1 INTRODUCTION

In our modern industrial society, people consistently awaken earlier on workdays than their biological rhythm dictates, while they sleep-in on weekends/free days to compensate for the accumulated sleep debt. Thus, sleep timing is different between weekdays and weekends. This has been coined as “social jetlag” (SJL; Roenneberg, Pilz, Zerbini, & Winnebeck, 2019; Wittmann, Dinich, Merrow, & Roenneberg, 2006). SJL is measured in relation to the midpoint of sleep, which is the midpoint between sleep onset and awakening. SJL presents the differences between the midpoint of sleep on workdays and free days. Usually, people have a positive SJL, which means that they go to bed and awaken later on free days. Sleep timing on free days is usually seen and understood as reflecting the internal biological time, while sleep timing on weekdays is reflecting social timing and demands (Wittmann et al., 2006). Therefore, wild animals display virtually no SJL (Randler, 2014) as do human infants (Randler, Fontius, & Vollmer, 2012). It increases from childhood to puberty, with the highest SJL at the end of adolescence, then declining gradually afterwards (Randler, Vollmer, Kalb, & Itzek-Greulich, 2019; Roenneberg et al., 2004).

While a positive SJL with later sleep timing on free days is widely acknowledged, studies describing negative SJL show that some people arise even earlier on weekends/free days compared to weekdays (Roenneberg et al., 2019; Wong, Hasler, Kamarck, Muldoon, & Manuck, 2015). However, few reports have described people with negative SJL in more detail. For example, in the Chinese population, Zhang, Cajochen, and Khatami (2019) found that 31.16% of their study population had negative SJL on work-free days. Reasons for negative SJL may be that people go to bed earlier on weekends, or that they are experiencing shift work. Also, having a pet may influence sleep–wake timing and may lead to earlier awakening times (Randler, Díaz-Morales, & Jankowski, 2018). While negative SJL has been described in previous work, few were searching for causations and correlates. For example, Kohyama (2020) related negative SJL to leisure activities in adolescents, with a special focus on physical activity (sports). In this case, highly physically active adolescents slept less and awoke earlier on weekend/free days. Therefore, leisure activities may be the reason, why people arise earlier on free days compared to weekdays. Apart from sports, nature-based recreational activities, such as birdwatching, hunting or fishing, might also be related to a negative SJL because people arise early at the weekends (Sparks, Huber, & Tryjanowski, 2008; Żmihorski, Sparks, & Tryjanowski, 2012). However, to our knowledge, there are no studies addressing the topic of negative SJL related to recreational activities.

In the present study, we focus on negative SJL with special consideration of leisure activities. Any definition that distinguishes “leisure” from “work” is a matter of judgment (Aguiar & Hurst, 2007), but leisure activity is usually an activity chosen for pleasure or relaxation, and it concerns free time, without work or other obligations (Veal, 1992). Although from a physiological viewpoint it does not matter whether a person arises for birdwatching as a hobby, a job, or as a student of biology, but the main difference from a psychological point is that either students or a professional ornithologist have to awaken earlier, while the hobbyist has the free decision (which is by definition leisure). While the other two groups have no choice, the recreational birdwatcher has a choice. Thus, if the birdwatcher would pursue a typical weekend life of most other people (Wittmann et al., 2006), he/she would sleep in at the weekend (weekend oversleep) to compensate for accumulated sleep debt during the week. Thus, a negative SJL resulting from a freely chosen leisure activity means that people might not live against their internal biological clock during the week (without a compensation for it on free days/weekends) but may even enforce this effect by arising earlier on weekends than on weekdays.

Another, more general aspect of sleep–wake timing is chronotype. One method to determine a person’s chronotype is referring to the midpoint of sleep (Roenneberg et al., 2004). Here, a correction algorithm is applied to the midpoint of sleep on free days (which is seen as a marker of sleep timing) to make the data comparable (Roenneberg et al., 2004). The midpoint of sleep on free days is correlated with the dim-light melatonin onset (secretion; r = .68; Kantermann, Sung, & Burgess, 2015). In contrast to SJL, chronotype has been related to personality and individual differences (see e.g. Adan et al., 2012 for a review), but there are only a few studies concerning leisure activities. For example, evening types have been found to travel less than morning ones, which was in contradiction to the expectations because evening types score higher in novelty seeking or sensation seeking (Chark, Lam, & Fong, 2020). Further, evening types had more sedentary activity and less active leisure (Wennman et al., 2015). In adolescents, evening types spent more time watching television, more time at the computer, but less time reading and in physical activity (Kauderer & Randler, 2013).

To describe negative SJL resulting from leisure activities we focussed on birdwatching in the present study, which is a common recreational activity with large individual differences among people. In general, birds are more active during the morning hours. Bird activities start often before or shortly after sunrise, especially during spring and early summer (Gwinner, 1996). Birdwatchers (birders) usually follow this diurnal pattern (Frątczak, Sparks, Randler, & Tryjanowski, 2020; Randler, Tryjanowski, Jokimäki, Kaisanlahti-Jokimäki, & Staller, 2020). Also, birdwatching in the early morning might be beneficial for city residents because parks and birding sites are less crowded and noisy at this time of day. Thus, we would expect a negative SJL in birders in general. We follow this hypothesis by comparing weekdays, weekends, and birdwatching days.

In addition, birders vary greatly in their recreational specialisation. Recreational specialisation was defined by Bryan (1977), representing a continuum between the generalists with low involvement and the specialists with a high involvement. Generalists may go birdwatching occasionally, while specialists may birdwatch several times a week and travel to farther places (Randler et al., 2020). A further distinction is made between the dimensions of behaviour (financial investment, e.g. expensive equipment or travel days; Scott & Shafer, 2001), level of competence (skill and knowledge, e.g. identifying different bird species; Lee & Scott, 2004), and centrality to lifestyle (i.e. how important is the leisure activity for someone’s life). Thus, birders can be graded along a continuum between highly specialised with a strong psychological, monetary and time commitment as one end of the continuum, and a very little specialisation with low commitment on the other end.

The aims of the present study were first, to assess general differences in sleep timing between weekdays, free days, and birdwatching days to investigate negative SJL. Further, we focussed on individual differences concerning the birding specialisation in relation to sleep timing. We hypothesised that more specialised birders may have stronger differences between usual schedules and sleep timing on birdwatching days because of their desire to watch even the earliest birds active.

2 SUBJECTS AND METHODS

Data collection took place via the online research tool SoSciSurvey, between February 2020 and October 2020. On the first webpage, study aims were explained, and a formal consent was asked for. Participants had to actively click on “yes” to start the survey and could stop and leave at any time. Recruitment took place via different channels, e.g. using announcements on the webpages for birders. In detail, the recruitment procedure was to join, e.g. Facebook webpages for birdwatchers in Germany, which are closed groups and need approval of the administrator to join. These administrators usually check the Facebook pages of the applicants to avoid spamming. In addition, mailing lists exist of members of local and regional ornithological societies. The survey link was distributed via these societies, so this mail only reached people who were members of that society, where they usually have to pay an annual fee for membership. Further, a paid advertisement was placed in a paper birdwatching journal in Germany. The survey was also distributed by a mailing list among people who report data to a web-based citizen science portal (Naturgucker.de). Lastly, the survey was posted on ornithological websites; some of them even need a login with passwords. This renders it highly likely that the target population was reached and that non-birdwatchers were excluded. Of course, we cannot rule out that a non-birdwatcher hypothetically spends time in surveying ornithological websites and then may participate in the survey. However, we consider this highly unlikely. Most of the recruitment procedure reached the target population. The study was granted permission by the Ethics Committee of the Eberhard Karls University Tübingen (Az: A2.5.4-113_aa). The questionnaire asked for birding specialisation items and habitual bed and awakening times. Concerning sleep and awaking times, we asked for bed and arising times on weekdays and on weekends, as well as on birdwatching days. As demographics we asked for age and gender. Additionally, shift work was used as an exclusion criterion.

2.1 Birding specialisation

Birding specialisation was based on five scales (Randler, 2021), which were subsequently converted into a single score (Section 2.2). First, the skill and competence scale asked for the number of species birders recognised by appearance and song, as well as self-assessed knowledge from 1 (novice) to 5 (expert). These questions were adapted from Lee and Scott (2004). The behaviour scale was based on self-reported behaviour, e.g. the number of birding trips, birding days, number of species seen throughout life, number of bird books owned (McFarlane, 1994), and equipment value (Hvenegaard, 2002). The personal commitment scale was measured with three questions: “Other leisure activities don’t interest me as much as birding.” (Lee & Scott, 2004); “I would rather go birding than do most anything else.” (Lee & Scott, 2013); and “Others would probably say that I spend too much time birding.” (Lee & Scott, 2013). While the behavioural commitment scale measured the following: “If I couldn’t go birding, I am not sure what I would do.” (Lee & Scott, 2004); “If I stopped birding, I would probably lose touch with a lot of my friends.” (Lee & Scott, 2013); “Because of birding, I don’t have time to spend participating in other leisure activities.” (Lee & Scott, 2013). Centrality to lifestyle was assessed with the modified involvement scale from Kyle, Absher, Norman, Hammitt, and Jodice (2007).

2.2 Statistical analyses

We used bed and awaking times to calculate different outcome variables, such as sleep duration and midpoint of sleep on weekdays, weekends, and birdwatching days. Additionally, the duration of wakefulness was calculated. Duration of wakefulness was the time spent awake in hours, complementary to sleep duration. SJL was calculated as suggested by Wittmann et al. (2006). In addition, we calculated a birding SJL. Here, the difference between the midpoints of sleep on free days compared to birdwatching days was calculated. Chronotype, as midpoint of sleep corrected for oversleep was calculated following Roenneberg et al. (2004) based on bed and awaking times. We here follow the measure of chronotype based on clock times in a continuous manner. Birding specialisation was based on the five different scales described above. We used a principal component factor analysis to reduce the number of scales and to combine them into a single score. The analysis extracted one factor with an eigen-value of 3.378, explaining 67.6% of the variance. The second factor was <1.0 with a value of 0.841. We saved the factor scores as residuals for further processing. The single factor was labelled “birding specialisation”, with a higher score representing a higher specialisation level. Table 1 shows the respective loadings of the factors. We used t tests to analyse differences between two groups and Pearson’s correlation to assess bivariate relationships. Linear regressions were used to assess the influence of different independent variables simultaneously.

TABLE 1. Factor loadings of the five birding specialisation scales Factor 1 Centrality to lifestyle 0.867 Personal commitment 0.838 Behavioural commitment 0.818 Behaviour 0.811 Skill/competence 0.773 3 RESULTS

A total of 2,404 birdwatchers participated in this study (1,330 male, 1,065 female, nine diverse), with a mean (SD) age of 49.96 (16.35) years.

3.1 Comparing bed and awaking times

Birders, like many other people, arise and go to bed later on weekends (Table 2). Concerning birdwatching days, birders arise on average 14 min earlier compared to weekdays, while they go to bed at the same time on birding days and weekdays. Thus, birding days are longer (longer wakefulness).

TABLE 2. Comparison of bed and awaking times of birdwatchers on weekdays, weekend days and on birdwatching days. Degrees of freedom (df) = 2,403 for all comparisons Mean, 24-hr clock SD, hr:min t p Wake week 06:43 01:05 −54.155 .001 Wake weekend 07:54 01:13 Wake week 06:43 01:05 8.541 .001 Wake birding 06:28 01:24 Wake weekend 07:54 01:13 49.192 .001 Wake birding 06:28 01:24 Bed week 22:46 00:57 −43.374 .001 Bed weekend 23:25 01:06 Bed week 22:46 00:57 1.692 .091 Bed birding 22:45 01:01 Bed weekend 23:25 01:06 35.357 .001 Bed birding 22:45 01:01 3.2 Comparing sleep duration, SJL and recreational jetlag

Table 3 shows the compound measures of weekdays, weekend, and birdwatching days. Every statistical comparison is significant at the p < .001 level. The weekend–weekday differences are as expected with longer sleep duration, later midpoint of sleep, and SJL of ~1 hr (Table 3). The period of wakefulness is shorter on weekends than on weekdays according to the longer sleep duration. SJL decreased with increasing age (r = −.379, p < .001). A regression model including age and gender as independent variables and SJL as dependent showed a significant influence of age, but not of gender (F2,2,390 = 202.876, p < .001, corrected R2 = .144; age, β = −0.379, p < .001; gender, β = 0.024, p = .198).

TABLE 3. Sleep duration, wake duration, midpoint of sleep and social jetlag of birdwatchers on weekdays, weekend days and on birdwatching days Mean, hr:min SD, hr:min t df p Sleep duration week 07:56 01:01 −26.77 2,403 .001 Sleep duration weekend 08:28 01:07 Sleep duration week 07:56 01:01 8.362 2,403 .001 Sleep duration birding 07:42 01:24 Sleep duration weekend 08:28 01:07 28.442 2,403 .001 Sleep duration birding 07:42 01:24 MS week 26:45 00:53 −57.814 2,403 .001 MS weekend 27:40 01:01 MS week 26:45 00:53 7.111 2,403 .001 MS birding 26:36 01:00 MS weekend 27:40 01:01 50.829 2,403 .001 MS birding 26:36 01:00 Wake duration week 16:03 01:01 26.77 2,403 .001 Wake duration weekend 15:31 01:07 Wake duration week 16:03 01:01 −8.362 2,403 .001 Wake duration birding 16:17 01:24 Wake duration weekend 15:31 01:07 −28.442 2,403 .001 Wake duration birding 16:17 01:24 Social jetlag 00:55 00:46 −7.111 2,403 .001 Social jetlag birding 01:03 01:01 Abbreviation: MS, midpoint of sleep.

Birdwatching days started earlier than weekdays (Table 2) and lasted longer than weekend and weekdays. Thus, birdwatching days are shifted towards an earlier sleep–wake rhythm in total, contrasting to weekend days. Concerning SJL, there was a difference of 55 min between weekdays and weekend days, which was a difference of 1:03 hr when comparing weekend days and birdwatching days, and finally, to 8 min when comparing weekdays with birdwatching days.

3.3 Influence of recreation specialisation on sleep–wake variables

The correlations between birding specialisation and sleep parameters on weekdays and weekend days were usually weak albeit significant (with an r <.09; Table 4). However, when it comes to birdwatching days, we found much stronger correlations between specialisation and sleep parameters (Table 4). The correlations between specialisation and sleep–wake variables on birdwatching days are significant even when controlling for multiple testing (Bonferroni correction). The more engaged and psychologically committed birders are, the less they sleep, the earlier they arise, and the earlier is their midpoint of sleep on birdwatching days. This means that highly specialised birders shift their sleep–wake rhythm to an earlier time compared to their weekend, and even their weekday sleep behaviour. Also, they extend their wake duration in comparison to weekdays and weekend days, staying awake longer on birdwatching days. This indicates that higher specialised birders tend to be more morning oriented and experience less SJL when comparing weekdays with free days/weekend days without birding. To identify the most influential predictor, we ran a multiple regression analysis including the predictors with the highest correlation coefficients, which were, in turn, the variables concerning birding days. The full model was significant (F3,2.400 = 85.349, p < .001, corrected R2 = .095). As many of the variables were inter-correlated, three entered the model, while two were excluded because they were redundant (Table 5). SJL on birding days failed significance marginally, and wake time on birding days showed the highest standardised beta coefficient (β = −0.233). This corroborates the correlational analysis and shows that high specialised birdwatchers change their sleep–wake rhythm primarily by arising earlier.

TABLE 4. Relationship between birding specialisation and sleep–wake variables Birding specialisation (factor score) Sleep duration week −0.086*** Sleep duration weekend −0.098*** Sleep duration birding −0.253**** MS week −0.027 ns MS weekend −0.056* MS birding −0.248**** MSFsc −0.048* Wake duration week 0.086*** Wake duration weekend 0.098*** Wake duration birding 0.253**** Social jetlag −0.042* Social jetlag birding 0.190**** Wake birding −0.305**** Note All correlations are significant with a *p < .05, ***p < .001 or ****p < .0001. Abbreviations: MS, midpoint of sleep; MSFsc corrected midpoint of sleep (chronotype); ns, not significant. TABLE 5. Relationship between birding specialisation and sleep–wake variables Standardised coefficient t p Constant 0.554 .579 Wake duration birding 0.067 2.352 .019 Social jetlag birding 0.044 1.918 .055 Wake birding −0.233 −7.397 <.001 Note Regression analysis of the influence of sleep–wake variables as predictors of birding specialisation. The birding sleep–wake variables from Table 4 were included as they showed the highest correlation coefficients. 4 DISCUSSION

Birders have a SJL corresponding to that of other people; they arise later over weekends than on weekdays (e.g. Roenneberg et al., 2004). Also, they act in accordance with others concerning sleep timing on free days and weekdays. However, this relationship fades on birding days, with birders waking and arising even earlier (compared to workdays), as birding usually takes place in the early morning hours (e.g. Frątczak et al., 2020; Randler et al., 2020). Although birdwatching is pursued mainly on weekends (Sparks et al., 2008, Żmihorski et al., 2012, Laney, Hallman, Curtis, & Robinson, 2021), people may also go birdwatching on weekdays before their regular work schedule starts. In both cases birders may accumulate even more sleep debt due to their leisure activity and are not able to compensate for their sleep deficit on weekends by sleeping-in to compensate for sleep loss during the week and they may even arise earlier. SJL is considered detrimental as people do not live in accordance with their internal biological rhythm. In this fashion a negative SJL can result in negative health outcomes. Thus, we expect birders to suffer more from the short- and long-term consequences of SJL. This hypothesis should be investigated further. Concerning an alternative calculation of SJL (Jankowski, 2017) using sleep onset as the anchor point, there is no difference between weekdays and birding days and the SJL might be considered negligible. However, the main difference is not between weekdays and birding days, but considering the free days, where the birdwatchers have the possibility to sleep-in (and they do so), there is indeed a negative SJL of >1 hr. Rather than compensating for the sleep debt accumulated during the week, they increase their total sleep debt by arising early on weekends. Thus, summing up, there are not only the 8 min that birdwatchers arise earlier compared to weekdays, but also they add to the 55 min of SJL. In terms of sleep duration, the weekday sleep was 7:56 hr, the weekend sleep 8:28 hr, and the birding sleep duration 7:42 hr. Thus, birdwatchers experience a sleep curtailment when they go birding. Instead of sleeping ~30 min longer, they arise ~15 min earlier, summing up to a sleep reduction of about ~45 min compared to a regular weekend.

However, birding as a nature-based recreational activity has a positive effect on the activity level of those who pursue this hobby, comparable to fishing and other activities outdoors (Ardahan & Turgut, 2012; Singh & Kiran, 2014). Furthermore, the success experienced after watching birds, as well as the environment surrounding the birders might elicit positive emotions (MacKerron & Mourato, 2013). Taken together those positive effects (more physical activity and positive emotions) may mitigate or outweigh the negative ones following the increased sleep deficit (Tryjanowski & Murawiec, 2021). In addition, greater exposure to daylight and a longer time span spent in nature has a positive health protective effect (Beute & Kort, 2014). Another positive aspect may be that birders get more tired because of their high activity level, even though they go to bed at the same time they usually do during weekdays. This could lead to lower consumption of stimulants such as alcohol or probably increase sleep quality. However, further research should investigate these considerations. Motivation in birdwatching and positive stress could positively impact on somatic and mental health (Folkman, 2008). This might be another interesting venue of future research, because on the one side, the impact of positive stress on somatic and mental health is equivocal (Anderson & Arnoult, 1989), and second, it is unknown whether birdwatchers experience positive or negative stress toward their recreation activity, and furthermore, whether this depends on their recreational specialisation.

The results obtained in the present study might stand representatively for other nature-related leisure activities, such as recreational fishing, which are bound to certain daytimes or encompass a large part of the day. Further, they are consistent with those of other studies concerning negative SJL (Kohyama, 2020; Randler et al., 2019; Wong et al., 2015; Roenneberg et al., 2019). SJL is a good concept to address the weekend and weekday (or free day) differences in the sleep–wake cycle. But, to put the results shown into practice, the SJL should be expanded to include a concept that describes a systematically recurring event with resulting negative SJL (e.g. nature-based recreation activity). The concept of negative SJL needs further examination, as not all life situations that lead or could lead to negative SJL have been considered in more detail up to this point. Although these aspects are discussed here in the framework of a leisure activity, we suggest extending it also to volunteering, e.g. to the dangerous work of unpaid volunteers, such as lifesavers or firefighters, as well as services for other social groups.

In addition to the general finding of negative SJL, we found strong individual differences according to specialisation of birdwatchers. Birders can be grouped alongside a continuum from generalist to specialist (Lee & Scott, 2004), and differ in the time, money, and psychological commitment they invest. Correlated with this graded specialisation, we found a stronger influence on sleep–wake rhythms in more specialised and committed birders. Specialised birders tend to prioritise birdwatching over sleep and forego sufficient sleep on observation days. They arise earlier and have a shorter sleep duration, accompanied by a correspondingly earlier midpoint of sleep. The resulting negative SJL is detrimental to health, but, as discussed above, may be mitigated by other positive effects following the nature-based recreational activity of birdwatching. Further studies are needed in both birdwatching and other activities alike (resulting in negative SJL) to elucidate the advantages and disadvantages for health.

Against this background, an actigraphic study of sleep and activity times would be very informative because the data collected here were generated from the subjects’ self-reports. The clear advantage of this procedure is the number of data sets obtained (~2,400), which cannot be gathered in the same quantity through actigraphic measurements within a reasonable time. In general, self-reports correlate well with actigraphic data (Faßl, Quante, Mariani, & Randler, 2019), but a breakdown of sleep phases and an approximate assessment of sleep quality would be a valuable extension in researching the consequences of negative SJL. Also, an actigraphic measurement comparing birdwatching days with normal days would be a feasible option to support the questionnaire results presented.

4.1 Strengths and Limitations

Although some of the correlations found here were comparably small, the present study is the first to identify, and examine the effects of nature-based recreational activities (using the example of birdwatching) on the sleep–wake behaviour. Our present results form a solid basis on which to propose the extension of the SJL concept to include a special consideration of leisure activities. We were able to recruit nearly 2,400 participants, who could be classified on a continuum along their specialisation. We were therefore able to show a gradient between low specialisation and corresponding low negative SJL and high specialisation with simultaneously more pronounced negative SJL. In order to further confirm the results obtained, consecutive studies should be carried out. Actigraphic measurements would be conceivable, but also investigations on other leisure activities close to nature. In addition, a questionnaire, such as the reduced form of Morningness–Eveningness Questionnaire (rMEQ) allowing a separation into groups (evening types, morning types, etc.), might be applied in the future, because it collects data on time preferences (Randler, 2013). Furthermore, it remains open as to which other life situations could be responsible for a persistent or recurring negative SJL. Moreover, the positive and negative health effects should be identified and investigated against each other.

ACKNOWLEDGEMENT

We are grateful for the help of many colleagues from different birdwatching and ornithological associations in helping us distributing the link.

CONFLICT OF INTEREST

No conflicts of interest declared.

AUTHOR CONTRIBUTION

Conceptualisation: CR and PT designed the study, Data curation: NS collected the data, Formal analysis: CR and NS made the calculations, Writing: Original draft: CR wrote the first draft, Writing: reviewing and editing: PT and NS contributed to writing.

ETHICAL APPROVAL

Ethics committee of the Eberhard Karls University Tübingen (Az: A2.5.4-113_aa).