Traditional cognitive screening relies on episodic clinical assessments and may miss early changes preceding cognitive impairment and dementia. Wearable and mobile health technologies enable continuous monitoring of sleep, physical activity, and circadian rhythms, generating digital biomarkers that may support scalable early detection and prevention. However, current evidence remains fragmented across devices, analytic approaches, and cognitive outcomes.

This study synthesizes and critically evaluates recent evidence on wearable devices for early detection and prevention of cognitive impairment and dementia, focusing on device categories, cognitive outcomes, analytic approaches, and prevention relevance.

We searched PubMed, Scopus, ACM Digital Library, and SpringerLink for peer-reviewed studies published between January 2020 and December 1, 2025. Eligible studies included human participants with a mean age ≥50 years, continuous wearable-derived data collected for ≥24 hours, and validated cognitive outcomes; reviews, protocols, smartphone-only studies, and pharmacological interventions were excluded. Two reviewers independently screened studies, extracted data, and assessed risk of bias using the Appraisal Tool for Cross-Sectional Studies, Newcastle-Ottawa Scale, Cochrane Risk of Bias tool, and Quality Assessment of Diagnostic Accuracy Studies-2. Owing to substantial heterogeneity in devices, outcomes, and analytic methods, quantitative meta-analysis was not feasible; a structured narrative synthesis was conducted in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidance. This study was not prospectively registered.

We included 49 studies, with sample sizes ranging from 14 to 91,948 participants (>200,000 total) and a median sample size of 145. Most used research-grade actigraphy (43/49, 87.8%), while fewer used commercial wearables (7/49, 14.3%). Cognitive outcomes most frequently relied on global screening instruments, including the Mini-Mental State Examination (18/49, 36.7%), followed by ICD-10 (International Statistical Classification of Diseases, Tenth Revision)-based clinical diagnoses (7/49, 14.3%) and the Montreal Cognitive Assessment (7/49, 14.3%). Analytic approaches were predominantly statistical (36/49, 73.5%), with fewer studies applying machine learning (7/49, 14.3%) or deep learning methods (6/49, 12.2%). Statistical analyses linked disrupted sleep, circadian rhythm fragmentation, and irregular activity patterns to worse cognitive outcomes, with modest-to-moderate effect sizes. Machine learning and deep learning approaches reported classification performance with area under the curve values between approximately 0.70 and 0.95. Approximately one-quarter of the studies (13/49, 26.5%) addressed early detection or prevention through longitudinal risk estimation or predictive modeling. Key limitations included small sample sizes, short monitoring durations, and limited external validation.

Wearable-derived behavioral markers show promise for early risk stratification. This review advances the field by shifting from descriptive associations toward a digital phenotyping framework evaluating artificial intelligence-driven prediction in the preclinical window. Unlike prior reviews focused on established dementia, it differentiates direct predictive evidence from indirect correlational findings and critically assesses methodological maturity. Continuous, passive monitoring may enable scalable detection of subtle behavioral changes, supporting earlier and more personalized risk reduction strategies.

Frontotemporal lobar degeneration (FTLD) can present as a behavioral or language variant (bvFTLD or a primary progressive aphasia [PPA], or as a syndrome with parkinsonism, such as corticobasal syndrome [CBS] or progressive supranuclear palsy [PSP]). The incidence of FTLD varies in epidemiologic studies, reaching 3 per 100,000 person-years. Only few data exist regarding survival times. We evaluated incidence and survival rates in a population-based registry with high coverage in Southern Germany.

The epidemiologic ALS-FTLD registry Swabia covers a population of 8.4 million inhabitants in south-west Germany. Raw and age-standardized incidence rates, as well as incidence rate ratios (IRR) with 95% CIs were calculated. Median survival time was estimated for different FTLD variants using the Kaplan-Meier method.

Between 2015 and 2022, 515 patients with FTLD (mean age at diagnosis 68.0 ± 9.5 years, 59.8% men) were registered. The median diagnostic delay was 24.8 months. The most common variant was bvFTLD (n = 185, 35.9%; 66.5% men), followed by PPA (n = 147, 28.5%; 51.0% men), PSP (n = 133, 25.8%; 62.9% men), and CBS (n = 22, 4.3%; 50% men). The overall FTLD incidence was 0.77 (95% CI 0.71-0.84), and the age-standardized incidence was 0.76 (95% CI 0.69-0.82) per 100.000 person-years. The age-standardized incidence was higher in men than in women, with an IRR of 1.73 (95% CI 1.44-2.00). In men, incidence increased from the age 50 years, primarily due to bvFTD, whereas in women this rise was primarily due to PSP. The median survival (N = 392) from diagnosis was 53.6 months (95% CI 50.9-62.0) overall, 73.1 months (95% CI 63.6-82.8) for patients with PPA, 42.8 months (95% CI 35.1-64.3) for patients with bvFTD, and 49.5 months (95% CI 39.2-53.7) for patients with PPS/CBS.

We observed a raw incidence rate of 0.77, thus considerably lower than in most previous reports. Incidence was substantially higher in men than in women. The prognosis from the time of diagnosis depended highly on the specific FTLD subtype. Our data are based on the large sample size and high capture rate of a central European population-based registry.

Language barriers pose a growing challenge in healthcare, potentially affecting the quality of care and patient safety.

This study quantified the prevalence and severity of language barriers in the emergency department (ED) and assess their impact on the ED consultation process and ED-related outcomes.

This was a prospective, observational single-centre cohort study. All patients between 18 April and 24 May 2024, presenting to the ED, were assessed for the presence of any language barrier. Demographic data and ED outcomes were collected for all patients. For patients with a language barrier, both the language barrier and its perceived impact on the consultation process (as assessed by the treating physician) were evaluated. Data were analysed using t-tests, chi-square tests. Regression analyses were performed to assess the impact of the severity of the language barrier on ED-related outcomes.

During the study period, 116 (7.9%) out of 1474 patients had a language barrier. These patients were younger (mean age 48.4 vs. 61.5 years, p < 0.001) and more often male (62.9% vs. 51.8%, p = 0.022) compared to those without a language barrier. Patients with a language barrier had shorter total treatment time (2:06 vs. 2:42 h, p = 0.009) and fewer ED revisits during the past 30 days (5.2% vs. 13.6%, p = 0.004). Communication aids were used in 62% of consultations, with family or acquaintances assisting in 44%, and professional interpreters were used in 2.2% of cases. Language barriers mostly affected history taking (mean score 2.71/5), explaining treatment plans (2.41/5), and follow-up discussions (2.32/5).

Language barriers are frequently encountered in emergency care, mostly affecting history taking, explaining treatment plans, and discussing follow-up instructions. Communication aids are inconsistently applied, and interpreter use is rare, risking loss of information and adverse outcomes.

Digital mental health interventions (DMHIs), such as cognitive bias modification for interpretations (CBM-I), offer promise for increasing access to anxiety treatment among underserved adolescents, but data regarding their efficacy are mixed. Paraprofessionals and other caring adults in youth's lives, such as non-parental adult mentors, may be able to support the use of DMHIs and increase teen engagement. The present mixed methods evaluation of a pilot open trial tested the feasibility, acceptability, and preliminary efficacy of implementing MindTrails Teen (an app-based, youth-adapted version of the web-based MindTrails CBM-I intervention) within mentor/mentee dyads. Thirty participants (composed of 15 dyads) participated in remote data collection for 5 weeks. A subset of participants (n = 7 mentors; n = 7 mentees) also provided qualitative feedback. Intervention outcomes (change in anxiety symptoms, and positive and negative interpretation bias), feasibility, and acceptability were assessed via a mix of qualitative interviews, quantitative change in questionnaire scores, and program completion and fidelity metrics. Outcomes were compared to pre-registered benchmarks. Large effect sizes were observed for changes in anxiety among youth. Small to medium effects were observed for change in positive interpretation bias, and no change was found for negative interpretation bias. Intervention outcomes should be considered with caution given very low internal consistency of the interpretation bias measure and the lack of a control comparison group. Acceptability of the intervention was rated positively by mentors and youth. Feasibility benchmarks were met for mentors but not for youth. Qualitative feedback indicated mentors perceived the app as helpful to their mentees, found that it either improved or did not affect their relationship, but also identified implementation challenges. Youth overall perceived the app as helpful but identified barriers to engagement.

Considering the impact of social support on women's mental health and the importance of their mental health in improving the health of the society, this study aimed to investigate the influence of social support, physical activity, general psychological distress, and demographic characteristics on self-reported health status among women.

This cross-sectional study was conducted on 350 women aged 18-75 in 2024 in Iran. The Vaux social support, international physical activities, Depression- Anxiety- Stress Scale (DASS-21) questionnaires were administered. The Cluster random sampling method was used. The data were analyzed using STATA version 18. The significance level for examining the hypotheses was p ≥ 0.05.

According to the results, there was a significant positive relationship between age, place of residence, history of chronic disease, evaluation of financial status and self-rated health in both crude and adjusted models. In addition, the positive significant relationship was observed between general psychological distress, and poor self- rated health in adjusted model. So that, the odds of poor self- rated health in women who achieved higher depression, anxiety, stress scale score was 1.04 times higher than others.

Considering the rising rates of psychological problems, particularly in recent years among women, as well as the influence of women's health on societal well-being, it is imperative for policymakers in women's health to pinpoint the underlying causes of mental disorders in women. They should take proactive measures to mitigate these causes, thereby decreasing the prevalence of anxiety, depression, and stress disorders through the implementation of effective interventions.

This study adopts the theoretical framework of "digital access divide-digital use divide-digital utility divide" to systematically investigate the differential impacts of different levels of the digital divide on the mental health of rural residents in China and its influencing mechanisms. Based on panel data from the China Family Panel Studies (CFPS) during 2020-2022, the study analyzes the internet access, usage, and perceived importance of rural residents in China, i.e., the situations of digital access divide, digital use divide, and digital utility divide they encounter, to examine the effects of these three levels of the digital divide on the mental health of rural residents.The findings are as follows: First, the digital access divide directly leads to a decline in mental health levels, and the digital use divide and digital utility divide, characterized by insufficient usage capabilities and improper usage behaviors, further exacerbate psychological damage. Second, different social groups exhibit heterogeneous results under the influence of the digital divide, with factors such as educational level and regional differences moderating the intensity of the digital divide's impact. Third, there are hierarchical differences in the mechanisms of influence: The digital access divide reduces the mental health level of farmers by lowering their self-assessed sense of fairness. The digital use divide reduces the mental health level of farmers by lowering their self-assessed social class. The impact of the digital utility divide on the mental health of rural residents is achieved by reducing both self-assessed social class and self-assessed economic status. This study provides a new analytical perspective for understanding the mental health issues of rural residents in the context of digital technology popularization and has reference value for formulating precise digital inclusion policies.

Domestic violence (DV) is a pervasive public health issue with profound physical, psychological, and social consequences. Help-seeking, particularly access to advocacy interventions, plays a pivotal role in promoting resilience and mental health well-being among DV survivors. Digital platforms and AI chatbots are emerging as promising tools for information and support. However, limited research has explored the views and needs of DV survivors regarding these technologies, impeding the development of culturally sensitive interventions for help-seeking.

This study aimed to investigate the perspectives and preferences of digital platform and AI chatbot among people with DV experience in Hong Kong, which could offer valuable insights to inform the design of tailored technological solutions for help-seeking.

Semi-structured qualitative interviews were conducted with 36 individuals who had DV experience over the past decade. Interviewees were recruited from DV-specific non-governmental organizations (NGOs) in the community using convenience and snowball sampling. Interviews took place either in-person or via videoconference between April 2023 and August 2024. Data were analyzed using reflexive thematic analysis, combining deductive and inductive approaches. Three trained coders identified themes and sub-themes through an iterative and collaborative process.

We identified three key themes regarding the recommended features of digital platforms: functions, content, and format. Regarding content, participants valued evidence-based information, step-by-step guidance, and survivor narratives. For format, participants valued procedural visualization, engaging multimedia, calming visual design, and clear text layout. Participants emphasized the potential of AI chatbots, highlighting benefits such as enhanced accessibility, efficient information filtering, and providing nonjudgmental feedback. However, concerns were raised about chatbots' limitations, particularly in empathy, personalization, and information accuracy.

DV survivors preferred digital platforms that prioritize safety, accessibility, and emotional support. Our study highlights the role of AI as a complementary tool to human support and calls for participatory approaches to facilitate designing effective interventions to reach their full potential.

Many factors, such as health, marital status, social relationships, and job status, influence psychological wellbeing. Previous research has suggested that educational attainment is also a key contributor to a happier life. Utilising data from the Understanding Society survey (2010 -2018), we conducted a comprehensive analysis of the direct and indirect effects of education on psychological wellbeing of 68,283 individuals in the UK. After controlling for relevant variables, we identified a direct association between educational attainment and psychological wellbeing. This aligns with earlier studies examining the link between education and happiness. While some of these studies report significant positive relationships, our results underscore the complexity of factors influencing psychological wellbeing, extending beyond education alone.

It is known that women with unintended pregnancies (UPs) experience many challenges. Women with psychiatric vulnerability may face specific concerns regarding the transmission of psychiatric vulnerability, parenting skills and bonding capacities with their offspring. This study aimed to explore how women with psychiatric vulnerability experience UPs.

This is a prospective qualitative study using semi-structured interviews during pregnancy and after delivery regarding the experiences of women with UPs and psychiatric vulnerability and involved partners. Follow-up interviews were conducted three to six months after delivery. Interpretative phenomenological analysis was employed to analyze the data.

Women with psychiatric vulnerabilities described unintended pregnancies as complex events, often marked by ambivalent pregnancy intentions, concerns about generational trauma, and fears about parental adequacy. The pregnancies triggered heightened psychiatric symptoms, resurfacing childhood memories, and concerns about stigma, yet also motivated participants to seek support from mental health professionals and trusted others. Women adopted coping strategies such as focusing on the future, seeking distraction, and accepting support to manage emotional challenges. Across pregnancy and postpartum, many participants reported developing strong prenatal and postnatal bonding with the newborn, creating safety nets, and making intentional behavioral changes to support their babies. For several women, the unintended pregnancy ultimately fostered personal growth and contributed to an improvement in mental well-being.

This study elucidates the experiences of unintended pregnancies in women with psychiatric vulnerability. Our findings show that for women with psychiatric vulnerability, UPs may also become a window of opportunity for treatment, personal growth and create a safety net for the baby and oneself. This work may help mental healthcare providers to support comprehensively expectant parents who decide to continue UPs.

Background: Comorbidity symptoms of posttraumatic stress disorder (PTSD) and depression are common and debilitating in schizophrenia, yet their patterns of co-occurrence remain poorly understood. This study aimed to identify severity-based comorbidity profiles of psychosis-related PTSD (PR-PTSD) and depression symptoms in hospitalised patients with schizophrenia and to examine their associations with sleep quality and quality of life.Methods: We conducted a cross-sectional study of 482 stabilised inpatients with schizophrenia (PANSS total score < 60), assessing PR-PTSD symptoms (IES-R), depression symptoms (SDS), sleep quality (PSQI), and quality of life (SQLS). Latent profile analysis was used to identify comorbidity profiles based on scores for PR-PTSD (intrusion, avoidance, arousal) and depression. Multinomial logistic regression and analysis of variance (ANOVA) were employed to examine correlates of profile membership and compare differences in outcomes.Results: LPA revealed an optimal three-profile solution: 'Low PR-PTSD/Low Depression' (50.0%), 'Moderate PR-PTSD/Mild Depression' (42.3%), and 'High PR-PTSD/Moderate Depression' (7.7%). Multinomial logistic regression indicated that a history of coercive treatment and polypharmacy were significantly associated with membership in the high-symptom profile. A clear dose-response relationship was observed for sleep quality, which progressively worsened with increasing comorbidity severity across profiles (p < .001). However, the overall group difference in quality of life total scores did not reach statistical significance (p = .067).Conclusion: Comorbid symptoms of PR-PTSD and depression in schizophrenia manifest as parallel severity profiles rather than distinct symptom-dominant subtypes. Sleep quality is a key differentiating factor and a potent transdiagnostic target for intervention. These findings underscore the need for stratified care models that address clinical correlates of high symptom burden, such as iatrogenic trauma and polypharmacy, to improve outcomes in this vulnerable population.