Human emotions are inherently complex, often manifesting intricate patterns of co-occurrence and variations across different contexts. Previous research has employed numerous indices to capture the complexity of emotional experience, yet these indices are usually mathematically redundant, leading to challenges in interpreting the multifaceted nature of emotions and their relevance to mental health. To address this, we propose a data-driven method to derive indices independently capturing co-occurring patterns of people's emotions across various contexts, which we term "emotion profiles," and evaluated it across three online community samples. Study 1 utilized video stimuli as emotion-eliciting contexts; 514 participants reported their experiences of four positive and four negative emotions in each context, which formed their emotion profiles. Parallel principal component analysis identified four significant principal components of emotion profiles (EP-PCs): context non-specificity, positive emotion co-occurrence, negative emotion co-occurrence, and mixed emotion. Study 2 recruited another 509 participants and assessed their emotion profiles twice over a 2-week interval. The four EP-PCs were replicated with different participants and different stimuli (r = .75 to .86), with EP-PC1 and EP-PC2 also showing good test-retest reliability. Study 3 employed an imagined scenario paradigm with 310 participants, confirming that the first three EP-PCs generalized across paradigms. Moreover, exploratory analysis revealed that EP-PCs mediated the associations between emotional granularity and mental health outcomes, clarifying distinct predictive pathways linking positive and negative emotional granularity to depressive and anxiety symptoms. This illustrates how the proposed method may inform emotion-mental health research.

To examine the association between occupational stress and mental health-related quality of life (HRQoL) among nurses in the Northern Border Region of Saudi Arabia and to determine whether this relationship varies across professional and clinical subgroups.

A cross-sectional, correlational study.

A stratified sample of 257 registered nurses and nurse managers was recruited from three hospitals in the Northern Border of Saudi Arabia (53.2% female, 86.0% staff nurses and 44.0% with > 10 years of experience). Occupational stress was assessed using a culturally adapted and forward-backward translated version of the Nursing Stress Scale (NSS), which measures seven stress domains. Mental HRQoL was evaluated using the Mental Component Summary (MCS) of the 12-item Short Form Health Survey (SF-12). Data were analysed using descriptive statistics, independent samples t-tests, one-way analysis of variance with post hoc comparisons, Pearson correlations and four-step hierarchical linear regression.

The mean MCS score was 52.01 (SD = 8.12), slightly above the SF-12 normative mean of 50. All seven occupational stress domains were significantly and negatively associated with MCS scores (r = -0.22 to -0.33, all p < 0.001). Workload was the highest-rated stressor (M = 2.91, SD = 0.65), whereas nurse-physician conflict demonstrated the strongest inverse correlation with mental HRQoL (r = -0.33). The final hierarchical regression model explained 34% of the variance in MCS scores (R² = 0.34, adjusted R² = 0.30). Occupational stress domains contributed an additional 15% of explained variance beyond demographic and professional characteristics (ΔR² = 0.15, F-change [7, 244] = 7.85, p < 0.001). No significant interaction effects were identified.

No Patient or Public Contribution.

Ecological momentary assessment (EMA) allows researchers to capture substance use as it occurs in daily life, but participants may not report every use event. Little is known about whether the environments where people spend time affect the completeness of these reports.

We examined how consistently young adults reported cigarette and cannabis use through event-based EMA and whether reporting differed by the social vulnerability of places they visited. We analysed 30 days of GPS-enabled EMA and daily diary data from 34 young adults in California (730 participant days). We compared daily cigarette and cannabis use events reported through EMA with those reported in the following day's diary and classified EMA reports as lower than, matching, or higher than the diary. Using GPS data and the Social Vulnerability Index, we measured the social vulnerability of participants' daily activity spaces relative to home.

Bayesian multilevel multinomial logistic regression showed that higher social vulnerability in daily activity spaces relative to home was associated with greater odds of reporting fewer use events through EMA than in the daily diary for cigarettes (aOR 1.55, 95% CrI 1.25-1.93) and cannabis (aOR 1.28, 95% CrI 1.06-1.55). The association for cigarettes was also observed in a larger independent dataset.

These findings suggest that the completeness of real-time substance use reporting may depend partly on where participants spend their time. Researchers using event-based EMA should consider environmental context when interpreting incomplete reports and designing studies to improve data completeness.

For this study, we defined "mental health support at pharmacies" as "mental support and reassurance through explanations for medications and illnesses, and health consultations," which are not difficult from a mental health perspective, and conducted a survey on how pharmacies can contribute to mental health in local residents (n=580). However, according to this definition, 80.3% answered that they had not received "mental health support at pharmacies." We then asked 77 people who had experienced "mental health support at pharmacies" when they had obtained this support. The answers received were "explanations of prescription medication" (46.8%) and "explanations of over-the-counter drugs [OTC drugs and pharmacist intervention required drugs (yo-shido-iyakuhin)]" (31.2%) during the pharmacy's main duties. Furthermore, in the survey of all 580 residents, the "initiatives that would be good to have in pharmacies to support mental health" were "mental health check" (31.2%), "explanations of prescription medication" (30.2%). Moreover, regardless of whether there were difficulties with mental health, the reasons given by the 55 people who answered that pharmacies should not be involved in mental health were "mental health is-difficult as a specialty" (52.7%) and "mental health is difficult in terms of personal information" (43.6%). Therefore, it is suggested that pharmacy pharmacists should initially provide "mental health support" at pharmacies for mental health areas that do not require specialist knowledge.

Children's health and well-being are cross-cutting indicators of sustainable development and underpin society's long-term development potential and productivity. The Shanghai Child and Adolescent Health Cohort (SCAHC) was established with a focus on the sociodemographic, environmental and biological determinants of children's growth and development.

The SCAHC adopted a two-stage random cluster sampling scheme stratified by economic development level to establish the cohort. A total of 13 primary schools from Pudong New Area were selected to recruit year 1 pupils and at least one of their parents. The SCAHC was initially designed to follow pupils from year 1 (aged 6-7) through to year 9 (aged 14-15), with a possible extension upon additional funding. Baseline data were collected in 2020 and included information on pupils (sociodemographic characteristics, health status, clinical conditions, personal medical history, sleep patterns, dietary consumption, lifestyles, environmental factors and laboratory test results on micronutrient status, lipid profile, thyroid function, renal function and metabolic status) and their parents (demographic characteristics, medical history, pregnancy status and lifestyle factors including smoking, alcohol consumption and physical activity). The primary growth and development outcomes include anthropometric measures (height, weight, waist circumference and hip circumference) and pubertal development (Tanner staging). Secondary outcomes include metabolic health, nutritional status, sleep quality and the prevalence of common childhood conditions (such as myopia, dental caries and asthma). Annual follow-up assessments with repeated measures were scheduled. All data were collected during baseline and follow-up periods through questionnaires, established instruments, standard physical examinations and routine laboratory tests. Sex differences in baseline data were evaluated using independent t-tests for continuous variables and χ2 or Fisher's exact tests for categorical variables where appropriate.

The baseline child population included 1363 boys and 1132 girls (mean age 6.44 years). The mean body mass index of the children at baseline was 16.44 kg/m², and the mean waist-to-hip ratio was 0.81. Compared with girls, boys exhibited a higher prevalence of overweight and obesity (40.8% vs 31.4%, p<0.001) and higher rates of asthma (2.9% vs 1.1%, p=0.002) and attention-deficit hyperactivity disorder (5.9% vs 2.1%, p<0.001). Conversely, girls had higher rates of vitamin D deficiency (50.5% vs 40.1%, p<0.001) and abnormal urine findings (17.2% vs 0.4%, p<0.001). The overall prevalence of dental caries was high (60.2%), whereas the prevalence of myopia (12.6%) was lower than the national estimates.

The SCAHC is an ongoing prospective cohort that provides rich information for identifying the multimodal determinants of children's growth and development. Findings from this cohort can inform targeted intervention strategies for major public health issues, such as obesity and sedentary lifestyles, as well as emerging challenges such as mental disorders in children and adolescents.

Migrants living in precarious conditions often face gendered violence (GV) and poor mental health (MH). However, most of the existing GV and MH measures assume residentially stable populations, missing migration-related precarity or structural conditions shaping migrants' experiences. As a result, the intersection of GV, poor MH and precarity across migrant populations remains unstudied, especially in low- and middle-income country (LMIC) settings, that the National Institute for Health and Care Research (NIHR)-funded research programme Gendered Violence and Poor Mental Health among Migrants in Precarious Situations (GEMMS) aims to explore.

This paper describes the development of the GEMMS survey tool and presents preliminary pilot validation evidence for selected adapted and newly developed components designed to measure GV, MH and precarity associated with migration across multiple LMIC settings.

GEMMS survey tool development followed a participatory process with multicountry research teams, international experts, local advisory groups and community members with lived experiences. Guided by GEMMS' conceptual frameworks, items were drawn from validated instruments where possible and newly developed as informed by GEMMS' ethnography and country profiling. After several rounds of expert reviews, community consultations and item-level content validation, the tool was pilot-tested in Cambodia, India and South Africa (total n=198), to improve wording, sequencing, skip logics and order. Exploratory factor analysis was done to assess internal coherence of the newly adapted items.

Final survey tool comprises 216 items. Exploratory factor analysis of selected adapted and de novo migration-related and psychosocial item sets in pilot analyses identified two coherent migration-related and three MH-related factors: structural harm, socio-cultural marginalisation; social exclusion, belonging/social integration and migration stress. All five factors were robust, with interpretable and meaningful loadings that aligned with the guiding theory.

The GEMMS survey tool provides an integrated, context-responsive, structurally informed survey tool for measuring GV, MH and multidimensional precarity in migrant populations. This paper demonstrates its development process, pilot feasibility and preliminary validation evidence for selected components, while establishing a foundation for future intersectional and syndemic-informed analysis across diverse migrant populations in LMICs.

To examine the relationship between personal birth companions and maternal mental health during labour and the postpartum period in low- and middle-income countries.

Systematic review using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines.

We performed a systematic search of Embase, Medline, PsycINFO, Global Health and Scopus from inception to 24 September 2024.

Peer-reviewed studies-either observational or experimental-that reported an association between personal birth companions and maternal mental health were included.

Data were extracted using a structured template and Joanna Briggs Institute tools were used for quality assessment. Due to heterogeneity across studies, a narrative synthesis was conducted.

Our review included 10 studies (6 observational, 4 experimental) conducted across seven countries, primarily in South Asia. Overall, we found promising evidence from experimental studies-conducted primarily on primigravida women and those with uncomplicated pregnancies-that the presence of birth companions from personal networks (particularly husbands) positively affects maternal mental health. The relative change in maternal anxiety between intervention and control groups ranged from -0.85% to 120% with most p values <0.001 favouring the intervention effect, while for depressive symptoms the relative changes were 4.5% and 22.8% with statistically insignificant effects. However, with the exception of two studies, none of the observational studies showed a statistically significant relationship, although the direction of effect supported a positive association. One observational study also found that characteristics of birth companionship (ie, type and level of support) increased the odds of postpartum anxiety and depression (2.86 (95% CI 1.52 to 5.39)).

Our review indicates promising evidence that birth companions from a woman's personal network may have a positive effect on maternal mental health and well-being, especially for nulliparous women and those with uncomplicated pregnancies. However, there is a dire need for more rigorous experimental research across countries in different regions and income strata.

Mental health problems, including stress-related complaints, are an increasing concern in today's workforce. Therefore, long-term sickness absence becomes a risk, yet effective return to work (RTW) interventions for employees suffering from mental health problems are scarce and they lack tailoring. The aim of this study is to describe the design of a randomised controlled trial (RCT) evaluating the effectiveness of the tailored Vital@Work reintegration programme for sick-listed workers with stress-related complaints.

An RCT involving 208 sick-listed workers with stress-related complaints will be conducted with measurements taking place at baseline and after 3, 6 and 12 months. Stress-related complaints will be assessed with a distress screener. All participants will receive care as usual. The intervention group will receive a tailored eHealth programme, followed by the participatory approach if full RTW has not been achieved after 6 weeks in the study. Participants assigned to the control group will be provided with general information via the eHealth programme. The primary outcome is sustainable RTW, defined as lasting at least 28 consecutive days without any relapse. Secondary outcomes are stress-related complaints, psychosocial job characteristics and behaviour change. A mixed-methods approach will be used for the process evaluation.

This study has been approved by the Medical Ethics Committee of Amsterdam UMC (approval number: 2024.0021). Results are expected to be published in peer-reviewed journals. In addition, interim and final results will be shared and discussed with the participating organisations involved in this study.

NCT06543732.

Generative AI (GenAI) tools, such as OpenAI's ChatGPT, Google's Gemini, and Microsoft Copilot, are being adopted across health care settings. Despite the popularity of GenAI, empirical data on the extent of adoption by mental health clinicians in routine psychotherapy practice are scarce.

This study aimed to characterize purposeful GenAI use among mental health professionals providing psychotherapy, including tools used, purposes, perceived workload effects, and the organizational context surrounding use.

We conducted a cross-sectional online survey between January 13, 2026, and March 30, 2026. A convenience sample of trained mental health professionals who had provided psychotherapy within the previous 12 months was recruited through professional associations and academic and clinical mailing lists, with snowball dissemination by email. The survey assessed lifetime purposeful GenAI use in psychotherapy practice; tools and purposes of use; perceived work burden reduction; and, for the previous 12 months, employer or professional organization encouragement, prohibition, and participation in AI training. Descriptive statistics were calculated. Univariable logistic regression models were used to examine associations between GenAI use and candidate factors. Variables meeting an entry criterion of P<.10 were entered into a multivariable logistic regression; statistical significance was set at P<.05.

A total of 766 mental health professionals who provide psychotherapy in 30 countries completed the survey. Of these, 54.6% (n=418, 95% CI 51.0%-58.1%) reported having purposely used at least 1 GenAI tool in clinical psychotherapy practice. ChatGPT was the most frequently used tool (354/418, 84.7%, 95% CI 81.2%-88.2%). The most commonly reported clinical purpose was assisting with treatment planning (175/418, 41.9%, 95% CI 37.1%-46.7%), followed by managing administrative tasks (n=173, 41.4%, 95% CI 36.6%-46.1%) and generating psychoeducational materials for clients (n=166, 39.7%, 95% CI 35.0%-44.4%). Among AI users, 82.8% (346/418, 95% CI 79.1%-86.4%) reported that these tools reduced their overall work burden. Only 18.1% (139/766, 95% CI 15.4%-20.9%) of respondents reported institutional encouragement to use GenAI tools, while 81.1% (n=621, 95% CI 78.3%-83.9%) reported not having received any professional training on AI use. In multivariable logistic regression (α=.05), younger age was associated with GenAI use, while practice setting showed mixed evidence of association. The overall adjusted effect of practice setting did not reach statistical significance (P=.07), although urban practitioners had lower odds of GenAI use than rural practitioners (adjusted odds ratio 0.614, 95% CI 0.388-0.971; P=.04).

This study extends previous predominantly national and profession-specific research by providing a multicountry, multiprofessional snapshot of reported GenAI use in psychotherapy practice. Use extended beyond administrative tasks into clinically consequential activities, including treatment planning and psychoeducation, while participation in professional AI training remained relatively uncommon. Findings highlight the need for professional bodies, health systems, and training programs to develop practical guidance and competencies for safe, privacy-conscious, and clinically appropriate GenAI use.

Identifying mechanisms of change in psychotherapy is imperative to optimize treatment effectiveness for depression. Research has identified specific mechanisms, primarily in outpatient pathology. However, the transdiagnostic robustness of these mechanisms remains to be quantified in more severely affected populations. This study aims to delineate the role of anxious and avoidant attachment, expressive suppression and cognitive reappraisal as within-person mechanisms of change in inpatient schema therapy and cognitive behaviour therapy for patients acutely and severely affected by major depressive disorder. A secondary analysis of a randomized clinical trial in an intensive multimodal inpatient and day-clinic setting with 198 patients was conducted. To differentiate stable between-person traits from therapeutic within-person shifts, Bayesian random-intercept cross-lagged panel models were employed. The data provided evidence that schema therapy and cognitive behaviour therapy do not differentially affect the mechanisms of change, that these mechanisms do not predict subsequent symptom change and that they do not mediate treatment effects on depressive symptoms. In contrast, a significant reverse association was identified: Symptom reduction was associated with subsequent improvements in cognitive reappraisal and expressive suppression. This temporal precedence suggests that alterations in cognitive reappraisal and expressive suppression are consequences of change in depressive symptoms rather than its primary drivers. These insights could guide researchers and clinicians in future investigations towards precision psychotherapy, directing attention not only to what interventions are performed but also to when they are performed.