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Background: Digital mental health interventions, such as artificial intelligence (AI) conversational agents, hold promise for improving access to care by innovating therapy and supporting delivery. However, little research exists on patient perspectives regarding AI conversational agents, which is crucial for their successful implementation. This study aimed to fill the gap by exploring patients' perceptions and acceptability of AI conversational agents in mental healthcare.
Methods: Adults with self-reported mild to moderate anxiety were recruited from the UMass Memorial Health system. Participants engaged in semi-structured interviews to discuss their experiences, perceptions, and acceptability of AI conversational agents in mental healthcare. Anxiety levels were assessed using the Generalized Anxiety Disorder scale. Data were collected from December 2022 to February 2023, and three researchers conducted rapid qualitative analysis to identify and synthesize themes.
Results: The sample included 29 adults (ages 19-66), predominantly under age 35, non-Hispanic, White, and female. Participants reported a range of positive and negative experiences with AI conversational agents. Most held positive attitudes towards AI conversational agents, appreciating their utility and potential to increase access to care, yet some also expressed cautious optimism. About half endorsed negative opinions, citing AI's lack of empathy, technical limitations in addressing complex mental health situations, and data privacy concerns. Most participants desired some human involvement in AI-driven therapy and expressed concern about the risk of AI conversational agents being seen as replacements for therapy. A subgroup preferred AI conversational agents for administrative tasks rather than care provision.
Conclusions: AI conversational agents were perceived as useful and beneficial for increasing access to care, but concerns about AI's empathy, capabilities, safety, and human involvement in mental healthcare were prevalent. Future implementation and integration of AI conversational agents should consider patient perspectives to enhance their acceptability and effectiveness.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11826059 | PMC |
http://dx.doi.org/10.3389/fpsyt.2024.1505024 | DOI Listing |
Ren Fail
December 2025
Department of Nephrology, The Affiliated Hospital of Qingdao University, Qingdao, China.
Large language models (LLMs) represent a transformative advance in artificial intelligence, with growing potential to impact chronic kidney disease (CKD) management. CKD is a complex, highly prevalent condition requiring multifaceted care and substantial patient engagement. Recent developments in LLMs-including conversational AI, multimodal integration, and autonomous agents-offer novel opportunities to enhance patient education, streamline clinical documentation, and support decision-making across nephrology practice.
View Article and Find Full Text PDFClin Pediatr (Phila)
September 2025
Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA.
The adolescent mental health crisis is compounded by a shortage of mental health services, which mobile health apps may alleviate. We assessed the feasibility and acceptability of the Wysa app (a commercially available app containing cognitive behavioral therapy-based digital modules and an artificial intelligence-based conversational agent) among 13- to 18-year-old adolescents recruited from a primary care clinic in New York City and online from March to June 2022. We assessed adolescent engagement in the Wysa app over a 3-week period.
View Article and Find Full Text PDFAppl Psychol Health Well Being
October 2025
State Key Laboratory of Cognitive Science and Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.
Background: Young adults face emotional problems in their daily lives. Considering that youth are prevalent among mobile internet users, it would be helpful if functions that can intervene in young people's depression and anxiety can be designed based on short video apps. Large language model (LLM)-based AI conversational agents based on short video apps may play an important role in intervening in young adults' negative emotions.
View Article and Find Full Text PDFPLOS Glob Public Health
September 2025
Centre for Infectious Disease Control, National Institute of Public Health and the Environment (RIVM), Bilthoven, the Netherlands.
The global population of older adults is growing. Older adults are more vulnerable to infectious diseases compared to younger adults. Vaccines are available to protect older adults against several infectious diseases, yet their uptake remains sub-optimal.
View Article and Find Full Text PDFBiomedicines
July 2025
Department of Integrative Translational Sciences, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA.
The RTK-RAS signaling cascade is a central axis in colorectal cancer (CRC) pathogenesis, governing cellular proliferation, survival, and therapeutic resistance. Somatic alterations in key pathway genes-including KRAS, NRAS, BRAF, and EGFR-are pivotal to clinical decision-making in precision oncology. However, the integration of these genomic events with clinical and demographic data remains hindered by fragmented resources and a lack of accessible analytical frameworks.
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