Relationships between recovery experiences and well-being among younger and older teachers

Vol.:(0123456789) 1 3 International Archives of Occupational and Environmental Health https://doi.org/10.1007/s00420-019-01475-8 ORIGINAL ARTICLE Relationships betweenrecovery experiences andwell‑being amongyounger andolder teachers AnniinaVirtanen1 · JessicaDeBloom1,2· UllaKinnunen1 Received: 27 March 2019 / Accepted: 16 September 2019 © The Author(s) 2019 Abstract Purpose The study had three aims. We investigated, first, how six recovery experiences (i.e., detachment, relaxation, control, mastery, meaning, and affiliation) during off-job time suggested by the DRAMMA model (Newman etal. in J Happiness Stud 15(3):555–578. https ://doi.org/10.1007/s1090 2-013-9435-x, 2014) are related to well-being (i.e., vitality, life satisfaction, and work ability). Second, we examined how age related to these outcomes, and third, we investigated whether age moderated the relationships between recovery experiences and well-being outcomes. Methods A sample of 909 Finnish teachers responded to an electronic questionnaire (78% women, average age 51years). The data were analyzed with moderated hierarchical regression analyses. Results Detachment from work, relaxation, control, and mastery were associated with higher vitality. Detachment, relaxation, meaning, and affiliation were related to higher life satisfaction. Older age was related to lower work ability, but not to vitality or life satisfaction. Older teachers benefited more from control and mastery during off-job time than did younger teachers in terms of vitality, whereas younger teachers benefited more from relaxation in terms of all well-being outcomes. Conclusions Detachment, relaxation, control, mastery, meaning, and affiliation during off-job time were related to higher well-being, supporting the DRAMMA model. Age moderated the relationships between control, mastery, and relaxation and vitality and life satisfaction. The role of aging in recovery from work needs further research. Keywords Recovery from work· Recovery experiences· Aging· Teachers Introduction Recovery from work is an important factor in mitigating the relation between high job demands and ill-health (Geurts and Sonnentag 2006; Sonnentag etal. 2017). It refers to the process of alleviating strain symptoms caused by job demands (Sonnentag and Fritz 2015) and restoring employees’ energy and mental resources (Zijlstra and Sonnentag 2006). Aging is known to slow down the recovery process on a physiological level (Ilmarinen 1999), but the scientific evidence on the effects of aging on psychological recovery processes remains very limited. Due to the increasing number of aging people in the workforce, it is crucial to understand the challenges that older workers face and to generate strategies to support longer, healthy careers and prevent early retirement. Recovery from work can be assumed to help prolong working careers, because it is closely related to health and well-being (e.g., de Bloom etal. 2015; Fritz and Sonnentag 2006; Geurts and Sonnentag 2006). However, we do not have yet a clear understanding of psychological recovery processes among aging workers. The target group of this study was teachers, who, according to several international studies, seem to be an especially stressed occupational group (e.g., Kinnunen etal. 1994; Kyriacou 2001; Salo 2002; Skaalvik and Skaalvik 2015). Teachers face job demands slightly different from those of other knowledge workers, although, for example, high workload is present in their daily working lives as it is in many other occupations. Typical teacher stressors mentioned in several studies include time pressure, students’ behavioral problems and low motivation, value conflicts, lack of recognition, lack of autonomy, conflicts with colleagues or parents, and the increasing use of technology in teaching (e.g., * Anniina Virtanen Anniina.Virt[email protected] 1 Faculty ofSocial Sciences (Psychology), Tampere University, Tampere33014, Finland 2 University ofGroningen, Groningen, TheNetherlands International Archives of Occupational and Environmental Health 1 3 Betoret 2009; Fernet etal. 2012; Friedman 1995; Hakanen etal. 2006; Klassen and Chiu 2011; Kokkinos 2007; Skaalvik and Skaalvik 2009, 2011, 2017). Teachers also tend to spend a lot of time on work-related activities outside formal work hours (e.g., Garrick etal. 2018), which limits the time available for recovery from work. It is, therefore, important to find new ways to promote teachers’ recovery and specifically to identify experiences aiding recovery which have not received much attention in earlier research on aging employees or teachers. The aim of this study is to contribute to recovery research in three ways. First, we focused on recovery from work among teachers, a highly loaded occupational group, whose recovery processes are under-examined. There is evidence showing that recovery is especially important when job stressors are high (Sonnentag 2018). Second, this is one of the first studies to investigate psychological recovery experiences (detachment, relaxation, control, mastery, meaning, and affiliation) suggested by the recently developed DRAMMA model (Newman etal. 2014) in the context of aging. Third, we examined whether age moderated the relationships between these recovery experiences and wellbeing. Thus, our study produces novel information about aging teachers’ recovery from work during off-job time. Recovery fromwork Research so far has distinguished two complementary processes underlying recovery from work (De Bloom etal. 2010; Geurts and Sonnentag 2006; Sonnentag 2001). First, the passive mechanism suggests that recovery only occurs when people stop working and rest (Meijman and Mulder 1998). Low demands and disengagement from work are assumed to enable employees’ psychobiological systems to return to baseline levels (McEwen 1998; Sonnentag and Fritz 2015). Second, the active perspective of recovery highlights the importance of engagement in pleasant or challenging leisure activities (Geurts and Sonnentag 2006). The active perspective suggests that to recover from work stress, employees need to replenish threatened or lost resources (Hofboll 1989), and engage in activities which produce positive emotions and satisfy their basic needs for autonomy, relatedness, and competence (Fredrickson 2001; Ryan and Deci 2000). Summing up, recovery entails resting and detaching from work, but also building new resources and engaging in meaningful leisure activities. Recovery can be elicited by certain subjective experiences, leisure-time activities, and physiological processes occurring during sleep (Sonnentag 2018). In this study, we focus on psychological recovery experiences underlying different leisure activities. Sonnentag and Fritz (2007) suggested a framework of four major recovery experiences: psychological detachment from work, relaxation, control, and mastery. Detachment refers to mental disengagement from work-related thoughts. Relaxation implies low levels of mental or physical activation and little physical or intellectual effort. Control refers to being able to decide on one’s leisure schedule and activities. Mastery encompasses learning opportunities and challenges, resulting in feelings of achievement and competence. Of these four experiences, detachment seems to be most consistently associated with positive changes in well-being (for reviews, see Sonnentag and Fritz 2015; Wendsche and Lohmann-Haislah 2017). Several studies have also demonstrated links between relaxation, control, mastery, and better well-being (for a metaanalysis, see Bennett etal. 2018). Based on a meta-analysis of 363 articles within psychology and leisure sciences, Newman etal. (2014) added the experiences of meaning and affiliation to this list of recovery experiences in their DRAMMA model, which aims to explain how leisure activities relate to subjective well-being. They also replaced control with autonomy, which refers to feelings of decision latitude. Autonomy is also one of the basic psychological needs suggested in Self-Determination Theory (Ryan and Deci 2000). Autonomy closely resembles control, but is broader by emphasizing feelings of volition in general instead of merely having control over one’s leisure schedule (Newman etal. 2014). Meaningful leisure activities are a means by which individuals gain something valuable in their lives (Iwasaki 2008). Experiencing meaning in life is beneficial for well-being on both trait level (e.g., Hicks and King 2007; King etal. 2006) and state level (e.g., King etal. 2006; Machell etal. 2015; Thrash etal. 2010). Also, at day level, active search for meaning is related to improvements in well-being (Newman etal. 2018). This means that proactively engaging in activities that add meaning to one’s life is likely to improve well-being. Affiliation refers to feelings of belongingness with other people and the fulfillment of people’s innate need for relatedness (Ryan and Deci 2000). According to Newman etal. (2014), of all DRAMMA experiences, affiliation has the most support from multiple theoretical perspectives. In addition to fulfilling the basic psychological need for relatedness (Ryan and Deci 2000), social affiliation also fosters social support, which helps to mitigate against stressful events (Lakey and Orehek 2011). In this study, we investigated how these DRAMMA recovery experiences during leisure time (i.e., evenings after working hours) are related to three aspects of well-being: vitality, life satisfaction, and work ability. Vitality and life satisfaction describe context-free wellbeing. Vitality refers to a positive feeling of aliveness and energy (Ryan and Frederick 1997). Since recovery from work allows employees to gain new internal resources such as energy and positive mood (Sonnentag and Fritz 2007), recovery experiences can be assumed to promote vitality. A meta-analysis by Bennett etal. (2018) showed that recovery International Archives of Occupational and Environmental Health 1 3 experiences are related to higher vigor, which includes vitality and positive activated affect. Life satisfaction is a subjective global judgement of one’s quality of life (Diener etal. 1985) and a central component of subjective well-being (Diener etal. 2017). Previous studies show that recoveryrelated experiences are associated with higher life satisfaction (e.g., Sonnentag and Fritz 2007; Strauss-Blasche etal. 2002). Work ability can be defined as the degree to which employees are mentally and physically capable of performing their current work role and of achieving a balance between a person’s resources and work demands (Ilmarinen etal. 1997; Tuomi etal. 1991). Work ability has its roots in health status (Ilmarinen 2009). Since recovery from work mitigates the relation between work stress and ill-health, and helps to build new resources (Geurts and Sonnentag 2006; Sonnentag etal. 2017), it can be presumed to promote work ability. In addition, we examined whether age is related to these three well-being outcomes. Earlier research has shown that age is associated with decreases in work ability (e.g., Alavinia etal. 2009; Ilmarinen etal. 1997; Kinnunen and Nätti 2018). Some studies suggest that life satisfaction tends to reach a low point in mid-life but increases again after reaching retirement age (Blanchflower and Oswald 2008; Stone etal. 2010). This means that in our sample consisting of working people aged up to 68years, aging may be associated with lower life satisfaction. Earlier studies suggest that although aging is generally related to higher affective wellbeing, this mostly applies to low-arousal positive states (e.g., relaxation, peace of mind), not more energized states like vitality (Kessler and Staudinger 2009; Scheibe and Zacher 2013). Some studies also show that aging may bring a shift in preference away from high-arousal positive emotions and towards low-arousal positive emotions (e.g., Scheibe etal. 2013). It could, therefore, be assumed that aging is either not related to vitality or related to lower vitality. Age, recovery, andemotion regulation As stated previously, scientific evidence of the effects of age on psychological recovery processes remains limited so far. However, recovery processes are closely linked to emotion regulation (Parkinson and Totterdell 1999; Sonnentag and Fritz 2007; Sonnentag etal. 2017), and the motivation and competence for emotion regulation tend to change with age (Scheibe and Zacher 2013). Consequently, it can be assumed that aging may play a role in recovery from work. It is important to note that the research streams of lifespan development and organizational literature differ in terms of the definitions of “older” or “aging” people (Doerwald etal. 2016). In the life-span literature, age 60 or 65 is often used as a cut-off for when old age begins (Baltes and Smith 2003), whereas definitions of older workers correspond to the general operationalization of middle age, around 40–60years (Doerwald etal. 2016). As this study is about teachers who are still working, we adhere to the definition for aging workers as it appears in the organizational literature (Doerwald etal. 2016). The few existing studies about age and recovery have mostly focused on individuals’ own perceptions of their need for recovery, which seems to change during the life course. Two studies have shown that employees’ need for recovery after the working day increases linearly until the age of 55 and then stabilizes for the oldest workers approaching retirement age (Kiss etal. 2008; Mohren etal. 2010). Explanations for these findings can be found in three domains (Mohren etal. 2010). First, in the work environment, the process of downshifting may have been initiated, for example, in terms of a reduction in working hours. Second, differences in the family situation may account for varying levels of need for recovery: often, the oldest employees no longer have children living at home, which is likely to reduce work–family conflict and the demands of the family domain. Third, older employees may have developed better strategies for dealing with need for recovery due to their longer experience and expertise in their working careers (Silverstein 2008). Consequently, it is possible that older employees have better “recovery skills”. These skills relate to leisure crafting, which refers to the proactive pursuit of leisure activities targeted at goal setting, human connection, and personal development (Petrou and Bakker 2016). The restoration of positive mood and energy are core functions of recovery from work, which supports the link between recovery and emotion regulation (Sonnentag and Fritz 2007). Research on emotion regulation has identified a range of strategies that individuals use to improve their mood, including both cognitive and behavioral strategies. Sonnentag and Fritz (2007) refer to the classification by Parkinson and Totterdell (1999), which proposes two main categories of emotion regulation: diversionary and engagement strategies. Diversionary strategies aim at avoiding a stressful situation or seeking distraction from it, whereas engagement strategies refer to confronting or accepting the stressful situation. According to Sonnentag and Fritz (2007), diversionary strategies are more relevant for work-stress recovery, because engagement strategies keep the individual cognitively occupied with the stressful situation, which makes recovery less likely. Diversionary strategies relate closely to three recovery experiences: detachment from work, relaxation, and mastery (Sonnentag and Fritz 2007). Higher age seems to be related to an increased preference to choose distraction (a less effortful, diversionary strategy) over reappraisal (an engagement strategy) when downregulating negative emotions (Scheibe etal. 2015). International Archives of Occupational and Environmental Health 1 3 Aging entails changes in emotion regulation motivation. Older adults seem to be more motivated to regulate emotions to optimize well-being, whereas younger adults are generally more focused on the achievement of goals (e.g., goals related to work and career development) (Carstensen 2006; Labouvie-Vief 2003). These changes are assumed to be driven by changes in future time perspective and cognitive abilities. In sum, higher age is associated with a higher motivation to avoid affective states that are negative and/or high in arousal (Scheibe and Zacher 2013). This is likely to have consequences for recovery, which focuses on dealing with job stress, a highly aroused negative state. It is possible that older employees, for example, have higher motivation to engage in detachment and relaxation during off-job time to distract from job stress. Due to their greater life experience, older adults may also be more effective in implementing emotion regulation strategies and more competent in emotion regulation (Scheibe and Zacher 2013). Prominent life-span psychology theories, such as socioemotional selectivity theory (Carstensen 2006) and the model of selection, optimization, and compensation (Baltes and Baltes 1990), propose that aging triggers proactive behavior and is related to prioritizing emotional goals. These proactive behaviors, especially when they relate to emotion regulation and goal setting, may also be associated with recovery from work. Due to their long work and life experience, older workers may have a clearer understanding of what helps them to recover more successfully and make the most of their leisure time. The present study: research questions andhypotheses In the present study, we sought answers to three research questions. First, we asked: How do recovery experiences of detachment, relaxation, control, mastery, meaning, and affiliation outside working hours relate to (a) vitality, (b) life satisfaction, and (c) work ability? Basing our examination on the DRAMMA model (Newman etal. 2014) and the existing research on recovery experiences (e.g., the meta-analysis by Bennett etal. 2018), we predict (H1) that all recovery experiences are related to higher well-being. Of the well-being outcomes, there is most evidence concerning the positive links to vitality. Second, we asked: Is age related to vitality, life satisfaction, and work ability? We expect (H2) that age relates to lower work ability (e.g., Alavinia etal. 2009; Ilmarinen etal. 1997; Kinnunen and Nätti 2018), and likely also to lower life satisfaction (Blanchflower and Oswald 2008; Stone etal. 2010), and possibly to lower vitality (e.g., Kessler and Staudinger 2009; Scheibe and Zacher 2013), as discussed above. Our third research question concerned the role of age in the relationship between recovery experiences and wellbeing outcomes. Thus, we asked: How does age moderate the relationship of recovery experiences and the outcomes described above? To the best of our knowledge, this issue has not yet been examined. Therefore, we did not formulate specific hypotheses regarding each recovery experience. In light of the existing literature about age-related changes in emotion regulation, we assume, for example, that detachment and relaxation may be more easily (i.e., with less effort) achieved by older teachers due to their greater motivation to avoid stress, which in turn is reflected in their higher levels of well-being. However, younger teachers may be in a greater need of detachment and relaxation due to their heavier family demands and, therefore, benefit more from these recovery experiences. All in all, concerning the last research question, our study can be considered explorative, although we expect (H3) to find moderator effects. Methods Participants andprocedure The participants of this study (N = 909) were teachers and school principals working in Finnish comprehensive or upper secondary schools. The sample was drawn in May 2017 from the register of the Trade Union of Education (OAJ). In Finland, around 95% of teachers are members of the trade union (OAJ 2015). The electronic questionnaire was sent to 3500 teachers all over the country by the union: to 1500 class teachers (teaching grades 1–6, i.e., pupils aged 7–12years in comprehensive school), to 1500 subject teachers (teaching in either comprehensive school grades 7–9, i.e., pupils aged 13–15years, or upper secondary school, i.e., pupils aged 16–18years), and to 500 school principals. In the groups of class teachers and subject teachers, the questionnaire was sent to 500 teachers in three age groups: under 45years, 45–55years, and over 55years. Due to the smaller total number of principals, this age division was not used in their group. The response rate was 26% (N = 909). Among class teachers, it was 30% (n = 448), among subject teachers 28% (n = 321) and among principals only 21% (n = 140). The response rate was highest (37% among class teachers and 23% among subject teachers) among the middle-age group (45–55years). The attrition analyses showed that the study participants were older (the share of teachers over 55years old was 41.5% vs. 18.6%; χ2 (2) = 278.01, p < 0.001), more often women (83.4% vs. 77.6%; χ2 (1) = 14.65, p < 0.001), and subject teachers (47.1% vs. 35.6%; χ2 (1) = 12.66, p < 0.001) than teachers registered as members of the Trade Union of Education. The age difference is explained by the International Archives of Occupational and Environmental Health 1 3 procedure through which the sample was drawn: as aging teachers were the target group of the study, the older age groups were given more weight than those under 45. Of all the participants, 78% were women (86% of class teachers, 80% of subject teachers, but only 49% of the principals). The mean age of the participants was 51years (SD = 9.76). Nearly all (99%) of the participants had a fulltime job, and most (86%) also had a permanent employment contract. On average, participants worked 37.44h per week (SD = 9.24). The majority (93%) of the participants worked in comprehensive schools (i.e., teaching students aged from 7 to 16years). Most of the participants lived either with a partner (41%) or with a partner and at least one child (36%). Measures Recovery experiences Each recovery experience was measured with three items referring to one’s free time outside working hours. Psychological detachment (α = 0.82, e.g., “I forget about work”), relaxation (α = 0.80, e.g., “I kick back and relax”), control (α = 0.78, e.g. “I feel that I can decide for myself what to do”), and mastery (α = 0.68, e.g., “I seek out intellectual challenges”) were measured with items from the Recovery Experience Questionnaire (Sonnentag and Fritz 2007), which has been validated in Finland (Kinnunen etal. 2011). Meaning (α = 0.69, e.g., “I do things which are personally meaningful for me”) was measured with three items adapted from the Job Diagnostics Survey (Hackman and Oldham 1974). Affiliation (α = 0.77, e.g., “I really like the people I interact with”) was measured with three items from Basic Needs Satisfaction in General Scale (Johnston and Finney 2010), but one item (“There are not many people that I am close to”) was excluded from the analyses due to low Cronbach’s alpha (α = 0.44). All recovery experiences were rated on a scale from 1 (totally disagree) to 5 (totally agree). All Cronbach’s alphas reported for the scales of recovery experiences and other variables were calculated from our sample. Moderator Age as a moderator was used as a continuous variable in our analyses. Age was calculated from year of birth. Well‑being Vitality was measured with four items from the scale by Ryan and Frederick (1997) (α = 0.89, e.g., “I felt alive and vital”). The items refer to feelings during the last month. The rating scale was from 1 (very rarely or never) to 5 (very often or always). Life satisfaction was measured with one item: “How satisfied do you generally feel about your life?” (e.g., Cheung and Lucas 2014) on a scale from 0 to 10. Work ability was measured with one item (“How would you rate your current ability to work?”) from the Work Ability Index (Tuomi etal. 1998). The item was rated on a scale from 1 to 10, where 1 refers to being totally incapable of working and 10 refers to one’s work ability at its best. It has been shown that this one-item measure accurately reflects the total work ability index (e.g., Jääskeläinen etal. 2016). Controls Several meta-analyses (e.g., Crawford etal. 2010; Nixon etal. 2011) indicate that individuals who are exposed to a higher level of job stressors report poorer well-being and poorer recovery experiences (Bennett etal. 2018). We, therefore, controlled for an important job stressor, workload, in our analyses. In addition, we controlled for one job resource, job autonomy, which is related to higher subjective wellbeing (e.g., Wheatley 2017). We also controlled for whether the participants had child(ren) living at home, because family situation may be related to recovery opportunities during off-job time. Finally, we controlled for leadership status, i.e., whether the participant was a school principal (= 1) or not (= 0), because managers may have heavier workload and, therefore, more problems with recovery than employees without leadership responsibility (e.g., Sonnentag and Fritz 2007). Workload was measured with three items (α = 0.87, e.g., “How often does your job require you to work under time pressure?”) from the scale by Spector and Jex (1998). The items were rated on a scale from 1 (very rarely or never) to 5 (very often or always). Job autonomy was measured with six items (α = 0.78, e.g., “I can set my own work pace”) from QPSNordic-ADW (Pahkin etal. 2008). The items were rated on a scale from 1 (very rarely or never) to 5 (very often or always). The number of children living at home was elicited with one question: “How many children do you have who live in the same household with you?”. The answers to this question were recoded into a dichotomous variable (0, no children living at home; 1, at least one child living at home). Statistical analyses First, we calculated means, standard deviations, and correlations between all study variables. Moderated hierarchical regression analyses (Aiken and West 1991) were used to test the direct effects of recovery experiences and age on three well-being indicators and the moderator effects between age and recovery experiences. We conducted hierarchical multiple regression analysis for each dependent variable using the following procedure: control variables (workload, job autonomy, having children living at home, and leadership status) were entered into the model at step International Archives of Occupational and Environmental Health 1 3 1, recovery experiences at step 2, age at step 3, and finally, the interaction terms of each recovery experience with age were entered at step 4 (6 interactions in total). Finally, we performed simple slope analyses to test the significance of the relationships among younger (1 SD below the mean age) and older (1 SD above the mean age) teachers. All recovery experiences, workload, job autonomy, and age were standardized in the regression analyses. All analyses were conducted in SPSS 24 software. Results Descriptive results Means, standard deviations, and correlations between all the study variables are presented in Table1. All recovery experiences correlated positively with vitality (0.18 ≤ r ≤ 0.42), life satisfaction (0.08 ≤ r ≤ 0.34), and work ability (0.10 ≤ r ≤ 0.26). Recovery experiences correlated positively with each other (0.09 ≤ r ≤ 0.55), with the exception that the correlation between mastery and affiliation was not statistically significant. Well-being outcomes (vitality, life satisfaction, and work ability) were highly correlated with each other (0.48 ≤ r ≤ 0.55). However, none of these correlations between the six recovery experiences or the outcomes is over 0.85, which is considered a limit for concepts not being separate from each other (Hair etal. 2010). Age correlated negatively with work ability (r = − 0.08, p < 0.05), but was not significantly associated with vitality or life satisfaction. In addition, age correlated with higher detachment (r = 0.11, p < 0.01), relaxation (r = 0.10, p < 0.01), control (r = 0.07, p < 0.05), and mastery (r = 0.08, p < 0.05). Higher age was related to not having children living at home (r = − 0.24, p < 0.01). Workload correlated negatively with all well-being outcomes (− 0.15 ≤ r ≤ − 0.25), most strongly with vitality, and with recovery experiences (− 0.09 ≤ r ≤ − 0.30), except for mastery and affiliation. Job autonomy was positively related to all outcomes (0.21 ≤ r ≤ 0.33) and all recovery experiences (0.09 ≤ r ≤ 0.29). Having children at home correlated negatively with relaxation (r = − 0.17, p < 0.01), control (r = − 0.19, p < 0.01), and mastery (r = − 0.08, p < 0.05), but positively with affiliation (r = 0.14, p < 0.01). It was not significantly related to well-being outcomes. Leadership status correlated with higher age (r = 0.14, p < 0.001), workload (r = 0.11, p < 0.01), job autonomy (r = 0.31, p < 001), and vitality (r = − 13, p < 0.001). Table 1 Means, standard deviations, and correlations between variables *p < 0.05, **p < 0.01, ***p < 0.001 Variable (range) MSD 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 1. Workload (1–5) 4.01 0.73 1 2. Autonomy at work (1–5) 2.75 0.71 − 0.33*** 1 3. Having child(ren) living at home (0, no; 1, yes) – – 0.08* − 0.03 1 4. Leadership status (0, no; 1, yes) – – 0.11** 0.31*** − 0.01 1 5. Detachment (1–5) 2.83 0.91 − 0.29*** 0.24*** − 0.06 0.02 1 6. Relaxation (1–5) 3.93 0.70 − 0.25*** 0.20*** − 0.17** 0.01 0.54*** 1 7. Control (1–5) 3.93 0.74 − 0.30*** 0.29*** − 0.19** 0.02 0.41*** 0.65*** 1 8. Mastery (1–5) 3.34 0.73 − 0.04 0.11** − 0.08* 0.05 0.15*** 0.24*** 0.20*** 1 9. Meaning (1–5) 4.36 0.57 − 0.09** 0.10** − 0.04 − 0.02 0.23*** 0.55*** 0.43*** 0.29*** 1 10. Affiliation (1–5) 4.58 0.51 − 0.06 0.09* 0.14** 0.00 0.09** 0.29*** 0.33*** 05 0.47*** 1 11. Age (18–68) 50.55 9.76 − 0.05 0.05 − 0.24** 0.14*** 0.11** 0.10** 0.07* 0.08* 0.01 0.04 1 12. Vitality (1–5) 3.25 0.83 − 0.25*** 0.33*** − 0.01 0.13*** 0.31*** 0.42*** 0.39*** 0.27*** 0.33*** 0.18*** 0.03 1 13. Life satisfaction (0–10) 8.80 1.39 − 0.17*** 0.21*** 0.05 0.02 0.28*** 0.34*** 0.31*** 0.08* 0.28*** 0.23*** 0.02 0.52*** 1 14. Work ability (1–10) 8.71 1.31 − 0.15*** 0.27*** 0.04 0.07 0.21*** 0.26*** 0.25*** 0.11** 0.16*** 0.10** − 0.08* 0.48*** 0.55*** 1 International Archives of Occupational and Environmental Health 1 3 Regression analyses: direct associations andinteractions betweenage andrecovery experiences The results of regression analyses are presented in Table2. Vitality At step 1, job autonomy, having children living at home, and being a school principal were related to higher vitality. Controls explained 13% of the variance in vitality. At step 2, four recovery experiences predicted higher vitality: detachment, relaxation, autonomy, and mastery, with relaxation and mastery playing the major roles. Therefore, concerning vitality, H1 got partial support. Together, the recovery experiences explained 16% of the variance in vitality. Age did not predict vitality. In terms of this outcome, H2 was not supported. There were three statistically significant interactions between age and recovery experiences at step 4, giving partial support to H3. The graphical presentations of the interactions were derived using the unstandardized regression coefficients of the regression lines for teachers high (1 SD above the mean age, that is, over 60years) and low (1 SD below the mean age, that is, under 40years) on the moderator variable of age. As shown in Fig.1, younger participants seemed to benefit more from relaxation experiences during off-job time than did older participants in terms of higher vitality (see Fig.1a). However, older participants benefited more from control and mastery experiences than did younger ones (see Fig.1b, c). The interactions added 1% to the explanation rate, and totally, the model explained 30% of vitality. The simple slope analyses (10) confirmed the age differences: the positive unstandardized regression coefficients (Bs) were higher and statistically significant for older teachers [control: B = 0.187, p < 0.001 (older) vs. B = 0.039, ns (younger); mastery: B = 0.183, p < 0.001 (older) vs. B = 0.057, ns (younger)], suggesting that older teachers benefit more from control and mastery than younger ones. The relationship between relaxation and vitality was positive in the younger age group (B = 0.245, p < 0.001), whereas the relationship was not significant in the older group (B = − 0.005, ns), suggesting that younger teachers benefit more from relaxation in terms of vitality. Life satisfaction At step 1, job autonomy and having children living at home were related to higher life satisfaction, explaining 7% of the variance in life satisfaction. At step 2, four recovery experiences (detachment, control, meaning, and affiliation) were Table 2 Results of regression analyses, β’s from the last step of the model *p < 0.05, **p < 0.01, ***p < 0.001 Independent variables Vitality Life satisfaction Work ability ΔR2βΔR2βΔR2β Step 1 0.13*** 0.07*** 0.09*** Workload − 0.08* − 0.04 − 0.04 Autonomy at work 0.16*** 0.12** 0.20*** Child(ren) living at home 0.07* 0.11** 0.09* Leadership status 0.08* − 0.02 0.02 Step 2 0.16*** 0.13*** 0.06*** Detachment 0.08* 0.10* 0.07 Relaxation 0.15** 0.10 0.09 Control 0.14** 0.13** 0.09 Mastery 0.14*** − 0.01 0.05 Meaning 0.08 0.11* 0.02 Affiliation 0.02 0.09* 0.02 Step 3 0.00 0.00 0.01* Age − 0.01 0.01 − 0.08** Step 4 0.01* 0.01 0.02* Age × detachment 0.03 − 0.02 0.08 Age × relaxation − 0.14** − 0.12* − 0.19** Age × control 0.09* 0.08 0.04 Age × mastery 0.08* 0.03 0.03 Age × meaning 0.03 − 0.03 0.09 (p = 0.058) Age × affiliation 0.01 0.03 0.01 Total R20.30*** 0.21*** 0.17*** International Archives of Occupational and Environmental Health 1 3 related to higher life satisfaction, control playing the biggest role. Recovery experiences added 14% to the explanation rate. This gives support to H1. At step 3, age did not predict life satisfaction. Therefore, H2 was not supported in terms of life satisfaction. At step 4, one interaction effect turned out to be significant; H3 gained partial support, showing that younger participants benefited more from relaxation experiences than did older ones (see Fig.1d). The simple slope analysis showed that in the younger age group, there was a significant positive relationship between relaxation and life satisfaction (B = 0.316, p < 0.01), whereas among the older group, the relationship was not significant (B = − 0.036, ns). This interaction added 1% to the explanation rate. In total, the model explained 21% of the variation in life satisfaction. Work ability At step 1, job autonomy and having children living at home were related to higher work ability, explaining 9% of the variation in work ability. In terms of work ability, H1 did not get support. At step 2, none of the recovery experiences predicted work ability significantly, but together they added 6% to the explanation rate. At step 3, greater age significantly predicted lower work ability, adding 1% to the explanation rate. This was in line with H2. At step 4, there was one significant interaction effect between age and relaxation, lending partial support to H3: again, younger participants seemed to benefit more from relaxation experiences than older participants (see Fig.1e). The simple slope analysis showed that in the younger age group, there was a significant positive relationship between relaxation and work ability 1 2 3 4 5 Low relaxation High relaxation Vitality Low age High age 1 2 3 4 5 Low controlHigh control Vitality Low age High age 1 2 3 4 5 Low masteryHigh mastery Vitality Low age High age 5 6 7 8 9 10 Low relaxation High relaxation Life satisfaction Low age High age 5 6 7 8 9 10 Low relaxation High relaxation Work ability Low age High age Fig. 1 Interactions between age and recovery experiences International Archives of Occupational and Environmental Health 1 3 (B = 0.382, p < 0.001), whereas among the older group, this relationship was not significant (B = − 0.148, ns). Also, in terms of work ability, older participants seem to benefit slightly more from detachment, although this interaction was only marginally significant (p = 0.058). The interactions added 2% to the explanation rate, and in total, the model explained 17% of the variation in work ability. Discussion The first aim of this study was to investigate how six recovery experiences—detachment, relaxation, control, mastery, meaning, and affiliation—during off-job time relate to vitality, life satisfaction, and work ability. Second, we examined whether age is related to these outcomes. Third, we investigated whether age moderated the relationship between recovery experiences and well-being outcomes. Main results The results show that recovery experiences during off-job time are consistently related to context-free well-being, that is, feelings of positive energy, vitality, and a general cognitive evaluation of one’s life as a whole, life satisfaction. However, none of the recovery experiences predicted work ability, although at a correlational level, they had positive associations with this aspect of work-related wellbeing. Therefore, H1 got only partial support from the results. Empirical evidence on these links has also been presented (see Bennett etal. 2018, for a meta-analysis). Compared to vitality and life satisfaction, work ability is based more on physical health status (Ilmarinen 2009), which likely makes it more difficult to impact with leisure recovery experiences. All in all, the results of this study give support to the DRAMMA model (Newman etal. 2014): in addition to the four recovery experiences suggested by Sonnentag and Fritz (2007), leisure-time experiences of affiliation and meaning also promote wellbeing. Meaning was associated with both higher vitality and life satisfaction, whereas affiliation was only related to life satisfaction. Age was not significantly related to vitality or life satisfaction, but, according to our expectations, higher age was related to lower work ability. This means that H2 also received partial support. Earlier research has also shown that work ability tends to decrease with age (e.g., Alavinia etal. 2009; Ilmarinen etal. 1997; Kinnunen and Nätti 2018). A few existing studies suggest that life satisfaction often reaches a low point in mid-life (which corresponds to 40–60-year old workers), whereas other hedonic aspects of well-being, like positive affect and happiness, are on an upward trajectory from youth to old age (Blanchflower and Oswald 2008; Stone etal. 2010). Our results did not show these age-related changes, which may be partly related to the fact that our study only included working people, while many earlier studies investigating age-related differences in psychological well-being have focused on older, retired individuals. In addition, we did not specifically study affective well-being (e.g., positive or negative affects), which tends to increase with age (e.g., Charles and Carstensen 2010; Scheibe and Carstensen 2010). Some studies have found no age-related differences in high-arousal positive affect (Kessler and Staudinger 2009). This is in line with our result, showing that age was not related to vitality. All in all, older teachers seemed to recover better from work during off-job time than did their younger counterparts: age correlated with higher detachment, relaxation, control, and mastery. It is possible that due to their longer work and life experience, older teachers have learned more effective recovery skills and know what works best for them in relieving work-related stress. This is in line with earlier studies, suggesting that age is associated with higher competence in emotion regulation (Scheibe and Zacher 2013). Recovery skills can be linked to leisure crafting, the proactive pursuit of leisure activities targeted at addressing basic psychological needs (Petrou and Bakker 2016). The crafting perspective suggests that recovery from work is a process which can be actively shaped—it is not something which just automatically happens. Given that older teachers generally had higher levels of recovery experiences, it is an interesting question why they did not always benefit more from these than did younger teachers. In line with our third hypothesis (H3), we found that age moderated the relationship between some recovery experiences and well-being. Younger teachers seemed to benefit more than older teachers from relaxation experiences in terms of all three well-being outcomes. However, older teachers benefited more than younger teachers from control and mastery experiences during leisure time in terms of vitality. There are several possible explanations for these moderator findings. First, age-related changes in family demands may play a role. Younger teachers more often have children living at home, which likely increases the demands of the family domain. Having high demands at both work and home, younger teachers may need relaxation more than do older teachers. Having children living at home and having relaxation experiences during off-job time were negatively correlated in our sample. The younger teachers may, therefore, have been in greater need of relaxation and, therefore, benefited more from it than did the older teachers. Second, the age-related differences in the relationship between leisure-time control and well-being may be explained by lifespan theories. Socioemotional selectivity theory (Carstensen 2006) and dynamic integration theory (Labouvie-Vief 2003)