Seasonality of mood and affect in a large general population sample.

Mood and behaviour are thought to be under considerable influence of the seasons, but evidence is not unequivocal. The purpose of this study was to investigate whether mood and affect are related to the seasons, and what is the role of neuroticism in this association. In a national internet-based crowdsourcing project in the Dutch general population, individuals were invited to assess themselves on several domains of mental health. ANCOVA was used to test for differences between the seasons in mean scores on the Positive and Negative Affect Schedule (PANAS) and Quick Inventory of Depressive Symptomatology (QIDS). Within-subject seasonal differences were tested as well, in a subgroup that completed the PANAS twice. The role of neuroticism as a potential moderator of seasonality was examined. Participants (n = 5,282) scored significantly higher on positive affect (PANAS) and lower on depressive symptoms (QIDS) in spring compared to summer, autumn and winter. They also scored significantly lower on negative affect in spring compared to autumn. Effect sizes were small or very small. Neuroticism moderated the effect of the seasons, with only participants higher on neuroticism showing seasonality. There was no within-subject seasonal effect for participants who completed the questionnaires twice (n = 503), nor was neuroticism a significant moderator of this within-subjects effect. The findings of this study in a general population sample participating in an online crowdsourcing study do not support the widespread belief that seasons influence mood to a great extent. For, as far as the seasons did influence mood, this only applied to highly neurotic participants and not to low-neurotic participants. The underlying mechanism of cognitive attribution may explain the perceived relation between seasonality and neuroticism.

Seasonal affective disorder and non-seasonal affective disorders: results from the NESDA study.

BACKGROUND: Seasonal affective disorder (SAD) is considered to be a subtype of depression. AIMS: To compare the clinical picture of SAD to non-seasonal affective disorders (non-SADs). METHOD: Diagnoses according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) were established in 2185 participants of the Netherlands Study of Depression and Anxiety. The Seasonal Pattern Assessment Questionnaire was administered to diagnose SAD. Symptoms of depression and anxiety were measured with the Inventory of Depressive Symptoms, the Beck Anxiety Inventory and the Fear Questionnaire. RESULTS: Participants with SAD, participants with a lifetime bipolar disorder and participants with a lifetime comorbid anxiety and depressive disorder scored highest in terms of psychopathology in the past year. The seasonal distribution of major depressive episodes was not different for participants with or without SAD. CONCLUSIONS: SAD may be a measure of severity of depression with a subjectively perceived worsening of symptoms in the winter months. DECLARATION OF INTEREST: Y.M. has received research funding and served as a consultant for Royal Philips Electronics NV and The Litebook Company Ltd. W.A.N. has received grants from the Netherlands Organization for Health Research and Development, the European Union, the Stanley Medical Research Institute, Astra Zeneca, Eli Lilly, GlaxoSmithKline and Wyeth; has received honoraria/speaker's fees from Astra Zeneca, Pfizer, Servier and Wyeth; and has served in advisory boards for Astra Zeneca, Pfizer and Servier. COPYRIGHT AND USAGE: © The Royal College of Psychiatrists 2017. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) license.

ADHD, circadian rhythms and seasonality.

OBJECTIVE: We evaluated whether the association between Adult Attention-Deficit/Hyperactivity Disorder (ADHD) and Seasonal Affective Disorder (SAD) was mediated by the circadian rhythm. METHOD: Data of 2239 persons from the Netherlands Study of Depression and Anxiety (NESDA) were used. Two groups were compared: with clinically significant ADHD symptoms (N = 175) and with No ADHD symptoms (N = 2064). Sleep parameters were sleep-onset and offset times, mid sleep and sleep duration from the Munich Chronotype Questionnaire. We identified the prevalence of probable SAD and subsyndromal SAD using the Seasonal Pattern Assessment Questionnaire (SPAQ). Clinically significant ADHD symptoms were identified by using a T score>65 on the Conners Adult ADHD Rating Scale. RESULTS: The prevalence of probable SAD was estimated at 9.9% in the ADHD group (vs. 3.3% in the No ADHD group) and of probable s-SAD at 12.5% in the ADHD group (vs 4.6% in the No ADHD group). Regression analyses showed consistently significant associations between ADHD symptoms and probable SAD, even after adjustment for current depression and anxiety, age, sex, education, use of antidepressants and benzodiazepines (B = 1.81, p < 0.001). Late self-reported sleep onset was an important mediator in the significant relationship between ADHD symptoms and probable SAD, even after correction for confounders (total model effects: B = 0.14, p ≤ 0.001). CONCLUSION: Both seasonal and circadian rhythm disturbances are significantly associated with ADHD symptoms. Delayed sleep onset time in ADHD may explain the increase in SAD symptoms. Treating patients with SAD for possible ADHD and delayed sleep onset time may reduce symptom severity in these complex patients.

The effects of low-intensity narrow-band blue-light treatment compared to bright white-light treatment in sub-syndromal seasonal affective disorder.

BACKGROUND: The discovery of a novel photoreceptor in the retinal ganglion cells with a highest sensitivity of 470-490 nm blue light has led to research on the effects of short-wavelength light in humans. Several studies have explored the efficacy of monochromatic blue or blue-enriched light in the treatment of SAD. In this study, a comparison has been made between the effects of broad-wavelength light without ultraviolet (UV) wavelengths compared to narrow-band blue light in the treatment of sub-syndromal seasonal affective disorder (Sub-SAD). METHOD: In a 15-day design, 48 participants suffering from Sub-SAD completed 20-minute sessions of light treatment on five consecutive days. 22 participants were given bright white-light treatment (BLT, broad-wavelength light without UV 10 000 lux, irradiance 31.7 Watt/m(2)) and 26 participants received narrow-band blue light (BLUE, 100 lux, irradiance 1.0 Watt/m(2)). All participants completed daily and weekly questionnaires concerning mood, activation, sleep quality, sleepiness and energy. Also, mood and energy levels were assessed by means of the SIGH-SAD, the primary outcome measure. RESULTS: On day 15, SIGH-SAD ratings were significantly lower than on day 1 (BLT 54.8 %, effect size 1.7 and BLUE 50.7 %, effect size 1.9). No statistically significant differences were found on the main outcome measures. CONCLUSION: Light treatment is an effective treatment for Sub-SAD. The use of narrow-band blue-light treatment is equally effective as bright white-light treatment. TRIAL REGISTRATION: This study was registered in the Dutch Trial Register (Nederlands Trial Register TC = 4342 ) (20-12-2013).

Self-attributed seasonality of mood and behavior: a report from the Netherlands study of depression and anxiety.

BACKGROUND: Seasonal changes in mood and behavior are considered to be common in the general population and in patients with psychiatric disorders. However, in several studies this seasonality could not be demonstrated. The present study examined self-attributed seasonality of depressive symptoms among patients with a lifetime diagnosis of a depressive disorder (D), an anxiety disorder (A), a comorbid depressive and anxiety disorder (DA), and healthy controls (HC). METHODS: The CIDI was used to establish diagnoses according to DSM-IV criteria in 2,168 participants of the Netherlands Study of Depression and Anxiety (NESDA). The Seasonal Pattern Assessment Questionnaire (SPAQ) was administered to assess variation in mood and behavior. RESULTS: Of the 2,168 participants 53.5% reported seasonality of mood. Highest percentages of low mood were seen in the winter months. Although all groups showed this pattern of lowered mood during the winter months, D, A, and DA were significantly (P < .001) more likely to experience seasonality is this respect. This was also shown for seasonal changes in energy, social activities, sleeping, eating, weight and for the Global Seasonality Score. A limitation of this study was the cross-sectional design. CONCLUSIONS: Seasonal variation in mood and behavior was demonstrated for both participants with a lifetime diagnosis of depression and/or anxiety disorder and for healthy controls, but patients with anxiety and/or depression were more likely to experience this seasonal variation. Clinicians should take into account that the time of the year could influence the feelings of well- and ill-being of their patients.

Role of the police in linking individuals experiencing mental health crises with mental health services.

BACKGROUND: The police are considered frontline professionals in managing individuals experiencing mental health crises. This study examines the extent to which these individuals are disconnected from mental health services, and whether the police response has an influence on re-establishing contact. METHODS: Police records were searched for calls regarding individuals with acute mental health needs and police handling of these calls. Mental healthcare contact data were retrieved from a Psychiatric Case Register. RESULTS: The police were called upon for mental health crisis situations 492 times within the study year, involving 336 individuals (i.e. 1.7 per 1000 inhabitants per year). Half of these individuals (N=162) were disengaged from mental health services, lacking regular care contact in the year prior to the crisis (apart from contact for crisis intervention). In the month following the crisis, 21% of those who were previously disengaged from services had regular care contact, and this was more frequent (49%) if the police had contacted the mental health services during the crisis. The influence of police referral to the services was still present the following year. However, for the majority (58%) of disengaged individuals police did not contact the mental health services at the time of crisis. CONCLUSIONS: The police deal with a substantial number of individuals experiencing a mental health crisis, half of whom are out of contact with mental health services, and police play an important role in linking these individuals to services. Training police officers to recognise and handle mental health crises, and implementing practical models of cooperation between the police and mental health services in dealing with such crises may further improve police referral of individuals disengaged from mental health services.

Seasonality in depressive and anxiety symptoms among primary care patients and in patients with depressive and anxiety disorders; results from the Netherlands Study of Depression and Anxiety.

BACKGROUND: Little is known about seasonality of specific depressive symptoms and anxiety symptoms in different patient populations. This study aims to assess seasonal variation of depressive and anxiety symptoms in a primary care population and across participants who were classified in diagnostic groups 1) healthy controls 2) patients with a major depressive disorder, 3) patients with any anxiety disorder and 4) patients with a major depression and any anxiety disorder. METHODS: Data were used from the Netherlands Study of Depression and Anxiety (NESDA). First, in 5549 patients from the NESDA primary care recruitment population the Kessler-10 screening questionnaire was used and data were analyzed across season in a multilevel linear model. Second, in 1090 subjects classified into four groups according to psychiatric status according to the Composite International Diagnostic Interview, overall depressive symptoms and atypical versus melancholic features were assessed with the Inventory of Depressive Symptoms. Anxiety and fear were assessed with the Beck Anxiety Inventory and the Fear questionnaire. Symptom levels across season were analyzed in a linear regression model. RESULTS: In the primary care population the severity of depressive and anxiety symptoms did not show a seasonal pattern. In the diagnostic groups healthy controls and patients with any anxiety disorder, but not patients with a major depressive disorder, showed a small rise in depressive symptoms in winter. Atypical and melancholic symptoms were both elevated in winter. No seasonal pattern for anxiety symptoms was found. There was a small gender related seasonal effect for fear symptoms. CONCLUSIONS: Seasonal differences in severity or type of depressive and anxiety symptoms, as measured with a general screening instrument and symptom questionnaires, were absent or small in effect size in a primary care population and in patient populations with a major depressive disorder and anxiety disorders.