Recognizing the Role of ChatGPT in Decision-Making and Recognition of Mental Health Disorders among Entrepreneurs DOI Open Access
Nadia A. Abdelmegeed Abdelwahed

OBM Neurobiology, Journal Year: 2024, Volume and Issue: 08(03), P. 1 - 16

Published: Aug. 19, 2024

Nowadays, mental health disorders have become a significant concern for everyone. There are diverse reasons emanating from the workplace, business, and everyday environment. Therefore, there is current need to use technology detect review their symptoms causes. Accordingly, in this study, researcher attempted recognize ChatGPT’s role decision-making recognition of among Egyptian entrepreneurs. The used quantitative approach study based its findings on 332 valid samples. study's results through path analysis using Analysis Moment Structures (AMOS) confirmed positive effect user perception ChatGPT trust process disorders. On other hand, found negative recognizing study’s demonstrate that hurts This assist development policies improve available digital services, such as or AI, increase societal awareness. Moreover, by providing empirical evidence entrepreneurs developing country context, contribute existing psychology, technology, management literature.

Language: Английский

ChatGPT: perspectives from human–computer interaction and psychology DOI Creative Commons

Jiaxi Liu

Frontiers in Artificial Intelligence, Journal Year: 2024, Volume and Issue: 7

Published: June 18, 2024

The release of GPT-4 has garnered widespread attention across various fields, signaling the impending adoption and application Large Language Models (LLMs). However, previous research predominantly focused on technical principles ChatGPT its social impact, overlooking effects human–computer interaction user psychology. This paper explores multifaceted impacts interaction, psychology, society through a literature review. author investigates ChatGPT’s foundation, including Transformer architecture RLHF (Reinforcement Learning from Human Feedback) process, enabling it to generate human-like responses. In terms studies significant improvements GPT models bring conversational interfaces. analysis extends psychological impacts, weighing potential mimic human empathy support learning against risks reduced interpersonal connections. commercial domains, discusses applications in customer service services, highlighting efficiency challenges such as privacy issues. Finally, offers predictions recommendations for future development directions impact relationships.

Language: Английский

Citations

16
“It happened to be the perfect thing”: experiences of generative AI chatbots for mental health DOI Creative Commons

Steven Siddals,

John Torous, Astrid Coxon

et al.

npj Mental Health Research, Journal Year: 2024, Volume and Issue: 3(1)

Published: Oct. 27, 2024

Abstract The global mental health crisis underscores the need for accessible, effective interventions. Chatbots based on generative artificial intelligence (AI), like ChatGPT, are emerging as novel solutions, but research real-life usage is limited. We interviewed nineteen individuals about their experiences using AI chatbots health. Participants reported high engagement and positive impacts, including better relationships healing from trauma loss. developed four themes: (1) a sense of ‘ emotional sanctuary’ , (2) insightful guidance’ particularly relationships, (3) joy connection ’, (4) comparisons between therapist ’ human therapy. Some themes echoed prior rule-based chatbots, while others seemed to AI. emphasised safety guardrails, human-like memory ability lead therapeutic process. Generative may offer support that feels meaningful users, further needed effectiveness.

Language: Английский

Citations

9
Healthcare professionals and the public sentiment analysis of ChatGPT in clinical practice DOI Creative Commons

Lizhen Lu,

Yueli Zhu,

Jiekai Yang

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 7, 2025

To explore the attitudes of healthcare professionals and public on applying ChatGPT in clinical practice. The successful application practice depends technical performance critically perceptions non-healthcare healthcare. This study has a qualitative design based artificial intelligence. was divided into five steps: data collection, cleaning, validation relevance, sentiment analysis, content analysis using K-means algorithm. comprised 3130 comments amounting to 1,593,650 words. dictionary method showed positive negative emotions such as anger, disgust, fear, sadness, surprise, good, happy emotions. Healthcare prioritized ChatGPT's efficiency but raised ethical accountability concerns, while valued its accessibility emotional support expressed worries about privacy misinformation. Bridging these perspectives by improving reliability, safeguarding privacy, clearly defining role is essential for practical integration

Language: Английский

Citations

1
Exploring the Ethical Challenges of Conversational AI in Mental Health Care: Scoping Review DOI Creative Commons
Mehrdad Rahsepar Meadi, Tomas Sillekens, Suzanne Metselaar

et al.

JMIR Mental Health, Journal Year: 2025, Volume and Issue: 12, P. e60432 - e60432

Published: Feb. 21, 2025

Background Conversational artificial intelligence (CAI) is emerging as a promising digital technology for mental health care. CAI apps, such psychotherapeutic chatbots, are available in app stores, but their use raises ethical concerns. Objective We aimed to provide comprehensive overview of considerations surrounding therapist individuals with issues. Methods conducted systematic search across PubMed, Embase, APA PsycINFO, Web Science, Scopus, the Philosopher’s Index, and ACM Digital Library databases. Our comprised 3 elements: embodied intelligence, ethics, health. defined conversational agent that interacts person uses formulate output. included articles discussing challenges functioning role added additional through snowball searching. English or Dutch. All types were considered except abstracts symposia. Screening eligibility was done by 2 independent researchers (MRM TS AvB). An initial charting form created based on expected revised complemented during process. The divided into themes. When concern occurred more than articles, we identified it distinct theme. Results 101 which 95% (n=96) published 2018 later. Most reviews (n=22, 21.8%) followed commentaries (n=17, 16.8%). following 10 themes distinguished: (1) safety harm (discussed 52/101, 51.5% articles); most common topics within this theme suicidality crisis management, harmful wrong suggestions, risk dependency CAI; (2) explicability, transparency, trust (n=26, 25.7%), including effects “black box” algorithms trust; (3) responsibility accountability (n=31, 30.7%); (4) empathy humanness (n=29, 28.7%); (5) justice (n=41, 40.6%), inequalities due differences literacy; (6) anthropomorphization deception (n=24, 23.8%); (7) autonomy (n=12, 11.9%); (8) effectiveness (n=38, 37.6%); (9) privacy confidentiality (n=62, 61.4%); (10) concerns care workers’ jobs (n=16, 15.8%). Other discussed 9.9% (n=10) articles. Conclusions scoping review has comprehensively covered aspects While certain remain underexplored stakeholders’ perspectives insufficiently represented, study highlights critical areas further research. These include evaluating risks benefits comparison human therapists, determining its appropriate roles therapeutic contexts impact access, addressing accountability. Addressing these gaps can inform normative analysis guide development guidelines responsible

Language: Английский

Citations

1
Beyond text: ChatGPT as an emotional resilience support tool for Gen Z – A sequential explanatory design exploration DOI

K. Kavitha,

V. P. Joshith,

Sonal Sharma

et al.

E-Learning and Digital Media, Journal Year: 2024, Volume and Issue: unknown

Published: June 3, 2024

In the digital era, Artificial Intelligence (AI) has arisen as a revolutionary influence with potential to transform multiple spheres of human life. Chatbots, particularly OpenAI's Chat Generative Pre-trained Transformer (ChatGPT), are increasingly recognised promising tools in diverse aspects, including mental health. This study delves into ChatGPT's effectiveness an emotional resilience support tool specifically for Generation Z (Gen Z), demographic deeply engaged interactions. Employing sequential explanatory design that integrates quantitative and qualitative analyses, research investigates Gen users' perceptions effectiveness, barriers its utilisation, impact on resilience. The findings reveal significant acknowledgement role enhancing well-being notable concerns regarding privacy security. Further, insights underscore significance personalised interactions, nonjudgmental space, active listening characteristics ChatGPT fostering Moreover, identifies key areas improvement, such expanded topic coverage cultural representation. Educational stakeholders health professionals encouraged utilise these integrate other AI tailored frameworks Z.

Language: Английский

Citations

6
ChatGPT vs. sleep disorder specialist responses to common sleep queries: Ratings by experts and laypeople DOI
Jiyoung Kim,

Seo‐Young Lee,

Jee Hyun Kim

et al.

Sleep Health, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 1, 2024

Language: Английский

Citations

5
Use of generative artificial intelligence (AI) in psychiatry and mental health care: a systematic review DOI Creative Commons
Sara Kolding, Robert M. Lundin, Lasse Hansen

et al.

Acta Neuropsychiatrica, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 14

Published: Nov. 11, 2024

Tools based on generative artificial intelligence (AI) such as ChatGPT have the potential to transform modern society, including field of medicine. Due prominent role language in psychiatry, e.g., for diagnostic assessment and psychotherapy, these tools may be particularly useful within this medical field. Therefore, aim study was systematically review literature AI applications psychiatry mental health.

Language: Английский

Citations

5
Preferred Uses of Generative AI Chatbots in Mental Health Care: Exploring Practitioners’ Perspectives (Preprint) DOI

Jessie-Marie Dorothy Goldie,

Simon Dennis,

Lyndsey Hipgrave

et al.

Published: Jan. 9, 2025

BACKGROUND Generative Artificial Intelligence (AI) chatbots have the potential to improve mental health care for practitioners and clients. Evidence demonstrates that AI can assist with tasks such as documentation, research, counselling, therapeutic exercises. However, research examining practitioners’ perspectives is limited. OBJECTIVE Drawing on qualitative quantitative data, this mixed-methods study investigates: (1) different uses of chatbots; (2) their likelihood recommending clients; (3) whether recommendation increases after viewing a demonstration. METHODS Participants were 23 (17 female, 6 male; M age = 39.39, SD 16.20). In forty-five-minute interviews, participants selected three most helpful from 11 options rated clients Likert-scale before 11-minute chatbot RESULTS Binomial tests found Generating Case Notes was at greater-than-chance levels (p .001), while Support Session Planning .863) Identifying Suggesting Literature .096) not. Although 55% (n 12) likely recommend clients, binomial test no significant difference 50% threshold .738). A paired samples t-test increased significantly .002) pre-demonstration post-demonstration. CONCLUSIONS Findings suggest favour administrative are more exposure. This highlights need practitioner education guidelines support safe effective integration in care.

Language: Английский

Citations

0
Evaluating Generative AI in Mental Health: A Systematic Review of Capabilities and Limitations (Preprint) DOI Creative Commons
Liying Wang,

Tanmay Bhanushali,

Zhuoran Huang

et al.

JMIR Mental Health, Journal Year: 2025, Volume and Issue: 12, P. e70014 - e70014

Published: Feb. 18, 2025

Abstract Background The global shortage of mental health professionals, exacerbated by increasing needs post COVID-19, has stimulated growing interest in leveraging large language models to address these challenges. Objectives This systematic review aims evaluate the current capabilities generative artificial intelligence (GenAI) context applications. Methods A comprehensive search across 5 databases yielded 1046 references, which 8 studies met inclusion criteria. included were original research with experimental designs (eg, Turing tests, sociocognitive tasks, trials, or qualitative methods); a focus on GenAI models; and explicit measurement abilities empathy emotional awareness), outcomes, user experience perceived trust empathy). Results studies, published between 2023 2024, primarily evaluated such as ChatGPT-3.5 4.0, Bard, Claude tasks psychoeducation, diagnosis, awareness, clinical interventions. Most used zero-shot prompting human evaluators assess AI responses, using standardized rating scales analysis. However, methods often insufficient fully capture complexity capabilities. reliance single-shot techniques, limited comparisons, task-based assessments isolated from may oversimplify GenAI’s overlook nuances human–artificial interaction, especially applications that require contextual reasoning cultural sensitivity. findings suggest while demonstrate strengths psychoeducation their diagnostic accuracy, competence, ability engage users emotionally remain limited. Users frequently reported concerns about trustworthiness, lack engagement. Conclusions Future could use more sophisticated evaluation methods, few-shot chain-of-thought uncover potential. Longitudinal broader comparisons benchmarks are needed explore effects GenAI-integrated care.

Language: Английский

Citations

0
Transforming Civic Education With ChatGPT to Boost Student Interaction and Social learning in the GenAI Era DOI

Ahmad M. Al Yakin,

Abdur Rasyid, Ali Said Al-Matari

et al.

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 305 - 332

Published: Jan. 10, 2025

To increase social interaction and encourage independent learning in Pancasila citizenship education classes, this project investigates the use of ChatGPT as a new teaching tool. The main goal is to test how well encourages student participation group work different classroom environments. By offering empirical evidence efficacy tool, research adds growing body literature on AI education. We have highlighted importance facilitating interactions self-directed learning, which essential for growth analytical communicative abilities. Educators lawmakers can research's practical insights incorporate tools into school courses improve engagement outcomes. better equip their students face problems digital age, instructors should participate ongoing professional development opportunities learn classroom.

Language: Английский

Citations

0