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Depression is a leading cause of illness and disability among adolescents worldwide, yet evidence on its burden among school-going adolescents in rural Kenyan counties remains limited. This study determined the prevalence and socio-demographic factors of depression among secondary school students in Bungoma County, Kenya, to provide baseline evidence for mental health planning. The study was guided by Hopelessness Theory of Depression and Ecological Systems Theory. An analytical mixed methods cross-sectional study design was adopted. The target population consisted of secondary school students, with a sample size of 400 respondents determined using Taro Yamane formula. The respondents were selected through multistage stratified and systematic sampling from three sub-counties of Bungoma County (Mt. Elgon, Kimilili and Bungoma South). Quantitative data were collected using the Patient Health Questionnaire (PHQ-9) and a structured questionnaire, and analyzed using descriptive statistics and ordinal logistic regression in SPSS version 28. Qualitative data were obtained through ten Focus group discussions with students and twelve in-depth interviews with class teachers, and analyzed thematically. The overall prevalence of depressive symptoms (PHQ-9 score ≥ 5) was 55.5% (n = 222), 41.5% (n = 166) had mild depression, 9.5% (n = 38) moderate depression, 3.5% (n = 14) moderately severe depression and 1.0% (n = 4) severe depression, while 44.5% (n = 178) were not depressed. Female students were found to be almost twice as likely to experience higher levels of depression compared to the males (AOR= 1.71, P= 0.04). On the other hand, students in mixed day and boarding schools were 78% less likely to experience higher level of depression, (AOR = 0.22, P<0.001), compared to those in girls’ boarding and day schools. Further, students who live with extended family were more than twice as likely as those with both parents to experience higher depression levels (AOR = 2.10, P= 0.04). The qualitative data pointed to gender and family structure as possible associations of depression. Depression is highly prevalent among secondary school students in Bungoma County, with one in seven students experiencing moderate to severe depression. Routine school-based mental health screening using validated tools such as the PHQ-9 is recommended to enable early identification, counselling and referral of affected students.

Background: Mothers of young children with neurodevelopmental disorders may experience substantial parenting demands, but their recent positive mental well-being varies. Objective: To examine the association between parenting stress and psychological well-being among mothers of children aged 0?6 years diagnosed with neurodevelopmental disorders. Methods: This quantitative cross-sectional correlational study analyzed 85 mothers using the 18-item Parental Stress Scale (PSS-18) and the WHO-5 Well-Being Index. Descriptive statistics, Pearson correlation, and a Spearman sensitivity analysis were reported. Results: Mean PSS-18 was 67.55 (SD = 4.73), and mean WHO-5 transformed score was 64.85 (SD = 12.92). Parenting stress was negatively correlated with well-being (Pearson r = -0.675, 95% CI [-0.777, -0.540], p < .001). Spearman correlation was also negative (? = -0.634, p < .001). Conclusion: Greater reported parenting stress was associated with lower recent subjective well-being in this sample. The cross-sectional design does not establish causation. These findings underscore the relevance of attending to caregivers? psychological experiences alongside child-focused services.

Mental healthcare needs are growing, yet awareness of available services remains limited, even in Houston, Texas. This study examined relationships between having experienced or been diagnosed with mental illness and awareness of community-based mental health or crisis services. Approximately 1,000 Houston-area adults were surveyed in 2024 and 2026. Chi-square and multivariable regression analyses showed that experience with mental illness was associated with SGM populations, race/ethnicity, and age after adjustment for sociodemographic characteristics. SGM participants had greater odds of reporting mental illness, whereas Black/African American, Hispanic/Latinx, Asian, and older adults had lower adjusted odds relative to their reference groups. Awareness of community-based services was independently associated with gender, SGM populations, race/ethnicity, age, and annual household income; females had greater odds of awareness, whereas Hispanic/Latinx, Asian, and older adults had lower odds. Findings highlight sociodemographic differences in reported experience with mental illness and awareness of community-based services. Longitudinal research is needed to further examine these relationships.

BACKGROUND: Israel's 2015 mental health reform transferred responsibility for mental health services from the government to community health maintenance organisations (HMOs), aiming to improve accessibility and equity and reduce stigma. However, its implications for different populations remain significantly underresearched. AIMS: To examine trends in mental health service utilisation and psychiatric medication issue rates among Arab and Ultra-Orthodox Jewish populations before and after the 2015 mental health reform. METHOD: = 2 847 184). Participants were classified as either general (non-Ultra-Orthodox Jewish), Ultra-Orthodox Jewish or Arab. The study analysed annual community visits to mental health professionals and dispensed psychiatric prescriptions. RESULTS: Between 2012 and 2019 the number of mental health service users increased across all populations, most prominently among Ultra-Orthodox Jewish and Arab populations (1.94- and 1.91-fold, respectively), compared with 1.55-fold in the general population. Annual community visits increased 2.4-fold in the general population, 2.2-fold in the Ultra-Orthodox Jewish population and 3.7-fold among Arabs, who had the lowest baseline utilisation. Psychiatric medication issue rates increased most in the Ultra-Orthodox Jewish population (2.5-fold), compared with 1.7-fold in the Arab and 1.5-fold in the general population. Women consistently used more services than men, with the greatest relative increase among Arab women. CONCLUSIONS: The findings suggest improved access to mental health services over the study period spanning the 2015 mental health reform, particularly in previously underserved populations. Continued progress requires culturally sensitive, community-tailored interventions for Arab and Ultra-Orthodox Jewish populations.

Aim The aim of the study was to assess the level of life satisfaction of forensic psychiatry patients and to identify selected demographic and clinical factors related to life satisfaction, with particular emphasis on illness acceptance. Material and methods The study included 121 patients hospitalized in four forensic psychiatry departments. Life satisfaction was assessed using the Satisfaction with Life Scale (SWLS), and illness acceptance using the Acceptance of Illness Scale (AIS). The relationship between SWLS scores and age and AIS scores was analyzed, as well as differences in SWLS scores based on gender, duration of hospitalization, psychiatric diagnosis, and pharmacotherapy regimen. Spearman’s rank correlation, Student’s t-test, one-way ANOVA, and the Mann-Whitney U test were used depending on the type of variables. A nominal significance level of α = 0.05 was adopted. No p-value correction was applied due to multiple testing. Results The mean SWLS score was 19.82 ± 7.50 points. The study group showed varied levels of life satisfaction. After converting the results to the sten scale, 39.7% of participants achieved results corresponding to a low level of life satisfaction, 26.4% - an average level, and 33.9% - a high level. The mean AIS score was 28.06 ± 7.70 points; low level of illness acceptance was found in 10.7% of participants, average in 47.1%, and high in 42.1%. There were no statistically significant differences in SWLS scores depending on gender (p = 0.412), psychiatric diagnosis (p = 0.951), pharmacotherapy regimen (p = 0.930), or duration of hospitalization (p = 0.211). There was no statistically significant correlation between the SWLS score and age (rho Spearman’s ratio = -0.166; p = 0.068). However, a weak positive correlation was observed between the AIS score and the SWLS score (rho Spearman’s α = 0.215; p = 0.018), statistically significant at the nominal level of α = 0.05. Conclusions of life satisfaction were found among the patients included in the study. The largest group consisted of participants classified as low (39.7%), but the differences in numbers between categories did not indicate a clear dominance of one category over the other. In the study group, the most common levels of illness acceptance were medium (47.1%) or high (42.1%). There was no statistically significant correlation between SWLS scores and age, nor were there any statistically significant differences in SWLS scores based on gender, psychiatric diagnosis, pharmacotherapy regimen, or length of hospitalization. However, a weak positive correlation was observed between illness acceptance and life satisfaction, significant at the nominal level of α = 0.05. The cross-sectional nature of the study does not allow for conclusions about a causal relationship between these variables. The results suggest the validity of considering illness acceptance in further studies on life satisfaction in forensic psychiatric patients.

Entry-level managers are usually promoted for their technical skills and are then expected to meet targets, lead teams and resolve conflicts with little preparation for the role. This study examined the relationship between workplace stress, mental health and job satisfaction among entry-level managers in Indian organizations. Using a quantitative correlational design, data were collected through an online questionnaire from 47 managers with up to five years of managerial experience across finance, manufacturing, IT/ITES, healthcare and service operations. Most participants reported moderate workplace stress (61.7%), while nearly half (46.8%) reported high job satisfaction. Workplace stress was positively correlated with mental health difficulty (r = .641) and negatively correlated with job satisfaction (r = -.477), and mental health difficulty was negatively correlated with job satisfaction (r = -.536), all at p < .01. Stress explained 41% of the variance in mental health difficulty, and mental health explained 29% of the variance in job satisfaction. When both were considered together, only mental health remained a significant predictor of satisfaction. The findings suggest that the mental health of new managers is central to their job satisfaction and point to the need for training, mentoring and psychological support early in a managerial career.

Background The first period of life shapes later life chances, but the economic consequences accumulate across later childhood, adolescence and adulthood and fall across several policy sectors. Existing reviews typically address one risk factor at a time, or focus on a restricted outcome domain, leaving the relevant evidence scattered. This umbrella review collates review-level evidence on how early childhood exposures affect later economic outcomes. Methods The review was registered on Open Science Framework (https://osf.io/szpx5/overview). Medline, APA PsycArticles, APA PsycINFO, CINAHL Plus with Full Text, Education Research Complete & Psychology and Behavioural Sciences Collection databases were searched in November 2025. Systematic, rapid, scoping, narrative and umbrella reviews were eligible if they examined early childhood exposures and later outcomes with measurable consequences for education, employment, income, criminal justice involvement, quality of life, wellbeing or service costs. Reviews reporting only health status outcomes, and those focused on low- and middle-income countries, were excluded. Two authors screened and extracted independently, and quality was appraised. Findings were synthesised narratively. Results Seventy-two reviews were included, published between 2001 and 2025 and increasingly since 2021. Adverse childhood experiences and related adversity were the most frequently examined exposures, followed by childhood physical health conditions, birth and perinatal factors, and neurodevelopmental and behavioural difficulties. Early years risk factors were consistently associated with poorer later education and employment, lower income and greater criminal justice involvement. Evidence on quality of life was mixed, and service use and costs were seldom reported. Few reviews addressed publication bias. Conclusion Difficulties experienced in the early years have consequences across several later life domains and public sectors. The evidence is most consistent for education and criminal justice involvement, and thinner for quality of life, service use and costs. Reviews rarely address correlations between risk factors or the pathways connecting them to later outcomes. Modelling these pathways and evaluating interventions to address early years risks are priorities. Limitations of the review were the inclusion of studies that covered a wide range of age groups and the exclusion of health outcomes.

Digital media has evolved from passive screen viewing into an algorithmically curated ecosystem of social platforms, short form video, games, generative artificial intelligence (AI), conversational agents, connected toys and educational technologies. These systems can support learning, creativity, communication, disability access and healthcare; however, engagement optimized design, commercial surveillance and synthetic content create risks that are not adequately captured by screen-time measures alone. This narrative review examines the effects of contemporary digital ecosystems on child and adolescent health and outlines implications for pediatric practice. PubMed/MEDLINE, Google Scholar and guidance from the World Health Organization, United Nations Children's Fund, UNESCO and the American Academy of Pediatrics were reviewed, with emphasis on evidence published from 2019 to June 2026. Associations have been reported between problematic digital media use and sleep disruption, reduced physical activity, visual and musculoskeletal symptoms, obesity related behaviours, anxiety, depressive symptoms, cyberbullying, disordered eating and impaired attention. Causal interpretation remains difficult because effects are heterogeneous, often small, bidirectional and strongly modified by age, content, context, displacement, family relationships and pre-existing vulnerability. AI adds distinct concerns: persuasive personalization, inaccurate health information, anthropomorphic dependency, deepfakes, sexual exploitation, biased outputs, privacy loss and erosion of learning through uncritical outsourcing. Benefits are also substantial when technologies are developmentally appropriate, evidence-based, inclusive and used with adult support. Pediatric counselling should shift from counting hours alone toward assessing the child's digital ecosystem, sleep, function, content, compulsivity, safety and relationships. Effective protection requires shared family practices, school digital literacy, safety by design, age-appropriate assurance, transparent algorithms, data minimization and independent research. The goal is not a screen free childhood but a child centred digital environment that supports health, agency and development.

Objectives: The coronavirus disease-2019 (COVID-19) infection has affected the lives of all strata of society since its beginning. To control the spread of the disease, a lockdown was imposed. During this time, there was a substantial increase in the usage of gadgets and reduction in outdoor activities because of online studies that resulted in serious the mental health issues, especially in the paediatric population. Material and Methods: To study the effect of the COVID-19 pandemic on screen time, playtime and behaviour of the students, the study was conducted on 153 subjects of 4–18 years age group attending the outpatient department, over a period of 3 months. A questionnaire format of ten questions was framed that was asked from the children or from their parents/guardians. This study included questions such as time spent on online classes, self-study or study with parents and gadgets used for the online classes. Results: Most of the children were students of classes upper kinder garden and I, comprising 19.0% and 18.3%, respectively. Females outnumbered males in the study. Weight gain was observed in 43.8%, and signs of irritability were observed in 68.0% of the children. Weight gain showed a statistically significant correlation with the duration of online classes, indoor and outdoor playtime with p-values of 0.044, <0.005 and 0.005, respectively. There was also a statistically significant correlation between change in behaviour with outdoor playtime and sleep timings with p < 0.005 and 0.019, respectively. Conclusion: This study concluded that there was a significant increase in screen time and a decrease in outdoor play activities during the time of COVID-19 pandemic with a statistically significant correlation with the weight gain and change in behaviour of the children.

This study evaluated the reliability and validity of a context-aware sleep holistic cycle gate algorithm and explored its potential for artificial intelligence (AI)-based personalized sleep management in digital health-care. A 6-week prospective observational study was conducted in 25 adults aged 20–65 years. Participants recorded daytime activities, eve-ning behaviors, presleep environmental factors, sleep outcomes, and feedback adherence using a mobile application. Five sleep-related indices were calculated, and a context-aware gate algorithm comprising five domains was applied. Reliability was assessed through internal consistency and reproducibility analyses, while validity was examined using correlations with sleep quality indicators and receiver operating characteristic curve analyses. Data completion and adherence rates were 80.3%±9.8% and 72.7%±11.6%, respectively. The sleep readiness index was positively correlated with subjective sleep quality (r=0.53, P<0.01). The algorithm demonstrated moderate predictive performance (area under the curve=0.73), with the environment and presleep gates showing the highest accuracy. Following personalized feedback, sleep onset latency decreased by 12.6%, and perceived sleep quality improved significantly (P<0.05). In conclusions, the context-aware sleep holistic cycle gate algorithm demonstrated acceptable reliability and validity for predicting sleep quality. These findings suggest that the proposed framework may serve as a foundational platform for the development of AI-driven personalized sleep management systems and future digital healthcare applications related to sleep rehabilitation and health promotion.

Objective Operating room nurses work long-term in high-intensity, high-risk environments and suffer from a high prevalence of occupational fatigue, which seriously affects their physical and mental health as well as patient safety. Based on the Job Demand-Control-Support (JDCS) model, this study aimed to examine the mediating role of perceived stress between the dimensions of the JDCS model and occupational fatigue—including acute fatigue, chronic fatigue, and inter-shift recovery—among operating room nurses. Methods This multi-center cross-sectional study was conducted from August to September 2026, enrolling 1,122 operating room nurses from 9 tertiary Grade-A hospitals in eastern, central, and western China. A general information questionnaire, the Occupational Fatigue Exhaustion Recovery Scale, the Perceived Stress Scale (PSS-10), and the Job Content Questionnaire (JCQ) were administered. SPSS 25.0 was used for descriptive statistics, difference analysis, correlation analysis, and hierarchical multiple regression; AMOS 21.0 was used to construct a structural equation model, and the bias-corrected Bootstrap method was employed to test mediating effects. Results The scores of acute fatigue, chronic fatigue, and inter-shift recovery among operating room nurses were 45.55 ± 18.77, 44.13 ± 17.89, and 56.27 ± 17.83, respectively, indicating an overall moderate level of occupational fatigue. The perceived stress score was 21.01 ± 5.24; job demand was 36.44 ± 4.80; job control was 71.54 ± 18.07; and social support was 24.02 ± 6.61. Hierarchical regression showed that, after controlling for demographic and work characteristics, job demand, job control, and social support remained independent correlates of all three outcomes (acute fatigue model R 2 = 0.460, chronic fatigue R 2 = 0.305, inter-shift recovery R 2 = 0.353). The structural equation model showed that job demand positively predicted perceived stress ( β = 0.182, p < 0.001), while job control ( β = −0.251, p = 0.033) and social support ( β = −0.168, p = 0.040) negatively predicted perceived stress. Perceived stress positively predicted acute fatigue ( β = 0.336, p < 0.001) and chronic fatigue ( β = 0.209, p < 0.001), and negatively predicted inter-shift recovery ( β = −0.134, p = 0.029). Bootstrap tests indicated that perceived stress played a significant partial mediating role between job demand, job control, and social support and the outcomes of acute fatigue, chronic fatigue, and inter-shift recovery, although the indirect effects were small in magnitude (proportion mediated 3.41–17.35%). Conclusion Occupational fatigue among operating room nurses in 9 tertiary Grade-A hospitals is at a moderate level, and inter-shift recovery needs improvement. Perceived stress acted as a mediating variable linking JDCS dimensions to occupational fatigue, although the mediating effects were modest in magnitude. Nursing managers can improve occupational fatigue and recovery among operating room nurses by reducing unreasonable job demands, enhancing job control, strengthening social support, and alleviating perceived stress.

Background Digital mental health platforms routinely deliver self-administered symptom scales on the assumption that users with more severe symptoms are more likely to enter professional care. That assumption is rarely tested with linked participant-level data, and almost never in the Arabic-speaking Gulf. Objective To examine whether symptom severity at a user’s first self-assessment predicts booking a professional session within 90 days, across four symptom domains, on a Saudi commercial digital mental health platform. Methods Retrospective cohort analysis of 10,100 first assessments — depression, generalized anxiety, panic, and obsessive-compulsive scales — contributed by 5,524 unique users of the Talbinah platform and linked to demographic and session-booking records through a pseudonymous (SHA-256 hashed) user identifier. The primary outcome was any session booked within 90 days after the assessment. Severity was banded by the established cut-offs for the PHQ-9 and GAD-7, and by percentage of scale maximum for the panic and obsessive-compulsive measures, for which no severity thresholds are established. Per-scale multivariable logistic regression estimated adjusted odds ratios (aOR) for severity band (reference None/Minimal), adjusting for age, sex, and device type. Pre-specified sensitivity analyses used 30- and 180-day windows, an attended-session outcome, percentage-of-maximum banding applied to all four scales, and a subset with no prior booking (incident help-seeking). Reporting followed STROBE. Results Users were young (mean age 26.7 years, SD 8.1) and predominantly female (78.1%); 16.6% of first assessments were followed by a booking within 90 days. No severity band on any of the four scales was associated with higher odds of booking (severe vs None/Minimal: depression aOR 0.71, 95% CI 0.51–1.01; generalized anxiety 0.76, 0.49–1.16; panic 0.83, 0.52–1.31; obsessive-compulsive 1.01, 0.59–1.74). One severity contrast was statistically significant, in the opposite direction: moderate depression was associated with lower odds of booking (0.66, 95% CI 0.45–0.97). Older age (aOR ~1.2 per decade) and iOS device use (1.4–2.0) were associated with booking across scales. This absence of a positive severity–booking association was consistent across 30-, 90-, and 180-day windows, the attended-session outcome, and percentage-of-maximum banding; a nominal association for moderate anxiety seen under percentage banding did not persist with validated GAD-7 cut-offs. Estimates for the panic and obsessive-compulsive scales, which lack established severity thresholds, are exploratory. Conclusions On a Saudi digital mental health platform, greater self-reported symptom severity at first assessment was not followed by higher subsequent booking of professional care, consistently across specifications, and for moderate depression was associated with lower odds of booking; demographic and access-related attributes showed stronger associations with booking than symptom load did. Self-screening on its own appears insufficient as a pathway into care.

Background Depression and anxiety symptoms are common among college students. Behavioral and psychosocial indicators may support preventive campus mental health work, but risk-stratification frameworks require external validation. Methods We developed a construct-level model-explanation framework using questionnaire data from a development sample. The cleaned dataset included 1,267 students; internal-validation analyses included 1,096 students for depression risk and 1,095 for anxiety risk. Risk was defined as a Patient Health Questionnaire-9 (PHQ-9) or Generalized Anxiety Disorder-7 (GAD-7) score of 10 or higher. The primary Feature set C random-forest (RF) pipelines integrated demographic, traditional, and emerging behavioral and psychosocial indicators. Fold-specific preprocessing and percentile cutoffs were used for internal validation. Locked pipelines were applied without retraining, predictor reselection, optimization, recalibration, or threshold adjustment to an independent university sample of 1,468 students. Results External area under the receiver operating characteristic curve (AUROC), area under the precision–recall curve (PR-AUC), and Brier scores were 0.813 (95% CI, 0.776–0.848), 0.402 (0.325–0.491), and 0.090 (0.083–0.098), respectively, for depression and 0.809 (0.765–0.851), 0.205 (0.144–0.300), and 0.063 (0.056–0.070), respectively, for anxiety. Ordinary participant-level bootstrap was the primary approach, with stratified bootstrap as a sensitivity analysis. Depression calibration was close to the prevalence baseline (Brier 0.091; intercept −0.668; slope 1.401), whereas anxiety showed miscalibration (Brier 0.063 vs. baseline 0.051; intercept −1.227; slope 1.102). The models supported external discrimination and risk ranking but did not validate individual absolute-risk probabilities or clinical thresholds. Conclusion Behavioral and psychosocial indicators supported externally validated risk stratification in an independent university sample. Anxiety-risk findings should be interpreted as preliminary because the number of positive cases was limited. Further evaluation is needed before wider implementation.

OBJECTIVE: To conduct a national environmental scan of child hearing health-related services and databases as part of the Australian National Child Hearing Health Outcomes Registry program, and to identify system-level barriers and enablers to developing a coordinated Learning Health System for deaf and hard-of-hearing children. METHODS: A cross-sectional national survey of organisations providing hearing health-related services or managing data for Australian deaf and hard-of-hearing children. The survey examined the scope and practices related to data collection, standardisation, interoperability, stewardship, and governance. RESULTS: Ninety-nine respondents from 92 organisations delivering 290 services participated. The scan identified a disjointed data landscape. Standardised data were limited, with inconsistent capture of key variables across organisations and 49.4% rating their data quality as acceptable or good. Interoperability was constrained by heterogenous data practices, including use of multiple databases (34.3%), limited external reporting (24.2%) and lack of accessible data dictionaries (71.9%). Stewardship and data governance arrangements were variable, with fewer than half of organisations reporting formal consent (47.6%), privacy statements (51.2%) or ethics oversight (38.1%). Despite these challenges, 56.5 and 54.8% of organisations expressed interest in data linkage and research participation, indicating readiness for coordinated system development. CONCLUSION: Despite Australia's substantial investment in newborn hearing screening and hearing health-related services, fragmented data systems limit Australia's ability to monitor outcomes, equity and system performance in child hearing health. However, strong stakeholder interest in data linkage provides important momentum. These findings inform policy and service planning, and support staged development of a national child deafness Learning Health System through the Australian National Child Hearing Health Outcomes Registry.

This longitudinal study examined the trajectories of healthcare workers’ mental health from the first to the second COVID-19 wave (May 2020–December 2020) in a Swiss tertiary hospital, and their association with individual and organizational factors. For each mental health outcome (depression, anxiety, peritraumatic stress, and well-being), a separate analysis identified two trajectories: one with higher, persistent levels of symptoms and one that was resilient, with low-level symptoms. The persistent trajectory comprised about 25%–30% of participants for anxiety, depression and peritraumatic stress and 47% for well-being; because the classifications were outcome-specific, membership differed across outcomes (about 15% of participants were on a persistent trajectory for all four outcomes and 46% resilient for all four). We found that women, nurses, caregivers, non-managerial employees, and frontline COVID-19 workers were more likely to follow a persistent trajectory. Organizational risk factors were a high workload and an irregular work schedule. These results provide a basis for implementing risk-adapted prevention measures and resilience-promotion programs to protect health workers from the impact of major crises. Future research should address the needs of vulnerable health workers to provide evidence-based health promotion.

Rising living costs and expensive higher education place many students under financial pressure, yet the evidence from Southeast Asia has not been brought together. Following the Arksey and O’Malley framework and PRISMA-ScR reporting guidelines, a total of 239 records were screened, comprising 174 records retrieved from Scopus and 65 records from non-Scopus sources. Eleven studies from five countries (the Philippines, Indonesia, Malaysia, Singapore, and Thailand) were charted and synthesised narratively. Six were quantitative surveys, and five of the eleven appeared in 2025 or 2026. Six themes emerged. First, costs extend beyond tuition: programme costs, rent, and other indirect expenses create hardship even where tuition is free. Second, access to family resources and financial aid is unequal. Third, financial strain is reported alongside psychological distress and academic strain, a pattern of co-occurrence rather than demonstrated cause. Fourth, students cope through income generation, saving and economising, building financial literacy, cognitive reappraisal, spiritual support, and selective use of social support. Fifth, financial literacy and behaviour appear to shape financial well-being, although findings on financial stress conflict. Sixth, authors call for support beyond tuition, but no study evaluated an intervention. The evidence is mostly cross-sectional, and no eligible study came from Vietnam, Myanmar, Cambodia, Laos, Brunei, or Timor-Leste. Malaysia contributes one study, which examines financial well-being rather than coping strategies. Future work needs harmonised measures, longitudinal and intervention designs, and wider country coverage.

Introduction/Objective Depression is a disabling mental health disorder affecting over 300 million people worldwide. In Tunisia, population-level data on its prevalence and determinants remain limited. Our study aimed to estimate the prevalence of depression in the Tunisian population and identify associated socio-demographic and clinical factors. Methods Data were drawn from the mental health component of the Tunisian Health Examination Survey (2016), a nationally representative study conducted among 9,209 individuals aged ≥15 years. Self-reported, physician-diagnosed lifetime depression was the main outcome. Associations with socio-demographic characteristics and clinical conditions, including rheumatoid arthritis, diabetes, and menopause, were examined. Results The study population comprised 4360 men (49.2%) and 4849 women (51.8%), with a mean age of 41.4±17.4 years. The prevalence of self-reported lifetime depression was 4.7%. Multivariate analysis identified female sex (OR=1.53, 95% CI [1.11–2.10]) and age groups 30–64 years (OR=1.81, 95% CI [1.20–2.73]) and ≥65 years (OR=1.82, 95% CI [1.06–3.14]) as factors significantly associated with higher prevalence. Conversely, marriage (OR=0.59, 95% CI [0.42–0.84]) and the absence of rheumatoid arthritis (OR=0.48, 95% CI [0.38–0.60]) were associated with a lower prevalence of the disorder. Discussion The findings indicate that self-reported depression in Tunisia is significantly influenced by gender and aging, consistent with global epidemiological trends. The strong association with physical comorbidities, particularly rheumatoid arthritis, underscores the necessity of integrated mental health screening for patients with chronic illnesses. Furthermore, the protective association of marriage suggests that social and family cohesion remain vital factors in the Tunisian sociocultural context. Conclusion Depression in Tunisia is shaped by gender, aging, and physical comorbidities. Targeted prevention and integrated screening strategies are needed, especially for vulnerable demographic and clinical groups.

Purpose This study examined the global landscape of mental health literacy (MHL) education for health professions students, focusing on publication trends, intervention designs, pedagogical approaches, MHL domains addressed, evaluation methods, and contextual influences. Methods Following PRISMA-ScR guidelines, an Evidence and Gap Mapping (EGM) scoping review was conducted to identify and visually synthesize MHL education interventions. Searches were conducted in PubMed, Embase, Scopus, Web of Science, EBSCOhost (including CINAHL, PsycINFO, and ERIC), and APA PsycArticles (February 1997-May 2025). The included studies involved pre-licensure health professions students and implemented structured educational interventions explicitly targeting MHL domains. The data were extracted using a standardized framework and analyzed through descriptive synthesis and visual mapping to identify research clusters and gaps. PROSPERO registration: CRD420251050891. Results Fifty-five studies met the inclusion criteria for this review. Notably, the number of publications increased significantly after 2016, with most of the evidence coming from Europe, the Western Pacific, and the Americas, while representation from the African and Eastern Mediterranean regions was limited. Quasi-experimental designs were the most common, characterized by short-term, classroom-based interventions primarily targeting specific professions, particularly nursing and medicine. Although traditional didactic teaching methods remained prevalent, experiential strategies such as simulation, role-play, and reflective practices were increasingly adopted. Within the existing body of evidence, interventions predominantly emphasized knowledge, attitudes, and confidence, whereas skills development, behavioral change, self-awareness, and help-seeking were less consistently addressed. Furthermore, evaluations mostly relied on short-term, self-reported outcomes, with few studies examining behavioral change or long-term impacts. Conclusions MHL education for future health professionals is expanding but remains unevenly distributed, pedagogically conservative, and methodologically limited. Advancing the field will require longitudinal, theory-informed, and experiential approaches, stronger evaluation designs, integration of lived-experience perspectives, and targeted capacity-building in low- and middle-income settings.

Suicidal ideation is the consideration of self-inflicted death and has emerged as a serious and rising concern for worldwide public health systems, contributing to over 800,000 deaths annually worldwide. Individuals express intentions, distress, and thoughts of self-harm and death, thereby offering a crucial and unprecedented avenue for timely psychological intervention and surveillance. The core problem addressed by this research is the pronounced global insufficiency in detecting and mitigating suicidal ideation across linguistically diverse environments, specifically focusing on low-resource languages. Previous computational studies have primarily focused on English and other widely used languages, leaving a critical research gap for contexts such as Amharic. The main aim of this study was to investigate and to develop a robust and optimal deep learning model for identifying suicidal ideation in Amharic social media content. A total of 5,428 postings from social media such as Facebook and Telegram were carefully collected, manually annotated, and processed to provide the first publicly available dataset on Amharic suicidal ideation. After preprocessing, Word2Vec, GloVe, and FastText were among the word embedding techniques used for feature engineering. Five deep learning models and four machine learning models were then compared in this study. Based on the experimental results, ensemble learning models achieved slightly higher performance than the individual deep learning models in suicidal ideation detection. Specifically, hard voting ensemble learning models achieved the highest accuracy (83.3%) and precision (86.55%). CNN-BiLSTM achieved an accuracy of 81.45%, while the BiLSTM model achieved an accuracy of 81.4%, indicating that bidirectional sequence learning effectively captures contextual information in Amharic texts. Beyond its strong empirical performance, this study contributes a robust detection framework and introduces a public Amharic dataset, thereby establishing a foundational methodological resource for mental health research. Future studies should focus on developing scalable datasets and context-aware deep learning models that effectively handle multimodal data, multilingual transformer models, fusion-based features, and addressing bias in low-resource computational linguistics.

افکار خودکشی به معنای اندیشیدن به مرگ خودخواسته است و به عنوان یک نگرانی جدی و رو به افزایش برای نظام‌های سلامت عمومی در سراسر جهان مطرح شده است، به طوری که سالانه بیش از ۸۰۰٬۰۰۰ مرگ را در سطح جهانی رقم می‌زند. افراد، نیت‌ها، پریشانی و افکار آسیب به خود و مرگ را ابراز می‌کنند و بدین ترتیب، مسیر مهم و بی‌سابقه‌ای برای مداخله و پایش روان‌شناختی به موقع فراهم می‌شود. مسئله اصلی که این پژوهش به آن می‌پردازد، کمبود چشمگیر جهانی در شناسایی و کاهش افکار خودکشی در محیط‌های زبانی متنوع، به ویژه در زبان‌های کم‌منبع است. مطالعات محاسباتی پیشین عمدتاً بر زبان انگلیسی و سایر زبان‌های پرکاربرد تمرکز داشته‌اند و این امر موجب ایجاد شکاف پژوهشی مهمی در زمینه‌هایی مانند زبان آمهاریک شده است. هدف اصلی این مطالعه، بررسی و توسعه یک مدل یادگیری عمیق قوی و بهینه برای شناسایی افکار خودکشی در محتوای شبکه‌های اجتماعی به زبان آمهاریک بود. در مجموع، ۵٬۴۲۸ پست از شبکه‌های اجتماعی مانند فیس‌بوک و تلگرام با دقت جمع‌آوری، به صورت دستی برچسب‌گذاری و پردازش شدند تا نخستین مجموعه‌داده عمومی درباره افکار خودکشی به زبان آمهاریک فراهم شود. پس از پیش‌پردازش، تکنیک‌های تعبیه واژه مانند Word2Vec، GloVe و FastText برای مهندسی ویژگی‌ها به کار گرفته شدند. در این پژوهش، پنج مدل یادگیری عمیق و چهار مدل یادگیری ماشین با یکدیگر مقایسه شدند. بر اساس نتایج تجربی، مدل‌های یادگیری تجمعی (ensemble learning) عملکردی اندکی بهتر از مدل‌های یادگیری عمیق منفرد در شناسایی افکار خودکشی داشتند. به طور خاص، مدل‌های یادگیری تجمعی با رأی‌گیری سخت (hard voting) بالاترین دقت (۸۳/۳٪) و دقت مثبت (precision) (۸۶/۵۵٪) را به دست آوردند. مدل CNN-BiLSTM به دقت ۸۱/۴۵٪ و مدل BiLSTM به دقت ۸۱/۴٪ دست یافتند که نشان می‌دهد یادگیری دنباله‌ای دوسویه به طور مؤثری اطلاعات زمینه‌ای را در متون آمهاریک استخراج می‌کند. افزون بر عملکرد تجربی قوی، این پژوهش چارچوب شناسایی قابل اعتمادی ارائه داده و مجموعه‌داده عمومی آمهاریک را معرفی می‌کند و بدین ترتیب منبع روش‌شناختی بنیادی برای پژوهش‌های سلامت روان فراهم می‌آورد. مطالعات آتی باید بر توسعه مجموعه‌داده‌های مقیاس‌پذیر و مدل‌های یادگیری عمیق آگاه از زمینه که به طور مؤثر داده‌های چندوجهی، مدل‌های ترنسفورمر چندزبانه، ویژگی‌های مبتنی بر همجوشی و رفع سوگیری در زبان‌شناسی محاسباتی کم‌منبع را مدیریت می‌کنند، تمرکز کنند.

Shift work is associated with irregular eating behaviors, increased energy intake, and impaired sleep quality. Poor dietary patterns may elevate systemic inflammation, contributing to long-term metabolic and cardiovascular risks. The aim of this study was to investigate differences in the Dietary Inflammatory Index (DII), sleep quality, dietary intake, and anthropometric and body composition measures between fixed daytime workers and rotating shift workers and to examine the associations among these parameters. This cross-sectional study included 52 male workers employed at a defense industry factory in Ankara, Türkiye, who worked either fixed daytime or rotating shifts. Dietary intake was assessed using 24-h dietary recalls for three non-consecutive days, from which macronutrient and micronutrient intakes were calculated. DII scores were computed to assess the inflammatory potential of the diet. Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI). Anthropometric measurements, body composition, blood pressure, and biochemical parameters, including fasting plasma glucose, lipid profile (total cholesterol, HDL-C, LDL-C, and triglycerides), C-reactive protein, and homocysteine, were measured using standardised protocols. Rotating shift workers had significantly higher total energy intake and higher daily intakes of fructose, total fat, saturated and monounsaturated fatty acids, cholesterol, and several micronutrients, including vitamin A, folate, iron, calcium, and phosphorus compared with fixed daytime workers (p < 0.05). Mean DII scores did not differ significantly between the groups (Fixed daytime: 0.2 ± 1.86; rotating shift: −0.2 ± 2.25). DII scores were positively correlated with global PSQI score (r = 0.278, p = 0.046), the PSQI sleep duration component score (r = 0.319, p = 0.021), and daytime dysfunction component score (r = 0.287, p = 0.039); however, the association between DII and overall sleep quality was no longer statistically significant after adjustment for potential confounding factors (age, BMI, smoking status, physical activity, and work schedule). These findings suggest that dietary habits, pro-inflammatory dietary patterns, and poor sleep quality may represent co-existing factors associated with metabolic risk, and addressing these factors may contribute to better overall metabolic health.

کار شیفتی با رفتارهای نامنظم غذایی، افزایش دریافت انرژی و کاهش کیفیت خواب همراه است. الگوهای غذایی نامطلوب ممکن است التهاب سیستمیک را افزایش داده و در نتیجه خطرات متابولیک و قلبی‌عروقی بلندمدت را افزایش دهند. هدف این مطالعه بررسی تفاوت‌های شاخص التهابی رژیم غذایی (DII)، کیفیت خواب، دریافت غذایی و اندازه‌گیری‌های آنتروپومتریک و ترکیب بدن بین کارکنان مرد با شیفت ثابت روزانه و کارکنان شیفت چرخشی و همچنین بررسی ارتباط میان این پارامترها بود. این مطالعه مقطعی شامل ۵۲ کارگر مرد شاغل در یک کارخانه صنایع دفاعی در آنکارا، ترکیه بود که به صورت شیفت ثابت روزانه یا شیفت چرخشی کار می‌کردند. دریافت غذایی با استفاده از یادآوری غذایی ۲۴ ساعته برای سه روز غیرمتوالی ارزیابی شد و دریافت درشت‌مغذی‌ها و ریزمغذی‌ها محاسبه گردید. امتیازهای DII برای ارزیابی پتانسیل التهابی رژیم غذایی محاسبه شد. کیفیت خواب با استفاده از شاخص کیفیت خواب پیتسبورگ (PSQI) ارزیابی گردید. اندازه‌گیری‌های آنتروپومتریک، ترکیب بدن، فشار خون و پارامترهای بیوشیمیایی شامل گلوکز پلاسمای ناشتا، پروفایل لیپیدی (کلسترول تام، HDL-C، LDL-C و تری‌گلیسرید)، پروتئین واکنشی C و هموسیستئین با استفاده از پروتکل‌های استاندارد اندازه‌گیری شد. کارکنان شیفت چرخشی دریافت انرژی کل و دریافت روزانه فروکتوز، چربی کل، اسیدهای چرب اشباع و تک‌غیراشباع، کلسترول و چندین ریزمغذی از جمله ویتامین A، فولات، آهن، کلسیم و فسفر به طور معناداری بالاتری نسبت به کارکنان شیفت ثابت روزانه داشتند (p < 0.05). میانگین امتیازهای DII بین دو گروه تفاوت معناداری نداشت (شیفت ثابت روزانه: ۰.۲ ± ۱.۸۶؛ شیفت چرخشی: ‎−۰.۲ ± ۲.۲۵). امتیازهای DII با امتیاز کلی PSQI (r = 0.278, p = 0.046)، امتیاز مؤلفه مدت خواب PSQI (r = 0.319, p = 0.021) و امتیاز مؤلفه اختلال عملکرد روزانه (r = 0.287, p = 0.039) همبستگی مثبت داشت؛ با این حال، پس از تعدیل برای عوامل مخدوش‌کننده بالقوه (سن، BMI، وضعیت سیگار کشیدن، فعالیت بدنی و برنامه کاری)، ارتباط بین DII و کیفیت کلی خواب از نظر آماری معنادار نبود. این یافته‌ها نشان می‌دهد که عادات غذایی، الگوهای غذایی پیش‌التهابی و کیفیت پایین خواب ممکن است عوامل هم‌زمان مرتبط با خطر متابولیک باشند و پرداختن به این عوامل می‌تواند به بهبود سلامت متابولیک کلی کمک کند.