Burst versus continuous delivery design in digital mental health interventions: Evidence from a randomized clinical trial.

Objective: Digital mental health interventions delivered via smartphone-based apps effectively treat various conditions; however, optimizing their efficacy while minimizing participant burden remains a key challenge. In this study, we investigated the potential benefits of a burst delivery design (i.e. interventions delivered only in pre-defined time intervals) in comparison to the continuous delivery of interventions. Methods: We randomly assigned 93 participants to the continuous delivery (CD) or burst delivery (BD) group. The CD group engaged in ReApp, a mobile app that increases positive cognitive reappraisal with a consistent delivery schedule that provides five prompts per day throughout the 3-week-long study, while the BD group received five daily prompts only in the first and third weeks of the study. Results: No significant differences were found between the groups in terms of adherence, mental health outcomes (specifically depressive and anxiety symptoms), level of perceived stress, and perceived helpfulness of intervention. The BD group showed a significantly decreased perceived difficulty of intervention over time. Conclusions: The results suggest that the burst delivery may be as suitable for digital mental health interventions as the continuous delivery. The perceived difficulty of the intervention declined more steeply for the BD group, indicating that it improved the feasibility of the positive cognitive reappraisal intervention without hurting its efficacy. This outcome may inform the design of less burdensome interventions with improved outcomes in future research.

Intraindividual time-varying dynamic network of affects: linear autoregressive mixed-effects models for ecological momentary assessment.

An interesting recent development in emotion research and clinical psychology is the discovery that affective states can be modeled as a network of temporally interacting moods or emotions. Additionally, external factors like stressors or treatments can influence the mood network by amplifying or dampening the activation of specific moods. Researchers have turned to multilevel autoregressive models to fit these affective networks using intensive longitudinal data gathered through ecological momentary assessment. Nonetheless, a more comprehensive examination of the performance of such models is warranted. In our study, we focus on simple directed intraindividual networks consisting of two interconnected mood nodes that mutually enhance or dampen each other. We also introduce a node representing external factors that affect both mood nodes unidirectionally. Importantly, we disregard the potential effects of a current mood/emotion on the perception of external factors. We then formalize the mathematical representation of such networks by exogenous linear autoregressive mixed-effects models. In this representation, the autoregressive coefficients signify the interactions between moods, while external factors are incorporated as exogenous covariates. We let the autoregressive and exogenous coefficients in the model have fixed and random components. Depending on the analysis, this leads to networks with variable structures over reasonable time units, such as days or weeks, which are captured by the variability of random effects. Furthermore, the fixed-effects parameters encapsulate a subject-specific network structure. Leveraging the well-established theoretical and computational foundation of linear mixed-effects models, we transform the autoregressive formulation to a classical one and utilize the existing methods and tools. To validate our approach, we perform simulations assuming our model as the true data-generating process. By manipulating a predefined set of parameters, we investigate the reliability and feasibility of our approach across varying numbers of observations, levels of noise intensity, compliance rates, and scalability to higher dimensions. Our findings underscore the challenges associated with estimating individualized parameters in the context of common longitudinal designs, where the required number of observations may often be unattainable. Moreover, our study highlights the sensitivity of autoregressive mixed-effect models to noise levels and the difficulty of scaling due to the substantial number of parameters.

Running in the FAMILY: understanding and predicting the intergenerational transmission of mental illness.

Over 50% of children with a parent with severe mental illness will develop mental illness by early adulthood. However, intergenerational transmission of risk for mental illness in one's children is insufficiently considered in clinical practice, nor is it sufficiently utilised into diagnostics and care for children of ill parents. This leads to delays in diagnosing young offspring and missed opportunities for protective actions and resilience strengthening. Prior twin, family, and adoption studies suggest that the aetiology of mental illness is governed by a complex interplay of genetic and environmental factors, potentially mediated by changes in epigenetic programming and brain development. However, how these factors ultimately materialise into mental disorders remains unclear. Here, we present the FAMILY consortium, an interdisciplinary, multimodal (e.g., (epi)genetics, neuroimaging, environment, behaviour), multilevel (e.g., individual-level, family-level), and multisite study funded by a European Union Horizon-Staying-Healthy-2021 grant. FAMILY focuses on understanding and prediction of intergenerational transmission of mental illness, using genetically informed causal inference, multimodal normative prediction, and animal modelling. Moreover, FAMILY applies methods from social sciences to map social and ethical consequences of risk prediction to prepare clinical practice for future implementation. FAMILY aims to deliver: (i) new discoveries clarifying the aetiology of mental illness and the process of resilience, thereby providing new targets for prevention and intervention studies; (ii) a risk prediction model within a normative modelling framework to predict who is at risk for developing mental illness; and (iii) insight into social and ethical issues related to risk prediction to inform clinical guidelines.

Predictors of stress resilience in Parkinson's disease and associations with symptom progression.

People with Parkinson's disease (PD) are sensitive to effects of long-term stress, but might differ in stress resilience, i.e. the ability to maintain mental health despite adversity. It is unclear whether stress resilience in PD is predominantly determined by dopamine deficiency, psychosocial factors, or both. In PD animal models, chronic stressors accelerate disease progression, but evidence in humans is lacking. Our objectives were to (1) distinguish stressor-reactive from resilient PD patients, (2) identify resilience factors, and (3) compare symptom progression between stressor-reactive and resilient patients. We conducted a longitudinal survey in Personalized Parkinson Project participants (N = 350 PD). We used the COVID-19 pandemic as a model of a stressor, aligned in time for the entire cohort. COVID-19-related stressors, perceived stress, and PD symptoms were assessed at 11 timepoints (April-October 2020). Both pre-COVID and in-COVID clinical assessments were available. We quantified stressor-reactivity as the residual between actual and predicted perceived stress relative to COVID-19-related stressors, and modeled trajectories of stressor-reactivity across timepoints. We explored pre-COVID predictors of 6-month average stressor-reactivity, and tested whether stressor-reactivity was prospectively associated with one-year clinical progression rates. Latent class trajectory models distinguished patients with high (N = 123) or low (N = 227) stressor-reactivity. Pre-existing anxiety, rumination and non-motor symptom severity predicted high stressor-reactivity (risk factors), whereas quality of life, social support, positive appraisal style and cognitive abilities predicted low stressor-reactivity (resilience factors). PD-specific factors, e.g. disease duration, motor severity, and levodopa use, did not predict stressor-reactivity. The COVID-19 pandemic did not accelerate disease progression, but worsened depressive symptoms in stressor-reactive PD patients.

Replication study on the role of dopamine-dependent prefrontal reactivations in human extinction memory retrieval.

Even after successful extinction, conditioned fear can return. Strengthening the consolidation of the fear-inhibitory safety memory formed during extinction is one way to counteract return of fear. In a previous study, we found that post-extinction L-DOPA administration improved extinction memory retrieval 24 h later. Furthermore, spontaneous post-extinction reactivations of a neural activation pattern evoked in the ventromedial prefrontal cortex (vmPFC) during extinction predicted extinction memory retrieval, L-DOPA increased the number of these reactivations, and this mediated the effect of L-DOPA on extinction memory retrieval. Here, we conducted a preregistered replication study of this work in healthy male participants. We confirm that spontaneous post-extinction vmPFC reactivations predict extinction memory retrieval. This predictive effect, however, was only observed 90 min after extinction, and was not statistically significant at 45 min as in the discovery study. In contrast to our previous study, we find no evidence that L-DOPA administration significantly enhances retrieval and that this is mediated by enhancement of the number of vmPFC reactivations. However, additional non-preregistered analyses reveal a beneficial effect of L-DOPA on extinction retrieval when controlling for the trait-like stable baseline levels of salivary alpha-amylase enzymatic activity. Further, trait salivary alpha-amylase negatively predicts retrieval, and this effect is reduced by L-DOPA treatment. Importantly, the latter findings result from non-preregistered analyses and thus further investigation is needed.

Neurobiology and systems biology of stress resilience.

Stress resilience is the phenomenon that some people maintain their mental health despite exposure to adversity or show only temporary impairments followed by quick recovery. Resilience research attempts to unravel the factors and mechanisms that make resilience possible and to harness its insights for the development of preventative interventions in individuals at risk for acquiring stress-related dysfunctions. Biological resilience research has been lagging behind the psychological and social sciences but has seen a massive surge in recent years. At the same time, progress in this field has been hampered by methodological challenges related to finding suitable operationalizations and study designs, replicating findings, and modeling resilience in animals. We embed a review of behavioral, neuroimaging, neurobiological, and systems biological findings in adults in a critical methods discussion. We find preliminary evidence that hippocampus-based pattern separation and prefrontal-based cognitive control functions protect against the development of pathological fears in the aftermath of singular, event-type stressors [as found in fear-related disorders, including simpler forms of posttraumatic stress disorder (PTSD)] by facilitating the perception of safety. Reward system-based pursuit and savoring of positive reinforcers appear to protect against the development of more generalized dysfunctions of the anxious-depressive spectrum resulting from more severe or longer-lasting stressors (as in depression, generalized or comorbid anxiety, or severe PTSD). Links between preserved functioning of these neural systems under stress and neuroplasticity, immunoregulation, gut microbiome composition, and integrity of the gut barrier and the blood-brain barrier are beginning to emerge. On this basis, avenues for biological interventions are pointed out.

Self-report assessment of Positive Appraisal Style (PAS): Development of a process-focused and a content-focused questionnaire for use in mental health and resilience research.

Positive Appraisal Style Theory of Resilience posits that a person's general style of evaluating stressors plays a central role in mental health and resilience. Specifically, a tendency to appraise stressors positively (positive appraisal style; PAS) is theorized to be protective of mental health and thus a key resilience factor. To this date no measures of PAS exist. Here, we present two scales that measure perceived positive appraisal style, one focusing on cognitive processes that lead to positive appraisals in stressful situations (PASS-process), and the other focusing on the appraisal contents (PASS-content). For PASS-process, the items of the existing questionnaires Brief COPE and CERQ-short were analyzed in exploratory and confirmatory factor analyses (EFA, CFA) in independent samples (N = 1157 and N = 1704). The resulting 10-item questionnaire was internally consistent (α = .78, 95% CI [.86, .87]) and showed good convergent and discriminant validity in comparisons with self-report measures of trait optimism, neuroticism, urgency, and spontaneity. For PASS-content, a newly generated item pool of 29 items across stressor appraisal content dimensions (probability, magnitude, and coping potential) were subjected to EFA and CFA in two independent samples (N = 1174 and N = 1611). The resulting 14-item scale showed good internal consistency (α = .87, 95% CI [.86, .87]), as well as good convergent and discriminant validity within the nomological network. The two scales are a new and reliable way to assess self-perceived positive appraisal style in large-scale studies, which could offer key insights into mechanisms of resilience.

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.

German Version of the Mobile Agnew Relationship Measure: Translation and Validation Study.

BACKGROUND: The mobile Agnew Relationship Measure (mARM) is a self-report questionnaire for the evaluation of digital mental health interventions and their interactions with users. With the global increase in digital mental health intervention research, translated measures are required to conduct research with local populations. OBJECTIVE: The aim of this study was to translate and validate the original English version of the mARM into a German version (mARM-G). METHODS: A total of 2 native German speakers who spoke English as their second language conducted forward translation of the original items. This version was then back translated by 2 native German speakers with a fluent knowledge of English. An independent bilingual reviewer then compared these drafts and created a final German version. The mARM-G was validated by 15 experts in the field of mobile app development and 15 nonexperts for content validity and face validity; 144 participants were recruited to conduct reliability testing as well as confirmatory factor analysis. RESULTS: The content validity index of the mARM-G was 0.90 (expert ratings) and 0.79 (nonexperts). The face validity index was 0.89 (experts) and 0.86 (nonexperts). Internal consistency for the entire scale was Cronbach α=.91. Confirmatory factor analysis results were as follows: the chi-square statistic to df ratio was 1.66. Comparative Fit Index was 0.87 and the Tucker-Lewis Index was 0.86. The root mean square error of approximation was 0.07. CONCLUSIONS: The mARM-G is a valid and reliable tool that can be used for future studies in German-speaking countries.

Addressing mental health problems among persons without stable housing in the context of the COVID-19 pandemic: study protocol for a randomised trial. RESPOND - France.

BACKGROUND: The COVID-19 pandemic has had an impact on population-wide mental health and well-being. Although people experiencing socioeconomic disadvantage may be especially vulnerable, they experience barriers in accessing mental health care. To overcome these barriers, the World Health Organization (WHO) designed two scalable psychosocial interventions, namely the web-based Doing What Matters in Times of Stress (DWM) and the face-to-face Problem Management Plus (PM+), to help people manage stressful situations. Our study aims to test the effectiveness of a stepped-care program using DWM and PM + among individuals experiencing unstable housing in France - a majority of whom are migrant or have sought asylum. METHODS: This is a randomised controlled trial to evaluate the effectiveness and cost effectiveness of a stepped-care program using DWM and PM + among persons with psychological distress and experiencing unstable housing, in comparison to enhanced care as usual (eCAU). Participants (N = 210) will be randomised to two parallel groups: eCAU or eCAU plus the stepped-care program. The main study outcomes are symptoms of depression and anxiety measured using the Patient Health Questionnaire Anxiety and Depression Scale (PHQ-ADS). DISCUSSION: This randomised controlled trial will contribute to a better understanding of effective community-based scalable strategies that can help address the mental health needs of persons experiencing socioeconomic disadvantage, whose needs are high yet who frequently have limited access to mental health care services. TRIAL REGISTRATION: this randomised trial has been registered at ClinicalTrials.gov under the number NCT05033210.

Effectiveness of a scalable, remotely delivered stepped-care intervention to reduce symptoms of psychological distress among Polish migrant workers in the Netherlands: study protocol for the RESPOND randomised controlled trial.

BACKGROUND: The COVID-19 pandemic has negatively affected the mental health of international migrant workers (IMWs). IMWs experience multiple barriers to accessing mental health care. Two scalable interventions developed by the World Health Organization (WHO) were adapted to address some of these barriers: Doing What Matters in times of stress (DWM), a guided self-help web application, and Problem Management Plus (PM +), a brief facilitator-led program to enhance coping skills. This study examines whether DWM and PM + remotely delivered as a stepped-care programme (DWM/PM +) is effective and cost-effective in reducing psychological distress, among Polish migrant workers with psychological distress living in the Netherlands. METHODS: The stepped-care DWM/PM + intervention will be tested in a two-arm, parallel-group, randomized controlled trial (RCT) among adult Polish migrant workers with self-reported psychological distress (Kessler Psychological Distress Scale; K10 > 15.9). Participants (n = 212) will be randomized into either the intervention group that receives DWM/PM + with psychological first aid (PFA) and care-as-usual (enhanced care-as-usual or eCAU), or into the control group that receives PFA and eCAU-only (1:1 allocation ratio). Baseline, 1-week post-DWM (week 7), 1-week post-PM + (week 13), and follow-up (week 21) self-reported assessments will be conducted. The primary outcome is psychological distress, assessed with the Patient Health Questionnaire Anxiety and Depression Scale (PHQ-ADS). Secondary outcomes are self-reported symptoms of depression, anxiety, posttraumatic stress disorder (PTSD), resilience, quality of life, and cost-effectiveness. In a process evaluation, stakeholders' views on barriers and facilitators to the implementation of DWM/PM + will be evaluated. DISCUSSION: To our knowledge, this is one of the first RCTs that combines two scalable, psychosocial WHO interventions into a stepped-care programme for migrant populations. If proven to be effective, this may bridge the mental health treatment gap IMWs experience. TRIAL REGISTRATION: Dutch trial register NL9630, 20/07/2021, https://www.onderzoekmetmensen.nl/en/trial/27052.

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.

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.

Effectiveness of a mental health stepped-care programme for healthcare workers with psychological distress in crisis settings: a multicentre randomised controlled trial.

BACKGROUND: Evidence-based mental health interventions to support healthcare workers (HCWs) in crisis settings are scarce. OBJECTIVE: To evaluate the capacity of a mental health intervention in reducing anxiety and depression symptoms in HCWs, relative to enhanced care as usual (eCAU), amidst the COVID-19 pandemic. METHODS: We conducted an analyst-blind, parallel, multicentre, randomised controlled trial. We recruited HCWs with psychological distress from Madrid and Catalonia (Spain). The intervention arm received a stepped-care programme consisting of two WHO-developed interventions adapted for HCWs: Doing What Matters in Times of Stress (DWM) and Problem Management Plus (PM+). Each intervention lasted 5 weeks and was delivered remotely by non-specialist mental health providers. HCWs reporting psychological distress after DWM completion were invited to continue to PM+. The primary endpoint was self-reported anxiety/depression symptoms (Patient Health Questionnaire-Anxiety and Depression Scale) at week 21. FINDINGS: Between 3 November 2021 and 31 March 2022, 115 participants were randomised to stepped care and 117 to eCAU (86% women, mean age 37.5). The intervention showed a greater decrease in anxiety/depression symptoms compared with eCAU at the primary endpoint (baseline-adjusted difference 4.4, 95% CI 2.1 to 6.7; standardised effect size 0.8, 95% CI 0.4 to 1.2). No serious adverse events occurred. CONCLUSIONS: Brief stepped-care psychological interventions reduce anxiety and depression during a period of stress among HCWs. CLINICAL IMPLICATIONS: Our results can inform policies and actions to protect the mental health of HCWs during major health crises and are potentially rapidly replicable in other settings where workers are affected by global emergencies. TRIAL REGISTRATION NUMBER: NCT04980326.

Positive Prospective Mental Imagery Characteristics in Young Adults and Their Associations with Depressive Symptoms.

Background: Positive prospective mental imagery plays an important role in mental well-being, and depressive symptoms have been associated with difficulties in generating positive prospective mental images (PPMIs). We used a mobile app to gather PPMIs generated by young adults during the COVID-19 pandemic and analyzed content, characteristics, and associations with depressive symptoms. Methods: This is a secondary analysis of a randomized controlled trial with 95 healthy young adults allocated into two groups (intervention and control). Participants used the mobile app decreasing mental health symptoms for seven consecutive days. Fifty participants in the intervention group reported PPMIs at least three times per day using a mobile app inducing PPMI generation. We categorized entries into themes and applied moderation models to investigate associations between PPMI characteristics and depressive symptoms. Results: We distinguished 25 PPMI themes. The most frequent were related to consuming food and drinks, watching TV/streaming platforms, and doing sports. Vividness and ease of generation of PPMIs, but not their anticipation, pleasure intensity or number of engagements with the app were associated with fewer depressive symptoms. Conclusions: We identified PPMI themes in young adults and found significant negative associations between depressive symptoms and vividness and generation ease of PPMIs. These results may inform prevention and intervention science, including the design of personalized interventions. We discuss implications for future studies and treatment development for individuals experiencing diminished PPMI. Supplementary Information: The online version contains supplementary material available at 10.1007/s10608-023-10378-5.

Are we equally at risk of changing smoking behavior during a public health crisis? Impact of educational level on smoking from the TEMPO cohort.

BACKGROUND: The COVID-19 pandemic as a public health crisis has led to a significant increase in mental health difficulties. Smoking is strongly associated with mental health conditions, which is why the pandemic might have influenced the otherwise decline in smoking rates. Persons belonging to socioeconomically disadvantaged groups may be particularly affected, both because the pandemic has exacerbated existing social inequalities and because this group was more likely to smoke before the pandemic. We examined smoking prevalence in a French cohort study, focusing on differences between educational attainment. In addition, we examined the association between interpersonal changes in tobacco consumption and educational level from 2018 to 2021. METHODS: Using four assessments of smoking status available from 2009 to 2021, we estimated smoking prevalence over time, stratified by highest educational level in the TEMPO cohort and the difference was tested using chi2 test. We studied the association between interpersonal change in smoking status between 2018 and 2021 and educational attainment among 148 smokers, using multinomial logistic regression. RESULTS: Smoking prevalence was higher among those with low education. The difference between the two groups increased from 2020 to 2021 (4.8-9.4%, p < 0.001). Smokers with high educational level were more likely to decrease their tobacco consumption from 2018 to 2021 compared to low educated smokers (aOR = 2.72 [1.26;5.89]). CONCLUSION: Current findings showed a widening of the social inequality gap in relation to smoking rates, underscoring the increased vulnerability of persons with low educational level to smoking and the likely inadequate focus on social inequalities in relation to tobacco control policies during the pandemic.

Fear circuit-based neurobehavioral signatures mirror resilience to chronic social stress in mouse.

Consistent evidence from human data points to successful threat-safety discrimination and responsiveness to extinction of fear memories as key characteristics of resilient individuals. To promote valid cross-species approaches for the identification of resilience mechanisms, we establish a translationally informed mouse model enabling the stratification of mice into three phenotypic subgroups following chronic social defeat stress, based on their individual ability for threat-safety discrimination and conditioned learning: the Discriminating-avoiders, characterized by successful social threat-safety discrimination and extinction of social aversive memories; the Indiscriminate-avoiders, showing aversive response generalization and resistance to extinction, in line with findings on susceptible individuals; and the Non-avoiders displaying impaired aversive conditioned learning. To explore the neurobiological mechanisms underlying the stratification, we perform transcriptome analysis within three key target regions of the fear circuitry. We identify subgroup-specific differentially expressed genes and gene networks underlying the behavioral phenotypes, i.e., the individual ability to show threat-safety discrimination and respond to extinction training. Our approach provides a translationally informed template with which to characterize the behavioral, molecular, and circuit bases of resilience in mice.

Consensus design of a calibration experiment for human fear conditioning.

Fear conditioning is a widely used laboratory model to investigate learning, memory, and psychopathology across species. The quantification of learning in this paradigm is heterogeneous in humans and psychometric properties of different quantification methods can be difficult to establish. To overcome this obstacle, calibration is a standard metrological procedure in which well-defined values of a latent variable are generated in an established experimental paradigm. These intended values then serve as validity criterion to rank methods. Here, we develop a calibration protocol for human fear conditioning. Based on a literature review, series of workshops, and survey of N = 96 experts, we propose a calibration experiment and settings for 25 design variables to calibrate the measurement of fear conditioning. Design variables were chosen to be as theory-free as possible and allow wide applicability in different experimental contexts. Besides establishing a specific calibration procedure, the general calibration process we outline may serve as a blueprint for calibration efforts in other subfields of behavioral neuroscience that need measurement refinement.

Deep learning and differential equations for modeling changes in individual-level latent dynamics between observation periods.

When modeling longitudinal biomedical data, often dimensionality reduction as well as dynamic modeling in the resulting latent representation is needed. This can be achieved by artificial neural networks for dimension reduction and differential equations for dynamic modeling of individual-level trajectories. However, such approaches so far assume that parameters of individual-level dynamics are constant throughout the observation period. Motivated by an application from psychological resilience research, we propose an extension where different sets of differential equation parameters are allowed for observation subperiods. Still, estimation for intra-individual subperiods is coupled for being able to fit the model also with a relatively small dataset. We subsequently derive prediction targets from individual dynamic models of resilience in the application. These serve as outcomes for predicting resilience from characteristics of individuals, measured at baseline and a follow-up time point, and selecting a small set of important predictors. Our approach is seen to successfully identify individual-level parameters of dynamic models that allow to stably select predictors, that is, resilience factors. Furthermore, we can identify those characteristics of individuals that are the most promising for updates at follow-up, which might inform future study design. This underlines the usefulness of our proposed deep dynamic modeling approach with changes in parameters between observation subperiods.

Effectiveness of a stepped-care programme of WHO psychological interventions in migrant populations resettled in Italy: Study protocol for the RESPOND randomized controlled trial.

Introduction: Migrant populations, including workers, undocumented migrants, asylum seekers, refugees, internationally displaced persons, and other populations on the move, are exposed to a variety of stressors and potentially traumatic events before, during, and after the migration process. In recent years, the COVID-19 pandemic has represented an additional stressor, especially for migrants on the move. As a consequence, migration may increase vulnerability of individuals toward a worsening of subjective wellbeing, quality of life, and mental health, which, in turn, may increase the risk of developing mental health conditions. Against this background, we designed a stepped-care programme consisting of two scalable psychological interventions developed by the World Health Organization and locally adapted for migrant populations. The effectiveness and cost-effectiveness of this stepped-care programme will be assessed in terms of mental health outcomes, resilience, wellbeing, and costs to healthcare systems. Methods and analysis: We present the study protocol for a pragmatic randomized study with a parallel-group design that will enroll participants with a migrant background and elevated level of psychological distress. Participants will be randomized to care as usual only or to care a usual plus a guided self-help stress management guide (Doing What Matters in Times of Stress, DWM) and a five-session cognitive behavioral intervention (Problem Management Plus, PM+). Participants will self-report all measures at baseline before random allocation, 2 weeks after DWM delivery, 1 week after PM+ delivery and 2 months after PM+ delivery. All participants will receive a single-session of a support intervention, namely Psychological First Aid. We will include 212 participants. An intention-to-treat analysis using linear mixed models will be conducted to explore the programme's effect on anxiety and depression symptoms, as measured by the Patient Health Questionnaire-Anxiety and Depression Scale summary score 2 months after PM+ delivery. Secondary outcomes include post-traumatic stress disorder symptoms, resilience, quality of life, resource utilization, cost, and cost-effectiveness. Discussion: This study is the first randomized controlled trial that combines two World Health Organization psychological interventions tailored for migrant populations with an elevated level of psychological distress. The present study will make available DWM/PM+ packages adapted for remote delivery following a task-shifting approach, and will generate evidence to inform policy responses based on a more efficient use of resources for improving resilience, wellbeing and mental health. Clinical trial registration: ClinicalTrials.gov, identifier: NCT04993534.