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Is the shift in chronotype associated with an alteration in well-being?


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The study aimed to test whether a shift in chronotype (determined by mid sleep on free days) is associated with alterations in psychological well-being and sleep parameters. One hundred and seventeen undergraduates were tested in longitudinal study with 4 repeated measures. Measurements were taken during spring in three-week intervals and each measurement consisted of self-reported sleep parameters on work and free days (i.e., bedtime, sleep latency, wake time, sleep-onset, mid-sleep time, social jetlag), satisfaction with life and mood (energetic arousal, tense arousal, hedonic tone). Between-subjects analyses revealed earlier chronotypes, as compared to the later ones, showing lower tense arousal, higher energetic arousal and life satisfaction, earlier bedtime, sleep onset and offset on both work and free days, longer sleep duration and shorter sleep latency on workdays and less social jetlag. Within-subjects analyses revealed increasing photoperiod associated with a shift toward earlier chronotype, decrease in social jetlag and shortening sleep latency. The seasonal shifts toward earlier chronotype was not associated with alterations in mood or life satisfaction, but it was associated with a shift toward earlier bedtimes and longer sleep duration on workdays, decrease in sleep latency and social jetlag. Results from the within-subjects analyses were consistent with the results of between-subjects analyses regarding sleep-wake functioning, but inconsistent in psychological outcomes.
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Is the shift in chronotype associated
with an alteration in well-being?
Konrad S. Jankowskia
a Faculty of Psychology, University of Warsaw, Stawki 5/7, 00-183,
Warsaw, Poland
Accepted author version posted online: 11 Nov 2014.Published
online: 27 Nov 2014.
To cite this article: Konrad S. Jankowski (2015) Is the shift in chronotype associated
with an alteration in well-being?, Biological Rhythm Research, 46:2, 237-248, DOI:
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Downloaded by [Konrad S. Jankowski] at 12:00 12 February 2015
Is the shift in chronotype associated with an alteration in well-being?
Konrad S. Jankowski*
Faculty of Psychology, University of Warsaw, Stawki 5/7, 00-183, Warsaw, Poland
(Received 22 September 2014; accepted 31 October 2014)
The study aimed to test whether a shift in chronotype (determined by mid-sleep on
free days) is associated with alterations in psychological well-being and sleep parame-
ters. One hundred and seventeen undergraduates were tested in longitudinal study with
four repeated measures. Measurements were taken during spring in three-week inter-
vals and each measurement consisted of self-reported sleep parameters on work and
free days (i.e. bedtime, sleep latency, wake time, sleep onset, mid-sleep time, social
jetlag), satisfaction with life, and mood (energetic arousal, tense arousal, hedonic
tone). Between-subjects analyses revealed earlier chronotypes, as compared to the later
ones, showing lower tense arousal, higher energetic arousal and life satisfaction, earlier
bedtime, sleep onset and offset on both work and free days, longer sleep duration and
shorter sleep latency on workdays, and less social jetlag. Within-subjects analyses
revealed increasing photoperiod associated with a shift toward earlier chronotype,
decrease in social jetlag, and shortening sleep latency. The seasonal shift toward earlier
chronotype was not associated with alterations in mood or life satisfaction, but it was
associated with a shift toward earlier bedtimes and longer sleep duration on workdays,
decrease in sleep latency, and social jetlag. Results from the within-subjects analyses
were consistent with the results of between-subjects analyses regarding sleepwake
functioning, but inconsistent regarding psychological outcomes.
Keywords: chronotype; morningnesseveningness; sleep timing; social jetlag; mood;
life satisfaction
Among individual characteristics of circadian functioning (Putilov et al. 2010; Ogińska
2011), chronotype, also named morningnesseveningness, gained most attention of
researchers. Chronotype reects individual differences in the phase of entrainment and
is the nal outcome of intrinsic components (e.g. genes) and environmental factors (e.g.
light; Roenneberg et al. 2007). People with earlier chronotype (e.g. morning types) exhi-
bit advanced circadian phase position in a number of physiological and psychological
characteristics, as compared to later chronotypes (e.g. evening types; Adan et al. 2012).
Probably, the easiest for self-observation facet of chronotype is sleepwake rhythm,
namely sleep timing. Sleep timing on free days (precisely mid-sleep time) has been
identied as a marker of chronotype, assuming that on free days people are more likely
to express their phase of entrainment, due to less pressure of social obligations
(Roenneberg et al. 2003,2007). Thus, in late chronotypes, sleep occurs in later hours,
particularly on free days (Roenneberg et al. 2003). On the other hand, during the
workdays, evening individuals fall asleep much later than morning subjects do, but this
© 2014 Taylor & Francis
Biological Rhythm Research, 2015
Vol. 46, No. 2, 237248,
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difference shrinks (Roenneberg et al. 2003) or disappears (Korczak et al. 2008) for wak-
ing up, as during workdays, the rising time in most people is constrained by social
duties (work, school, etc.). This results in shortened sleep duration in late individuals
during workdays (Zavada et al. 2005; Korczak et al. 2008); something they try to
recover during free days by prolonging sleep (Zavada et al. 2005). However, average
weekly sleep duration seems not related to sleep timing (Roenneberg et al. 2003). Late
chronotype is also related to other phenomenon social jetlag (Wittmann et al. 2005).
Social jetlag, occurring more in evening chronotypes, conceptually represents misalign-
ment between social and biological time and is expressed as a time shift of sleep phase
between free days (biological time) and workdays (social time).
A number of studies revealed that the most central facets of psychological well-
being life satisfaction and affect (Ryff 1989)are associated with chronotype. Lower
life satisfaction has been linked to eveningness (Díaz-Morales et al. 2013) and similar
results have been observed for affect. Among various conceptualizations, a three-dimen-
sional model of mood seems to cover the widest denotation of core affective experience
(Schimmack & Grob 2000). In the framework developed by Matthews et al. (1990),
three dimensions of affect have been distinguished: energetic arousal (EA) (energetic
tired), tense arousal (TA) (nervousrelaxed), and hedonic tone (HT) (pleasantunpleas-
ant). Research on the above mood components and chronotype revealed no such time of
day when evening chronotypes exhibited more advantageous mood composition, as
compared to morning chronotypes (Adan & Guardia 1993; Jankowski & Ciarkowska
2008). On the contrary, evening people generally showed lower EA, HT, and
greater tension arousal (Jankowski 2014a)a depression-like structure of affect
(Gozdzik-Zelazny et al. 2011). Furthermore, adverse mood has been also related to
greater social jetlag (Levandovski et al. 2011).
Consequently, there is a growing interest in factors inuencing chronotype and in
the question whether these factors also inuence sleep parameters and psychological
outcomes interrelated with chronotype. Light seems to be the main environmental factor
inuencing the circadian system (Roenneberg et al. 2007), and individuals exposed to
sunlight earlier in the morning tend to be active and sleep at earlier times of day
(Borisenkov et al. 2012; Jankowski et al. 2014). The above observation was derived
from between-subjects comparisons of individuals living in different longitudes within
the same time zone, but this could also be tested in within-subjects research. Namely,
seasonal variability in sleep timing can be observed, as seasonal alteration in
photoperiod is linked to alteration in the timing of sunrise.
In a prospective study of ten Japanese participants (Honma et al. 1992), the earliest
sleep timing was observed in the summer, the latest in the winter, and intermediate in
the spring and autumn. Moreover, the seasonal difference was more pronounced for
sleep offset than sleep onset. In a between-subjects comparison, mean sleep onset
latency exceeding 30 min was more prevalent in winter than summer in southern
Norway, whereas in northern Norway, sleep onset latency exceeding 30 min was less
prevalent in winter than summer (Pallesen et al. 2001). In another study (Nixon et al.
2008), sleep duration in seven-year-old children from New Zealand was shorter in the
summer compared to the winter, autumn, and spring, whereas in Iceland, sleep duration
was shorter in the spring than in the winter in preschool children, but not in older indi-
viduals (Thorleifsdottir et al. 2002); however, there is also indication of lack of seasonal
variation in sleep (Park et al. 2007). Friborg et al. (2012) have shown seasonality of
sleep dependent on latitude. Namely, in Tromsø (69
N), sleep was altered in winter as
compared to summer, but not in Accra (5
N); in Norwegian university, students sleep
238 K.S. Jankowski
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timing (only during workdays) was earlier and sleep latency was shorter (both for work-
days and weekend) in summer than it was in winter. Thus, in more central latitudes,
where there is less variation in photoperiod and consequently in time of sunrise, sleep
timing seems stable.
Seasonal variations also occur in moods, dependent on latitude. For example, indi-
viduals exhibited more depressive symptoms during the winter (when compared to the
summer months) (Park et al. 2007), in a city placed more to the north (Rochester
N), but not in the south (San Diego 32
N), where no summer to winter difference in
depression was observed. Comparison of sites more distant in latitude has shown that in
winter, as compared to summer, greater levels of depression and no difference in anxiety
were observed in Norwegian students and no seasonal alteration in affect among
Ghanaians (Friborg et al. 2012). Such lowering of mood in greater latitudes during
winter, in a clinical form known as seasonal affective disorder, has gained much
attention; however, it should be noted that other forms of mood seasonality (e.g.
summer depression) are existent, but to a lesser extent (Murray 2006). Interestingly,
peak of suicides generally occurs in late spring (Christodoulou et al. 2012), but other
seasonal effects in suicidality have been also reported (Aydin et al. 2013).
To sum up, relationships between chronotype or sleep timing and psychological out-
comes or other sleep parameters have resulted mostly from between-subjects compari-
sons; it is often assumed that on the individual level, a shift toward earlier sleep hours
alters these psychological and sleep characteristics. However, such supposition has yet
to be extensively veried. Longitudinal research on sleep timing and mood has shown
their dependence on photoperiod, however, whether or not alteration in sleep timing
itself is related to change in psychological outcomes and other sleep parameters have
not been tested. Namely, observations that in longer photoperiods, individuals sleep in
earlier hours and are less depressive do not imply existence of a link between shift in
sleep timing and shift in mood it is not known whether mood improves only in those
subjects who shifted toward earlier sleep hours or mood improves in longer photoperi-
ods regardless of shift in sleep timing.
The main aim of the present research is to test whether a shift in chronotype (deter-
mined by mid-sleep time on free days) and social jetlag is associated with alterations in
psychological well-being and sleep parameters. Specically, it is hypothesized that a
shift toward earlier chronotype and less social jetlag is accompanied by a shift toward
greater well-being, while a shift toward later chronotype and more social jetlag is
accompanied by a shift toward lower well-being, as such changes could be implied from
between-subjects comparisons. Thus, the present research tests state-like (e.g. environ-
mentally or light dependent) alterations in chronotype. These within-subjects relation-
ships are further supplemented with between-subjects associations to nd out whether or
not both analyses provide concordant results, and conclusions derived from
between-subjects relationships could be translated into within-subjects recommendations.
Furthermore, this study aims to test whether longitudinal increase in photoperiod is
accompanied by a shift toward earlier sleep times, decrease of social jetlag, alteration of
other sleep parameters, and psychological well-being into more advantageous.
Self-reported actual sleep parameters were measured based on the method proposed by
Roenneberg et al. (2003). It allows for quantication of sleepwake parameters with a
Biological Rhythm Research 239
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single administration of a questionnaire that takes about three minutes and shows good
concordance with sleep diaries (Roenneberg et al. 2003; Jankowski 2014b). Such a par-
adigm allows for repeated measurements without a need to use sleep diaries or actigra-
phy, which would make multiple repeated measures hard to accomplish (e.g. overload
of participants with sleep diaries or high costs of over a hundred actigraphs). The ques-
tionnaire consisted of questions referring to the most current living conditions and asked
about self-reported bedtime, time needed to fall asleep and wake-up time (sleep offset),
separately for work and free days, and the number of free days during a week. Based
on the above variables, secondary measures were calculated: sleep onset (bed-
time + sleep latency), mid-sleep time (half way between sleep onset and wake-up time)
and sleep duration; these variables were calculated separately for free and workdays.
Mid-sleep time on free days (MSF) was also calculated via a formula correcting for
sleep need (MSFsc; Roenneberg et al. 2007). MSF and MSFsc are considered to be
indicators of chronotype, as during free days, individuals are assumed to express their
phase of entrainment, as main obstacles, like social obligations (work, school, etc.) are
absent during free days. Consequently, in the present paper whenever the term chrono-
typeappears, it refers to mid-sleep on free days, unless otherwise specied. Moreover,
mean weekly sleep duration and social jetlag were calculated. Social jetlag is the differ-
ence between MSF and mid-sleep time on workdays (MSW) and shows misalignment
of biological (MSF) and social time (MSW) the greater the value, the greater the
misalignment (Wittmann et al. 2005).
Satisfaction with life was measured using the Polish translation of the Satisfaction
with Life Scale (SWLS) (Diener et al. 1985), which consists of ve items scored with a
seven-point Likert-type response format. The Polish translation of SWLS was conducted
by the author of this manuscript using parallel blind technique (Behling & Law 2000).
SWLS measures global cognitive judgments of satisfaction with ones life, and its lower
scores indicate lower satisfaction with life. The internal consistency of the SWLS
assessed by Cronbachsαwas high in the present sample: .86. Testretest reliability in
the present sample was: .85.93 (three-week intervals); .87.88 (six-week intervals); and
.86 (nine-week interval).
Mood was assessed with the UWIST Mood Adjective Check List (UMACL) devel-
oped by Matthews et al. (1990) in the Polish adaptation provided by Goryńska (2005).
The scale has 29 items scored with a four-point Likert-type response format and is
divided into three subscales measuring: EA (with poles: energetictired, 10 items); TA
(nervousrelaxed, nine items); and HT (pleasantunpleasant, 10 items). Higher scores
indicate greater levels of each mood domain. Internal consistency for each subscale, as
indicated by Cronbachsα, was high in the present sample (.88 for each scale).
Morningnesseveningness preference was assessed for descriptive purposes and for
between-subjects comparisons, using the Polish version of the reduced Morningness
Eveningness Questionnaire (Jankowski 2013). The scale has 4 items scored with 4 or 5
response options. Internal consistency for the scale, as indicated by Cronbachsα, was
high both in previous work (.73; Jankowski 2013) and in this study (.81). Testretest
reliability with one-week interval in the present sample was .90.
Participants and procedure
The participants were 117 psychology students (101 females) aged between 19 and 31
(M= 22.2, SD = 1.9) from two universities situated in Warsaw (51
N). Subjects were
tested anonymously between 10:00 in the morning and 18:00 in the afternoon in groups
240 K.S. Jankowski
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of 15 in classrooms just before beginning the classes, and each subject was tested at the
same time of a day across all measurements. According to the cutoff scores based on a
morningnesseveningness scores distribution in a student population (Jankowski 2013),
the present sample consisted of 21% morning types, 51% neither types, and 28% even-
ing types. There were four measurements taken from the beginning of April (a week
after a shift into summer time) to the beginning of June in three-week intervals. Each
measure consisted of self-reported sleep parameters, satisfaction with life, and mood.
Sixty-ve individuals participated in all 4 measurements, 42 in 3 measurements, 5 in 2
measurements, and 5 in 1 measurement. Subjects who accomplished only one measure-
ment (5 females) were not considered in within-subjects analyses.
Statistical analyses were conducted using SPSS 21 software. At rst, Pearson corre-
lations were calculated between rMEQ scores, MSF, MSFsc, social jetlag, and the
remaining variables. This analysis aimed to replicate previous ndings; thus, all vari-
ables were averaged across all repeated measurements at rst, and rcoefcients at
p< .05 one-tailed were considered statistically signicant. The above analyses were also
conducted to establish reference rvalues for the succeeding analyses of within-subjects
relationships. Within-subjects relationships were studied using regression models for
repeated measures as proposed by Bland and Altman (1995). This method allows for
revealing bivariate relationships and might be viewed as equivalent of Pearson correla-
tion for within-subjects associations. Here, in the regression models, single predictors
were photoperiod, MSF, MSFsc, or social jetlag, and outcomes were the remaining vari-
ables. Reported are standardized coefcients (beta here equivalence of Pearson rcoef-
cient, as requals beta from regression with a single predictor) to check for strength of
pairwise relationships and unstandardized coefcients (B) to show how an increase of
one hour in a given predictor alters dependent variables (in raw scores for psychological
outcomes or in minutes for sleep related variables). Within-subjects relationships were
studied to test the main research question. Coefcients at p< .05 two-tailed were
considered statistically signicant.
Between-subjects relationships
Analyses of between-subjects relationships, as indicated by rPearson correlations,
revealed that morningness preference (rMEQ) and sleep timing on free days (MSF,
MSFsc) were highly intercorrelated. Individuals with greater morningness preference or
earlier sleep times on free days had lower TA and greater EA, but morningness and
sleep timing on free days were unrelated to HT (Table 1). Furthermore, individuals suf-
fering greater social jetlag were higher on TA. Subjects with earlier sleep times on free
days were more satised with their lives (SWLS), but morningness preference and
social jetlag turned out to be unrelated to life satisfaction.
As for sleep variables, morningness and sleep timing on free days showed consistent
relationships with bedtime, sleep onset, and sleep offset. Namely, individuals higher on
morningness were earlier going to bed, falling asleep, and waking up both on workdays
and free days. Moreover, individuals with earlier MSF and MSFsc needed less time to
fall asleep on workdays. Individuals with earlier MSF had longer sleep on workdays,
and individuals with greater morning preference had shorter sleep on free days. Individ-
uals higher on morningness and sleep timing on free days also had earlier mid-sleep on
workdays (MSW) and experienced less social jetlag.
Biological Rhythm Research 241
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Social jetlag itself was also related to a number of sleep variables. Individuals suf-
fering greater jetlag were, on workdays, falling asleep later but waking up earlier, thus
their sleep duration was shorter. On free days, individuals higher on social jetlag were
waking up later, going to bed, and falling asleep later, thus, having shorter sleep latency.
Subjects with greater social jetlag had shorter mean sleep duration across a week.
Within-subjects relationships
Descriptive statistics for four measurements are presented in Table 2, but averaged
levels are not compared using statistic test due to missing measurements (see
participants and procedure). Thus, within-subjects regressions, which handle missing
data, are further used.
Within-subjects regressions revealed that increasing photoperiod resulted in a shift
toward earlier sleep timing in the studied sample (Table 3). Namely, every one-hour
increase in photoperiod resulted in an earlier MSF of 5.73 min and an earlier MSFsc of
5.54 min. Further, a one-hour increase in photoperiod produced 6.62 min less social
jetlag, almost one minute shorter sleep latency on both work and free days, and an ear-
lier bedtime, sleep onset, and offset on free days. Interestingly, increment in photoperiod
also resulted in lowering of HT and heightening TA. However, when the fourth (June)
measurement was removed from the analyses, effects of photoperiod on mood were
absent, while its effects on sleep remained unchanged. This removal of the June mea-
sure was done only for a test and all the analyses included the June measurement, and
Table 1. Correlation coefcients between studied variables averaged across all measurements
(between-subjects analyses).
rMEQ MSF MSFsc Social jetlag
HT .10 .14 .11 .15
TA .24** .19* .17* .18*
EA .18* .18* .18* .15
SWLS .05 .24** .24** .11
Bedtime W .52*** .74*** .70*** .15
Sleep latency W .15 .20* .19* .04
Sleep onset W .54*** .76*** .71*** .16*
Sleep offset W .45*** .50*** .64*** .24**
Sleep duration W .07 .23** .05 .38***
Bedtime F .57*** .91*** .91*** .58***
Sleep latency F .04 .01 .01 .18*
Sleep onset F .58*** .92*** .92*** .56***
Sleep offset F .72*** .93*** .83*** .63***
Sleep duration F .25** .12 .02 .15
Mean sleep duration .01 .15 .02 .26**
MSW .57*** .73*** .78*** .05
Social jetlag .38*** .65*** .50***
MSFsc .61*** .94***
MSF .70***
Note: rMEQ morningness preference, MSF mid-sleep on free days, MSFsc mid-sleep on free days
corrected for sleep need, MSW mid-sleep on workdays, HT hedonic tone, TA tense arousal, EA
energetic arousal, SWLS life satisfaction, F free days, W workdays.
*p < .05; **p < .01; ***p < .001.
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Table 2. Means (standard error) of the studied variables at the four measurements.
Photoperiod 12:54 (00:00) 14:31 (00:00) 15:33 (00:00) 16:29 (00:00)
MSF 05:27 (00:07) 05:28 (00:07) 05:11 (00:06) 05:14 (00:07)
MSFsc 04:20 (00:07) 04:25 (00:07) 04:13 (00:06) 04:12 (00:07)
MSW 03:38 (00:05) 03:40 (00:05) 03:36 (00:05) 03:45 (00:04)
Social jetlag 01:49 (00:05) 01:47 (00:05) 01:34 (00:05) 01:28 (00:05)
HT 30.14 (.58) 29.40 (.67) 30.21 (.64) 29.02 (.69)
TA 16.55 (.56) 17.33 (.61) 17.15 (.57) 17.98 (.59)
EA 27.50 (.75) 28.35 (.64) 28.72 (.68) 27.28 (.72)
SWLS 22.83 (.60) 22.54 (.62) 23.13 (.67) 22.95 (.72)
Bedtime W 23:40 (00:06) 23:46 (00:06) 23:39 (00:06) 23:51 (00:05)
Sleep latency W 19.40 (1.53) 16.72 (1.05) 15.43 (.93) 14.94 (1.00)
Sleep onset W 00:00 (00:06) 00:02 (00:06) 23:53 (00:06) 00:05 (00:05)
Sleep offset W 07:17 (00:07) 07:19 (00:06) 07:20 (00:07) 07:26 (00:06)
Sleep duration W 07:18 (00:08) 07:17 (00:07) 07:28 (00:07) 07:20 (00:07)
Bedtime F 00:43 (00:08) 00:49 (00:07) 00:31 (00:06) 00:36 (00:07)
Sleep latency F 17.31 (1.39) 15.52 (.87) 15:33 (.91) 13:90 (.93)
Sleep onset F 01:01 (00:07) 01:04 (00:07) 00:46 (00:06) 00:50 (00:07)
Sleep offset F 09:54 (00:08) 09:51 (00:08) 09:35 (00:08) 09:39 (00:09)
Sleep duration F 8:53 (00:07) 08:46 (00:07) 08:48 (00:06) 08:48 (00:07)
Mean sleep duration 07:46 (00:07) 07:46 (00:06) 07:53 (00:06) 07:48 (00:06)
Note: MSF mid-sleep on free days, MSFsc mid-sleep on free days corrected for sleep need, MSW mid-
sleep on workdays, HT hedonic tone, TA tense arousal, EA energetic arousal, SWLS life satisfaction,
Ffree days, W workdays.
Table 3. Results of within-subjects regression analyses. Values in front of brackets show
standardized coefcients. Values in brackets show alteration of a dependent variable (rows) in raw
scores (for psychological outcomes) and minutes (for remaining variables) if a predictor (columns)
increases for 1 h.
Photoperiod MSF MSFsc Social jetlag
HT .12 (.36)* .09 (.75) .06 (.44) .06 (.48)
TA .18 (.42)** .00 (.04) .02 (.18) .02 (.16)
EA .06 (.17) .04 (.31) .02 (.15) .07 (.54)
SWLS .04 (.06) .01 (.05) .06 (.22) .05 (.17)
Bedtime W .08 (1.26) .20 (9.44)*** .02 (.89) .19 (8.06)**
Sleep latency W .21 (.90)*** .15 (1.94)* .09 (.97) .07 (.85)
Sleep onset W .03 (.53) .23 (11.01)*** .04 (1.83) .17 (7.64)**
Sleep offset W .06 (1.25) .02 (1.11) .31 (16.27)*** .45 (24.71)***
Sleep duration W .03 (.72) .13 (9.89)* .22 (14.44)** .25 (17.08)***
Bedtime F .20 (5.23)*** .76 (57.80)*** .88 (57.83)*** .58 (39.50)***
Sleep latency F .20 (.81)*** .12 (1.44)* .12 (1.25)* .07 (.79)
Sleep onset F .23 (6.00)*** .77 (59.57)**** .89 (59.30)*** .58 (40.39)***
Sleep offset F .21 (5.46)*** .78 (60.43)*** .37 (24.52)*** .67 (47.27)***
Sleep duration F .02 (.54) .01 (0.86) .41 (34.79)*** .08 (6.87)
Mean sleep
.05 (1.13) .10 (6.98) .02 (1.39) .15 (9.42)*
MSW .07 (.89) .15 (6.06)** .27 (9.05)*** .45 (16.17)***
Social jetlag .30 (6.62)*** .81 (53.94)*** .57 (32.87)***
MSFsc .24 (5.54)*** .81 (56.15)***
MSF .28 (5.73)***
Note: MSF mid-sleep on free days, MSFsc mid-sleep on free days corrected for sleep need, MSW mid-
sleep on workdays, HT hedonic tone, TA tense arousal, EA energetic arousal, SWLS life satisfaction,
Ffree days, W workdays.
*p < .05; **p < .01; ***p < .001.
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all the results and conclusions are based on all available data (including the fourth
measurement). The reason for testing what would happen if the June measurement was
discarded is addressed in the discussion. It should be noted that the strength of relation-
ship between photoperiod and MSF was of .28, what means that about 8% of variabil-
ity in MSF was explained by changes in photoperiod, and a number of other factors
could affect shifts in MSF.
A shift in sleep timing on free days or in social jetlag was not associated with alter-
ation in either mood or life satisfaction. Alterations in mood and life satisfaction were
also unrelated to change in any other sleep variables, for example, sleep duration (these
results are omitted in the tables as their analyses were not the main aim of this study).
Regarding sleep variables, a shift toward earlier sleep timing on free days, as indicated
by earlier MSF, was linked with a shift toward earlier bedtime, sleep onset, and shorter
sleep latency on both work and free days. Sleep offset on workdays was unrelated to
MSF. Further, an hour shift toward earlier MSF resulted in 9.89 min longer sleep on
workdays, 6.06 min earlier mid-sleep on workdays, and a reduction of social jetlag by
53.94 min.
A shift in MSFsc, although highly correlated with the timing of MSF, was, in some
aspects, differently related to sleep variables and similarly in others, as compared to
MSF. Namely, an earlier MSFsc was unrelated to bedtime, sleep onset and latency on
workdays, while it was linked to an earlier sleep offset on workdays. Further, unlike
MSF, earlier MSFsc was associated with shorter sleep duration on workdays and longer
sleep duration on free days. Relationships between MSFsc and other variables were sim-
ilar to those for MSF.
Decrease in social jetlag was related to later bedtime, sleep onset and sleep offset on
workdays and to earlier bedtime, sleep onset and sleep offset on free days. Thus, reduc-
tion of social jetlag was associated with a shift toward later mid-sleep on workdays and
earlier mid-sleep on free days, however, still, sleep timing on workdays remained earlier
than that on free days (reduction in social jetlag meant more similar sleep timing across
all week). Further, an hour reduction in social jetlag was linked to a 17.08 min increase
in sleep duration on workdays, which resulted in a 9.42 min increase in weekly mean
sleep duration.
The present research aimed to test whether conclusions that earlier chronotypes, as com-
pared to the later ones, present more advantageous sleepwake rhythm and well-being,
could be conrmed by observations that a shift in chronotype is related to a change in
well-being and alterations in sleepwake functioning.
Results of between-subjects relationships showed indeed, that earlier chronotypes, as
compared to later ones, exhibit lower TA, higher EA and higher life satisfaction. These
results are concordant with previous ndings regarding mood (Adan & Guardia 1993;
Jankowski & Ciarkowska 2008; Jankowski 2014a), life satisfaction (Díaz-Morales et al.
2013), and other indicators of well-being (Haraszti et al. 2014), and provide deepened
insight, showing that individual differences in chronotype indicated by MSF and MSFsc
are related to better mood and higher life satisfaction. This provides evidence that indi-
vidual differences in chronotype might be important for individual levels of TA, EA and
life satisfaction the observation also resembling the previous one regarding depressive-
ness (Levandovski et al. 2011). Further, individuals with greater social jetlag showed
greater TA; this is coherent with a study showing greater social jetlag related to
244 K.S. Jankowski
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depressiveness (Levandovski et al. 2011). However, relationships of social jetlag with
other mood components and life satisfaction were statistically non-signicant presum-
ably because of insufcient sample size, as the study was designed primarily for within-
subjects analyses. Furthermore, the between-subjects relationships replicated previous
ndings showing later chronotype related to greater social jetlag, later bedtimes, and
sleep onsets and offsets both on free days and workdays (Roenneberg et al. 2003;
Zavada et al. 2005; Korczak et al. 2008). Moreover, in the present study, later chrono-
type, as indicated by MSF, was also related to longer sleep latency and shorter sleep
duration on workdays the former relationship presumably can be ascribed to too early
timing of sleep on workdays as compared to the internal time.
Within-subjects analyses showed that, during the spring, increasing photoperiod was
related to a shift toward earlier chronotype (MSF and MSFsc). As sleep timing on
workdays was not related to photoperiod, it could be concluded that on workdays indi-
viduals mainly follow social time, while on free days individuals are allowed to be cou-
pled to sun time a relationship previously suggested in between-subjects analyses
(Borisenkov et al. 2012; Jankowski et al. 2014). Moreover, the present results showed
sleep latency, both on free and workdays, and social jetlag decreasing with increasing
photoperiod, suggesting that longer daylight has a positive effect on the speed of falling
asleep and harmony between internal and social time.
The present results of within-subjects analyses showed that a shift toward earlier
chronotype, as indicated by MSF, was related to advantageous alteration in sleepwake
functioning, whereas a shift toward later chronotype was related to disadvantageous
alterations in sleep. Namely, when individuals shifted toward earlier chronotype, not
only did their sleep timing on workdays become earlier, but also, their sleep latency on
workdays and free days decreased; in addition, sleep duration on workdays increased
and social jetlag diminished. Interestingly, some discrepancy between the results based
on MSF and MSFsc could be observed, which suggests that the correction formula used
to calculate MSFsc advances MSF beyond the physiological meaningfulness. Namely,
the results obtained using MSFsc showing that people shifting toward earlier chronotype
also start to sleep less on workdays and sleep more on free days, are counterintuitive
(these are like for evening chronotypes) and against conclusions derived from between-
subjects analyses (Zavada et al. 2005; Korczak et al. 2008). The correction formula for
sleep debt applied to the MSFsc indicator (Roenneberg et al. 2007) assumes that on free
days people, in a linear manner, catch up the exact number of hours of sleep lost during
workdays, by recovery oversleeping. This, however, seems not be the mechanism, as
people recover from sleep debt by prolonging their sleep only to some extent (much less
than the number of hours of sleep loss) due to increased sleep efciency of recovery
sleep (Herscovitch & Broughton 1981; Van Dongen et al. 2003; Alhola & Polo-Kantola
Confronting the results of within-subjects relationships with between-subjects associ-
ations it can be concluded that the two provide similar results regarding sleep. However,
a shift in chronotype was not accompanied by an alteration in mood or life satisfaction,
despite the observation that these psychological outcomes were more favorable in more
morning oriented subjects than in the evening ones. This suggests that disadvantageous
mood and lower life satisfaction are intrinsic components of late chronotype, with a
common trait-like underpinnings, for example, genes (Mansour et al. 2006) or tempera-
ment (Jankowski 2014a). On the other hand, state-like components of chronotype, for
instance, the environmentally or light-dependent ones, seem to be unrelated to
well-being conclusion corresponding to the results showing that residents of Western
Biological Rhythm Research 245
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localization within a time zone do not exhibit more depressive symptoms than those
living on the east (differences in sun time), despite they show later sleep timing
(Jankowski et al. 2014). Nevertheless, it should be noted that externally evoked altera-
tions in sleep timing may evoke changes in well-being in some circumstances. For
instance, changing school start times into later ones was shown to decrease depressive
symptoms in high school students (Wahistrom 2002). Thus, when analyzing effects of
alterations in sleep times, it seems important to consider whether change in sleep times
refer to free or workdays and the origin of the change (e.g. spontaneous, induced by
sunlight vs. imposed by the authorities).
Interestingly, increasing photoperiod was related to a shift toward higher TA and
lower HT an association that disappeared when, only for the test, the last (June) mea-
surement was excluded from the analyses. This implicates two interpretations. First, lati-
tudes distant from the equator have a high variability in day length, with highly
increasing photoperiods during spring, believed to cause irritability and consequently
peak of suicides in late spring (Christodoulou et al. 2012). Second, in the student sam-
ple studied here, the last measurement was taken near the end of semester when antici-
pation of an examination session could have affected their mood. Thus, the study period
and sample specicity are the main limitations of the present research, and the presented
results require further replications in different study designs. It should be tested whether
or not a shift in chronotype within other seasons or between seasons is also unrelated to
alteration in well-being. It could be also asked whether the presented results occur in
other populations (e.g. workers, students from lower levels of the education system) or
when alterations in chronotype are evoked by experimentally controlled manipulations
instead of spontaneous drifts partly associated with the seasonal shifts in photoperiod.
Moreover, in the studied sample, males were underrepresented to the extent that gender
differences could not be addressed. Considering that gender is known to affect individ-
ual preferences in circadian functioning (Putilov et al. 2008), the presented results might
represent effects most likely to occur in females and further studies with more male
participants should be carried out.
Nevertheless, the present study is the rst showing that recommendations regarding
psychological outcomes derived from comparisons of individuals differing in chronotype
might not be transferable into individual level recommendations. Namely, it exhibited
that a shift in chronotype was not accompanied by alterations in mood or life satisfac-
tion. Such a result is of great concern as it gives direction to further studies to consider
intrinsic underpinnings of chronotype in relationship to well-being, rather than environ-
mentally dependent components of circadian phase position.
The study was supported by a grant [grant number 2011/03/D/HS6/05760] from the National
Science Centre (Poland).
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... Chronotype is a relatively stable construct (Broms et al. 2014;Druiven et al. 2020); however, it may shift over time. One of the observable fluctuations is seasonal changes, wherein the summer months' wake times are earlier, and sleep duration decreases, compared to winter months (Jankowski 2015a;Mattingly et al. 2021). Such seasonal fluctuations can also be observed in depressive symptoms, and these are associated with alterations in the timing and duration of sleep (Wirz-Justice 2008). ...
... In the present study, we attempted to test the hypotheses regarding the moderating effects of two personality traits -conscientiousness and neuroticism -on the magnitude of seasonal covariance between morningness-eveningness and depressive symptoms. As expected, and consistent with previous studies (Harmatz et al. 2000;Jankowski 2015a), our results showed that there was a significant seasonal lowering in depressive symptoms and a shift towards morningness from winter to summer. Moreover, a greater decrease in depressive symptoms was observed in individuals that experienced a greater shift towards morningness. ...
... It needs to be stressed, however, that SAD is not a standalone clinical diagnosis, but rather a specifier for depressive disorders, and prevalence reports can be biased due to inadequate validity of commonly used self-report methods (Hansen et al. 2008). Seasonal alterations in exposure to sunlight are considered to be an environmental agent exerting impact on seasonal changes in depressive symptomatology as well as chronotype (Jankowski 2015a;Levitan 2007). In the northern hemisphere, which was the venue for our study, the shortest and longest photoperiods occurred in December and June, respectively, which were our sampling periods. ...
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Recent research provided evidence that the well-established association between morningness-eveningness and depressive symptoms may be moderated by personality features – conscientiousness and neuroticism. In the present study, we attempted to broaden these findings using a longitudinal design. We hypothesized that these personality traits may influence the degree to which morningness-eveningness and depressiveness covary in time. Participants (n = 380) filled measures of morningness-eveningness, the Big Five personality, and depressive symptoms twice, in December and in June. Consistent with previous results, we observed a significant seasonal shift towards morningness and lower depressive symptoms from December to June. Seasonal shifts in chronotype and depressive symptoms were interrelated: a seasonal shift towards morningness was associated with a decrease in depressive symptoms. The strength of this association was exaggerated by neuroticism but attenuated by conscientiousness, suggesting that among neurotic individuals seasonal changes in depressive symptomatology are more dependent on seasonal shifts in morningness-eveningness but less dependent among conscientious ones. This result suggests that conscientiousness and emotional stability play a protective role against maladaptive consequences of eveningness.
... A large number of studies have shown a greater incidence of mental health problems and mood disorders among evening-types compared to morning-types and intermediate-types (Taylor & Hasler, 2018). For instance, eveningness is reported to be associated with an inclination toward a higher level of negative moods, such as anger (Jankowski & Linke, 2020), confusion (Gobin, Banks, Fins, & Tartar, 2015), depressiveness (Van den Berg, Kivelä, & Antypa, 2018), fatigue (Merikanto et al., 2021), and tension (Gobin et al., 2015), as well as poor well-being (Jankowski, 2014;Merikanto et al., 2021). ...
... Chronotype was calculated as midsleep on free days sleep-corrected (MSFsc; Roenneberg, Wirz-Justice, & Merrow, 2003) for the period before the COVID-19 suspension, and using midsleep across the week for the period during the COVID-19 suspension, as there were no work schedulerelated changes in sleep across the week (i.e., no social jetlag). Shift in chronotype (Jankowski, 2014) was determined by subtracting the 'during COVID-19 midsleep time' from the 'before COVID-19 MSFsc'. Shift in chronotype shows the amount and direction of change in midsleep time, expressed in hours and minutes. ...
... There was not much research on shifts in sleep timing in naturalistic conditions. One such study, conducted in a setting different from the COVID-19 stay-at-home condition, did not find changes in mood and well-being despite apparent shifts in chronotype evoked by seasonal changes in the photoperiod (Jankowski, 2014). ...
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It is suggested that social obligations, such as early work/school starts, have a disadvantageous impact on sleep behavior that can further transfer to mental health problems. Lockdown as a result of the COVID-19 pandemic created a unique opportunity to research human sleep-wake behavior in naturalistic conditions of decreased social obligations. This study aimed to test whether a change in habitual sleep-wake timing (shift in chronotype) during the COVID-19 lockdown impacted mood and well-being, and whether the impact differs according to morningness-eveningness preference. University students (N = 1011; Meanage = 21.95 ± 1.95 years) filled out self-report questionnaires containing measures of chronotype (midpoint of sleep) before and during the COVID-19 lockdown, morningness-eveningness preference, mood, and well-being. The impact of morningness-eveningness preference and shift in chronotype was tested via multiple regression analyses. Results showed that participants shifted their chronotype in line with their morningness-eveningness preference, and that shift toward earlier sleep-wake timing was related to better moods and well-being. Moreover, higher levels of positive mood (vigor) and well-being were found in individuals who shifted their sleep-wake timing earlier and were higher on morningness.
... The questionnaire is designed for adults (both healthy and ill ones). It is a useful instrument for measuring life satisfaction per se [24]. Cronbach's (α) reliability analysis was used in order to verify the internal consistency of the questionnaire: the reliability of the tool was assessed as α = 0.872, which is a satisfactory level of reliability; 3. ...
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Background: COVID-19 pandemic has struck all of us suddenly and unexpectedly; it deprived the society of a sense of control over their lives on different levels. In a short period of time, it led to a number of changes in everyday life of people all over the world. In particular, these changes affected medical staff, who, all of a sudden, were burdened with new work-related responsibilities and duties. This situation may have had a detrimental effect on their mental health. Due to the unpredictability of the COVID-19 pandemic, we attempted to assess its consequences in terms of mental health and physical fitness of university students from countries in which different approaches to these issues were adopted. Methods: A total of 779 medical students (374 students from John Paul II University of Applied Sciences (ABNS) in Biala Podlaska, Poland, and 405 students from Yanka Kupala State University of Grodno (YKSUG), Belarus) took part in the survey. Three standardised psychometric tools were used in the study: The Satisfaction With Life Scale (SWLS), The General Health Questionnaire (GHQ-28) and Stress Coping Inventory (Mini-COPE). In addition, the International Physical Activity Questionnaire (IPAQ) was applied. Results: The vast majority of students both from Poland and Belarus demonstrated high levels of physical activity. However, students from ABNS manifested significantly higher levels of physical activity compared to their counterparts from YKSUG. Students from Biala Podlaska had greater satisfaction with life during the COVID-19 pandemic, whereas their peers from Grodno exhibited higher levels of mental distress. Conclusion: The COVID-19 pandemic resulted in a significant exacerbation of mental health issues among medical students. In order to alleviate negative effects of the pandemic, it seems necessary for universities to monitor the physical and mental health state of students and to implement prevention programmes.
... Eight found significant results for other variables: engagement [69,113] and achievement [69], prosociality [92], optimism [113], 'should' conflicts [107], marijuana use [110], and sleep [116,117]. Finally, four studies in the Self domain did not find any significant results for prospective wellbeing [106,111,112,115]. Figure 4 shows the semipartial correlations of study variables from the Relationships domain which were significantly associated with T2 wellbeing after controlling for T1 wellbeing. ...
Background and objectives: Wellbeing among university students is associated with better academic outcomes and diminished harm from mental illness. This study systematically reviews and meta-analyses longitudinal studies of the antecedents and consequences of wellbeing within this population, providing an overview which establishes a ‘natural history’ of wellbeing to form a background for intervention and policy. Method: This study was a systematic review and meta-analysis of the peer-reviewed literature, based on a broad range of search terms across four journal databases in psychology, medicine and education. Studies were organised by the domain of their study variables (i.e., Self, Relationships, or Institutional Context) and variables relating to wellbeing were extracted. The incremental effect of study variables measured at baseline upon prospective wellbeing was calculated with semipartial correlation coefficients which controlled for baseline wellbeing. Meta-regressions were used to examine the effect of follow-up interval on effect sizes. Results: Sixty-two longitudinal studies of university student cohorts were identified. In 57 studies, wellbeing was an outcome variable. Meta-analyses showed that effects were moderated by measurement interval between baseline and follow-up, becoming weaker with longer intervals, and that this was not an artifact of the measurement instrument. The study factors with the strongest positive effect sizes after controlling for baseline wellbeing were authenticity, self-esteem, self-support for autonomy, emotional repair, and ability to regulate distress and despondency; relationship commitment and group memberships; self-identification with the university and time pressure. Study factors with the strongest negative effect sizes were uncertainty regarding university, materialism, a belief in social complexity, depression, and stress. In five studies, wellbeing was an antecedent, showing positive associations with educational outcomes. Conclusion: This review identified several antecedents of student wellbeing which could be targeted for interventions. These included self-relationship, emotion regulation, and interventions to decrease mental illness. Universities might also make it easier to establish and maintain groups (e.g., study cohorts, interest groups). Many variables which affect wellbeing are not amenable to study with experimental methods, but their study and use in wellbeing interventions should not be neglected. Because the antecedents of wellbeing are numerous and diverse, further research in the area should take advantage of research methods which maximise the variety of data collected and minimise respondent burden, such as passively collected and linked data.
... Responses were given on a 7-point Likert scale, ranging from 1 to 7. Higher scores signify greater satisfaction with life. The psychometric properties of the Polish version of SWLS were satisfactory and there the internal consistency (assessed by Cronbach's alpha) was 0.86 [25]. The Cronbach's alpha coefficient in our study was 0.87. ...
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Ego-resiliency is a set of traits that promotes positive adaptation to life’s vicissitudes. High ego-resiliency helps in upholding one’s personality system when facing adversity and in adjusting it to new environmental demands. Our study aimed at evaluating the connections between ego-resiliency, the severity of anxiety and depressive symptoms as well as life satisfaction during the COVID-19 pandemic in Poland. A total of 604 Polish citizens aged 16 to 69 years participated in the online survey. Ego-resiliency was measured with the Ego Resiliency Scale (ER89-R12), anxiety and depression with the Hospital Anxiety and Depression Scale (HADS), and life satisfaction with the Satisfaction with Life Scale (SWLS). Statistical analyses were performed using the Spearman rank correlation coefficient. The results revealed correlations between the intensity of depressive and anxiety symptoms, life satisfaction, and the intensity of ego-resiliency. Individuals with a high level of ego-resiliency tended to experience a lower intensity of anxiety and depressive symptoms during the COVID-19 pandemic. Moreover, individuals with a high level of ego-resiliency exhibited a higher level of life satisfaction. Our conclusions might assist in better understanding the close link between levels of ego-resiliency, the occurrence of depressive and anxiety symptoms, and satisfaction with life among Polish individuals experiencing crises.
... The Satisfaction with Life Scale (SWLS) was proposed by Diener and colleagues to measure life satisfaction [52]. The Polish adaptation was carried out by Jankowski [53]. It consists of five statements with which respondents may or may not agree. ...
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Religiousness has a positive effect on the mental health of an individual and social groups in many difficult situations. In the conducted research, we wanted to check, inter alia, whether religiosity and social support are positively related to the mental health of students during the COVID-19 pandemic in Poland and Ukraine. The research was conducted at a time (August 2021) when the very contagious Delta variant was spreading over Europe, and numerous pandemic-related personal restrictions and obligations (such as using facemasks in selected places, social distancing, and obligatory self-isolation of the ill or those who had contact with the pathogen) were in force in both countries. For this purpose, a representative survey was carried out using the CAPI technique on a sample of 1000 students in Poland (50% boys and 50% girls in the age range 10–19) and 1022 in Ukraine (51% boys and 49% girls in the age range 10–18). The results of the research shows that depression measured by the PHQ-9 scale was experienced by 20% of students in Poland, and 13% in Ukrainian. Anxiety, measured with the GAD-7 scale, was experienced by 9% of the Polish and 6% of the Ukrainian students. The performed regression analysis showed that religiosity had no effect on the mental health of students. The main risk factor for mental disorders was the lack of social support.
... Sosyal saat sosyal faaliyetlerimizi içeren saattir (8,9). Bu zaman dilimi içerisinde gerçekleştirdiğimiz sosyal faaliyetler; diğer insanlarla sosyal ilişkiler kurma ve okula/işe gitme, alışveriş yapma, seyahat etme gibi gündelik işlerimizi kapsar (2,8,10). SJL, sirkadiyen saat ile sosyal saat arasındaki dengenin bozulması ile ortaya çıkan bir durumdur (5,7,(11)(12)(13). ...
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Adolescence is a period when many physiological, social, and psychological changes take place. During this period, some differences occur in the duration and timing of adolescents’ sleep. Recognized as a condition associated with the duration and timing of sleep during the week, social jetlag describes the mismatch between the social clock and the circadian clock. Social jetlag causes cardiovascular and metabolic problems and obesity and behavioral problems in adolescents. However, it negatively affects not only their physical health but also their mental health. Reflecting on this information, this review was conducted to reveal the effects of social jetlag on mental health in adolescents and to discuss the role of health professionals in its management in the light of the literature. Accordingly, the content of the study was presented under the headings of circadian rhythm, chronotype, social jetlag, adolescents and social jetlag, social jetlag and adolescent mental health, and the role of the nurse in the management of social jetlag. This review revealed that social jetlag affected the mental health of adolescents in the areas of anxiety, depression, smoking and alcohol addiction, aggression, quality of life, and menstrual symptoms and that the literature on the subject was limited.
... Satisfaction with life. Life satisfaction was assessed using the Polish adaptation (Jankowski, 2015) of the Satisfaction with Life Scale (SWLS; Diener et al., 1985). The SWLS is a unidimensional, five-item instrument measuring global cognitive judgments of satisfaction with one's life. ...
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Background and aims Some people are preoccupied with their sexual urges and fantasies and lose control over their sexual behaviors, which can cause adverse consequences for their health and well-being. One of the options available for individuals seeking treatment for compulsive sexual behavior disorder (CSBD) is a self-help group based on the twelve-step program. The main purpose of the current study was to examine the direct and indirect (through meaning in life and hope) relationships between involvement in Sexaholics Anonymous (SA) and life satisfaction. Methods The sample consisted of 80 Polish members of SA (72 men and 8 women) with a mean age of 38.96 years (SD = 10.56). The Sex Addiction Screening Test-Revised, the Meaning of Life Questionnaire, the Herth Hope Index, the Satisfaction with Life Scale, and items adapted from the Alcoholics Anonymous Involvement Scale were used to measure the study variables. Results Path analysis showed a direct positive relationship between SA involvement and life satisfaction. Moreover, the relationship between these variables was mediated by the presence of meaning in life and hope. Simultaneously, more severe symptoms of CSBD were related to lower levels of the presence of meaning in life and higher levels of the search for meaning in life, which, in turn, predicted lower levels of life satisfaction. Discussion and conclusions The results suggest that finding meaning in life and restoring hope partly underlie the relationship between SA involvement and life satisfaction.
... It consists of 5 items that are rated on a 7-point Likert-type scale from 1 = strongly disagree; to 7 = strongly agree. Jankowski [47] showed that the Polish version of the scale has adequate reliability (Cronbach's α = 0.86). ...
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We provide an initial empirical test of three conceptual models reflecting possible patterns of causality effects in the relationships between time perspective (TP), gratitude, savoring the moment, and prioritizing positivity (referred to as well-being boosters, WBBs), and mental well-being. The first one, trait-behavior model, states trait TPs increase the tendency to use specific WBBs in order to increase mental well-being. The second model, the accumulation model, proposes that a regular practice of particular WBBs fosters adaptive TPs which in turn impact well-being. The third model, the feedback loop, suggests that WBBs and positive TPs reciprocally strengthen one another and together contribute to higher mental well-being. Participants (N = 206; Mage = 30.90, SD = 8.39, 74% females) filled questionnaires measuring TPs, WBBs, and well-being twice, in a one-year interval. Using cross-lagged panel analyses we examined the direction of causation in the relationships among the variables. Past-Positive had a significant cross-lagged effect on gratitude, Present-Fatalistic had a significant effect on savoring. Both Past-Negative and Present-Fatalistic perspectives displayed significant causal effects on well-being. The results partly support the trait-behavior model. However, given that the second wave was conducted shortly after the onset of the COVID-19 pandemic, further studies are required to better understand the interplay between the studied traits.
... An example item of the SWLS is "If I could live my life over, I would change almost nothing". To address cultural validity of the SWLS in our study, we administered the original English language version in the USA (Diener et al., 1985), the Spanish language version in Spain (Atienza et al., 2000;Vazquez et al., 2013), the Polish language version in Poland (Jankowski, 2015), and the Japanese language version in Japan (Sumino, 1994). Measurement invariance was addressed by conducting pairwise CFAs for the SWLS. ...
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We assessed the cross-cultural role of Time Perspective (TP) tendencies [Past Positive (PP), Past Negative (PN), Present Hedonistic (PH), Present Fatalistic (PF), and Future (F)], the Deviation from a Balanced Time Perspective (DBTP) profile, the Deviation from a Negative Time Perspective (DNTP) profile, and mindfulness on life satisfaction (LS). The sample consisted of psychology undergraduate students (N = 867, M AGE = 20.19, SD = 3.417) in four countries: USA, Spain, Poland and Japan. We used a 17-item short version of the Zimbardo Time Perspective Inventory (ZTPI), the Mindful Attention Awareness Scale (MAAS), and the Satisfaction with Life Scale (SWLS) in all countries. For ensuring measurement invariance, we conducted pairwise CFAs for the ZTPI-17, MAAS and SWLS. Regression analyses showed that PN predicted decreased LS in Poland and Japan. PP predicted increased LS in Spain. F predicted increased LS in Poland. DNTP predicted decreased LS in Poland. Mindfulness predicted decreased LS in Japan and increased LS in USA, Spain and Poland. Moreover, mediation analyses revealed that the DBTP partially mediated the relationship between mindfulness and LS in Spain and USA. The DNTP partially mediated the relationship between mindfulness and LS in Spain, Poland and Japan (opposite direction). The findings suggest that the association of TP, mindfulness and LS differs across the investigated countries as a function of culture.
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Studies on suicide seasonality are significant, as they may assist in understanding the factors that contribute to suicidal behavior. Although some studies do not confirm the existence of seasonal variation, most of them, both from the Northern as well as the Southern hemisphere, indicate the existence of seasonal variation for suicides. The majority even converges to the fact that there is a peak of suicides during the Spring and early Summer. Seasonal variation of suicides seems to be mainly influenced by gender (male), older ages and violent methods of suicide. Apart from these parameters, there are additional ones that have been taken into consideration with a view to a more comprehensive understanding of the phenomenon of seasonality. Biological, cultural, socio-economic and bio-climatic factors are likely to be involved in the seasonal pattern for suicidal behavior. Studies on suicide seasonality are not only an important source of epidemiological data for suicides, but represent a global effort to clarify the parameters of self-destructive behavior with a view to prevention.
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Research using a refinement of existing measures of mood, the UWIST Mood Adjective Checklist (UMACL), is reviewed. A factor analysis (N = 388), using a validated criterion for assessing the number of factors to be extracted, confirmed that the UMACL measures dimensions of energetic arousal, tense arousal and hedonic tone. Psychometric properties of UMACL scales were satisfactory. Discriminant validity was established by showing that correlations between UMACL scales and demographic and personality variables were small in magnitude, though of theoretical importance. Significant correlations between the arousal scales and psychophysiological measures of autonomic arousal demonstrate concurrent validity. A series of studies shows that the UMACL scales are sensitive to external ‘stressors’. Specific influences on each of the three principal scales have been found. Certain stressors appear to evoke a more general stress syndrome associated with reduced energetic arousal and hedonic tone, and increased tense arousal.
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Morningness–eveningness describes individual preferences for activity at specified times of the day. The present research aimed to test whether sun time entrains humans and whether this effect is observable in sleep–wake timing, in the timing of social rhythm and in morningness preference. Furthermore, we tested whether different reference points (activity expressed in standard time or in sun time, morningness preference scores) provide concordant results about differences in chronotype according to longitude. University students were tested in two locations (Warsaw, Poland; Heidelberg, Germany) positioned within the same time zone but differing according to longitude, thus daylight appeared earlier in the east (Warsaw) than in the west (Heidelberg). Sampling was scheduled to obtain similar photoperiods and other environmental factors in two locations. Measures consisted of times of day when various activities occurred (e.g. going to bed, waking up, going outdoors) in the seven days prior to data collection, morningness preference, and depressiveness. Varsovians and Heidelbergers did not differ in morningness preference and depressiveness, but Varsovians, compared to Heidelbergers, undertook a number of activities (e.g. wake up, get up, having breakfast, first contact with another person and going outdoors) at an earlier clock time (21–38 min earlier, depending on activity), did not differ in starting and finishing classes/work, and were later in eating lunch and dinner. However, all the activities of Varsovians (except for going outdoors) were positioned later according to sun time reference. Thus, residents from east as compared to those from the west had similar morningness preference, were more morning positioned in many aspects according to standard time, but were later according to sun time. Results indicated university students entrained to sun time to some extent, and morning activities more coupled to sun time.
The sensitivity of the Stanford Sleepiness Scale (SSS) to shortterm cumulative partial sleep deprivation (PSD) and subsequent recovery oversleeping was examined. A repeated-measures design included 7 paid healthy undergraduate volunteers. who were normal sleepers (mean sleep time, 7.6 hr), and consisted ofthe following schedule: (a) pre-baseline; (b) sleep reduction of 40% of 1 night (mean, 4.6 hr) for 5 nights; (c) recovery oversleeping for night 1 (mean, 10.6 hr) and night 2 (mean, 9.1 hr); (d) post-baseline. Daytime performance testing utilized a 1 hr auditory vigilance task and four short-duration (10 min) tests, two of which have been shown sensitive to total and partial sleep loss effects. Subjects completed SSS forms every 15 min while awake and 1-9 scales of mood and energy upon awakening. Subjective measures were analyzed across conditions for mean all-day and task-related SSS values and mood and energy ratings. A correlational analysis investigated individual correspondences between ratings and performance. Results indicate that the SSS is sensitive to deficits in alertness following PSD. However, it generally does not predict individual performance efficiency and therefore cannot act as a substitute for performance measures in studies involving chronic sleep loss.
This article reports the development and validation of a scale to measure global life satisfaction, the Satisfaction With Life Scale (SWLS). Among the various components of subjective well-being, the SWLS is narrowly focused to assess global life satisfaction and does not tap related constructs such as positive affect or loneliness. The SWLS is shown to have favorable psychometric properties, including high internal consistency and high temporal reliability. Scores on the SWLS correlate moderately to highly with other measures of subjective well-being, and correlate predictably with specific personality characteristics. It is noted that the SWLS is suited for use with different age groups, and other potential uses of the scale are discussed.
In the early 1990s, medical research found that teenagers have biologically different sleep and wake patterns than the preadolescent or adult population. On the basis of that information, in 1997 the seven comprehensive high schools in the Minneapolis Public School District shifted the school start timefrom 7:15 a. m. to 8:40 a. m. This article examines that change, finding significant benefits such as improved attendance and enrollment rates, less sleeping in class, and less student-reported depression. Policy implications are briefly discussed, acknowledging this to be a highly charged issue in school districts across the United States.
Sleep and health are closely interrelated and sleep quality is a well-known contributor to perceived health. However, effects of sleep-timing preference i.e. morningness-eveningness on health has yet to be revealed. In this study, we explored the relationship between morningness-eveningness and perceived health in a sample of female working professionals (N = 202). Sleep-timing preference was measured using the Composite Scale of Morningness. Perceived health was characterized by Center for Epidemiologic Studies Depression Scale, WHO Well-Being Scale-5 and Patient Health Questionnaire-15 scores. We also investigated possible mechanisms, including stress and health-impairing behaviours. In accordance with previous data, we found more depressive mood, lower well-being and poorer perceived health among evening types. To assess health-impairing behaviours we collected data on smoking habits, alcohol consumption, physical activity and diet. Among the possible mechanism variables, greater stress, less frequent physical activity and less healthy diet were associated with eveningness. Furthermore, stress diminished the strength of the association between morningness-eveningness and depressed mood. Physical activity attenuated the strength of the association between morningness-eveningness and well-being. No effects of alcohol consumption could be identified. Our data show that evening preference behaves as a health risk in terms of associating with poor perceived health. Our findings also suggest that this effect might be mediated by health behaviours and stress.