Neglect is the leading cause of acute child protection interventions across high-income countries. In England, reducing the number of children subject to these interventions is a policy priority. However, limited evidence on the health and social factors driving recent trends in neglect constrains effective prevention. We aimed to assess the associations of area-level adult mental health, child poverty and employment, with recorded neglect, and to compare these associations with those observed for other forms of maltreatment.

Longitudinal ecological study using panel data.

147 upper-tier local authorities in England from 2014/2015 to 2022/2023.

Children aged 0-17 years.

Primary: annual rate of new child protection plans (CPPs) due to neglect. Secondary: annual rate of CPPs due to other maltreatment types (emotional, physical, sexual abuse) and rate of children entering care. We used two-way linear fixed effects models to estimate associations between each exposure and outcome, controlling for confounders.

Rising adult mental ill health was associated with higher rates of neglect and emotional abuse CPPs at area-level, but CIs included the null. Child poverty was positively associated with neglect CPPs: a one-percentage point increase was associated with around one additional CPP per 10 000 children (95% CI 0.2 to 2.2), equivalent to a model-estimated difference of over 30 000 plans over the study period. Higher employment was associated with fewer physical abuse CPPs, though CIs included the null. Care entry was positively associated with mental ill health and child poverty, and negatively associated with employment.

Recorded neglect and care entry appear particularly sensitive to wider social conditions affecting caregiving capacity and service response. Preventative policies to support parental mental health and tackle child poverty may help reduce the need for the most common and acute child protection interventions.

Despite the availability of student well-being services, university students remain highly susceptible to mental health challenges. Recent research highlights the potential of mindfulness-based interventions and attachment security priming in enhancing psychological well-being. This study compared the immediate and sustained effects of digitally delivered attachment priming and mindfulness-based practices on student mental health over one week. Using a randomized controlled design, 122 UK undergraduate students were assigned to one of three groups: repeated attachment security priming, mindfulness practice, or a waitlist control. Participants completed baseline assessments of stress, insomnia, attachment anxiety, emotion regulation, and mindfulness. The intervention groups engaged in five consecutive days of digital practice, and all participants completed follow-up assessments immediately after (T2), one week later (T3), and four weeks later (T4). Compared with the control group, both intervention groups showed significant long-term improvements in stress, insomnia, emotion regulation, and academic dropout intention. Attachment priming produced the most consistent and substantial benefits across time points. Each intervention also resulted in specific gains in mindfulness and attachment-related outcomes. These findings support the integration of digital attachment priming and mindfulness-based programs as promising supplements or alternatives to traditional university mental health services, especially when timely, accessible support is lacking.

Chronic diseases account for approximately 90% of the $4.5 trillion annual healthcare expenditure in the United States. While traditional clinical risk factors have been extensively studied, the predictive utility of multidimensional social determinants of health (SDOH), including psychosocial factors such as loneliness, psychological distress, and social support, remains inadequately characterized within machine learning (ML) prediction frameworks.

To develop and compare ML models that classify the presence of six major chronic conditions-hypertension, type 2 diabetes, coronary heart disease, COPD, depression, and anxiety-using an integrated framework encompassing demographic, socioeconomic, behavioral, psychosocial, healthcare access, functional status, and COVID-19-related predictors; and to quantify the relative predictive importance of each domain across disease categories.

We conducted a cross-sectional analysis of 32,614 adults from the 2024 NHIS. Twenty-four predictor variables spanning seven SDOH domains were used to train three ML algorithms: Logistic Regression (LR), Gradient Boosting Machine (GBM), and Random Forest (RF). Model performance was evaluated using 5-fold stratified cross-validation with AUROC, F1 score, and AUPRC. Subgroup analyses were performed by age, sex, and race/ethnicity. Because the design is cross-sectional, the models estimate the likelihood of prevalent disease, not incident risk; robustness was confirmed with alternative imputation (KNN and random-forest MICE), hyperparameter optimization, and three importance methods (Gini, permutation, and SHAP).

GBM achieved the highest AUROC for 5 of 6 outcomes, ranging from 0.793 (anxiety) to 0.857 (COPD). For cardiometabolic outcomes, age and BMI were dominant predictors (hypertension: age importance = 0.641, BMI = 0.117). In contrast, psychological distress (K6) and loneliness emerged as the top predictors for depression (importance = 0.285 and 0.234) and anxiety (0.245 and 0.161). Psychosocial factors collectively contributed 52% and 42% of predictive importance for depression and anxiety, but less than 3% for cardiometabolic diseases. Subgroup analyses showed consistent performance across demographic strata.

Integrating psychosocial determinants substantially enhances prediction of mental health outcomes but contributes minimally to cardiometabolic disease prediction. These findings support disease-specific screening and case-identification strategies that appropriately weight social, behavioral, and psychological dimensions.

Patients with Duchenne muscular dystrophy (DMD) experience increased rates of behavioral and neuropsychiatric disorders. The Centers for Disease Control and Prevention recommends routine mental health screenings and referrals for psychotherapy. However, utilization of psychosocial services among patients with DMD remains understudied.

We conducted a retrospective chart review of 163 male patients followed in a pediatric DMD clinic. Clinical documentation was reviewed for mental health concerns, pharmacologic treatment, and documentation of counseling referral and engagement within the electronic medical record.

Mental health concerns were reported in 86% of patients, and 63% of these individuals experienced more than one type of mental health concern. The most common concerns included anger, aggression, or irritability (52%), attention and hyperactivity disorders (34%), and symptoms consistent with autism spectrum disorder (31%). Among patients with documented mental health concerns, 44 (32%) received pharmacologic treatment. Documentation of counseling engagement was present in 36 (26%) patients, while 104 (74%) had no documented counseling engagement. Thirty-four (24%) patients had documentation of referral without documented attendance, and 70 (50%) patients had no documented referral or documentation of counseling services within the electronic medical record.

Neuropsychiatric symptoms were frequently documented among children with DMD in this cohort, while documentation of counseling referral and engagement was variable. Given the retrospective design, these findings may reflect documentation patterns rather than definitive measures of access to psychosocial care. Prospective studies are needed to further characterize psychosocial service engagement and evaluate multidisciplinary care approaches.

The United States maternal health crisis persists as a public health emergency characterized by high mortality rates and stark racial disparities. These disparities reflect structural racism and intersecting social inequities operating simultaneously across multiple systems.

This scoping review maps maternal health innovations implemented in the United States from 2017 to 2025, examining equity integration, implementation approaches, and scalability through structural racism, intersectionality, and RE-AIM frameworks.

A scoping review was conducted following PRISMA-ScR guidelines and JBI methodology. Systematic searches of PubMed/MEDLINE, CINAHL Plus, PsycINFO, and grey literature were performed from April through August 2025. Two independent reviewers screened records; a third reviewer resolved disagreements. Quality assessment used the Mixed Methods Appraisal Tool.

Fourteen studies across six categories were identified: Digital Health and Telehealth (n = 4, 29%), Clinical Quality Improvement (n = 2, 14%), Community Workforce Development (n = 2, 14%), Social Determinants of Health (n = 2, 14%), Policy and Payment Reform (n = 2, 14%), and Communication and Mental Health Access (n = 2, 14%). All retrieved innovations incorporated explicit equity considerations targeting Medicaid populations, racial and ethnic minorities, and safety-net communities. Nine innovations (64%) achieved scaled implementation; sustainability was strongest among policy-institutionalized and cost-effective interventions. The equity integration finding reflects characteristics of the equity-focused literature retrieved rather than a field-wide empirical claim. Critical scaling factors include infrastructure capacity, policy alignment, sustainable funding, and demonstrated cost-effectiveness.

Nurses are positioned to lead equity-centered maternal health innovation and advance the dismantling of structural determinants driving persistent racial disparities in maternal outcomes across the United States.

Consciousness science is fragmented, and empirical investigations are largely confined within the framework of each theory of consciousness (ToC). Proliferating ToCs accumulate anomalies without progress, operating orthogonally. The principle of recurrency, functional and architectural, specifies a unifying, mechanistic scaffold for consciousness to arise. We show that all theories tacitly invoke feedback loops and can be re-expressed along a single axis of recursion. Four nested levels, viz., cellular, local inter-areal, global, and lateral, map onto state consciousness, phenomenal (P) content, conscious access (A), and phenomenal character, respectively, thus tying evolved anatomy to phenomenality. The classical P-A distinction dissolves into a graded cascade wherein deeper recursion expands the set of reportable, behaviour-driving variables. Recurrency, defined as structural, causal, and/or functional feedforward and feedback connections between elements within a system, is favoured in biological architectures, and supports the closed-loop interactions between brain, body, and environment that underlie adaptive behaviour and self-related processing. Disparities in the explanatory mechanisms across theories of consciousness can thus be resolved by converging onto this shared principle on the implementation axis, rather than deal with phenomenal-first or functional-first ontologies. The field urgently requires this implementation-first distillation that is biologically plausible, mechanistic, and empirically testable.

Socioemotional competencies (SEC) are essential for nurses to provide quality care and to maintain their own health. Historically underrepresented, nursing programs are changing their curricula to incorporate SEC development more strongly. Although it is recommended to practice SEC during clinical placement, studies on how to support nursing students in developing these competencies are lacking.

Our study explores second-year nursing students' perceived and actual use of a reflection tool during their first 20-week clinical placement. Designed to support SEC development, the study focuses on how students incorporate the application in their learning process for SEC development.

An embedded mixed method study was conducted with 15 students from a nursing program in the Netherlands. Qualitative surveys and semistructured interviews were used to capture students' experiences with the application both during and at the end of the clinical placement. Log data from the application provided insight into how the app was used. The mixed methods data were analyzed using warranted assertion analysis.

The app helped students relate learning goals to clinical experiences, identify learning opportunities, and experience a sense of growth. Features that removed practical barriers to reflecting were experienced as most beneficial. Although SEC-focused use was limited (n=7), involved students used the app over a longer period of time and reported greater benefits. Nevertheless, 13 students stopped using the app halfway through their clinical placement, as their attitude shifted from learning to working.

This study gives a rich description of how nursing students used a reflection app to structure their learning process during clinical placement. It reveals that smartphone-based reflection supports students in clinical placement learning. Specifically, the app lowers barriers to engaging in structural reflection and decreases the mental burden of self-regulated learning. However, more guidance and a multimodal intervention approach seem necessary for SEC development. Further research into how to account for students' shifting attitudes toward learning is needed.

The burden of mental disorders is high in conflict-affected populations. In Palestine, we piloted Inuka Coaching, a digital intervention adapted from the Friendship Bench delivered by trained and supervised lay coaches. This paper documents the implementation of the intervention in this highly volatile context after October 7, 2023.

This study aimed to describe the implementation of Inuka Coaching, a digital mental health tool based on task shifting, in Palestine and examine contextual challenges, fidelity to the coaching model, and lessons learned regarding recruitment, retention, and delivery during escalating ethnic cleansing.

Two Palestinian mental health professionals were trained and certified in the Inuka method as head coaches, and subsequently trained 5 lay coaches. Palestinian adults in Gaza and the West Bank were recruited primarily through social media and received up to 4 structured, text-based coaching sessions typically delivered over 4 weeks depending on participant availability and preference. Standardized mental health screening questionnaires (Self-Reporting Questionnaire-20 [SRQ-20] and Posttraumatic Stress Disorder Checklist for the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition [PCL-5]) were collected at baseline, immediately after the first coaching session, and 3 months after the final session. Session transcripts were reviewed to assess coaches' fidelity to the Inuka method, and a focus group discussion explored coaches' experiences with training, delivery, and contextual challenges.

Between August 2023 and February 2024, a total of 70 participants were enrolled. Baseline assessments indicated high levels of psychological distress: 95.7% (67/70) scored above the PCL-5 threshold of 31, suggesting likely posttraumatic stress disorder, and 69.4% (43/62) scored in the "at risk" range on the SRQ-20. The effectiveness of the method could not be determined as retention was low, with only 7.1% (5/70) completing the program. Coach fidelity was high, with 94.6% (35/37) of transcripts adhering to all 5 steps of the intervention. Coaches reported positive experiences with the method but identified challenges related to recruitment, session continuity, platform usability, and the need for flexibility during acute crises. Key implementation learnings included the importance of early in-person collaboration and training, culturally sensitive framing, flexible delivery and session structures, and robust support for lay coaches.

While digital, task-shifted mental health interventions can be delivered with fidelity in conflict settings, sustaining engagement during escalating violence remains challenging. Future implementations require flexible design, context-sensitive recruitment and retention strategies, adaptive delivery models, and strong support for lay coaches.

Continuity of care is essential in psychiatric services due to the chronic, relapsing nature of mental health conditions, yet care pathways remain heavily fragmented at critical transition points. Although advancements in AI and machine learning (ML) offer powerful capabilities to track longitudinal data and automate clinical decision-making, a structured appraisal of their efficacy in supporting continuity of psychiatric care is lacking. This protocol outlines a mixed methods systematic review to evaluate how AI-driven workflows can proactively enhance monitoring, optimize triage and care resource allocation, and address systemic coordination gaps.

The primary objective of this systematic review is to evaluate the effectiveness of AI and ML interventions in psychiatric care settings in improving the continuity of patient care. Secondary objectives include stratifying the types of AI architectures used and identifying implementation barriers and facilitators.

A systematic literature search of MEDLINE, Embase, CENTRAL, CINAHL, and APA PsycInfo will be conducted to identify peer-reviewed randomized controlled trials, nonrandomized interventional studies, and qualitative or mixed methods evaluations published between January 1, 2016, and December 31, 2025. Two independent reviewers will perform study screening, data extraction, and quality assessment. A mixed methods convergent synthesis using the Joanna Briggs Institute (JBI) convergent segregated approach will be carried out to synthesize quantitative evidence on effectiveness and qualitative data on implementation.

This review is self-funded and was officially registered with PROSPERO on January 24, 2026 (CRD420251245352). Comprehensive database searches have commenced, with full-text screening and transcript reviews projected to conclude by late August 2026, followed by data analysis and submission of the systematic review manuscript targeted for early spring 2027.

By systematically mapping interventions across patient, institutional, and health system levels, this review will clarify the clinical effectiveness, ethical boundaries, and logistical implementation factors of psychiatric AI tools. Ultimately, these consolidated insights will provide an evidence-based foundation to inform clinical guidelines; governance frameworks; and the design of proactive, learning mental health systems.

PROSPERO CRD420251245352; https://www.crd.york.ac.uk/PROSPERO/view/CRD420251245352.

PRR1-10.2196/95931.

There is an urgent and critical need to support the mental health of health care providers, given high rates of stress and burnout. Although the issues are complex, digital access to information and support can help address the needs, as technology can facilitate on-demand links to private, customized resources, including peer support. Beyond Silence (McMaster University) is an evidence-informed mobile health platform co-designed with health care workers and grounded in prior evidence that mental health literacy and peer support can reduce stigma and facilitate earlier help-seeking.

This study aimed to (1) explore how health care workers across diverse health care settings use the app and (2) identify opportunities and barriers to implementation.

A multiple-case study framework, informed by the Consolidated Framework for Implementation Research (CFIR), was applied to capture 4 months of implementation across a purposive sample of 7 diverse Canadian health care organizations. Implementation within each organization was led by designated organizational champions who leveraged existing communication channels and standardized promotional materials to invite employees to voluntarily download and use the app. Implementation outcomes were assessed using app analytics (downloads and feature use) and semistructured baseline and follow-up interviews with organizational champions to explore contextual influences on uptake.

Approximately 1066 employees downloaded the app over the 4-month period, ranging from <2% to >45% of employees across the 7 organizations. Interviews with 28 organizational champions noted that there was good leadership support for the technology, aligning with their mission to address employee mental health. Barriers to use, however, included workplace culture surrounding mental health and help-seeking, lack of awareness about when and how to use the app, and infrastructure-related challenges, such as limited time and a lack of private spaces to download and use the technology.

Effective implementation is a precondition for positive outcomes; therefore, strategies are needed to optimize technology implementation. Recommendations include evaluating organizational readiness, building mental health literacy, creating a multimodal communication and implementation plan, addressing technology requirements, and embedding the technology into organizational policies and practices. This study highlights key challenges in the implementation of the Beyond Silence peer support platform for health care workers, including slow adoption linked to mental health stigma, competing demands, and limited frontline engagement. Addressing these barriers will require innovative, trust-building strategies to support meaningful uptake and sustained use.