Chronobiology International, 2014; 31(4): 523–531 ! Informa Healthcare USA, Inc. ISSN: 0742-0528 print / 1525-6073 online DOI: 10.3109/07420528.2013.874355
ORIGINAL ARTICLE
Chronotype and personality factors of predisposition to seasonal affective disorder Halszka Oginska and Katarzyna Oginska-Bruchal
The study aimed to recognize the personality factors of a predisposition to seasonal mood fluctuations in a nonclinical sample. A group of 101 subjects (57 women, 44 men; mean age 26.4 ± 6.5 years) completed a battery of tests comprising a Seasonal Pattern Assessment Questionnaire (SPAQ), Chronotype Questionnaire (ChQ), a NEO-Five Factor Inventory and a Coping Inventory for Stressful Situations (CISS). A smaller sample (n ¼ 44) completed a Winter Blues Scale (WBS). Women scored significantly higher than men in seasonality (p ¼ 0.014), neuroticism (p ¼ 0.049), agreeableness (p ¼ 0.010), and avoidance-oriented coping style (p ¼ 0.041). Subjects with seasonal affective disorder (SAD) (n ¼ 41) or sub-SAD (n ¼ 33), as diagnosed with SPAQ, exhibited higher levels of neuroticism (p ¼ 0.017) and openness (p ¼ 0.016) in comparison to non-SAD individuals. The latter declared a less frequent avoidance coping style. Both measures of seasonality, i.e. the SPAQ Global Seasonality Score and WBS, correlated significantly (r ¼ 0.28 and 0.44, respectively) with the subjective amplitude of the circadian rhythm, as described with the ‘‘distinctness’’ scale of ChQ. Female gender, neuroticism and openness were confirmed as factors linked to seasonal mood variability. Additionally, the study revealed an association between susceptibility to mild winter depression and an avoidance-oriented coping style. The avoidance coping style was correlated positively with all the aspects of seasonality described by SPAQ (correlation coefficients from 0.21 to 0.34). Both sub-types of avoidance-oriented style, i.e. distraction and social diversion, were associated with marked subjective seasonal changes in sleep length, mood and the energy level. While the subjective amplitude of circadian rhythm proved to be connected with seasonality, the subjective acrophase of the rhythm (morningness–eveningness preference) did not. It may be hypothesized that sensitivity to natural environmental conditions/synchronizers is a separate individual trait shaping the subject’s proneness to energy and mood changes both in diurnal and year scale, i.e. circadian and seasonal mood variations. Keywords: Avoidance coping, Chronotype questionnaire, coping strategies, mood changes, morningness–eveningness, openness, seasonality, winter depression
INTRODUCTION
subjective tool to identify SAD (see, e.g. Chotai et al., 2004b; Maeno et al., 2005; Øyane et al., 2010; Steinhausen et al., 2009), but not for diagnostic purposes. First, our sample is non-clinical and, second, we were aware of the fact that the questionnaire does not provide a clinical diagnosis – the history of the disorder, its recurrence, remission in warm seasons, etc., should be discussed in a direct interview with a patient. Therefore, we prefer to use here the terms ‘‘susceptibility’’, ‘‘predisposition’’, or ‘‘proneness’’ to seasonal depression, as described within SPAQ. SAD is likely to have a quite complex aetiology influenced by several variables, including genetic vulnerability, environment, socio-cultural context and psychosocial factors. We understand SAD as an extreme form of ‘‘seasonality’’, sensitivity to the changing seasons of the year or, more precisely, to external
Almost 30 years after the first description of seasonal affective disorder (SAD) by Rosenthal et al. (1984), the phenomenon is still a hot topic of discussion among psychiatrists. Although it has been officially introduced into the Diagnostic and Statistical Manual (DSM), the final opinion on whether SAD is indeed a ‘‘valid’’ and specific disorder, is far from unanimous (see, e.g. Michalak & Lam, 2002 vs. Grof, 2002, or a critique by Hansen et al., 2008). In the DSM-IV classification, SAD was defined as a sub-type of a Major Depressive Disorder (MDD) with a seasonal pattern. This definition is unchanged in DSM-5, launched in 2013, which means that calls for a more specific distinct diagnosis have not been supported. In this study, we have used the Seasonal Pattern Assessment Questionnaire (SPAQ), the most popular
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Department of Neuroergonomics, Institute of Applied Psychology, Jagiellonian University, Krakow, Poland
Submitted August 15, 2013, Returned for revision December 8, 2013, Accepted December 9, 2013
Correspondence: Halszka Oginska, Department of Neuroergonomics, Institute of Applied Psychology, Jagiellonian University, Lojasiewicza 4, Krakow 30-348, Poland. E-mail: [email protected]
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H. Oginska & K. Oginska-Bruchal
climatic conditions and a daily photo-period in a given location (which is strongly related to its latitude). This extreme seasonality resembles an animal’s ability to hibernate in order to survive an adverse, cold season. It seems unwanted and useless in the contemporary world, a throwback of the evolutionary process. Reduced energy in winter means less willingness to meet the challenges of everyday tasks which do not usually follow the seasonal pattern. In addition to a depressed mood, SAD syndrome is characterized by a set of so-called atypical symptoms, such as longer sleep, increased appetite, craving for sweets and/or carbohydrate-rich food and, in consequence, gaining weight. This may be seen as a kind of ‘‘resource saving’’ behaviour. Large epidemiological studies (over 11 500 participants) showed that a high level of self-reported seasonality was associated with objective health risk factors (Øyane et al., 2010). SAD probably results from a complex interplay between environmental and individual biological and psychological factors. In search of individual ‘‘risk factors’’, personality studies were conducted mainly in clinical samples. Enns et al. (2006) compared the scores – using the five-factor model of personality – of SAD patients with a matched group of non-seasonal depressed patients and published normative data. SAD patients showed elevated openness scores relative to both non-seasonal depression patients and norms. Their neuroticism scores were higher than the norms (but lower than those of the non-seasonal patients). Jain (1999) also found higher scores in the openness domain in SAD patients. Moreover, this was true even after light treatment and, according to the author, may be seen as an enduring characteristic of patients with SAD. This is consistent with previous research by Bagby et al. (1996), who compared two sub-types of patients with major, non-psychotic depression with and without seasonality. Patients were assessed during an acute depressive episode and while controlling the severity of the depression, a difference was found in only one of the five dimensions, namely openness. A study done in a random community sample in Australia (n ¼ 303) by Murray et al. (2002) seasonality was measured not as a retrospective self-description, but as a prospective pattern of current mood states in winter and summer, across two years. Here again, openness appeared to be connected with the tendency of a lowered mood in winter relative to summer. Ennis & McConville (2003) showed that profound seasonal disturbances in mood and behaviour were associated with increased levels of neurotic personality traits but the degree of seasonal variation in mood and behaviour was equally well-explained in terms of ‘‘impulsivity’’. Later, Ennis & McConville (2004) studied the daily mood profiles of 59 subjects during the months of January and February and found that mood variability was significantly and positively associated with seasonality. Chotai et al. (2004b) discovered that individuals
who reported feeling at their worst in winter (and also those feeling at their worst in summer) exhibited high ‘‘harm avoidance’’ as assessed by the Temperament and Character Inventory. Finally, Maeno et al. (2005), in a study involving 6135 Japanese, found the same tendency (a higher harm avoidance score) in individuals with the summer form of SAD. In order to better understand the mechanism and development of SAD, Sigmon et al. (2006) proposed to investigate similarities and differences in stress reactivity, coping strategies and psychosocial stress impact in individuals with seasonal and non-seasonal depression. Greater psychophysiological reactions to laboratory stressors were observed in subjects in the non-seasonal group. No significant differences in the reported use of problem- and emotion-focused coping strategies were found between the groups. Neither were there any significant differences in acceptance coping use by individuals in the two depressed groups and both MDD-SAD patients (n ¼ 19) and MDD patients (n ¼ 17) reported a greater use of avoidance coping (as described by the COPE questionnaire) compared with controls. Coping strategies are partly controlled by personality and partly by social context. It can be supposed that the use of maladaptive coping strategies results in increased vulnerability to depression and the tendency to experience a more depressed mood when exposed to stressful situations. The term ‘‘chronotype’’ is used to describe relatively stable traits of the subjective diurnal rhythm of activity, characteristic of the individual – it may be considered an element of personality. Traditionally, it refers to the subjective morning-evening preference, i.e. the selfreported ‘‘feeling best’’ and ‘‘best performance’’ times of day. Sleep-wake behaviour is the key question here. Although fundamental to describe circadian functioning, the subjective phase is not the only parameter needed to characterize the chronotype. The strength of preferences, i.e. the distinctness of the circadian variability in activation levels (or subjective amplitude) should also be taken into account. Most of the tools used in chronotype studies are limited to only one dimension, i.e. to the morningness scale. Chronotype and seasonality represent two facets of an individual’s adjustment to exogenous biological rhythms – daily and yearly changes in the external environment associated with the Earth’s rotation and movement. Both chronotype and seasonality are connected with melatonin secreted by the pineal gland, under the influence of the circadian mechanism on the one hand, and external light exposure on the other hand. A study reported by Wehr (2005) comparing SAD patients with healthy controls suggested that SAD people respond to the external changes in a photoperiod in a manner similar to other mammals (longer melatonin secretion time in winter than in summer), while healthy people seem to have lost this property (having a similar length of melatonin secretion in warm and cold Chronobiology International
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Chronotype, personality and seasonality seasons). It is possible that the retention of this ability to track seasons in this way might explain the seasonal presentation of the disorder in SAD people. In view of the above, it is strange that very few studies have looked for a connection between circadian type and symptoms of SAD in its winter form, although the link between the eveningness and depressive moods has been observed. The ‘‘phase shift hypothesis’’ of SAD by Lewy et al. (1987, 2006) posited a delay in internal circadian rhythms relative to the external clock to be crucial in understanding the disorder and the effectiveness of light therapy. It could be assumed that late (evening) chronotypes are those who tend to show SAD symptoms more often than others; however, it was not stated explicitly. In the context of this hypothesis, Murray et al. (2005) tested whether fluoxetine and light treatments for SAD patients do operate by advancing the circadian phase. They have found that both treatments resulted in a significant antidepressant effect and phase advance but the degree of symptom change did not correlate with the degree of phase change. There is no evidence to suggest that circadian phase advance mediates the therapeutic mechanism. However, in a recent study, Lee et al. (2011) suggested that delayed sleep phase syndrome (DSPS) and SAD may share a pathophysiological mechanism that causes a delayed circadian phase. DSPS patients showed higher seasonality scores, compared with controls, in mood, appetite, energy level and winter–summer differences in sleep length and weight. SAD and sub-SAD subjects reported higher eveningness. Natale et al. (2005) found a slight but significant negative correlation between the morningness score (Morningness–Eveningness Questionnaire (MEQ) by ¨ stberg) and seasonality (Global Seasonality Horne and O Score – GSS, from SPAQ), with a significantly higher incidence of evening vs. morning types among students with seasonal depression. But in the prospective study evening types did not present a higher annual range of mood variations than morning ones. According to the authors, ‘‘caution should be exercised in ascribing eveningness as a risk factor in SAD since other underestimated factors, including social-cultural conditions, might be involved in the pathogenesis of mood seasonality’’. In a group of Finnish twins with bipolar disorder, Hakkarainen et al. (2003) found that patients were no more likely to be an evening type than their healthy cotwins. However, they did discover a connection between the preference for evening activities and a higher GSS after accounting for gender, age, zygosity and mental health. This correlation was seen only in the total score, with no significant associations between the circadian type and the seasonal changes in length of sleep, weight or appetite. All of the aforementioned research is based on only one characteristic of diurnal rhythm, namely the subjective phase, referred to as ‘‘morningness’’ or !
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‘‘morningness–eveningness (ME)’’. The present study included the Chronotype Questionnaire (ChQ) (Ogin´ska, 2011) that refers to two dimensions: the subjective phase (morning–evening preference) and subjective amplitude (i.e. distinctness) of the circadian rhythm of activation. The aim of the study was to recognize chronotype and other personality factors linked to the predisposition to seasonal affective fluctuations in a non-clinical sample. Studies conducted in healthy populations are free from the masking effects of drug administration, hospital stays (limited activity and disruption of daily habits) and other conditions that may modulate the well-being of patients. Exploring personality correlation in SAD-prone individuals may bring new ideas as regards both the aetiology of this disorder and its treatment, especially in terms of ‘‘client-tailored’’ therapy.
MATERIALS AND METHODS Location and participants The study was conducted in Krakow, south Poland (500 0300 latitude and 190 5600 longitude), a town of about 760 thousands inhabitants, which is a vivid and vibrant cultural and student centre with almost round-the-clock activity. The studied group was made up of mainly young urban professionals and final-year students who were often in concurrent employment. One hundred and one people (57 women and 44 men) with a mean age of 26.4 ± 6.5 years were recruited. This age group was deliberately selected since, according to the literature, SAD typically manifests between 20 and 30 years of age (Magnusson & Partonen, 2005). Over 240 questionnaires were distributed and less than 50% were returned. Global Seasonality Score (SPAQ) The GSS is the central sub-scale of the SPAQ, elaborated by Rosenthal (1993, 2005). It asks the subject to rate the degree of seasonal variation he/she experiences in six areas – sleep, social activity, mood, weight, appetite and energy level. There is a 5-point answer option: from 0 – ‘‘no change’’, to 4 – ‘‘extremely marked change’’. The sum produces a GSS, ranging from 0 to 24. According to Rosenthal’s criteria, a subject with GSS of 11 points or more, feeling worst in December–February and experiencing seasonal changes as a problem to at least a ‘‘moderate’’ degree is considered to have SAD. Subsyndromal SAD is diagnosed when a subject reports the same months as ‘‘the worst’’ and scores at least 10 points, even if she/he reports ‘‘no problem’’, or scores 8–9 points and estimates the problem at least as ‘‘mild’’. Although there are some doubts about the accuracy of SPAQ because of its tendency to provide a false positive diagnosis, this questionnaire remains the most widespread tool used in epidemiologic research, allowing for intercultural comparisons. SPAQ is not sensitive enough to be considered a diagnostic instrument for SAD, but it is accurate enough to be used as a screening instrument (Mersch et al., 2004). The Global Seasonality
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Scale, consisting of two factors (a food factor and a psychological one) has good internal consistency (Mersch et al., 2004). According to Steinhausen et al. (2009), SPAQ as the sole measurement leads to an overestimation of SAD – its prevalence based on this single test was almost 8%, while the addition of a second method brought it down to 2%. Nevertheless, seasonal mood variations seem to be a rather common phenomenon in the population of central Europe – in a Swiss community study, sub-syndromal SAD was diagnosed in 33% of cases.
Winter Blues Scale With the potential flaws of SPAQ in mind, the authors decided to use an additional method, the Winter Blues Scale (WBS), which was administered to the smaller sample of participants (n ¼ 44), i.e. only to those who were examined in January and February. The WBS looks to identify SAD symptoms more directly than GSS. The scale was developed during a research project conducted in 2004 regarding the seasonal aspects of drowsiness in workplaces (Ogin´ska, 2005). It examines 21 symptoms of seasonal depression (chosen from a list of 50 subjective complaints by means of discrimination analysis) in 7 areas: sleepiness, appetite, mood, socialization, energy, libido and ‘‘general malaise’’. The subjects are asked to rate how much each symptom applies to them on a 4-point scale. The WBS is not a diagnostic tool, it is aimed at mild, sub-clinical forms of winter depression. Cronbach’s alpha for WBS reached 0.90; individual scores for a group of 96 psychology students showed significant correlation with GSS (r ¼ 0.63; p50.001). Chronotype Questionnaire The ChQ (Ogin´ska, 2011) consists of two scales which refer to two important parameters of diurnal subjective activation rhythm: acrophase (eight-item ‘‘ME’’ scale) and amplitude (six-item ‘‘distinctness of the rhythm’’ scale – DI). Both scales show satisfactory psychometric properties (Cronbach’s alpha 0.82–0.84 for ME and 0.61–0.72 for DI scale) if used with adults. The subjective phase, reflected by morning–evening orientation, regards awareness of one’s own possibilities and limitations, preferences and unwillingness to undertake activities at various times of day. The scale does not refer to clock hours, but is aimed at a variety of functional states: mood, attention, energy level, efficiency, etc., in the diurnal time frame. Subjective amplitude or the range of circadian variations manifests as the ‘‘distinctness’’ of daily activation changes, the feeling (or lack thereof) of difference between hyperand hypo-activation phases. While the ME scale has proved to be psychometrically robust (Oginska et al., ´ ska, 2011) and shows strong correlation with 2010; Ogin the classic MEQ (Dosseville et al., 2013), the DI scale was apparently weaker. However, it correlated significantly with the range of diurnal variations in energy levels, as
described by Thayer’s adjective list (Ogin´ska, 2011). Morningness and distinctness scales are independent variables, except for younger subjects (adolescents), in which associations between ME and DI scales are often observed – young evening types show strong preferences as to their ‘‘best time of day’’.
NEO-Five Factor Inventory This classic tool for describing personality dimensions was proposed by Paul Costa and Robert McCrae in the early 1990s. Their five-factor model: neuroticism, extraversion, openness to experience, agreeableness and conscientiousness (NEOAC) are known as The Big Five. The NEOAC structure allows the prediction of the academic and professional success of an individual, his/ her state of health and life satisfaction. It is also connected with individual coping strategies and cognitive functioning. A Polish adaptation of the questionnaire has been developed by Zawadzki & Strelau (1998). Coping inventory for stressful situations Seasonal climate changes may be regarded as a specific form of stress. We decided to broaden the classical personality description with a coping style questionnaire. CISS refers to Lazarus and Folkman’s transactional model of stress – coping strategies are related to an individual’s approach to stressful life events. Specific coping styles can either promote mental and physical health or aggravate health problems. The questionnaire was proposed by Endler and Parker around 1990 and measures three main coping strategies: task focused – dealing with the problem at hand, emotion-focused – concentrating on the resultant emotions, and avoidance coping – trying to avoid the problem. Avoidanceoriented strategies comprise two sub-types: distraction and social diversion. In general, task-oriented coping styles are positively related to adaptability and good health, while emotion-oriented styles are the opposite. The results for avoidance-oriented coping and adaptation are equivocal (Cosway et al., 2000). This may be related to the complex composition of this factor. Depression was found to correlate negatively with social diversion, but it showed no relationship with distraction. The questionnaire was adapted for a Polish population by Strelau et al. (2005). The protocol for this study complied with the ethical standards of the journal for the conduct of human biological rhythm research (Portaluppi et al., 2008). The statistical analyses (correlation and regression analyses and analysis of variance (ANOVA)) were performed with use of SPSS 11.0 for Windows (SPSS Inc., Chicago, IL) and IBM SPSS Statistics for Windows, Version 20.0 (IBM Corp., Armonk, NY). RESULTS The GSS showed a normal distribution, with a mean of 12.4 points and SD 5.2. This is higher than any other Chronobiology International
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Chronotype, personality and seasonality group studied previously. The gender aspect should be taken into account – women scored significantly higher than men (Table 1). Only 15% of women did not experience seasonal changes in well-being, while twice as many male participants (30%) were ‘‘not seasonal’’. Women experienced more distinct changes in all the aspects listed in SPAQ. The most important difference between male and female subjects regarded changes in appetite, which were perceived mostly by women as connected with the seasons of the year (40.7% female vs. 14.6% male). Yet, gender does not differentiate the general pattern of seasonality, in that affective symptoms (mood and energy) are higher in proportion than atypical symptoms (sleep, weight, appetite and social activity) (Figure 1). Apart of seasonality, significant gender differences were observed in personality dimensions (neuroticism and agreeableness – higher in female subjects) and coping strategies. Women scored visibly higher on the avoidance-oriented scale (and in its sub-scale relating to distraction) and tended to apply more emotion-oriented strategies and fewer task-oriented strategies (p 0.07). The difference (at the limit of significance) between men and women was observed in the distinctness scale of the ChQ – females showed a larger subjective amplitude of the circadian rhythm. A comparison of the groups of subjects with SAD (n ¼ 41), sub-SAD (n ¼ 33), and non-SAD (n ¼ 21), distinguished on the basis of SPAQ classification rules, exposed significant differences in two personality traits: neuroticism (ANOVA: F(2, 93) ¼ 4.278, p ¼ 0.017) and openness (F(2, 93) ¼ 4.330, p ¼ 0.016). The sub-groups’ scores did not differ in extraversion, agreeableness and conscientiousness scales (Figure 2a). The most notable difference between the groups concerned avoidanceoriented coping strategies (ANOVA: F(2, 93) ¼ 6.192, p ¼ 0.003; Figure 2b). The results described above were confirmed by correlation analysis: the GSS correlated positively with
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neuroticism (r ¼ 0.33, p ¼ 0.006), openness (r ¼ 0.24, p ¼ 0.018), and avoidance strategy (r ¼ 0.38, p50.001), while higher results on the WBS linked to avoidance coping only (r ¼ 0.32, p ¼ 0.035, n ¼ 44). Moreover, both seasonality measures, GSS and WBS turned out to be
FIGURE 1. SPAQ: ‘‘To what degree do the following change with the season?’’ Percentage of subjects describing seasonal fluctuations in various spheres of well-being as ‘‘marked change’’ or ‘‘extremely marked change’’ (n ¼ 101).
TABLE 1. Average results (means and SD) of female and male participants in the study. ANOVA Females (n ¼ 57) Age SPAQ – GSS ChQ – ME ChQ – DI NEO-FFI – Neuroticism NEO-FFI – Extraversion NEO-FFI – Openness NEO-FFI – Agreeableness NEO-FFI – Conscientiousness CISS – Task orientation CISS – Emotion CISS – Avoidance CISS – Distraction CISS – Social diversion !
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Males (n ¼ 44)
27.0 ± 6.5 25.7 ± 5.9 13.6 ± 4.8 10.9 ± 5.4 26.2 ± 9.7 25.5 ± 9.5 20.7 ± 5.3 18.5 ± 5.9 24.4 ± 8.8 21.02 ± 8.1 28.3 ± 6.7 28.9 ± 5.8 30.6 ± 5.1 28.8 ± 5.7 29.1 ± 6.6 25.7 ± 5.9 30.2 ± 7.0 29.8 ± 8.2 58.0 ± 7.6 60.9 ± 8.3 47.4 ± 9.9 43.3 ± 12.9 45.8 ± 8.9 42.1 ± 9.2 20.0 ± 5.7 17.6 ± 5.8 17.4 ± 3.8 16.3 ± 3.5
F
p
1.030 6.261 0.102 3.823 3.978 0.201 2.344 6.965 0.010 3.430 3.282 4.276 4.228 2.099
0.313 0.014 0.750 0.053 0.049 0.655 0.129 0.010 0.919 0.067 0.073 0.041 0.042 0.151
FIGURE 2. Personality traits (a) and coping strategies (b) in SAD, sub-SAD, and non-SAD subjects, as defined by SPAQ criteria.
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H. Oginska & K. Oginska-Bruchal
linked significantly with the distinctness scale of the ChQ – correlation coefficients amounted to 0.28 (p ¼ 0.006) and 0.44 (p ¼ 0.003), respectively. A multiple regression check was run to test if seasonality (GSS) may be predicted from four variables identified in the course of previous analyses (neuroticism, openness, avoidance coping and subjective circadian amplitude). Two variables significantly predicted the GSS: F(4, 89) ¼ 7.126, p ¼ 0.025, R2 ¼ 0.243. Avoidance coping added most to the prediction ( ¼ 0.258, p ¼ 0.011), followed by neuroticism ( ¼ 0.197, p ¼ 0.050), while openness did not reach statistical significance ( ¼ 0.175, p ¼ 0.064). Interestingly, in the case of the WBS score, the analogical multiple regression analysis gave quite different results – the subjective circadian amplitude was the only significant predictor: F(4, 39) ¼ 3.136, p50.001, R2 ¼ 0.243, with coefficient of 0.356, p ¼ 0.023. The following analysis concerned the personality and coping styles of four chronotypes distinguished on the basis of the ChQ. Due to the relatively small group, the medians were taken as cut-off points to delineate the sub-groups according to the configuration of morning– evening and distinctness scales: definite-morning (or ‘‘strong larks’’ – morning orientation, large amplitude), moderate morning (or ‘‘weak larks’’ – morning orientation, small amplitude), moderate evening (or ‘‘weak owls’’ – evening orientation, small amplitude) and definite evening (or ‘‘strong owls’’ – evening orientation, large amplitude). Individuals representing ‘‘moderate morning’’ preferences differed clearly from other types, showing lower seasonality, lower neuroticism and less emotion-oriented and avoiding-oriented coping in stressful situations (Table 2). Chronotype dimensions, if considered separately, revealed different strengths of relationship with personality factors. ME preference did not show significant connections with any of the parameters studied, while the DI demonstrated associations with neuroticism and all three coping styles defined by CISS. A larger subjective amplitude correlated negatively with task-oriented strategies and positively with emotion- and avoidance-oriented coping styles (Table 3).
Finally, the avoidance-oriented coping style was revealed to correlate positively with all six aspects of seasonality. Both sub-types of avoidance-oriented style, i.e. distraction and social diversion, proved to be related to more marked seasonal changes in sleep length, mood and energy level (Table 4). TABLE 3. Simple correlation coefficients of chronotype dimensions, seasonality scores and personality traits studied. ME
GSS WBS Neuroticism Extraversion Openness Agreeableness Conscientiousness Task coping Emotion coping Avoidance coping
DI
n
Corr. Coeff.
p
Corr. Coeff.
p
95 44 98 98 98 98 98 101 101 101
0.185 0.065 0.109 0.012 0.157 0.128 0.110 0.073 0.124 0.137
n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s.
0.282 0.437 0.303 0.074 0.092 0.251 0.022 0.192 0.302 0.283
0.006 0.003 0.002 n.s. n.s. n.s. n.s. 0.055 0.002 0.004
TABLE 4. Coping strategies and susceptibility to seasonal changes in mood and behaviour (simple correlation coefficients, n ¼ 95). Seasonality aspects
Task- Emotion- AvoidanceSocial oriented oriented oriented Distraction diversion
Sleep length R Sig.
0.087 0.402
0.123 0.236
0.341 0.001
0.217 0.034
0.388 0.000
Social activity R Sig.
0.157 0.130
0.155 0.135
0.210 0.041
0.158 0.125
0.188 0.068
Mood R Sig.
0.166 0.109
0.152 0.141
0.296 0.004
0.257 0.012
0.205 0.047
Weight R Sig.
0.162 0.116
0.107 0.302
0.295 0.004
0.265 0.010
0.148 0.152
0.105 0.311
0.009 0.929
0.215 0.037
0.199 0.053
0.142 0.169
0.027 0.798
0.163 0.115
0.290 0.004
0.205 0.047
0.268 0.009
Appetite R Sig. Energy level R Sig.
TABLE 2. The results of ANOVA in four chronotype sub-types: seasonality, personality traits and coping strategies. ‘‘Strong lark’’
GSS WBS Neu Ext Opn Agr Con CISS-task CISS-emo CISS-avoid
‘‘Weak lark’’
‘‘Weak owl’’
‘‘Strong owl’’
n
Mean ± SD
n
Mean ± SD
n
Mean ± SD
n
Mean ± SD
ANOVA F/p
20 10 20 20 20 20 20 21 21 21
13.8 ± 5.2 15.4 ± 11.2 26.1 ± 5.6 27.6 ± 4.9 29.4 ± 5.1 29.3 ± 3.9 30.1 ± 5.6 59.4 ± 7.2 48.5 ± 7.8 45.5 ± 8.9
25 11 27 27 27 27 27 27 27 27
9.8 ± 5.2 6.4 ± 6.3 19.3 ± 8.0 29.8 ± 6.1 29.2 ± 6.2 27.5 ± 5.6 32.6 ± 7.0 60.6 ± 6.9 40.2 ± 12.8 40.3 ± 8.7
23 9 24 24 24 24 24 25 25 25
12.9 ± 4.9 8.0 ± 4.2 22.4 ± 8.9 27.8 ± 7.5 30.1 ± 5.7 27.8 ± 7.5 29.0 ± 7.9 60.4 ± 8.6 46.0 ± 11.6 44.0 ± 9.2
27 14 27 27 27 27 27 28 28 28
13.5 ± 4.8 15.6 ± 10.2 24.8 ± 9.9 28.9 ± 6.6 30.7 ± 4.8 26.2 ± 7.8 28.0 ± 8.6 56.9 ± 9.0 48.3 ± 10.8 47.2 ± 8.9
3.177/0.028 3.466/0.025 3.084/0.031 n.s. n.s. n.s. n.s. n.s. 3.192/0.027 2.881/0.040
Chronobiology International
Chronotype, personality and seasonality
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DISCUSSION The average GSS score was surprisingly high in the study participants. In preliminary research conducted previously with a group of 95 psychology students (80% female) the mean GSS was 9.2 ± 4.7 points. Both results are higher than those cited in the existing literature. According to Lam & Levitt (1999), the average GSS in general community samples is about 5 points, while SAD patients score about 16 points. The non-random method of recruiting participants to the study might have affected the results, as the forms were filled in by those interested in the topic. Also, the 22–30 age group focus may have played a role, as this is the period when SAD typically manifests and symptoms may be particularly intense. Nevertheless, such limitations do not undermine the essence of the cross-sectional analysis which focused on associations between personality traits and seasonal mood changes. Seasonality has been recognized as a phenomenon strongly connected with gender. Our study confirmed this observation, additionally pointing to some chronotype differences between men and women, namely in the subjective distinctness of the circadian rhythm. It may be hypothesized that women are more sensitive to changes in their mood and alertness (or they are better self-observers). Does this mean that females are generally more ‘‘rhythmic’’ than males? Natale & Danesi (2002) suggested that a genetically programmed circamensual rhythm in women may contribute to a less flexible circadian system also less adaptable to environmental changes. Having a ‘‘distinct’’ rhythm may indeed be understood as having a ‘‘stable’’ or ‘‘less flexible’’ rhythm. According to Chotai et al. (2004a), these subtle gender differences in perceiving the symptoms of seasonality and their importance may be an indication of different mechanisms for male and female SAD and for the need for different methods of effective therapy. The configuration of NEOAC factors in our sample is typical for both genders, however, according to Zawadzki & Strelau (1998), in Polish samples women also scored higher in extraversion, openness and conscientiousness. Coping strategies used by men and women are different, according to Strelau et al. (2005), only as regards emotion-oriented strategies. In our sample women scored visibly higher on the avoidanceoriented scale (and in its sub-scale relating to distraction) and tended to apply more emotion-oriented strategies and fewer task-oriented strategies (p 0.07). Our analyses are in line with the results of previous personality studies conducted in clinical samples and showing higher levels of ‘‘openness’’ in SAD patients (Bagby et al., 1996; Enns et al., 2006; Jain et al., 1999; Murray et al., 2002). It is not easy, however, to interpret the higher vulnerability to seasonal changes in subjects who are ‘‘open to experience’’, i.e. show more imagination, aesthetic sensitivity and intellectual curiosity. One possible explanation could be that the same mechanism !
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drives individual openness to the social and physical environment – interest in the external world augments the reaction to all the changes that are observed, including those regarding light, noise, temperature and other factors that define weather or season. Besides, openness also means being receptive to inner emotional states that mean open people are more aware of their own feelings, sensations and moods. According to McCrae & John (1992) openness is the most controversial of the five factor personality model. It is often seen as an intellectual feature, forming an important part of consciousness and affecting social perceptions. The authors argue that ‘‘O includes aspects of intellect, but is considerably broader in scope’’ and shall be seen also in terms of a motivation theory, as a need for variety and experience. It may be associated with quite ‘‘esoteric’’ phenomena such as chills in response to sudden beauty, the experience of de´ja` vu, and homesickness for the unknown (McCrae and Sutin, 2009). Openness to experience, as a personality factor, is connected to divergent thinking and creativity. Norman Rosenthal in his Winter Blues (1993) pointed to the increased vulnerability to seasonal depression observed in poets, artists and other creative individuals. He brought up a remark by Aristotle who described the outstanding personalities in philosophy, politics, poetry and arts as showing melancholic tendencies. Although much research has shown that creative behaviour is often associated with the risk of depression, the mechanism is still unclear. Verhaeghen et al. (2005) posited that there is third underlying factor, namely a self-reflective rumination that may explain this connection. Using path analysis, the authors found that rumination was related to objectively measured creative fluency, originality and elaboration. As no link exists between depressed moods and creative behaviours, rumination seems to be the sole factor explaining the association between depression and creativity. Our study showed another link to personality traits in season-vulnerable subjects, stemming from the analysis of CISS results. SAD-prone individuals exhibited higher scores in avoidance-oriented coping. This tallied with the results of Sigmon et al. (2006) obtained with a different coping questionnaire. Indeed, the description of avoidance-coping strategies pertains to the characteristic behaviour of a seasonally depressed person. Typical strategies for surviving an unfavourable situation include overeating, sleeping or retreating into a different activity that leads to temporary relief (watching TV or other substitute actions). Such an attempt to wait out the uncomfortable situation brings to mind the strategy well known from the animal world as hibernation. The question arises whether extreme seasonality is the human equivalent of hibernation? (Cizza et al., 2011). It is important here to differentiate psychological coping strategies and ‘‘defence mechanisms’’ – the former are applied consciously. This means there are
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chances to work on them during a therapeutic process, e.g. with a cognitive-behavioural approach. The chronotype dimensions did show different relations with seasonality. ME was not confirmed as a ‘‘risk factor’’. This is in line with the results of Natale et al. (2005). The second chronotype aspect proposed here – the ‘‘subjective amplitude’’, was shown to be linked to seasonality scores. Indirect confirmation of this result may be found in the study of Ennis and McConville (2004) who found seasonality unrelated to average mood levels, but with a significantly positive association with mood variability, as defined by the Positive and Negative Affect Schedule questionnaire completed twice daily over two weeks. It is worth noting that the greater diurnal variability of moods predicts a positive reaction to light therapy (Wirz-Justice, 2000), as well as a potent antidepressant response to sleep deprivation (Wirz-Justice, 2008). There are some limitations in interpreting the results referring to subjective amplitude due to the weakness of the DI (distinctness) scale in the ChQ. It revealed the poor psychometrics in the French version (Dosseville et al., 2013) and a lower reliability than the ME scale in the Polish version (Ogin´ska, 2011). Nevertheless, this original DI scale proved to correlate with the range of diurnal variations in the self-reported level of energy (Ogin´ska, 2011). According to Murray et al. (2002), two affective processes that seem to be involved in mood variations across a seasonal time frame, can be named as adaptive environmental sensitivity and endogenous mood variability. One may assume that both point to the distinctness of the biological rhythm. Recent theories on the pathophysiology of SAD include both a vulnerability to depression (and its neurotransmitter regulation) and another factor responsible for the seasonal course it takes. This was called by Young (1999) The Dual Vulnerability Hypothesis. The main mechanisms thought to shape individual seasonality are: circadian rhythms, photoperiod-melatonin and retinal sensitivity to light. The simple cross-sectional questionnaire survey presented here cannot add to the understanding of the pathophysiologic mechanism of the disorder. However, it is worth noting that our findings, pointing to a specific configuration of personality and chronotype traits, are coherent with the twofactor model of SAD: higher levels of neuroticism and openness – a characteristic for depressive individuals – on the one hand, and on the other, a larger subjective amplitude of the rhythm, indicating sensitivity to environmental synchronizers. It may be argued that a convergence of those traits with an avoidance coping style enhances seasonality.
CONCLUSIONS In summary, the analyses of mood seasonality performed in a non-clinical sample are consistent with
previous research pointing to increased neuroticism and openness as personality factors characterizing the SAD-prone subjects. The study revealed some new associations between the susceptibility to mild winter depression and an avoidance coping strategy as measured by the CISS. The subjective amplitude of circadian rhythm showed to be another related factor, while the traditionally understood chronotype, defined solely by the subjective acrophase of the rhythm (ME preference), did not prove to have any relation to it. It may be hypothesized that sensitivity to natural environmental conditions is a separate individual trait shaping the subject’s proneness to mood changes, both in diurnal and year scales, i.e. circadian and seasonal fluctuations.
ACKNOWLEDGMENTS The data have been collected in the fulfilment of master thesis prepared by Katarzyna Oginska, under the supervision of professor Leszek Pawlowski at the Institute of Applied Psychology of the Jagiellonian University. The Winter Blues Scale has been elaborated in frame of research project No. 501/PKL/146/L (headed by H. Oginska) at the Jagiellonian University Medical College.
DECLARATION OF INTEREST The authors report no conflicts of interest. The authors alone are responsible for the content and writing of this article.
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ORIGINAL ARTICLE
Chronotype and personality factors of predisposition to seasonal affective disorder Halszka Oginska and Katarzyna Oginska-Bruchal
The study aimed to recognize the personality factors of a predisposition to seasonal mood fluctuations in a nonclinical sample. A group of 101 subjects (57 women, 44 men; mean age 26.4 ± 6.5 years) completed a battery of tests comprising a Seasonal Pattern Assessment Questionnaire (SPAQ), Chronotype Questionnaire (ChQ), a NEO-Five Factor Inventory and a Coping Inventory for Stressful Situations (CISS). A smaller sample (n ¼ 44) completed a Winter Blues Scale (WBS). Women scored significantly higher than men in seasonality (p ¼ 0.014), neuroticism (p ¼ 0.049), agreeableness (p ¼ 0.010), and avoidance-oriented coping style (p ¼ 0.041). Subjects with seasonal affective disorder (SAD) (n ¼ 41) or sub-SAD (n ¼ 33), as diagnosed with SPAQ, exhibited higher levels of neuroticism (p ¼ 0.017) and openness (p ¼ 0.016) in comparison to non-SAD individuals. The latter declared a less frequent avoidance coping style. Both measures of seasonality, i.e. the SPAQ Global Seasonality Score and WBS, correlated significantly (r ¼ 0.28 and 0.44, respectively) with the subjective amplitude of the circadian rhythm, as described with the ‘‘distinctness’’ scale of ChQ. Female gender, neuroticism and openness were confirmed as factors linked to seasonal mood variability. Additionally, the study revealed an association between susceptibility to mild winter depression and an avoidance-oriented coping style. The avoidance coping style was correlated positively with all the aspects of seasonality described by SPAQ (correlation coefficients from 0.21 to 0.34). Both sub-types of avoidance-oriented style, i.e. distraction and social diversion, were associated with marked subjective seasonal changes in sleep length, mood and the energy level. While the subjective amplitude of circadian rhythm proved to be connected with seasonality, the subjective acrophase of the rhythm (morningness–eveningness preference) did not. It may be hypothesized that sensitivity to natural environmental conditions/synchronizers is a separate individual trait shaping the subject’s proneness to energy and mood changes both in diurnal and year scale, i.e. circadian and seasonal mood variations. Keywords: Avoidance coping, Chronotype questionnaire, coping strategies, mood changes, morningness–eveningness, openness, seasonality, winter depression
INTRODUCTION
subjective tool to identify SAD (see, e.g. Chotai et al., 2004b; Maeno et al., 2005; Øyane et al., 2010; Steinhausen et al., 2009), but not for diagnostic purposes. First, our sample is non-clinical and, second, we were aware of the fact that the questionnaire does not provide a clinical diagnosis – the history of the disorder, its recurrence, remission in warm seasons, etc., should be discussed in a direct interview with a patient. Therefore, we prefer to use here the terms ‘‘susceptibility’’, ‘‘predisposition’’, or ‘‘proneness’’ to seasonal depression, as described within SPAQ. SAD is likely to have a quite complex aetiology influenced by several variables, including genetic vulnerability, environment, socio-cultural context and psychosocial factors. We understand SAD as an extreme form of ‘‘seasonality’’, sensitivity to the changing seasons of the year or, more precisely, to external
Almost 30 years after the first description of seasonal affective disorder (SAD) by Rosenthal et al. (1984), the phenomenon is still a hot topic of discussion among psychiatrists. Although it has been officially introduced into the Diagnostic and Statistical Manual (DSM), the final opinion on whether SAD is indeed a ‘‘valid’’ and specific disorder, is far from unanimous (see, e.g. Michalak & Lam, 2002 vs. Grof, 2002, or a critique by Hansen et al., 2008). In the DSM-IV classification, SAD was defined as a sub-type of a Major Depressive Disorder (MDD) with a seasonal pattern. This definition is unchanged in DSM-5, launched in 2013, which means that calls for a more specific distinct diagnosis have not been supported. In this study, we have used the Seasonal Pattern Assessment Questionnaire (SPAQ), the most popular
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Department of Neuroergonomics, Institute of Applied Psychology, Jagiellonian University, Krakow, Poland
Submitted August 15, 2013, Returned for revision December 8, 2013, Accepted December 9, 2013
Correspondence: Halszka Oginska, Department of Neuroergonomics, Institute of Applied Psychology, Jagiellonian University, Lojasiewicza 4, Krakow 30-348, Poland. E-mail: [email protected]
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climatic conditions and a daily photo-period in a given location (which is strongly related to its latitude). This extreme seasonality resembles an animal’s ability to hibernate in order to survive an adverse, cold season. It seems unwanted and useless in the contemporary world, a throwback of the evolutionary process. Reduced energy in winter means less willingness to meet the challenges of everyday tasks which do not usually follow the seasonal pattern. In addition to a depressed mood, SAD syndrome is characterized by a set of so-called atypical symptoms, such as longer sleep, increased appetite, craving for sweets and/or carbohydrate-rich food and, in consequence, gaining weight. This may be seen as a kind of ‘‘resource saving’’ behaviour. Large epidemiological studies (over 11 500 participants) showed that a high level of self-reported seasonality was associated with objective health risk factors (Øyane et al., 2010). SAD probably results from a complex interplay between environmental and individual biological and psychological factors. In search of individual ‘‘risk factors’’, personality studies were conducted mainly in clinical samples. Enns et al. (2006) compared the scores – using the five-factor model of personality – of SAD patients with a matched group of non-seasonal depressed patients and published normative data. SAD patients showed elevated openness scores relative to both non-seasonal depression patients and norms. Their neuroticism scores were higher than the norms (but lower than those of the non-seasonal patients). Jain (1999) also found higher scores in the openness domain in SAD patients. Moreover, this was true even after light treatment and, according to the author, may be seen as an enduring characteristic of patients with SAD. This is consistent with previous research by Bagby et al. (1996), who compared two sub-types of patients with major, non-psychotic depression with and without seasonality. Patients were assessed during an acute depressive episode and while controlling the severity of the depression, a difference was found in only one of the five dimensions, namely openness. A study done in a random community sample in Australia (n ¼ 303) by Murray et al. (2002) seasonality was measured not as a retrospective self-description, but as a prospective pattern of current mood states in winter and summer, across two years. Here again, openness appeared to be connected with the tendency of a lowered mood in winter relative to summer. Ennis & McConville (2003) showed that profound seasonal disturbances in mood and behaviour were associated with increased levels of neurotic personality traits but the degree of seasonal variation in mood and behaviour was equally well-explained in terms of ‘‘impulsivity’’. Later, Ennis & McConville (2004) studied the daily mood profiles of 59 subjects during the months of January and February and found that mood variability was significantly and positively associated with seasonality. Chotai et al. (2004b) discovered that individuals
who reported feeling at their worst in winter (and also those feeling at their worst in summer) exhibited high ‘‘harm avoidance’’ as assessed by the Temperament and Character Inventory. Finally, Maeno et al. (2005), in a study involving 6135 Japanese, found the same tendency (a higher harm avoidance score) in individuals with the summer form of SAD. In order to better understand the mechanism and development of SAD, Sigmon et al. (2006) proposed to investigate similarities and differences in stress reactivity, coping strategies and psychosocial stress impact in individuals with seasonal and non-seasonal depression. Greater psychophysiological reactions to laboratory stressors were observed in subjects in the non-seasonal group. No significant differences in the reported use of problem- and emotion-focused coping strategies were found between the groups. Neither were there any significant differences in acceptance coping use by individuals in the two depressed groups and both MDD-SAD patients (n ¼ 19) and MDD patients (n ¼ 17) reported a greater use of avoidance coping (as described by the COPE questionnaire) compared with controls. Coping strategies are partly controlled by personality and partly by social context. It can be supposed that the use of maladaptive coping strategies results in increased vulnerability to depression and the tendency to experience a more depressed mood when exposed to stressful situations. The term ‘‘chronotype’’ is used to describe relatively stable traits of the subjective diurnal rhythm of activity, characteristic of the individual – it may be considered an element of personality. Traditionally, it refers to the subjective morning-evening preference, i.e. the selfreported ‘‘feeling best’’ and ‘‘best performance’’ times of day. Sleep-wake behaviour is the key question here. Although fundamental to describe circadian functioning, the subjective phase is not the only parameter needed to characterize the chronotype. The strength of preferences, i.e. the distinctness of the circadian variability in activation levels (or subjective amplitude) should also be taken into account. Most of the tools used in chronotype studies are limited to only one dimension, i.e. to the morningness scale. Chronotype and seasonality represent two facets of an individual’s adjustment to exogenous biological rhythms – daily and yearly changes in the external environment associated with the Earth’s rotation and movement. Both chronotype and seasonality are connected with melatonin secreted by the pineal gland, under the influence of the circadian mechanism on the one hand, and external light exposure on the other hand. A study reported by Wehr (2005) comparing SAD patients with healthy controls suggested that SAD people respond to the external changes in a photoperiod in a manner similar to other mammals (longer melatonin secretion time in winter than in summer), while healthy people seem to have lost this property (having a similar length of melatonin secretion in warm and cold Chronobiology International
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Chronotype, personality and seasonality seasons). It is possible that the retention of this ability to track seasons in this way might explain the seasonal presentation of the disorder in SAD people. In view of the above, it is strange that very few studies have looked for a connection between circadian type and symptoms of SAD in its winter form, although the link between the eveningness and depressive moods has been observed. The ‘‘phase shift hypothesis’’ of SAD by Lewy et al. (1987, 2006) posited a delay in internal circadian rhythms relative to the external clock to be crucial in understanding the disorder and the effectiveness of light therapy. It could be assumed that late (evening) chronotypes are those who tend to show SAD symptoms more often than others; however, it was not stated explicitly. In the context of this hypothesis, Murray et al. (2005) tested whether fluoxetine and light treatments for SAD patients do operate by advancing the circadian phase. They have found that both treatments resulted in a significant antidepressant effect and phase advance but the degree of symptom change did not correlate with the degree of phase change. There is no evidence to suggest that circadian phase advance mediates the therapeutic mechanism. However, in a recent study, Lee et al. (2011) suggested that delayed sleep phase syndrome (DSPS) and SAD may share a pathophysiological mechanism that causes a delayed circadian phase. DSPS patients showed higher seasonality scores, compared with controls, in mood, appetite, energy level and winter–summer differences in sleep length and weight. SAD and sub-SAD subjects reported higher eveningness. Natale et al. (2005) found a slight but significant negative correlation between the morningness score (Morningness–Eveningness Questionnaire (MEQ) by ¨ stberg) and seasonality (Global Seasonality Horne and O Score – GSS, from SPAQ), with a significantly higher incidence of evening vs. morning types among students with seasonal depression. But in the prospective study evening types did not present a higher annual range of mood variations than morning ones. According to the authors, ‘‘caution should be exercised in ascribing eveningness as a risk factor in SAD since other underestimated factors, including social-cultural conditions, might be involved in the pathogenesis of mood seasonality’’. In a group of Finnish twins with bipolar disorder, Hakkarainen et al. (2003) found that patients were no more likely to be an evening type than their healthy cotwins. However, they did discover a connection between the preference for evening activities and a higher GSS after accounting for gender, age, zygosity and mental health. This correlation was seen only in the total score, with no significant associations between the circadian type and the seasonal changes in length of sleep, weight or appetite. All of the aforementioned research is based on only one characteristic of diurnal rhythm, namely the subjective phase, referred to as ‘‘morningness’’ or !
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‘‘morningness–eveningness (ME)’’. The present study included the Chronotype Questionnaire (ChQ) (Ogin´ska, 2011) that refers to two dimensions: the subjective phase (morning–evening preference) and subjective amplitude (i.e. distinctness) of the circadian rhythm of activation. The aim of the study was to recognize chronotype and other personality factors linked to the predisposition to seasonal affective fluctuations in a non-clinical sample. Studies conducted in healthy populations are free from the masking effects of drug administration, hospital stays (limited activity and disruption of daily habits) and other conditions that may modulate the well-being of patients. Exploring personality correlation in SAD-prone individuals may bring new ideas as regards both the aetiology of this disorder and its treatment, especially in terms of ‘‘client-tailored’’ therapy.
MATERIALS AND METHODS Location and participants The study was conducted in Krakow, south Poland (500 0300 latitude and 190 5600 longitude), a town of about 760 thousands inhabitants, which is a vivid and vibrant cultural and student centre with almost round-the-clock activity. The studied group was made up of mainly young urban professionals and final-year students who were often in concurrent employment. One hundred and one people (57 women and 44 men) with a mean age of 26.4 ± 6.5 years were recruited. This age group was deliberately selected since, according to the literature, SAD typically manifests between 20 and 30 years of age (Magnusson & Partonen, 2005). Over 240 questionnaires were distributed and less than 50% were returned. Global Seasonality Score (SPAQ) The GSS is the central sub-scale of the SPAQ, elaborated by Rosenthal (1993, 2005). It asks the subject to rate the degree of seasonal variation he/she experiences in six areas – sleep, social activity, mood, weight, appetite and energy level. There is a 5-point answer option: from 0 – ‘‘no change’’, to 4 – ‘‘extremely marked change’’. The sum produces a GSS, ranging from 0 to 24. According to Rosenthal’s criteria, a subject with GSS of 11 points or more, feeling worst in December–February and experiencing seasonal changes as a problem to at least a ‘‘moderate’’ degree is considered to have SAD. Subsyndromal SAD is diagnosed when a subject reports the same months as ‘‘the worst’’ and scores at least 10 points, even if she/he reports ‘‘no problem’’, or scores 8–9 points and estimates the problem at least as ‘‘mild’’. Although there are some doubts about the accuracy of SPAQ because of its tendency to provide a false positive diagnosis, this questionnaire remains the most widespread tool used in epidemiologic research, allowing for intercultural comparisons. SPAQ is not sensitive enough to be considered a diagnostic instrument for SAD, but it is accurate enough to be used as a screening instrument (Mersch et al., 2004). The Global Seasonality
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Scale, consisting of two factors (a food factor and a psychological one) has good internal consistency (Mersch et al., 2004). According to Steinhausen et al. (2009), SPAQ as the sole measurement leads to an overestimation of SAD – its prevalence based on this single test was almost 8%, while the addition of a second method brought it down to 2%. Nevertheless, seasonal mood variations seem to be a rather common phenomenon in the population of central Europe – in a Swiss community study, sub-syndromal SAD was diagnosed in 33% of cases.
Winter Blues Scale With the potential flaws of SPAQ in mind, the authors decided to use an additional method, the Winter Blues Scale (WBS), which was administered to the smaller sample of participants (n ¼ 44), i.e. only to those who were examined in January and February. The WBS looks to identify SAD symptoms more directly than GSS. The scale was developed during a research project conducted in 2004 regarding the seasonal aspects of drowsiness in workplaces (Ogin´ska, 2005). It examines 21 symptoms of seasonal depression (chosen from a list of 50 subjective complaints by means of discrimination analysis) in 7 areas: sleepiness, appetite, mood, socialization, energy, libido and ‘‘general malaise’’. The subjects are asked to rate how much each symptom applies to them on a 4-point scale. The WBS is not a diagnostic tool, it is aimed at mild, sub-clinical forms of winter depression. Cronbach’s alpha for WBS reached 0.90; individual scores for a group of 96 psychology students showed significant correlation with GSS (r ¼ 0.63; p50.001). Chronotype Questionnaire The ChQ (Ogin´ska, 2011) consists of two scales which refer to two important parameters of diurnal subjective activation rhythm: acrophase (eight-item ‘‘ME’’ scale) and amplitude (six-item ‘‘distinctness of the rhythm’’ scale – DI). Both scales show satisfactory psychometric properties (Cronbach’s alpha 0.82–0.84 for ME and 0.61–0.72 for DI scale) if used with adults. The subjective phase, reflected by morning–evening orientation, regards awareness of one’s own possibilities and limitations, preferences and unwillingness to undertake activities at various times of day. The scale does not refer to clock hours, but is aimed at a variety of functional states: mood, attention, energy level, efficiency, etc., in the diurnal time frame. Subjective amplitude or the range of circadian variations manifests as the ‘‘distinctness’’ of daily activation changes, the feeling (or lack thereof) of difference between hyperand hypo-activation phases. While the ME scale has proved to be psychometrically robust (Oginska et al., ´ ska, 2011) and shows strong correlation with 2010; Ogin the classic MEQ (Dosseville et al., 2013), the DI scale was apparently weaker. However, it correlated significantly with the range of diurnal variations in energy levels, as
described by Thayer’s adjective list (Ogin´ska, 2011). Morningness and distinctness scales are independent variables, except for younger subjects (adolescents), in which associations between ME and DI scales are often observed – young evening types show strong preferences as to their ‘‘best time of day’’.
NEO-Five Factor Inventory This classic tool for describing personality dimensions was proposed by Paul Costa and Robert McCrae in the early 1990s. Their five-factor model: neuroticism, extraversion, openness to experience, agreeableness and conscientiousness (NEOAC) are known as The Big Five. The NEOAC structure allows the prediction of the academic and professional success of an individual, his/ her state of health and life satisfaction. It is also connected with individual coping strategies and cognitive functioning. A Polish adaptation of the questionnaire has been developed by Zawadzki & Strelau (1998). Coping inventory for stressful situations Seasonal climate changes may be regarded as a specific form of stress. We decided to broaden the classical personality description with a coping style questionnaire. CISS refers to Lazarus and Folkman’s transactional model of stress – coping strategies are related to an individual’s approach to stressful life events. Specific coping styles can either promote mental and physical health or aggravate health problems. The questionnaire was proposed by Endler and Parker around 1990 and measures three main coping strategies: task focused – dealing with the problem at hand, emotion-focused – concentrating on the resultant emotions, and avoidance coping – trying to avoid the problem. Avoidanceoriented strategies comprise two sub-types: distraction and social diversion. In general, task-oriented coping styles are positively related to adaptability and good health, while emotion-oriented styles are the opposite. The results for avoidance-oriented coping and adaptation are equivocal (Cosway et al., 2000). This may be related to the complex composition of this factor. Depression was found to correlate negatively with social diversion, but it showed no relationship with distraction. The questionnaire was adapted for a Polish population by Strelau et al. (2005). The protocol for this study complied with the ethical standards of the journal for the conduct of human biological rhythm research (Portaluppi et al., 2008). The statistical analyses (correlation and regression analyses and analysis of variance (ANOVA)) were performed with use of SPSS 11.0 for Windows (SPSS Inc., Chicago, IL) and IBM SPSS Statistics for Windows, Version 20.0 (IBM Corp., Armonk, NY). RESULTS The GSS showed a normal distribution, with a mean of 12.4 points and SD 5.2. This is higher than any other Chronobiology International
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Chronotype, personality and seasonality group studied previously. The gender aspect should be taken into account – women scored significantly higher than men (Table 1). Only 15% of women did not experience seasonal changes in well-being, while twice as many male participants (30%) were ‘‘not seasonal’’. Women experienced more distinct changes in all the aspects listed in SPAQ. The most important difference between male and female subjects regarded changes in appetite, which were perceived mostly by women as connected with the seasons of the year (40.7% female vs. 14.6% male). Yet, gender does not differentiate the general pattern of seasonality, in that affective symptoms (mood and energy) are higher in proportion than atypical symptoms (sleep, weight, appetite and social activity) (Figure 1). Apart of seasonality, significant gender differences were observed in personality dimensions (neuroticism and agreeableness – higher in female subjects) and coping strategies. Women scored visibly higher on the avoidance-oriented scale (and in its sub-scale relating to distraction) and tended to apply more emotion-oriented strategies and fewer task-oriented strategies (p 0.07). The difference (at the limit of significance) between men and women was observed in the distinctness scale of the ChQ – females showed a larger subjective amplitude of the circadian rhythm. A comparison of the groups of subjects with SAD (n ¼ 41), sub-SAD (n ¼ 33), and non-SAD (n ¼ 21), distinguished on the basis of SPAQ classification rules, exposed significant differences in two personality traits: neuroticism (ANOVA: F(2, 93) ¼ 4.278, p ¼ 0.017) and openness (F(2, 93) ¼ 4.330, p ¼ 0.016). The sub-groups’ scores did not differ in extraversion, agreeableness and conscientiousness scales (Figure 2a). The most notable difference between the groups concerned avoidanceoriented coping strategies (ANOVA: F(2, 93) ¼ 6.192, p ¼ 0.003; Figure 2b). The results described above were confirmed by correlation analysis: the GSS correlated positively with
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neuroticism (r ¼ 0.33, p ¼ 0.006), openness (r ¼ 0.24, p ¼ 0.018), and avoidance strategy (r ¼ 0.38, p50.001), while higher results on the WBS linked to avoidance coping only (r ¼ 0.32, p ¼ 0.035, n ¼ 44). Moreover, both seasonality measures, GSS and WBS turned out to be
FIGURE 1. SPAQ: ‘‘To what degree do the following change with the season?’’ Percentage of subjects describing seasonal fluctuations in various spheres of well-being as ‘‘marked change’’ or ‘‘extremely marked change’’ (n ¼ 101).
TABLE 1. Average results (means and SD) of female and male participants in the study. ANOVA Females (n ¼ 57) Age SPAQ – GSS ChQ – ME ChQ – DI NEO-FFI – Neuroticism NEO-FFI – Extraversion NEO-FFI – Openness NEO-FFI – Agreeableness NEO-FFI – Conscientiousness CISS – Task orientation CISS – Emotion CISS – Avoidance CISS – Distraction CISS – Social diversion !
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Males (n ¼ 44)
27.0 ± 6.5 25.7 ± 5.9 13.6 ± 4.8 10.9 ± 5.4 26.2 ± 9.7 25.5 ± 9.5 20.7 ± 5.3 18.5 ± 5.9 24.4 ± 8.8 21.02 ± 8.1 28.3 ± 6.7 28.9 ± 5.8 30.6 ± 5.1 28.8 ± 5.7 29.1 ± 6.6 25.7 ± 5.9 30.2 ± 7.0 29.8 ± 8.2 58.0 ± 7.6 60.9 ± 8.3 47.4 ± 9.9 43.3 ± 12.9 45.8 ± 8.9 42.1 ± 9.2 20.0 ± 5.7 17.6 ± 5.8 17.4 ± 3.8 16.3 ± 3.5
F
p
1.030 6.261 0.102 3.823 3.978 0.201 2.344 6.965 0.010 3.430 3.282 4.276 4.228 2.099
0.313 0.014 0.750 0.053 0.049 0.655 0.129 0.010 0.919 0.067 0.073 0.041 0.042 0.151
FIGURE 2. Personality traits (a) and coping strategies (b) in SAD, sub-SAD, and non-SAD subjects, as defined by SPAQ criteria.
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linked significantly with the distinctness scale of the ChQ – correlation coefficients amounted to 0.28 (p ¼ 0.006) and 0.44 (p ¼ 0.003), respectively. A multiple regression check was run to test if seasonality (GSS) may be predicted from four variables identified in the course of previous analyses (neuroticism, openness, avoidance coping and subjective circadian amplitude). Two variables significantly predicted the GSS: F(4, 89) ¼ 7.126, p ¼ 0.025, R2 ¼ 0.243. Avoidance coping added most to the prediction ( ¼ 0.258, p ¼ 0.011), followed by neuroticism ( ¼ 0.197, p ¼ 0.050), while openness did not reach statistical significance ( ¼ 0.175, p ¼ 0.064). Interestingly, in the case of the WBS score, the analogical multiple regression analysis gave quite different results – the subjective circadian amplitude was the only significant predictor: F(4, 39) ¼ 3.136, p50.001, R2 ¼ 0.243, with coefficient of 0.356, p ¼ 0.023. The following analysis concerned the personality and coping styles of four chronotypes distinguished on the basis of the ChQ. Due to the relatively small group, the medians were taken as cut-off points to delineate the sub-groups according to the configuration of morning– evening and distinctness scales: definite-morning (or ‘‘strong larks’’ – morning orientation, large amplitude), moderate morning (or ‘‘weak larks’’ – morning orientation, small amplitude), moderate evening (or ‘‘weak owls’’ – evening orientation, small amplitude) and definite evening (or ‘‘strong owls’’ – evening orientation, large amplitude). Individuals representing ‘‘moderate morning’’ preferences differed clearly from other types, showing lower seasonality, lower neuroticism and less emotion-oriented and avoiding-oriented coping in stressful situations (Table 2). Chronotype dimensions, if considered separately, revealed different strengths of relationship with personality factors. ME preference did not show significant connections with any of the parameters studied, while the DI demonstrated associations with neuroticism and all three coping styles defined by CISS. A larger subjective amplitude correlated negatively with task-oriented strategies and positively with emotion- and avoidance-oriented coping styles (Table 3).
Finally, the avoidance-oriented coping style was revealed to correlate positively with all six aspects of seasonality. Both sub-types of avoidance-oriented style, i.e. distraction and social diversion, proved to be related to more marked seasonal changes in sleep length, mood and energy level (Table 4). TABLE 3. Simple correlation coefficients of chronotype dimensions, seasonality scores and personality traits studied. ME
GSS WBS Neuroticism Extraversion Openness Agreeableness Conscientiousness Task coping Emotion coping Avoidance coping
DI
n
Corr. Coeff.
p
Corr. Coeff.
p
95 44 98 98 98 98 98 101 101 101
0.185 0.065 0.109 0.012 0.157 0.128 0.110 0.073 0.124 0.137
n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s.
0.282 0.437 0.303 0.074 0.092 0.251 0.022 0.192 0.302 0.283
0.006 0.003 0.002 n.s. n.s. n.s. n.s. 0.055 0.002 0.004
TABLE 4. Coping strategies and susceptibility to seasonal changes in mood and behaviour (simple correlation coefficients, n ¼ 95). Seasonality aspects
Task- Emotion- AvoidanceSocial oriented oriented oriented Distraction diversion
Sleep length R Sig.
0.087 0.402
0.123 0.236
0.341 0.001
0.217 0.034
0.388 0.000
Social activity R Sig.
0.157 0.130
0.155 0.135
0.210 0.041
0.158 0.125
0.188 0.068
Mood R Sig.
0.166 0.109
0.152 0.141
0.296 0.004
0.257 0.012
0.205 0.047
Weight R Sig.
0.162 0.116
0.107 0.302
0.295 0.004
0.265 0.010
0.148 0.152
0.105 0.311
0.009 0.929
0.215 0.037
0.199 0.053
0.142 0.169
0.027 0.798
0.163 0.115
0.290 0.004
0.205 0.047
0.268 0.009
Appetite R Sig. Energy level R Sig.
TABLE 2. The results of ANOVA in four chronotype sub-types: seasonality, personality traits and coping strategies. ‘‘Strong lark’’
GSS WBS Neu Ext Opn Agr Con CISS-task CISS-emo CISS-avoid
‘‘Weak lark’’
‘‘Weak owl’’
‘‘Strong owl’’
n
Mean ± SD
n
Mean ± SD
n
Mean ± SD
n
Mean ± SD
ANOVA F/p
20 10 20 20 20 20 20 21 21 21
13.8 ± 5.2 15.4 ± 11.2 26.1 ± 5.6 27.6 ± 4.9 29.4 ± 5.1 29.3 ± 3.9 30.1 ± 5.6 59.4 ± 7.2 48.5 ± 7.8 45.5 ± 8.9
25 11 27 27 27 27 27 27 27 27
9.8 ± 5.2 6.4 ± 6.3 19.3 ± 8.0 29.8 ± 6.1 29.2 ± 6.2 27.5 ± 5.6 32.6 ± 7.0 60.6 ± 6.9 40.2 ± 12.8 40.3 ± 8.7
23 9 24 24 24 24 24 25 25 25
12.9 ± 4.9 8.0 ± 4.2 22.4 ± 8.9 27.8 ± 7.5 30.1 ± 5.7 27.8 ± 7.5 29.0 ± 7.9 60.4 ± 8.6 46.0 ± 11.6 44.0 ± 9.2
27 14 27 27 27 27 27 28 28 28
13.5 ± 4.8 15.6 ± 10.2 24.8 ± 9.9 28.9 ± 6.6 30.7 ± 4.8 26.2 ± 7.8 28.0 ± 8.6 56.9 ± 9.0 48.3 ± 10.8 47.2 ± 8.9
3.177/0.028 3.466/0.025 3.084/0.031 n.s. n.s. n.s. n.s. n.s. 3.192/0.027 2.881/0.040
Chronobiology International
Chronotype, personality and seasonality
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DISCUSSION The average GSS score was surprisingly high in the study participants. In preliminary research conducted previously with a group of 95 psychology students (80% female) the mean GSS was 9.2 ± 4.7 points. Both results are higher than those cited in the existing literature. According to Lam & Levitt (1999), the average GSS in general community samples is about 5 points, while SAD patients score about 16 points. The non-random method of recruiting participants to the study might have affected the results, as the forms were filled in by those interested in the topic. Also, the 22–30 age group focus may have played a role, as this is the period when SAD typically manifests and symptoms may be particularly intense. Nevertheless, such limitations do not undermine the essence of the cross-sectional analysis which focused on associations between personality traits and seasonal mood changes. Seasonality has been recognized as a phenomenon strongly connected with gender. Our study confirmed this observation, additionally pointing to some chronotype differences between men and women, namely in the subjective distinctness of the circadian rhythm. It may be hypothesized that women are more sensitive to changes in their mood and alertness (or they are better self-observers). Does this mean that females are generally more ‘‘rhythmic’’ than males? Natale & Danesi (2002) suggested that a genetically programmed circamensual rhythm in women may contribute to a less flexible circadian system also less adaptable to environmental changes. Having a ‘‘distinct’’ rhythm may indeed be understood as having a ‘‘stable’’ or ‘‘less flexible’’ rhythm. According to Chotai et al. (2004a), these subtle gender differences in perceiving the symptoms of seasonality and their importance may be an indication of different mechanisms for male and female SAD and for the need for different methods of effective therapy. The configuration of NEOAC factors in our sample is typical for both genders, however, according to Zawadzki & Strelau (1998), in Polish samples women also scored higher in extraversion, openness and conscientiousness. Coping strategies used by men and women are different, according to Strelau et al. (2005), only as regards emotion-oriented strategies. In our sample women scored visibly higher on the avoidanceoriented scale (and in its sub-scale relating to distraction) and tended to apply more emotion-oriented strategies and fewer task-oriented strategies (p 0.07). Our analyses are in line with the results of previous personality studies conducted in clinical samples and showing higher levels of ‘‘openness’’ in SAD patients (Bagby et al., 1996; Enns et al., 2006; Jain et al., 1999; Murray et al., 2002). It is not easy, however, to interpret the higher vulnerability to seasonal changes in subjects who are ‘‘open to experience’’, i.e. show more imagination, aesthetic sensitivity and intellectual curiosity. One possible explanation could be that the same mechanism !
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drives individual openness to the social and physical environment – interest in the external world augments the reaction to all the changes that are observed, including those regarding light, noise, temperature and other factors that define weather or season. Besides, openness also means being receptive to inner emotional states that mean open people are more aware of their own feelings, sensations and moods. According to McCrae & John (1992) openness is the most controversial of the five factor personality model. It is often seen as an intellectual feature, forming an important part of consciousness and affecting social perceptions. The authors argue that ‘‘O includes aspects of intellect, but is considerably broader in scope’’ and shall be seen also in terms of a motivation theory, as a need for variety and experience. It may be associated with quite ‘‘esoteric’’ phenomena such as chills in response to sudden beauty, the experience of de´ja` vu, and homesickness for the unknown (McCrae and Sutin, 2009). Openness to experience, as a personality factor, is connected to divergent thinking and creativity. Norman Rosenthal in his Winter Blues (1993) pointed to the increased vulnerability to seasonal depression observed in poets, artists and other creative individuals. He brought up a remark by Aristotle who described the outstanding personalities in philosophy, politics, poetry and arts as showing melancholic tendencies. Although much research has shown that creative behaviour is often associated with the risk of depression, the mechanism is still unclear. Verhaeghen et al. (2005) posited that there is third underlying factor, namely a self-reflective rumination that may explain this connection. Using path analysis, the authors found that rumination was related to objectively measured creative fluency, originality and elaboration. As no link exists between depressed moods and creative behaviours, rumination seems to be the sole factor explaining the association between depression and creativity. Our study showed another link to personality traits in season-vulnerable subjects, stemming from the analysis of CISS results. SAD-prone individuals exhibited higher scores in avoidance-oriented coping. This tallied with the results of Sigmon et al. (2006) obtained with a different coping questionnaire. Indeed, the description of avoidance-coping strategies pertains to the characteristic behaviour of a seasonally depressed person. Typical strategies for surviving an unfavourable situation include overeating, sleeping or retreating into a different activity that leads to temporary relief (watching TV or other substitute actions). Such an attempt to wait out the uncomfortable situation brings to mind the strategy well known from the animal world as hibernation. The question arises whether extreme seasonality is the human equivalent of hibernation? (Cizza et al., 2011). It is important here to differentiate psychological coping strategies and ‘‘defence mechanisms’’ – the former are applied consciously. This means there are
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chances to work on them during a therapeutic process, e.g. with a cognitive-behavioural approach. The chronotype dimensions did show different relations with seasonality. ME was not confirmed as a ‘‘risk factor’’. This is in line with the results of Natale et al. (2005). The second chronotype aspect proposed here – the ‘‘subjective amplitude’’, was shown to be linked to seasonality scores. Indirect confirmation of this result may be found in the study of Ennis and McConville (2004) who found seasonality unrelated to average mood levels, but with a significantly positive association with mood variability, as defined by the Positive and Negative Affect Schedule questionnaire completed twice daily over two weeks. It is worth noting that the greater diurnal variability of moods predicts a positive reaction to light therapy (Wirz-Justice, 2000), as well as a potent antidepressant response to sleep deprivation (Wirz-Justice, 2008). There are some limitations in interpreting the results referring to subjective amplitude due to the weakness of the DI (distinctness) scale in the ChQ. It revealed the poor psychometrics in the French version (Dosseville et al., 2013) and a lower reliability than the ME scale in the Polish version (Ogin´ska, 2011). Nevertheless, this original DI scale proved to correlate with the range of diurnal variations in the self-reported level of energy (Ogin´ska, 2011). According to Murray et al. (2002), two affective processes that seem to be involved in mood variations across a seasonal time frame, can be named as adaptive environmental sensitivity and endogenous mood variability. One may assume that both point to the distinctness of the biological rhythm. Recent theories on the pathophysiology of SAD include both a vulnerability to depression (and its neurotransmitter regulation) and another factor responsible for the seasonal course it takes. This was called by Young (1999) The Dual Vulnerability Hypothesis. The main mechanisms thought to shape individual seasonality are: circadian rhythms, photoperiod-melatonin and retinal sensitivity to light. The simple cross-sectional questionnaire survey presented here cannot add to the understanding of the pathophysiologic mechanism of the disorder. However, it is worth noting that our findings, pointing to a specific configuration of personality and chronotype traits, are coherent with the twofactor model of SAD: higher levels of neuroticism and openness – a characteristic for depressive individuals – on the one hand, and on the other, a larger subjective amplitude of the rhythm, indicating sensitivity to environmental synchronizers. It may be argued that a convergence of those traits with an avoidance coping style enhances seasonality.
CONCLUSIONS In summary, the analyses of mood seasonality performed in a non-clinical sample are consistent with
previous research pointing to increased neuroticism and openness as personality factors characterizing the SAD-prone subjects. The study revealed some new associations between the susceptibility to mild winter depression and an avoidance coping strategy as measured by the CISS. The subjective amplitude of circadian rhythm showed to be another related factor, while the traditionally understood chronotype, defined solely by the subjective acrophase of the rhythm (ME preference), did not prove to have any relation to it. It may be hypothesized that sensitivity to natural environmental conditions is a separate individual trait shaping the subject’s proneness to mood changes, both in diurnal and year scales, i.e. circadian and seasonal fluctuations.
ACKNOWLEDGMENTS The data have been collected in the fulfilment of master thesis prepared by Katarzyna Oginska, under the supervision of professor Leszek Pawlowski at the Institute of Applied Psychology of the Jagiellonian University. The Winter Blues Scale has been elaborated in frame of research project No. 501/PKL/146/L (headed by H. Oginska) at the Jagiellonian University Medical College.
DECLARATION OF INTEREST The authors report no conflicts of interest. The authors alone are responsible for the content and writing of this article.
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