Iron is an indispensable element for the normal physiological function of the brain. In terms of neuronal metabolism, iron is involved in multiple critical biological processes such as oxygen transport, energy metabolism, DNA synthesis, neurotransmitter synthesis and myelin formation. Maintaining brain iron homeostasis is crucial for neurodevelopment and function. Iron dyshomeostasis has been associated with the onset and progression of various neuropsychiatric disorders, including Parkinson’s disease, Alzheimer’s disease, depression, schizophrenia, attention deficit hyperactivity disorder, and autism spectrum disorder. In neurodegenerative diseases such as Parkinson’s disease and Alzheimer’s disease, abnormally elevated iron levels can be detected in specific brain regions, including the basal ganglia and the prefrontal cortex. These changes are often accompanied by pathological processes such as oxidative stress, neuroinflammation, and pathological protein aggregation. Therefore, brain iron metabolism is an important entry point for understanding the pathophysiological process of neuropsychiatric disorders. Mechanistically, iron overload induces oxidative damage through the Fenton reaction, exacerbating mitochondrial dysfunction and abnormal protein aggregation. The effects of iron deficiency vary across different diseases; its impact on myelination and neurotransmitter synthesis may increase the risk of neurodevelopmental disorders such as attention deficit hyperactivity disorder (ADHD), while its effects on immune activation and energy metabolism may contribute to the development of mental disorders such as depression. This article systematically reviews the current research progress of the role of cerebral iron metabolism in neuropsychiatric diseases. It focuses on the mechanisms underlying iron homeostasis imbalances in neurodegenerative and psychiatric diseases. Building on this foundation, the article analyzes the therapeutic targets and clinical significance of iron metabolism-related interventions and outlines future research directions in this field.
Exposure to negative physical and social factors accelerates brain aging
Nature Medicine, Published online: 21 April 2026; doi:10.1038/s41591-026-04348-z
In a study that included 18,701 people from 34 countries, 73 aggregated physical and social exposomes exhibited nonlinear, synergistic effects that accelerated brain aging. In some cases, these effects were comparable to or stronger than those of mild cognitive impairment and dementia. Environmental inequities might shape brain aging and demand multisectoral and structural policy responses.
Adapting Behavioral Interventions for Dementia to Address NCDs and Mental Health
Conditions: Mental Health; Non Communicable Diseases; Dementia
Interventions: Behavioral: BECOME-D Intervention
Sponsors: Possible; University of California, San Francisco; National Institute of Mental Health (NIMH); Ministry of Health and Population, Nepal
Completed
Interventions: Behavioral: BECOME-D Intervention
Sponsors: Possible; University of California, San Francisco; National Institute of Mental Health (NIMH); Ministry of Health and Population, Nepal
Completed
Access to Technology-Mediated Community Mental Health Care Among Low-Socioeconomic Status Consumers With Serious Mental Illness: Qualitative Study
Background: Access to mental health care is critical for the effective management of serious mental illness (SMI), but consumers with low socioeconomic status (SES) have lower rates of service usage and worse retention in care. Digital technologies are often lauded as a way to bridge access gaps; however, little is known about how technology-mediated care may influence care access among low-SES consumers and how consumers use technology in care access. Objective: This study aimed to examine the applicability of Levesque et al’s access framework to technology-mediated care for SMI and analyze how low-SES consumers use technology to facilitate care access. Furthermore, the study assesses whether and how technologies are involved in care access at multiple points within the process of accessing care. Methods: This study used 2 qualitative methods: ethnographic observations at a mental health treatment court and interviews with low-SES consumers with SMI using community mental health care (n=14) and key informant interviews with health and service providers working with this population (n=14). Observations occurred from July 2022 through September 2023, and interviews occurred between January 2022 and May 2024. Data analysis involved both inductive and deductive coding approaches. Data from both the interviews and observations were analyzed in NVivo and further triangulated through analytic memos. Results: Levesque et al’s framework required several extensions to accommodate technology-mediated care related to SMI for low-SES consumers: (1) a cyclical rather than linear trajectory; (2) simultaneous care acquisition from multiple health and service providers; (3) staying in care long-term; (4) identification of both one-time and ongoing health needs; and (5) an emergency pathway for entering care. Consumers often faced challenges related to the varied digital requirements of each provider and a dearth of integrative, patient-facing tools like portals. Within this context, some consumers use mobile apps, communication, and telehealth technologies across various care access stages. Consumers used technology by figuring out how to navigate technology-mediated care, especially by leaning on others, such as case managers, for support. These others provided consumers with temporary technologies, showed them how to use technologies, and accompanied them through the process of using technology for accessing care. Conclusions: This study highlights that accessing care is iterative and ongoing, involving multiple forms of co-occurring service provision. A theoretical contribution of this work is its extension of Levesque et al’s care access framework to better reflect technology-mediated care for SMI among low-SES consumers. This work also underscores ongoing challenges for accessing technology-mediated care and the importance of human support in addressing access difficulties. Clinical implications include incorporating digital readiness assessments and providing comprehensive guidance on how consumers can effectively use technologies for care. Future work should investigate how technology-mediated care can make care access easier rather than harder.
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Opportunities for Digital Health to Support Early Psychosis Care in Ghana: Qualitative Study Among Patients, Caregivers, and Clinicians
Background: Youth experiencing early psychosis in West Africa often face delays in accessing evidence-based treatment. Digital mental health interventions may offer an acceptable and scalable approach to improve access to early psychosis care in West Africa; however, few data exist on the experiences and perspectives of patients with early psychosis and their caregivers to inform digital intervention development. Objective: This study aims to explore current experiences of early psychosis care, identify barriers and facilitators to in-person early psychosis care within health facilities, and identify opportunities for digital interventions to support patients with early psychosis and caregivers in Ghana. Methods: We conducted qualitative focus group discussions among patients with early psychosis, their caregivers, and their mental health care providers recruited at Accra Psychiatric Hospital in Accra, Ghana. Trained qualitative researchers facilitated discussions using a structured qualitative interview guide, exploring current care practices for early psychosis in Ghana, barriers and facilitators to facility-based care, and perceptions of digital mental health interventions. Transcripts were translated, transcribed, and analyzed thematically using a hybrid inductive and deductive approach grounded in the theoretical framework of acceptability. Results: Overall, we conducted 4 focus group discussions (N=31) among 7 patients with early psychosis (median age 28, IQR 21‐41 years), 6 caregivers (median age 58, IQR 29‐34 years), and 18 clinicians (median age 30, IQR 29‐34 years). Participants described current early psychosis care practices in Ghana, including seeking spiritual and traditional healing, the dearth of information and resources about psychosis, and the integral role of caregivers in facilitating treatment engagement and continuation (often at the cost of caregiver mental distress and burnout). Common barriers to facility-based mental health care included stigma associated with mental illness, lack of prior knowledge about early psychosis and treatment options, and practical constraints (eg, financial, logistical, and health care system limitations). Motivating factors for facility-based care included success stories from community members and strong rapport and trust in mental health clinicians. Technology (eg, mobile phones, laptops, radio, and television) was commonly used among participants in typical daily tasks, health information seeking, and stress reduction. Participants expressed support for digital tools that could deliver psychoeducation about early psychosis, support treatment adherence, and extend patient-provider communication between clinic visits. Conclusions: Digital mental health interventions have the potential to complement facility-based early psychosis services in Ghana by addressing misinformation, reducing access barriers, and supporting caregiver roles. These qualitative findings inform potential integration points, content, attributes, and strengths of digital modalities that could be leveraged to support patients with early psychosis and their caregivers in Ghana.
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Popular Online Content as a Treatment-as-Usual Control in Digital Mental Health Intervention Trials: Secondary Analysis of Two Online Randomized Controlled Trials With Repeated Measures
Background: Treatment-as-usual (TAU) conditions are intended to reflect the support typically received in routine treatment settings. For digital mental health interventions (DMHIs) delivered online, TAU conditions should reflect the usual patterns of online help-seeking. The lack of ecologically valid TAU control conditions has been a gap in effectiveness trials of online DMHIs. In this study, mental health–related popular online content (eg, advice TikToks, lived experience vlogs, and self-care infographics) was examined as a valuable TAU control condition. Objective: This study examined the feasibility of popular online content as a TAU control condition in DMHI trials. Methods: This study was a secondary analysis of two randomized controlled trials. Both trials recruited participants online, primarily via an online study recruitment platform. In study 1 (N=916), US adults with elevated depression or anxiety were randomized to either (1) complete a single-session DHMI for depression and anxiety (n=291), (2) search the web for popular online content relevant to their struggles (n=312), or (3) search a curated library of mental health–related popular online content (n=313). In study 2 (N=431), US adults with elevated loneliness were randomized to (1) complete a single-session DHMI for loneliness (n=136), (2) search a curated library of popular online content related to loneliness (n=145), or (3) complete an attention-matched control condition (n=150). All 6 programs took approximately 10 to 20 minutes to complete and were entirely self-guided. Participants rated each program’s credibility and expected benefit, as well as their feelings of distress (study 1) and loneliness (study 2). The studies did not involve interaction between participants and the research team. Results: In study 1, dropout during the treatment was 4.8% (14/291) for the single-session intervention, 25.9% (81/312) for online help-seeking, and 9.6% (30/313) for the curated library. The curated library’s credibility and expected benefit score did not differ from that of the single-session intervention (Cohen =0.08; =.88) and was higher than that of unguided help-seeking (Cohen =0.23; =.01). In study 2, dropout was higher in the curated library condition (7/145, 4.8%) than in the single-session intervention and the attention-matched control condition (0/136, 0.0% and 0/150, 0.0%). The mean credibility and expected benefit score for the curated library was comparable to that of the attention-matched control condition (Cohen =0.00; >.99) but lower than that of the single-session intervention (Cohen =0.32; =.02). Changes in distress and loneliness from baseline to 8-week follow-up did not differ across the conditions in study 1. All effect sizes were small in study 1 (Cohen <0.15 and no comparisons were statistically significant >.06). Similarly, in study 2, all effect sizes were small (Cohen <0.12), and no comparisons were statistically significant (>.25). Conclusions: Curated libraries of popular online content are a feasible, ecologically valid TAU benchmark for effectiveness trials of online DMHIs. Future research on TAU conditions in online help-seeking contexts should better align with observed DMHI attrition rates and account for the increasingly central role of conversational artificial intelligence in online mental health support. Trial Registration: OSF Registries 3DYMA; https://osf.io/3dyma and NVD79; https://osf.io/nvd79; ClinicalTrials.gov NCT05687162; https://clinicaltrials.gov/study/NCT05687162
Correction: Promoting Sustained Real-Life Benefits of Virtual Reality–Based Interventions in People With Mental Health and Substance Use Disorders: Qualitative Study
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A Toolkit to Improve Mental Health Treatment for Autistic Individuals
Conditions: Autism; Mental Health Conditions
Interventions: Behavioral: Enhanced Psychotherapy; Behavioral: Treatment as Usual (TAU)
Sponsors: Florida International University; Organization for Autism Research
Not yet recruiting
Interventions: Behavioral: Enhanced Psychotherapy; Behavioral: Treatment as Usual (TAU)
Sponsors: Florida International University; Organization for Autism Research
Not yet recruiting
Exploring Influencing Factors of Medication Adherence Among Chinese Patients With Alzheimer Disease: Delphi Study Informing Future Artificial Intelligence–Supported Interventions
Background: Alzheimer disease (AD) affects cognition, treatment adherence, family connections, and health care resource allocation. Most patients with AD have low adherence to medication therapy due to the limitations associated with cognitive impairment. Therefore, increasing the involvement of patients and their family members in medication management is important to improve treatment outcomes and reduce the burden of care. Objective: This study explores the potential application of artificial intelligence (AI) in medication management for Chinese patients with early- to mid-stage AD focusing on enhancing medication adherence. The study first predicts and evaluates key factors through an online Delphi study, which provides a basis for their subsequent incorporation into the AI model as input variables to enable prediction of medication-taking behaviors. Since AI research in medication management for this population is still undeveloped, this paper further explores the multiple potentials of AI from a theoretical view, including drug dosage optimization, multidrug interaction detection, and family education support. It will provide a preliminary direction and theoretical basis for the development of an intelligent medication management system in the future. Methods: The exploratory online Delphi study with no modification predicted the key factors influencing medication adherence. Based on the results, the study confirmed the potential of AI to improve adherence. Participation by 12 experts in 3 rounds systematically assessed the core elements influencing patients’ adherence to their medication. Results: Family care, social support, environmental factors, emotional support, and patient behaviors were identified as the primary factors influencing medication adherence among Chinese patients with AD. These factors were validated and ranked through iterative Delphi rounds, with family care and social support receiving the highest importance scores. The Wilcoxon signed-rank test indicated no significant difference between rounds (=.06), supporting the stability of the consensus. These findings establish a foundational set of variables for AI systems that predict and enhance medication adherence. Conclusions: This study highlights the critical factors affecting medication adherence by Chinese patients with AD. It was designed as an exploratory online Delphi study to identify and prioritize key influencing factors, rather than to validate a specific AI-based system, and the findings provide a theoretical foundation for future AI-informed interventions. The results also indicate theoretical potential roles for AI in supporting medication management, such as optimizing drug dosage, detecting multidrug interactions, and enhancing family education.
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Development of iGET Living, a Digital Graded Exposure Intervention for Youth With Chronic Pain: Multiphase User-Centered Design and Pilot Study
Background: Pediatric chronic pain affects up to one-third of youth and is associated with significant disruptions in social, emotional, and behavioral functioning. Although behavioral treatments are effective, access remains limited due to geographic, financial, and systemic barriers. Digital behavioral health interventions offer a promising solution, but many lack user-centered design, iterative refinement, and implementation-informed development strategies that support usability and scalability. Objective: This study aimed to develop and iteratively refine iGET Living, a digital graded exposure intervention for youth with chronic pain, using a combined user-centered and implementation-informed framework, and to evaluate its preliminary acceptability, feasibility, and user-perceived success. Methods: Guided by the Consolidated Framework for Implementation Research (CFIR) and the mHealth (mobile health) Agile Development and Lifecycle model, intervention development proceeded through 3 phases. Phase 0 translated an evidence-based in-person graded exposure treatment (GET Living) into an initial digital prototype. Phase 1 involved iterative user-centered refinement across 3 cycles of qualitative development sessions with youth with chronic pain (n=15), incorporating think-aloud usability testing, Likert-rated feedback, and rapid qualitative analysis mapped to CFIR constructs to guide real-time modifications to content, design, and functionality. Phase 2 piloted the refined intervention with a new sample of youth (n=38, n=30 completers) recruited from a tertiary pediatric pain clinic to evaluate feasibility, acceptability, treatment credibility and expectancy, and user-perceived functional improvements. Quantitative outcomes were summarized descriptively, and qualitative exit interview data were analyzed using rapid qualitative analysis. Results: Across development cycles, youth feedback informed substantive refinements to the intervention, including reducing text density, incorporating animated educational videos, enhancing interactive features, and improving navigation and layout. These changes resulted in progressive improvements in clarity, satisfaction, and acceptability across prototypes. In the Phase 2 pilot study, participants reported moderate-to-high treatment credibility (mean of 19.71 out of 30) and expectancy (mean of 17.96 out of 30), as well as high satisfaction (mean of 46.12 out of 60). Acceptability ratings across domains of the Theoretical Framework of Acceptability were favorable. Qualitative exit interviews highlighted the interventions’ perceived role in helping youth re-engage in valued activities. Conclusions: Using a combined CFIR and agile development approach, iGET Living emerged as a feasible, acceptable, engaging digital graded exposure intervention for youth with chronic pain. These findings highlight the value of integrating implementation frameworks and participatory design early in digital intervention development and support further evaluation in a preliminary efficacy trial. Trial Registration: ClinicalTrials.gov NCT05079984; https://clinicaltrials.gov/study/NCT05079984 International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2022-065997
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