This study aimed to investigate the influence of postpartum depression literacy on health promoting behaviors among postpartum women, focusing on the mediating role of self-efficacy and the moderating effect of family functioning in this dynamic relationship. A cross-sectional survey was conducted with 622 postpartum women recruited during routine prenatal visits. Data were collected using validated instruments, including the Postpartum Depression Literacy Scale, Health-Promoting Lifestyle Profile II, General Self-Efficacy Scale, and Family Adaptability and Cohesion Scale. A moderated mediation model was adopted to examine direct, indirect, and interaction effects among the variables. Higher levels of postpartum depression literacy were significantly associated with increased engagement in health promoting behaviors. Self-efficacy partially mediated this relationship, with an indirect effect size of 0.35, indicating its central role in translating mental health literacy into positive behavioral outcomes. Family functioning moderated the association between postpartum depression literacy and self-efficacy, with stronger family support amplifying the beneficial effect (interaction effect, p < 0.05). These findings indicate that postpartum depression literacy significantly contributes to the adoption of health promoting behaviors among postpartum women, primarily by enhancing self-efficacy, a mechanism that is further reinforced in the context of high family functioning. This underscores the necessity of incorporating both mental health literacy enhancement and family-centered support strategies into comprehensive maternal health promotion programs to maximize behavioral engagement and improve overall maternal well being.

Passive and task-based MEG responses have been extensively studied in clinical populations to identify signatures that could serve as markers for clinical diagnosis or to monitor progression of treatment. Establishing the reliability of these responses across repeat testing as a benchmark is therefore essential. Emerging MEG technology using optically pumped magnetometers (OPMs) promises a new era for MEG, enhancing both research capabilities and clinical applications. However, the test-retest reliability of various MEG responses measured by these new systems has not yet been characterised. In this study, we measured a range of neural responses to task and rest using a whole-head OPM-MEG system. We assessed the stability of these responses over time in five adult participants, each tested across five different days. Our findings indicated that the well-established face-sensitive M170 response shows reliable group amplitude and latency over time, with a standard deviation of only 1 ms in latency. We showed that induced responses were more variable than evoked. Passive MEG power (via movie-watching as a pseudo-resting state metric) particularly in the alpha band, demonstrated high consistency across sessions, aligning with conventional MEG literature. Our results demonstrate reliability of a range of MEG metrics and provide a benchmark for evaluating changes over successive recordings.

Stress inherent in the modern world is considered one of the main causes of Mental Health Disorders (MHDs) that spread in every country around the world. These mental and behavioral problems primarily affect the mind and brain that change emotions and perception, especially if they are not diagnosed or treated early. MHD diseases are difficult to be distinguished from each other because they come in many forms with different severity of symptoms and different periods of suffering. A person's bioactivity can be measured by the wearable technology such as smart watches that become more advanced and widely spread. A new framework based on analyzing the motor activity data measured by smart watches is presented to diagnose mental illnesses such as schizophrenia and depression as well as analyze complex behavioral patterns. The framework encodes the behavioral time series data into image patterns using modified Markov Transition Field. These images have been processed using a modified Convolutional Neural Network and an attention pooling approach for the classification of depression and schizophrenia patients. The proposed system achieved an accuracy of 96.6% in schizophrenia and 94.85% in depression as a precision of 92.1% in schizophrenia and 96.77% in depression. The proposed system is able to analyze the motor activity of individual and able to diagnose the mental illness. The results of the proposed system are superior to those used in detecting mental health disorders.

This case report presents the treatment process and recovery of a man in his 30s who presented with post-traumatic stress disorder (PTSD) symptoms as a result of and exacerbated by the ongoing violence following a period of civil unrest. The patient presented with extreme hypervigilance, intrusive thoughts, sleep disturbance and social withdrawal. Within a resource-poor community mental health context, the patient was provided with a treatment model that included psychoeducation, culturally sensitised cognitive-behavioural therapy, a selective serotonin reuptake inhibitor medication and community support. Adaptations to the standard PTSD care included an extended treatment duration, present-focused coping strategies to address chronic trauma and innovative medication management during supply shortages. Despite insecurity and stigma, the symptoms significantly reduced and the patient reported functional gains, including cofacilitating peer groups. This case describes the outcome of a task-shifted, culturally sensitive intervention in a conflict zone and a scalable model for trauma care amid resource constraints and ongoing unrest.

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterised by deficits in social communication and repetitive behaviours, often accompanied by sleep disturbances. These sleep problems, including prolonged sleep latency and fragmented sleep, affect more than half of autistic individuals, exacerbating functional impairments and diminishing quality of life. Cognitive behavioural therapy (CBT) has shown promise in addressing sleep disturbances in ASD, with preliminary studies indicating improvements in sleep quality. However, no systematic review has comprehensively summarised the effects of CBT on sleep in autistic individuals.

This systematic review and meta-analysis will synthesise evidence on the efficacy of CBT for improving sleep quality in individuals with ASD. We will search multiple databases (eg, PubMed, Web of Science) for studies published until May 2025. Inclusion criteria encompass randomised controlled trials, single-arm studies and observational studies involving children and adults with ASD and moderate sleep problems. Interventions targeting sleep quality using CBT techniques will be considered. Data extraction will focus on study details, participant information, intervention specifics and sleep outcome measures (eg, total sleep time, sleep onset latency, etc). Risk of bias will be assessed using tools such as Cochrane Risk of Bias Tool V.2, Risk Of Bias In Non-randomised Studies-of Interventions and Review Manager 5.3. A meta-analysis will be conducted using Stata 18, with heterogeneity evaluated using the I² statistic and Cochran's Q test.

Given that the dataset for this investigation is derived from publicly accessible databases, there is no direct interaction with patients; thus, ethical approval is not required.

CRD42025643701.

The high prevalence of loneliness in young people, aged 10-24 years, is increasingly recognised as an urgent global health concern. The experience of loneliness is linked to a wide range of adverse physical and mental health outcomes. A lack of loneliness scales that can accurately capture the authentic experiences of young people has hampered progress in our understanding of the aetiology and sequelae of youth loneliness, as well as the development of preventative policies and interventions. Here, we provide a protocol for developing and validating an age-sensitive loneliness scale for young people aged 10-24 years: the Youth Loneliness Scale (YLS). The scale is designed to measure loneliness in the general population of young people in the UK.

The scale is coproduced with young people from design to dissemination. The scale development process follows a three-phased, multistep approach that includes item development, scale construction and scale evaluation. Item development is achieved via deductive (literature review) and inductive methods (arts workshops and focus groups), as well as a Delphi survey of experts (by profession and experience) for initial refinement. The scale is then constructed via pretesting items in cognitive interviews with young people, and exploratory testing for preliminary evaluation and refinement. Finally, the scale is administered in confirmatory testing, where a full psychometric evaluation is provided.

The project was approved by the Queen Mary University of London Research Ethics Committee (Reference: 2024-0231-341) as the lead site and subsequently endorsed by the University of Manchester Research Ethics Committee. The YLS scale and results of its psychometric evaluation will be published open-access. The protocol provided here will allow researchers to evaluate the final scale generated against the plans set out. We also encourage the use and adaptation of the protocol to develop age-sensitive loneliness scales for other populations.

Research suggests that hormonal fluctuations may contribute to sleep-related physiological and psychological outcomes that differentially affect women's overall health and well-being. Yet, systematic enquiries on this potential interaction across the menstrual cycle are scant.

This protocol paper describes a pilot observational study investigating changes in objective and subjective sleep measures, metabolic biomarkers (body temperature, blood glucose and hormonal concentrations) and psychological outcomes (depressive symptoms, menstrual cycle-related pain and psychological distress), in a cohort of healthy premenopausal women aged 18-35, regularly menstruating, and without sleep disorders. Participants' sleep is monitored every night over the course of two full menstrual cycles using a Food and Drug Administration (FDA)-approved diagnostic ring from SleepImage and via next morning self-reports (ie, sleep diaries). To minimise the likelihood of undiagnosed sleep disorders, participants also complete two nights of at-home polysomnography. Daily hormonal concentrations are assessed via morning urinalysis using the Mira Fertility Monitor while transitions between hormonal phases are further confirmed by biochemical assays. Body temperature, blood glucose concentrations, diet and physical activity behaviours are continuously recorded using wearable devices and smartphone apps from Oura and Levels. The primary outcomes of this study are total sleep time and sleep quality. Secondary outcomes include sleep onset latency, wakefulness after sleep onset, sleep staging, daytime sleepiness, respiratory rate, resting heart rate, heart rate variability and subjective mood. This study will provide novel data to disentangle the intricate relationship between sleep behaviours, mental well-being and menstrual health in premenopausal women.

The study was approved by the Institutional Review Board at Parker University (protocol number PUIRB-2025-3). Study findings will be presented in peer-reviewed publications and at academic conferences.

Timely access to healthcare has implications for health through early diagnosis and management of long-term conditions. However, when healthcare services are provided during traditional working hours, this limits workers' ability to attend appointments.

We use repeated cross-sectional data from full-time employees participating in the National General Practice Patient Survey in England between 2013 and 2017 (N= 1,097,156). We estimate the health-related quality of life effects (measured by EQ-5D-5L) of an individual being unable to take time away from work to attend primary care appointments. We use an instrumental variable approach to overcome endogeneity concerns around health and employment.

Jobs constraining primary care access led to significantly lower EQ-5D-5L utility scores (local average treatment effect on the treated = -0.101 (95% CI: -0.153 to -0.044)), representing an 11.4 percentage point decrease at the mean. The effects were concentrated on physical health domains of the EQ-5D-5L rather than mental health, and the effect on pain/discomfort was the largest in magnitude. The negative effect on the EQ-5D-5L utility score was larger in magnitude for individuals with long-term conditions than those without.

Improving access to primary care by reducing constraints on access during typical working hours could improve population health. Further investigation is needed of the effects of this access barrier for individuals with long-term conditions, and the cost effectiveness of different policy approaches.

Over 30% of people in the United Kingdom are living with a long-term physical health condition. Early preventative peer support interventions could improve the lives and psychosocial well-being of people with long-term physical health conditions and reduce progression of any symptoms of low mood to more significant depression. In partnership with people with long-term conditions and industry stakeholders, we have co-designed an online peer support platform, CommonGround, to help people with long-term health conditions connect, support others, share experiences, and receive evidence-based information and advice on self-management.

This feasibility randomized controlled trial will investigate whether the CommonGround platform is usable and acceptable for people with long-term physical health conditions experiencing mild depressive symptoms and whether conducting a future, larger confirmatory randomized controlled trial is feasible.

A mixed methods, 2-arm, parallel-group, unblinded randomized controlled feasibility trial will be conducted nationally across the United Kingdom. Participants will include 150 adults (aged ≥18 years) who have access to the internet and are living with at least one long-term physical health condition and subthreshold depression (scoring 5-9 on the Patient Health Questionnaire-8). Following baseline assessments, eligible participants will be randomized to a coproduced online peer support and psychoeducation platform or a control condition where participants will receive fortnightly emails containing links to the National Health Service mental health web pages. Assessment measures will be collected at baseline and the midintervention (6 weeks) and postintervention (12 weeks) time points. A purposive sample of approximately 40 participants will be interviewed after the intervention to evaluate participant experiences and views on acceptability. The primary feasibility outcome is the number of participants recruited to the trial per week and in total via each recruitment route (as self-reported by participants).

Recruitment for the feasibility trial began on February 12, 2024. Quantitative data collection was completed by October 23, 2024, and qualitative data collection was completed by December 3, 2024.

This trial will explore the acceptability and feasibility of our coproduced online peer support platform with embedded psychoeducational resources targeted for people living with long-term physical health conditions and subthreshold depression who are at risk of developing major depressive disorder. The findings will inform the future design of a larger randomized controlled trial exploring the platform's clinical efficacy and cost-effectiveness.

ClinicalTrials.gov NCT06222346; https://clinicaltrials.gov/study/NCT06222346.

DERR1-10.2196/71513.

Dating apps are virtual sociosexual networking platforms that facilitate varying social and sexual relationships and have considerably changed the way that many queer individuals form social, sexual, and romantic connections. Despite evidence that social media use can be associated with either diminished or improved mental health, few studies have explored the association between dating apps and mental health among queer adults.

Using reparative theory and a transformative paradigm, this research sought to critically explore the association between dating apps and mental health among queer adults in Canada..

We used a convergent mixed methods design comprising an online survey (N=250) and one-on-one interviews (subsample of n=22) among queer adults from across Canada. Participants were recruited using Grindr advertisements and selected for diverse identities. The survey and interview collected information on dating app use and mental health. A structural equation model assessed the association between dating app use and mental health symptoms and the mediating role of discrimination and community connectedness. Hybrid reflexive thematic analysis of interviews elucidated how power and marginalization are negotiated, resisted, and refused in everyday app use.

Participants used an average of 3.22 (SD 1.78) dating apps, most commonly for casual sex (208/249, 83.5%). Dating app use was associated with increased life satisfaction (β=0.31, 95% CI 0.32-1.12; P<.001) and self-esteem (β=0.21, 95% CI 0.04-0.38; P=.02) but not with depression (β=-0.16, 95% CI -0.33 to 0.02; P=.07) or anxiety (β=-0.11, 95% CI -0.45 to 0.10; P=.20). Discrimination and seeking social approval were associated with adverse mental health. Although seeking friendship was the least commonly reported motivation (98/249, 39.4%), interviewees described making friends unintentionally through intimate experiences. Increased community connection was associated with heightened life satisfaction (β=0.18, 95% CI 0.14-0.82; P=.01) and self-esteem (β=0.13, 95% CI 0.004-0.28; P=.04). Interviewees described managing negative impacts of use by adjusting expectations, using technological features to avoid unwanted interactions, and welcoming unexpected interactions in addition to their desired connections from use. Participant accounts of the inconsistent and evolving ways to use dating apps revealed the complex relationship between app use and well-being.

Queer peoples use dating apps conscientiously, leveraging hope and serendipity to stumble upon novel and welcomed connections. Queer peoples use strategies to promote their well-being while navigating this threatening internet-based sociosexual space. The mixed methods approach provides nuance to the relationship between dating app use and well-being, underscoring the context-dependent and temporally dynamic association between them.