Effect of health literacy and shared decision-making on choice of weight-loss plan among overweight or obese participants receiving a prototype artificial intelligence robot intervention facilitating weight-loss management decisions

Author:

Chu Yi-Tang12ORCID,Huang Ru-Yi123ORCID,Chen Tara Tai-Wen2,Lin Wei-Hsuan2ORCID,Tang James TaoQian234ORCID,Lin Chi-Wei23,Huang Chi-Hsien23,Lin Chung-Ying5678,Chen Jung-Sheng9,Kurtz-Rossi Sabrina10,Sørensen Kristine11

Affiliation:

1. Department of Holistic Medicine, E-Da Hospital, Kaohsiung, Taiwan

2. Department of Family and Community Medicine, E-Da Hospital, Kaohsiung, Taiwan

3. School of Medicine, College of Medicine, I-Shou University, Kaohsiung, Taiwan

4. Department of Engineering and System Science, National Tsing Hua University, Hsinchu, Taiwan

5. Institute of Allied Health Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan

6. Department of Occupational Therapy, College of Medicine, National Cheng Kung University, Tainan, Taiwan

7. Biostatistics Consulting Center, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan

8. Department of Public Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan

9. Department of Medical Research, E-Da Hospital, Kaohsiung, Taiwan

10. Department of Public Health & Community Medicine, Tufts University School of Medicine, Boston, MA, USA

11. Global Health Literacy Academy, Risskov, Denmark

Abstract

Implementation of artificial intelligence (AI) in medical decision-making is still in early development. We developed an AI robot intervention prototype with a health literacy-friendly interface that uses interactive voice response (IVR) surveying to assist in decision-making for weight loss. The weight-specific health literacy instrument (WSHLI) and Shared Decision-Making Questionnaire (SDMQ) were used to measure factors influencing weight-loss decisions. Factors associated with participants choosing to lose weight were analyzed using logistic regression, and factors influencing the selection of specific weight-loss plans were examined with one-way analysis of variance. Our study recruited 144 overweight or obese adults (69.4% women, 58.3% with body mass index (BMI) ≥ 24). After interacting with the AI robot, 78% of the study population made the decision to lose weight. SDMQ score was a significant factor positively influencing the decision for weight-loss (odds ratio [OR]: 2.16, 95% confidence interval [CI]: 1.09–4.29, p = 0.027). Individuals who selected self-monitored lifestyle modification (mean ± SD: 11.52 ± 1.95) had significantly higher health literacy than those who selected dietician-assisted plan (9.92 ± 2.30) and physician-guided treatment (9.60 ± 1.52) (both p = 0.001). The study results demonstrated that our prototype AI robot can effectively encourage individuals to make decisions regarding weight management and that both WSHLI and SDMQ scores affect the choice of weight-loss plans.

Funder

EDA Center of Medical Artificial Intelligence

Publisher

SAGE Publications

Subject

Health Information Management,Computer Science Applications,Health Informatics,Health Policy

Reference40 articles.

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