The impact of daylight-saving time (DST) on patients with delayed sleep-wake phase disorder (DSWPD).

Due to time zones, sun time and local time rarely match. The difference between local and sun time, which we designate by Solar Jet Lag (SoJL), depends on location within a time zone and can range from zero to several hours. Daylight saving time (DST) simply adds 1 h to SoJL, independently of the location. We hypothesised that the impact of DST is particularly problematic in patients with delayed sleep-wake phase disorder (DSWPD), worsening their sleep debt. DSWPD is characterised by a chronic misalignment between the internal and social timing, reflected by an inability to fall asleep and wake-up at conventional or socially acceptable times. We analysed the clinical records of 162 DSWPD patients from a sleep medicine centre in Lisbon, Portugal (GMTzone), and separated them into two groups: the ones diagnosed across DST or across Standard Time (ST). We included 82 patients (54.9% male; age: median [Q1 , Q3 ] 34.5 [25.0, 45.3]; range 16-92; 54 in DST and 28 in ST) who had Dim Light Melatonin Onset (DLMO) measured as a marker for the circadian phase and sleep timing (onset, SO, mid-point, MS and end, SE) self-reported separately for work- and work-free days. Differences between ST and DST were compared using Mann-Whitney or Student's t-tests. On a weekly average, patients in DST slept less (difference between medians of 37 min. p < .01), mainly due to sleep on workdays (SDw, p < .01), which also correlated with SoJL (rsp = .38, p < .01). While the time from DLMO to SO was similar in those in ST or those in DST, the time from DLMO to SE was significantly shorter for those in DST. The average duration between DLMO and sleep end was close to 10.5 h in ST, the biological night length described in the literature. Our results favour perennial ST and suggest assigning time-zones close to sun time to prevent social jetlag and sleep deprivation.

Validation of the Munich Actimetry Sleep Detection Algorithm for estimating sleep-wake patterns from activity recordings.

Periods of sleep and wakefulness can be estimated from wrist-locomotor activity recordings via algorithms that identify periods of relative activity and inactivity. Here, we evaluated the performance of our Munich Actimetry Sleep Detection Algorithm. The Munich Actimetry Sleep Detection Algorithm uses a moving 24-h threshold and correlation procedure estimating relatively consolidated periods of sleep and wake. The Munich Actimetry Sleep Detection Algorithm was validated against sleep logs and polysomnography. Sleep-log validation was performed on two field samples collected over 54 and 34 days (median) in 34 adolescents and 28 young adults. Polysomnographic validation was performed on a clinical sample of 23 individuals undergoing one night of polysomnography. Epoch-by-epoch analyses were conducted and comparisons of sleep measures carried out via Bland-Altman plots and correlations. Compared with sleep logs, the Munich Actimetry Sleep Detection Algorithm classified sleep with a median sensitivity of 80% (interquartile range [IQR] = 75%-86%) and specificity of 91% (87%-92%). Mean onset and offset times were highly correlated (r = .86-.91). Compared with polysomnography, the Munich Actimetry Sleep Detection Algorithm reached a median sensitivity of 92% (85%-100%) but low specificity of 33% (10%-98%), owing to the low frequency of wake episodes in the night-time polysomnographic recordings. The Munich Actimetry Sleep Detection Algorithm overestimated sleep onset (~21 min) and underestimated wake after sleep onset (~26 min), while not performing systematically differently from polysomnography in other sleep parameters. These results demonstrate the validity of the Munich Actimetry Sleep Detection Algorithm in faithfully estimating sleep-wake patterns in field studies. With its good performance across daytime and night-time, it enables analyses of sleep-wake patterns in long recordings performed to assess circadian and sleep regularity and is therefore an excellent objective alternative to sleep logs in field settings.

Using routinely collected clinical data for circadian medicine: A review of opportunities and challenges.

A wealth of data is available from electronic health records (EHR) that are collected as part of routine clinical care in hospitals worldwide. These rich, longitudinal data offer an attractive object of study for the field of circadian medicine, which aims to translate knowledge of circadian rhythms to improve patient health. This narrative review aims to discuss opportunities for EHR in studies of circadian medicine, highlight the methodological challenges, and provide recommendations for using these data to advance the field. In the existing literature, we find that data collected in real-world clinical settings have the potential to shed light on key questions in circadian medicine, including how 24-hour rhythms in clinical features are associated with-or even predictive of-health outcomes, whether the effect of medication or other clinical activities depend on time of day, and how circadian rhythms in physiology may influence clinical reference ranges or sampling protocols. However, optimal use of EHR to advance circadian medicine requires careful consideration of the limitations and sources of bias that are inherent to these data sources. In particular, time of day influences almost every interaction between a patient and the healthcare system, creating operational 24-hour patterns in the data that have little or nothing to do with biology. Addressing these challenges could help to expand the evidence base for the use of EHR in the field of circadian medicine.

Daylight exposure and mood in real life: Direct association and mediating role of sleep and routine regularity.

The light/dark cycle is the main external cue to synchronize the human biological clock. Modern lifestyles typically lead to less daylight exposure and blunted 24 h-amplitude. We evaluated the association of outdoor daylight exposure (frequency, duration, regularity and shift) with chronotype estimated by sleep phase, regularity of routines, sleep, well-being (WHO-5), and depressive symptoms (PHQ-9), in a sample of 1,095 participants (81.8% female; 87.9% aged 18-49) surveyed online between July and November 2020. We analyzed direct and indirect associations in daylight-mood relationship with chronotype-estimate, routine regularity, and sleep as mediators. Outdoor daylight exposure was associated with WHO-5/PHQ-9 scores in mediation models, with higher total effects when the exposure was every day (ß = 4.13 ± 0.53/ ß = -3.81 ± 0.67), for more than 4 hours (ß = 3.77 ± 0.91/ ß = -3.83 ± 1.31) and during the morning (ß = 3.41 ± 0.53/ ß = -3.74 ± 0.70) in reference to lack of exposure. Chronotype-estimate, routine regularity score, and sleep problems acted as mediators, while social jetlag and sleep duration did not play an important role in this association. This study advanced the understanding of the complex interplay between light exposure, mental health, and individual characteristics of sleep and other routine regularities, and showed the benefits of optimizing daylight exposure to improve mental health.

Greater within- and between-day instability is associated with worse anxiety and depression symptoms.

BACKGROUND: Depression and anxiety affect hundreds of millions of people worldwide, and their prevalence increased during the COVID-19 pandemic as social schedules were disrupted. This study explores the associations between anxiety and depression and within- and between-day instability of affective, somatic, and cognitive symptoms during the early pandemic stages. METHODS: Participants (n = 153, ages 18-77, 72 % female) reported daily levels of affective (anxiety/sadness), somatic (appetite/sleepiness), and cognitive (concentration/energy) symptoms for 14-44 days at five timepoints: 0, 3, 6, 9, and 12 h after awakening. At the end of the study, participants completed validated scales for anxiety (GAD-7) and depression (PHQ-9). Symptom instability was assessed using the Absolute Real Variability (ARV) index. Regression models examined within-day instability (WD-I) and between-day instability (BD-I) with GAD-7 and PHQ-9 scores as outcomes. RESULTS: Greater instability (both WD-I and BD-I) of affective symptoms correlated with elevated GAD-7 and PHQ-9 scores. For somatic and cognitive symptoms, greater BD-I was associated with higher scores. LIMITATIONS: The study used retrospective daily data, which could benefit from real-time assessments for improved accuracy. CONCLUSIONS: This study provides empirical evidence of a connection between greater anxiety and depression severity and increased instability in daily mood and physiological symptoms. The findings underscore the importance of consistent symptom monitoring to understand overall mental health trajectories. Additionally, it highlights the role of daily routines in stabilizing the circadian system, potentially regulating physiological and psychological processes and reducing symptom instability.

Routine regularity during a global pandemic: Impact on mental health outcomes and influence of chronotype.

Among the public health recommendations for supporting mental health during the COVID-19 pandemic, many strategies had an impact on biological rhythms, like sleep hygiene, physical exercise and healthy eating habits. Considering the known relationship between circadian organization and mental health, our aim was to test the association between behavioral regularity and mental health, and its interaction with chronotype, in a large sample surveyed in Brazil. We collected longitudinal data using online questionnaires that assessed sociodemographic characteristics, behavioral routines, mental health (PHQ-9, GAD-7, WHO-5 scales), and chronotype estimation based on midpoint of sleep on free days - MSF (µMCTQ), in a sample of 1390 participants (81% females). We computed a Routine Regularity Score (RRS) that reflects regularity across four behaviors: sleep, eating, working, exercising. There was a strong negative association between RRS and the severity of anxiety and depressive symptoms (GAD-7 and PHQ-9 scores), which was weaker among participants with late MSF, and a strong positive association with well-being (WHO-5 scores). RRS was a mediator of the MSF-mental health association and a predictor of mental health states. This study provides empirical evidence that maintaining behavioral routines during times of hardship may serve as tools to alleviate the negative impact on mental health.

Chronotype, Social Jetlag, and Nicotine Use.

Late chronotype, which often leads to higher social jetlag (SJL), is strongly associated with the prevalence of smoking. Any circadian disruption, strain, or misalignment, results in people not being able to live according to their biological time as is described by SJL, which we will therefore use as umbrella term. We hypothesized two scenarios potentially explaining the association between smoking and SJL: (A) If smoking delays the clock, circadian phase should advance upon quitting. (B) If people smoke more to compensate the consequences of SJL, circadian phase should not change upon quitting. To distinguish between these two hypotheses, we accompanied participants of a smoking cessation program (not involving nicotine replacement products) across the cessation intervention (3 weeks prior and 6 weeks after) by monitoring their circadian behavior, sleep quality, and daytime sleepiness via questionnaires and actimetry. Our results show no effects of cessation on SJL, chronotype, sleep quality, or daytime sleepiness, thereby favoring scenario (B). Thus, smoking may be a consequence of rather than a cause for SJL. Daytime sleepiness was a significant predictor for the outcome in our model but did not improve with cessation.

Chronobiological parameters as predictors of early treatment response in major depression.

BACKGROUND: Alterations in circadian system organization have been related to major depressive disorder manifestations. This study aimed to evaluate chronobiological parameters, such as sleep, levels of 6-sulfatoxymelatonin, and others derived from actimetry as potential predictors of adequate treatment response in MDD. METHODS: 98 adult women with confirmed diagnosis of MDD were included. Participants completed standard questionnaires (Hamilton Depression Rating Scale - HAM-D; Munich Chronotype Questionnaire - MCTQ) at baseline and after 4 weeks of treatment. Urinary samples for assessing 6-sulfatoxymelatonin were collected on the day before and immediately after pharmacological treatment administration, and 28 continuous days of actigraphy data were collected during the protocol. Participants were classified into Responder (R) or Non-responder (NR) to antidepressant treatment in 4 weeks (early responder), which was characterized by a ≥50 % decrease in the HAM-D score. RESULTS: The following biological rhythms variables significantly predicted a better treatment response in a model controlling for age, sex, and previous treatments: higher levels of activity (M10 - average activity in the 10 most active hours within the 24 h-day) and an earlier center of the 10 most active hours (M10c), as well as lower intradaily variability (IV) of light exposure. Sleep parameters and 6-sulfatoxymelatonin levels did not associate with treatment response prediction. LIMITATION: Actimetry data were not assessed before changing in the treatment plan. CONCLUSION: Different patterns in activity and light exposure might be linked to early antidepressant response.

AMPA glutamate receptors mediate the antidepressant-like effects of N-acetylcysteine in the mouse tail suspension test.

The aim of this study was to investigate the involvement of noradrenaline, serotonin, and subtypes of glutamate receptors in the antidepressant-like effects of N-acetylcysteine (NAC). The tail suspension test was used with male CF1 albino mice. D,L-α-methyl-ρ-tyrosine and ρ-chlorophenylalanine methyl ester hydrochloride were used as synthesis inhibitors of noradrenaline and serotonin, respectively. N-methyl-D-aspartate (NMDA) and 2,3-dihydroxy-6-nitro-7-sulfamoyl-benzo[f]quinoxaline-2,3-dione were used as an NMDA receptor agonist and an α-amino acid-3-hydroxy-5-methyl-4-isoxazol propionic acid (AMPA) receptor antagonist, respectively. NAC (10, 25, and 50 mg/kg intraperitoneally) significantly (P<0.05) decreased tail suspension test immobility time, whereas pretreatment with D,L-α-methyl-ρ-tyrosine, ρ-chlorophenylalanine methyl ester hydrochloride, and NMDA partially prevented (P<0.05) the effects of NAC (25 mg/kg), and pretreatment with 2,3-dihydroxy-6-nitro-7-sulfamoyl-benzo[f]quinoxaline-2,3-dione completely abolished (P<0.01) this effect. The study corroborates the antidepressant-like effects of NAC in the TST, a model with a well-established predictive value. The results point to the key role of AMPA receptors in the mechanism of the antidepressant-like action of NAC. Like other AMPA potentiators, NAC indirectly modulates noradrenaline and serotonin pathways. It is suggested that the value of NAC as an antidepressant arises from combined and intertwined effects on a variety of pathways.

Development and testing of methods for detecting off-wrist in actimetry recordings.

STUDY OBJECTIVES: In field studies using wrist-actimetry, not identifying/handling off-wrist intervals may result in their misclassification as immobility/sleep and biased estimations of rhythmic patterns. By comparing different solutions for detecting off-wrist, our goal was to ascertain how accurately they detect nonwear in different contexts and identify variables that are useful in the process. METHODS: We developed algorithms using heuristic (HA) and machine learning (ML) approaches. Both were tested using data from a protocol followed by 10 subjects, which was devised to mimic contexts of actimeter wear/nonwear in real-life. Self-reported data on usage according to the protocol were considered the gold standard. Additionally, the performance of our algorithms was compared to that of visual inspection (by 2 experienced investigators) and Choi algorithm. Data previously collected in field studies were used for proof-of-concept analyses. RESULTS: All methods showed similarly good performances. Accuracy was marginally higher for one of the raters (visual inspection) than for heuristically developed algorithms (HA, Choi). Short intervals (especially < 2 h) were either not or only poorly identified. Consecutive stretches of zeros in activity were considered important indicators of off-wrist (for both HA and ML). It took hours for raters to complete the task as opposed to the seconds or few minutes taken by the automated methods. CONCLUSIONS: Automated strategies of off-wrist detection are similarly effective to visual inspection, but have the important advantage of being faster, less costly, and independent of raters' attention/experience. In our study, detecting short intervals was a limitation across methods.

Handling missing data in rest-activity time series measured by actimetry.

A handling procedure of off-wrist episodes in actimetry time series of motor activity is presented using two records (regular vs. irregular sleep-wake cycle and daytime activity) of 14 consecutive days sampled in 1-minute epochs. We generated single missing value (NA) intervals of 1 h, 2 h, 4 h, 6 h, 12 h, and 24 h as well as random NA episodes following probabilistic rules to simulate real-life off-wrist episodes. Then, we replaced these episodes with "zeroes" (i.e., the default of immobility records), mean or median of the remaining 13 days corresponding to the missing bins. Single missing episodes of up to 12 h resulted in less than 5% variation from the original values. The irregular series showed higher variability in acrophase, MESOR, L5, M10 and RA compared to the regular series. Random missing allocation simulating real-life off-wrist episodes resulted in significant changes in most parameters, and the imputation of zeroes significantly increased the variance; however, replacing NA with mean or median resulted in patterns similar to those of NA. We recommend replacing 'zeroes' with NA whenever possible, given the risk of inflating invariance using zeroes. If the parameters cannot be computed in the presence of NA, we recommend using the weekly mean of corresponding timepoints.

Sleep disturbances, circadian activity, and nocturnal light exposure characterize high risk for and current depression in adolescence.

STUDY OBJECTIVES: Major depressive disorder (MDD) in adolescence is associated with irregularities in circadian rhythms and sleep. The characterization of such impairment may be critical to design effective interventions to prevent development of depression among adolescents. This study aimed to examine self-reported and actimetry-based circadian rhythms and sleep-wake behavior associated with current MDD and high risk (HR) for MDD among adolescents. METHODS: Ninety-six adolescents who took part in the IDEA-RiSCo study were recruited using an empirically developed depression-risk stratification method: 26 classified as low risk (LR), 31 as HR, and 39 as a current depressive episode (MDD). We collected self-report data on insomnia, chronotype, sleep schedule, sleep hygiene as well as objective data on sleep, rest-activity, and light exposure rhythms using actimetry for 10 days. RESULTS: Adolescents with MDD exhibited more severe insomnia, shorter sleep duration, higher social jetlag (SJL), lower relative amplitude (RA) of activity, and higher exposure to artificial light at night (ALAN) compared with the other groups. They also presented poorer sleep hygiene compared with the LR group. The HR group also showed higher insomnia, lower RA, higher exposure to ALAN, and higher SJL compared with the LR group. CONCLUSIONS: HR adolescents shared sleep and rhythm alterations with the MDD group, which may constitute early signs of depression, suggesting that preventive strategies targeting sleep should be examined in future studies. Furthermore, we highlight that actimetry-based parameters of motor activity (particularly RA) and light exposure are promising constructs to be explored as tools for assessment of depression in adolescence.

Effective recommendations towards healthy routines to preserve mental health during the COVID-19 pandemic.

OBJECTIVE: To assess the adherence to a set of evidence-based recommendations to support mental health during the coronavirus disease 2019 (COVID-19) pandemic and its association with depressive and anxiety symptoms. METHODS: A team of health workers and researchers prepared the recommendations, formatted into three volumes (1: COVID-19 prevention; 2: Healthy habits; 3: Biological clock and sleep). Participants were randomized to receive only Volume 1 (control), Volumes 1 and 2, Volumes 1 and 3, or all volumes. We used a convenience sample of Portuguese-speaking participants over age 18 years. An online survey consisting of sociodemographic and behavioral questionnaires and mental health instruments (Patient Health Questionnaire-9 [PHQ-9] and Generalized Anxiety Disorder-7 [GAD-7]) was administered. At 14 and 28 days later, participants were invited to complete follow-up surveys, which also included questions regarding adherence to the recommendations. A total of 409 participants completed the study - mostly young adult women holding university degrees. RESULTS: The set of recommendations contained in Volumes 2 and 3 was effective in protecting mental health, as suggested by significant associations of adherence with PHQ-9 and GAD-7 scores (reflecting anxiety and depression symptoms, respectively). CONCLUSION: The recommendations developed in this study could be useful to prevent negative mental health effects in the context of the pandemic and beyond.

Melatonin and Depression: A Translational Perspective From Animal Models to Clinical Studies.

Daily rhythm of melatonin synchronizes the body to the light/dark environmental cycle. Several hypotheses have been raised to understand the intersections between melatonin and depression, in which changes in rest-activity and sleep patterns are prominent. This review describes key experimental and clinical evidence that link melatonin with the etiopathology and symptomatology of depressive states, its role in the follow up of therapeutic response to antidepressants, as well as the clinical evidence of melatonin as MDD treatment. Melatonin, as an internal temporal cue contributing to circadian organization and best studied in the context of circadian misalignment, is also implicated in neuroplasticity. The monoaminergic systems that underly MDD and melatonin production overlap. In addition, the urinary metabolite 6-sulfatoxymelatonin (aMT6) has been proposed as biomarker for antidepressant responders, by revealing whether the blockage of noradrenaline uptake has taken place within 24 h from the first antidepressant dose. Even though animal models show benefits from melatonin supplementation on depressive-like behavior, clinical evidence is inconsistent vis-à-vis prophylactic or therapeutic benefits of melatonin or melatonin agonists in depression. We argue that the study of melatonin in MDD or other psychiatric disorders must take into account the specificities of melatonin as an integrating molecule, inextricably linked to entrainment, metabolism, immunity, neurotransmission, and cell homeostasis.

Relationship Between Circadian Strain, Light Exposure, and Body Mass Index in Rural and Urban Quilombola Communities.

Industrialization has greatly changed human lifestyle; work and leisure activities have been moved indoors, and artificial light has been used to illuminate the night. As cyclic environmental cues such as light and feeding become weak and/or irregular, endogenous circadian systems are increasingly being disrupted. These disruptions are associated with metabolic dysfunction, possibly contributing to increased rates of overweight and obesity worldwide. Here, we aimed to investigate how activity-rest rhythms, patterns of light exposure, and levels of urbanization may be associated with body mass index (BMI) in a sample of rural and urban Quilombola communities in southern Brazil. These are characterized as remaining social groups who resisted the slavery regime that prevailed in Brazil. Quilombola communities were classified into five groups according to their stage of urbanization: from rural areas with no access to electricity to highly urbanized communities. We collected anthropometric data to calculate BMI, which was categorized as follows: from ≥ 18.5 kg/m2 to < 25 kg/m2 = normal weight; from ≥ 25 kg/m2 to < 30 kg/m2 = overweight; and ≥ 30 kg/m2 = obese. Subjects were asked about their sleep routines and light exposure on workdays and work-free days using the Munich Chronotype Questionnaire (N = 244 included). In addition, we analyzed actimetry data from 121 participants with seven consecutive days of recordings. Living in more urbanized areas and higher intradaily variability (IV) of activity-rest rhythms were associated with an increased risk of belonging to the overweight or obese group, when controlling for age and sex. These findings are consistent with preclinical data and point to potential strategies in obesity prevention and promotion of healthy metabolic profiles.

Circadian Strain, Light Exposure, and Depressive Symptoms in Rural Communities of Southern Brazil.

Irregular light-dark cycles and circadian/sleep disturbances have been suggested as risk or co-occurring factors in depression. Among a set of metrics developed to quantify strain on the circadian system, social jetlag (SJL) has been put forward as a measure of the discrepancy between biological and social clocks. Here, we approached the question on whether light exposure and SJL would also be associated with depressive symptoms in Quilombola communities in Southern Brazil. These rural communities are void of potential confounders of modern lifestyles and show low levels of SJL. 210 Quilombolas (age range 16-92; 56% women) were asked about their sleep times and light exposure using the Munich ChronoType Questionnaire (MCTQ). The Beck Depression Inventory (BDI) was used to assess depressive symptoms. Additionally, we analyzed 7-day actimetry recordings in 124 subjects. BDI scores higher than 10 (having clinically significant depressive symptoms; controlled for age and sex in the multivariate analysis) were positively associated with SJL >1 h and negatively associated with median light exposure during the day, especially in the morning from 8:00 to 10:00. Our results suggest that low light exposure during the day, and higher levels of SJL are associated with depressive symptoms; longitudinal and experimental studies are needed to understand the underlying mechanisms. Nevertheless, we highlight the potential of treatment strategies aimed at decreasing circadian strain and insufficient light exposure, which are suggested as areas of further research in Psychiatry.

Social timing influences sleep quality in patients with sleep disorders.

OBJECTIVES: We aimed to compare three variants of the Pittsburgh Sleep Quality Index (PSQI usual, work- and work-free days: PSQIu, PSQIw, PSQIf) and to assess whether chronotype (MSFsc)/social jetlag (SJL) are associated with sleep quality in patients with sleep disorders (SD). METHODS: In sum, 431 SD patients and 338 subjects from the general population (GP) were included. Participants filled in three variants of the PSQI and the Munich ChronoType Questionnaire (MCTQ). We used Generalized Estimating Equations (GEE) to investigate effects of group (GP, SD), PSQI (usual, work or free) and their interaction (group∗PSQI) on scores. To investigate associations between MSFsc/SJL and the difference between PSQIw and PSQIf (PSQIdiff) in patients with SD we used linear regressions (N = 352). We used Sobel to test whether there was a mediation effect of SJL on the association between MSFsc and PSQIdiff. RESULTS: PSQI scores differed between groups (p < 0.001). Post-hoc analysis revealed a significant difference between PSQIu vs. PSQIf and PSQIw vs. PSQIf with PSQIf presenting lower scores, while PSQIu vs. PSQIw did not differ in any group. In line with previous findings, SJL was associated to PSQIdiff in SD patients. CONCLUSIONS: PSQIu mainly represents sleep quality on workdays also in SD patients. Being a late chronotype seems to be associated with higher differences in sleep quality on work-vs. free days mostly when it coincides with societal time constraints. Since sleep quality is poorer on workdays even in SD patients, we suggest that treatment strategies should address social aspects affecting sleep, including ways of minimizing SJL.

The impact of selective serotonin reuptake inhibitors on the thyroid function among patients with major depressive disorder: A systematic review and meta-analysis.

Selective serotonin reuptake inhibitors (SSRI) have been claimed to negatively affect the thyroid function, albeit the evidence is controversial. We searched for studies that measured parameters of thyroid function (TSH, T4, Free T4, or T3) before and after a course of SSRI treatment in euthyroid patients with major depressive disorder. Electronic searches were conducted on MEDLINE, Embase and Web of Science databases from inception through April 4th, 2018. We performed random-effects meta-analyses to estimate the effect of SSRIs on each hormone. A total 1791 records were identified in the electronic search, and 14 observational clinical studies were included in the analyses. All studies had at least moderate risk of bias and were considered of low quality. A course of SSRI treatment was associated with a decrease in T4 of -6.58 nmol/L (95% Confidence Interval [CI], -12.17 to -.99, p = .005, I2=97%; Cohen's d = .50), a decrease in Free T4 of -.91 pmol/L (95% CI, -1.65 to -.16, p = .017, I2=96%; Cohen's d = .66), and a decrease in T3 of -.10 nmol/L (95% CI, -.18 to -.03, p = .007, I2=96%; Cohen's d = .45), and no effect on TSH (0.06 microIU/L, 95% CI, -.05 to .17, p = .285, I2=98%; Cohen's d = .17). We did not detect publication bias in any of the four meta-analyses. We conclude that there is preliminary evidence that SSRIs slightly decrease thyroid function, but quality of evidence is low. Clinical magnitude of such effect is yet unclear.

The µMCTQ: An Ultra-Short Version of the Munich ChronoType Questionnaire.

Individuals vary in how their circadian system synchronizes with the cyclic environment (zeitgeber). Assessing these differences in "phase of entrainment"-often referred to as chronotype-is an important procedure in laboratory experiments and epidemiological studies but is also increasingly applied in circadian medicine, both in diagnosis and therapy. While biochemical measurements (e.g., dim-light melatonin onset [DLMO]) of internal time are still the gold standard, they are laborious, expensive, and mostly rely on special conditions (e.g., dim light). Chronotype estimation in the form of questionnaires is useful in approximating the timing of an individual's circadian clock. They are simple, inexpensive, and location independent (e.g., administrable on- and offline) and can therefore be easily administered to many individuals. The Munich ChronoType Questionnaire (MCTQ) is an established instrument to assess chronotype by asking subjects about their sleep-wake-behavior. Here we present a shortened version of the MCTQ, the µMCTQ, for use in situations in which instrument length is critical, such as in large cohort studies. The µMCTQ contains only the core chronotype module of the standard MCTQ (stdMCTQ), which was shortened and adapted from 17 to 6 essential questions, allowing for a quick assessment of chronotype and other related parameters such as social jetlag and sleep duration. µMCTQ results correspond well to the ones collected by the stdMCTQ and are externally validated by actimetry and DLMO, assessed at home (no measure of compliance). Sleep onset, midpoint of sleep, and the µMCTQ-derived marker of chronotype showed slight deviations toward earlier times in the µMCTQ when compared with the stdMCTQ (<35 min). The µMCTQ assessment of chronotype showed good test-retest reliability and correlated significantly with phase markers from actimetry and melatonin (DLMO), especially with measurements taken on work-free days. Because of its brevity, the µMCTQ represents an ideal tool to estimate individual internal time in time-critical contexts, from large cohort studies to individualized medicine.

Chronotype and Social Jetlag: A (Self-) Critical Review.

The Munich ChronoType Questionnaire (MCTQ) has now been available for more than 15 years and its original publication has been cited 1240 times (Google Scholar, May 2019). Additionally, its online version, which was available until July 2017, produced almost 300,000 entries from all over the world (MCTQ database). The MCTQ has gone through several versions, has been translated into 13 languages, and has been validated against other more objective measures of daily timing in several independent studies. Besides being used as a method to correlate circadian features of human biology with other factors-ranging from health issues to geographical factors-the MCTQ gave rise to the quantification of old wisdoms, like "teenagers are late", and has produced new concepts, like social jetlag. Some like the MCTQ's simplicity and some view it critically. Therefore, it is time to present a self-critical view on the MCTQ, to address some misunderstandings, and give some definitions of the MCTQ-derived chronotype and the concept of social jetlag.