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

Yi Tang Chu; Ru Yi Huang; Tara Tai Wen Chen; Wei Hsuan Lin; James Tao Qian Tang; Chi Wei Lin; Chi Hsien Huang; Chung Ying Lin; Jung Sheng Chen; Sabrina Kurtz-Rossi; Kristine Sørensen

doi:10.1177/20552076221136372

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

Yi Tang Chu, Ru Yi Huang, Tara Tai Wen Chen, Wei Hsuan Lin, James Tao Qian Tang, Chi Wei Lin, Chi Hsien Huang, Chung Ying Lin, Jung Sheng Chen, Sabrina Kurtz-Rossi, Kristine Sørensen

Institute of Allied Health Sciences

Research output: Contribution to journal › Article › peer-review

4 Citations (Scopus)

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.

Original language	English
Journal	Digital Health
Volume	8
DOIs	https://doi.org/10.1177/20552076221136372
Publication status	Published - 2022

All Science Journal Classification (ASJC) codes

Health Policy
Health Informatics
Computer Science Applications
Health Information Management

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Chu, Y. T., Huang, R. Y., Chen, T. T. W., Lin, W. H., Tang, J. T. Q., Lin, C. W., Huang, C. H., Lin, C. Y., Chen, J. S., Kurtz-Rossi, S., & Sørensen, K. (2022). 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. Digital Health, 8. https://doi.org/10.1177/20552076221136372

@article{d2e374e3191e4162b9a35d3363a567c2,

title = "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",

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.",

author = "Chu, {Yi Tang} and Huang, {Ru Yi} and Chen, {Tara Tai Wen} and Lin, {Wei Hsuan} and Tang, {James Tao Qian} and Lin, {Chi Wei} and Huang, {Chi Hsien} and Lin, {Chung Ying} and Chen, {Jung Sheng} and Sabrina Kurtz-Rossi and Kristine S{\o}rensen",

note = "Funding Information: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the EDA Center of Medical Artificial Intelligence (grant number EDAH-AI-107-013) and E-Da Healthcare Group (EDAHM109006). Funding Information: The authors would like to thank Dr Jian-Han Chen, chief of the E-Da Hospital Metabolism and Diabetes Surgery Center for assistance in implementing this project; Yi-Chen Lee, chief of E-Da Hospital Department of Clinical Nutrition Therapy for offering nutrition recommendations; Chia-Wei Liu, family medicine physician for proofreading. The authors would also like to thank all the colleagues of E-Da Center of Medical Artificial Intelligence who provided the funding for this project. The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the EDA Center of Medical Artificial Intelligence (grant number EDAH-AI-107-013) and E-Da Healthcare Group (EDAHM109006). Publisher Copyright: {\textcopyright} The Author(s) 2022.",

year = "2022",

doi = "10.1177/20552076221136372",

language = "English",

volume = "8",

journal = "Digital Health",

issn = "2055-2076",

publisher = "SAGE Publications Inc.",

}

Chu, YT, Huang, RY, Chen, TTW, Lin, WH, Tang, JTQ, Lin, CW, Huang, CH, Lin, CY, Chen, JS, Kurtz-Rossi, S & Sørensen, K 2022, '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', Digital Health, vol. 8. https://doi.org/10.1177/20552076221136372

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. / Chu, Yi Tang; Huang, Ru Yi; Chen, Tara Tai Wen et al.
In: Digital Health, Vol. 8, 2022.

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - 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

AU - Chu, Yi Tang

AU - Huang, Ru Yi

AU - Chen, Tara Tai Wen

AU - Lin, Wei Hsuan

AU - Tang, James Tao Qian

AU - Lin, Chi Wei

AU - Huang, Chi Hsien

AU - Lin, Chung Ying

AU - Chen, Jung Sheng

AU - Kurtz-Rossi, Sabrina

AU - Sørensen, Kristine

N1 - Funding Information: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the EDA Center of Medical Artificial Intelligence (grant number EDAH-AI-107-013) and E-Da Healthcare Group (EDAHM109006). Funding Information: The authors would like to thank Dr Jian-Han Chen, chief of the E-Da Hospital Metabolism and Diabetes Surgery Center for assistance in implementing this project; Yi-Chen Lee, chief of E-Da Hospital Department of Clinical Nutrition Therapy for offering nutrition recommendations; Chia-Wei Liu, family medicine physician for proofreading. The authors would also like to thank all the colleagues of E-Da Center of Medical Artificial Intelligence who provided the funding for this project. The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the EDA Center of Medical Artificial Intelligence (grant number EDAH-AI-107-013) and E-Da Healthcare Group (EDAHM109006). Publisher Copyright: © The Author(s) 2022.

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

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ER -

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

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