Coping styles and mental health outcomes in partners who have experienced a perinatal loss: a longitudinal study
Occupational burnout and risk of suicidality in healthcare professionals: a PRISMA-guided systematic review
TeleABA for Hospitalized Adolescents and Young Adults With Autism Spectrum Disorder
Interventions: Behavioral: Standard Hospital Care; Behavioral: Telehealth Applied Behavior Analysis (TeleABA)
Sponsors: Caring Technologies, Inc.; National Institute of Mental Health (NIMH); Hackensack Meridian Health; Center for Social Dynamics; Rutgers University
Not yet recruiting
A Web-Based Self-Management Intervention for Return-to-Work Among Persons With Common Mental Disorders on Sick Leave: Case Study of mWorks
Background: mWorks is a co-designed, web-based self-management intervention developed to empower persons with common mental disorders who are on sick leave during the return-to-work process. However, limited knowledge of how mWorks is delivered and engaged with in real-world settings constrains further development and implementation. In line with the Medical Research Council framework for complex intervention evaluation, such an approach is required to examine (1) contextual factors influencing implementation, (2) fidelity and variation in delivery, and (3) how service users and professionals experience and respond to the intervention. Objective: This study aimed to evaluate the process of implementing mWorks, specifically focusing on assessing the intervention’s delivery in relation to the context, implementation process, and mechanisms of impact. Methods: This single-case study was bounded by the delivery period of 10 weeks in a primary and specialist mental health service context. During this period, return-to-work professionals (n=2) and service users (n=6) collaborated to initiate mWorks usage. Both qualitative and quantitative methods were used to triangulate multiple data sources. Results: The pandemic and mental health problems posed contextual barriers, particularly during recruitment. However, perceptions of mWorks as a credible and relevant intervention facilitated its implementation. The delivery was performed according to plan, with minimal adaptations. All users adhered to the intervention, and dialogue meetings were highly valued. mWorks was used flexibly according to users’ needs, both during sick leave and at work. The potential impacts included a transformative process for users, fostering acceptance, self-esteem, self-compassion, and a sense of control. It also had the potential to prevent mental ill health, transform negatives into positives, facilitate disclosure of mental health, and support goal setting. The use of quantitative measures for empowerment, engagement, self-efficacy, depression stigma, and quality of life proved feasible and supported the assumptions and direction of results. Conclusions: The recruitment stage of the implementation program encountered significant contextual barriers. However, once the delivery stage began, the implementation of mWorks proved to be feasible. Despite the limited scope of this study, with its small number of participants, the triangulation of data suggests that both users and professionals benefited from mWorks.
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AI Agents Are Coming: 5-Stage Taxonomy of Language-Based AI Systems for Psychiatry, Psychotherapy, and Counseling
The rapid evolution of large language models has accelerated the development of agentic artificial intelligence (AI) systems capable of pursuing autonomous goals, creating an urgent need for structural frameworks in psychiatry and psychotherapy. While existing classifications often draw parallels to autonomous driving, this paper argues that the mental health domain requires a distinct, domain-specific theoretical foundation, as the 2 domains differ fundamentally in their semantic, ideographic, and epistemological demands. Furthermore, they differ in their end goals, for which we introduce terms such as agentic guidance capability. To guide clinicians and researchers through these developments, we propose a 5-stage taxonomy for language-based AI systems that differentiates technical functionality from clinical effectiveness. The taxonomy progresses from level 1 (knowledge level), in which systems perform static benchmark tasks, to level 2 (elementary level), characterized by dynamic engagement in specific therapeutic microskills. At level 3 (integration level), systems achieve consistency across and within modules, as well as basic case-level conceptualization suitable for blended therapy under human oversight. Level 4 (saturation level) describes therapist-in-the-loop systems capable of autonomous functioning with minimal supervision, whereas level 5 (mastery level) represents AI systems that are technically capable of performing autonomous therapy. By distinguishing technical functionality from clinical effectiveness, we conclude that level 4 or level 5 performance does not automatically translate into full treatment effectiveness, even if high treatment fidelity can be achieved. We conclude by emphasizing the need to shift benchmarking from static knowledge tests to dynamic evaluations of therapeutic capabilities in order to safely navigate the transition toward autonomous care.
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Family caregivers’ involvement in home-based recovery for patients with schizophrenia: a qualitative study in Beijing, China
Case Report: A novel de novo heterozygous truncating mutation in MED12L identified in a Chinese autistic boy
STAT+: HHS presses ahead with effort to curb antidepressant use
WASHINGTON — Health secretary Robert F. Kennedy Jr. is pressing forward with his effort to help Americans stop taking psychiatric drugs, a medical practice known as deprescribing.
Earlier this month, dozens of mental health professionals met with federal health officials to map out forthcoming clinical guidance they hope will help providers instruct patients on how to come off of antidepressant medications. While the Department of Health and Human Services has discussed plans to hold such a meeting, the outlines of the discussion haven’t been reported.
During those talks, they reviewed guidance from European nations and worked on recommendations for nonmedication-based options for patients to address their mental health, such as therapy. A senior HHS official said they discussed gaps in the research around deprescribing SSRIs, including the side effects a person may experience, which vary depending on the drug and how long the person was on it, and how to recognize the difference between those side effects and a return of a patient’s depressive symptoms.
HALO-TRIAL: High, Medium And LOw Intensity Psychotherapy for Binge Eating Disorder
Interventions: Behavioral: Cognitive Behavioral Therapy Enhanced – Individual; Behavioral: Cognitive Behavioral Therapy Enhanced – Group; Behavioral: Cognitive Behavioral Therapy – Guided Self Help; Behavioral: Systemic Narrative Therapy – Group
Sponsors: Herlev and Gentofte Hospital; Jascha Fonden; BETA-HEALTH Foundation; Mental Health Centre Ballerup; Region Capital Denmark; University of Copenhagen
Recruiting

