Co-design of a single session intervention chatbot for people on waitlists for eating disorder treatment: a qualitative interview and workshop study

Journal of Eating Disorders, Год журнала: 2025, Номер 13(1)

Опубликована: Март 11, 2025

Abstract Background Early treatment is critical to improve eating disorder prognosis. Single session interventions have been proposed as a strategy provide short term support people on waitlists for treatment, however, it not always possible access this early intervention. Conversational artificial intelligence agents or “chatbots” reflect unique opportunity attempt fill gap in service provision. The aim of research was co-design novel chatbot capable delivering single intervention adults the waitlist across diagnostic spectrum and ascertain its preliminary acceptability feasibility. Methods A Double Diamond approach employed which included four phases: discover, define, develop, deliver. There were 17 participants total Australia; ten with lived experience an seven registered psychologists working field disorders, who participated online interviews workshops. Thematic content analyses undertaken interview/workshop transcriptions findings from previous phase informing ideas development next phase. final prototype presented deliver Results identified main themes that present phases interviews/workshops: conversational tone, safety risk management, user journey structure, content. Conclusions Overall, feedback positive throughout process both psychologists. Incorporating allowed refinement chatbot. Further required evaluate chatbot’s efficacy settings.

Язык: Английский

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Enhancing parental skills through artificial intelligence‐based conversational agents: The PAT Initiative

Family Relations, Год журнала: 2025, Номер unknown

Опубликована: Фев. 27, 2025

Abstract Objective We aim to describe the development of a conversational agent (CA) for parenting, termed PAT (Parenting Assistant platform), demonstrate how artificial intelligence (AI) can enhance parenting skills. Background Behavioral problems are most common issues in childhood mental health. Developing and disseminating scalable interventions address early‐stage behavioral high priority. Artificial (AI)‐based CAs offer innovative methods deliver reduce problems. have capability interact through text or voice conversations undergo training using evidence‐based programs. However, research on is limited. Experience The consisted three phases: Phase 1 was purely rule‐based, 2 hybrid (rule‐based format plus large language models), 3 featured an agentic architecture. latest version includes prompt engineering, guardrails, retrieval‐augmented generation, few‐shots learning, context, memory management Although comprehensive empirical results pending, iterative enhancement indicate potential effective digital intervention. architecture aims provide robust, context‐aware interactions support challenges. Implications reach broader population parents personalized tailored their specific needs. Moreover, structured timely support, which family dynamics contribute improved long‐term outcomes both children. Conclusion AI‐based be used as alternatives waitlists; cotherapists; implemented health care, health, school settings. benefits risks different types CA features discussed.

Язык: Английский

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Understanding and overcoming barriers to digital health adoption: a patient and public involvement study

Translational Behavioral Medicine, Год журнала: 2025, Номер 15(1)

Опубликована: Янв. 1, 2025

Abstract Background Digital health (DH) technologies provide scalable and cost-effective solutions to improve population but face challenges of uneven adoption high attrition, particularly among vulnerable minority groups. Purpose This study explores factors influencing DH in a multicultural identifies strategies equitable access. Methods Using Patient Public Involvement approach, lay facilitators engaged adults at public eateries Singapore discuss motivations barriers adoption. A semi-structured guide facilitated discussions, followed by an optional socio-demographic survey. Data were analyzed through inductive thematic analysis mapped behavior change theory identify mechanisms action (MoA) techniques (BCTs) support Results Facilitators 118 participants between November 2022 February 2023. Five key themes identified from the discussions: (a) awareness solutions, (b) weighing benefits against burdens, (c) accessibility, (d) trust developers technology, (e) impact user experience. These 13 MoA 26 BCTs, informing five enhance adoption: community-based promotion credible digital literacy training, brief counselling opportune moments healthcare settings, variable rewards tied personal values, policies ensuring accessibility regulation, gamified, user-friendly designs emphasizing feedback behavioral cues. Conclusion Designing implementing that are accessible, trustworthy, motivating—integrated within services promoted community efforts—can address diverse communities may help narrow divide.

Язык: Английский

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LvL UP 1.0, a holistic mHealth lifestyle coaching intervention for the prevention of non-communicable diseases and common mental disorders: a mixed methods feasibility study

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Май 24, 2025

LvL UP is a smartphone-based holistic lifestyle coaching intervention aimed at improving health behaviours, mental well-being, and preventing noncommunicable diseases common disorders. It features ‘talk tools’ approach, combining automated literacy via conversational agent with digital tools such as journaling, life hacks, slow-paced breathing exercises. An ‘in-the-wild' mixed-methods study was conducted in Singapore to evaluate UP’s feasibility acceptability inform future definitive trial. The app available on iOS Android from March August 2023 promoted through online offline strategies. Data collection included in-app surveys, usage metrics, interviews, summarised using descriptive statistics template analysis. downloaded 307 times. 99 active users were analysed. Most female aged 21–35 years mild moderate vulnerabilities physical activity, diet, depressive symptoms. Engagement highest during the first eight days, 9% remaining engaged for up 50 days. Users rated technology acceptance highly, finding enjoyable, easy use, informative. Suggested improvements streamlined onboarding, fixing bugs, shortening dialogues, adding rewards. findings support have informed enhancements trials.

Язык: Английский

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Person-Generated Health Data in Women’s Health: Scoping Review (Preprint)

Journal of Medical Internet Research, Год журнала: 2024, Номер 26, С. e53327 - e53327

Опубликована: Март 26, 2024

Background The increased pervasiveness of digital health technology is producing large amounts person-generated data (PGHD). These can empower people to monitor their promote prevention and management disease. Women make up one the largest groups consumers self-tracking technology. Objective In this scoping review, we aimed (1) identify different areas women’s monitored using PGHD from connected devices, (2) explore personal metrics collected through these technologies, (3) synthesize facilitators barriers adoption use devices. Methods Following PRISMA (Preferred Reporting Items for Systematic Reviews Meta-Analyses) guidelines reviews, searched 5 databases articles published between January 1, 2015, February 29, 2020. Papers were included if they targeted women or female individuals incorporated tools that outside a clinical setting. Results We total 406 papers in review. Articles on steadily 2015 focused spanned several topics, with pregnancy postpartum period being most prevalent followed by cancer. Types used collect mobile apps, wearables, websites, Internet Things smart 2-way messaging, interactive voice response, implantable A thematic analysis 41.4% (168/406) revealed 6 themes regarding collecting PGHD: accessibility connectivity, design functionality, accuracy credibility, (4) audience adoption, (5) impact community service, (6) behavior. Conclusions Leading COVID-19 pandemic, address concerns was steady rise. prominence related reflects strong focus reproductive research highlights opportunities development other topics. Digital acceptable when it relevant target audience, seen as user-friendly, considered personalization preferences while also ensuring measurements credibility information. integration technologies into care will continue evolve, factors such liability provider workload need be considered. While acknowledging diversity individual needs, positively self-care numerous journeys. pandemic has ushered acceptance This study could serve baseline comparison how field evolved result. International Registered Report Identifier (IRRID) RR2-10.2196/26110

Язык: Английский

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Artificial Intelligence (AI) and academic publishing in psychiatry

International Journal of Law and Psychiatry, Год журнала: 2025, Номер 101, С. 102105 - 102105

Опубликована: Май 3, 2025

The current and potential impact of various applications artificial intelligence (AI) to the field academic publishing in psychiatry is subject increasing attention. At present, AI algorithms assist data analysis, allowing researchers process large datasets quickly uncover complex patterns that would be challenging detect manually. In psychiatry, this capability can potentially help integrate from genetics, neuroimaging, clinical assessments. AI-driven natural language processing (NLP) tools might also facilitate systematic reviews meta-analyses by automating extraction synthesis information vast bodies published literature. publishing, streamline publication certain ways. Automated systems screen manuscripts for methodological rigor, ethical compliance, conflicts interest, thereby reducing burden on editors prompting them consider matters, possibly accelerating timeline. AI-powered are already used with dissemination research findings generating summaries identifying key insights, making more accessible a broader audience. future, has enhance psychiatric other Predictive analytics identify emerging trends gaps literature, guiding future studies funding priorities, although remains speculative now. could robust collaborations connecting complementary expertise interests. Additionally, integration digital platforms democratise access cutting-edge research, promote global knowledge sharing, accelerate advancements care. As continues evolve, its hold drive significant progress understanding treating mental disorders. It essential these developments accompanied openness about use clear declarations authors publishers specific work.

Язык: Английский

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AI in Mental Health: A Review of Technological Advancements and Ethical Issues in Psychiatry

Issues in Mental Health Nursing, Год журнала: 2025, Номер unknown, С. 1 - 9

Опубликована: Май 16, 2025

Artificial intelligence (AI) is transforming digital health, its influence expanding across multiple sectors, with mental health and psychiatric care emerging as key areas of transformation. While significant advancements have been made in medical AI, there remains a need to better understand how these technologies are integrated into clinical practice what challenges they introduce. We examine the use AI identifying treating disorders, highlighting impact on screening, diagnosis, intervention strategies. Technologies such natural language processing (NLP), machine learning (ML), computer-delivered cognitive behavioral therapy (CBT) discussed context enhancing Clinical Decision Support Systems (CDSS). innovations promise increased efficiency accessibility care, also introduce ethical challenges, including concerns over privacy, bias, reduced human interaction. Through critical evaluation, we find that greater transparency, unbiased model development systems work hand human-led should be encouraged. Our findings underscore importance continued research regulation ensure responsible effective deployment services.

Язык: Английский

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Psychological, economic, and ethical factors in human feedback for a chatbot-based smoking cessation intervention

npj Digital Medicine, Год журнала: 2025, Номер 8(1)

Опубликована: Май 31, 2025

Язык: Английский

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New technology, psychiatry, and the law: Panic, prudence, possibility

International Journal of Law and Psychiatry, Год журнала: 2024, Номер 94, С. 101984 - 101984

Опубликована: Март 23, 2024

Throughout human history, all new technology has been met with surprise, anxiety, panic, and - eventually prudent adoption of certain aspects specific technological advances. This pattern is evident in the histories most technologies, ranging from steam power nineteenth century, to television twentieth now 'artificial intelligence' (AI) twenty-first century. Each generation believes that advances its era are quantitatively qualitatively different those previous generations, but underlying phenomenon same: shock new, followed by more gradual adjustment (and of) technology. These concerns apparent today relation AI, which reflects interesting incremental on existing rather than stand-alone developments. The usual technologies (e.g., they will replace function) are, perhaps, concerning fields such as mental capacity law, often applies people impaired decision-making who might be especially vulnerable appear capable encroaching disproportionately or other areas core function. paper approaches this topic an historical standpoint, noting both panics past possibilities offered AI today, provided it approached a proportionate, prudent, person-centered way, underpinned appropriate ethical guidance active awareness clinical legal practice.

Язык: Английский

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Combining AI and human support in mental health: a digital intervention with comparable effectiveness to human-delivered care

medRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Июль 17, 2024

Abstract Escalating global mental health demand exceeds existing clinical capacity. Scalable digital solutions will be essential to expand access high-quality healthcare. This study evaluated the effectiveness of a intervention alleviate mild, moderate and severe symptoms generalized anxiety. structured, evidence-based program combined an Artificial Intelligence (AI) driven conversational agent deliver content with human oversight user support maximize engagement effectiveness. The was compared three propensity-matched real-world patient comparator groups: i) waiting control; ii) face-to-face cognitive behavioral therapy (CBT); iii) remote typed-CBT. Endpoints for effectiveness, engagement, acceptability, safety were collected before, during after intervention, at one-month follow-up. Participants (n=299) used median 6 hours over 53 days. There large clinically meaningful reduction in anxiety group (per-protocol (n=169): change on GAD-7 = −7.4, d 1.6; intention-to-treat (n=299): −5.4, 1.1) that statistically superior control, non-inferior human-delivered care, sustained By combining AI support, achieved outcomes comparable care while significantly reducing required clinician time. These findings highlight immense potential technology scale effective healthcare, address unmet need, ultimately impact quality life economic burden globally.

Язык: Английский

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