Investigating adverse daily life effects following a psychosocial laboratory stress task, and the moderating role of Psychopathology.

Laboratory stress tasks are necessary to closely investigate the stress response in a controlled environment. However, to our knowledge, no study has tested whether participating in such tasks can pose any daily life adverse effect. Fifty-three healthy participants (46 women) took part in a laboratory session where stress was induced using a typical psychosocial stressor: the repeated Montreal Imaging Stress Task (rMIST). Average levels of negative affect (NA), heart rate (HR), root mean square of successive differences (RMSSD), and skin conductance level (SCL), as well as reactivity across all these parameters as measured with the experience sampling method (ESM) in the four days prior to the laboratory session were compared with the four days following the session. We also assessed whether vulnerability to psychopathology moderated these associations. Findings showed that the task did not pose any significant adverse effect on participants. However, there was an unexpected increase in average RMSSD and a decrease in average SCL pre- to post- task. In addition, more vulnerable individuals were more likely to experience an increase in average levels of NA in the days following the task compared to the days preceding it. Our findings suggest that laboratory stress tasks may pose a significant risk to more vulnerable individuals.

Strategies, processes, outcomes, and costs of implementing experience sampling-based monitoring in routine mental health care in four European countries: study protocol for the IMMERSE effectiveness-implementation study.

BACKGROUND: Recent years have seen a growing interest in the use of digital tools for delivering person-centred mental health care. Experience Sampling Methodology (ESM), a structured diary technique for capturing moment-to-moment variation in experience and behaviour in service users' daily life, reflects a particularly promising avenue for implementing a person-centred approach. While there is evidence on the effectiveness of ESM-based monitoring, uptake in routine mental health care remains limited. The overarching aim of this hybrid effectiveness-implementation study is to investigate, in detail, reach, effectiveness, adoption, implementation, and maintenance as well as contextual factors, processes, and costs of implementing ESM-based monitoring, reporting, and feedback into routine mental health care in four European countries (i.e., Belgium, Germany, Scotland, Slovakia). METHODS: In this hybrid effectiveness-implementation study, a parallel-group, assessor-blind, multi-centre cluster randomized controlled trial (cRCT) will be conducted, combined with a process and economic evaluation. In the cRCT, 24 clinical units (as the cluster and unit of randomization) at eight sites in four European countries will be randomly allocated using an unbalanced 2:1 ratio to one of two conditions: (a) the experimental condition, in which participants receive a Digital Mobile Mental Health intervention (DMMH) and other implementation strategies in addition to treatment as usual (TAU) or (b) the control condition, in which service users are provided with TAU. Outcome data in service users and clinicians will be collected at four time points: at baseline (t0), 2-month post-baseline (t1), 6-month post-baseline (t2), and 12-month post-baseline (t3). The primary outcome will be patient-reported service engagement assessed with the service attachment questionnaire at 2-month post-baseline. The process and economic evaluation will provide in-depth insights into in-vivo context-mechanism-outcome configurations and economic costs of the DMMH and other implementation strategies in routine care, respectively. DISCUSSION: If this trial provides evidence on reach, effectiveness, adoption, implementation and maintenance of implementing ESM-based monitoring, reporting, and feedback, it will form the basis for establishing its public health impact and has significant potential to bridge the research-to-practice gap and contribute to swifter ecological translation of digital innovations to real-world delivery in routine mental health care. TRIAL REGISTRATION: ISRCTN15109760 (ISRCTN registry, date: 03/08/2022).

Longitudinal Assessment of Seasonal Impacts and Depression Associations on Circadian Rhythm Using Multimodal Wearable Sensing: Retrospective Analysis.

BACKGROUND: Previous mobile health (mHealth) studies have revealed significant links between depression and circadian rhythm features measured via wearables. However, the comprehensive impact of seasonal variations was not fully considered in these studies, potentially biasing interpretations in real-world settings. OBJECTIVE: This study aims to explore the associations between depression severity and wearable-measured circadian rhythms while accounting for seasonal impacts. METHODS: Data were sourced from a large longitudinal mHealth study, wherein participants' depression severity was assessed biweekly using the 8-item Patient Health Questionnaire (PHQ-8), and participants' behaviors, including sleep, step count, and heart rate (HR), were tracked via Fitbit devices for up to 2 years. We extracted 12 circadian rhythm features from the 14-day Fitbit data preceding each PHQ-8 assessment, including cosinor variables, such as HR peak timing (HR acrophase), and nonparametric features, such as the onset of the most active continuous 10-hour period (M10 onset). To investigate the association between depression severity and circadian rhythms while also assessing the seasonal impacts, we used three nested linear mixed-effects models for each circadian rhythm feature: (1) incorporating the PHQ-8 score as an independent variable, (2) adding seasonality, and (3) adding an interaction term between season and the PHQ-8 score. RESULTS: Analyzing 10,018 PHQ-8 records alongside Fitbit data from 543 participants (n=414, 76.2% female; median age 48, IQR 32-58 years), we found that after adjusting for seasonal effects, higher PHQ-8 scores were associated with reduced daily steps (ß=-93.61, P<.001), increased sleep variability (ß=0.96, P<.001), and delayed circadian rhythms (ie, sleep onset: ß=0.55, P=.001; sleep offset: ß=1.12, P<.001; M10 onset: ß=0.73, P=.003; HR acrophase: ß=0.71, P=.001). Notably, the negative association with daily steps was more pronounced in spring (ß of PHQ-8 × spring = -31.51, P=.002) and summer (ß of PHQ-8 × summer = -42.61, P<.001) compared with winter. Additionally, the significant correlation with delayed M10 onset was observed solely in summer (ß of PHQ-8 × summer = 1.06, P=.008). Moreover, compared with winter, participants experienced a shorter sleep duration by 16.6 minutes, an increase in daily steps by 394.5, a delay in M10 onset by 20.5 minutes, and a delay in HR peak time by 67.9 minutes during summer. CONCLUSIONS: Our findings highlight significant seasonal influences on human circadian rhythms and their associations with depression, underscoring the importance of considering seasonal variations in mHealth research for real-world applications. This study also indicates the potential of wearable-measured circadian rhythms as digital biomarkers for depression.

Abnormalities in emotion regulation are associated with negative, but not positive or disorganized schizotypy: An experience sampling study.

BACKGROUND: Schizotypy, a multidimensional construct with positive, negative, and disorganized dimensions, represents a vulnerability marker for the development of schizophrenia. Although there has been increasing evidence linking schizotypy to emotion regulation (ER) deficits, the specific association between different schizotypal dimensions and alterations in ER strategy use in daily life remains poorly understood. METHODS: Using the experience sampling method (ESM), the present study examined the associations between positive, negative, and disorganized schizotypy and ER strategy use in daily life in a nonclinical young adult sample (N = 258). Participants were instructed to report their ER strategy use 5 times a day for 14 days. Four adaptive ER strategies (reflection, reappraisal, social sharing, and distraction) and two maladaptive ER strategies (suppression and rumination) were included. RESULTS: Multilevel modeling analyses showed that positive schizotypal traits predicted greater use of adaptive ER strategies, while negative schizotypal traits predicted less use of adaptive ER strategies and more frequent use of emotional suppression in daily life. No associations between disorganized schizotypal traits and any ER strategy use were found. CONCLUSION: Schizotypy dimensions are differentiated by preferences for different ER strategies in daily life. The findings suggest a strong association between negative schizotypy and notable dysfunctions in ER, emphasizing the significance of negative schizotypy as a vulnerability factor for psychosis.

Not just emotion regulation, but cognition: An experience sampling study testing the relations of ecological interpretation biases and use of emotion regulation strategies with momentary affective states during daily life functioning.

BACKGROUND: Current research is moving from studying cognitive biases and maladaptive emotion regulation (ER) as relatively stable phenomena contributing to affective disturbances, adopting ecological methodologies, such as Experience Sampling Methods (ESM). However, there is still limited ESM evidence on the interactions between stress and ER strategies' use, and negative interpretation biases, regarding their relations with momentary affective states. In this study, we used a new ESM design to disentangle the contextual, regulatory and cognitive processes implicated in daily affective experiences. METHOD: A sample of 103 participants completed an ESM study (3 times a day for 10 days) that included self-reports of momentary affect, stress intensity, ER strategies' use and a cognitive task measuring momentary negative interpretation biases. RESULTS: Multilevel analyses supported significant interactions of both rumination and worry with stress intensity, to account for momentary higher negative and lower positive affect levels. Furthermore, higher state negative interpretation bias levels uniquely predicted both higher negative and lower positive momentary affect levels. CONCLUSION: This study implemented a novel online cognitive task within an ESM procedure, which helped to disentangle how contextual ER strategies' use and momentary cognitive biases uniquely relate to affective experiences in daily life.

A Comparison of Affective-Cognitive States in Daily Life Between Emerging Adults With and Without Past-Year Nonsuicidal Self-Injury.

Although the literature suggests trait-like differences in affective and cognitive vulnerabilities between individuals with and without a history of nonsuicidal self-injury (NSSI), little is known about how these dispositional differences are experienced in the natural environment. The present study compares the intensity, inertia, interaction, and variability of affective (negative and positive affect) and cognitive states (rumination, self-criticism) in the everyday lives of individuals who do and do not engage in NSSI. Using experience sampling methodology (ESM), 60 emerging adults (ages = 18-22 years) with and without past-year NSSI (equally distributed) completed eight questionnaires per day for 12 days (in total, 96 questionnaires per participant), resulting in 4,587 assessments (median compliance = 83.3%; IQR = 71.9-91.7). In a dynamic structural equation modeling framework, dynamic parameters (i.e., mean intensity, carryover effects, spillover effects, and within-person variability) were evaluated using multilevel vector autoregressive models. Emerging adults who engage in NSSI experience higher intensity and greater variability of negative affect, rumination, and self-criticism, whereas those who do not engage in NSSI experience higher intensity and lower variability of positive affect. In addition, past-year NSSI predicted stronger affective-cognitive interactions over time, with stronger spillover effects of negative and positive affect on subsequent rumination and self-criticism in individuals who engage in NSSI. Depressive symptoms and trait levels of emotion dysregulation and self-criticism partially negated these differences. Our findings provide evidence that emerging adults who self-injure experience more negative affective-cognitive states in daily life and point to the potential relevance of boosting positive emotions to buffer negative cognitions.

Changes in adolescents' daily-life solitary experiences during the COVID-19 pandemic: an experience sampling study.

BACKGROUND: Adolescent solitude was drastically impacted by the COVID-19 pandemic. As solitude is crucial for adolescent development through its association with both positive and negative developmental outcomes, it is critical to understand how adolescents' daily-life solitary experiences changed as a result of the pandemic. METHODS: Using three waves of Experience Sampling Method data from a longitudinal study, we compared adolescents' daily-life solitary experiences in the early (nT1=100; MAge=16.1; SDAge=1.9; 93% girls) and mid-pandemic (nT2=204; MAge=16.5; SDAge=2.0; 79% girls) to their pre-pandemic experiences. RESULTS: We found that adolescents with lower levels of pre-pandemic social support and social skills reported wanting to be alone less and feeling like an outsider more at both time points during the pandemic. In the mid-pandemic wave, adolescents with higher levels of pre-pandemic social support and social skills reported decreases in positive affect compared to the pre-pandemic wave. CONCLUSION: This study shows that adolescents' daily-life solitary experiences worsened throughout the COVID-19 pandemic. There should be continued concern for the wellbeing of all adolescents, not only those already at risk, as effects of the pandemic on mental health might only manifest later.

Anticipating future threats: Evidence for association, but not interaction, of childhood adversity and identity development with threat anticipation in adolescence.

AIM: Childhood adversity may result in a negative expectation of future interactions with others, also referred to as 'threat anticipation'. It may also negatively impact on identity development, which subsequently may influence how individuals deal with their environment. Here, we examine the hypotheses that (1) identity synthesis is associated with reduced anticipation of threat, whereas the opposite would be true for identity confusion, and (2) that identity confusion exacerbates the association between childhood adversity and threat anticipation. METHODS: One thousand nine hundred and thirteen adolescents from the general population (mean age = 13.8 years, SD = 1.86, range = 11-20) completed self-report questionnaires assessing exposure to childhood adversity, identity development and threat anticipation. RESULTS AND DISCUSSION: Identity development was significantly associated with threat anticipation in the expected direction: identity synthesis was associated with reduced anticipation of threat (ß = -.0013, p < .001), whereas identity confusion was association with increased threat anticipation (ß = .0017, p < .001). Furthermore, childhood adversity was positively associated with threat anticipation (ß = .0018, p < .001). However, no evidence for an interaction effect of identity on the association between childhood adversity and threat anticipation was found, suggesting childhood adversity and identity development have an independent rather than synergistic effect on threat anticipation. CONCLUSION: The current study illustrates the importance of exposure to childhood adversity and identity development for threat anticipation in adolescence. Further research is needed to clarify how both factors influence each other within a developmental framework.

The Role of Childhood Trauma in Affective Stress Recovery in Early Psychosis: An Experience Sampling Study.

BACKGROUND AND HYPOTHESES: Affective recovery, operationalized as the time needed for affect to return to baseline levels after daily stressors, may be a putative momentary representation of resilience. This study aimed to investigate affective recovery in positive and negative affect across subclinical and clinical stages of psychosis and whether this is associated with exposure to childhood trauma (sexual, physical, and emotional abuse). STUDY DESIGN: We used survival analysis to predict the time-to-recovery from a daily event-related stressor in a pooled sample of 3 previously conducted experience sampling studies including 113 individuals with first-episode psychosis, 162 at-risk individuals, and 94 controls. STUDY RESULTS: Negative affective recovery (ie, return to baseline following an increase in negative affect) was longer in individuals with first-episode psychosis compared with controls (hazard ratio [HR] = 1.71, 95% confidence interval [CI; 1.03, 2.61], P = .04) and in at-risk individuals exposed to high vs low levels of emotional abuse (HR = 1.31, 95% CI [1.06, 1.62], P = .01). Positive affective recovery (ie, return to baseline following a decrease in positive affect) did not differ between groups and was not associated with childhood trauma. CONCLUSIONS: Our results give first indications that negative affective recovery may be a putative momentary representation of resilience across stages of psychosis and may be amplified in at-risk individuals with prior experiences of emotional abuse. Understanding how affective recovery contributes to the development of psychosis may help identify new targets for prevention and intervention to buffer risk or foster resilience in daily life.

Investigating Receptivity and Affect Using Machine Learning: Ecological Momentary Assessment and Wearable Sensing Study.

BACKGROUND: As mobile health (mHealth) studies become increasingly productive owing to the advancements in wearable and mobile sensor technology, our ability to monitor and model human behavior will be constrained by participant receptivity. Many health constructs are dependent on subjective responses, and without such responses, researchers are left with little to no ground truth to accompany our ever-growing biobehavioral data. This issue can significantly impact the quality of a study, particularly for populations known to exhibit lower compliance rates. To address this challenge, researchers have proposed innovative approaches that use machine learning (ML) and sensor data to modify the timing and delivery of surveys. However, an overarching concern is the potential introduction of biases or unintended influences on participants' responses when implementing new survey delivery methods. OBJECTIVE: This study aims to demonstrate the potential impact of an ML-based ecological momentary assessment (EMA) delivery system (using receptivity as the predictor variable) on the participants' reported emotional state. We examine the factors that affect participants' receptivity to EMAs in a 10-day wearable and EMA-based emotional state-sensing mHealth study. We study the physiological relationships indicative of receptivity and affect while also analyzing the interaction between the 2 constructs. METHODS: We collected data from 45 healthy participants wearing 2 devices measuring electrodermal activity, accelerometer, electrocardiography, and skin temperature while answering 10 EMAs daily, containing questions about perceived mood. Owing to the nature of our constructs, we can only obtain ground truth measures for both affect and receptivity during responses. Therefore, we used unsupervised and supervised ML methods to infer affect when a participant did not respond. Our unsupervised method used k-means clustering to determine the relationship between physiology and receptivity and then inferred the emotional state during nonresponses. For the supervised learning method, we primarily used random forest and neural networks to predict the affect of unlabeled data points as well as receptivity. RESULTS: Our findings showed that using a receptivity model to trigger EMAs decreased the reported negative affect by >3 points or 0.29 SDs in our self-reported affect measure, scored between 13 and 91. The findings also showed a bimodal distribution of our predicted affect during nonresponses. This indicates that this system initiates EMAs more commonly during states of higher positive emotions. CONCLUSIONS: Our results showed a clear relationship between affect and receptivity. This relationship can affect the efficacy of an mHealth study, particularly those that use an ML algorithm to trigger EMAs. Therefore, we propose that future work should focus on a smart trigger that promotes EMA receptivity without influencing affect during sampled time points.

Higher emotion regulation flexibility predicts more stable negative emotions and faster affective recovery in early psychosis: an experience sampling study.

BACKGROUND: While evidence shows that people with early psychosis are flexible in using different emotion regulation (ER) strategies to manage the varying contextual demands, no studies have examined the effectiveness of such regulatory flexibility in this population. We addressed this issue by investigating whether and how ER flexibility relate to different dynamic aspects (variability, instability, inertia, and recovery) of negative affect (NA) in a combined early psychosis sample, consisting of both individuals at high clinical risk for psychosis and those diagnosed with first-episode psychosis. METHODS: Participants were 148 individuals from the INTERACT project, a multi-center randomized controlled trial on the efficacy of acceptance and commitment therapy in early psychosis. We utilized data from the baseline assessment, during which all participants completed six days of experience sampling assessment of momentary NA, as well as end-of-day assessments of ER strategy use. RESULTS: Multilevel models of within-person associations showed that greater ER flexibility was associated with more stable NA, and quicker recovery of NA from stressors during the day. Linear regression analyses of between-person associations showed that people who had more variable and unstable NA reported greater ER flexibility generally. No evidence was found for associations with NA inertia. CONCLUSIONS: The current study identified unique within-person and between-person links between ER flexibility and dynamics of NA in early psychosis. These findings further provide evidence for ER flexibility in early psychosis, emphasizing the adaptive nature of regulatory flexibility in relation to reduced instability in NA and faster recovery from NA in everyday life.

The temporal association between social isolation, distress, and psychotic experiences in individuals at clinical high-risk for psychosis.

BACKGROUND: Psychotic experiences (PEs) and social isolation (SI) seem related during early stages of psychosis, but the temporal dynamics between the two are not clear. Literature so far suggests a self-perpetuating cycle wherein momentary increases in PEs lead to social withdrawal, which, subsequently, triggers PEs at a next point in time, especially when SI is associated with increased distress. The current study investigated the daily-life temporal associations between SI and PEs, as well as the role of SI-related and general affective distress in individuals at clinical high risk (CHR) for psychosis. METHODS: We used experience sampling methodology in a sample of 137 CHR participants. We analyzed the association between SI, PEs, and distress using time-lagged linear mixed-effects models. RESULTS: SI did not predict next-moment fluctuations in PEs, or vice versa. Furthermore, although SI-related distress was not predictive of subsequent PEs, general affective distress during SI was a robust predictor of next-moment PEs. CONCLUSIONS: Our results suggest that SI and PEs are not directly related on a moment-to-moment level, but a negative emotional state when alone does contribute to the risk of PEs. These findings highlight the role of affective wellbeing during early-stage psychosis development.

Acceptance and Commitment Therapy for individuals at risk for psychosis or with a first psychotic episode: A qualitative study on patients' perspectives.

AIM: The aim of this qualitative study is to explore patients' perspectives on Acceptance and Commitment Therapy for early stages of psychosis. Therefore, we interviewed participants of the INTERACT study, that quantitatively investigated Acceptance and Commitment Therapy in Daily Life (ACT-DL) in combination with treatment as usual, for early stages of psychosis, comparing it to treatment as usual. METHODS: Within 6 months after finishing ACT-DL, we conducted semi-structured, individual interviews with 19 participants. All interviews were audio-recorded and transcribed. Thematic analysis was used for coding and analysis. RESULTS: Two overarching themes were formed: 'the meaning of ACT' and 'what to improve'. Considering the first, participants generally understood and connected with the meaning of ACT, noticing more awareness and acceptance of their thoughts and feelings, and living more in line with their personal values. The second theme included comments on the protocol not being personal or psychosis specific enough and some elements of ACT being too difficult to understand when having active psychotic symptoms. CONCLUSIONS: This study suggests that ACT is an acceptable and promising new form of treatment for early stages of psychosis, and it provides relevant information to further develop ACT for this group.

Childhood Adversity and Emerging Psychotic Experiences: A Network Perspective.

BACKGROUND AND HYPOTHESIS: Childhood adversity is associated with a myriad of psychiatric symptoms, including psychotic experiences (PEs), and with multiple psychological processes that may all mediate these associations. STUDY DESIGN: Using a network approach, the present study examined the complex interactions between childhood adversity, PEs, other psychiatric symptoms, and multiple psychological mediators (ie, activity-related and social stress, negative affect, loneliness, threat anticipation, maladaptive cognitive emotion regulation, attachment insecurity) in a general population, adolescent sample (n = 865, age 12-20, 67% female). STUDY RESULTS: Centrality analyses revealed a pivotal role of depression, anxiety, negative affect, and loneliness within the network and a bridging role of threat anticipation between childhood adversity and maladaptive cognitive emotion regulation. By constructing shortest path networks, we found multiple existing paths between different categories of childhood adversity and PEs, with symptoms of general psychopathology (ie, anxiety, hostility, and somatization) as the main connective component. Sensitivity analyses confirmed the robustness and stability of the networks. Longitudinal analysis in a subsample with Wave 2 data (n = 161) further found that variables with higher centrality (ie, depression, negative affect, and loneliness) better predicted follow-up PEs. CONCLUSIONS: Pathways linking childhood adversity to PEs are complex, with multifaceted psychological and symptom-symptom interactions. They underscore the transdiagnostic, heterotypic nature of mental ill-health in young people experiencing PEs, in agreement with current clinical recommendations.

Imager-A mobile health mental imagery-based ecological momentary intervention targeting reward sensitivity: A randomized controlled trial.

Robust reward sensitivity may help preserve mental well-being in the face of adversity and has been proposed as a key stress resilience factor. Here, we present a mobile health application, "Imager," which targets reward sensitivity by training individuals to create mental images of future rewarding experiences. We conducted a two-arm randomized controlled trial with 95 participants screened for reward sensitivity. Participants in the intervention group received an ecological momentary intervention-Imager, which encouraged participants to create mental images of rewarding events for 1 week. The control group participants received only ecological momentary assessment, without the instruction to generate mental images. Adherence to Imager was high; participants in the intervention group engaged in 88% of the planned activities. In the follow-up assessment, the intervention group reported less mental health symptoms, mainly in depression (ß = -0.34, df = 93, p = .004) and less perceived stress (ß = -0.18, df = 93, p = .035), than control group participants and compared with the baseline assessment. Our results show the positive effects of Imager on mental health symptoms. The encouraging effects of the app on mental health outcomes may lead to greater use of ecological momentary interventions in the clinical preventive practice of affective disorders.

Usability of the Experience Sampling Method in Specialized Mental Health Care: Pilot Evaluation Study.

BACKGROUND: Mental health problems occur in interactions in daily life. Yet, it is challenging to bring contextual information into the therapy room. The experience sampling method (ESM) may facilitate this by assessing clients' thoughts, feelings, symptoms, and behaviors as they are experienced in everyday life. However, the ESM is still primarily used in research settings, with little uptake in clinical practice. One aspect that may facilitate clinical implementation concerns the use of ESM protocols, which involves providing practitioners with ready-to-use ESM questionnaires, sampling schemes, visualizations, and training. OBJECTIVE: This pilot study's objective was to evaluate the usability of an ESM protocol for using the ESM in a specialized mental health care setting. METHODS: We created the ESM protocol using the m-Path software platform and tested its usability in clinical practice. The ESM protocol consists of a dashboard for practitioners (ie, including the setup of the template and data visualizations) and an app for clients (ie, for completing the ESM questionnaires). A total of 8 practitioners and 17 clients used the ESM in practice between December 1, 2020, and July 31, 2021. Usability was assessed using questionnaires, ESM compliance rates, and semistructured interviews. RESULTS: The usability was overall rated reasonable to good by practitioners (mean scores of usability items ranging from 5.33, SD 0.91, to 6.06, SD 0.73, on a scale ranging from 1 to 7). However, practitioners expressed difficulty in personalizing the template and reported insufficient guidelines on how to use the ESM in clinical practice. On average, clients completed 55% (SD 25%) of the ESM questionnaires. They rated the usability as reasonable to good, but their scores were slightly lower and more variable than those of the practitioners (mean scores of usability items ranging from 4.18, SD 1.70, to 5.94, SD 1.50 on a scale ranging from 1 to 7). Clients also voiced several concerns over the piloted ESM template, with some indicating no interest in the continued use of the ESM. CONCLUSIONS: The findings suggest that using an ESM protocol may facilitate the implementation of the ESM as a mobile health assessment tool in psychiatry. However, additional adaptions should be made before further implementation. Adaptions include providing training on personalizing questionnaires, adding additional sampling scheme formats as well as an open-text field, and creating a dynamic data visualization interface. Future studies should also identify factors determining the suitability of the ESM for specific treatment goals among different client populations.

Psychological Resilience Factors and Their Association With Weekly Stressor Reactivity During the COVID-19 Outbreak in Europe: Prospective Longitudinal Study.

BACKGROUND: Cross-sectional relationships between psychosocial resilience factors (RFs) and resilience, operationalized as the outcome of low mental health reactivity to stressor exposure (low "stressor reactivity" [SR]), were reported during the first wave of the COVID-19 pandemic in 2020. OBJECTIVE: Extending these findings, we here examined prospective relationships and weekly dynamics between the same RFs and SR in a longitudinal sample during the aftermath of the first wave in several European countries. METHODS: Over 5 weeks of app-based assessments, participants reported weekly stressor exposure, mental health problems, RFs, and demographic data in 1 of 6 different languages. As (partly) preregistered, hypotheses were tested cross-sectionally at baseline (N=558), and longitudinally (n=200), using mixed effects models and mediation analyses. RESULTS: RFs at baseline, including positive appraisal style (PAS), optimism (OPT), general self-efficacy (GSE), perceived good stress recovery (REC), and perceived social support (PSS), were negatively associated with SR scores, not only cross-sectionally (baseline SR scores; all P<.001) but also prospectively (average SR scores across subsequent weeks; positive appraisal (PA), P=.008; OPT, P<.001; GSE, P=.01; REC, P<.001; and PSS, P=.002). In both associations, PAS mediated the effects of PSS on SR (cross-sectionally: 95% CI -0.064 to -0.013; prospectively: 95% CI -0.074 to -0.0008). In the analyses of weekly RF-SR dynamics, the RFs PA of stressors generally and specifically related to the COVID-19 pandemic, and GSE were negatively associated with SR in a contemporaneous fashion (PA, P<.001; PAC,P=.03; and GSE, P<.001), but not in a lagged fashion (PA, P=.36; PAC, P=.52; and GSE, P=.06). CONCLUSIONS: We identified psychological RFs that prospectively predict resilience and cofluctuate with weekly SR within individuals. These prospective results endorse that the previously reported RF-SR associations do not exclusively reflect mood congruency or other temporal bias effects. We further confirm the important role of PA in resilience.

Emotion regulation in daily life in early psychosis: The role of contextual appraisals.

BACKGROUND: Little is known about whether and how contextual appraisals relate to emotion regulation (ER) strategy use across the ultra-high risk and first episode stages of psychosis. The present study extends previous research by investigating the extent to which different appraisal dimensions of the most negative and positive events of the day are associated with ER strategy use in individuals with ultra-high risk (UHR) and first-episode psychosis (FEP). METHOD: Sixty-eight UHR individuals and fifty-five FEP individuals filled out an experience sampling evening questionnaire for six consecutive days, in which their appraisal of intensity, importance and perceived control concerning the most negative or positive event of the day, and the ER strategies they deploy in response to these events were measured. RESULTS: Multilevel mixed effect models showed that intensity appraisal was most closely associated with ER strategy use, as opposed to importance and controllability appraisals. Higher intense negative events were associated with more rumination and social sharing, while less intense negative events were associated with more reappraisal. Higher intense positive events were associated with a greater number of deployed strategies and more efforts in using savoring, expression and social sharing. The UHR and FEP individuals did not significantly differ regarding effects of above-mentioned appraisal dimensions on ER. CONCLUSIONS: These results provide evidence supporting ER flexibility in early psychosis, and event intensity emerged as the dimension most strongly associated with ER. Future research should better account for other situational factors (such as social context) that might affect ER use in psychosis.

Challenges in Using mHealth Data From Smartphones and Wearable Devices to Predict Depression Symptom Severity: Retrospective Analysis.

BACKGROUND: Major depressive disorder (MDD) affects millions of people worldwide, but timely treatment is not often received owing in part to inaccurate subjective recall and variability in the symptom course. Objective and frequent MDD monitoring can improve subjective recall and help to guide treatment selection. Attempts have been made, with varying degrees of success, to explore the relationship between the measures of depression and passive digital phenotypes (features) extracted from smartphones and wearables devices to remotely and continuously monitor changes in symptomatology. However, a number of challenges exist for the analysis of these data. These include maintaining participant engagement over extended time periods and therefore understanding what constitutes an acceptable threshold of missing data; distinguishing between the cross-sectional and longitudinal relationships for different features to determine their utility in tracking within-individual longitudinal variation or screening individuals at high risk; and understanding the heterogeneity with which depression manifests itself in behavioral patterns quantified by the passive features. OBJECTIVE: We aimed to address these 3 challenges to inform future work in stratified analyses. METHODS: Using smartphone and wearable data collected from 479 participants with MDD, we extracted 21 features capturing mobility, sleep, and smartphone use. We investigated the impact of the number of days of available data on feature quality using the intraclass correlation coefficient and Bland-Altman analysis. We then examined the nature of the correlation between the 8-item Patient Health Questionnaire (PHQ-8) depression scale (measured every 14 days) and the features using the individual-mean correlation, repeated measures correlation, and linear mixed effects model. Furthermore, we stratified the participants based on their behavioral difference, quantified by the features, between periods of high (depression) and low (no depression) PHQ-8 scores using the Gaussian mixture model. RESULTS: We demonstrated that at least 8 (range 2-12) days were needed for reliable calculation of most of the features in the 14-day time window. We observed that features such as sleep onset time correlated better with PHQ-8 scores cross-sectionally than longitudinally, whereas features such as wakefulness after sleep onset correlated well with PHQ-8 longitudinally but worse cross-sectionally. Finally, we found that participants could be separated into 3 distinct clusters according to their behavioral difference between periods of depression and periods of no depression. CONCLUSIONS: This work contributes to our understanding of how these mobile health-derived features are associated with depression symptom severity to inform future work in stratified analyses.

Dynamic Modelling of Mental Resilience in Young Adults: Protocol for a Longitudinal Observational Study (DynaM-OBS).

BACKGROUND: Stress-related mental disorders are highly prevalent and pose a substantial burden on individuals and society. Improving strategies for the prevention and treatment of mental disorders requires a better understanding of their risk and resilience factors. This multicenter study aims to contribute to this endeavor by investigating psychological resilience in healthy but susceptible young adults over 9 months. Resilience is conceptualized in this study as the maintenance of mental health or quick recovery from mental health perturbations upon exposure to stressors, assessed longitudinally via frequent monitoring of stressors and mental health. OBJECTIVE: This study aims to investigate the factors predicting mental resilience and adaptive processes and mechanisms contributing to mental resilience and to provide a methodological and evidence-based framework for later intervention studies. METHODS: In a multicenter setting, across 5 research sites, a sample with a total target size of 250 young male and female adults was assessed longitudinally over 9 months. Participants were included if they reported at least 3 past stressful life events and an elevated level of (internalizing) mental health problems but were not presently affected by any mental disorder other than mild depression. At baseline, sociodemographic, psychological, neuropsychological, structural, and functional brain imaging; salivary cortisol and α-amylase levels; and cardiovascular data were acquired. In a 6-month longitudinal phase 1, stressor exposure, mental health problems, and perceived positive appraisal were monitored biweekly in a web-based environment, while ecological momentary assessments and ecological physiological assessments took place once per month for 1 week, using mobile phones and wristbands. In a subsequent 3-month longitudinal phase 2, web-based monitoring was reduced to once a month, and psychological resilience and risk factors were assessed again at the end of the 9-month period. In addition, samples for genetic, epigenetic, and microbiome analyses were collected at baseline and at months 3 and 6. As an approximation of resilience, an individual stressor reactivity score will be calculated. Using regularized regression methods, network modeling, ordinary differential equations, landmarking methods, and neural net-based methods for imputation and dimension reduction, we will identify the predictors and mechanisms of stressor reactivity and thus be able to identify resilience factors and mechanisms that facilitate adaptation to stressors. RESULTS: Participant inclusion began in October 2020, and data acquisition was completed in June 2022. A total of 249 participants were assessed at baseline, 209 finished longitudinal phase 1, and 153 finished longitudinal phase 2. CONCLUSIONS: The Dynamic Modelling of Resilience-Observational Study provides a methodological framework and data set to identify predictors and mechanisms of mental resilience, which are intended to serve as an empirical foundation for future intervention studies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/39817.