Background and Aims To elucidate the genetic architecture of blood pressure (BP) and heart rate (HR) during early life and assess their potential relevance to adult health outcomes.Methods The largest genome-wide association study (GWAS) meta-analyses to date of childhood systolic BP, diastolic BP, pulse pressure, and mean arterial pressure (n = 28 425) and HR (n = 22 565) were conducted in children of European ancestry aged 4-17 years. Follow-up analyses included comparisons with adult GWAS results, polygenic risk score (PRS) analyses in independent cohorts of diverse ancestries, and a phenome-wide association study in the UK Biobank.Results Eight genome-wide significant loci were identified for childhood BP (KIAA2013, CACNB2, PLCE1, PAX2, COL4A2, RP11-236L14.1, CFDP1, TPX2) and three loci for childhood HR (CCDC141, ACHE, MYH6); all novel in children but previously reported in adults. Childhood PRSs explained up to 1.6% of BP variance and 5.2% of HR variance among children of European ancestry. Genetic correlations between childhood and adulthood BP traits were moderate (rg = 0.4-0.7), suggesting age-specific genetic effects on BP. In the UK Biobank, higher childhood BP PRS levels were significantly associated with a broad range of adult health outcomes, particularly cardiometabolic outcomes such as hypertension, angina, myocardial infarction, and cardiovascular disease-related mortality.Conclusions These findings advance the understanding of the genetic architecture of childhood BP and HR and provide compelling genetic evidence linking childhood BP to a broad spectrum of adult health outcomes-particularly cardiometabolic conditions-which may inform targeted prevention strategies from a young age.

INTRODUCTION:Depressive symptoms are common in cancer survivors. Recognizing depression can be complicated due to recall bias or oncological treatment-related symptoms including cognitive problems, which in turn may undermine the reliability of self-report questionnaires. AIM:To explore the feasibility and patient satisfaction of smartphone-based Ecological Momentary Assessment (EMA) in primary care cancer survivors. METHODS:Patients > 18 years, curatively treated for cancer within the past two years, regardless whether they experienced depressive symptoms, were selected based on the GPs' health records. EMA questionnaires were sent three times daily for 6 weeks, covering positive and negative affect, along with related experiences. Patients received weekly EMA feedback reports. After the EMA period, they completed an evaluation questionnaire and participated in a follow-up phone call to discuss their EMA experiences. RESULTS:Patient recruitment achieved a reach of 17.0% who were invited for participation (158/931), of whom 33/158 agreed to participate yielding a response rate of 20.9%. Patients found the EMA questions clear and study participation easy with a completion rate of 67% among those who started. However, 64% felt the frequency of EMA prompts was excessive, with 52% considering the 6-week duration appropriate and 48% feeling it was too long. During phone call evaluations, patients reported becoming inattentive with filling out the EMA's. Weekly reports were viewed as relevant and provided valuable insights into levels and changes in their mood. CONCLUSION:The relatively low reach and response rate do not entirely support the feasibility and acceptability of a 6-week EMA in cancer survivors in primary care without depressive symptoms. EMA was, however, completed by a majority among those who started and was regarded as a user-friendly tool that offered valuable insights to individuals. It could potentially benefit cancer survivors or other patients who do experience depressive symptoms in primary care.

OBJECTIVES:Case conceptualization is essential to provide a holistic and person-tailored working theory for psychotherapy. The objective of this study was to illustrate the way how personalized Experience Sampling Method (ESM) can support this process by systematically monitoring daily-life experiences and providing structured feedback during schema therapy in later life. METHODS:A mixed-method case illustration of a patient in her seventies diagnosed with a recurrent depressive disorder and avoidant personality disorder, whose schema therapy had stalled. During eight weeks of schema therapy in an outpatient clinic for geriatric mental health care, she completed a personalized ESM diary assessing momentary affect (e.g., sadness), activities, (social) context, core beliefs, and coping strategies five times daily, tailored to her case-conceptualization and treatment goals. Feedback was delivered in three sessions via interactive reports visualizing ESM data trajectories, person-specific network graphs, and contextual notes. RESULTS:The patient completed 228/235 (97%) ESM assessments during six weeks and five days. Feedback sessions focused on 1) sadness, showing a reactive pattern to psychosocial stressors; 2) energy and physical activity, in relation to somatic complaints and mood; and 3) restlessness, which partially improved but persisted as a residual symptom. Evaluation of the collaborative feedback sessions with patient, therapist and researcher showed enhanced shared understanding of psychiatric complaints and more informed therapeutic decision-making. CONCLUSIONS:Integrating personalized ESM and ESM-based feedback in schema therapy appears feasible in later life, fostering awareness, insight, and self-management in patients. Systematic self-monitoring of complex symptom dynamics may complement case-conceptualization in psychotherapy.

Cross-sectional studies show that individuals diagnosed with depression are likely to reside in deprived neighbourhoods. However, whether social and physical neighbourhood characteristics contribute to the persistence of depression in understudied. The associations between 11 socioeconomic, social and physical neighbourhood characteristics, and persistence of depression were examined in a pooled sample of the Netherlands Study of Depression and Anxiety and the Netherlands Study of Depression in Older Persons cohorts. Participants (18-90 years) diagnosed with major depressive disorder (MDD), dysthymia or both at baseline were included (n = 1001). Using the Composite International Diagnostic Interview, persistent depression was defined as being diagnosed with MDD, dysthymia, or both at the 2-year follow-up. First, logistic regression models tested the association between each standardized neighbourhood characteristic and persistent depression, adjusting for individual-level characteristics. Second, age moderation between neighbourhood characteristics and persistent depression was tested. At 2-year follow-up, 466 (46%) had persistent depression. Neighbourhood socioeconomic position (NSEP) index (odds ratio (OR), 95% confidence interval ([95%CI]) = 0.86 [0.75-0.97]), percentage residents of non-Dutch origin (OR [95%CI]) = 1.24 [1.08-1.45]), social security beneficiaries [95%CI] = 1.14 [1.00-1.30], safety score (OR [95%CI] = 0.85 [0.75-0.97]) and green space (OR [95%CI] = 0.87 [0.76-1.03]), were associated with persistence of depression. Associations were not modified by age. These findings suggest that neighbourhood socioeconomic and environmental contexts may contribute to the persistence of depression beyond individual-level factors.

BackgroundPremenstrual disorders, including premenstrual syndrome, premenstrual dysphoric disorder, and premenstrual exacerbation of psychiatric disorders affect a significant portion of reproductive-age females. Accurate diagnosis and tailored treatment are often constrained by the limitations of traditional paper-based symptom diaries. These diaries lack flexibility for personalized symptom tracking and fail to capture treatment-relevant factors such as lifestyle and social events. A digital, adaptable symptom diary is therefore needed. In this paper, we present the protocol for the CycleWise study. This study is a multi-method study aimed at developing a digital menstrual cycle diary within PETRA (PErsonalized Treatment by Real-time Assessment), an ESM-based tool previously designed to support treatment in routine mental health care.Methods and analysisFollowing a human-centered design approach and the Centre for eHealth and Wellbeing Research roadmap, patients and clinicians will be involved throughout all phases to ensure the tool meets their needs. In the contextual inquiry phase, we will identify stakeholders and analyze current practices. The value specification phase will focus on assessing stakeholder needs through two focus groups and translating them into functional requirements. A user experience designer will then develop a prototype in the design phase, refining it iteratively based on stakeholder feedback. Implementation strategies will be formulated in the operationalization phase. Finally, uptake, impact and working mechanisms will be evaluated through qualitative interviews and quantitative measures.

Introduction: There is limited knowledge regarding the effect of anxiety symptoms on behavioural avoidance in patients diagnosed with a depressive disorder. The aim of this study is to improve insight into the association between levels of anxiety symptoms, daily life activity levels, social interactions, and physical activity in depressed individuals. Methods: Participants were 54 patients diagnosed with major depressive disorder experiencing mild to severe levels of depressive symptoms. The current study is a secondary analysis of the Transitions in Depression Recovery study (TRANS-ID Recovery). Symptoms of anxiety were assessed at baseline using the Symptom Check List-90 anxiety subscale. Daily life active behaviours were assessed using Ecological Momentary Assessment (EMA, five times a day for one week). We tested the between-subject associations between anxiety symptom levels and four operationalizations of active behaviours: number of activities, perceived physical activity, perceived social interaction, and social activity using linear mixed models. Additionally, we explored the association between anxiety levels and specific activities. Results: Levels of anxiety were not associated with any of the four operationalizations of active behaviour. However, in a post-hoc analysis, a positive association was found between levels of anxiety and the specific activity category 'household, groceries, administration'. Conclusions: Higher levels of symptoms of anxiety in depressed individuals are not associated with active behaviours in daily life but are associated with more household activities. In clinical practice, it therefore may be more beneficial to assess specific behaviours rather than broad categories of behaviour.

ABSTRACT Objectives Associations between physical activity and affect (activity‐affect dynamics) vary among individuals for which reasons remain unclear. We examined whether such heterogeneity is explained by psychiatric status or sociodemographic, clinical, and ambulatory assessment characteristics. Methods Two‐week ambulatory assessment data of 300 participants with current (n = 79), subthreshold (n = 67), and no (n = 154) depressive and/or anxiety disorders or symptoms were obtained from the Netherlands Study of Depression and Anxiety. Positive and negative affect (PA/NA) were assessed with ecological momentary assessment (5xdaily) and physical activity using actigraphy. Group iterative multiple model estimation was used to model associations shared across the sample, psychiatric subgroups, and those specific to individuals. Results No activity‐affect associations were shared across the sample (i.e., present in > 75% of all individuals) or psychiatric subgroups (i.e., present in > 51% of individuals within subgroups). Nevertheless, 45% of participants had at least one activity‐affect association, with considerable heterogeneity in their nature. The most frequent association was a positive contemporaneous association between physical activity and PA (present in 25% of the sample). Conclusions These findings suggest large heterogeneity in activity‐affect dynamics among individuals and underscore the importance of considering the unique dynamics of the individual.

Background/Objectives: Combined chronotherapy (CCT), which combines repeated sleep deprivation and light therapy, is used in the clinical treatment of severe depression. Despite its potential to rapidly reduce depressive symptoms, CCT is infrequently used in clinical practice. We explored whether actigraphy-derived within-patient changes in physical activity, sleep parameters, and sleep-wake patterns prior to CCT can help identify those most likely to benefit from this treatment, supporting personalized mental health care. Methods: Actigraphy data from nine severely depressed patients were collected before, during, and after CCT. Data were assessed with a questionnaire on depressive symptoms (Inventory of Depressive Symptomatology-Self Report, IDS-SR) and actigraphy measures for sleep-wake patterns and physical activity: daily mean activity level, rhythm (intradaily variability (IV), interdaily stability (IS)), Midpoint of Sleep (MSF), time in bed, sleep efficiency (SE), and the fragmentation index (FI). Variables were compared before and after CCT by systematic visual inspection due to the small sample size. A prior set Minimal Clinically Important Difference (MCID) of a 30% change in IDS scores from before and the week after CCT was used to categorize patients as responders (n = 3) or nonresponders (n = 6) to CCT. Results: After CCT, for both responders and nonresponders, there was a notable decrease in IDS, IV and FI. Prior to CCT, responders, compared to nonresponders, were characterized with higher IDS, more time in bed and higher FI, while having lower SE. Conclusions: We concluded that actigraphy assessments during regular CCT are feasible and found preliminary evidence that patients with the most disrupted sleep-wake patterns prior to treatment may benefit most from CCT.

BackgroundHeart rate variability (HRV) is related to cognitive functioning and may serve as an early Alzheimer's disease biomarker.ObjectiveWe examine whether HRV predicts cognitive and pathophysiological brain markers assessed eight and thirteen years later, independently of coronary calcification.Methods269 cognitively unimpaired adults were selected based on their coronary artery calcification score (absent, score=0; high, score≥300), obtained from cardiac computed tomography scans (T2, 2017-2022). HRV in the time domain (root mean square of successive RR interval differences), measured at T0 (2007-2013), T1 (2014-2017), and the change between T0 and T1, was the predictor. Outcomes included cognitive measures, serum Alzheimer's disease biomarkers, and brain imaging markers obtained at T3 (2022-2023). Linear regression models were run, stratified by coronary calcification groups and adjusted for demographics, lifestyle and cardiometabolic factors.ResultsParticipants with high T2 calcification showed lower HRV at T0 and a positive change compared to those with absent calcification. In participants with high T2 calcification, higher HRV at T0 was associated with lower Aβ42/Aβ40 at T3, while associations with all other markers were not significant. HRV at T1 and the change were not associated with any of the outcomes.ConclusionsHRV was not associated with cognitive and brain imaging outcomes. In participants with high calcification, higher HRV measured thirteen-year earlier, typically a marker of a healthier state, was associated with a lower Aβ42/Aβ40 ratio, typically linked to Alzheimer's disease. Findings underscore the need to consider coronary calcification in research of HRV as a marker of cognitive decline.

BACKGROUND:Insomnia represents a common sleep disorder in major depressive disorder (MDD) that is associated with unfavourable treatment outcomes. Yet, it is unknown whether this relationship varies between treatment modalities. The present study aimed to evaluate the predictive value of insomnia for remission status following pharmacotherapy, psychotherapy, and combined therapy. METHODS:Data were obtained from five randomised clinical trials investigating the efficacy of MDD treatment in a homogeneous study population. Patients with MDD (N = 898) aged between 18 and 65 years were assessed for insomnia (item score ≥ 2) and remission (total score ≤ 7) using the Hamilton depression rating scale (HDRS-17). Logistic regression analyses were performed to evaluate and compare the predictive value of pre-treatment insomnia for remission status following 24 weeks of treatment while controlling for sex, age, and baseline depression severity. RESULTS:Insomnia was associated with significantly lower odds of remission overall (OR = 0.618, 95%CI [0.450-0.849]) as well as for pharmacotherapy (OR = 0.219, 95%CI [0.069-0.692]) and combined therapy (OR = 0.583, 95%CI [0.348-0.976]) but not for psychotherapy. The predictive value was, however, not significantly different between the treatment modalities even though direct comparisons revealed significantly higher odds of remission following psychotherapy compared to pharmacotherapy in the insomnia relative to the control group (OR = 3.414, 95%CI [1.013-11.505]). CONCLUSION:Insomnia is associated with a decreased likelihood of remission in MDD. The most profound impact is observed for pharmacotherapy and combined therapy whereas the clinical relevance for psychotherapy appears modest.

The Poincaré plot was introduced as a tool to analyze heart rate variations caused by arrhythmias. Later, it was applied to time series with normal beats. The plot shows the relationship between the inter-beat interval (IBI) of one beat to the next. Several parameters were developed to characterize this relationship. The short and long axis of the fitting ellipse, SD1 and SD2, respectively, their ratio, and their product are used. The difference between the IBI of a beat and m beats later are also studied, SD1(m) and SD2(m). We studied the mathematical relations between heart rate variability measures and the Poincaré measures in the time (standard deviation of IBI, SDNN, root mean square of successive differences, RMSSD) and frequency domain (power in low and high frequency band, and their ratio). We concluded that SD1 and SD2 do not provide new information compared to SDNN and RMSSD. Only the correlation coefficient r(m) provides new information for m > 1. Novel findings are that ln(SD2(m)/SD1(m)) = tanh−1(r(m)), which is an approximately normal distributed transformation of r(m), and that SD1(m) and SD2(m) can be calculated by multiplying the power spectrum by a weighing function that depends on m, revealing the relationship with spectral measures, but also the relationship between SD1(m) and SD2(m). Both lagged parameters are extremely difficult to interpret compared to low and high frequency power, which are more closely related to the functioning of the autonomic nervous system.

Psychopathological disorders are increasingly conceptualized as complex dynamic systems, which can be represented as networks of interconnected symptoms. These dynamic networks are often constructed using Multilevel Vector AutoRegression (mlVAR) models. However, psychological processes frequently violate these assumptions. An alternative approach for examining temporal relationships between variables is Dynamic Time Warping (DTW). This paper evaluates the potential applications, advantages, and disadvantages of DTW and mlVAR. As part of the Netherlands Study of Depression and Anxiety, an Ecological Momentary Assessment module was administered five times daily for 2 weeks, to 376 participants (Mean age 49.3 years, 64.4% women). We created item networks based on 20 of the mood and physical condition items from this module using the mlVAR and DTW techniques, and repeated these analyses using simulated data to explore violations of mlVAR assumptions, including various lagged relationships and the presence of collider variables. Analysis of simulated datasets revealed that mlVAR networks were more susceptible to spurious connections, while DTW produces more reliable networks under these conditions. While mlVAR better reveals causal relationships when assumptions are met, DTW provides a robust method for examining co-occurrence, synchrony, and the directionality of lagged connections in real-world psychological data.

Early warning signals are considered to be generic indicators of a system’s accumulating instability and ‘critical slowing down’ prior to substantial and abrupt transitions between stable states. In clinical psychology, these signals have been proposed to enable personalized predictions of the impending onset, recurrence and remission of mental health problems before changes in symptoms occur, thereby facilitating timely therapeutic interventions. In this Perspective, we question the idea that early warning signals in a person’s emotion time series can predict changes in mental health symptoms. Using the empirical findings to date and the theoretical and methodological limitations inherent in their application, we argue that there is little support for the use of early warning signals based on critical slowing down in clinical psychology. Deepening our knowledge of the theoretical foundations of these predictors and improving their measurement are key to clarifying the potential and boundaries for their use in psychopathology. It is necessary to build on the insights gained from early warning signal studies and to improve and evaluate alternative methods, keeping in mind that clinical applications require prospective, real-time predictions that not only indicate whether, but also when, a specific person is likely to experience changes in their mental health. Early warning signals have been proposed to predict symptom changes and to provide timely warnings of mental health risk and recovery. In this Perspective, Helmich et al. question the clinical utility of such signals and discuss alternative avenues for early change prediction.

Group-level studies showed associations between depressive symptoms and circadian rhythm elements, though whether these associations replicate at the within-person level remains unclear. We investigated whether changes in circadian rhythm elements (namely, rest-activity rhythm, physical activity, and sleep) occur close to depressive symptom transitions and whether there are differences in the amount and direction of circadian rhythm changes in individuals with and without transitions. We used 4 months of actigraphy data from 34 remitted individuals tapering antidepressants (20 with and 14 without depressive symptom transitions) to assess circadian rhythm variables. Within-person kernel change point analyses were used to detect change points (CPs) and their timing in circadian rhythm variables. In 69% of individuals experiencing transitions, CPs were detected near the time of the transition. No-transition participants had an average of 0.64 CPs per individual, which could not be attributed to other known events, compared to those with transitions, who averaged 1 CP per individual. The direction of change varied between individuals, although some variables showed clear patterns in one direction. Results supported the hypothesis that CPs in circadian rhythm occurred more frequently close to transitions in depression. However, a larger sample is needed to understand which circadian rhythm variables change for whom, and more single-subject research to untangle the meaning of the large individual differences.

Background Major Depressive Disorder (MDD) is one of the most prevalent psychiatric disorders, and involves high relapse rates in which persistent negative thinking and rumination (i.e., perseverative cognition [PC]) play an important role. Positive fantasizing and mindfulness are common evidence-based psychological interventions that have been shown to effectively reduce PC and subsequent depressive relapse. How the interventions cause changes in PC over time, is unknown, but likely differ between the two. Whereas fantasizing may change the valence of thought content, mindfulness may operate through disengaging from automatic thought patterns. Comparing mechanisms of both interventions in a clinical sample and a non-clinical sample can give insight into the effectivity of interventions for different individuals. The current study aims to 1) test whether momentary psychological and psychophysiological indices of PC are differentially affected by positive fantasizing versus mindfulness-based interventions, 2) test whether the mechanisms of change by which fantasizing and mindfulness affect PC differ between remitted MDD versus never-depressed (ND) individuals, and 3) explore potential moderators of the main effects of the two interventions (i.e., what works for whom). Methods In this cross-over trial of fantasizing versus mindfulness interventions, we will include 50 remitted MDD and 50 ND individuals. Before the start of the measurements, participants complete several individual characteristics. Daily-life diary measures of thoughts and feelings (using an experience sampling method), behavioural measures of spontaneous thoughts (using the Sustained Attention to Response Task), actigraphy, physiological measures (impedance cardiography, electrocardiography, and electroencephalogram), and measures of depressive mood (self-report questionnaires) are performed during the week before (pre-) the interventions and the week during (peri-) the interventions. After a wash-out of at least one month, pre- and peri-intervention measures for the second intervention are repeated. Discussion This is the first study integrating self-reports, behavioural-, and physiological measures capturing dynamics at multiple time scales to examine the differential mechanisms of change in PC by psychological interventions in individuals remitted from multiple MDD episodes and ND individuals. Unravelling how therapeutic techniques affect PC in remitted individuals might generate insights that allows development of personalised targeted relapse prevention interventions. Trial registration ClinicalTrials.gov: NCT06145984, November 16, 2023.

BACKGROUND:Motor activity fluctuations in healthy adults exhibit fractal patterns characterized by consistent temporal correlations across wide-ranging time scales. However, these patterns are disrupted by aging and psychiatric conditions. This study aims to investigate how fractal patterns vary across the sleep-wake cycle, differ based on individuals' recency of depression diagnosis, and change before and after a depressive episode. METHODS:Using actigraphy from two cohorts (n = 378), we examined fractal motor activity patterns both between individuals without depression and with varying recencies of depression and within individuals before and after depressive symptom recurrence. To evaluate fractal patterns, we quantified temporal correlations in motor activity fluctuations across different time scales using a scaling exponent, α. Linear mixed models were utilized to assess the influence of the sleep-wake cycle, (recency of) depression, and their interaction on α. RESULTS:Fractal activity patterns in all individuals varied across the sleep-wake cycle, showing stronger temporal correlations during wakefulness (larger α = 1.035 ± 0.003) and more random activity fluctuations during sleep (smaller α = 0.784 ± 0.004, p < 0.001). This sleep-wake difference was reduced in recently depressed individuals (1-6 months), leading to larger α during sleep (0.836 ± 0.017), compared to currently depressed (0.781 ± 0.018, p = 0.006), remitted (0.776 ± 0.014, p < 0.001), and never-depressed individuals (0.773 ± 0.016, p < 0.001). Moreover, remitted individuals who experienced depressive symptom recurrence during antidepressant tapering exhibited a larger α during sleep after the symptom onset as compared to before (after: α = 0.703 ± 0.022; before: α = 0.680 ± 0.022; p < 0.001). CONCLUSIONS:These findings suggest a link between fractal motor activity patterns during sleep and depressive symptom recurrence in remitted individuals and those with recent depression.

Loss-adaptation has been described as being characterized by ‘waves of grief’, which may result in a Prolonged Grief Disorder (PGD). Although this assumption about the fluctuating nature of grief is supported by theoretical work, it is not (yet) supported by empirical work. We are the first to explore to what extent PGD reactions fluctuate in everyday life and whether fluctuations in PGD reactions are related to overall PGD levels using experience sampling methodology (ESM). Data from 38 bereaved individuals (74

The current study investigated to what extent personalised information on interrelated risk-relevant behavioural, psychological, and contextual features obtained using experience sampling method (ESM) can be deployed to inform forensic case formulations of adult men with a history of sexual offences. Five adult men in outpatient forensic treatment for committing sexual offences monitored personal risk-relevant features using ESM and discussed the resulting feedback report with their therapist. Data were collected using the Twente engagement with Ehealth technologies Scale, an online questionnaire, a semi-structured interview and log data. Participants reported increased awareness of personal patterns of risk-relevant features and their possible association with the risk of sexual reoffending. The participants did not perceive the ESM procedure as burdensome or intrusive. Obtaining personalised information on risk-relevant features by ESM was feasible and achievable for adult men with a history of sexual offences. Insights derived from ESM measurements could enhance traditional forensic case formulation.PRACTICE IMPACT STATEMENTCombining experience sampling method (ESM) and traditional forensic case formulation can help adult men with a history of sexual offences to better understand patterns in their risk-relevant characteristics. A more thorough understanding of such patterns may improve treatment plans focused on desistance of sexual reoffending.

The experience sampling method (ESM) is increasingly used as a clinical tool in mental health care. Currently, ESM studies pay relatively little attention to assessing contextual factors, such as a person’s experience and perception of events, activities, and social interactions. This has been referred to as the 'contextual black box’. However, personalized context information is essential for applications in clinical settings to gain insight in triggering and maintaining factors of psychopathology. Typically, ESM context items are designed for nomothetic research questions, to capture broad factors that are shared across individuals, such as ‘unpleasant events’. We provide an overview of such items and argue that they have limited clinical utility. We instead propose an idiographic approach to ESM context assessment to obtain more specific and personalized information about individual clients. In the current manuscript, we outline three idiographic ESM techniques to context assessment with clinical potential. First, we illustrate qualitative ESM items that prompt clients to fill in text, such as a description of a specific unpleasant event they experienced. Second, we describe personalized response options and self-learning items that ask clients to define personally relevant response categories, such as types of events the client finds unpleasant. Third, we describe personalized ESM items that client and clinician select or formulate together for concepts of interest. We discuss the advantages and disadvantages of the idiographic approach. Additionally, we suggest future directions for clinical research aiming to address the ‘contextual black box’ and enhance the potential of ESM in mental health care.

Despite many available treatment options for depression, response rates remain suboptimal. To improve outcome, circadian markers may be suitable as markers of treatment response. This systematic review provides an overview of circadian markers that have been studied as predictors of response in treatment of depression. A search was performed (EMBASE, PUBMED, PSYCHINFO) for research studies or articles, randomized controlled trials and case report/series with no time boundaries on March 2, 2024 (PROSPERO: CRD42021252333). Other criteria were; an antidepressant treatment as intervention, treatment response measured by depression symptom severity and/or occurrence of a clinical diagnosis of depression and assessment of a circadian marker at baseline. 44 articles, encompassing 8,772 participants were included in the analysis. Although additional research is needed with less variation in types of markers and treatments to provide definitive recommendations, circadian markers, especially diurnal mood variation and chronotype, show potential to implement as response markers in the clinic.