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Seasonality, social zeitgebers and mood variability in entrainment of mood
Journal of Affective Disorders 59 (2000) 47–54 www.elsevier.com / locate / jad
Research report
Seasonality, social zeitgebers and mood variability in entrainment of mood Implications for seasonal affective disorder S. Reid*, A.D. Towell, J.F. Golding University of Westminster, Department of Psychology, 309 Regent Street, London W1 R 8 AL, UK Received 23 December 1998; received in revised form 10 June 1999; accepted 10 July 1999
Abstract Background: Seasonal variations in mood (seasonality) appear to be entrained to light, a physical zeitgeber. We hypothesised that people high in seasonality may be responsive to a range of zeitgebers, because of greater mood variability. We investigated whether the moods of people high in seasonality were more strongly entrained to the calendar week, a social zeitgeber, and whether any such effect was dependent on variability of mood. Methods: 53 participants (14 male, 39 female; overall mean age 5 30) completed a daily mood report, over 56 consecutive days. Participants also completed the Seasonality Score Index (SSI) of the Seasonal Pattern Assessment Questionnaire. Each participant’s time series of daily mood was analysed by spectral analysis to quantify the strength of their weekly mood cycle. Results: Participants with high SSI scores ( $ 11) had significantly stronger weekly mood cycles than those with low SSI scores ( , 11), and significantly greater variability in mood. Covarying for mood variability reduced the difference between high and low SSI groups in mean strength of weekly mood cycle to non-significance. Limitations: The time series of moods obtained was relatively short, and moods among high seasonal participants may have been affected by seasonal weather variability. Conclusions: People high in seasonality appear to be more responsive to external zeitgebers, and this could be linked to their greater variability in mood. The integration of research on mood variability with research on SAD appears to be warranted. 2000 Elsevier Science B.V. All rights reserved. Keywords: Entrainment; Mood variability; Seasonality; Zeitgebers
1. Introduction Seasonal variation in mood (seasonality) appears to be continuously distributed in the general population (cf. Rosen et al., 1990; Hardin et al., 1991; *Corresponding author. E-mail address: [email protected] (S. Reid)
Rosen and Rosenthal, 1991; Magnusson and ´ Stefansson, 1993; Hegde and Woodson, 1996; Okawa et al., 1996). At its upper extreme, seasonality may be defined by either sub- or full syndromal seasonal affective disorder (SAD) (Kasper et al., 1989a,b; Rosenthal, 1989; Spoont et al., 1991; Schlager et al., 1993; Magnusson, 1996; Raheja et al., 1996). SAD is characterised by recurrent season-
0165-0327 / 00 / $ – see front matter 2000 Elsevier Science B.V. All rights reserved. PII: S0165-0327( 99 )00122-6
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al affective illness, with onset occurring most commonly in autumn or winter, and remission in spring or summer (Dalgleish et al., 1996). The onset of SAD is associated with seasonal reductions in daylight, and remission to ensuing seasonal increases in daylight (Young et al., 1997), and both sub- and full- syndromal forms of the disorder may respond to bright-light therapy (e.g. Rosenthal et al., 1984; Kasper et al., 1989b). Several theories have been advanced to explain the occurrence of SAD and its response to bright-light therapy, with most focusing exclusively on biological factors that could be affected by light (for reviews see Rosenthal et al., 1988; Skwerer et al., 1988; Wehr and Rosenthal, 1989; Tam et al., 1995; Dalgleish et al., 1996; Lee et al., 1997; Sato, 1997; Young et al., 1997). Despite the emphasis of current theorising, biological mechanisms of SAD remain largely unknown (Lee et al., 1997). Against this background, alternative mechanisms of SAD should be considered. One possible mechanism of SAD is mood variability, a relatively stable characteristic of individuals (Larsen, 1987; Cooper and McConville, 1990; McConville and Cooper, 1997). Given that mood variability is linked to emotional reactivity (Eysenck and Eysenck, 1985; Hepburn and Eysenck, 1989; Williams, 1993), people with greater mood variability may be more emotionally responsive to powerful external zeitgebers (timegivers). Germane to the argument proposed in this paper is that emotional reactivity does appear to be a feature of seasonality, as people with stronger seasonality tend to score relatively high on measures of neuroticism (Murray et al., 1995; Jang et al., 1997), and are often emotionally responsive to weather conditions (Rosenthal et al., 1987; Albert et al., 1991; Molin et al., 1996). Moreover, seasonality could be conceptualised as a continuum representing increasingly stronger entrainment to the annual cycle of light, a powerful physical zeitgeber. Entrainment refers to the coupling between the timing of a rhythm and its external zeitgeber, and many human rhythms at the behavioural, physiological, and psychological level can be entrained to zeitgebers of both a physical and social nature (McGrath et al., 1984; McGrath and Kelly, 1986). If it is the case that highly seasonal individuals have generally increased mood variability, we might expect to find evidence that their moods
are more responsive to entrainment by not only light, but also zeitgebers of a social nature. Social zeitgebers are an important form of entrainment for humans. For instance, routine activities, such as work and recreation, may serve to entrain circadian rhythms (Monk et al., 1990; Ehlers et al., 1988, 1993; Elmore et al., 1994). One of the most powerful social zeitgebers in daily life is the calendar week. Because it is cyclical, the week is an important unit of temporal organisation in which certain activities and events tend to occur at predictable or usual times (Zerubavel, 1985; Huttenlocher et al., 1992). The week appears to build periodicity into mood, as several studies have documented 7-day mood cycles, with people tending to report more positive moods at weekends (Stone et al., 1985; McFarlane et al., 1988; Almagor and Ehrlich, 1990; Larsen and Kasimatis, 1990). The present study aimed to investigate whether people high in seasonality have a stronger weekly mood cycle, and whether any such effect was independent of average level of daily mood and, more germane to the present study, variability in daily mood. Mood cyclicity was explored by spectral analysis, a technique which involves analysing a time series to quantify the amplitude of any cycles in the data (Larsen, 1990). We hypothesised that the daily moods of participants high in seasonality would be more strongly entrained to a weekly cycle than the daily moods of participants low in seasonality, and that this effect will depend on mood variability. We based our hypothesis on the proposal that people high in seasonality may have greater mood variability and, as such, will be generally more responsive to entrainment by external zeitgebers such as the calendar week.
2. Method
2.1. Participants and design Sixty-four adults were recruited through adverts placed in a national magazine and in the University of Westminster student magazine, and through posters in sites throughout the University. The posters and adverts invited people with seasonal changes in mood to participate. Participants completed a report
S. Reid et al. / Journal of Affective Disorders 59 (2000) 47 – 54
form on daily mood for 56 consecutive days between 5 April 1998 and 30 May 1998. They also completed a questionnaire providing information on demographic characteristics and seasonality. Completed, useable sets of reports and questionnaires were received from 53 participants (14 males and 39 females), a response rate of 83%. The mean6SD age of participants was 28.8613.11 years for females and 34.3615.89 years for males. The majority (66%) were full-time students at the University of Westminster, whilst the remainder were either University staff (11%), or members of the general public (23%). There were no restrictions placed on those who could participate.
2.2. Materials and procedure Participants were instructed to complete their reports in the evening. The report consisted of two adjectives, ‘cheerful’ and ‘sad’, adapted from the Profile of Mood States Bipolar form (Lorr and McNair, 1984), which has been used with clinical and normal populations (Myhill and Lorr, 1985), and is sensitive to changes in mood (Benkelfat et al., 1994). For each adjective, participants indicated how well it described their mood that day, by marking a separate 90 mm line anchored either end with the phrases ‘Much like this’ and ‘Much unlike this’. Scores of the two adjectives were added (‘sad’ was reverse scored), with higher total score indicating more positive mood for that day. The scale demonstrated high internal consistency (a 5 0.92).
2.3. Questionnaire Demographic characteristics assessed were age, gender, and education. The questionnaire included the Seasonality Scale Index (SSI) of the Seasonal Pattern Assessment Questionnaire (SPAQ; Rosenthal et al., 1987). The SSI has high internal consistency (Magnusson et al., 1997), and respondents scoring 11 or more may be regarded as a potential cases of subsyndromal SAD, or full syndromal SAD if they also indicate that seasonal change is experienced as at least a moderate problem (Magnusson, 1996). Participants were instructed to complete the questionnaire on or before the start of the 56-day mood reporting period (5 April 1998).
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2.4. Data analysis 1. In order to quantify mood cyclicity, each participant’s time series of daily mood was submitted to spectral analysis. (The data were detrended first, because a time series that contains a trend violates the stationarity assumption of spectral analysis. Various windowing functions were applied to the data, but were not used in the final analysis, as they did not improve the model fit.) Spectral estimates were calculated, separately for each participant, for cycle lengths ranging from 2 to 28 days. The spectral estimates for six, seven, and eight days were added together. The resultant figure (‘weekly-cycle strength’) can be interpreted as indicating how strongly a participant’s mood is entrained to a cycle of approximately a week in length. The rationale for adding the 6-, 7-, and 8-day components is that within any individual a weekly cycle may vary slightly from week to week (frequency jitter causing what is sometimes referred to as relaxation or broadening of the spectral peak). 2. Individual differences in weekly-cycle strength with respect to SSI scores were examined. The sample was divided into two groups: those scoring 11 or more on the SSI versus those scoring under 11. (No distinction was made between SAD and S-SAD, as the SSI discriminates poorly between these conditions; Magnusson, 1996.) The mean weekly-cycle strength for each group was calculated. Adjusted means were also calculated, with average level of daily mood and mood variability (within-subjects standard error computed from mood ratings over 56-days) as separate covariates. 3. Finally, a number of t-tests and correlations were computed to address finer grain questions arising from the main analyses.
3. Results
3.1. Spectral analysis of mood Almost half of the sample (47%) scored 11 or more on the SSI, indicating that they potentially experience SAD or S-SAD, as defined by SPAQ criteria (Magnusson, 1996). The mean weekly-cycle
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strength (given in arbitrary spectral power units of mood) was greater for the high seasonal group (mean6SD spectral estimate 5 14 53568130 mood units) than for the low seasonal group (mean6SD spectral estimate 5 898068855 mood units). The difference between the groups was significant (t 5 2.37; df 5 51; P , 0.05). The difference remained robust after covarying for individual differences in average daily mood level (F 5 4.24; df 5 1.50; P , 0.05), but not after covarying for individual differences in mood variability (F 5 1.35; df 5 1.50; P . 0.05). As university studies do not require attendance at college every weekday, the strength of the zeitgeber ‘calendar week’ is possibly weaker for the students than for the other participants. However, the
mean6SD spectral estimate for the students was 12 05869190 mood units, compared with 10 70968463 mood units for the other participants, and there was no significant difference between the two (t 5 0.61; df 5 51, P . 0.05). Fig. 1 displays the mean strength (given in arbitrary spectral power units of mood) of the weekly mood cycle for the high and low seasonal groups before and after covarying separately for average mood level and mood variability.
3.2. Further analyses Mood variability was found to be positively correlated with both weekly cycle strength (r 5 0.72;
Fig. 1. Group comparisons of raw and adjusted means for strength of weekly mood cycle.
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Table 1 Average6SD mood levels a by day of week, and 2-tailed T-test comparisons b between high and low seasonal groups Day
Total sample N 5 53
High seasonal N 5 25
Low seasonal N 5 28
Comparison High versus low
Monday Tuesday Wednesday Thursday Friday Saturday Sunday
122.19621.89 118.43624.81 122.98621.83 121.16622.51 124.77624.29 126.18621.99 122.51622.80
124.24619.55 115.76623.43 119.72622.93 115.13622.64 116.80624.76 125.66620.69 119.51622.10
120.35623.99 120.81626.17 125.89620.79 126.54621.37 131.88621.92 126.65623.45 125.19623.48
NS NS NS NS NS NS NS
a b
Range of possible mood scores 5 0 (least positive / happy)–180 (most positive / happy). Corrected for multiple comparisons (~ set at 0.05 / 7 5 0.0035).
P , 0.001) and seasonality (r 5 0.29; P , 0.05). To investigate whether seasonality is associated with a tendency to have stronger mood cycles in general, the spectral estimate of each participant’s strongest mood cycle was correlated against their seasonality (SSI) score. These variables were not significantly correlated (r 5 0.20; P . 0.05). To investigate which times of the week participants’ moods were least and most positive, average mood levels were computed by day of week for the total sample, and again separately for the high and low seasonal groups. The figures displayed in Table 1 indicate that moods were least positive midweek, and most positive at the start (Friday) and middle (Saturday) of the weekend. It can be seen that there was no significant difference between the groups in average mood level by day of week. Moreover, we found no significant difference between the groups in average mood level across the 56-days of the study (t 5 1.09; df 5 51; P . 0.05).
4. Discussion The present study provides evidence that people high in seasonality are more responsive to entrainment by external zeitgebers. Besides their increased seasonality, the high seasonal group in this study had significantly stronger weekly mood cycles, and this appears to reflect stronger entrainment to a powerful social zeitgeber, the calendar week. The findings in Table 1 indicate that across the sample as a whole, average daily moods follow a traditional midweek low-weekend high pattern (cf. Stone et al., 1985; Zerubavel, 1985; McFarlane et al.,
1988; Almagor and Ehrlich, 1990; Larsen and Kasimatis, 1990; Huttenlocher et al., 1992). This pattern suggests that participants’ moods were, at least to some extent, entrained to the calendar week. A possible explanation for the stronger weekly mood cycle of the high seasonal group is that it reflects a more general phenomenon whereby the periodic component of mood displays greater amplitude in affective illness (Eastwood et al., 1985). This explanation appears to be ruled out, though, because the high seasonal group did not experience significantly lower average mood than the low seasonal group. Moreover, the spectral estimate of each participant’s strongest mood cycle was not significantly correlated with their seasonality (SSI) score, which indicates that the high seasonal group did not have stronger mood cycles in general. The results suggest instead that the stronger weekly mood cycle of the high seasonal group is linked to their greater variability in mood, which itself is strongly correlated with the strength of the weekly mood cycle. It could, of course, be argued that since mood variability was indexed by the within-subjects standard error computed from daily mood ratings, it is bound to be strongly correlated with the amplitude of mood. However, this would not explain how highly seasonal individuals come to show greater mood variability in the first place. As we indicated above, mood variability is linked to emotional reactivity (Eysenck and Eysenck, 1985; Hepburn and Eysenck, 1989; Williams, 1993), which itself appears to be a feature of seasonality (Murray et al., 1995; Jang et al., 1997). We suggest that highly seasonal individuals may have greater mood
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variability because they are more emotionally reactive, and that this could make such individuals more responsive to powerful external zeitgebers, such as environmental light and the calendar week. Moreover, as mood variability is a relatively stable characteristic of individuals (Larsen, 1987; Cooper and McConville, 1990; McConville and Cooper, 1997), our results suggest that people high in seasonality may have a relatively stable vulnerability to entraining influences. The findings that seasonality predicted differences in mood entrainment to the calendar week, and the apparent link with mood variability, does not appear to be explained by current biological models of SAD (cf. Rosenthal et al., 1988; Skwerer et al., 1988; Wehr and Rosenthal, 1989; Tam et al., 1995; Dalgleish et al., 1996; Lee et al., 1997; Sato, 1997; Young et al., 1997). Thus there may be potential benefits to integrating research on mood variability with research on SAD. In suggesting this, we are not ruling out the possibility that mood variability itself has a biological basis (Eysenck and Eysenck, 1985; McConville and Cooper, 1992). We must emphasise that our results do not demonstrate that mood variability is predictive of fullblown seasonal affective illness, as we assessed seasonality retrospectively by questionnaire, and did not investigate a clinical population. It may be noted that the length of time series of daily mood obtained in this study was 56 days, and that longer series result in more stable spectral estimates (Larsen, 1990). It may also be noted that as this study was conducted during British springtime, moods could have been affected by the variable British weather during this season (Kelly et al., 1997). The effect may be greater for the high seasonal participants whose moods are probably more responsive to weather conditions (Rosenthal et al., 1987; Albert et al., 1991; Molin et al., 1996). It may be worthwhile to extend the findings reported here by conducting investigations with SAD patients in the winter months, as this might help establish in what ways mood variability and mood cycling may be linked to symptoms of winter SAD. Any such study may wish to control for social routine stability, as this is associated with depressive symptomatology (Monk et al., 1991, 1996; Szuba et al., 1992; Prigerson et al., 1994; Brown et al., 1996),
which in turn is associated with increased mood variability (McConville and Cooper, 1996). Future studies should include emotional reactivity as a variable in its own right, as this would allow one to determine the extent to which it may mediate or moderate the relationship between mood variability and mood cycling. In conclusion, the present study provides evidence that people high in seasonality are more responsive to external zeitgebers. Besides their increased seasonality, the moods of highly seasonal participants showed stronger entrainment to a social zeitgeber, the calendar week, and this could be linked to their greater variability in mood. These findings do not appear to be explained by current biological models of SAD, and thus the integration of research on mood variability with research on SAD appears to be warranted.
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Research report
Seasonality, social zeitgebers and mood variability in entrainment of mood Implications for seasonal affective disorder S. Reid*, A.D. Towell, J.F. Golding University of Westminster, Department of Psychology, 309 Regent Street, London W1 R 8 AL, UK Received 23 December 1998; received in revised form 10 June 1999; accepted 10 July 1999
Abstract Background: Seasonal variations in mood (seasonality) appear to be entrained to light, a physical zeitgeber. We hypothesised that people high in seasonality may be responsive to a range of zeitgebers, because of greater mood variability. We investigated whether the moods of people high in seasonality were more strongly entrained to the calendar week, a social zeitgeber, and whether any such effect was dependent on variability of mood. Methods: 53 participants (14 male, 39 female; overall mean age 5 30) completed a daily mood report, over 56 consecutive days. Participants also completed the Seasonality Score Index (SSI) of the Seasonal Pattern Assessment Questionnaire. Each participant’s time series of daily mood was analysed by spectral analysis to quantify the strength of their weekly mood cycle. Results: Participants with high SSI scores ( $ 11) had significantly stronger weekly mood cycles than those with low SSI scores ( , 11), and significantly greater variability in mood. Covarying for mood variability reduced the difference between high and low SSI groups in mean strength of weekly mood cycle to non-significance. Limitations: The time series of moods obtained was relatively short, and moods among high seasonal participants may have been affected by seasonal weather variability. Conclusions: People high in seasonality appear to be more responsive to external zeitgebers, and this could be linked to their greater variability in mood. The integration of research on mood variability with research on SAD appears to be warranted. 2000 Elsevier Science B.V. All rights reserved. Keywords: Entrainment; Mood variability; Seasonality; Zeitgebers
1. Introduction Seasonal variation in mood (seasonality) appears to be continuously distributed in the general population (cf. Rosen et al., 1990; Hardin et al., 1991; *Corresponding author. E-mail address: [email protected] (S. Reid)
Rosen and Rosenthal, 1991; Magnusson and ´ Stefansson, 1993; Hegde and Woodson, 1996; Okawa et al., 1996). At its upper extreme, seasonality may be defined by either sub- or full syndromal seasonal affective disorder (SAD) (Kasper et al., 1989a,b; Rosenthal, 1989; Spoont et al., 1991; Schlager et al., 1993; Magnusson, 1996; Raheja et al., 1996). SAD is characterised by recurrent season-
0165-0327 / 00 / $ – see front matter 2000 Elsevier Science B.V. All rights reserved. PII: S0165-0327( 99 )00122-6
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al affective illness, with onset occurring most commonly in autumn or winter, and remission in spring or summer (Dalgleish et al., 1996). The onset of SAD is associated with seasonal reductions in daylight, and remission to ensuing seasonal increases in daylight (Young et al., 1997), and both sub- and full- syndromal forms of the disorder may respond to bright-light therapy (e.g. Rosenthal et al., 1984; Kasper et al., 1989b). Several theories have been advanced to explain the occurrence of SAD and its response to bright-light therapy, with most focusing exclusively on biological factors that could be affected by light (for reviews see Rosenthal et al., 1988; Skwerer et al., 1988; Wehr and Rosenthal, 1989; Tam et al., 1995; Dalgleish et al., 1996; Lee et al., 1997; Sato, 1997; Young et al., 1997). Despite the emphasis of current theorising, biological mechanisms of SAD remain largely unknown (Lee et al., 1997). Against this background, alternative mechanisms of SAD should be considered. One possible mechanism of SAD is mood variability, a relatively stable characteristic of individuals (Larsen, 1987; Cooper and McConville, 1990; McConville and Cooper, 1997). Given that mood variability is linked to emotional reactivity (Eysenck and Eysenck, 1985; Hepburn and Eysenck, 1989; Williams, 1993), people with greater mood variability may be more emotionally responsive to powerful external zeitgebers (timegivers). Germane to the argument proposed in this paper is that emotional reactivity does appear to be a feature of seasonality, as people with stronger seasonality tend to score relatively high on measures of neuroticism (Murray et al., 1995; Jang et al., 1997), and are often emotionally responsive to weather conditions (Rosenthal et al., 1987; Albert et al., 1991; Molin et al., 1996). Moreover, seasonality could be conceptualised as a continuum representing increasingly stronger entrainment to the annual cycle of light, a powerful physical zeitgeber. Entrainment refers to the coupling between the timing of a rhythm and its external zeitgeber, and many human rhythms at the behavioural, physiological, and psychological level can be entrained to zeitgebers of both a physical and social nature (McGrath et al., 1984; McGrath and Kelly, 1986). If it is the case that highly seasonal individuals have generally increased mood variability, we might expect to find evidence that their moods
are more responsive to entrainment by not only light, but also zeitgebers of a social nature. Social zeitgebers are an important form of entrainment for humans. For instance, routine activities, such as work and recreation, may serve to entrain circadian rhythms (Monk et al., 1990; Ehlers et al., 1988, 1993; Elmore et al., 1994). One of the most powerful social zeitgebers in daily life is the calendar week. Because it is cyclical, the week is an important unit of temporal organisation in which certain activities and events tend to occur at predictable or usual times (Zerubavel, 1985; Huttenlocher et al., 1992). The week appears to build periodicity into mood, as several studies have documented 7-day mood cycles, with people tending to report more positive moods at weekends (Stone et al., 1985; McFarlane et al., 1988; Almagor and Ehrlich, 1990; Larsen and Kasimatis, 1990). The present study aimed to investigate whether people high in seasonality have a stronger weekly mood cycle, and whether any such effect was independent of average level of daily mood and, more germane to the present study, variability in daily mood. Mood cyclicity was explored by spectral analysis, a technique which involves analysing a time series to quantify the amplitude of any cycles in the data (Larsen, 1990). We hypothesised that the daily moods of participants high in seasonality would be more strongly entrained to a weekly cycle than the daily moods of participants low in seasonality, and that this effect will depend on mood variability. We based our hypothesis on the proposal that people high in seasonality may have greater mood variability and, as such, will be generally more responsive to entrainment by external zeitgebers such as the calendar week.
2. Method
2.1. Participants and design Sixty-four adults were recruited through adverts placed in a national magazine and in the University of Westminster student magazine, and through posters in sites throughout the University. The posters and adverts invited people with seasonal changes in mood to participate. Participants completed a report
S. Reid et al. / Journal of Affective Disorders 59 (2000) 47 – 54
form on daily mood for 56 consecutive days between 5 April 1998 and 30 May 1998. They also completed a questionnaire providing information on demographic characteristics and seasonality. Completed, useable sets of reports and questionnaires were received from 53 participants (14 males and 39 females), a response rate of 83%. The mean6SD age of participants was 28.8613.11 years for females and 34.3615.89 years for males. The majority (66%) were full-time students at the University of Westminster, whilst the remainder were either University staff (11%), or members of the general public (23%). There were no restrictions placed on those who could participate.
2.2. Materials and procedure Participants were instructed to complete their reports in the evening. The report consisted of two adjectives, ‘cheerful’ and ‘sad’, adapted from the Profile of Mood States Bipolar form (Lorr and McNair, 1984), which has been used with clinical and normal populations (Myhill and Lorr, 1985), and is sensitive to changes in mood (Benkelfat et al., 1994). For each adjective, participants indicated how well it described their mood that day, by marking a separate 90 mm line anchored either end with the phrases ‘Much like this’ and ‘Much unlike this’. Scores of the two adjectives were added (‘sad’ was reverse scored), with higher total score indicating more positive mood for that day. The scale demonstrated high internal consistency (a 5 0.92).
2.3. Questionnaire Demographic characteristics assessed were age, gender, and education. The questionnaire included the Seasonality Scale Index (SSI) of the Seasonal Pattern Assessment Questionnaire (SPAQ; Rosenthal et al., 1987). The SSI has high internal consistency (Magnusson et al., 1997), and respondents scoring 11 or more may be regarded as a potential cases of subsyndromal SAD, or full syndromal SAD if they also indicate that seasonal change is experienced as at least a moderate problem (Magnusson, 1996). Participants were instructed to complete the questionnaire on or before the start of the 56-day mood reporting period (5 April 1998).
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2.4. Data analysis 1. In order to quantify mood cyclicity, each participant’s time series of daily mood was submitted to spectral analysis. (The data were detrended first, because a time series that contains a trend violates the stationarity assumption of spectral analysis. Various windowing functions were applied to the data, but were not used in the final analysis, as they did not improve the model fit.) Spectral estimates were calculated, separately for each participant, for cycle lengths ranging from 2 to 28 days. The spectral estimates for six, seven, and eight days were added together. The resultant figure (‘weekly-cycle strength’) can be interpreted as indicating how strongly a participant’s mood is entrained to a cycle of approximately a week in length. The rationale for adding the 6-, 7-, and 8-day components is that within any individual a weekly cycle may vary slightly from week to week (frequency jitter causing what is sometimes referred to as relaxation or broadening of the spectral peak). 2. Individual differences in weekly-cycle strength with respect to SSI scores were examined. The sample was divided into two groups: those scoring 11 or more on the SSI versus those scoring under 11. (No distinction was made between SAD and S-SAD, as the SSI discriminates poorly between these conditions; Magnusson, 1996.) The mean weekly-cycle strength for each group was calculated. Adjusted means were also calculated, with average level of daily mood and mood variability (within-subjects standard error computed from mood ratings over 56-days) as separate covariates. 3. Finally, a number of t-tests and correlations were computed to address finer grain questions arising from the main analyses.
3. Results
3.1. Spectral analysis of mood Almost half of the sample (47%) scored 11 or more on the SSI, indicating that they potentially experience SAD or S-SAD, as defined by SPAQ criteria (Magnusson, 1996). The mean weekly-cycle
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strength (given in arbitrary spectral power units of mood) was greater for the high seasonal group (mean6SD spectral estimate 5 14 53568130 mood units) than for the low seasonal group (mean6SD spectral estimate 5 898068855 mood units). The difference between the groups was significant (t 5 2.37; df 5 51; P , 0.05). The difference remained robust after covarying for individual differences in average daily mood level (F 5 4.24; df 5 1.50; P , 0.05), but not after covarying for individual differences in mood variability (F 5 1.35; df 5 1.50; P . 0.05). As university studies do not require attendance at college every weekday, the strength of the zeitgeber ‘calendar week’ is possibly weaker for the students than for the other participants. However, the
mean6SD spectral estimate for the students was 12 05869190 mood units, compared with 10 70968463 mood units for the other participants, and there was no significant difference between the two (t 5 0.61; df 5 51, P . 0.05). Fig. 1 displays the mean strength (given in arbitrary spectral power units of mood) of the weekly mood cycle for the high and low seasonal groups before and after covarying separately for average mood level and mood variability.
3.2. Further analyses Mood variability was found to be positively correlated with both weekly cycle strength (r 5 0.72;
Fig. 1. Group comparisons of raw and adjusted means for strength of weekly mood cycle.
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Table 1 Average6SD mood levels a by day of week, and 2-tailed T-test comparisons b between high and low seasonal groups Day
Total sample N 5 53
High seasonal N 5 25
Low seasonal N 5 28
Comparison High versus low
Monday Tuesday Wednesday Thursday Friday Saturday Sunday
122.19621.89 118.43624.81 122.98621.83 121.16622.51 124.77624.29 126.18621.99 122.51622.80
124.24619.55 115.76623.43 119.72622.93 115.13622.64 116.80624.76 125.66620.69 119.51622.10
120.35623.99 120.81626.17 125.89620.79 126.54621.37 131.88621.92 126.65623.45 125.19623.48
NS NS NS NS NS NS NS
a b
Range of possible mood scores 5 0 (least positive / happy)–180 (most positive / happy). Corrected for multiple comparisons (~ set at 0.05 / 7 5 0.0035).
P , 0.001) and seasonality (r 5 0.29; P , 0.05). To investigate whether seasonality is associated with a tendency to have stronger mood cycles in general, the spectral estimate of each participant’s strongest mood cycle was correlated against their seasonality (SSI) score. These variables were not significantly correlated (r 5 0.20; P . 0.05). To investigate which times of the week participants’ moods were least and most positive, average mood levels were computed by day of week for the total sample, and again separately for the high and low seasonal groups. The figures displayed in Table 1 indicate that moods were least positive midweek, and most positive at the start (Friday) and middle (Saturday) of the weekend. It can be seen that there was no significant difference between the groups in average mood level by day of week. Moreover, we found no significant difference between the groups in average mood level across the 56-days of the study (t 5 1.09; df 5 51; P . 0.05).
4. Discussion The present study provides evidence that people high in seasonality are more responsive to entrainment by external zeitgebers. Besides their increased seasonality, the high seasonal group in this study had significantly stronger weekly mood cycles, and this appears to reflect stronger entrainment to a powerful social zeitgeber, the calendar week. The findings in Table 1 indicate that across the sample as a whole, average daily moods follow a traditional midweek low-weekend high pattern (cf. Stone et al., 1985; Zerubavel, 1985; McFarlane et al.,
1988; Almagor and Ehrlich, 1990; Larsen and Kasimatis, 1990; Huttenlocher et al., 1992). This pattern suggests that participants’ moods were, at least to some extent, entrained to the calendar week. A possible explanation for the stronger weekly mood cycle of the high seasonal group is that it reflects a more general phenomenon whereby the periodic component of mood displays greater amplitude in affective illness (Eastwood et al., 1985). This explanation appears to be ruled out, though, because the high seasonal group did not experience significantly lower average mood than the low seasonal group. Moreover, the spectral estimate of each participant’s strongest mood cycle was not significantly correlated with their seasonality (SSI) score, which indicates that the high seasonal group did not have stronger mood cycles in general. The results suggest instead that the stronger weekly mood cycle of the high seasonal group is linked to their greater variability in mood, which itself is strongly correlated with the strength of the weekly mood cycle. It could, of course, be argued that since mood variability was indexed by the within-subjects standard error computed from daily mood ratings, it is bound to be strongly correlated with the amplitude of mood. However, this would not explain how highly seasonal individuals come to show greater mood variability in the first place. As we indicated above, mood variability is linked to emotional reactivity (Eysenck and Eysenck, 1985; Hepburn and Eysenck, 1989; Williams, 1993), which itself appears to be a feature of seasonality (Murray et al., 1995; Jang et al., 1997). We suggest that highly seasonal individuals may have greater mood
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variability because they are more emotionally reactive, and that this could make such individuals more responsive to powerful external zeitgebers, such as environmental light and the calendar week. Moreover, as mood variability is a relatively stable characteristic of individuals (Larsen, 1987; Cooper and McConville, 1990; McConville and Cooper, 1997), our results suggest that people high in seasonality may have a relatively stable vulnerability to entraining influences. The findings that seasonality predicted differences in mood entrainment to the calendar week, and the apparent link with mood variability, does not appear to be explained by current biological models of SAD (cf. Rosenthal et al., 1988; Skwerer et al., 1988; Wehr and Rosenthal, 1989; Tam et al., 1995; Dalgleish et al., 1996; Lee et al., 1997; Sato, 1997; Young et al., 1997). Thus there may be potential benefits to integrating research on mood variability with research on SAD. In suggesting this, we are not ruling out the possibility that mood variability itself has a biological basis (Eysenck and Eysenck, 1985; McConville and Cooper, 1992). We must emphasise that our results do not demonstrate that mood variability is predictive of fullblown seasonal affective illness, as we assessed seasonality retrospectively by questionnaire, and did not investigate a clinical population. It may be noted that the length of time series of daily mood obtained in this study was 56 days, and that longer series result in more stable spectral estimates (Larsen, 1990). It may also be noted that as this study was conducted during British springtime, moods could have been affected by the variable British weather during this season (Kelly et al., 1997). The effect may be greater for the high seasonal participants whose moods are probably more responsive to weather conditions (Rosenthal et al., 1987; Albert et al., 1991; Molin et al., 1996). It may be worthwhile to extend the findings reported here by conducting investigations with SAD patients in the winter months, as this might help establish in what ways mood variability and mood cycling may be linked to symptoms of winter SAD. Any such study may wish to control for social routine stability, as this is associated with depressive symptomatology (Monk et al., 1991, 1996; Szuba et al., 1992; Prigerson et al., 1994; Brown et al., 1996),
which in turn is associated with increased mood variability (McConville and Cooper, 1996). Future studies should include emotional reactivity as a variable in its own right, as this would allow one to determine the extent to which it may mediate or moderate the relationship between mood variability and mood cycling. In conclusion, the present study provides evidence that people high in seasonality are more responsive to external zeitgebers. Besides their increased seasonality, the moods of highly seasonal participants showed stronger entrainment to a social zeitgeber, the calendar week, and this could be linked to their greater variability in mood. These findings do not appear to be explained by current biological models of SAD, and thus the integration of research on mood variability with research on SAD appears to be warranted.
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