Challenge and hindrance demands in relation to self-reported job performance and the role of restoration, sleep quality, and affective rumination

Journal of Occupational and Organizational Psychology (2019), 92, 225–254 ©2018 The Authors. Journal of Occupational and Organizational Psychology published by John Wiley & Sons Ltd on behalf of British Psychological Society www.wileyonlinelibrary.com Challenge and hindrance demands in relation to self-reported job performance and the role of restoration, sleep quality, and affective rumination Michelle Van Laethem 1 * , Debby G. J. Beckers 2 , Jessica de Bloom 3,4 , Marjaana Sianoja 3 and Ulla Kinnunen 3 1 Department of Work and Organizational Psychology, University of Amsterdam, The Netherlands 2 Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands 3 Faculty of Social Sciences (Psychology), University of Tampere, Finland 4 Faculty of Economics and Business, HRM &OB, University of Groningen, The Netherlands Longitudinal research on the relationship between job demands and job performance and its underlying mechanisms is scarce. The aims of this longitudinal three-wave study among 920 Finnish employees were to ascertain whether (1) challenge job demands (i.e.,workload, cognitive demands) and self-reported job performance are positively related over time, (2) job insecurity (i.e., a hindrance demand) and job performance are negatively related over time, (3) restorative experiences during off-job time and sleep quality are underlying mechanisms in these relations,and (4) affectiverumination mediates the proposedrelations of job demands and job insecurity with restoration and sleep quality. Self-report data were analysed with structural equation modelling. The results revealed a positive, temporal relationship between challenge job demands and job performance (task and contextual performance) across 1 year, but no temporal relationship between job insecurity and selfreported job performance. Moreover, high challenge job demands were positively related to the restorative value of off-job activities, and favourable restoration was positively related to subsequent task performance. Finally, affective rumination mediated the relationshipof challenge job demands with both restoration and sleep quality. Job insecurity was not longitudinally related to restoration, sleep quality, or affective rumination. The implications of our findings for occupational health psychology are discussed. Practitioner points Provide employees with sufficient job resources (e.g., high autonomy and social support) to adequately deal with high job demands. Allow employees sufficient time to recover from high job demands during off-job time and provide training sessions in recovery, relaxation, meditation, and goal setting. Employees may attempt to counteract perseverative thoughts by actively pursuing distracting restoration activities (e.g., exercise, meditation). This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. *Correspondence should be addressed to Michelle Van Laethem, Department of Work and Organizational Psychology, University of Amsterdam, P.O. Box 15919, 1001 NK Amsterdam, The Netherlands (e-mail: [email protected]). DOI:10.1111/joop.12239 225 Numerous scientific theories and empirical studies have focused on explaining how job demands (i.e., stressors) affect health and job performance (Cheng & Chan, 2008; Gilboa, Shirom, Fried, & Cooper, 2008; Schaufeli & Taris, 2014). Job stress models, such as the job demands–control model (Karasek, 1979) and the job demands–resources model (Demerouti, Bakker, Nachreiner, & Schaufeli, 2001; Schaufeli & Taris, 2014), suggest that job demands are important predictors of well-being and job performance. In addition, it has been proposed that some job demands may be appraised as challenges (i.e., as challenge demands) and may have a favourable effect on performance, while others may be appraised as hindrances (i.e., as hindrance demands), negatively impacting performance (Cavanaugh, Boswell, Roehling, & Boudreau, 2000; LePine, Podsakoff, & LePine, 2005). However, few empirical studies so far have aimed to provide a detailed picture of the mechanisms underlying the pathway from high challenge and hindrance demands to job performance. Two underlying mechanisms may be key in explaining the complex relationship between job demands and job performance: restorative experiences during off-job time and sleep quality. These are essential for replenishment of an employee’s resources during off-job time (Meijman & Mulder, 1998), enabling sustainable performance. To date, the role of restoration and sleep quality as underlying mechanisms in the association between job demands and job performance has been often overlooked and not properly studied (cf. mostly with cross-sectional designs). A more detailed picture of the pathway from job demands to performance also includes a focus on the role of stress-related cognitive processes, like rumination, preceding and influencing restoration and sleep quality ( Akerstedt, Nilsson, & Kecklund, 2009). Affective rumination refers to a negative thought process defined as ‘a cognitive state characterized by the appearance of intrusive, pervasive, recurrent thoughts, about work, which are negative in affective terms’ (Cropley & Zijlstra, 2011, p. 493). Affective rumination may act as a mediator in the relationship between job demands on the one hand, and restoration and sleep quality on the other hand. Examining challenge and hindrance demands in relation to job performance, as well as possible underlying mechanisms, is warranted for both theoretical and practical reasons. From a theoretical perspective, this study contributes to the literature by addressing important research gaps: Few empirical studies so far aimed to provide a detailed picture of the underlying mechanisms in the pathway from high challenge and hindrance demands to job performance. Additionally, longitudinal designs have rarely been used to examine the temporal relations between the concepts of these pathways. The three-wave longitudinal design used in our study offers a unique possibility to study the pathways and the consequences for job performance for up to 2 years. Thus theoretically, our aim was to fill these research gaps and expand the challenge–hindrance stressor model developed by Cavanaugh et al. (2000) by including potential underlying mechanisms of the longterm demand–performance relationship. From a practical perspective, our findings may be of help to improve job design, to develop and plan organizational interventions, and enhance productivity of the workforce. The specific objectives of this study were to examine whether (1) challenge demands and job performance are positively related over time, (2) hindrance demands and job performance are negatively related over time, (3) restorative experiences during off-job time and sleep quality are underlying mechanisms in these relations, and (4) affective rumination mediates the relations of challenge and hindrance demands with restoration (i.e., the restorative value of off-job activities) and sleep quality. 226 Michelle Van Laethem et al. Challenge and hindrance demands in relation to job performance Researchers initially assumed high levels of job demands to be invariably unfavourable for employees’ performance (Kwag & Kim, 2009). However, previous research revealed inconsistent findings, including evidence for both negative and positive relations (see LePine et al., 2005; for a review). This indicates that the relationship between job demands and job performance is complex. The challenge–hindrance stressor model of Cavanaugh et al. (2000) addresses this complexity. A core element of the model is the distinction between ‘challenge’ and ‘hindrance’ demands. Challenge demands refer to demands offering an opportunity for personal growth and rewards, such demands being workload and job complexity (Cavanaugh et al., 2000; Crawford, LePine, & Rich, 2010; Webster, Beehr, & Love, 2011). To the extent that they are not too high, these challenge demands may be positively related to job performance. Hindrance demands refer to stressful demands such as long-term exposure to high job insecurity (i.e., the perceived threat of losing the current job), role ambiguity, or role conflict (Cavanaugh et al., 2000; Crawford et al., 2010; Webster et al., 2011). These demands are either not associated with the opportunity for personal growth and rewards or may even hinder them and are expected to be negatively related to job performance in the long run. A meta-analysis of mostly cross-sectional studies by LePine et al. (2005) indeed found support for the challenge–hindrance stressor model. In the studies included in the metaanalysis, job performance was most often self-reported and reflected overall job performance, but also objective assessments and supervisor and peer ratings were used. More specifically, it revealed that many studies reported a positive relation between challenging job demands (e.g., workload, cognitive demands) and job performance. Additionally, research has supported a slight negative relation between job insecurity (i.e., a hindrance demand) and job performance (see Cheng & Chan, 2008; Sverke, Hellgren, & N€ aswall, 2002, for meta-analyses). Most of the studies in these meta-analyses relied on selfreported measures of performance. Notably, research on the demand–performance association has been quite onedimensional, with insufficient attention paid to the richness of the performance concept (see Koopmans et al., 2011; Sonnentag, Volmer, & Spychala, 2008). Most earlier studies have almost exclusively focused on task performance. However, performance is a multidimensional concept encompassing an outcome aspect and behavioural aspect (Sonnentag et al., 2008). The outcome aspect refers to the product or result of an employee’s behaviour (e.g., number of sales, targets attained). The behavioural aspect consists of the behaviour itself and what employees actually do to establish the preferred outcomes (e.g., sale negotiations with customers). In our study, we included both aspects of performance. The behavioural aspects are mostly reflected in the measurement of contextual performance, and the outcome aspects are central in the measurement of task performance. The distinction between contextual and task performance is another element of the multidimensionality of job performance. Whereas task performance refers to employee’s success in performing the duties formally required on the job (reflecting accomplishment of tasks), contextual performance refers to work behaviours that benefit the organizational, social, and psychological environment in a broader sense, potentially also supporting core task performance but not formally required on the job (Motowildo, Borman, & Schmit, 1997). It includes organizational citizenship behaviour and prosocial behaviour at work (Sonnentag et al., 2008) such as helping colleagues with their tasks or endorsing organizational initiatives. As both contextual performance and task performance are key to organizational prosperity (Bolino & Turnley, 2005; Podsakoff, MacKenzie, Paine, & Bachrach, 2000), it Job demands, restoration, and sleep 227 is essential to include both types of performance in research, as each performance dimension may be predicting different aspects of organizational success (Sonnentag et al., 2008). The few studies that examined challenge demands (e.g., workload, time pressure) in relation to contextual performance found support for a positive relationship (Ohly & Fritz, 2010; Rodell & Judge, 2009) or found no evidence for a relation between challenge demands and contextual performance (Wallace, Edwards, Arnold, Frazier, & Finch, 2009). So far, most earlier studies used various designs such as cross-sectional or experience sampling and relied on self-rated and/or supervisor-rated performance. Moreover, task and contextual performance are often combined into one overall factor of job performance. The relationship of challenge demands with task and contextual performance may differ and may thus be an explanation for some of the previous null-findings in studies focusing on one overall performance concept. Having a high workload and cognitive demands may leave little room (no time, no mental capacity) for work behaviours beyond one’s formal work tasks. It may be hard to ‘walk the extra mile’ if one is burdened with a lot of work and deadlines, resulting in a weaker positive relationship between challenge demands and contextual performance compared to task performance. For hindrance demands, the negative relationship with contextual performance seems more straightforward. Most studies have revealed evidence for a negative relation between hindrance demands (e.g., job insecurity) and contextual performance (King, 2000; K€ onig, Debus, H€ ausler, Lendenmann, & Kleinmann, 2010; Reisel, Probst, Chia, Maloles, & K€ onig, 2010). All of the mentioned studies used self-rated behaviour measures, and only K€ onig et al. (2010) used supervisor ratings in addition to self-report measures. Performance has often been assessed with other ratings (e.g., supervisor ratings, coworker ratings) which are considered to be less susceptible to social desirability biases compared to self-reported performance (Carpenter, Berry, & Houston, 2014; Chan, 2009). However, employees are often more knowledgeable about their own work behaviour and actual work tasks than their supervisors or co-workers (Berry, Carpenter, & Barratt, 2012; Carpenter et al., 2014; Chan, 2009). Moreover, self-ratings are more feasible when striving for large datasets. Even though job performance ratings may be slightly inflated, the focus in our longitudinal study was on changes over time within the same persons. For these reasons, we chose to assess self-reported performance in the present study. In our longitudinal study, we expect to replicate earlier cross-sectional findings and additionally find longitudinal support for a positive temporal relationship between challenge job demands (i.e., workload and cognitive demands) and two core dimensions of job performance, that is, task performance and contextual performance. We anticipate the positive relationship with contextual performance to be weaker compared to task performance. Moreover, we expect to find longitudinal evidence for a negative relationship between hindrance demands (i.e., job insecurity) and both dimensions of job performance. Hypothesis 1: Challenge demands (i.e., workload and cognitive demands) at T1 and T2 are positively related to task performance (H1a) and contextual performance (H1b) 1 year later. The relationship between challenge demands and contextual performance will be weaker compared to the relationship with task performance. Hypothesis 2: Hindrance demands (i.e., high job insecurity) at T1 and T2 are negatively related to task performance (H2a) and contextual performance (H2b) 1 year later. 228 Michelle Van Laethem et al. Insufficient restoration and sleep quality as mechanisms In addition to the scarcity of longitudinal research on challenge and hindrance demands and their connection to two key aspects of job performance, specific underlying mechanisms in these relations are not yet fully understood (Sonnentag et al., 2008). Earlier studies have found that some factors, for example, job strain, offset the positive relationship between challenge demands and task and contextual performance (LePine et al., 2005; Rodell & Judge, 2009). More research into underlying mechanisms, and in particular longitudinal research, is necessary to understand the complex relationship between job demands and job performance. Poor restoration during off-job time may be one likely mechanism that may offset the relation between challenging job demands and favourable job performance and may explain the relation between hindrance demands (i.e., job insecurity) and unfavourable job performance. Restoration refers to processes of replenishing resources or capacities that have been depleted by exposure to demands of everyday life (Hartig, 2004). In occupational health psychology, this process is usually referred to as ‘recovery’ (Korpela, de Bloom, & Kinnunen, 2015). According to effort–recovery theory (Meijman & Mulder, 1998), replenishment of resources after work is crucial to reduce load effects (unavoidably associated with expending effort at work) and to let stress-related psychophysiological systems return to baseline (pre-demand) levels (Geurts & Sonnentag, 2006). When restoration is insufficient while facing new cognitive, emotional, and/or physical challenges, compensatory effort is needed to adequately meet these challenges and to sustain a satisfactory performance level (Hockey, 2013), thereby further increasing the demands on the restoration process. Following McEwen’s (1998) allostatic load theory, a chronic imbalance between effort and restoration will result in an adverse bodily state called ‘allostatic load’, which is proposed to have negative consequences not only for health but also for performance (Hammen, 2005; Kivim€ aki & Kawachi, 2015; McEwen, 2008). Research has shown that high challenge job demands are associated with a greater need for recovery (Sonnentag & Zijlstra, 2006), but also with less effective recovery processes during off-job time, including poorer detachment from work and poorer sleep quality (Kinnunen, Feldt, Siltaloppi, & Sonnentag, 2011; Linton et al., 2015; Sonnentag & Fritz, 2007; Van Laethem, Beckers, Kompier, Dijksterhuis, & Geurts, 2013). Likewise, hindrance demands (i.e., job insecurity) have been associated with decreased restoration and poor sleep quality in several cross-sectional studies (Burgard & Ailshire, 2009; Vander Elst, Baillien, De Cuyper, & De Witte, 2010; Vander Elst, De Cuyper, Baillien, Niesen, & De Witte, 2016; Virtanen, Janlert, & Hammarstrom, 2011). Thus, there seem to be indications that increased challenge and hindrance demands negatively relate to restoration and sleep quality (i.e., sleep quality is defined as sleep in terms of sleep continuity). Based on recovery theories and the limited amount of research so far, we propose insufficient restoration and poor sleep quality to be key mechanisms in offsetting the positive effects of high challenge job demands on job performance and explaining the negative effects of high job insecurity on job performance. Hypothesis 3: Restoration at T2 mediates the relationship between challenge demands (H3a) and hindrance demands (H3b) at T1 and job performance at T3 such that high challenge and hindrance demands are related to decreased restoration, which in turn is related to impaired job performance (in terms of task performance and contextual performance). Job demands, restoration, and sleep 229 Hypothesis 4: Sleep quality at T2 mediates the relationship between challenge demands (H4a) and hindrance demands (H4b) at T1 and job performance at T3 such that high challenge and hindrance demands are related to decreased sleep quality, which in turn is related to impaired job performance (in terms of task performance and contextual performance). Affective rumination as a mechanism In addition to restoration and sleep quality, we examine stress-related cognitive processes following job demands as mechanisms in the job demands–performance relationship. One such cognitive process is affective rumination ( Akerstedt et al.,2009).Accordingto prolonged activation theory (Brosschot, Pieper, & Thayer, 2005) and the perseverative cognition hypothesis (Brosschot, Gerin, & Thayer, 2006), perseverative thought following job demands may be related to prolonged physiological activation and thus delay recovery and sleep. There is some evidence showing that perseverative cognitions are key mediators in the unfavourable relations between job demands and sleep (De Witte, Pienaar, & De Cuyper, 2016; Van Laethem et al., 2015). Moreover, challenge (e.g., workload, cognitive demands) and hindrance (e.g., job insecurity) demands have previously been related to high affective rumination, lower psychological detachment from work during off-job time, and greater need for recovery (H€ oge, Sora, Weber, Peir o, & Caballer, 2015; Kinnunen, Mauno, & Siltaloppi, 2010; Kinnunen et al., 2017). A recent meta-analysis has shown that especially challenge demands relate to poor detachment from work during off-job time (Bennett, Bakker, & Field, 2018), which may refer to affective rumination. Hence, the most likely response of an employee faced with high challenge job demands and high job insecurity is not to adequately detach from work, but to continue a mental connection to work, which may be associated with physiological activation (Sonnentag & Fritz, 2015) to some extent preventing psychophysiological recovery. Thus, affective rumination may act as a mediator in the relationship between challenging job demands and job insecurity on the one hand and restoration and sleep quality on the other. Hypothesis 5: Affective rumination at T2 mediates the relation between challenge demands (H5a) and hindrance demands (H5b) at T1 and restoration at T3 such that high challenge and hindrance demands are related to increased affective rumination, which in turn is related to decreased restoration. Hypothesis 6: Affective rumination at T2 mediates the relation between challenge demands (H6a) and hindrance demands (H6b) at T1 and sleep quality at T3 such that high challenge and hindrance demands are related to increased affective rumination, which in turn is related to impaired sleep quality. See Figure 1 for a heuristic model of our hypotheses. For clarity, the heuristic model was divided into two separate figures: one for challenge demands and one for hindrance demands. Methods Design and participants We tested our hypotheses using a three-wave longitudinal design with time lags of 1 year. Because it is often difficult to define a ‘perfect’ time lag when examining specific temporal 230 Michelle Van Laethem et al. associations, partly due to a lack of theories of change (Kelloway & Francis, 2013), it would be optimal to include multiple measurement waves over different time lags (Sonnentag et al., 2008; Taris & Kompier, 2014). However, in our case this was impossible due to the reality of collecting data in multiple organizations. In this study, we chose time lags of 1 year to examine the long-term lagged relationships, because using time lags of 1 year controls for potential seasonal effects that may affect job demands or job performance (e.g., returning to work from a vacation). In addition, 1-year time lags appear to be most common and useful in longitudinal studies investigating the long-term job demand–strain relationship (see Ford et al., 2014; for a review) and recovery (Kinnunen & Feldt, 2013; Rodriguez-Mu~ noz, Sanz-Vergel, Demerouti, & Bakker, 2012). Also with regard to affective rumination, previous research has shown that perseverative modes of thinking may prevail over longer time periods (Van Laethem et al., 2015). Concerning self-rated performance, most existing research is cross-sectional. As performance is a dynamic construct that varies over time, longitudinal research on the relationship between stressors and performance is warranted (Beal, Weiss, Barros, & MacDermid, 2005). In addition, Sonnentag et al. (2008) expressed a need to systematically investigate time frames as there may not be only one suitable time lag to examine performance. The few longitudinal studies that exist have used a variety of time lags from a few weeks to several years. Given that we examined long-term associations between stressors and performance, we considered a 1-year time lag as an acceptable choice. The study population consisted of employees in 12 Finnish organizations from different sectors. There was high diversity in jobs, and largest sectors were education, Figure 1. (a) The proposed research model for challenge demands without a time frame. All relationships are examined as temporal, that is, from T1 to T2–T3 and from T2 to T3. (b) The proposed research model for hindrance demands without a time frame. All relationships are examined as temporal, that is, from T1 to T2–T3 and from T2 to T3. Job demands, restoration, and sleep 231 public administration, information technology, and media. Organizations were mainly contacted via the client organizations pool of a company providing occupational health care services. Online questionnaire surveys were distributed in three phases. In each phase, information about the study goals was included in the questionnaires. Participants were moreover assured that their responses would be treated in confidence and that participation was voluntary. In 11 organizations, the data were collected in the spring of 2013 (T1), 2014 (T2), and 2015 (T3). One organization (N=603 employees contacted) entered the study 1 year later, and the participants from this company completed the questionnaires in 2014 and 2015. Surveys were either sent directly to the employees’ work email addresses or to a contact person, who distributed the survey (e.g., HR manager). Of the employees contacted at T1 (N=3,593), 1,347 returned the questionnaire after two reminders, yielding a response rate of 37.5%. At T2, the electronic questionnaire was sent to those employees’ email addresses who responded at T1 and who were still employed in the same organizations (N=1,192) and to the employees working in the organization that entered in 2014 (N=603). Of these, 841 (70.6%) and 359 (59.5%), respectively, returned the questionnaire. The final wave was in the spring of 2015 (T3). Again, the survey was sent to those employees’ email addresses who had responded to the previous questionnaire and who had not changed jobs (N=1,140). Of the employees contacted, 920 responded after two reminders (response rate: 80.7%). Of the sample, 62.5% was female, most participants were between 40 and 60 years old (M baseline =47.26, SD baseline =9.79; range: 21–66 years) and were highly educated (41% of participants had a bachelor’s degree or higher). In addition, most participants held a fulltime job and worked at least 38 hr per week (see Table 1 for characteristics of the study sample at T1 in more detail). In analysing sample attrition, we compared the final sample (N=920) to non-respondents at T3. There were no differences in gender, education, occupational status, or having children. However, the respondents more often had a permanent employment contract (89.8% vs. 80.5%, p<.001), worked more often on regular day shifts (92.5% vs. 87.0%, p<.01), were somewhat older (M=47.3 vs. 46.1 years, p<.001), and worked slightly shorter hours (M=35.2 vs. 36.5 hr, p<.01) than the non-respondents. Measures The present study had a full-panel design as all concepts were measured at every measurement point. Reliability coefficients (Cronbach alphas) of all measures except for the contextual performance measure (<0.70) were at least acceptable (>0.80). Challenge job demands were assessed with three items adapted from Spector and Jex (1998) assessing workload (e.g., ‘How often does your job require you to work very fast?’) and three items inspired by Pejtersen, Kristensen, Borg, and Bjorner (2010) and De Jonge et al. (2007) measured cognitive demands (e.g., ‘How often do you need to display high levels of concentration and precision at work?’). The response scale ranged from 1 (very seldom or never) to 5 (very often or always). All items were combined to calculate an overall score for challenging job demands. Cronbach’s alpha coefficients were 0.84 across T1–T3. Job insecurity as a job hindrance demand was assessed with three items (e.g., ‘I think I might get fired in the near future’) from De Witte (2000). All items were answered on a five-point scale ranging from 1 (strongly disagree) to 5 (strongly agree). Cronbach’s alphas were 0.93 across T1–T3. 232 Michelle Van Laethem et al. Job performance was evaluated with measures of task and contextual performance. Task performance was measured with five items from the personal accomplishment scale of the Maslach Burnout Inventory, which has been validated in Finland (Kalimo, Hakanen, & Toppinen-Tanner, 2006; Maslach, Jackson, & Leiter, 2006). These items (e.g., ‘I have accomplished many worthwhile things in this job’) reflect being able to attain work-related achievements and thus fit well with the definition of task performance presented in the introduction. Answers were given on a seven-point scale ranging from 1 (never) to 7 (always, every day). Cronbach’s alphas ranged between 0.80 and 0.81. Contextual performance was assessed with three items (cf. Goodman & Svyantek, 1999; Staufenbiel & Hartz, 2000). The items (e.g., ‘I volunteer to do things not formally required by my job’) were answered on a five-point rating scale (1 =very seldom or never, 5 =very often or always). Cronbach’s alphas for contextual performance ranged from 0.60 to 0.65. The restoration scale measured the restorative (i.e., resource replenishing) value of off-job activities. It consisted of four items adapted from the Restoration Outcome Scale (Korpela, Yl en, Tyrv€ ainen, & Silvennoinen, 2008). An example item is ‘My free time activities provide me with new enthusiasm and energy for my everyday routines’. All items were scored on a seven-point scale ranging from 1 (not at all) to 7 (completely). Cronbach’s alphas ranged from 0.92 to 0.93. Table 1. Sample characteristics of final sample at T1 N% Gender Men 345 37.5 Women 574 62.4 Undisclosed 1 0.1 Age 21–29 46 5.0 30–39 173 18.8 40–49 274 29.8 50–59 346 37.6 60–66 79 8.6 Undisclosed 2 .2 Educational level Comprehensive school 15 1.6 Vocational qualification or upper secondary education 111 12.1 Specialized vocational qualification 34 3.7 Vocational college qualification 161 17.5 Bachelor’s degree or polytechnic bachelor’s degree 225 24.5 Master’s degree 359 39.0 Doctoral or other higher degree 15 1.6 Average working hours per week 12–23 15 1.6 24–37 385 41.8 38–49 425 46.2 50–60 12 1.3 Undisclosed 83 9.0 Note.T1=time point 1. Job demands, restoration, and sleep 233 demands. Staufenbiel and K€ onig (2010) argue that it may be more appropriate to evaluate each demand based on two dimensions: a challenge and a hindrance dimension. Thus, job insecurity could be a hindrance demand to some extent while simultaneously being a challenge demand to a certain level. Similarly, challenging job demands may have a high score on the challenge dimension, but a low score on the hindrance dimension. This alternative conceptualization of challenge and hindrance demands may explain why this study revealed a positive relationship between challenge job demands and job performance, but no association between job insecurity and job performance. Future studies may empirically test the different conceptualization discussed by Staufenbiel and K€ onig (2010). Based on the different results regarding the association of challenge demands with two important types of job performance, we recommend that future research investigates this difference more closely. Our results also suggest that the common practice of combining both types of performance into one single factor may not be advisable. Possible nullfindings reported in earlier studies may be explained by differences in (strength of) relationships with task or contextual performance. In addition, in future studies a more complete range of different challenge and hindrance demands may be examined. For example, job responsibility and complexity (challenge demands), resource inadequacy, and role ambiguity/conflict (hindrance demands) could be included. Their relationships with job performance may turn out to be different from the ones found in our study. Poor restoration, sleep quality, and affective rumination as underlying mechanisms in the challenge demands–performance relation Our results did not support poor restoration as a mechanism in the pathway from challenge demands to job performance. Contrary to our expectations, we found that employees with higher challenge job demands reported higher subsequent restoration (i.e., higher restorative value of off-job activities), which in turn predicted favourable task performance 1 year later. These findings are partly in line with earlier research on job demands, recovery, and job performance (e.g., Binnewies, Sonnentag, & Mojza, 2010). However, the results are not in line with other research reporting an unfavourable relationship between job demands and recovery processes, including recovery experiences and sleep quality (Kinnunen et al., 2011; Linton et al., 2015; Sonnentag & Fritz, 2007; Van Laethem et al., 2013). One explanation for the unexpected positive relationship between challenge demands and restoration relates to our measurement of restoration. In our research, this variable was not directly operationalized as ‘need for recovery’, but rather as ‘the recovery value of off-job activities’. It could be that for workers faced with high challenge demands, off-job activities have more recuperative value than for workers faced with fewer challenge demands. If an employee experiences high challenge demands, (s)he therefore experiences higher levels fatigue after work and thus the leisure activities pursued may have a high resource replenishing value. This is also in line with the effort– recovery theory (Meijman & Mulder, 1998), which postulates that recovery is mostly needed in demanding and stressful jobs. Thus, the full potential of recovery processes is reached when demands are high (Sonnentag & Fritz, 2015). However, regarding all alternative explanations for the positive relationship between challenge job demands and restoration, it should be kept in mind that the relationship was not robust when isolating hypothesized effects. Before paying too much attention to this effect, the positive relationship should be replicated in future longitudinal studies to ensure its robustness. 240 Michelle Van Laethem et al. No longitudinal evidence was found for a relationship between challenge or hindrance demands and sleep quality. This contradicts some earlier research ( Akerstedt et al., 2015; De Lange et al., 2009), but concurs with some other longitudinal studies on job demands and sleep quality (Van Laethem, Beckers, van Hooff, Dijksterhuis, & Geurts, 2016; Van Laethem et al., 2015). Earlier research into the mechanisms underlying the demand–sleep relationship found that the direct relationship between a demand and sleep often disappeared when simultaneously testing for rumination, as is also the case in the present study. This is generally seen as an indication for rumination as an important underlying mechanism in the job demands–sleep relationship. Experiencing challenge job demands was prospectively associated with an increase in affective rumination, which in turn was related to decreased restoration and sleep quality. Thus, affective rumination was a mediating mechanism in the longitudinal relationship between challenge job demands, restoration, and sleep quality, which lends support to the perseverative cognition hypothesis and prolonged activation theory (Brosschot et al., 2005, 2006) and also to earlier research on this topic (Sonnentag & Fritz, 2015; Van Laethem et al., 2015, 2016). In addition, this study extends the existing research on the job demands–affective rumination–restoration/sleep quality sequence by including different job performance outcomes as distal outcome measures of the pathway. Strengths, limitations, and suggestions for future research The present study has several strengths. First, we employed a full-panel longitudinal design with three waves, which enabled us to explore mediation. In addition, we were able to shed light on the relations between challenge and hindrance demands and two job performance outcomes as well as several explanatory mechanisms such as restoration, sleep quality and affective rumination. Our study also has some limitations. Although longitudinal, our non-experimental study design only allows us to draw tentative conclusions about causal relationships. Future studies may use varying approaches in examining the job demand–performance relationship to optimally investigate the causality of this complex relationship. One example could be an experimental study in which highly challenging job demands are induced in one group and their subsequent restoration, sleep, and performance are compared to that of a control group. In addition, longitudinal studies examining demands in relation to performance may use varying time lags. As outlined in the methods section, we chose to use 1-year time lags. In our study, exposure to challenge and hindrance demands was rather stable (autoregressions were high and ranged between 0.55 and 0.78), so our 1-year time lag implied long-term exposure to certain demands in relation to a change in performance. Other time lags (e.g., day-to-day examination of the same associations), and even varying time lags within the same longitudinal study, may also be interesting to consider in future research as we lack theories of change (Kelloway & Francis, 2013). A second limitation may concern the time frame included in our assessment of sleep quality. All study variables except for sleep quality were measured by asking participants to report their average level of the specific variable, not having a specific time frame in mind. While measuring sleep quality, however, participants were asked to report their sleep quality over the past month. We chose this approach as we were interested in longterm associations between general levels of demands and performance. Therefore, we did not include a specific time frame for most of the study variables. Only for sleep quality we chose a specific time frame of 1 month as previous sleep research suggests that a 1-month time frame is adequate to assess sleep (e.g., Jenkins, Stanton, Niemcryk, & Rose, 1988). Job demands, restoration, and sleep 241 The difference in time frames may have had implications for the effect sizes (i.e., the standardized beta coefficients) of this study. Future research may use identical time frames to match time frames of all measured variables. A third limitation may be the risk of common method bias due to the exclusive use of self-report measures. Nonetheless, it has been argued that the issues underlying common method bias, such as social desirability, may not be as problematic as previously thought (Spector, 2006). Monomethod correlations between variables do not seem to be higher than multimethod correlations, and in longitudinal studies, in particular this may not be an issue. In addition, most of our study variables are best measured or even have to be measured with self-report measures (e.g., perceived job demands including job insecurity, affective rumination, restoration). Other variables may additionally be assessed with objective measures (e.g., sleep quality/performance) or observer reports (performance). Using an objective measure in addition to subjective performance measures may possibly improve validity and generalizability of results. However, given the longitudinal design of this study and the necessity of a large sample, we chose to solely focus on self-report measures. Nonetheless, future research may also attempt to include more objective measures to assess sleep quality and performance to provide an even more nuanced picture of relations between demands, sleep, and performance. It is also worth noting that the reliability coefficients of the contextual performance measure were rather low (0.60– 0.65). This may relate to the fact that this measure included a variety of different behaviours (e.g., helping and cheering-up colleagues) and thus functioned as an index rather than a scale. Internal reliability (=consistency) may therefore not be a good criterium for the validity of this measure (Streiner, 2003). A final limitation may be that most effect sizes were small, which is rather common in longitudinal research. It is crucial to note that small effect sizes in absolute terms do not imply small effects in relative terms. When examining changes over time in outcomes and employing the structural equation modelling approach, baseline levels of all variables are controlled for and usually explain a large part of the variance (cf. the high autocorrelations over time in the supplementary material) (Van Hooff et al., 2005). In addition, many factors beyond the demands of this study may possibly influence job performance, thus small effect sizes should not be deemed irrelevant. Practical implications The present study makes several contributions to the field of occupational health psychology and has implications for job design. The fact that challenge demands were positively related to performance and restorative value of off-job activities is useful information for employees and employers alike. Apparently challenge job demands are not necessarily harmful for job performance. However, too high job demands may turn a challenging work environment into a stressful work environment. Accordingly, it is essential to also provide employees with sufficient job resources (e.g., high autonomy and social support) which help them to adequately deal with high job demands (Demerouti et al., 2001; Schaufeli & Taris, 2014) and to prevent challenging job demands from becoming overwhelmingly high and hindering. Our results further suggest that sufficient restoration is important for performance. Thus, employers should allow their employees sufficient time to recover from high job demands during off-job time (e.g., by preventing long working hours). The restorative value of off-job time may be further increased by providing trainings in recovery, relaxation and meditation techniques (i.e., mindfulness meditation and particularly acting 242 Michelle Van Laethem et al. with awareness; Querstret, Cropley, & Fife-Schaw, 2017), which have been shown to reduce stress and anxiety, and improve mental health and sleep quality (e.g., Hahn, Binnewies, Sonnentag, & Mozja, 2011; Jain et al., 2007; Querstret & Cropley, 2013; Richardson & Rothstein, 2008). Lastly, ruminating about job demands may interfere with restoration and sleep quality, ultimately harming performance. Cognitive behavioural interventions seem to be especially effective in reducing rumination, because these interventions do not only reduce negative thoughts and feelings (such as relaxation and meditation techniques), but also help employees to actively change dysfunctional behaviours (Richardson & Rothstein, 2008). An efficient low-cost intervention to prevent rumination is instructing employees to set daily goals and to create an action plan at the end of the day for (1) where, (2) when, and (3) how they will accomplish unfulfilled goals (Smit, 2016), which can be triggers for rumination (Syrek & Antoni, 2014). Finally, employees may also attempt to counteract perseverative thoughts by actively pursuing distracting restorative leisure activities, for example, by exercising (De Vries, van Hooff, Geurts, & Kompier, 2016). Conclusion To conclude, the present study showed that challenge job demands are positively related to later task and contextual performance and restoration (i.e., higher restorative value of off-job activities), which in turn predicts favourable task performance 1 year later. Affective rumination is an important unfavourable mechanism in the challenge demand– restoration/sleep relationship. 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