‘State Well-Being,
Personality, and Off-Job
Activities: a Diary Study’
- Master Thesis -
ame:
N.A. Rida
Student number:
292084
Field of Specialization:
Industrial and Organizational Psychology
Thesis Supervisor:
Dr. W.G.M. Oerlemans
Second Reader:
Prof. dr. A.B. Bakker
Personality, Off-job activities and State Well-Being
2
Abstract
The main aim of this study was to test whether personality plays a moderating role in the
relationship between off-job activities and state well-being (i.e. daily recovery and state
happiness). A day reconstruction method was used to accurately examine day-to-day activities
and happiness. In total, 641 operable diaries were completed by 228 participants, generating
more than 6,300 reported activities and happiness scores. The results show that individuals
who score high on introversion derive greater happiness from working overtime, low-effort
activities, and derive less happiness from social activities and physical activities compared
with their high-extravert counterparts. Furthermore, high neurotic individuals derive greater
happiness from working overtime, low-effort activities, and physical activities in comparison
to low neurotic individuals. Also, individuals who score high on neuroticism as well as people
who score high on introversion deduct greater daily recovery from engaging in household
activities, and work overtime activities. The study extends work on Gray’s personality theory
and the situational congruence hypothesis by demonstrating that engaging in trait-congruent
activities is related to more positive emotions. Also, personality traits such as extraversion and
neuroticism play a decisive role in the kind of activities that contribute most to daily recovery
and state happiness.
Personality, Off-job activities and State Well-Being
3
State Well-being, Personality, and Leisure Activities: a Diary Study
Researchers have increasingly argued that recovery from a workday is important for
employee well-being (e.g., Demerouti, Bakker, Geurts & Taris, 2009; Sonnentag, 2001;
Sonnentag & Natter, 2004). Thus, engaging in off-job activities that stimulate recovery from
job demands in order to replenish one’s resources (e.g. physical, psychological resources) is
argued to be extremely important for maintaining one’s well-being. It has been suggested that
the degree of recovery obtained during free time is influenced by the nature of the leisure
activity undertaken during that free time (Tucker, Dahlgren, Akerstedt & Waterhouse, 2008).
In their effort-recovery model (ERM), Meijman and Mulder (1998) argued that if recovery
after a workday is successful, an individual’s well-being improves, and resources (e.g.
energy) drawn upon during the workday are restored. Empirical research on the ERM,
however, has not been able to substantiate this view (e.g., Sonnentag, 2001; Sonnentag &
Natter, 2004). Likewise, a more recent paper suggests that the type of activity that is
undertaken during off-job time can only have a positive effect on well-being when the activity
is congruent with one’s personality (Trougakos & Hideg, 2009). But which activities, then,
lead to appropriate recovery after a workday? Could it be that other factors – such as
personality - play a moderating role in the leisure activities-recovery relationship?
Moreover, previous research has established a clear link between personality and wellbeing (e.g., Costa & McCrae, 1980; Costa & McCrae, 1985). Personality traits account for as
much as 40% to 55% of the variance in individual differences in state happiness (Diener, Suh,
Lucas & Smith, 1999). Mainly extraversion and neuroticism have shown to have systematic
effects on psychological well-being. Accordingly, research indicated that extraversion has a
consistent positive correlation with happiness, whereas neuroticism has a consistent negative
one. But why is it, then, that extraverts, in general, are happier than introverts? And why do
neurotic individuals feel less happy than emotional stable individuals?
The central aim of the present study was to reconcile these two research streams –
leisure activities and recovery, as well as personality and well-being – in order to identify the
kind of daily lifestyle that contributes most to the happiness within a population of Dutch
employees. First, as global questionnaire studies on happiness are far from ideal for capturing
day-to-day fluctuations, a within-person study design, the day reconstruction method (DRM;
Kahneman, Krueger, Schkade, Schwarz & Stone, 2004), was used to accurately capture those
day-to-day fluctuations in activities and happiness among participants. The DRM is a method
Personality, Off-job activities and State Well-Being
4
that asks participants to systematically reconstruct the preceding day’s activities and
happiness using procedures designed to reduce recall biases. Second, this study will
investigate which off-job activities have a consistent positive influence on daily recovery and
happiness, and which activities have a consistent negative relationship with daily recovery
and happiness. Third, this study extends research on Gray’s personality theory (1991) and the
situational congruence hypothesis (Diener, Larsen & Emmons, 1984) by examining whether
differences in trait characteristics (personality) moderates the day-to-day relationship between
off-job activities and happiness as well as recovery. To the best of my knowledge, this has
never been researched before.
Measuring (State) Happiness and the Day Reconstruction Method
There are two main ways to conceive happiness (Csikszentmihalyi & Wong, 1991).
The first view perceives happiness as a personal trait, which is a relatively permanent
disposition to experience well-being regardless of external conditions. The second view
considers happiness more as a state or a transitory subjective experience responsive to
momentary events or conditions in the environment. Researchers presume that these two
aspects are inter-related. One would expect, for instance, that a happy person will have more
frequent and intense momentary experiences of happiness (Csikszentmihalyi & Wong, 1991).
Judgments of happiness, thus, comprise experiencing pleasant emotions or affect during a
certain period of time and/or the genetic predisposition of an individual to experience such
emotions.
Importantly, happiness resides within the experience of a person and is, therefore,
always subjective. Yet, past research on well-being has relied almost entirely on reports of life
satisfaction and happiness, which are global retrospective measurements of well-being.
However, experimental researchers found that retrospective evaluations are heavily affected
by a person’s mood, memory, and immediate context (e.g., Kahneman, Fredrickson, Schreiber
& Redelmeier, 1993; Schwarz, 1983, as cited in Diener et al., 1999). In addition, with their
laboratory experiment, Kahneman et al. (1993) showed that with retrospective assessment of
global happiness, subjects were unable to accurately assess duration of episodes of positive
and negative affect, leading to an incorrect assessment of global happiness. Also, global
questionnaire studies on happiness are not adequately capable of capturing day-to-day
fluctuations in activities and experienced happiness, or, put differently, the state component of
happiness. Therefore, Kahneman et al. (2004) proposed that retrospective evaluations of
Personality, Off-job activities and State Well-Being
5
happiness were not a good measure of (‘state’) happiness. Consistent with this reasoning, the
present study measured happiness from a moment-to-moment basis in accordance with the
DRM. The DRM assesses how people spend their time by systematically reconstructing a
persons’ activities and experiences of the preceding day with procedures designed to reduce
recall biases. Research has shown that the DRM can recover the actual happiness experienced
to a significant degree of accuracy, as indicated by their convergence with concurrent mood
reports used in experience sampling methods (Oerlemans et al., 2011).
The Effort-Recovery Model and off-job activities
The ERM (Meijman & Mulder, 1998) suggests that recovery processes play an
important role in predicting individual happiness. According to Sonnentag (2001), happiness
can be conceptualized as an indicator that recovery is occurring. Accordingly, in this paper,
‘state’ well-being will be assessed, which encompasses both state happiness as well as daily
recovery before going to sleep. Daily recovery refers to the process during which an
individual’s functioning returns to its pre-stressor level and in which strain is reduced
(Meijman & Mulder, 1998). More specifically, the ERM proposes that effort expenditure at
work leads to specific load reactions (e.g. accelerated heart rate, elevated blood pressure
levels, and fatigue) in the individual. Whenever a person is no longer confronted with any
work demands, psychobiological systems will return to their pre-stressor levels and recovery
occurs. However, when demands are continuously put on an individual, recovery cannot occur
and negative effects (e.g. impaired health, stress, and burnout) will occur within the
individual. The effort-recovery model proposes that refraining from work demands allows
recovery processes to occur. Moreover, it is crucial that resources needed during work are not
further called upon during time periods when recovery is supposed to occur.
Although little studies are performed to study recovery on a day-to-day basis, most of
them are performed by Sonnentag and colleagues, using the ERM (e.g. Sonnentag, 2001;
Sonnentag, 2003, Sonnentag & Natter, 2004). These studies all failed to confirm that
demanding activities (e.g. household activities) during off-job time inhibit daily recovery. For
example, Sonnentag (2001) could not prove that spending time on household activities is
harmful for one’s recovery. Also, Sonnentag and Natter (2004) did not find any effect of
household and childcare activities as well as low-effort activities on well-being. Instead, they
found that, contrary to the ERM, social activities after work time have a detrimental effect on
Personality, Off-job activities and State Well-Being
6
well-being. These conflicting findings could be explained by the possible moderating role of
personality traits in the relationship between off-job activities and state well-being.
Personality and Well-being
Extraversion refers to the tendency to be sociable, active, fun-loving, outgoing, friendly,
and talkative, and neuroticism refers to the tendency to be worrying, insecure, self-conscious,
and experience different temperaments (Costa & McCrae, 1980). In general, extraverts report
being happier than introverts, and neurotics report being less happy than emotional stable
individuals (Costa & McCrae, 1980). Both personality traits have been shown to have
systematic effects on psychological well-being (for a review, see Diener & Lucas, 1999).
Most theories explaining the personality−well-being relationship have focused on this direct
effect (see Figure 1, path a) of personality on well-being. For example, Eysenck (1981)
proposed that arousal is a key facet of extraversion, such that extraverts are motivated to
engage in stimulating social activities because of their inherent under arousal. However, it is
also likely that there are indirect or interactional effects, such that different activities affect
well-being differently depending on one’s personality (Diener, Oishi & Lucas, 2003). For
example, although extraverts are generally happier than introverts, Kette (1991) found that
extraverted prisoners were less happy than introverted prisoners. This suggests that the
situational features of prison were not congruent with an extraverted disposition (Diener et al.,
2003). But how does personality affect the link between daily leisure activities and,
consequentially, state well-being (see Figure 1, path b)? Examining such moderating effects is
the main aim of this study.
Figure 1
The Relationship between Personality, Leisure Time Activities, and State Well-Being
personality
a
Leisure time
activities
b
‘state’ well-being
‘state’
Happiness
Recovery
Personality, Off-job activities and State Well-Being
7
Accordingly, Watson and Clark (1997) posit that neurotics and extraverts have a
temperamental susceptibility to experience negative and positive affect, respectively. This
claim is based on Gray's (1991) theory of personality. Gray claims that two underlying
hypothetical brain systems are responsible for much of the individual differences in
personality. The behavioral activation system (BAS) regulates reactions to signals of
conditioned reward and non-punishment, whereas the behavioral inhibition system (BIS)
regulates responses to signals of punishment and non-reward. Experimental studies (e.g.,
Derryberry & Reed, 1994; Larsen & Ketelaar, 1991; Rusting & Larsen, 1997) confirmed that
extraverts are characterized by a greater sensitivity towards rewards and a differential
attention to positive stimuli, following a positive mood induction in which people had to think
about happy social events. Moreover, it was found that neurotic participants exerted more
attention towards negative stimuli.
In addition, the situational congruence hypothesis (Diener et al., 1984) proposed that
individuals should experience more pleasant affect and less unpleasant affect in situations that
are congruent with their personality characteristics. Mixed results for the situational
congruence model have been found (Diener et al., 1984; Emmons, Diener & Larsen, 1985).
Several predictions have been supported; for example, extraversion correlates more highly
with pleasant affect in social situations that in situations in which the individual was alone.
Other predictions have, however, not been supported. In line with Diener et al. (1999), it is
argued that the limited support for personality-environment interaction effect in past research
could be attributable to methodological limitations of early research. Given that early studies
all focused on trait happiness for assessing well-being, the ‘state’ component of well-being
was not incorporated in the measurement of happiness. Thus, measuring the impact of specific
leisure time activities using a global measurement of well-being would not have been able to
capture the fluctuations in activity-specific state happiness.
Rather, this research paper will look at the variability of activity-specific ‘state’ happiness
within persons through happiness and recovery, when evaluating the personality-leisure
activities interaction. In addition, past research has almost exclusively focused on happiness
as an outcome variable for the interaction between off-job leisure activities and personality.
Recovery, however, has not yet been researched profoundly. Therefore, we will start by
offering hypotheses based on the interaction between personality and leisure time activities on
‘state’ happiness and incorporate daily recovery in our hypotheses in a more exploratory
Personality, Off-job activities and State Well-Being
8
manner, based on findings combining the theory of Gray (1991) and the situational
congruence hypothesis (Diener et al., 1984).
Hypotheses
Empirical research and people’s daily experiences show that individuals cannot spend
all their time on off-job activities that have a ‘recovering effect’ (Sonnentag & Natter, 2004).
Sonnentag (2001) differentiates between two types of activities: high-duty profile activities
and low-duty profile activities. The difference between high-profile and low-profile activities
is that low-duty profile activities are not obligatory and may be skipped or postponed easily
without any negative consequences. These activities correspond with typical leisure time
activities such as ‘watching television’ or ‘meeting with friends’ and comprise: (a) low-effort
activities, (b) social activities, and (c) physical activities. High-duty profile activities (e.g.
cooking, working overtime), however, are characterized by a high degree of obligation, and
include: (d) job-related activities and (e) household chores and child-care activities.
High-Duty Profile Activities
Job-related activities draw on the similar resources to those called upon during
(formal) working time. According to the ERM (Meijman, & Mulder, 1998), recovery occurs
only when no further demands are put on resources that were also required during working
time. Following the ERM, Sonnentag and Natter (2004) found that time spent on work-related
activities resulted in lower levels of vigor and higher levels of fatigue at bedtime in a
population of flight attendants. A similar argument applies to household activities, which are
often cognitively or physically demanding activities. However, concerning household
activities, Sonnentag and Natter (2004) as well as several other studies (e.g., Sonnentag, 2001;
Sonnentag & Zijlstra, 2006), did not find any negative effects on well-being. This lack of
findings could be attributable to the notion that all these studies did not look at the possible
moderating effect of personality in the high-duty profile activities-recovery relation.
Hence, personality differences may influence to what extent individuals may recover
from their workday. Both extraversion and neuroticism have been shown to have systematic
effects on psychological well-being (for a review, see Diener et al., 1999). Indirect evidence
for the proposed moderating effect of personality in the leisure activity-‘state’ well-being
relationship stems from a study by Brandstätter (1994). This study demonstrates that
Personality, Off-job activities and State Well-Being
9
introverts as well as neurotic individuals are not happier when engaging in low-duty profile
leisure activities than when at work. Emotional stable and extraverted individuals, however,
were significantly happier during low-duty profile leisure activities than when at work. Also,
the preference for leisure activities, in contrast to working, within neurotics as well as
introverted individuals was less pronounced than within extraverts and emotional unstable
individuals.
In line with Gray’s personality theory (1991), it is argued that personality can ‘undo’
the negative effects of job-related and household activities on state well-being during leisure
time. More precisely, previous researchers (e.g., Furnham & Brewin, 1990) have claimed that,
as a result of a strong BAS activity, extraverts tend to magnify rewards and non-punishment,
whereas neurotic individuals are sensitive to signals of punishment and non-reward as a result
of a strong BIS activity. Accordingly, we propose that neurotics will have a stronger incentive
for completing activities with a high-duty profile than emotional stable persons, in order to
avoid the possible threat of punishment, which leads to an increase amount of negative
emotions. Moreover, neurotic individuals will want to remove the threat of a possible negative
consequence (e.g. a negative comment from one’s superior when not finishing a work-related
task at home for the next day) that is attached to not completing a high-duty profile activity. It
is possible that this emotional ‘threat’ will lead to a higher level of stress which, in turn, will
hamper ‘state’ well-being for neurotics, unless they engage in work-related activities and
finish the job.
The opposite is argued for extraverted individuals. As extraverts are more sensitive to
rewards, they will have a stronger incentive to conduct an activity that is perceived as
‘enjoyable’ or ‘fun’, which will increase positive emotions. This does not include job-related
activities or household activities, for most individuals. State well-being (i.e. happiness with
activities and daily recovery) within extraverts will, then, not improve when engaging in these
activities because resources used during the workday cannot be restored. Thus, it is
hypothesized that:
Hypothesis 1a: Time spent on overtime work is positively related to happiness when neuroticism is
high, and time spent on overtime work is negatively related to happiness when neuroticism is low.
Hypothesis 1b: Time spent on overtime work is positively related to recovery when neuroticism is
high, and time spent on overtime work is negatively related to recovery when neuroticism is low.
Personality, Off-job activities and State Well-Being
10
Hypothesis 2a: Time spent on overtime work is positively related to happiness when extraversion is
low, and time spent on overtime work is negatively related to happiness when extraversion is high.
Hypothesis 2b: Time spent on overtime work is positively related to recovery when extraversion is low,
and time spent on overtime work activities is negatively related to recovery when extraversion is high.
Hypothesis 3a: Time spent on household activities is positively related to happiness when neuroticism
is high, and time spent on household activities is negatively related to happiness when neuroticism is
low.
Hypothesis 3b: Time spent on household activities is positively related to recovery when neuroticism is
high, and time spent on household activities is negatively related to recovery when neuroticism is low.
Hypothesis 4a: Time spent on household activities is positively related to happiness when extraversion
is low, and time spent on overtime work activities is negatively related to happiness when extraversion
is high.
Hypothesis 4b: Time spent on household activities is positively related to recovery when extraversion
is low, and time spent on overtime work activities is negatively related to recovery when extraversion
is high.
Low-duty profile activities
This study concentrates on three types of leisure time activities that have a potentially
recovering effect: low-effort activities, social activities, and physical activities. Typical loweffort activities are relatively passive activities such as watching television, reading a book, or
just relaxing (Sonnentag, 2001). Often, these activities are characterized by a high degree of
passivity, thus representing below-baseline activities. This implies that no demands are put on
resources normally required for accomplishing one’s work tasks. As a consequence, in line
with the ERM, the functional systems can return to their normal, pre-stressor level. Therefore,
different researchers have argued that low-effort activities have a recovering effect and
engaging in these activities will improve an individual’s state well-being (e.g., Sonnentag,
2001; Sonnentag & Natter, 2004). Although low-effort activities seem to be relaxing and
pleasurable, another line of research claims that passive leisure activities have a detrimental
effect on individual’s health and well-being because they are related to boredom and apathy
(e.g., Iso-Ahola, 1997). Likewise, Tkach and Lyubomirsky (2006) found that frequent passive
leisure was not related to happiness.
An explanation for these inconclusive, and apparently contradicting, findings is that
personality plays an important moderating role in the passive leisure–happiness relation.
Hence, researchers found that neuroticism is related to passive forms of leisure activities. For
Personality, Off-job activities and State Well-Being
11
example, Nias (1977) found that an interest in listening to music was associated with
neuroticism, and Hills and Argyle (1998) found that neuroticism was associated with an
increased amount of watching TV. In addition, researchers also found that introversion might
also be related to passive forms of leisure activities (Kirkcaldy & Furnham, 1990). These
findings support the situational congruence hypothesis (Diener et al., 1984), which proposes
that experiencing trait-congruent or trait-incongruent situations is related to differential levels
of affect, so that individuals with high scores on a personality characteristic experience
positively valenced affect when engaging in congruent situations compared with individuals
with low scores on that personality characteristic. In contrast individuals with high scores on a
personality characteristic experience more negatively valenced affect when engaging in a
situation discordant with the trait than individuals with low scores on that personality
characteristic experience when engaging in that behavior.
Specifically, the trait of extraversion is related to energy, excitement-seeking and
action-orientation. Naturally, these features are trait-discordant with low-effort activities.
Thus, it is expected that extraverts would experience negatively valenced affect when
engaging in low-effort activities. The opposite is true for introverted individuals, who are
expected to experience positive valenced affect when engaging in low-effort activities.
Moreover, the trait of neuroticism is related to anxiety, frustration, and stress. Engaging in
activities that provide maximum opportunity for relaxation, as with low-effort activities, is
expected to render more positive valenced affect for high neurotic individuals than for low
neurotic individuals. Thus, it is proposed that:
Hypothesis 5a: Time spent on low-effort activities is positively related to happiness when neuroticism
is high, and time spent on low-effort activities is negatively related to happiness when neuroticism is
low.
Hypothesis 5b: Time spent on low-effort activities is positively related to recovery when neuroticism is
high, and time spent on low-effort activities is negatively related to recovery when neuroticism is low.
Hypothesis 6a: Time spent on low-effort activities is positively related to happiness when extraversion
is low, and time spent on low-effort activities is negatively related to happiness when extraversion is
high.
Hypothesis 6b: Time spent on low-effort activities is positively related to recovery when extraversion
is low, and time spent on low-effort activities is negatively related to recovery when extraversion is
high.
Personality, Off-job activities and State Well-Being
12
Social activities refer to activities that focus on a social contact, such as meeting with
family members, friends or a having a drink with colleagues after work time. This category
also includes activities such as going to a party, having dinner with others, or phoning other
people (Sonnentag, 2001). The literature provides two main mechanisms why social
participation has the potential for successful recuperation after a workday. First, social
activities offer the perfect opportunity for social support. There is broad empirical evidence
that social support has positive effects on well-being (Viswesvaran, Sanchez & Fischer, 1999)
and that social support reduces the negative influence of job demands on psychological wellbeing (Bakker, Demerouti & Euwema, 2005). Second, during social activities, no further
demand is put on resources needed during work-related activities. As a consequence,
resources that were drained from a person during the workday can be replenished (Meijman &
Mulder, 1998).
Accordingly, different studies report a positive relation between social participation
and happiness (e.g., Bradburn, 1969; Diener et al., 1984). For example, Bradburn (1969) has
found a direct link between social participation and happiness when controlling for health and
other demographic variables. Likewise, a more recent study from Helliwell and Putnam
(2004) found a strong link between social capital, measured by the strength of a person’s
social ties, and subjective well-being. Moreover, Tkach and Lyubomirsky (2006) found that
social affiliation, as a happiness-increasing strategy, showed a strong positive relation to
happiness. But, despite all the positive evidence for the social activities-happiness interaction,
several studies did not find any relationship between social activities and happiness (e.g.,
Liang, Dvorking, Kahana & Mazian, 1980; Sonnentag & Natter, 2004). These contradictory
findings can be explained by personality as a third variable, which moderates the social
participation-happiness relationship. In line with this notion, Trougakos and Hideg (2009)
found that introverts were not able to recover their resources after a group lunch; rather it
exhausted them even more. Extraverts, conversely, who enjoy being in the company of others,
experienced a group lunch break as a respite and experienced greater restoration of their
resources.
An important consideration is that, undoubtedly, people have different needs for social
activities. Perceived ability is a strong prevenient of taking up a leisure activity (Argyle & Lu,
1990; Lu & Hu, 2005). Consequently, introvert and neurotic individuals may lack the
necessary social skills and, therefore, lots of energy is directed towards compensating for this
lack of skills. In turn, recovery is impaired and resources are continued to be drawn upon and
Personality, Off-job activities and State Well-Being
13
state well-being declines. This notion is supported by Diener et al. (1999), whom reported that
extraverts are happier than introverts in social situations. Accordingly and in line with the
situational congruence hypothesis (Diener et al., 1984), it is expected that extraverts would
experience positively valenced affect when engaging in social activities, as they tend to be
talkative, and feel more comfortable around other people. The opposite is true for introverted
individuals, who are more tranquil and less socially skilled than extraverts. As a consequence,
introverts are expected to experience negative valenced affect when engaging in social
activities. Moreover, the trait of neuroticism is related to anxiety, frustration, and stress. High
neurotic individuals might focus more on negative feedback, and fear social disapproval
during social encounters. Engaging in social activities is, therefore, expected to render more
negative valenced affect for high neurotic individuals than for low neurotic individuals. Thus,
it is proposed that:
Hypothesis 7a: Time spent on social activities is positively related to state happiness when neuroticism
is low, and time spent on social activities is negatively related to happiness when neuroticism is high.
Hypothesis 7b: Time spent on social activities is positively related to recovery when neuroticism is
low, and time spent on social activities is negatively related to recovery when neuroticism is high.
Hypothesis 8a: Time spent on social activities is positively related to happiness when extraversion is
high, and time spent on social activities is negatively related to happiness when extraversion is low.
Hypothesis 8b: Time spent on social activities is positively related to recovery when extraversion is
high, and time spent on social activities is negatively related to recovery when extraversion is low.
Physical activities comprise a wide range of behaviors; including exercise, sports, and
other activities such as work on one’s hobbies and try to maintain health and fitness. During
physical activities, most individuals use other resources than those needed in work
accomplishment processes, with the exception of individuals who work in jobs with heavy
physical demands. Active involvement in physical activities implies a cognitive distraction of
job-related duties (Yeung, 1996). Consequently, a temporary relief from job-related problems
and demands occur, that allows the functional system to recover to baseline energy levels.
Moreover, physical activities stimulate physiological and psychological processes, which
contribute to an increase in individuals’ health and well-being (Wankel & Berger, 1990).
Empirical research shows that physical activities have a positive effect on individuals’ mood
and well-being, including both short-term and long-term benefits (e.g., Demerouti et al., 2009;
Personality, Off-job activities and State Well-Being
14
Sonnentag, 2001). Also, Tkach and Lyubomirsky (2006) found that active leisure was a
strong predictor of happiness.
Previous research has demonstrated that there might be a difference in physical
activities for neurotics and emotionally stable individuals. Evidence for this difference comes
from research performed by Lu and Argyle (1994), who have found that neurotics tend to
prefer hobbies rather than sports. Moreover, Brebner (1985) found that sports people tend to
be low on neuroticism. In addition, Kirkcaldy and Furnham (1990) note that neuroticism is a
powerful predictor for whether a person likes or dislikes physical activities. Research has also
established a clear link between extraversion and physical activities. Firstly, Hills and Argyle
(1998) found that people who score high on extraversion tend to belong to sports clubs more
often. Likewise, Brebner and Cooper (1985) pointed out that, undoubtly, persons who engage
in sports tend to be extraverted because of their higher pain thresholds, sensation-seeking,
assertiveness, competitiveness, and speed of reaction. Finally, researchers found that the
introversion-extraversion factor seems most powerful in predicting sport preference
(Kirkcaldy & Furnham, 1990).
In accordance with the congruence hypothesis (Diener et al., 1984), it is argued that
people choose their leisure activity in congruence with their personality which, in turn, will
influence how happy a person feels during a specific activity. Moreover, improved well-being
indicates that recovery is occurring. Thus, choosing a leisure activity that is congruent with
one’s personality will improve state well-being. For example, it is expected that, congruent
with their energetic and excitement-seeking personality, extraverts will beneficiate more from
pursuing physical activities. Indeed, it was found that physical activities are pursued for the
excitement and are associated with states of high arousal (Hills & Argyle, 1997). This is not
meant to imply that physical activities will have a negative influence on introverted
individuals, as physical activities undoubtly contribute to a healthy and balanced lifestyle
(Wankel & Berger, 1990). The same argument applies for neurotic individuals: congruent
with their anxious, and tensed personality, introverts might be frightened to injure themselves
during a physical activity. This leads to negative valenced emotions, and physical activities
will, therefore, have a negative influence on state well-being (i.e. state happiness and recovery
before sleep). Therefore, it is hypothesized that:
Hypothesis 9a: Time spent on physical activities is positively related to state happiness when
neuroticism is low, and negatively related to state happiness when neuroticism is high.
Personality, Off-job activities and State Well-Being
15
Hypothesis 9b: Time spent on physical activities is positively related to state happiness when
neuroticism is low, and negatively related to state happiness when neuroticism is high.
Hypothesis 10a: Time spent on physical activities is more strongly positively related to state happiness
when extraversion is high than when extraversion is low.
Hypothesis 10b: Time spent on physical activities is more strongly positively related to recovery when
extraversion is high than when extraversion is low.
Methods
Participants
In total, more than 10,000 subjects participated in an electronic diary survey, which
was part of an ongoing research project on lifestyle and happiness in The Netherlands. This
resulted in 106,936 reported activities and momentary happiness scores. Of these participants,
approximately 1,736 respondents also both filled in the personality inventory as well as an
electronic diary survey on the internet. However, to get an accurate indication of people’s
daily off-job activity patterns and recovery, only days on which respondents had worked were
included in the study. In total, 228 out of the 1,736 (13%) respondents met this criterion. The
average number of daily DRM diaries filled out by participants was 2,87 times and ranged
from 1 up to 41 times (SD = 3,89). After removing 13 unreliable diaries, which were used
solely for test purposes, we gathered a total of 641 operable diaries for the working
population. This resulted in a total of 6,385 reported activities after work time (starting 17.00
pm) and momentary happiness scores.
The mean age was 40 years (SD = 11.42), ranging from 15 to 81 years. The working
sample consisted of 25 males and 203 females (11% to 89%). Concerning income, 43% of the
participants earned an above average income (> € 2,500 a month), 36% earned an average
income (€ 2500 a month), and 21% earned a below average income (< € 2,500 a month).
Furthermore, on average, the respondents worked 31,10 (SD = 11,15) hours a week and 4,29
(SD = 1.14) days a week.
Procedure
The data were collected through an ongoing research project on lifestyle and happiness
in The Netherlands. Participants were recruited via social media, and HTML links on internet
sites in the Netherlands. Upon agreement, participants were first invited to fill out their
‘personal profile’, which consisted out of socio-demographic and lifestyle variables, like their
Personality, Off-job activities and State Well-Being
16
age, gender, educational level, family life, and employment status. Moreover, participants
were provided with the opportunity to fill in the NEO-FFI. Thereafter, participants created a
unique name and password which allowed them to access their happiness diary.
The happiness diary followed the Day Reconstruction Method (Kahneman et al,
2004). On the first webpage, participants were asked to reconstruct their previous day in
chronological order by filling in what kind of activities they had pursued and the approximate
time they had spend on each activity. Participants could choose from main activity categories
as proposed by Sonnentag and colleagues (Sonnentag, 2001; Sonnentag, 2003; Sonnentag &
Zijlstra, 2006). Within these main categories, respondents were shown specific sub-activities
associated with each main categories. Also, participants could indicate with whom they had
pursued each activity (e.g. with friends, alone).
On the second page of the happiness diary, respondents were presented a
chronological overview of their reported activities and were asked to rate how happy they had
felt during each activity. Thereafter, participants answered about their daily recovery before
going to sleep that day.
Measures
Daily off job-activities. Based on the work of Sonnentag (2001), main categories
included high-duty profile activities and low-duty profile activities. High-duty profile
activities consisted of: (a) job-related activities and (b) household activities. Job related
activities included time spent on overtime work. More precisely, we calculated the amount of
time a person spent working each day. Next we subtracted the standard amount of work hours
in The Netherlands (8 hours a day). Thereafter, we presumed that overtime work was
classified as the hours a person had worked that day, beyond the standard amount of 8 hours a
day. On average, participants indicated they had worked overtime 163 times (M = 0:19; SD =
0:51 hours a day). Household activities included cooking, cleaning, doing groceries, doing
odd jobs, doing administration and, finally, taking care of one’s children and spouse. On
average, participants indicated they had engage in household activities 357 times (M = 1:07;
SD = 1:53 hours a day).
Low-duty profile activities consisted of: (c) social activities, (d) physical activities,
and (e) low-effort activities. Social activities consisted of talking, going out to the theater, the
movies, a club, cultural event, a bar, and watching sports with friends. On average,
participants indicated they had engaged in social activities 153 times (M = 0:37; SD = 1:22
Personality, Off-job activities and State Well-Being
17
hours a day). Physical activities included walking, cycling, and doing sports. On average,
participants indicated they had pursued physical activities a 141 times (M = 0:19; SD = 0:47
hours a day). Lastly, Low-effort activities included reading, using one’s computer, watching
television, listening to music, taking a nap and doing nothing. On average, participants
indicated they had engaged in low-effort activities 491 times (M = 2:22; SD = 2:21 hours a
day).
State Happiness during off-job activities was rated with one item for each reported
activity during the day using a ‘faces scale’ that ranged from 0 (extremely unhappy) up to 10
(extremely happy). According to Abdel-Khalek (2006), a single item for measuring happiness
has good temporal stability and concurrent, convergent, and divergent validity.
Daily recovery before sleep was assessed with three items that were slightly adapted
from the measure of Sonnentag (2003), being, “Yesterday before going to sleep, I felt
recovered”, “Yesterday before going to sleep, I felt rested”, and “Yesterday before going to
sleep I felt I had enough time to recover from my workday”. Items were answered on a 7point likert scale ranging from 1 (I don’t agree at all) up to 7 (I totally agree). Cronbach’s
alpha varied between 0.93 and 0.94 depending on the week-day, indicating very good
reliabilities.
Extraversion and 7euroticism were measured using the NEO-FFI. The NEO-FFI is a
shortened version of the NEO Personality Inventory-Revised (NEO PI–R; Costa & McCrae,
1992), and was used to assess personality traits (only neuroticism and extraversion were used
in this particular study), which represent tendencies to show consistent patterns of thoughts,
feelings, and actions. The 60 items of the self-report questionnaire allow a reliable
measurement of five domains of adult personality (neuroticism, extraversion, openness to
experience, conscientiousness, and agreeableness). The items are rated on a 5-point Likert
scale ranging from 1 (strongly disagree) up to 5 (strongly agree) and are balanced to control
for acquiescence response set. Cronbach’s alpha was .89 for neuroticism and .81 for
extraversion, showing good levels of reliability.
Control variables. We controlled for gender, educational level, income, the amount of
hours worked that day, workdays a week, and day of the week (weekend vs. a weekday).
Controlling for work variables is important in order to cancel out any correlation between
leisure activities and recovery due to their mutual dependence on the influence of work
demands (Tucker et al., 2008).
Personality, Off-job activities and State Well-Being
18
Analysis
The data have a hierarchical structure with days nested within persons and activities
nested within days. We aggregated the time spend on each activity to the day-level. Therefore,
a hierarchical linear modeling using a cross-level interaction between personality and
activities was used to analyze the data. In this analysis, first, a null model that includes only
the intercept was entered. In the following steps, the person-level variables – gender,
educational level, income, hours worked, workdays a week, day of the week, neuroticism, and
extraversion – were entered and centered at the grand mean (step 1). Hereafter, personality
variables were entered and, also, centered at the grand mean (step 2). In step 3, time spent on
off-job activities was aggregated to the day-level and was centered at the person mean. The
last step consisted of entering the cross-level interactions in the model (step 4). Momentary
happiness derived from off-job activities and recovery before going to sleep was aggregated
to the day-level and was centered at the person mean. Hierarchical linear modeling is the most
appropriate method for dealing with this kind of a hierarchically structured dataset and takes
the dependence of the day-level measurements within each person into account (Snijders &
Bosker, 1999). Data analysis was conducted using MLwiN (Rabash, Browne, Healy,
Cameron & Charlton, 2000).
Results
Preliminary Analyses
Table 1 reports means, standard deviations, bivariate correlations, and zero-order
correlations. Table 1 shows that mean state happiness score was 6.61 (SD = 1.41), and mean
recovery score was 4.11 (SD = 1.52). As expected, we found that extraversion is positively
related to state happiness (r = .27, p < .001). In contrary, neuroticism is negatively related to
state happiness (r = -.35, p < .001). Unexpectedly, neuroticism also correlated negatively with
daily recovery before sleep (r = -.22, p < .001). Furthermore, as is often the case, neuroticism
and extraversion are strongly intercorrelated (r = -.53 p < .001).
When we look at time spent on activities, Table 1 shows that participants spend most
of their daily off-job time on low-effort activities and least time on overtime work activities
and physical activities. Moreover, the data shows that extraverts spend more time on physical
activities (r = .09, p < .05). Other activities show non-significant relationships with
personality traits.
Personality, Off-job activities and State Well-Being
19
Daily Recovery before Sleep
Before testing our hypotheses, we examined the variability of recovery before sleep across the
two levels (person level, day level). Of total variance, 43.3% was between persons
(1.134/(1.134+1.485)) and 56.7% within persons at the day level (1.485/(1.485+1.134)),
indicating that recovery before sleep varied significantly within persons from day-to-day. Due
to the high intercorrelation between neuroticism and extraversion, we opted for two different
models: one model solely comprising neuroticism, and one model solely including
extraversion. In Model 1, neuroticism or extraversion was entered as a predictor variable, and
sex, income, education, whether the specific day was weekend or working day and the amount
of hours worked on that particular day as control variables. In Model 2, the type of activity
(social, physical, household, and low-effort, and overtime work activities) was added. Model
3 included the social, physical, household, low-effort, and overtime work activities x
personality (extraversion and neuroticism) interaction terms. Table 2 and Table 3 present the
findings of each Model.
We tested the improvement of each model over the previous one by computing the
differences of the respective log likelihood statistic -2*log, subjecting the difference to a chisquared (chi²) test. Regarding daily recovery, results demonstrated that Model 1 had a better
model fit compared to the Null (intercept only) model (see Table 2, ∆-2 x log = 6412.934, ∆df
= 6, p < .001; and Table 3, ∆-2 x log = 6412.934, ∆df = 6, p < .001), indicating that the
control variables explain a part of the variance in daily recovery. We did not find that Model 2
had a better fit than Model 1 (see Table 2, ∆-2 x log = 2.891, ∆df = 5, p < .001; and Table 3,
∆-2 x log = 3.090, ∆df = 5, ns), implying that off-job activities do not account for any
variance in recovery before sleep. Furthermore, concerning the neuroticism x activities
interaction, Model 3 had a better fit than Model 2 (see Table 2, ∆-2 x log = 20.152, ∆df = 5, p
< .001), suggesting that the personality x leisure activities interaction (partly) explains the
variance in daily recovery. In contrast, regarding the extraversion x activities interaction,
Model 3 did not have a better fit than Model 2 (see Table3, ∆-2 x log = 8.710, ∆df = 5, ns).
Results in Table 2 and 3, Model 1, show that income was positively related to
recovery before sleep (t = 1.78, p < .05). Gender, education, whether the day was a weekend
or workday, and hours worked that day, however, were not related to recovery before sleep in
both models. Moreover, neuroticism, related negatively to recovery before sleep (see Table 2;
t = -3.45, p < .001). Extraversion, however, was not connected to recovery before sleep.
Personality, Off-job activities and State Well-Being
20
Interestingly, results in Table 2, Model 2 indicated that there were no main effects of leisure
activities on daily recovery before sleep.
State Happiness
Hereafter, the variability of state happiness across the two levels (person level, day
level) was examined more thoroughly. Of the total variance, 66,4% was between persons
(1.168/(1.168+0.820)) and 33,6% at the day level (0.820/(0.820+1.168)) showing that state
happiness depended mostly on differences in personality and demographic/lifestyle variables,
but also on how a person chooses to spent his/her time during the day. Models and hypotheses
were tested in a similar manner as with daily recovery before sleep.
Concerning state happiness, results demonstrated that Model 1 had a better model fit
compared to the Null (intercept only) model (see Table 4, ∆-2 x log = 9081.341, ∆df = 6, p <
.001; and Table 5, ∆-2 x log = 6,412.934, ∆df = 6, p < .001), meaning that control variables
explain a part of the variance in state happiness. We did, however, not find that Model 2 had a
better fit than Model 1 (see Table 4, ∆-2 x log = 5.452, ∆df = 5, ns; and Table 5, ∆-2 x log =
9,075.485, ∆df = 5, ns). This finding implies that off-job activities per se do not explain a part
of the variance in state happiness. Furthermore, we found that Model 3 had a better fit than
Model 2 (see Table 4, ∆-2 x log = 22.150, ∆df = 5, p < .001; and Table 5, ∆-2 x log = 26.590,
∆df = 5, p < .001), suggesting that the personality x leisure activity interaction explains a part
of the variance in state happiness.
The results in Model 1 showed that hours worked on a day (up to a maximum of eight
hours) were significantly positively related to state happiness (see Table 4, t = 2.38, p <.05;
and Table 5, t = 2.57, p <.01). Gender, education, and whether the day was a weekend or
workday, however, were not related to state happiness. Income was only related to state
happiness in the interaction model between extraversion and daily activities (t = 3.08, p
<.001), but not in the neuroticism and daily activities model. Neuroticism related negatively
to state happiness (t = -4.87, p <.001), and extraversion was positively related to state
happiness (t = 4.18, p <.001). Again, the results in Table 4 and 5, Model 2 indicated that
there was no significant main effect of time spent on off-job activities on state happiness.
Testing Hypotheses
Results from Table 2 up to Table 5 show all interaction effects between time spent on off-job
activities and personality on recovery before going to sleep, as well as state happiness. Out of
Personality, Off-job activities and State Well-Being
21
the 20 interaction effects that were tested, 11 interaction effects (55%) proved to be
significant. In total, 5 interaction effects (25%) were in the expected direction and 6
interaction effects (30%) were partly in the expected direction and partly in the opposite
direction. Figures 1 through 11 provide more insight in the nature of the interaction effects
that were significant. To examine the nature of these interactions in more detail, we conducted
simple slope tests for HLM models as proposed by Preacher, Curran, and Bauer (2006).
Hypothesis 1a and 1b stated that time spent on overtime work activities is
positively related to ‘state well-being’ (i.e. daily recovery and state happiness) when
neuroticism is high, and negatively when neuroticism is low. Table 2, Model 3 indicates that
the interaction effect of time spent on overtime work activities and neuroticism on daily
recovery before sleep was significant (t = 2.61, p < .01). Moreover, Table 4, Model 3 shows
that the interaction effect of time spent on overtime work x neuroticism on state happiness
was also significant (t = 3.10, p < .001). Figure 1 and 2 show these interaction patterns in
more detail.
Figure 1. Interaction effect of time spent on overtime work activities and neuroticism on daily recovery before
sleep.
Simple slope analyses revealed that time spent on overtime work activities related
positively to daily recovery before sleep for people who scored high on neuroticism (1 SD
above the mean; γ = 1.709, SE = 0.872, z = 1.960, p < 0.05), but also for people who scored
low on neuroticism (1 SD above the mean; γ = 0.342, SE = 0.175, z = 1.960, p < 0.05), partly
rejecting Hypothesis 1a. Also, the effect of overtime work on daily recovery before sleep was
stronger for people who are high on neuroticism.
Personality, Off-job activities and State Well-Being
22
Figure 2. Interaction effect of time spent on overtime work activities and neuroticism on state happiness.
Moreover, when neuroticism is high (γ = 1.012, SE = 0.516, z = 1.960, p < 0.05), the
time spent on overtime work related positively to state happiness (1 SD above the mean).
Contrary to Hypothesis 1a, when neuroticism is low (1 SD above the mean; γ = 0.315, SE =
0.161, z = 1.960, p < 0.05), time spent on overtime work is also positively related to state
happiness, partly rejecting Hypothesis 1a. Nevertheless, the effect of overtime work activities
on state happiness was stronger for people who are high on neuroticism.
Hypothesis 2a and 2b indicated that time spent on overtime work is positively
related to recovery when neuroticism is high, and time spent on overtime work activities is
negatively related to recovery when neuroticism is low. Table 3, Model 3 indeed indicates
that the interaction effect of time spent on overtime work activities and extraversion on daily
recovery before sleep was significant (t = -1.90, p < .01). Likewise, the interaction effect of
time spent on overtime work activities and extraversion on state happiness was also
significant (see Table 5, Model 3, t = -3.16, p < .001). A detailed picture of these interaction
effects are demonstrated in Figure 3 and 4.
Confirming Hypothesis 2a, the amount of time spent on overtime work activities
related positively to daily recovery before sleep for people who scored low on extraversion (1
SD below the mean; γ = 0.334, SE = 0.170, z = 1.960, p < 0.05). In contrast, spending time on
overtime work activities related negatively to state happiness when extraversion was high (1
SD above the mean; γ = -1.098, SE = 0.560, z = -1.960, p < 0.05).
Personality, Off-job activities and State Well-Being
23
Figure 3. Interaction effect of time spent on overtime work activities and extraversion on daily
recovery before sleep.
Figure 4. Interaction effect of time spent on overtime work activities and extraversion on state
happiness.
Moreover, confirming Hypothesis 2b, examination of simple slopes revealed that time
spent on overtime work related positively to daily recovery before sleep for people who
scored low on extraversion (1 SD below the mean; γ = 5.008, SE = 2.555, z = -1.960, p <
0.05). Conversely, spending time on overtime work activities related negatively to daily
recovery before sleep when extraversion was high (1 SD above the mean; γ = -0.402, SE =
0.205, z = -1.960, p < 0.05).
Hypothesis 3a and 3b stated that neuroticism positively moderates the relation
between the amount of time spent on household activities and ‘state well-being’. Table 2,
Model 3 indicates that the interaction effect of time spent on household activities and
Personality, Off-job activities and State Well-Being
24
neuroticism on daily recovery before sleep was significant (t = 2.10, p < .05). Figure 5 shows
this interaction pattern in more detail.
Testing of the individual slopes revealed that time spent on household activities (1 SD
above the mean) related positively to daily recovery before sleep among people who scored
high on neuroticism (γ = 0. 249, SE = 1.271, z = 1.960, p < 0.05). In contrast to what we
expected, individuals who were low in neuroticism also felt significantly more recovered
when engaging in household activities (1 SD above the mean; γ = 0.303, SE = 0.155, z =
1.960, p < 0.05). Still, the effect of household activities on daily recovery before sleep was
stronger for people who are high on neuroticism. Thus, the interaction pattern partly
supported Hypothesis 3b.
Figure 5. Interaction effect of time spent on household activities and neuroticism on daily recovery before sleep.
The interaction effect of time spent on household activities and neuroticism on
state happiness was, however, not significant (t = -0.29, ns) (rejecting Hypothesis 3a).
Hypothesis 4a and 4b stated that time spent on household activities is positively
related to ‘state well-being’ when extraversion is low, and negatively when extraversion is
high. The interaction effect of time spent on household activities x extraversion on daily
recovery before sleep was significant (see Table 3, Model 3, t = -2.11, p < .05). A detailed
picture of this interaction effect is demonstrated in Figure 6. Analyzing simple slopes
unveiled that when extraversion was low, individuals felt significantly more recovered after
spending time on household activities (1 SD above the mean; γ = 0. 527, SE = 0.269, z =
1.960, p < 0.05). In contrast, spending time on household activities related significantly and
Personality, Off-job activities and State Well-Being
25
negatively to daily recovery before sleep for people high in extraversion (1 SD below the
mean; γ = -1.372, SE = 0.699, z = -1.960, p < 0.05). Thus, the interaction pattern fully
supported Hypothesis 4b. Hypothesis 4a, however, had to be rejected as the interaction effect
of time spent on household activities x extraversion on state happiness was not significant (t =
-0.41, ns).
Figure 6. Interaction effect of time spent on household activities and extraversion on daily recovery before sleep.
Hypothesis 5a and 5b stated that neuroticism moderates the relation between the
amount of time spent on low-effort activities and ‘state well-being’. Rejecting Hypothesis 5b,
Table 2, Model 3 indicated that the interaction effect of time spent on low-effort activities and
neuroticism on daily recovery before sleep was not significant (t = 1.59, ns). Conversely, the
time spent on low-effort activities x neuroticism interaction on state happiness yielded a
significant result (see Table 4, Model 3, t = 2.28, p < .05). Figure 7 shows this interaction
pattern in more detail.
Personality, Off-job activities and State Well-Being
26
Figure 7. Interaction effect of time spent on low-effort activities and neuroticism on state happiness.
As hypothesized, analyzing simple slopes uncovered that for people high in
neuroticism (γ = 1.829, SE = 0.933, z = 1.960, p < 0.05), as well as for people low in
neuroticism (γ = -0.318, SE = 0.162, z = -1.960, p < 0.05), spending time on low-effort
activities leads to an increase in state happiness (1 SD above the mean). The effect of loweffort activities on state happiness was, nevertheless, stronger for people who are high on
neuroticism. Thus, the interaction pattern partly supported Hypothesis 5a.
Hypothesis 6a and 6b stated that time spent on low-effort activities is
positively related to ‘state happiness’ when extraversion is low, and time spent on low-effort
activities is negatively related to state happiness when extraversion is high. Hypothesis 6b had
to be rejected as Table 3, Model 3 indicated that the interaction effect of time spent on loweffort activities and extraversion on daily recovery before sleep was not significant (t = -0.57,
ns). Conversely, Table 5, Model 3 shows that the interaction effect of time spent on low-effort
activities and extraversion on state happiness was significant (t = -2.13, p < .05). Figure 8
shows the nature of this interaction effect.
Personality, Off-job activities and State Well-Being
27
Figure 8. Interaction effect of time spent on low-effort activities and extraversion on state happiness.
Analyzing simple slopes revealed that time spent on low-effort activities related
significantly and positively to state happiness for people who scored low on extraversion (1
SD above the mean; γ = 0.349, SE = 0.178, z = 1.960, p < 0.05). In addition, spending time on
low-effort activities related significantly and negatively to state happiness for people high in
extraversion (1 SD below the mean; γ = -4.922, SE = 2.511, z = -1.960, p < 0.05). Thus, the
interaction patterns fully supported Hypothesis 6a.
Hypothesis 7a and 7b were both rejected. Table 2, Model 3 indicated that the
interaction effect of time spent on social activities and neuroticism on daily recovery before
sleep was not significant (t = -1.31, ns). Moreover, Table 4, Model 3 shows that the
interaction effect of time spent on social activities and neuroticism on state happiness was,
also, not significant (t = 1.14, ns).
Hypothesis 8a and 8b stated that time spent on social activities is positively related to
‘state well-being’ when extraversion is high, and negatively when extraversion is low. Table
3, Model 3 indicated that the interaction effect of time spent on social activities and
extraversion on daily recovery before sleep was not significant (t = 0.49, ns), rejecting
Hypothesis 8b. In contrast, the interaction effect of time spent on social activities x
extraversion on state happiness was significant (see Table 5, Model 3, t = 1.91, p < .05).
Figure 9 shows this interaction pattern in more detail. Hypothesis 8a was fully supported as
examination of simple slopes unveiled that when engaging in social activities, individuals felt
significantly less happy when extraversion was low (1 SD below the mean; γ = -0.395, SE =
0.201, z = -1.960, p < 0.05). In addition, spending time on social activities related positively
Personality, Off-job activities and State Well-Being
28
to state happiness for people high in extraversion (1 SD above the mean; γ = 10.343, SE =
5.276, z = 1.960, p < 0.05).
Figure 9. Interaction effect of time spent on social activities and extraversion on state happiness.
Hypothesis 9a and 9b stated that neuroticism moderates the relation between the
amount of time spent on physical activities and ‘state well-being’. Table 2, Model 3 indicates
that the interaction effect of time spent on physical activities and neuroticism on daily
recovery before sleep was significant (t = -1.72, p < .05). A detailed picture of this interaction
effect is provided in Figure 10. Contrariwise, Hypothesis 9a had to be rejected as the
interaction effect of time spent on physical activities and neuroticism on state happiness was
not significant (see Table 4, Model 3; t = -1.27, ns).
Figure 10. Interaction effect of time spent on physical activities and neuroticism on daily recovery before sleep.
Personality, Off-job activities and State Well-Being
29
Testing of the individual slopes uncovered that time spent on physical activities related
negatively to daily recovery for people who scored high on neuroticism (1 SD below the
mean; γ = -4.659, SE = 2.377, z = -1.960, p < 0.05). Contrary to expectations, spending time
on physical activities also related significantly and negatively to daily recovery when
neuroticism was low (1 SD below the mean; γ = -0.393, SE = 0.201, z = -1.960, p < 0.05).
Still, the results indicated that engaging in physical activities was more strongly associated
with daily recovery for who are high on neuroticism. Thus, the interaction pattern partly
supported Hypothesis 9b.
Hypothesis 10a and 10b stated that time spent on physical activities is more
strongly positively related to state happiness when extraversion is high than when
extraversion is low. Table 3, Model 3 indicated that the interaction effect of time spent on
overtime work activities and extraversion on daily recovery before sleep was not significant (t
= 0.11, ns), rejecting Hypothesis 10b. In contrary, Table 5, Model 3 showed that the
interaction effect of time spent on physical activities and extraversion on state happiness was,
however, significant (t = 1.65, p < .05). Figure 11 shows this interaction pattern in more
detail.
Figure 11. Interaction effect of time spent on physical activities and extraversion on state happiness.
Analyzing simple slopes unveiled that time spent on physical activities related
positively to state happiness for people who scored high on extraversion (1 SD above the
mean; γ = 3.811, SE = 1.944, z = 1.960, p < 0.05). Individuals who scored low on
extraversion also felt happier when spending time physical activities (1 SD below the mean; γ
Personality, Off-job activities and State Well-Being
30
= 0.401, SE = 0.205, z = 1.960, p < 0.05). As hypothesized, the effect of physical activities on
state happiness was stronger for people who are high on neuroticism. Thus, the interaction
pattern fully supported Hypothesis 10a.
In sum, Hypotheses 2a, 2b, 4b, 6a, 8a, and 10a were fully supported, Hypotheses 1a,
1b, 3b, 5a, and 9b were partly supported, and Hypotheses 3a, 4a, 5b, 6b, 7a, 7b, 8b, 9a, and
10b were rejected. Concerning state happiness, 6 out of 10 hypotheses were fully or partly
supported (60%) and 5 out of 20 hypotheses for recovery before sleep (45%). The results
show that individuals who score high on introversion derive greater happiness from working
overtime, low-effort activities, and derive less happiness from social activities and physical
activities compared with their high-extravert counterparts. Furthermore, high neurotic
individuals deduct greater happiness from working overtime, low-effort activities, and
physical activities in comparison to low neurotic individuals. Also, individuals who score
high on neuroticism as well as people who score high on introversion derive greater daily
recovery from engaging in household activities, and work overtime activities. Finally, this
study found that individuals who score low on neuroticism deduct more recovery from
pursuing physical activities.
Discussion
In an ever more demanding workplace, adequate recovery from one’s workday is
crucial for people to maintain a high level of well-being (Demerouti et al., 2009; Sonnentag,
2001). People may enhance their recovery by engaging in certain activities during off-job
time. However, this study demonstrates that which activities contribute most to recovery and
well-being seems to depend (at least partly) on one’s personality.
The central aim of this study was to identify the kind of daily lifestyle that contributes
most to the happiness and recovery of employees. In doing so, this study contributes to the
empirical literature in three ways. First, the DRM was used to accurately capture day-to-day
fluctuations in happiness experienced by employees during activities (Kahneman et al., 2004).
Second, this study demonstrated the nature of the off-job activity per se may be less important
for state well-being than whether the activity accords with individual preference. Third, the
results show that personality moderates the relationship between activities and happiness, as
well as between activities and daily recovery. This confirms the theoretical view of Gray
(1991), as well as the situational congruence hypothesis (Diener et al., 1984), which were
Personality, Off-job activities and State Well-Being
31
previously untested on a day-to-day level. The findings, as well as the strengths and
limitations of this study, are discussed in more detail subsequently.
Personality, High-Duty Profile Activities and Daily Recovery before Sleep
This study demonstrates that high neurotics experience greater levels of recovery
before going to sleep when engaging in high-duty profile activities (household activities as
well as work-related activities) than their low neurotic individuals. However, contrary to the
ERM (Meijman & Mulder, 1998) and the work of Sonnentag and Natter (2004), we found that
spending time on high-duty profile activities (overtime work and household activities) is also
beneficial - in terms of daily recovery - for low neurotic individuals. A possible explanation
for this finding is that other mechanisms apart from work demands play an important role in
the recovery process. For example, in their study, researchers found that recovery not only
depended on what one does, but also on one’s subjective evaluation of activities as
pleasurable (Oerlemans, Bakker & Demerouti, 2010). It might be possible that if a person
regards his/her work as pleasant, recovery also may improve. The notion that job-related
and/or household activities do not always relate negatively to recovery was also found in
several other studies (e.g. Beckers et al., 2008; Sonnentag, 2001). Accordingly, in a study
about overtime work among faculty employees, Beckers et al. (2008) found that overtime
activities were experienced differently than activities during regular hours. More specifically,
overtime work was being experienced as less effortful and less stressful than regular work
hours.
Also, we found that low extraverts felt more recovered when engaging in high-duty
profile activities (household activities as well as work-related activities), whereas high
extraverts do not. In contrast, high extraverts tend to be less recovered before they go to sleep
the more they engage in household or work-related activities. These finding indirectly
supports the notion of Gray (1991) that extraversion relates to a higher BAS, regulating
reactions to signals of conditioned rewards and non-punishments and that neuroticism relates
to a higher BIS, regulating reactions to signals of conditioned non-rewards and punishments.
As a consequence, engaging in high-duty profile activities reduces the emotional threat of a
possible negative consequence, as these activities are characterized by a high degree of
obligation. As a result, overtime work and household activities enables high introverts, as well
as high neurotic individuals, to experience more positive emotions.
Personality, Off-job activities and State Well-Being
32
Personality, High-Duty Profile Activities and State Happiness
Contrary to daily recovery, this study did not find that neither high neurotics nor low
extraverts tend to experience greater levels of state happiness when engaging in household
activities. Thus, although happiness and recovery on a daily level are both important
indicators of state well-being (Sonnentag, 2001), they appear to have different antecedents in
terms of the interaction between time spent on a leisure activity and personality. It might also
be possible that recovery influences other well-being indiactors which we did not measure in
this particular study, such as life satisfaction.
However, the results demonstrate that, in line with our expectations, high neurotics
experience greater levels of state happiness when engaging in work-related activities than low
neurotics. Also, low extraverts experience greater levels of state happiness when working
overtime, whereas high extraverts report lower levels of state happiness the more they engage
in work-related activities in the evening. These finding, also, indirectly supports the notion of
Gray (1991) that extraversion relates to a higher BAS regulating reactions to signals of
conditioned rewards and non-punishments and that neuroticism relates to a higher BIS,
regulating reactions to signals of conditioned rewards and punishments. As a consequence,
high neurotics as well as low extraverts – compared with low neurotics and high extraverts –
may be better able to pick up signals of non-reward in work-related situations, enabling them
to experience more positive emotions, such as happiness, during work-related situations.
Personality, Low-Duty Profile Activities and Daily Recovery before Sleep
Furthermore, this study did not show that neuroticism plays a moderating role in the
relationship between low-effort activities and daily recovery, neither did it show that
neuroticisms moderates the relationship between social activities and daily recovery.
Interestingly, we found that both high as well as low neurotic individuals felt less recovered
after engaging in physical activities. Highly neurotic individuals beneficiated even less from
doing activities that require a physical effort in terms of daily recovery. This finding could be
explained by the fact that we measured daily recovery before a person goes to sleep and not
how recovered a person feels the next day. It might be possible that although physical
activities lead to a lower amount of energy in the evening, doing such activities will lead to a
higher amount of recovery the next day.
Also, we found that extraversion does not play a moderating role in the relationship
between low-duty profile activities (low-effort, social and physical activities) and daily
Personality, Off-job activities and State Well-Being
33
recovery before going to sleep. This finding shows us that engaging in low-duty profile
activities does not contribute to recovery differently depending on one’s extraversion trait.
Personality, Low-Duty Profile Activities and State Happiness
In line with our expectations, the results of this study seem to confirm the idea that, in
line with the situational congruence hypothesis, extraversion plays a moderating role in the
connection between low-duty profile activities (low-effort, social, and physical activities) and
happiness. More precisely, firstly, we found that high introverts experience greater levels of
state happiness when engaging in low-effort activities, whereas high extraverts do not. In
contrast, high extraverts show less state happiness the more they engage in low-effort
activities. This finding reinforces the notion extraverts experience negative valenced affect
when engaging in trait incongruent activities, such as low-effort activities.
Second, we found that high extraverts felt happier when engaging in social activities,
whereas low extraverts felt less happy when pursuing social activities. This study replicated
the finding by Trougakos and Hideg (2009) that extraverts, who enjoy being in the company
of others, experience a social activity as a respite and experienced greater state happiness
afterwards. Introverts individuals, however, may lack the necessary social skills and,
therefore, lots of energy is directed towards compensating for this lack of skills, disabling
them to experience positive emotions during social encounters.
Finally, this study demonstrates that when extraversion is high, individuals experience
greater levels of state happiness when engaging in physical activities than low extraverted
employees. Put differently, high extraverts become happier from doing activities that require a
physical effort than low extraverts. Previous research on this issue has received mixed support
(Diener et al., 1999) and relied exclusively on questionnaire data and on cross-sectional
designs (Lu & Hu, 2005), which may be an inaccurate method for capturing the happiness
experiences by employees during daily activities (Kahneman et al., 2004). The DRM applied
in this study allows for a more accurate examination of the many low-duty profile activities in
the daily lives of employees and the happiness they derive from such activities.
Hence, contrary to our expectations, neuroticism did not moderate the social activitiesstate happiness connection; neither did it moderate the physical activities–state happiness
relationship. However, as hypothesized, we did find that high neurotics experience greater
levels of state happiness when engaging in low-effort activities than their low neurotics
counterparts. In other words, high neurotics become happier from doing low-effort activities
Personality, Off-job activities and State Well-Being
34
than low neurotics. This result supports the situational congruence hypothesis (Diener et al.,
1984) by showing that the personality features of high neurotic individuals are congruent with
more passive activities, of which they derive more state happiness. Moreover, based on this
finding, an alternative explanation may be that high neurotic individuals choose to engage
more often in low-effort activities on the basis of their personality and these activities lead to
positive emotions and state happiness. This mediating path (Diener et al., 1984) between
personality, off-job activities and state well-being implies that individuals choose activities
on the basis of their personality and fit between personality and situation leads to greater wellbeing (Diener et al., 1984; Emmons et al., 1986). For instance, Eysenck (1967) found that
introverts seem to seek out situations which are low in stimulation – low-effort activities –
and avoid situations including those which involve assertiveness and competition. Likewise,
Emmons et al. (1986) showed that in their everyday environment, individuals chose to spend
time in certain situations and to avoid others and that these patterns were predictable from
personality trait scores. With our data exploration, we analyzed this mediating path; however,
we were not able to confirm that personality leads to a different choice of activities. This path
was proven to be unfruitful and, therefore, not covered further is this paper.
Strengths and Weaknesses
This study has some limitations. First, females were largely overrepresented in our
convience sample compared to percentages in the Dutch workforce (89% versus 11%). Future
research should aim at replicating our results with other samples in order to establish the
generalizability of our findings. Second, another limitation of this study involves the relative
broad categories used for assessing off-job activities. Therefore, effects of specific activities
(e.g. watching television) that might have worked into the direction opposite to their
respective larger categories could not be detected. Thirdly, we made the assumption that
overtime work consisted of each time a person had worked above the standard amount of
work hours in the Netherlands (8 hours a day). However, it might be possible that instead of
working 8 hours a day for consecutive 5 days, a person works 10 hours a day for 4 days, a
construction which is not uncommon in the Netherlands. Nevertheless, we controlled for work
hours during the day, and according to ERM (Meijman & Mulder, 1998) more hours worked
should ultimately lead to resource depletion, especially after working for over 8 hours.
Fourthly, this study does not take into account any other well-being outcome than happiness
and daily recovery, disregarding such outcomes as life satisfaction, physical health, or longer
Personality, Off-job activities and State Well-Being
35
life. However, the extensive review conducted by Lyubomirsky, King and Diener (2005)
revealed that happiness is associated with and precedes successful life outcomes, including
marriage, friendship income, work performance, subjective, and objective health outcomes.
These limitations notwithstanding, this study has also some particular strengths. First,
the DRM offers the advantage of minimizing recall biases. The results obtained from the
DRM are remarkably similar to those obtained using the experience sampling method
involving real-time reports of emotions (Kahneman et al., 2004). Accordingly, we are
confident that we have accurately monitored the daily activities of Dutch employees and the
happiness they experienced while personding the activities. Second, using the data of an
ongoing research project on lifestyle and happiness, we were able to dispose over a
remarkably high amount of subjects in a longitudinal study which enabled us to draw more
reliable conclusions.
Directions for Future Research
This study focused on the interaction between behavioral activities and personality as
a way to optimally recover from work and happiness. However, future studies may also
consider investigating the impact of off-job activities and personality on other recovery
outcome variables, such as physical vigor, cognitive liveliness and happiness outcome
variables, such as life satisfaction and physical health.
Also, in this study, we concentrated on the moderating path between personality, offjob activities and state well-being. However, future studies should direct their attention also to
the mediating path, which states that individuals choose activities on the basis of their
personality and fit between personality and situation leads to greater well-being (Diener,
Larsen & Emmons, 1984; Emmons et al., 1986). In this research paper, however, we were not
able to confirm that personality leads to a different choice of activities. This path was,
therefore, not explored further whereas the moderating path yielded interesting findings. Even
so, as mentioned earlier, effects of specific activities could not be detected for we used
relative broad categories. Hence, research on the mediating path between personality, off-job
activities and state well-being should be focused on more specific activities.
Concluding Remarks
This study sheds more light on which kind of daily lifestyle contributes to the
happiness of employees. Interestingly, we found that the amount of hours worked a day is
Personality, Off-job activities and State Well-Being
36
positively related to state happiness. This result must be interpreted cautiously, as the amount
of hours worked only encompassed regular work hours during the daytime and did not exceed
eight hours, for all hours worked above the amount of eight hours were categorized as
overtime work. Nevertheless, this finding seems to support the notion that working promotes
happiness. Several third variables may account for this relationship. For example, research
found that working is associated with positive outcome variables such as psychological status,
self-esteem, job satisfaction and social integration (Pugliesi, 1995). Also, paid work is
associated with lower levels of distress and depression (Pugliesi, 1995).
Importantly, contrary to the effort-recovery model (Meijman & Mulder, 1998), which
states that effort expenditure at work leads to the depletion of one’s resources and a lower
amount of energy, we did not find any main effects of activities on state well-being. More
precisely, we demonstrated that daily recovery and state happiness depend on the fit between
personality and activity. Therefore, the present study suggests that depending on one’s
personality, activities either contribute or not to recovery and/or happiness and not the activity
itself per se.
Personality, Off-job activities and State Well-Being
37
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5.46
2.23
1.20
4.29
5.69
4.11
6.61
2 Educational level
3 Income
4 Weekday (1 = weekday, 2 = weekend)
5 Workdays a week
Hours worked a day
Neuroticism
Extraversion
Recovery
6
7
8
9
10 Happiness
a
0:19
0:34
0:19
1:07
2:22
3.35
0:52
1:23
0:53
1:60
2:21
1.52
1.52
0.59
0.68
2.43
1.14
0.40
0.76
1.55
0.31
SD
0.04
0.11
0.00
0.04
-0.15
0.02
0.01
0.14
-0.14
0.02
-0.07
-0.13
0.17
0.16
-
1
0.01
0.07
-0.01
-0.02
-0.12
0.11
0.06
0.04
-0.15
0.04
0.22
-0.03
0.35
-
2
0.03
-0.02
0.05
0.02
0.16
0.22
0.16
0.10
-0.44
0.11
-0.02
-0.07
-
3
-0.07
0.15
0.00
0.00
0.05
0.01
0.10
0.04
-0.02
-0.19
0.10
-
4
0.04
0.08
0.05
-0.10
0.05
0.11
0.16
0.18
-0.06
0.03
-
5
0.36
-0.13
-0.17
-0.27
-0.26
0.11
0.01
-0.01
-0.07
-
6
-0.02
-0.01
-0.02
0.06
-0.02
-0.35
-0.22
-0.53
-
-0,07
7
0.05
0.08
0.09
-0.06
-0.04
0.27
0.09
-
-0.53
-0.04
8
-0.05
-0.02
0.06
-0.02
0.03
0.37
-
0.09
-0.22
0.00
9
-0.02
0.05
0.03
-0.02
-0.01
-
0.37
0.34
-0.50
-0.07
10
-0.13
-0.17
0.00
-0.02
-
-0.05
`0.03
-0.03
-0.03
-0.30
11
-0.13
-0.05
0.02
-
-0.06
0.01
-0.03
-0.13
0.11
-0.24
12
-0.08
-0.00
-
-0.03
-0.07
0.03
0.06
0.13
0.03
-0.17
13
-0.09
-
0.04
-0.04
-0.17
0.15
0.00
0.13
-0.01
-0.16
14
a
Means and SDs for activities are reported in an hour:minute format.
going to sleep.
|.13| being significant at p <.01. Time= time spent on activity. Happiness = momentary happiness during activity. Recovery = recovery before
significant at p <.01.Correlations above the diagonal are within-person correlations with correlations r ≥ |.10| being significant at p <.05 and r ≥
Notes: Correlations below the diagonal are person-level correlations with correlations r ≥ |.09| being significant at p <.05 and r ≥ |.11| being
15 Time overworka
14 Time social activities
a
13 Time physical activities
a
12 Time household activities
11 Time low-effort activities
a
1.89
1 Gender (1 = female, 2 = male)
2.94
Mean
Variable name
Means, Standard Deviations and Correlations between the Study Variables (7= 228 persons and 641 activities)
Table 1
-
-0.11
-0.07
-0.12
-0.16
-0.05
-0.05
0.01
0.01
0.37
15
1,134
1,485
Estimate
4,097
0,099
0,056
8078,267
Note: * p < .05. ** p < .05. *** p < .05.
-2*log (lh)
Diff-2*log
Df
Level 1 intercept variance (person)
Level 2 intercept variance (day)
Constant
Sex
Education
Income
Hours worked (a day)
Weekend
neuroticism
Time working
Time household
Time low effort
Time physical
Time social
Overwork activities x neuroticism
Household activities x neuroticism
Low-effort activities x neuroticism
Physical activities x neuroticism
Social activities x neuroticism
Null Model
SE
t
0,048
85,354
1583,479
6494,788***
6,000
0,593
0,153
1,585
0,123
Estimate
3,466
0,087
-0,037
0,264
0,008
0,092
-0,556
Model 1
SE
0,478
0,279
0,074
0,148
0,031
0,174
0,160
t
7,251
0,312
-0,500
1,784
0,258
0,529
-3,475
***
*
***
0,605
1,568
Estimate
3,453
0,094
-0,036
0,259
0,02
0,093
-0,556
-0,078
0,032
0,001
0,078
-0,057
Table 2
Multilevel Estimates for Models Predicting Recovery before Sleep (7 = 151 persons and 474 diaries)
1580,588
2,891 ns
5,000
0,154
0,122
Model 2
SE
0,480
0,280
0,074
0,149
0,034
0,116
0,161
0,088
0,049
0,037
0,104
0,061
t
7,194
0,336
-0,486
1,738
0,588
0,802
-3,453
-0,886
0,653
0,027
0,750
-0,934
***
*
***
0,635
1,477
Estimate
3,487
0,092
-0,035
0,247
0,024
0,080
-0,571
-0,216
0,03
-0,022
0,104
-0,08
0,428
0,103
0,084
-0,311
-0,109
42
1560,436
20,152**
5,000
0,155
0,115
Model 3
SE
0,482
0,282
0,074
0,149
0,034
0,172
0,161
0,101
0,048
0,037
0,104
0,059
0,164
0,049
0,053
0,181
0,083
Personality, Off-job activities and State Well-Being
t
7,234
0,326
-0,473
1,658
0,706
0,465
-3,547
-2,139
0,625
-0,595
1,000
-1,356
2,610
2,102
1,585
-1,718
-1,313
*
**
*
***
*
*
***
1,134
1,485
Estimate
4,097
0,099
0,056
8078,267
Note: * p < .05. ** p < .05. *** p < .05.
-2*log (lh)
Diff-2*log
Df
Level 1 intercept variance (person)
Level 2 intercept variance (day)
Constant
Sex
Education
Income
Hours worked (a day)
Weekend
Extraversion
Time working
Time household
Time low effort
Time physical
Time social
Overwork activities x extraversion
Household activities x extraversion
Low-effort activities x extraversion
Physical activities x extraversion
Social activities x extraversion
Null Model
SE
t
0,048
85,354
1665,333
6412,934***
6,000
0,697
0,165
1,596
0,122
Estimate
3,148
0,122
0,002
0,358
0,003
0,138
0,227
Model 1
SE
0,623
0,283
0,069
0,137
0,031
9,173
0,172
t
5,053
0,431
0,029
2,613
0,097
0,015
1,320
**
Model 2
SE
0,626
0,285
0,069
0,138
0,034
0,174
0,173
0,088
0,049
0,036
0,094
0,060
1662,243
3,090 ns
5,000
0,713
0,167
1,578
0,121
Estimate
3,122
0,134
0,002
0,35
0,012
0,143
0,229
-0,05
0,029
0,008
0,082
-0,067
Table 3
Multilevel Estimates for Models Predicting Recovery before Sleep (7 = 151 persons and 474 diaries)
t
4,987
0,470
0,029
2,536
0,353
0,822
1,324
-0,568
0,592
0,222
0,872
-1,117
**
***
1653,533
8,710 ns
5,000
0,748
0,169
1,530
0,118
Estimate
3,094
0,158
0,004
0,340
0,016
0,116
0,230
1,442
0,494
0,135
0,003
-0,251
-0,459
-0,133
-0,039
0,02
0,047
43
Model 3
SE
0,632
0,288
0,070
0,139
0,034
0,173
0,174
0,791
0,231
0,233
0,657
0,354
0,242
0,063
0,069
0,187
0,097
Personality, Off-job activities and State Well-Being
t
4,896
0,549
0,057
2,446
0,471
0,671
1,322
1,823
2,139
0,579
0,005
-0,709
-1,897
-2,111
-0,565
0,107
0,485
*
*
*
*
**
1,618
0,820
0,079
0,029
11123,472
Estimate
6,560
Note: * p < .05. ** p < .05. *** p < .05.
-2*log (lh)
Diff-2*log
Df
Level 1 intercept variance (person)
Level 2 intercept variance (day)
Constant
Sex
Education
Income
Hours worked
Weekend
neuroticism
time working
time household
time low effort
time physical
time social
Time overwork x neuroticism
time household x neuroticism
time low effort x neuroticism
time physical x neuroticism
time social x neuroticism
Null Model
SE
t
0,036 182,222
2042,131
9081,341***
6,000
1,005
0,146
0,962
0,066
Estimate
-0,647
-0,103
0,049
0,183
0,050
0,062
-0,647
Model 1
SE
0,133
0,262
0,058
0,123
0,021
0,125
0,133
t
-4,865
-0,393
0,845
1,488
2,381 *
0,496
-4,865 ***
Model 2
SE
t
0,256 25,488
0,263
-0,342
0,058
0,862
0,123
1,463
0,023
2,826 **
0,125
0,304
0,133
-4,865 ***
0,062
-1,194
0,034
0,706
0,025
-0,120
0,063
1,016
0,042
1,476
2036,679
5,452 ns
5,000
1,013
0,147
0,949
0,066
Estimate
6,525
-0,09
0,05
0,18
0,065
0,038
-0,647
-0,074
0,024
-0,003
0,064
0,062
Table 4
Multilevel Estimates for Models Predicting State Happiness (7 = 228 persons and 641 diaries)
2014,529
22,150***
5,000
1,057
0,148
0,895
0,062
Estimate
6,518
-0,090
0,051
0,181
0,061
0,055
-0,649
-0,085
0,018
-0,011
0,077
0,055
0,229
-0,010
0,082
-0,124
0,065
44
Model 3
SE
t
0,258
25,264
0,265
-0,340
0,059
0,864
0,124
1,460
0,023
2,652
0,123
0,447
0,134
-4,843
0,061
-1,393
0,033
0,545
0,025
-0,440
0,063
1,222
0,041
1,341
0,074
3,095
0,034
-0,294
0,036
2,278
0,098
-1,265
0,057
1,140
Personality, Off-job activities and State Well-Being
*
***
***
**
1,618
0,820
Null Model
SE
t
0,036 182,222
0,079
0,029
11123,472
Note: * p < .05. ** p < .05. *** p < .05.
-2*log (lh)
Diff-2*log
Df
Level 1 intercept variance (person)
Level 2 intercept variance (day)
Constant
Gender
Education
Income
Hours worked
Weekday
Extraversion
Time overtime work activities
Time household activities
Time low effort activities
Time physical activities
Time social activities
Time overwork x extraversion
Time household x extraversion
Time low effort x extraversion
Time physical x extraversion
Time social x extraversion
Estimate
6,560
Model 1
SE
t
0,550
8,138
0,266
-0,440
0,059
0,814
0,117
3,077
0,021
2,571
0,125
0,696
0,147
4,177
2047,987
9075,485***
6,000
1,041 0,150
0,963 0,067
Estimate
4,476
-0,117
0,048
0,360
0,054
0,087
0,614
***
***
**
Model 2
SE
t
0,551
8,076
0,660
-0,158
0,059
0,831
0,117
3,051
0,023
3,000
0,125
0,488
0,147
4,204
0,062
-1,242
0,034
0,735
0,025
-0,080
0,063
1,032
0,042
1,476
2042,324
5,663 ns
5,000
1,050
0,150
0,950
0,066
Estimate
4,45
-0,104
0,049
0,357
0,069
0,061
0,618
-0,077
0,025
-0,002
0,065
0,062
Table 5
Multilevel Estimates for Models Predicting State Happiness (7 = 228 persons and 641 diaries)
***
***
***
Model 3
SE
t
0,554
8,002
0,268
-0,373
0,059
0,847
0,118
3,034
0,023
2,957
0,123
0,797
0,148
4,182
0,481
3,200
0,160
0,438
0,157
2,032
0,062
0,710
0,246
-1,813
0,144
-3,160
0,044
-0,409
0,046
-2,130
0,133
1,654
0,068
1,912
45
2015,734
26,590***
5,000
1,097
0,151
0,887
0,061
Estimate
4,433
-0,100
0,050
0,358
0,068
0,098
0,619
1,539
0,07
0,319
0,044
-0,446
-0,455
-0,018
-0,098
0,220
0,13
Personality, Off-job activities and State Well-Being
*
*
*
*
***
*
***
***
***
**