Chatbot Intervention in Asthma and Obstructive Sleep Apnea: A Systematic Review

Pimnipa Thoumrungroje¹, Austtasit Chainarong², Puthachad Namwaing³, Lapassakarn Pitiruangsit⁴, Yuwares Sittichanbuncha⁵, Chetta Ngamjarus⁶, Kittisak Sawanyawisuth⁷, Bundit Sawunyavisuth¹

Affiliation : ¹ Department of Marketing, Faculty of Business Administration and Accountancy, Khon Kaen University, Khon Kaen, Thailand, ² Faculty of Sport Science, Burapha University, Chonburi, Thailand, ³ Department of Physical Therapy, Khon Kaen Hospital, Khon Kaen, Thailand, ⁴ Physical Therapy Unit, Department of Rehabilitation, Buriram Hospital, Buriram, Thailand, ⁵ Department of Emergency Medicine, Faculty of Medicine, Mahidoll University, Bangkok, Thailand, ⁶ Department of Epidemiology and Biostatistics, Faculty of Public Health, Khon Kaen University, Khon Kaen, Thailand, ⁷ Department of Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand

Objective: Asthma and obstructive sleep apnea (OSA) are two common diseases in clinical practice. Both diseases are treated with devices which may require an intervention by an artificial intelligence such as chatbot. The present study aimed to evaluate if chatbot can be used to improve asthma and OSA management by using a systematic review.
Materials and Methods: The present study was a systematic review conducted on five databases. The inclusion criteria were articles conducted in children or adults, used any types of chatbot regardless of outcomes or study types in asthma and OSA management. Eligible studies were reviewed for study characteristics, outcomes, and biases.
Results: There were 275 articles searched from five databases. Of those, two articles met the inclusion criteria. Both eligible articles were conducted in children with asthma with an age of lower than 15 years. The first study used the kBot, a knowledge-enabled personalized chatbot system. This system monitor medication adherence and track asthma status of children asthmatic patients. The average system usability scale scores by physicians and researchers were 83.13 and 82.81/100, respectively. The second study used the MAX in children with asthma age of 10 and 15 years. Almost all conversations were occurred between patients and the MAX agent (99.5%). The asthma knowledge was significantly increased from 7.73 at baseline to 8.79 at the end of study (p<0.001).
Conclusion: There is limited data of chatbot on asthma and OSA. However, chatbot may be feasible for pediatric asthmatic patients. Further studies on OSA and objective outcomes such as asthma control or CPAP adhere are needed.

DOI:10.35755/jmedassocthai.2023.S01.13741

Keywords : Management; Artificial intelligence; Knowledge; Control

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