This paper is in the following e-collection/theme issue:

Digital Health Reviews (1315) Artificial Intelligence (1407) Clinical Information and Decision Making (1423) Adoption and Change Management of eHealth Systems (729) Decision Support for Health Professionals (1201)

Published on in Vol 24, No 1 (2022): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/32939, first published .
Perceptions and Needs of Artificial Intelligence in Health Care to Increase Adoption: Scoping Review

Perceptions and Needs of Artificial Intelligence in Health Care to Increase Adoption: Scoping Review

Perceptions and Needs of Artificial Intelligence in Health Care to Increase Adoption: Scoping Review

Authors of this article:

Han Shi Jocelyn Chew1 Author Orcid Image ;   Palakorn Achananuparp2 Author Orcid Image
Article Authors Cited by (69) Tweetations (17) Metrics

Journals

  1. Kwong J, Erdman L, Khondker A, Skreta M, Goldenberg A, McCradden M, Lorenzo A, Rickard M. The silent trial - the bridge between bench-to-bedside clinical AI applications. Frontiers in Digital Health 2022;4 View
  2. Chew H, Li J, Chng S. Improving adult eating behaviours by manipulating time perspective: a systematic review and meta-analysis. Psychology & Health 2024;39(10):1485 View
  3. Sasseville M, Barony Sanchez R, Yameogo A, Bergeron-Drolet L, Bergeron F, Gagnon M. Interactive Conversational Agents for Health Promotion, Prevention, and Care: Protocol for a Mixed Methods Systematic Scoping Review. JMIR Research Protocols 2022;11(10):e40265 View
  4. Chew H, Lim S, Kim G, Kayambu G, So B, Shabbir A, Gao Y. Essential elements of weight loss apps for a multi-ethnic population with high BMI: a qualitative study with practical recommendations. Translational Behavioral Medicine 2023 View
  5. van der Meijden S, de Hond A, Thoral P, Steyerberg E, Kant I, Cinà G, Arbous M. Intensive Care Unit Physicians’ Perspectives on Artificial Intelligence–Based Clinical Decision Support Tools: Preimplementation Survey Study. JMIR Human Factors 2023;10:e39114 View
  6. King H, Wright J, Treanor D, Williams B, Randell R. What Works Where and How for Uptake and Impact of Artificial Intelligence in Pathology: Review of Theories for a Realist Evaluation. Journal of Medical Internet Research 2023;25:e38039 View
  7. Pap I, Oniga S. A Review of Converging Technologies in eHealth Pertaining to Artificial Intelligence. International Journal of Environmental Research and Public Health 2022;19(18):11413 View
  8. Chew H, Gao Y, Shabbir A, Lim S, Geetha K, Kim G, Chong C, Lomanto D, So B. Personal motivation, self-regulation barriers and strategies for weight loss in people with overweight and obesity: a thematic framework analysis. Public Health Nutrition 2022;25(9):2426 View
  9. Morrow E, Zidaru T, Ross F, Mason C, Patel K, Ream M, Stockley R. Artificial intelligence technologies and compassion in healthcare: A systematic scoping review. Frontiers in Psychology 2023;13 View
  10. An R, Shen J, Xiao Y. Applications of Artificial Intelligence to Obesity Research: Scoping Review of Methodologies. Journal of Medical Internet Research 2022;24(12):e40589 View
  11. Chew H, Koh W, Ng J, Tan K. Sustainability of Weight Loss Through Smartphone Apps: Systematic Review and Meta-analysis on Anthropometric, Metabolic, and Dietary Outcomes. Journal of Medical Internet Research 2022;24(9):e40141 View
  12. Guse R, Thiebes S, Hennel P, Rosenkranz C, Sunyaev A. Datenmarktplätze für Künstliche Intelligenz im Gesundheitswesen: Potenziale, Herausforderungen und Strategien zur Bewältigung. HMD Praxis der Wirtschaftsinformatik 2022;59(6):1527 View
  13. Shi J, Wei S, Gao Y, Mei F, Tian J, Zhao Y, Li Z. Global output on artificial intelligence in the field of nursing: A bibliometric analysis and science mapping. Journal of Nursing Scholarship 2023;55(4):853 View
  14. Chew H, Rajasegaran N, Chin Y, Chew W, Kim K. Effectiveness of Combined Health Coaching and Self-Monitoring Apps on Weight-Related Outcomes in People With Overweight and Obesity: Systematic Review and Meta-analysis. Journal of Medical Internet Research 2023;25:e42432 View
  15. Beets B, Newman T, Howell E, Bao L, Yang S. Surveying Public Perceptions of Artificial Intelligence in Health Care in the United States: Systematic Review. Journal of Medical Internet Research 2023;25:e40337 View
  16. Cinalioglu K, Elbaz S, Sekhon K, Su C, Rej S, Sekhon H. Exploring Differential Perceptions of Artificial Intelligence in Health Care Among Younger Versus Older Canadians: Results From the 2021 Canadian Digital Health Survey. Journal of Medical Internet Research 2023;25:e38169 View
  17. Han S. The Contributions of Information and Communications Technology on the Sustainable Development of Artificial Intelligence in the Medical Field. Journal of Innovation and Development 2023;2(2):86 View
  18. Shahsavar Y, Choudhury A. User Intentions to Use ChatGPT for Self-Diagnosis and Health-Related Purposes: Cross-sectional Survey Study. JMIR Human Factors 2023;10:e47564 View
  19. Tong W, Wu S, Cheng M, Huang H, Liang J, Li C, Guo H, He D, Liu Y, Xiao H, Hu H, Ruan S, Li M, Lu M, Wang W. Integration of Artificial Intelligence Decision Aids to Reduce Workload and Enhance Efficiency in Thyroid Nodule Management. JAMA Network Open 2023;6(5):e2313674 View
  20. Hua D, Petrina N, Young N, Cho J, Poon S. Understanding the factors influencing acceptability of AI in medical imaging domains among healthcare professionals: A scoping review. Artificial Intelligence in Medicine 2024;147:102698 View
  21. Vo V, Chen G, Aquino Y, Carter S, Do Q, Woode M. Multi-stakeholder preferences for the use of artificial intelligence in healthcare: A systematic review and thematic analysis. Social Science & Medicine 2023;338:116357 View
  22. van der Vegt A, Scott I, Dermawan K, Schnetler R, Kalke V, Lane P. Implementation frameworks for end-to-end clinical AI: derivation of the SALIENT framework. Journal of the American Medical Informatics Association 2023;30(9):1503 View
  23. Jiao W, Zhang X, D’Souza F. The Economic Value and Clinical Impact of Artificial Intelligence in Healthcare: A Scoping Literature Review. IEEE Access 2023;11:123445 View
  24. Lammons W, Silkens M, Hunter J, Shah S, Stavropoulou C. Centering Public Perceptions on Translating AI Into Clinical Practice: Patient and Public Involvement and Engagement Consultation Focus Group Study. Journal of Medical Internet Research 2023;25:e49303 View
  25. Wang X, Luo R, Liu Y, Chen P, Tao Y, He Y. Revealing the complexity of users’ intention to adopt healthcare chatbots: A mixed-method analysis of antecedent condition configurations. Information Processing & Management 2023;60(5):103444 View
  26. Sallam M, Salim N, Barakat M, Al-Mahzoum K, Al-Tammemi A, Malaeb D, Hallit R, Hallit S. Assessing Health Students' Attitudes and Usage of ChatGPT in Jordan: Validation Study. JMIR Medical Education 2023;9:e48254 View
  27. Durairaj K, Baker O, Bertossi D, Dayan S, Karimi K, Kim R, Most S, Robotti E, Rosengaus F. Artificial Intelligence Versus Expert Plastic Surgeon: Comparative Study Shows ChatGPT “Wins” Rhinoplasty Consultations: Should We Be Worried?. Facial Plastic Surgery & Aesthetic Medicine 2024;26(3):270 View
  28. Kiuchi K, Otsu K, Hayashi Y. Psychological insights into the research and practice of embodied conversational agents, chatbots and social assistive robots: a systematic meta-review. Behaviour & Information Technology 2024;43(15):3696 View
  29. Alanzi T, Alhajri A, Almulhim S, Alharbi S, Alfaifi S, Almarhoun E, Mulla R, Alasafra Z, Alalwan Z, Alnasser F, Almukhtar F, Al Ghadeer F, Amro S, Alodhayb I, Alanzi N. Artificial Intelligence and Patient Autonomy in Obesity Treatment Decisions: An Empirical Study of the Challenges. Cureus 2023 View
  30. Meeus M, Beirnaert C, Mahieu L, Laukens K, Meysman P, Mulder A, Van Laere D. Clinical Decision Support for Improved Neonatal Care: The Development of a Machine Learning Model for the Prediction of Late-onset Sepsis and Necrotizing Enterocolitis. The Journal of Pediatrics 2024;266:113869 View
  31. Zhang W, Di X, Wei G, Geng S, Fu Z, Hong S. Cardiac arrhythmia classification with rejection of ECG recordings based on uncertainty estimation from deep neural networks. Neural Computing and Applications 2024;36(8):4047 View
  32. He X, Zheng X, Ding H. Existing Barriers Faced by and Future Design Recommendations for Direct-to-Consumer Health Care Artificial Intelligence Apps: Scoping Review. Journal of Medical Internet Research 2023;25:e50342 View
  33. Tino C, Becker A, Pereira B, Corrêa L, Soares M, Nascimento-e-Silva D. Ethical, legal, and information management aspects in the context of patient safety. Revista de Gestão e Secretariado 2024;15(1):167 View
  34. Gültekin M, Şahin M. The use of artificial intelligence in mental health services in Turkey: What do mental health professionals think?. Cyberpsychology: Journal of Psychosocial Research on Cyberspace 2024;18(1) View
  35. Chew H, Achananuparp P, Dalakoti M, Chew N, Chin Y, Gao Y, So B, Shabbir A, Peng L, Ngiam K. Public acceptance of using artificial intelligence-assisted weight management apps in high-income southeast Asian adults with overweight and obesity: a cross-sectional study. Frontiers in Nutrition 2024;11 View
  36. Moriniello F, Martí-Testón A, Muñoz A, Silva Jasaui D, Gracia L, Solanes J. Exploring the Relationship between the Coverage of AI in WIRED Magazine and Public Opinion Using Sentiment Analysis. Applied Sciences 2024;14(5):1994 View
  37. Wilkinson L, Dunbar J, Lip G. Clinical Integration of Artificial Intelligence for Breast Imaging. Radiologic Clinics of North America 2024;62(4):703 View
  38. Chew H, Chew N, Loong S, Lim S, Tam W, Chin Y, Chao A, Dimitriadis G, Gao Y, So J, Shabbir A, Ngiam K. Effectiveness of an Artificial Intelligence-Assisted App for Improving Eating Behaviors: Mixed Methods Evaluation. Journal of Medical Internet Research 2024;26:e46036 View
  39. Heredia-Negrón F, Tosado-Rodríguez E, Meléndez-Berrios J, Nieves B, Amaya-Ardila C, Roche-Lima A. Assessing the Impact of AI Education on Hispanic Healthcare Professionals’ Perceptions and Knowledge. Education Sciences 2024;14(4):339 View
  40. Sommer D, Schmidbauer L, Wahl F. Nurses’ perceptions, experience and knowledge regarding artificial intelligence: results from a cross-sectional online survey in Germany. BMC Nursing 2024;23(1) View
  41. Zhang Y, Yang X, Tong W. University Students’ Attitudes Toward ChatGPT Profiles and Their Relation to ChatGPT Intentions. International Journal of Human–Computer Interaction 2024:1 View
  42. Rafiq M, Mazzocato P, Guttmann C, Spaak J, Savage C. Predictive analytics support for complex chronic medical conditions: An experience-based co-design study of physician managers’ needs and preferences. International Journal of Medical Informatics 2024;187:105447 View
  43. Kuziemsky C, Chrimes D, Minshall S, Mannerow M, Lau F. AI Quality Standards in Health Care: Rapid Umbrella Review. Journal of Medical Internet Research 2024;26:e54705 View
  44. Yang Y, Ngai E, Wang L. Resistance to artificial intelligence in health care: Literature review, conceptual framework, and research agenda. Information & Management 2024;61(4):103961 View
  45. Grassini E, Buzzi M, Leporini B, Vozna A. A systematic review of chatbots in inclusive healthcare: insights from the last 5 years. Universal Access in the Information Society 2024 View
  46. Liou J, Vo T. Exploring the Relationships among Factors Influencing Healthcare Chatbot Adoption. Sustainability 2024;16(12):5050 View
  47. Mbonye V, Moodley M, Nyika F. Examining the applicability of the Protection of Personal Information Act in AI-driven environments. South African Journal of Information Management 2024;26(1) View
  48. Danilov S, Matveev G, Babenko A, Shlyakhto E. Model for Predicting the Effect of Sibutramine Therapy in Obesity. Journal of Personalized Medicine 2024;14(8):811 View
  49. Isaac M, Jen-Hui Wang R, Napper L, Marsh J. To err is human: Bias salience can help overcome resistance to medical AI. Computers in Human Behavior 2024;161:108402 View
  50. Sharma N. Use of AI in Pediatric Occupational Therapy: A Review. Rehabilitation Science 2024;9(2):21 View
  51. Fechner R, Pate J. Could Freely Available Artificial Intelligence Chatbots Simulate a Multidisciplinary Workshop to More Efficiently Cogenerate Ideas?. JOSPT Open 2024;2(3):225 View
  52. Hurley M, Lang B, Kostick-Quenet K, Smith J, Blumenthal-Barby J. Patient Consent and The Right to Notice and Explanation of AI Systems Used in Health Care. The American Journal of Bioethics 2024:1 View
  53. Kim T, Yu C, Hinson C, Fung E, Allam O, Nazerali R, Ayyala H. ChatGPT Virtual Assistant for Breast Reconstruction: Assessing Preferences for a Traditional Chatbot versus a Human AI VideoBot. Plastic and Reconstructive Surgery - Global Open 2024;12(10):e6202 View
  54. Beregovykh V, Panteleev V, Shimanovsky N. Polypharmacotherapy: the Use of Artificial Intelligence to Reduce Risk of Adverse Drug Reactions (Review). Annals of the Russian academy of medical sciences 2024;79(4):346 View
  55. Dean T, Seecheran R, Badgett R, Zackula R, Symons J. Perceptions and attitudes toward artificial intelligence among frontline physicians and physicians’ assistants in Kansas: a cross-sectional survey. JAMIA Open 2024;7(4) View
  56. Qin H, Zhu Y, Jiang Y, Luo S, Huang C. Examining the impact of personalization and carefulness in AI-generated health advice: Trust, adoption, and insights in online healthcare consultations experiments. Technology in Society 2024;79:102726 View
  57. Mwogosi A, Mambile C, Shao D, Kibinda N. AI-driven innovations for enhancing mental health care in Tanzania: opportunities and challenges. Mental Health and Social Inclusion 2024 View
  58. Liu F, Chang X, Zhu Q, Huang Y, Li Y, Wang H. Assessing clinical medicine students’ acceptance of large language model: based on technology acceptance model. BMC Medical Education 2024;24(1) View
  59. Hassan N, Slight R, Bimpong K, Bates D, Weiand D, Vellinga A, Morgan G, Slight S. Systematic review to understand users perspectives on AI-enabled decision aids to inform shared decision making. npj Digital Medicine 2024;7(1) View
  60. Rakers M, Mwale D, de Mare L, Chirambo L, Bierling B, Likumbo A, Langton J, Chavannes N, van Os H, Calis J, Dellimore K, Villalobos-Quesada M. Cautiously optimistic: paediatric critical care nurses’ perspectives on data-driven algorithms in low-resource settings—a human-centred design study in Malawi. BMC Global and Public Health 2024;2(1) View

Books/Policy Documents

  1. Eddine Z. Advanced Bioinspiration Methods for Healthcare Standards, Policies, and Reform. View
  2. Nagarathinam A, Chellasamy A, Elangovan N, Rengasamy S. Proceedings of the 2nd International Conference on Emerging Technologies and Intelligent Systems. View
  3. Franklin A, Zhang J. Clinical Decision Support and Beyond. View
  4. Durrah O, Aldhmour F, El-Maghraby L, Chakir A. Engineering Applications of Artificial Intelligence. View
  5. Aliferis C, Simon G. Artificial Intelligence and Machine Learning in Health Care and Medical Sciences. View
  6. Guse R, Thiebes S, Hennel P, Rosenkranz C, Sunyaev A. Digitalisierung der Arbeitswelten. View
  7. Singh B. Physical Health, Mental Health, and Human Well-Being in the Age of AI. View
  8. Singh B, Jermsittiparsert K, Lal S, Arora M. Physical Health, Mental Health, and Human Well-Being in the Age of AI. View