Male mental health remains a major global concern, with men underrepresented in mental health care and overrepresented in suicide statistics. Masculine norms that link emotional restraint with strength can discourage help-seeking and vulnerability. Anonymous digital spaces such as Reddit (Reddit Inc) and YouTube (Google LLC) have become informal support environments where men share experiences and emotions outside traditional constraints. Understanding these interactions offers insight into masculine identity and help-seeking behavior.

This study examines how men discuss and negotiate mental health within anonymous online communities. It explores whether these spaces support emotional openness, peer validation, and challenges to hegemonic masculinity norms. It triangulates digital discourse with survey and interview data to assess how these patterns align with men's lived experiences and perceived barriers to support.

This cross-sectional, exploratory mixed methods study analyzed publicly available online discourse from Reddit (n=740 posts) and YouTube (n=6287 comments). The qualitative component included 23 adult men (aged 18-55 years, predominantly Asian and employed) recruited via LinkedIn (Microsoft) who completed an anonymous online survey. Of these, 9 volunteered for follow-up semistructured interviews. Data underwent computational text mining using the Natural Language Toolkit and National Research Council Lexicon for word frequency and emotion analysis, followed by Braun and Clarke's 6-phase reflexive thematic analysis. Online discourse patterns were then compared with survey and interview data. Theoretical frameworks included hegemonic masculinity, toxic positivity, and peer-support theory.

Four themes emerged across the datasets: (1) normalizing emotional expression, (2) mutual validation and peer support, (3) coping through humor and irony, and (4) pushback against toxic positivity and societal norms. Emotion analysis showed prominent expressions of sadness, fear, trust, and anger across the Reddit and YouTube corpus. Survey data showed that 20 of 23 (87%) respondents reported having no safe offline space to discuss mental health. Interview participants (n=9) largely confirmed digital discourse themes, though some divergence emerged regarding whether humor functioned as deflection or connection.

This study combines large-scale analysis of online discourse with qualitative triangulation across Reddit, YouTube, surveys, and interviews. Theoretically, it extends inclusive masculinity theory into anonymous online contexts, showing how digital platforms enable men to negotiate emotional expression outside traditional masculine constraints. It introduces the concept of "digitally mediated sanctuaries" to describe online spaces where men practice vulnerability and mutual support with less social risk. From an infodemiological perspective, the findings show how mental health information and peer-support narratives circulate and gain legitimacy within male-dominated online communities. Findings can inform gender-sensitive digital mental health interventions that build on features men already use, including humor, anonymity, and peer validation. Digital peer environments may complement formal mental health services by reducing help-seeking barriers for men hesitant to access traditional care.

Depressive symptoms are common among patients with renal disease and are associated with poorer outcomes. This study examined depressive symptom dimensions (somatic vs. cognitive-affective) among hemodialysis patients and aimed to determine whether socioeconomic and clinical factors were differentially associated with these domains. A cross-sectional study was conducted in two major hemodialysis centers in Sana'a city between June and September 2025. Adult patients receiving maintenance hemodialysis completed the Patient Health Questionnaire-9 (PHQ-9). Multivariable logistic regression analyses were conducted to identify factors independently associated with depressive symptoms. Of the 308 participants (56.8% male), 67.2% had PHQ-9 scores ≥10, indicating moderate-to-severe depressive symptoms. Low monthly household income was independently associated with higher odds of depressive symptoms (AOR 2.18; 95% CI 1.06-4.47; p = 0.032). Female sex (p = 0.076) and the presence of comorbidities (p = 0.052) showed borderline associations with depressive symptoms. The absence of medical insurance was associated with lower odds of depressive symptoms (AOR 0.46; 95% CI 0.26-0.81; p = 0.008), although this finding should be interpreted with caution. Low income and multimorbidity were associated with somatic symptoms, whereas smoking status and income were associated with cognitive-affective symptoms. Depressive symptoms were highly prevalent among hemodialysis patients in Sana'a, highlighting the need to integrate mental-health screening into dialysis care. Reducing financial barriers to treatment should also be prioritized in dialysis care settings in Sana'a and similar resource-limited settings.

More than 20% of perinatal women experience depression, with suicide being a leading cause of maternal death in the United States. Professional societies emphasize the need to identify those at risk of developing perinatal depression to better target preventive care delivery during pregnancy.

We evaluated receptivity to a machine learning-based predictive screener designed to identify women in the first trimester of pregnancy who were asymptomatic but were at risk for developing moderate to severe depression symptoms later in pregnancy.

Our participants were adult pregnant women with negative first-trimester depression (Patient Health Questionnaire-9) screens at 1 of 4 obstetric practices. Of the 810 women who were clinically eligible, 787 were successfully contacted via their patient portal. Of these, 289 (36.7%) viewed the screener and 255 (88.2%) completed the 6-question predictive screener. In total, 51 (20%) were identified by the screener as being at risk for developing perinatal depression. Participants were asked a series of follow-up questions regarding the acceptability of the predictive screener and desired preventive resources. Chi-square tests were used to compare demographic characteristics, perceived benefits and concerns, and desired resources between those identified as at risk for depression and those who were not. Differences in acceptability ratings between the two risk groups were determined using nonparametric Mann-Whitney U tests.

On a 5-point Likert scale of agreement, participants found the screener questions easy to complete (median score 5, IQR 5-5) and felt comfortable sharing their answers with their obstetric care providers (median 5, IQR 4-5). Key perceived benefits of completing the screener included opportunities to seek preventive care (75/255, 29.4%) and to receive education on depression risk (66/255, 25.9%). Primary concerns about knowing one's risk of future depression included worrying about developing depression (90/255, 35.3%) and a lack of prevention opportunities (39/255, 15.3%). Desired preventive resources included counseling (197/255, 77.3%), mind-body interventions (166/255, 65.1%) such as exercise, and prenatal classes or support groups (81/255, 31.8%).

Participants found the screener acceptable and felt comfortable receiving it through their patient portal. Specific preventive care options were commonly endorsed, several of which are scalable and evidence based. A minority of participants voiced addressable concerns about knowing their risk of developing depression in the future.

The growing integration of artificial intelligence (AI) in higher education has transformed learning processes but also raised concerns about potential mental health risks. Medical students represent a particularly vulnerable group due to high academic stress and increasing reliance on generative AI tools for study and decision-making tasks. Despite this, the relationship between AI dependence and psychological distress remains underexplored in Latin American contexts.

This study aimed to evaluate the association between generative AI dependence and levels of stress, anxiety, and depression among medical students.

A cross-sectional study was conducted with 187 human medicine students from a Peruvian university during the first academic semester of 2025. The Dependence on Artificial Intelligence Scale and the Depression, Anxiety, and Stress Scale-21 were applied. Negative binomial regression models, both crude and adjusted for sex, age, income, and year of study, were used to assess associations, reporting rate ratios (RRs) and 95% CIs.

Participants had a median age of 22 (IQR 19-24) years, and 58.8% (110/187) were female. The median Dependence on Artificial Intelligence Scale score was 10 (IQR 7-14). Generative AI dependence showed significant correlations with anxiety (ρ=0.336, 95% CI 0.22-0.44) and depression (ρ=0.316, 95% CI 0.20-0.43) and a smaller correlation with stress (ρ=0.277, 95% CI 0.16-0.39). In the adjusted regression models, each 1-point increase in generative AI dependence was associated with a 5% higher expected anxiety score (RR 1.05, 95% CI 1.01-1.09; P=.01) and a 4% higher depression score (RR 1.04, 95% CI 1.01-1.08; P=.03), whereas the association with stress was positive but nonsignificant (RR 1.03, 95% CI 1.00-1.07; P=.08). Fifth-year students had significantly greater anxiety levels than their sixth-year peers (RR 1.82, 95% CI 1.09-3.01; P=.02). No significant effects were observed for sex, age, or income.

This study empirically examined generative AI dependence as a distinct behavioral construct and its association with mental health symptoms in medical students. Unlike prior research, this study evaluated psychological dependence on generative AI and modeled its relationship with anxiety and depression using appropriate count-based regression techniques. By providing early evidence from a Latin American context, it contributes to the emerging field of digital mental health and medical education research. These findings underscore the need for universities to promote balanced and responsible AI use, integrate digital literacy with mental health support strategies, and develop preventive policies that mitigate potential maladaptive reliance on generative AI tools.

The integration of digital health technologies into nursing education in Saudi Arabia requires reliable tools to assess nursing informatics competency and digital technology self-efficacy among students.

This study aimed to evaluate the reliability and validity of the Canadian Nursing Informatics Competency Assessment Scale (C-NICAS) and Digital Technology Self-Efficacy (DT-SE) scale among undergraduate nursing students at a Saudi university.

A descriptive cross-sectional survey of 243 undergraduate nursing students at the University of Ha'il was conducted using the C-NICAS and DT-SE. Internal consistency was examined using Cronbach α, and construct validity was assessed using exploratory and confirmatory factor analyses.

A total of 243 students participated (mean C-NICAS score 54.0, SD 16.9; mean DT-SE score 2.7, SD 0.56). Both scales showed good internal consistency (C-NICAS total α=0.90; DT-SE α=0.80). C-NICAS demonstrated a multidimensional factor structure with an acceptable model fit (comparative fit index=1.00; root mean square error of approximation=0.081), whereas DT-SE showed a 3-factor structure with a suboptimal confirmatory model fit (comparative fit index=0.76, root mean square error of approximation=0.146).

The C-NICAS and the DT-SE are suitable for assessing informatics competency and digital self-efficacy among undergraduate nursing students at this institution, although further refinement of the DT-SE may improve model fit. These validated tools can inform curriculum reform at this and similar institutions in Saudi Arabia and support the digital health goals of Saudi Vision 2030.

Digital remote monitoring using smartphones and wearable devices is a promising solution for psychosis management, where precise, time-sensitive intervention is crucial. Combining active symptom monitoring (ASM) and passive sensing (PS) can support self-management by allowing remote, low-burden mental health monitoring.

This study aimed to explore (1) views on collecting data using ASM and PS methods and comfort levels with different types of data gathered via these methods, (2) views on using smartphones and wearable devices in the context of mental health care, and (3) the ownership and usage of smartphones and wearable devices.

We conducted a cross-sectional survey study with service users with psychosis in the United Kingdom between March 2023 and March 2024.

A total of 309 participants completed the survey. They reported mixed views on using ASM and PS technologies for monitoring mental health, with more participants endorsing the concept than opposing it (ASM: n=145, 46.9% and PS: n=132, 42.7%). However, the type of data gathered using these methods was an important factor. Collecting personal information was deemed less acceptable (P<.001) than other data types (physical health, mental health, environment, and nonpersonal device information).

We found that participants were comfortable with using apps and wearables for digital remote monitoring, though personal information was less acceptable than other data types due to privacy and surveillance concerns. This highlights the importance of further exploring trust issues related to digital monitoring and ensuring that end users have choices regarding the types of data that digital systems gather and share with mental health services.

To identify and prioritize system-level factors contributing to Kansas' long-term population health decline compared with the United States and demonstrate the application and value of the modified Delphi technique for complex, state-level health assessment.

A modified Delphi study was conducted in Kansas to engage experts and leaders in Kansas' health across sectors. Participants (n = 50 Round 1; n = 67 Round 2; n = 60 Round 3) provided qualitative input and completed quantitative prioritization across 3 Delphi rounds. Issue statements were developed from open-ended responses (Round 1), rated for importance (Round 2), and prioritized through a constant sum resource allocation exercise (Round 3).

Participants identified 52 factors contributing to Kansas' health decline. Of these, 4 emerged as the highest priorities: closure of rural hospitals and health care services, failure to expand Medicaid, limited mental health service availability, and low public health funding. Seven additional factors were identified as high priorities. The highest-ranked issues reflected system-level drivers rather than individual behaviors.

Kansas' declining health trajectory is primarily driven by structural system vulnerabilities, including policies and infrastructure gaps misaligned with what produces health.

Addressing Kansas' health decline will require targeted policy reforms that strengthen system capacity and align with evidence-based approaches used by higher-performing states.

With increasing life-expectancy, the older population of Nepal has also been increasing with Nepal census 2021 reporting 60 years and above population to be 10.21%. Nepal also has a high migration rate with 2.2 million absentee population reported in the 2021 census. Outmigration of adult children can negatively impact parental health, including loneliness, depression, and poor psychological health, despite potentially increasing parents' financial resources and access to welfare services. This study aims to evaluate the level of depression and their associated factors among the empty nest older population residing in ward number 9 of Kathmandu Metropolitan City after adult children's migration. A cross-sectional mixed-method study was carried out among 140 older parents aged over 60, with all children migrated abroad, selected randomly from a social security list. Depression was measured using Geriatric Depression Scale and regression analysis was performed. Qualitative part included 21 in-depth interviews analyzed thematically and triangulated with quantitative data. The study revealed that nearly half of empty nesters had depression, with 30% mild and 5% severe. The study identified that single (widowed, divorced or separated) parents had 28.3 times higher cumulative odds of being in a higher category of depressive symptoms, i.e., "moderate/severe and mild" versus "mild and normal" compared to those who are married and living together with their spouses holding constant all other variables. Qualitative interviews supported these findings, highlighting depression among older, widowed parents. The empty nest older population are at increased risk of suffering from depression. Due to the limited evidence, this study investigates if adult children's migration affects the mental health of older parents in Nepal, specifically aiming to understand depression among them and inform policies for their better psychological well-being.

Intimate partner violence (IPV) has harmful effects on women's physical, mental, and reproductive health. This study investigates the relationship between experiencing IPV and unmet need for family planning in two provinces of the Democratic Republic of the Congo (DRC), emphasizing the potential mediating effect of reproductive coercion. To our knowledge, this is the first examination of the connection between IPV and unmet need for family planning in the DRC, particularly regarding the underlying mechanisms of this association.

This research utilized secondary data from the third wave of the Performance Monitoring for Action (PMA) surveys carried out in two provinces of the DRC during the period from 2021 to 2022. The analysis focused on a sample comprising 1,387 women in unions aged between 15 and 49 years. To investigate the relationship between IPV and unmet need for family planning, linear probability models were employed and various factors were controlled. Additionally, we explored the moderating influence of reproductive coercion in this context.

The linear probability model indicated that experiencing sexual IPV within the past 12 months was linked to an unmet need for family planning [aCoef = 0.12, CI95% = 0.04-0.21]. When sexual IPV occurred alongside reproductive coercion, a stronger correlation with unmet need was detected [aCoef = 0.24, CI95% = 0.03-0.44].

We showed that sexual IPV is associated with an unmet need for family planning in the DRC. While IPV should be considered a policy target, these results emphasize the importance of responding appropriately to IPV when sexual and reproductive health services are provided to women. This was the first study on the DRC and, more generally, on sub-Saharan Africa (SSA) to illuminate the underlying mechanisms of the association, revealing the moderating role of reproductive coercion.

Incarcerated pregnant and postpartum people experience poor mental health. Conditions of confinement (e.g., inadequate prenatal care, shackling, isolation, stigma) exacerbate distress, contributing to new or worsening psychological challenges. Although awareness of perinatal mental health needs is increasing, the extent to which federal and state laws address these needs remains unclear. To address this gap, we conducted a systematic search in WestLaw through July 2025, combining the terms pregnancy, postpartum, and incarceration. The search returned 545 statutes from 48 states and the federal government. Using a deductive codebook of maternal health topics, we extracted and analyzed legislative text related to mental health screening and treatment. Ten states had statutes addressing mental health care for incarcerated perinatal people. Nine mandated access to mental health treatment but varied in scope, screening, and conditions addressed. Five states referenced pregnant people only, three included both pregnant and postpartum people, and two focused exclusively on postpartum populations. Two states required specialized mental health training for carceral staff. Few states mandate availability of mental health care for incarcerated pregnant and postpartum people despite national clinical guidelines. Limited statutory guidance may hinder early identification and treatment, increasing the risk of adverse maternal outcomes, including postpartum depression, suicide, and recidivism.