotional) effort and therefore may lead to exhaustion and strain. Job

resources, instead, refer to aspects of the job that are functional in achieving work

goals, reduce job demands, or stimulate personal growth and they may instigate a

motivational process leading to work engagement and learning at work. Given the

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support of the model (see Bakker & Demerouti, 2007, for a review), our second

hypothesis was as follows:

Hypothesis 2a: Time demands at work are more robustly related to need for recovery

and job exhaustion than are job control and perceived justice of the supervisor.

Hypothesis 2b: Job control and perceived justice of the supervisor are more robustly

related to work engagement than are time demands at work.

Our line of reasoning for the moderating role of recovery experiences in the work

characteristics�well-being outcomes relationship was as follows: As personal strategies

by which individuals try to restore their energy resources, recovery experiences can

affect the strain process. This may occur, for example, on the basis of the stressor

reactivity model (Bolger & Zuckerman, 1995; see also Kammeyer-Mueller, Judge, &

Scott, 2009). Stressor reactivity indicates to what extent an individual is likely to

express strain reactions to the situation perceived as stressful. We can expect that

individuals with well-functioning recovery experiences (i.e. high levels of detachment,

relaxation, mastery, and control) may have less strain when job stressors are

experienced than individuals with poor recovery experiences. Thus, with the help of

these personal recovery experiences, individuals in stressful job situations can replenish

their resources and maintain their well-being. This means that the link between work

characteristics and occupational well-being can be moderated by recovery experiences.

Because job exhaustion is considered a more serious sign of the long-term strain

process than need for recovery, we expected that recovery experiences might have a

stronger moderating role at the beginning of the strain process, that is, in relation to

need for recovery. However, job exhaustion, as the core symptom of burnout and as a

long-term strain indicator, may be more difficult to buffer against. In addition, we

expected that this may apply in the same way to work engagement because it is

described as the positive antipode of burnout. This led to our third hypothesis:

Hypothesis 3: Recovery experiences (psychological detachment, relaxation, mastery, and

control) buffer against the negative effects of time demands, lack of job control, and lack

of justice of the supervisor more robustly on need for recovery than on job exhaustion

and work engagement.

Method

Participants and procedure

The original sample (N�1042) included employees of five organizations from various

sectors such as business, telecommunications and information technology, hotel and

catering, travel services, and education. By sampling different organizations, we

wanted to capture employees from a variety of different jobs. The data collection was

performed in spring 2007, using a 12-page questionnaire distributed to each employee

to his or her workplace. The completed questionnaires were returned in closed

envelopes to the researchers by mail. Of the employees contacted, 527 returned the

completed questionnaire after a reminder, yielding a response rate of 50.6%.

Of the participants, 52.9% were women. Participants’ mean age was 42.4 (SD�11.7). Most participants (77.1%) were living with a partner (either married or

cohabiting), and 43.1% had children (average of two) living at home. The majority

(60.0%) had an academic degree, 21.0% had a higher vocational diploma, and the

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rest (19.0%) had a vocational school education or less. Of the participants, 52.9%

worked in the public sector as teachers and researchers, and 47.1% worked in the

private sector in hotels (16.5%), in an information technology company (11.2%), in

travel services (8.9%), and in hardware stores (10.4%). Most participants had apermanent job (68.2%), and worked full-time (86.8%). Mean working hours per

week were 43.3 hours (SD�9.9).

Measures

Recovery experiences. Each recovery experience � psychological detachment, relaxa-

tion, mastery, and control � was measured using the Recovery Experience

Questionnaire (Sonnentag & Fritz, 2007). Participants were asked to respond to the

items with respect to their free time after work. The relaxation scale included three

and other scales four items, for example, ‘‘I use the time to relax’’ (relaxation), ‘‘I

distance myself from my work’’ (psychological detachment), ‘‘I seek out intellectualchallenges’’ (mastery), and ‘‘I decide my own schedule’’ (control). One item from the

original relaxation scale was removed (‘‘I kick back and relax’’) due to the observed

cross-loading on two factors shown in an as yet unpublished study by Kinnunen,

Feldt, Siltaloppi, and Sonnentag. The hypothesized four-factor structure of the

Finnish Recovery Experience Questionnaire was supported in the same study. (The

results of this study are available on application from the authors.) The items were

rated on a 5-point scale ranging from 1 (totally agree) to 5 (totally disagree) and

recoded so that a high score on each scale indicates a high level of the experienceunder study. Internal consistency (Cronbach’s alpha) was .89 for psychological

detachment, .82 for relaxation, .83 for mastery, and .85 for control.

Psychosocial work characteristics. To assess the psychosocial work characteristics �time demands, control at work, and justice of the supervisor � we used the

QPSNordic Questionnaire (Lindstrom et al., 2000). Time demands at work included

four items (e.g. ‘‘Do you have too much work?’’), job control four items (e.g. ‘‘Can

you influence your workload?’’) and justice of the supervisor three items (e.g. ‘‘My

immediate supervisor treats employees fairly and impartially’’) which were scored on

a 5-point rating scale ranging from 1 (very seldom or never) to 5 (very often oralways). On the scale of justice of the supervisor, there was also an option of ‘‘no

immediate supervisor.’’ Those choosing this option (n�21) were excluded from the

analysis. The Cronbach’s alphas were .78 for time demands, .73 for job control, and

.83 for justice of the supervisor.

Occupational well-being. To assess the short-term effects of a day at work, we

measured need for recovery by nine items from the Need for Recovery Scale

(Sluiter, van der Beek, & Frings-Dresen, 1999). All the items we used focus on the

time after the working day (e.g. ‘‘When I get home from work, I need to be left in

peace for a while’’) and they were rated on a 4-point scale from 1 (never) to 4(always). High scores reflect high levels of need for recovery. The Cronbach’s alpha

of the scale was .89.

Job exhaustion was measured using the 5-item exhaustion scale of the Maslach

Burnout Inventory-General Survey (Kalimo, Hakanen, & Toppinen-Tanner, 2006;

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Maslach, Jackson, & Leiter, 1996). The items (e.g. ‘‘I feel emotionally drained from

my work’’) were scored on a 7-point rating scale ranging from 0 (never) to 6 (daily).

The Cronbach’s alpha of the job exhaustion scale was .93.

Work engagement was measured by the scales of vigour and dedication from the

9-item Utrecht Work Engagement Scale (Schaufeli, Bakker, & Salanova, 2006),

which has also been found to be valid in Finnish occupational samples (Seppala et

al., 2009). Thus, we focused on assessing the core dimensions of work engagement

(Gonzalez-Roma et al., 2006). Both scales of vigour (e.g. ‘‘At my work, I feel bursting

with energy’’) and dedication (e.g. ‘‘I am enthusiastic about my work’’) include three

items and were rated on a 7-point scale ranging from 0 (never) to 6 (daily). Because

of a high mutual correlation of the two scales (r�.71, pB.001), we combined them

into a single scale of work engagement. The Cronbach’s alpha of this combined scale

was .83.

Control variables. In the analyses, we controlled for gender (1�woman, 2�man), age

(in years), education (1�low, 3�high), employment sector (1�public, 2�private),

and working hours per week, because these variables have been shown to be significant

in relation to occupational well-being (e.g. Kinnunen, Feldt, & Makikangas, 2008;

Mauno, Kinnunen, Makikangas, & Natti, 2005).

Data analysis

Moderated multiple regression analysis (see Baron & Kenny, 1986) was used as the

principal data analysis technique to test the direct and interaction effects of

psychosocial work characteristics and recovery experiences (i.e. moderators) on the

indicators of occupational well-being. We performed hierarchical multiple regression

analysis for each dependent variable using the following procedure: the demographic

variables (gender, age, education, hours worked weekly, employment sector) were

entered at step 1 to control for their effects; the psychosocial work characteristics

(time demands, job control, and justice of the supervisor) were entered at step 2 and

the moderator variables (psychological detachment, relaxation, mastery, and

control) at step 3 to examine their main effects, and finally the interaction terms

of each recovery experience with psychosocial work characteristics (total of 12

interactions) were entered at the last step of the equation. However, from the final

models all interaction terms which did not originally correlate or finally significantly

contribute to the equation were excluded (removed one by one and re-analyzed).

Results

Descriptive results

The means, standard deviations, and correlations of all the study variables are

presented in Table 1. As shown in Table 1, the intercorrelations showed, first, that

psychosocial work characteristics were related to the hypothesized well-being

outcomes (except that time demands were not related to work engagement),

especially to need for recovery and job exhaustion. Although the psychosocial

work characteristics correlated with each other, the correlations were fairly weak.

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Table 1. Means, standard deviations, and intercorrelations of the study variables (N�506�527).

Variables M SD 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14.

1. Gendera � �2. Age (years) 42.35 11.66 .02

3. Educationb 2.41 0.79 .05 .31***

4. Working hours

per week

43.26 9.93 .01 .38*** �.35***

5. Employment

sectorc

� � .43*** �.54*** �.77*** �.45***

6. Time demands 3.48 0.79 �.15*** �.28*** .20*** .51*** �.35***

7. Job control 3.16 0.79 .17*** .14** .41*** .16*** �.39*** �.17***

8. Justice of the

supervisor

3.84 0.94 .12** �.06 �.02 �.14** .10* �.27*** .24***

9. Psychological

detachment

3.10 0.98 .15** �.26*** �.26*** �.39*** .36*** �.46*** �.01 .21***

10. Relaxation 3.72 0.82 .07 �.17*** �.19*** �.29*** .29*** �.33*** .07 .24*** .54***

11. Mastery 3.43 0.81 .09* .16*** .03 .12** �.01 �.06 .10* .10* .01 .27***

12. Control 3.74 0.82 .05 �.14** �.19*** �.20*** .28*** �.26*** .15** .25*** .41*** .60*** .27***

13. Need for

recovery

2.19 0.55 �.21*** .09* �.03 .13** �.07 .38*** �.30*** �.42*** �.46*** �.39*** �.19*** �.41***

14. Job

exhaustion

1.74 1.40 �.14** .06 �.01 .16*** �.06 .43*** �.31*** �.41*** �.36*** �.29*** �.16*** �.26*** .69***

15. Work

engagement

4.34 1.22 �.04 .11* .02 .13** �.06 �.04 .25*** .27*** .11* .11* .29*** .23*** �.39*** �.43***

Note: a1� female, 2�male; b1�low, 3�high; c1�public, 2�private.*pB.05; **pB.01; ***pB.001.

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Second, the recovery experiences correlated with the outcomes; the highest

correlations were again with need for recovery. The recovery experiences correlated

significantly with each other (except for psychological detachment and mastery), as

did the outcome variables. Among the recovery experiences, the highest correlation(r�.60) was between relaxation and control. Despite this high correlation, our

earlier confirmatory factor analyses (CFAs) showed that all the recovery experiences

are separate constructs. Of the outcome variables, need for recovery and job

exhaustion correlated highest (r�.69). Due to this high mutual correlation, we

investigated whether these two constructs are separate using confirmatory factor

analysis. We tested both one-factor (including all items of need for recovery and job

exhaustion) and two-factor models (items of need for recovery and job exhaustion

were set to their own factors) using the Mplus 5.0 programme (Muthen & Muthen,1998�2007). The goodness-of-fit statistics supported the two-factor model [x2(35)�367.516, CFI�.93, TLI�.98, RMSEA�.130] more than the one-factor model

[x2(32)�679.662, CFI�.87, TLI�.95, RMSEA�.196]. The chi-square difference

test implemented in Mplus for WLSMV method (see Mplus Technical Appendices at

www.statmodel.com) supported the goodness of the two-factor model compared to

the unidimensional structure of the scales [Dx2 (1)�145.700, pB.001]. Thus, the two

constructs turned out to be separate.

Third, the control variables showed only minor relations to the well-beingoutcomes. However, their correlations with recovery experiences were moderate; the

highest correlation was with high weekly working hours and poor psychological

detachment (r��.39). Weekly working hours also correlated strongly with time

demands at work (r�.51). In addition, the control variables showed strong mutual

correlations. The strongest correlations were between employment sector and

education (r��.77) and between employment sector and age (r��.54). Those

working in the public sector were better educated and older than employees in the

private sector. Due to these strong correlations, employment sector was excludedfrom the regression analyses in order to avoid multicollinearity.

Testing the research hypotheses

Direct effects of work characteristics and recovery experiences on well-being

Regression analyses are reported in Table 2 for need for recovery and job exhaustion

and in Table 3 for work engagement. As shown in Table 2, both need for recovery and

job exhaustion were explained by psychosocial work characteristics and recoveryexperiences. The controls had only a minor role. Of the work characteristics, high

time demands and lack of justice of the supervisor made the greatest (pB.001)

contributions to both dependent variables. Also, lack of job control was related to

high levels of need for recovery (pB.01) and job exhaustion (pB.001). Of the

recovery experiences, poor psychological detachment (pB.001) contributed most to

the explanation for both dependent variables. In addition, lack of control (pB.001)

explained need for recovery, and low mastery explained both need for recovery (pB

.05) and job exhaustion (pB.05). Altogether, need for recovery (15%) was betterexplained by recovery experiences compared to job exhaustion (5%).

Work engagement was explained by job control and justice of the supervisor

(pB.001). Of the recovery experiences, mastery made the most significant

contribution (pB.001), but psychological detachment (pB.01) was also related to

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Table 2. Results of hierarchical regression analyses for need for recovery and job exhaustion.

Need for recovery (n�485) Job exhaustion (n�486)

Independent variables r b ^R2 R2 r b ^R2 R2

Step 1: Demographics .07*** .07*** .05*** .05***

Gender (1�f, 2�m) �.21*** �.05 �.15*** .01

Age (in years) .11** .05 .07 �.01

Education (1� low, 3�high) �.02 �.10* �.01 �.03

Working hours per week .14** �.08 .14** �.08

Step 2: Work characteristics .24*** .31*** .28*** .33***

Time demands .40*** .17*** .45*** .30***

Job control �.30*** �.13** �.31*** �.16***

Justice of the supervisor �.43*** �.23*** �.42*** �.24***

Step 3: Recovery experiences .15*** .45*** .05*** .37***

Psychological detachment �.47*** �.29*** �.37*** �.20***

Relaxation �.40*** �.03 �.31*** �.02

Mastery �.20*** �.09* �.15*** �.08*

Control �.43*** �.17*** �.27*** �.02

Step 4: Interactions .01** .47*** .01* .38***

Time demands�Relaxation � � �.08* �.08*

Job control�Detachment .11** .09* � �Job control�Mastery .11* .08* � �

Note: r�Pearson correlation, b�standardized beta-coefficient from the final step, ^R2�change in explanation rate in each step, R2�explanation rate.*pB.05; **pB.01; ***pB.001.

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work engagement. Altogether, recovery experiences explained 7% of the variance of

work engagement. Again, controls had only a minor role; the most notable finding

was that high weekly working hours were linked to high work engagement.

Thus, our hypothesis 1, expecting links from all recovery experiences to all

occupational well-being indicators, received only partial support. Our hypothesis

2a, suggesting that job demands (time demands) are related more robustly than job

resources (job control and justice of the supervisor) to need for recovery and job

exhaustion, did not receive support. Hypothesis 2b, expecting more robust

relations of job resources than job demands with work engagement, was fully

supported.

Moderator effects of recovery experiences on psychosocial work

characteristics�well-being relationship

As seen from Table 2 (step 4), a few significant moderator effects were also detected.

First, the interaction terms between job control and detachment (b�.09) and job

control and mastery (b�.08) on need for recovery were significant. These effects are

shown graphically in Figure 1 (a�b). These graphical representations of the

interactions were derived using the standardized regression coefficients of the

regression lines for employees with high (1 SD above the mean) and low (1 SD below

the mean) scores on the moderator variables. As Figure 1 (a�b) shows, employees

with high detachment reported less need for recovery, both generally and especially

in a low control situation, compared to those with low detachment. Further, less

need for recovery was reported under the condition of low job control with high

mastery compared to that with low mastery.

Table 3. Results of hierarchical regression analysis for work engagement.

Work engagement (n�484)

Independent variables r b ^R2 R2

Step 1: Demographics .02* .02*

Gender (1�f, 2�m) �.04 �.14**

Age (in years) .12** .08

Education (1�low, 3�high) .01 �.10*

Working hours per week .12** .12*

Step 2: Work characteristics .13*** .16***

Time demands �.03 .07

Job control .24*** .21***

Justice of the supervisor .28*** .22***

Step 3: Recovery experiences .07*** .23***

Psychological detachment .12** .14**

Relaxation .16*** �.03

Mastery .28*** .22***

Control .23*** .09

Note: r�Pearson correlation, b�standardized beta-coefficient from the final step, ^R2�change inexplanation rate in each step, R2�explanation rate.*pB.05; **pB.01; ***pB.001.

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Second, the interaction effect between time demands and relaxation (b��.08)

on job exhaustion was significant. This moderator effect is illustrated in Figure 2. As

shown in Figure 2, employees reported more job exhaustion under conditions of high

time demands and low relaxation, whereas employees with high relaxation were

better protected from the negative effects of high time demands on job exhaustion.

Third, none of the interaction terms turned out to be significant for work

engagement.

Thus, our hypothesis 3, expecting more robust moderator effects on need for

recovery than on job exhaustion and work engagement, received partial support;

there were two significant moderator effects on need for recovery and one on job

exhaustion.

Discussion

Direct and moderator roles of recovery experiences

The purpose of this study was to examine the direct links of recovery experiences to

occupational well-being as well as the moderator role of these experiences in the

relation between psychosocial work characteristics and occupational well-being. Our

first hypothesis, related to the direct relations of recovery experiences with

-0.4

-0.2

0

0.2

0.4

0.6

Job control

Nee

d f

or

reco

very

Low psychologicaldetachment

High psychologicaldetachment

Low High

Figure 1a. Significant interaction effect between job control and psychological detachment

on need for recovery.

-0.2

-0.1

0

0.1

0.2

0.3

0.4

Low High

Job control

Nee

d f

or

reco

very

Low mastery

High mastery

Figure 1b. Significant interaction effect between job control and mastery on need for

recovery.

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occupational well-being, gained partial support. When studying all the recovery

experiences together (in the regression analysis), poor psychological detachment

showed the most significant association with the negative indicators (need for

recovery and job exhaustion), and mastery showed the most significant association

with the positive indicator (work engagement). Furthermore, both these recovery

experiences were related to each well-being indicator examined. Poor control in off-

job time had a direct relation only with need for recovery, and relaxation did not

have any relation with the occupational well-being indicators examined. The strong

correlation of relaxation with control in off-job time (r�.60) and psychological

detachment (r�.54) might partly explain these non-existent relationships. It is

noteworthy that at the correlational level relaxation was significantly related

especially to the negative indicators of occupational well-being. Altogether, our

findings suggest that psychological detachment is the most powerful recovery

experience; its relation to low levels of need for recovery and job exhaustion was

most significant. Thus, better the psychological detachment from work, lesser the job

exhaustion and need for recovery. This result corroborates earlier findings reporting

its effectiveness in this regard (e.g. Sonnentag & Bayer, 2005; Sonnentag, Bienewies

et al., 2008). Only Sonnentag and Fritz (2007) examined the correlations of all

recovery experiences but with partly different well-being indicators. Also, in their

study, poor psychological detachment showed the most significant connection with

impaired well-being.

Overall, it seems that psychological detachment and relaxation, which are based

on the Effort-Recovery Model (Meijman & Mulder, 1998), have at the correlational

level more robust links to negative well-being indicators. Instead, those recovery

experiences based on Conservation of Resources Theory (Hobfoll, 1998), that is,

mastery and control, are linked more robustly to the positive indicator of work

engagement. These findings can be interpreted as giving some support to the view

based on the JD�R model (Demerouti et al., 2001) that work engagement is

particularly the result of resources; in our case, the result of recovery experiences

aiming at gaining internal resources. Altogether, our results suggest, in line with our

hypothesis 1, that psychological detachment especially but also relaxation, mastery

and control in off-job time, are prerequisites for psychological recovery, and further,

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

Low High

Time demands

Job

exh

aust

ion

Low relaxation

High relaxation

Figure 2. Significant interaction effect between time demands and relaxation on job

exhaustion.

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if psychological recovery does not occur, need for recovery, job exhaustion, and

lowered work engagement follow.

Our hypothesis 2a suggesting that job demands (i.e. time demands at work) are

related more robustly than job resources (i.e. job control and justice of the

supervisor) to need for recovery and job exhaustion, did not receive support.

Hypothesis 2b, expecting more robust relations of job control and justice of thesupervisor than time demands with work engagement, was fully supported. All these

expected findings were based on the JD�R Model (Demerouti et al., 2001), in

accordance with which the idea that job resources may initiate a motivational

process leading to work engagement, received support. When job exhaustion and

need for recovery were examined, lack of resources also proved a significant

contributor. This finding is in line with earlier studies in which both job demands

and lack of resources have been related to job exhaustion and need for recovery (e.g.

Demerouti et al., 2001; Sonnentag & Fritz, 2007; Sonnentag & Zijlstra, 2006).

Our third hypothesis, concerning the moderating role of recovery experiences in

the relationship between psychosocial work characteristics and occupational well-

being, received partial support: psychological detachment, mastery, and relaxation

proved significant moderators. Although the effects cannot be regarded as strong,

psychological detachment and mastery were protective mechanisms against in-

creased need for recovery under poor job control. Relaxation showed a protective

effect against job exhaustion under high time demands. Thus, our hypothesis that

recovery experiences may have a more robust moderator role at the beginning of the

strain process (i.e. in relation to need for recovery rather than in relation to jobexhaustion) got partial support; there were more significant moderator effects on

need for recovery. However, no similar moderator effects were found for work

engagement.

Moderator effects are difficult to detect in non-experimental field studies, and

even when such effects are found, the explanation rates are often disconcertingly low

(e.g. McClelland & Judd, 1993). Evans (1985) concluded that even those explaining

as little as 1% of the total variance should be considered important. Our results

suggest that different recovery experiences may function as moderators in different

job conditions. In the case of high time demands, relaxation (i.e. doing relaxing

things, taking time for leisure) may help recovery, whereas in the case of lack of job

control either psychological detachment (i.e. distancing oneself from work) or

mastery (i.e. doing challenging things) on off-job time may be helpful strategies.

However, regarding lack of justice of the supervisor, the recovery experiences did not

provide any relief. On the contrary, lack of justice of the supervisor had a strong

direct link to the indicators of well-being, confirming that it is a major source of

psychosocial strain at work (Elovainio et al., 2003; Kivimaki et al., 2003).

Altogether, our moderator findings were quite modest and they should be confirmedin future studies.

Limitations

This study has some limitations that are worth noting. Above all, the study was

cross-sectional, meaning that no reliable conclusions regarding the causal direction

of effects can be drawn. As an example of this, our results might indicate that poor

recovery experiences impair occupational well-being, but it could also be that

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employees suffering from impaired occupational well-being cannot enjoy positive

recovery experiences. Longitudinal studies are needed to confirm both the direct and

moderator roles of recovery experiences between psychosocial work characteristics

and occupational well-being. In addition, all the data were based on self-reports, socommon method variance may have biased our findings. However, Spector (2006)

has argued that common method variance does not automatically inflate associa-

tions measured with self-report measures. Nevertheless, in the future, for example,

physiological data on the recovery process integrated into recovery experiences could

be useful. Further, the response rate was 50.6%. Although the rate is quite low, it is

not unusually low for studies conducted in organizations (Roth & BeVier, 1998). In

addition, the respondents represented the original sample in terms of gender (the

only background information available) reasonably well, and the fact that the samplewas heterogeneous adds the generalizability of the findings.

Conclusion

By studying recovery experiences, our study contributed to a better understanding of

the mechanisms underlying the recovery process. First, our study revealed thatthe recovery experiences examined � psychological detachment and mastery in

particular � had direct links to occupational well-being. Second, recovery experiences

seemed to some extent to buffer against the adverse effects of psychosocial work

characteristics on occupational well-being. All in all, they play a significant role in

maintaining well-being.

Acknowledgements

The research project ‘‘The Role of Recovery from Job Strain in Maintaining Occupational

Well-being’’ was financially supported by The Finnish Work Environment Fund (grant No.

106046).

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