Beyond Step Count: Are We Ready to Use Digital Phenotyping to Make Actionable Individual Predictions in Psychiatry?

Some models for mental disorders or behaviors (eg, suicide) have been successfully developed, allowing predictions at the population level. However, current demographic and clinical variables are neither sensitive nor specific enough for making individual actionable clinical predictions. A major hope of the "Decade of the Brain" was that biological measures (biomarkers) would solve these issues and lead to precision psychiatry. However, as models are based on sociodemographic and clinical data, even when these biomarkers differ significantly between groups of patients and control participants, they are still neither sensitive nor specific enough to be applied to individual patients. Technological advances over the past decade offer a promising approach based on new measures that may be essential for understanding mental disorders and predicting their trajectories. Several new tools allow us to continuously monitor objective behavioral measures (eg, hours of sleep) and densely sample subjective measures (eg, mood). The promise of this approach, referred to as digital phenotyping, was recognized almost a decade ago, with its potential impact on psychiatry being compared to the impact of the microscope on biological sciences. However, despite the intuitive belief that collecting densely sampled data (big data) improves clinical outcomes, recent clinical trials have not shown that incorporating digital phenotyping improves clinical outcomes. This viewpoint provides a stepwise development and implementation approach, similar to the one that has been successful in the prediction and prevention of cardiovascular disease, to achieve clinically actionable predictions in psychiatry.

How to distinguish promotion, prevention and treatment trials in public mental health? Study protocol for the development of the VErona-LUgano Tool (VELUT).

INTRODUCTION: Promoting mental health, preventing and treating mental disorders are critically important in public health, and many randomised controlled trials (RCTs) evaluate intervention strategies for these objectives. However, distinguishing promotion from prevention and from treatment RCTs is challenging. A tool to place studies along the promotion-to-treatment continuum in mental health research does not exist, leaving it to researchers and policymakers to decide on how to classify individual RCTs, which hinders evidence synthesis. METHODS AND ANALYSIS: We present a protocol for the development of a new tool to assist researchers in distinguishing RCTs along the promotion-to-treatment continuum. We will establish a Tool Development Group, and use the Population, Intervention, Comparison and Outcome framework to define constructs. We will generate, define, categorise and reduce the items in the tool using qualitative methods, including cognitive interviews and a Delphi exercise. Psychometric evaluation-including unidimensionality, local independence, monotonicity and item homogeneity-will include data collection, scoring, internal consistency checks and factor analysis of the tool's indicators for available RCTs. We will use standard Cohen's kappa statistics to assess the reliability of the tool. ETHICS AND DISSEMINATION: This study involves data collection from the already published literature. However, this protocol has been approved by the ethics committee of the Università della Svizzera Italiana (CE 2024 04). The results of the present project will be disseminated in peer-reviewed journals and at international and national scientific meetings. Training materials for the application of the tool will also be developed and disseminated to the scientific community. The tool and all related implementation materials will be published on a website and will be freely accessible to the public.

Exploring the return-on-investment for scaling screening and psychosocial treatment for women with common perinatal mental health problems in Malawi: Developing a cost-benefit-calculator tool.

This study sought to develop a user-friendly decision-making tool to explore country-specific estimates for costs and economic consequences of different options for scaling screening and psychosocial interventions for women with common perinatal mental health problems in Malawi. We developed a simple simulation model using a structure and parameter estimates that were established iteratively with experts, based on published trials, international databases and resources, statistical data, best practice guidance and intervention manuals. The model projects annual costs and returns to investment from 2022 to 2026. The study perspective is societal, including health expenditure and productivity losses. Outcomes in the form of health-related quality of life are measured in Disability Adjusted Life Years, which were converted into monetary values. Economic consequences include those that occur in the year in which the intervention takes place. Results suggest that the net benefit is relatively small at the beginning but increases over time as learning effects lead to a higher number of women being identified and receiving (cost­)effective treatment. For a scenario in which screening is first provided by health professionals (such as midwives) and a second screening and the intervention are provided by trained and supervised volunteers to equal proportions in group and individual sessions, as well as in clinic versus community setting, total costs in 2022 amount to US$ 0.66 million and health benefits to US$ 0.36 million. Costs increase to US$ 1.03 million and health benefits to US$ 0.93 million in 2026. Net benefits increase from US$ 35,000 in 2022 to US$ 0.52 million in 2026, and return-on-investment ratios from 1.05 to 1.45. Results from sensitivity analysis suggest that positive net benefit results are highly sensitive to an increase in staff salaries. This study demonstrates the feasibility of developing an economic decision-making tool that can be used by local policy makers and influencers to inform investments in maternal mental health.

Efficacy of a transdiagnostic Internet prevention approach in adolescents (EMPATIA study): study protocol of a randomized controlled trial.

BACKGROUND: Most mental disorders have their onset in adolescence. Preventive interventions during this period are important; however, help-seeking behavior is generally poor in this age group resulting in low treatment rates. Internet interventions are expected to be an effective, low-threshold, and scalable approach to overcome barriers to help-seeking, particularly for individuals experiencing subclinical symptoms. Internet-delivered indicated prevention seems promising as it targets individuals with minimal symptoms of mental disorders who might need care but are not help-seeking yet. Previous indicated prevention-approaches have mainly targeted specific risk-syndromes. However, this contradicts the increasing recognition of emerging psychopathology as a complex system characterized by co-occurrence and rapid shifts of subclinical symptoms cutting across diagnostic categories. Therefore, this study will investigate the efficacy, mediators, moderators, and core symptomatic changes of a transdiagnostic Internet-delivered indicated prevention program (EMPATIA program) for adolescents. METHODS: This randomized controlled trial (RCT) will be conducted in a general population sample (planned n = 152) of adolescents aged 12-18 years with subclinical symptoms but without any current or past mental disorder. Participants will be randomly assigned to the EMPATIA program or a care as usual (CAU) control condition. The 8-week guided EMPATIA program encompasses 8 modules targeting the following transdiagnostic mechanisms: repetitive negative thinking, self-perfectionism, emotion regulation, intolerance of uncertainty, rejection sensitivity, and behavioral avoidance. Participants will be asked to answer online self-report questionnaires at baseline, after 8 weeks, and at 6-, 9-, and 12-month follow-up. Diagnostic telephone interviews will be conducted at baseline and at 12-month follow-up. Additionally, intervention-specific constructs (motivation, alliance, negative effects, satisfaction, adherence) will be assessed during and after the EMPATIA program. The level of self-reported general psychopathology post-intervention is the primary outcome. DISCUSSION: Results will be discussed considering the potential of Internet interventions as a scalable, low-threshold option for indicated prevention in adolescents experiencing subclinical symptoms. The EMPATIA program introduces a novel Internet prevention program targeting six transdiagnostic mechanisms associated with various mental health outcomes. Thereby, this trial pursues a very timely and important topic because it may contribute to narrow the current care gap for adolescents, to prevent mental health problems and related negative consequences, and to promote mental health in the long-term. TRIAL REGISTRATION: The trial was approved by Swissmedic (Registration Number: 10001035, 08/22/2022) and the Ethics Committee of Bern (Registration Number: 2022-D0036, 08/22/2022). The trial was registered at ClinicalTrials.gov NCT05934019 on 07-03-2023.

Using joint probability density to create most informative unidimensional indices: a new method using pain and psychiatric severity as examples.

BACKGROUND: Dimension reduction methods do not always reduce their underlying indicators to a single composite score. Furthermore, such methods are usually based on optimality criteria that require discarding some information. We suggest, under some conditions, to use the joint probability density function (joint pdf or JPD) of p-dimensional random variable (the p indicators), as an index or a composite score. It is proved that this index is more informative than any alternative composite score. In two examples, we compare the JPD index with some alternatives constructed from traditional methods. METHODS: We develop a probabilistic unsupervised dimension reduction method based on the probability density of multivariate data. We show that the conditional distribution of the variables given JPD is uniform, implying that the JPD is the most informative scalar summary under the most common notions of information. B. We show under some widely plausible conditions, JPD can be used as an index. To use JPD as an index, in addition to having a plausible interpretation, all the random variables should have approximately the same direction(unidirectionality) as the density values (codirectionality). We applied these ideas to two data sets: first, on the 7 Brief Pain Inventory Interference scale (BPI-I) items obtained from 8,889 US Veterans with chronic pain and, second, on a novel measure based on administrative data for 912 US Veterans. To estimate the JPD in both examples, among the available JPD estimation methods, we used its conditional specifications, identified a well-fitted parametric model for each factored conditional (regression) specification, and, by maximizing the corresponding likelihoods, estimated their parameters. Due to the non-uniqueness of conditional specification, the average of all estimated conditional specifications was used as the final estimate. Since a prevalent common use of indices is ranking, we used measures of monotone dependence [e.g., Spearman's rank correlation (rho)] to assess the strength of unidirectionality and co-directionality. Finally, we cross-validate the JPD score against variance-covariance-based scores (factor scores in unidimensional models), and the "person's parameter" estimates of (Generalized) Partial Credit and Graded Response IRT models. We used Pearson Divergence as a measure of information and Shannon's entropy to compare uncertainties (informativeness) in these alternative scores. RESULTS: An unsupervised dimension reduction was developed based on the joint probability density (JPD) of the multi-dimensional data. The JPD, under regularity conditions, may be used as an index. For the well-established Brief Pain Interference Inventory (BPI-I (the short form with 7 Items) and for a new mental health severity index (MoPSI) with 6 indicators, we estimated the JPD scoring. We compared, assuming unidimensionality, factor scores, Person's scores of the Partial Credit model, the Generalized Partial Credit model, and the Graded Response model with JPD scoring. As expected, all scores' rankings in both examples were monotonically dependent with various strengths. Shannon entropy was the smallest for JPD scores. Pearson Divergence of the estimated densities of different indices against uniform distribution was maximum for JPD scoring. CONCLUSIONS: An unsupervised probabilistic dimension reduction is possible. When appropriate, the joint probability density function can be used as the most informative index. Model specification and estimation and steps to implement the scoring were demonstrated. As expected, when the required assumption in factor analysis and IRT models are satisfied, JPD scoring agrees with these established scores. However, when these assumptions are violated, JPD scores preserve all the information in the indicators with minimal assumption.

Interventions targeting patients with co-occuring severe mental illness and substance use (dual diagnosis) in general practice settings - a scoping review of the literature.

BACKGROUND: People with dual diagnosis die prematurely compared to the general population, and general practice might serve as a setting in the healthcare system to mend this gap in health inequity. However, little is known about which interventions that have been tested in this setting. AIM: To scope the literature on interventions targeting patients with dual diagnosis in a general practice setting, the outcomes used, and the findings. DESIGN AND SETTING: A scoping review of patients with dual diagnosis in general practice. METHODS: From a predeveloped search string, we used PubMed (Medline), PsychInfo, and Embase to identify scientific articles on interventions. Studies were excluded if they did not evaluate an intervention, if patients were under 18 years of age, and if not published in English. Duplicates were removed and all articles were initially screened by title and abstract and subsequent fulltext were read by two authors. Conflicts were discussed within the author group. A summative synthesis of the findings was performed to present the results. RESULTS: Seven articles were included in the analysis. Most studies investigated integrated care models between behavioural treatment and primary care, and a single study investigated the delivery of Cognitive Behavioral treatment (CBT). Outcomes were changes in mental illness scores and substance or alcohol use, treatment utilization, and implementation of the intervention in question. No studies revealed significant outcomes for patients with dual diagnosis. CONCLUSION: Few intervention studies targeting patients with dual diagnosis exist in general practice. This calls for further investigation of the possibilities of implementing interventions targeting this patient group in general practice.

Development of an eye-tracking system based on a deep learning model to assess executive function in patients with mental illnesses.

Patients with mental illnesses, particularly psychosis and obsessive‒compulsive disorder (OCD), frequently exhibit deficits in executive function and visuospatial memory. Traditional assessments, such as the Rey‒Osterrieth Complex Figure Test (RCFT), performed in clinical settings require time and effort. This study aimed to develop a deep learning model using the RCFT and based on eye tracking to detect impaired executive function during visuospatial memory encoding in patients with mental illnesses. In 96 patients with first-episode psychosis, 49 with clinical high risk for psychosis, 104 with OCD, and 159 healthy controls, eye movements were recorded during a 3-min RCFT figure memorization task, and organization and immediate recall scores were obtained. These scores, along with the fixation points indicating eye-focused locations in the figure, were used to train a Long Short-Term Memory + Attention model for detecting impaired executive function and visuospatial memory. The model distinguished between normal and impaired executive function, with an F1 score of 83.5%, and identified visuospatial memory deficits, with an F1 score of 80.7%, regardless of psychiatric diagnosis. These findings suggest that this eye tracking-based deep learning model can directly and rapidly identify impaired executive function during visuospatial memory encoding, with potential applications in various psychiatric and neurological disorders.

Clarifying terminology and definitions in education services for mental health users: A disambiguation study.

In the wake of the mental health crisis in children and adolescents, the coordination of education and mental health services has become a global priority. However, differing terminologies and classifications across sectors, hinder effective comparison. The classification in education focuses mainly on outputs like qualifications or throughputs like teaching programs. This proof-of-concept study tested the applicability of a standard classification of health services, the Description and Evaluation of Services and DirectoriEs (DESDE), to evaluate education services for mental health users in the context of Spain and The Netherlands. It was conducted alongside the PECUNIA project, that sought to develop methods for the assessment of mental health costs and outcomes in different sectors. The study followed an ontoterminology approach involving: 1) identification of services from a predefined list of 46 resource-use items, 2) disambiguation of identified services with the DESDE, and classifying them as accurate, ambiguous, vague or confuse; and 3) external validation by an expert panel. The analysis was conducted at the level of type of resource, target population and care provision. From the initial list, only ten of the resources could be categorized as services using DESDE, and not activities, interventions or professionals. Only four of them (8,65%) were accurate across all disambiguation categories. Experts were unaware of terminology problems in classification of service provision in the education sector. Classifications and glossaries can clarify service naming, description and costing allowing comparative effectiveness analysis and facilitating cross-sectoral planning. This should be grounded in common methodologies, tools, and units of analysis.

Towards effective screening for paternal perinatal mental illness: a meta-review of instruments and research gaps.

Background: Paternal perinatal mental illness (PPMI), which affects around one in 10 fathers, is under-recognised despite increasing awareness of men's mental health in the perinatal period. Social stigma and men's reluctance to seek help exacerbate this gap. Neglecting the mental health needs of new fathers not only puts them at increased risk for mental illness themselves, but also has a profound and long-lasting impact on their families, children and their own self-esteem as they navigate their new role in the family dynamic. Objective: This meta-review systematically identifies instruments assessing PPMI symptoms, evaluates their psychometric properties and applicability, presents key findings from studies using these tools, and identifies gaps and limitations in the literature on PPMI symptom assessment. Methods: A systematic literature review was conducted using search strategies applied to PubMed, PsycNet APA, Cochrane, and Web of Science, supplemented by hand searches. Relevant information was extracted from each included study. Extracted data were analysed narratively to address the research questions. Results: Findings identified limitations and gaps in current screening practices. While the Edinburgh Postnatal Depression Scale (EPDS) is the most widely used screening tool for both fathers and mothers, it inadequately captures atypical depressive symptoms in men. Cutoff scores lack consensus, and instrument sensitivity varies significantly due to cultural and sociodemographic factors. A number of other screening tools have been identified, most of which are more general and not specifically designed for perinatal mental health. Conclusion: This meta-review broadens perspectives on PPMI screening instruments, highlighting key themes, patterns, and differences across the included reviews. While a variety of screening tools are used, the review underscores the necessity for tools specifically tailored to fathers during the perinatal period.

The role of maternal and child healthcare providers in identifying and supporting perinatal mental health disorders.

BACKGROUND: Perinatal depression (PND) is underdiagnosed in the clinical setting. This study explores the role of obstetricians, and other primary care providers of maternal and child healthcare in detecting, screening, and referring women during the perinatal period identified as depressed, anxious, or exhibiting other symptoms of mental health disorders. METHOD: Information was gathered from obstetricians (n = 16), and other primary care providers (pediatricians, nurse practitioners, physician assistants) (n = 85), on identifying and supporting childbearing women with symptoms of perinatal depression using an online survey. RESULTS: Statistical comparisons across participant groups were adjusted for years of practice in the profession. Statistically significant differences were noted. Obstetricians inquired more about the mother's social support network (p = .011) and addressed mothers that appeared sad, upset, or unhappy (p = .044) compared to other primary care providers. Other primary care providers were more likely to refer patients to mental health support services (p = .005), provide PND-related information in their waiting rooms (p = .008), and use the Edinburgh Postnatal Depression Scale (EPDS) (p = .027). There was also a significant difference in positively identifying eight symptoms of PND between provider groups. Obstetricians had higher rates of identifying the following symptoms: excessive crying (p < .001), feeling little or no attachment to the infant (p < .001), little feeling of enjoyment (p = .021), feelings of failure (p < .001), hopelessness (p < .001), agitation with self and infant (p < .001), fear of being alone with the infant (p = .011), and fear that these symptoms would last (p < .001). CONCLUSION: Although certain screening practices were performed well, especially by the obstetrician group, screening deficits were noted within each group, and screening practices differed between groups. Training offered to maternal child health primary care providers on addressing perinatal mental health disorders may help improve provider screening practices and detection of PND symptoms in perinatal women. PND screening that combines face-to-face open-ended interviews with standardized screening tools can enhance patient-provider communication, potentially improving PND detection rates and follow-up care in perinatal women.

Measurement-Based Care for Pediatric and Adolescent Mental Health Disorders as a Decision-Making Support Paradigm for Clinical Practice: A Review.

This article makes a case to encourage pediatric/adolescent care providers and healthcare systems to implement measurement-based standardized assessments of patient's baseline and longitudinal health outcomes for mental disorders to help institute evidence-based treatments. The article discusses the current underutilization, challenges, barriers, and concerns from stakeholders with measurement-based care in clinical settings while also highlighting the advantages and importance of the aforementioned care model.

Developing a transdiagnostic Ecological Momentary Assessment protocol for psychopathology.

OBJECTIVES: The network approach to psychopathology posits that mental disorders emerge from dynamic interactions among psychopathology-relevant variables. Ecological Momentary Assessment (EMA) is frequently used to assess these variables in daily life. Considering the transdiagnostic nature of the network approach to psychopathology, this study describes the development of a transdiagnostic EMA protocol for psychopathology. METHODS: First, 96 clinicians completed an online survey, providing three EMA constructs for up to three disorders they specialize in, and three EMA constructs relevant across disorders (transdiagnostic constructs). Second, 12 focus groups were conducted with clinical experts for specific types of diagnoses (e.g., mood disorders, anxiety disorders). Finally, a selection of items was reached by consensus. Two raters independently coded the online survey responses with an inter-rater agreement of 87.3%. RESULTS: Jaccard indices showed up to 52.6% overlap in EMA items across types of diagnoses. The most frequently reported transdiagnostic constructs were mood, sleep quality, and stress. A final set of EMA items is created based on items' frequency and informativeness, ensuring completeness across diagnoses and minimizing burden. CONCLUSIONS: The described procedure resulted in a feasible EMA protocol to examine psychopathology transdiagnostically. Feasibility was helped by the overlap in mentioned symptoms across disorders. Such overlap raises questions about the validity of DSM categories.

Validation of an abbreviated Big Five personality inventory at large population scale: Psychometric structure and associations with common psychiatric and neurological disorders.

BACKGROUND: The five-factor model of personality, as quantified using instruments such as the Big Five Inventory, consists of broad personality domains including Extraversion, Agreeableness, Conscientiousness, Neuroticism (emotional instability), and Openness. Such instruments typically include >40 items. However, instruments with many items can be unwieldly and a cause of measurement error in clinical and cohort studies where multiple scales are sequenced. Conversely, established 5- and 10-item versions of the Big Five Inventory have poor reliability. Here, we developed and validated an abbreviated 18-item Big Five Inventory that balances efficiency, reliability and sensitivity. METHOD: We analysed three datasets (N = 59,797, N = 21,177, and N = 87,983) from individuals who participated in the online Great British Intelligence Test (GBIT) study, a collaborative citizen science project with BBC2 Horizon. We applied factor analyses (FA), predictive normative modelling, and one-sample t-tests to validate the 18-item version of the Big Five and to investigate its associations with psychiatric and neurological conditions. RESULTS: The 18-item version of the Big Five Inventory had higher validity and retest reliability compared to the other previously shortened versions in the literature, with comparable demographic associations to the full Big Five Inventory. It exhibited strong (i.e. large effect size) associations with psychiatric conditions, and moderate (small-medium) associations with neurological conditions. Neuroticism (emotional instability) was substantially higher in all psychiatric conditions, whereas Conscientiousness, Openness and Extraversion showed differential associations across conditions. CONCLUSION: The newly validated 18-item version of the Big Five provides a convenient means of measuring personality traits that is suitable for deployment in a range of studies. It retains psychometric structure, retest reliability and clinical-group sensitivity, as compared to the full original scale.

Exploratory rasch analysis of a static-99R clinical cohort assessment.

Modern test theory supplements the more prevalent classic methods for assessing test properties. However, such an assessment of the commonly used sexual recidivism risk assessment instrument, Static-99R, has yet to be attempted. This study evaluated the psychometric properties of said instrument using Rasch analysis. The clinical cohort assessed consisted of individuals with mental disorders convicted of a sexual offense (N = 146). Results showed that the original ten-item Static­99R did not meet the Rasch model requirements, and revisions of the instrument with seven and nine items each only marginally improved performance. More reliable results could likely have been obtained with a larger, non-clinical sample and a more randomized distribution of missing data. Despite the consistently poor performance of item 3 ("Index non-sexual violence") in all three analyses, reliability was slightly improved by dichotomizing the only two polytomous items in the Static-99R; items 1 ("Age at release from index offense") and 5 ("Prior sexual offenses"). These results may be of interest considering the significant change of splitting the formerly dichotomous item 1 into four different response categories in the revision of Static-99 to Static-99R.

Diagnóstico y formulación de casos en terapia psicodinámica: una revisión sobre herramientas actuales.

En las últimas dos décadas, diversos grupos de trabajo de la comunidad psicoanalítica internacional se han interesado por el desarrollo de herramientas sistemáticas para el diagnóstico, la formulación de los casos y la planificación del tratamiento psicodinámico. Este tipo de manuales diagnósticos psicodinámicos son esfuerzos de integración sistemática de una enorme y rica cantidad de información históricamente parcializada y dispersa, pero que constituye el aporte sustancial del psicoanálisis al campo de la salud mental. El objetivo del presente artículo es ofrecer una revisión actualizada sobre esta clase de herramientas sistemáticas de diagnóstico, formulación del caso y planificación terapéutica, diseñadas para el campo de los abordajes psicodinámicos. A estos fines, se describe la estructura y los objetivos de: 1) el Manual Diagnóstico Psicodinámico 2 (PDM-2), 2) el Diagnóstico Psicodinámico Operacionalizado (OPD-2/OPD-3) y 3) el Diagnóstico Psicodinámico Operacionalizado Infanto-Juvenil 2 (OPD-IJ-2).Se discuten las contribuciones de estas herramientas actuales para la práctica clínica y la investigación empírica, así como la necesidad de difundir este tipo de instrumentos en nuestro contexto regional.

A community case detection tool to promote help-seeking for mental health care among children and adolescents in Ugandan refugee settlements: a stepped wedge cluster randomised trial.

BACKGROUND: Strategies to promote mental health care help-seeking among children are needed, especially in low-income and middle-income countries and in complex settings. The aim of this trial was to compare a vignette-based, community-level, proactive case detection tool (CCDT) against standard awareness raising for promoting mental health help-seeking among children and adolescents. METHODS: This stepped wedge cluster randomised trial was conducted in the Bidi Bidi, Kyaka II, Kyangwali, Omugo, and Rhino refugee settlements in Uganda. Community gatekeepers received a 2-day training session on using the CCDT to proactively detect children with mental health concerns and encourage children (or their caregivers) to use the mental health-care service run by Transcultural Psychosocial Organization Uganda. At baseline, organisations implemented routine detection or mental health awareness-raising activities. At cross-over to CCDT implementation, gatekeepers used the tool in their daily activities. The primary outcome was mental health-care service use by children and adolescents. Child population size estimates at the zone level were not available. Therefore, service use was calculated using total population size. We report the effect of CCDT implementation as an incidence rate ratio (IRR), which we produced from a model that accounts for calendar time, exposure time, and person-time. IRRs were estimated for the analysis of effect over time in the per-protocol and intention-to-treat populations. The trial is registered with the ISRCTN registry, number ISRCTN19056780. FINDINGS: 28 administrative zones were selected for trial participation by October, 2021. Between Jan 1, and Nov 8, 2022, seven clusters of four zones sequentially crossed over from routine care to CCDT implementation in 1-month intervals. The CCDT was implemented by 177 trained community gatekeepers. In 9 months, 2385 children visited a mental health-care service; of these, 1118 (47%) were girls and 1267 (53%) were boys (mean age 12·18 years [SD 4.03]). 1998 children made a first or re-entry visit to a service; of these, 937 (47%) were girls and 1061 (53%) were boys (mean age 12·08 years [SD 4·06]). Compared to standard awareness-raising activities, CCDT implementation was associated with an increase in mental health-care service use in the first month after implementation (20·91-fold change [95% CI 12·87-33·99]). Despite a slight decline in service use over time in both the CCDT and pre-CCDT zones, CCDT zones maintained a time-average 16·89-fold increase (95% CI 8·15-34·99) in mental health service use. INTERPRETATION: The CCDT enabled community gatekeepers to increase mental health-care service use by children and adolescents. Vignette-based strategies rooted in the community could become a valuable contribution towards reducing the mental health-care gap among children, especially when accompanied by accessible mental health-care services. FUNDING: Sint Antonius Stichting Projects. TRANSLATIONS: For the Arabic, French and Spanish translations of the abstract see Supplementary Materials section.

Detection and disclosure of workplace mental health challenges: an exploratory study from India.

Workplace mental health challenges have emerged as a significant concern post-pandemic. Despite this, the pervasive stigma surrounding mental illness leads to the concealment of symptoms and reluctance to seek professional help among employees. This study aims to explore the perception of different stakeholders towards the 'Detection and disclosure' of workplace mental health challenges in the Indian context. Fifteen semi-structured interviews were conducted with human resource professionals, counselors, and employees who had previously experienced mental health challenge(s). Thematic analysis was done to identify recurring themes and sub-themes. Three critical pathways were identified: minimizing the inhibitory factors, including lack of awareness, denial, low self-efficacy, stigma, and underestimating organizational capability; maximizing the encouraging factors, including psychological safety, perceived social support, and communicating success stories; and implementing supportive organizational practices, including generating awareness and literacy, build the organizational capability, strengthen the role of managers, leadership advocacy, policies, and processes. By fostering a culture of support and prioritizing employee well-being, organizations in India can create healthier and more resilient work environments, benefiting both individuals and the larger society.

The evaluation of the General Health Questionnaire (GHQ-12) reliability generalization: A meta-analysis.

BACKGROUND: The General Health Questionnaire (GHQ-12) is widely used for detecting psychiatric disorders, but its reliability across different populations remains to be determined. OBJECTIVE: This meta-analysis aims to evaluate the reliability of GHQ-12 across varied cultural and demographic settings. METHOD: This meta-analysis evaluates the reliability of General Health Questionnaire [GHQ-12]' across diverse populations, employing a systematic search strategy and rigorous inclusion criteria. This meta-analysis evaluates the General Health Questionnaire (GHQ-12) using a pre-registered protocol (CRD42023488436) to ensure unbiased results. Data from 20 studies published between 2016-2023 were analysed using a random-effects model, with quality assessment guided by COSMIN Risk of Bias and QUADAS-2. This study enhances our understanding of GHQ-12's psychometric properties. RESULTS: For the GHQ-12 subscales, Cronbach's alpha coefficients were 0.72 (90% CI [0.68, 0.75]) for anxiety and depression, 0.82 (90% CI [0.79, 0.86]) for social dysfunction, and 0.72 (90% CI [0.68, 0.76]) for loss of confidence. However, the analysis showed substantial heterogeneity (I2 = 90.04%), with significant variability in reliability estimates across different studies. The overall Cronbach's alpha was 0.84 (95% Cl [0.810, 0.873]) with SE = 0.016 (90% CI [0.68, 0.82], p < .05), indicating moderate to high internal consistency. Quantifying heterogeneity revealed a substantial level (se = 0.0016, I2 = 96.7%), signifying considerable variability in the reliability estimate among the studies. Results further show Cronbach's alpha coefficients range from 0.82 to 0.85 (95% Cl [0.77, 0.86 to 0.81, 0.90]) for the GHQ 12 items. CONCLUSION: While reaffirming the GHQ-12's utility in mental health assessment, our findings urge a more cautious and context-aware application of the questionnaire. The substantial heterogeneity and variability in reliability scores indicate a need for further research. Future studies should explore the reasons behind this variability, focusing on cultural, socio-economic, and methodological factors that might influence the GHQ-12's reliability. This critical analysis underscores the need for a deeper understanding of the GHQ-12's applicability and the importance of tailoring mental health assessment tools to specific population characteristics.