Background and objectiveWithin the interdisciplinary field of cyberpsychology and mental health, trait mindfulness has been associated with lower levels of subclinical anomalous symptoms, such as Psychotic-Like Experiences (PLEs), has gained increasing attention. However, in the context of daily digital human-computer interactions (e.g., listening to AI-generated music), the specific pathways through which Mindfulness operates (the involvement with Presence and Perceived Interactivity) and the boundary conditions of physiological arousal, remain to be clarified. This study aims to explore the direct predictive relationship between mindfulness and individuals’ PLEs, and to investigate the multipath effect of brief AI-generated music listening context (with Presence and Perceived Interactivity), along with the moderating effect of Arousal.MethodsWith a cross-sectional survey design, self-reported multimodal data were collected from 527 Chinese participants. Structural equation modeling (SEM) was conducted using Mplus 8.3 to empirically test the main effects (path coefficients) of the theoretical hypotheses and the moderation model.ResultsBoth the measurement and structural models demonstrated good fit. The path analysis results indicated that: (1) trait trait mindfulness was significantly and negatively associated with PLEs (p < 0.001); (2) regarding the main effect paths of brief AI-generated music listening context, mindfulness significantly and positively predict individuals’ Presence and Perceived Interactivity, while both significantly and negatively predict PLEs; (3) Arousal played a significant moderating role in the relationship between mindfulness and brief AI-generated music listening context, exhibiting a synergistic enhancement effect. Higher levels of Arousal significantly amplified the positive prediction of Mindfulness on both Presence and Perceived Interactivity (p < 0.01).ConclusionsWith the help the SEM, this study maps out the underlying multipath network through which mindfulness is associated with lower PLEs within a brief AI-generated music listening context. The observed associations suggest that presence and perceived interactivity may function as pivotal correlational nodes relevant to mental health correlates, while these results also nuance classic cognitive load assumptions by indicating a potential synergistic association between trait mindfulness and emotional arousal. These results provide a solid empirical foundation and prospective insights, for the mental health-oriented design of AI music products, such as the immersive acoustic environment construction and dynamic, arousal-based interaction recommendations.
RutiSafeNet: a behavioral risk and nursing workload monitoring tool for open-door acute inpatient mental health units
IntroductionOpen-door policies for acute inpatient mental health units (AIMHU) have shown promising results in reducing coercive measures, but concerns remain among patients and staff regarding increased workload, constant surveillance, and potential safety risks associated with these policies. This study aims to develop a monitoring tool to facilitate safety management in AIMHUs by monitoring behavioral risks and nursing workload.MethodsThis study employed a qualitative approach using the content analysis method. Data were collected through three in-depth interviews and two focus groups involving staff (n=19) from the AIMHU of the hospital.Results34 items were identified to define behavioral risks related to self-harm and suicide, aggressiveness, and absconding, alongside factors affecting nursing workload. These items were categorized into three levels of risk: low, moderate, and high.DiscussionRutiSafeNet is a preliminary, observation-based monitoring prototype intended to support, rather than to predict, structured risk and workload monitoring in acute inpatient mental health units. As a qualitatively developed instrument, it requires psychometric validation, including inter-rater reliability, construct and criterion validity, predictive value, and clinical feasibility, before it can be implemented as a validated scale in clinical practice.
Path and Bayesian network analyses in the complex design of a well-being survey via New Zealand’s Integrated Data Infrastructure
IntroductionIn mental health research involved with sensitive features and privacy issues, using integrated data offers an efficient alternative to traditional approaches such as interviews or in−person data collection. These conventional methods frequently face logistical barriers, including low response rates among study populations. Using integrated data from multiple existing administrative and survey sources provides protection for participants and economic savings for researchers, despite being constrained by the limitations of the original data sources. Our research questions were: 1) Can we conduct path and network analyses of school absenteeism, psychosocial factors, and mental health outcomes using the integrated survey data from New Zealand’s Integrated Data Infrastructure (IDI)? and 2) How can we account for the complex design of the General Social Survey (GSS) to ensure representative inference?Materials and methodsThe study population was New Zealand youth enrolled in school, aged 15 years and older in 2018, who participated in the 2018 GSS. The study analyzed the Ministry of Education data integrated with the 2018 GSS survey data from New Zealand’s IDI. To explore the relationship between outcomes of including the WHO-5, “perceived life worthwhileness”, “perceived general health”, and predictors including school absenteeism, psychosocial factors, and family factors, quantile mixed−effects regression, path analysis, and Bayesian network (BN) analysis were used. The complex survey design was calibrated using replicated weights from the GSS, a design-based method for complex sampling, in path and regression analyses, and bootstrap resampling, in BN analysis.ResultsIn descending order from the weighted path model, overall life satisfaction (standardized path coefficient: 0.36), perceived health condition (0.34), ease in accepting cultural identity (0.12), and trust in the education system (0.07) were all significantly (positively) related to students’ mental health well-being (WHO-5). Perceived life worthwhileness correlated with the WHO-5 but was only connected to overall life satisfaction. Similar factors were identified for perceived health, with additional attributing factors, such as fear of crime in the area and the family’s overall well-being.ConclusionThe integration of Bayesian networks and path analysis offers rigorous methods for detecting complex interrelationships among integrated mental health outcomes from population data and variables from a complex survey design.
Governing AI for Mental Health: Fragmented State Approaches and the Case for a Federal Framework
State-level regulation of AI used for mental health is emerging in the absence of a federal framework. States are taking different approaches to regulation, resulting in a fragmented regulatory landscape. This Viewpoint aims to identify the governance approaches that US states are using to regulate the use of AI in mental health and analyze the limitations of each. A 4-state case analysis was conducted using the statutory text of bills and laws in Illinois, Utah, New York, and Nevada. Two governance approaches were identified. The first regulates the use of AI in clinical contexts, and the second regulates the technology itself. Some states have combined elements of both approaches to address AI use more comprehensively. While these approaches aim to mitigate harm, they differ in where they believe risk lies in the use of AI for mental health support. The limitations of these divergent approaches include uneven protections for consumers and regulatory uncertainty for developers, vendors, deployers, and clinicians. Because AI in mental health operates across both clinical and consumer domains, neither approach alone can address the risks associated with its use for mental health support. A coordinated, risk-based federal regulatory floor is needed to ensure consistent protections across states.
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Structuring Digital Mental Health Care Navigation: Co-Design Nominal Group Technique Study to Develop the MChart Definition and Typology of the Characteristics of Digital Mental Health Care Navigation Tools
<strong>Background:</strong> Australia’s mental health care system has been characterized by complexity and fragmentation, as highlighted by numerous reports, commissions, and inquiries. In response, digital mental health care navigation tools have emerged as a promising solution to help individuals locate appropriate mental health services. The rapid proliferation of these tools—without a clear understanding of their definitions and characteristics—risks creating confusion rather than clarity for users. Terms such as “navigation” and “navigators” are often used interchangeably, further complicating the landscape. <strong>Objective:</strong> This study addressed the need for a standardized definition and typology of the characteristics of digital mental health care navigation tools. <strong>Methods:</strong> This study was part of the development of a digital mental health care navigation tool for navigators and planners (MChart). It used a co-design approach using expert-based cooperative analysis, which is a nominal group technique to develop a definition and typology of the characteristics of digital mental health care navigation tools. This process was guided by the Technology Readiness Level for Implementation Sciences framework. The co-design process involved two 2-hour sessions with an expert panel comprising 28 participants, including representatives from mental health planning, primary health care, health care financing and delivery, community-managed organizations, clinical settings (psychiatrists, psychologists, and general practitioners), and consumers. <strong>Results:</strong> The expert panel collaboratively developed a consensus definition of digital mental health care navigation tools, outlining their scope and intended targets. Through the co-design process, the panel identified 157 characteristics of digital mental health care navigation tools. These characteristics were organized into 5 primary domains: type, management, content, design, and quality. The definition and typology characteristics provide a structured framework for understanding and evaluating the diverse range of digital mental health care navigation tools currently available. <strong>Conclusions:</strong> The co-designed definition and typology offer a foundational step toward reducing confusion in the digital mental health care navigation space. This study supports the development of quality standards that can be used to assess and compare existing and future tools. This framework has the potential to guide developers, end users, and policymakers in creating more effective, user-centered navigation solutions within Australia’s mental health care system and internationally.
Mobility Patterns and Mental Health During the COVID-19 Pandemic: Longitudinal Observational Study Using Smartphone Mobility Data
<strong>Background:</strong> The COVID-19 pandemic disrupted mobility globally, but its mental health implications remain difficult to characterize because most studies relied on lockdown status, population-level mobility indicators, or self-reported mobility. These approaches may miss individual differences in actual movement patterns and cannot fully examine bidirectional relationships between mobility and mental health. Individual-level smartphone geolocation data may provide a more objective and temporally aligned measure of mobility during periods of societal disruption. <strong>Objective:</strong> This study aimed to use individual-level Google location history (GLH) data and population-level Google community mobility reports (GCMRs) to examine concurrent and longitudinal relationships between pandemic-era mobility patterns and mental health symptoms in Hong Kong. <strong>Methods:</strong> This study analyzed data from the CU-COVID19 cohort study, an online longitudinal survey study of the psychological impact of the pandemic in Hong Kong. Mental health symptoms over the previous 14 days were assessed at baseline, 6 months, and 12 months using the 9-item Patient Health Questionnaire, the 7-item Generalized Anxiety Disorder scale, and the 4-item PTSD Checklist for DSM-5. Participants provided retrospective GLH data reflecting their mobility during the corresponding 14-day survey periods. The analytic sample included 145 participants with baseline GLH data, of whom 110 had 6-month follow-up data and 49 had data available at all 3 assessment waves. GLH data were used to derive mobility factors representing journey diversity, immobility, and remoteness. Population-level mobility during the same 14-day periods was measured using Hong Kong GCMR residential stay data. Concurrent mediation models examined whether individual mobility mediated associations between population-level residential stay and mental health symptoms. Longitudinal models examined bidirectional associations between changes in individual mobility and mental health across 6-month intervals. <strong>Results:</strong> Population-level residential stay was not directly associated with mental health. In concurrent mediation models, higher population-level residential stay was associated with lower individual journey diversity (β=–0.36; <i>P</i><.001), and lower journey diversity was associated with higher depression (β=–0.29; <i>P</i>=.02) and posttraumatic stress disorder (PTSD) (β=–0.35; <i>P</i>=.002). Bootstrapped indirect effects suggested mediation through journey diversity for depressive symptoms (β=0.11, 95% CI 0.02-0.25) and PTSD symptoms (β=0.13, 95% CI 0.05-0.27), although the depression-related indirect effect became less robust after adjustment for local and individual COVID-19 infection indicators. Longitudinally, higher baseline depressive symptoms predicted subsequent reductions in journey diversity (β=–0.15; <i>P</i>=.02), and reductions in journey diversity predicted higher subsequent depressive symptoms (β=–0.43; <i>P</i>=.008). <strong>Conclusions:</strong> Individual-level mobility patterns, particularly lower journey diversity, showed more consistent associations with mental health symptoms than population-level residential stay. Findings suggest bidirectional relationships between mobility and mental health and demonstrate the potential of smartphone geolocation data for digital phenotyping. However, the modest and self-selected sample, limited GCMR availability, and observational design require cautious interpretation.
Daily Multivitamin May Help Older Adults Maintain Cardiovascular Function
A daily multivitamin-mineral supplement modestly improved cardiovascular-related functional health in older adults over three years, according to a secondary analysis of the large COSMOS randomized clinical trial. The findings suggest that routine multivitamin use may help preserve day-to-day physical functioning as people age, particularly among those with certain preexisting cardiovascular conditions.
The research was presented July 27 at NUTRITION 2026, the annual meeting of the American Society for Nutrition.
The findings add to a growing body of evidence from the COSMOS trial suggesting that daily multivitamin supplementation may support healthy aging. Previous analyses reported modest improvements in cognitive function and slower biological aging, although multivitamins have not been shown to reduce major cardiovascular events.
The analysis included 16,027 participants from the COcoa Supplement and Multivitamin Outcomes Study (COSMOS), a randomized, double-blind, placebo-controlled trial that enrolled 21,442 U.S. adults without major cardiovascular disease at baseline. Men were at least 60 years old, and women were at least 65 years old when they entered the study.
Investigators evaluated participants’ responses to the Kansas City Cardiomyopathy Questionnaire (KCCQ), a validated patient-reported measure of cardiovascular health status. The questionnaire assesses physical function, symptom burden, and an overall clinical summary score reflecting the combined impact of both.
Participants assigned to receive a daily multivitamin experienced small but statistically significant improvements in symptom burden compared with those receiving placebo. While the supplements did not significantly improve physical ability scores overall, they produced a modest improvement in the overall clinical summary score.
“The results provide new evidence that a daily multivitamin modestly improved cardiovascular-related functional health, with more pronounced benefits in those with existing carotid stenosis,” the investigators concluded.
The largest benefits were seen in participants with carotid stenosis, a narrowing of the carotid arteries that increases the risk of stroke. Among the 122 participants with the condition, multivitamin supplementation produced clinically meaningful improvements in cardiovascular functional health scores, suggesting this subgroup may derive greater benefit than the broader study population.
The researchers noted that maintaining cardiovascular functional health has practical implications for older adults. Improvements in symptom burden may translate into greater ease performing everyday activities such as dressing, bathing, walking, climbing stairs, and completing household chores. Reduced fatigue, shortness of breath, and swelling could also help older adults remain active and independent.
The trial also evaluated cocoa extract supplementation, but it did not improve cardiovascular functional health in the study population overall. However, a subgroup analysis suggested cocoa extract helped preserve symptom burden scores among participants with heart failure, indicating that additional studies may be warranted in patients with established cardiovascular disease.
Unlike many nutrition studies that focus on disease prevention, this analysis examined how supplementation affected participants’ daily functioning and quality of life.
The investigators cautioned that the observed improvements with multivitamin use were modest and should not be viewed as a replacement for established healthy lifestyle measures such as maintaining a nutritious diet and engaging in regular physical activity.
Because this was a secondary analysis, the findings should be considered hypothesis-generating. The authors said future targeted clinical trials are needed to determine whether specific groups of older adults—particularly those with carotid stenosis or other cardiovascular conditions—may experience greater functional benefits from daily multivitamin supplementation.
The post Daily Multivitamin May Help Older Adults Maintain Cardiovascular Function appeared first on Inside Precision Medicine.
Resting-state functional connectivity of the sensorimotor network in medication-naïve Chinese children with ADHD: cross-sectional associations with hyperactivity/impulsivity and executive function
BackgroundAttention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder, often—but not always—characterized by inattention, hyperactivity/impulsivity, and deficits in executive functions (EFs); some individuals may also exhibit sensorimotor dysfunction. While SMN dysfunction has been implicated in ADHD, the patterns of SMN functional connectivity (FC) and their relationships with clinical symptoms and EFs remain inconsistent, partly due to methodological heterogeneity.MethodsThe study included 62 medication-naïve patients with ADHD (aged 6–15 years) and 46 healthy controls matched for age, sex, and IQ. Clinical symptoms and EFs were assessed using CPRS, IVA-CPT, and Stroop tests. Resting-state fMRI data were acquired, and ROIs within SMN, SN, DMN, and FPN were selected from the Dosenbach atlas. FC was analyzed using Network-Based Statistics (NBS). Partial correlations explored FC–behavior relationships in the ADHD group, controlling for age, sex, and IQ.ResultsThe ADHD group showed significantly higher CPRS hyperactivity/impulsivity scores and poorer IVA-CPT and Stroop performance. Compared to controls, ADHD showed increased FC within SMN (right posterior insula to left precentral gyrus/parietal lobe), between SMN–DMN (precentral gyrus, dorsal frontal cortex, temporal lobe, angular gyrus, posterior cingulate cortex, and precuneus), and SMN–SN (middle insula, superior parietal lobule, superior temporal gyrus, basal ganglia, and fusiform gyrus). Enhanced intra-SMN FC was negatively correlated with impulsivity/hyperactivity and hyperactivity index scores. Enhanced SMN–DMN FC was negatively correlated with hyperactivity symptoms and positively correlated with control quotients in IVA-CPT. Enhanced SMN–SN FC was negatively correlated with Stroop correct responses and positively correlated with omission errors.ConclusionsIn this medication-naïve pediatric sample, distinct SMN connectivity patterns differentially related to ADHD symptoms and executive function. However, given the cross-sectional design and modest sample size, these associations cannot establish causality; they require replication in longitudinal studies and larger cohorts to clarify whether they reflect developmental variation, neurobiological subtypes, or epiphenomena.
Historical trauma as a contributor to postpartum depression among Indigenous mothers
IntroductionPostpartum depression (PPD) is a significant public health concern. Moreover, research suggests that American Indian/Alaskan Native (AI/AN) mothers experience postpartum depression at higher rates than the general population (Heck, 2021; Ko et al., 2017). As a result, understanding the potential causes of higher PPD among AI/AN mothers is helpful to the development of better interventions to reduce PPD among AI/AN mothers. A potential cause of higher PPD symptoms among AI/AN mothers is historical trauma (HT). HT refers to the cumulative psychological wounding experienced across generations due to systemic oppression, colonization, slavery, and other traumatic events experienced by a group of individuals.MethodsTo test the theorized relationships between HT and PPD symptoms, we conducted an online survey of adult women who both identified as Indigenous and who give birth in the past five years (N = 56). The survey consisted of the psychometrically suitable measures of the Historical Loss Scale (HLS: Whitbeck at al, 2004) and the Edinburgh Postnatal Depression Scale (EPDS; Cox et al., 1987). .ResultsThe results indicated that a model of HLS scores as a predictor of PPD symptoms over and above the controls of income, mental health diagnosis, and the total number of children of the birth mother fit the data well (χ2 = 13.60; df = 10; p = .192; RMSEA = .081 [90% CI: .000, .178]; CFI = .949). Moreover, of all the predictors, the dimension of the HLS measuring mothers’ endorsement of the presence of oppressive governmental and institutional policies toward AI/AN was the strongest predictor of greater PPD (β = .28, p < .05). A Bollen Stine bootstrap test was also used to confirm the stability of the model. The Bollen Stine operates by comparing the theorized model to a model that perfectly fits the data. The results of the Bollen Stine test indicated that the theorized model was not significantly different than a model of perfect fit. .DiscussionSuch results suggest that a potential explanation of higher PPD symptoms among AI/AN mothers is the effects of HT. Future interventions to reduce PPD symptoms among AI/AN mothers may benefit from an additional focus on treating HT.
Clinical Outcomes and Predictors of Improvement With Virtual Behavioral Health Care for Gambling Disorder: Retrospective Cohort Study
<strong>Background:</strong> Gambling disorder is associated with substantial psychiatric and functional burden, yet few individuals receive treatment. Limited real-world evidence exists evaluating outcomes of virtually delivered behavioral health care for gambling disorder, particularly among clinically complex patients. <strong>Objective:</strong> The purpose of this study was to evaluate gambling symptom severity outcomes among adults with gambling disorder receiving care from Birches Health. We aimed to (1) characterize the clinical profile of adults seeking treatment for gambling disorder; (2) quantify changes in gambling symptom severity over the initial 12 weeks of treatment and examine whether baseline clinical complexity, such as gambling symptom severity, depression severity, and psychiatric comorbidities, was associated with differences in gambling symptom severity improvement over time; and (3) estimate the timing and likelihood of achieving clinically meaningful improvement in gambling symptom severity. <strong>Methods:</strong> This retrospective cohort study included 1305 adults receiving virtual behavioral health treatment for gambling disorder through Birches Health between June 2024 and April 2026. Gambling symptom severity was assessed using the Gambling Symptom Assessment Scale (G-SAS) weekly. Linear mixed-effects models evaluated changes in gambling symptom severity over 12 weeks and associations with baseline clinical characteristics. Clinically meaningful improvement was defined as a reduction of 4 or more points in the G-SAS score. <strong>Results:</strong> Participants had a mean age of 41.5 (SD 13.1) years, 65.2% (851/1305) were male, and baseline gambling symptom severity was moderate (mean G-SAS score 20.5, SD 11.83). Over half (730/1305, 56%) of participants presented with at least one psychiatric comorbidity, most commonly anxiety disorder (351/1305, 26.9%) and depressive disorder (276/1305, 21.1%). Gambling symptom severity declined significantly over the first 12 weeks of treatment, with G-SAS scores decreasing by approximately 0.099 points per day (<i>P</i><.001), corresponding to an estimated 8.3-point reduction over 12 weeks. Higher baseline depressive symptom severity was associated with faster improvement in gambling symptoms (<i>P</i>=.01), whereas depressive disorder (<i>P</i>=.03) and attention-deficit/hyperactivity disorder (<i>P</i>=.008) diagnoses were associated with slower improvement trajectories. Among patients with routine follow-up assessments recorded during the initial 12 weeks of treatment (1071/1305, 82.1%), 71.7% (935/1305) achieved clinically meaningful improvement in gambling symptom severity, with a median time to improvement of 14 days. <strong>Conclusions:</strong> A clinically complex population of adults receiving care through a national virtual behavioral health care provider demonstrated rapid and clinically meaningful reductions in gambling symptom severity. These findings highlight the potential of specialized virtual care models to expand access to gambling treatment and support symptom improvement in routine care settings. Future research should evaluate longer-term recovery trajectories and identify factors associated with sustained improvement and ongoing engagement in care.
