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Systematic review and meta-analysis of the effectiveness of chatbots on lifestyle behaviours

Singh, Ben, Olds, Timothy, Brinsley, Jacinta, Dumuid, Dot, Virgara, Rosa, Matricciani, Lisa, Watson, Amanda, Szeto, Kimberley, Eglitis, Emily, Miatke, Aaron, Simpson, Catherine E. M., Vandelanotte, Corneel, Maher, Carol·2023·npj Digital Medicine
DOI 10.1038/s41746-023-00856-1PMC PMC10290125
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Abstract

Chatbots (also known as conversational agents and virtual assistants) offer the potential to deliver healthcare in an efficient, appealing and personalised manner. The purpose of this systematic review and meta-analysis was to evaluate the efficacy of chatbot interventions designed to improve physical activity, diet and sleep. Electronic databases were searched for randomised and non-randomised controlled trials, and pre-post trials that evaluated chatbot interventions targeting physical activity, diet and/or sleep, published before 1 September 2022. Outcomes were total physical activity, steps, moderate-to-vigorous physical activity (MVPA), fruit and vegetable consumption, sleep quality and sleep duration. Standardised mean differences (SMD) were calculated to compare intervention effects. Subgroup analyses were conducted to assess chatbot type, intervention type, duration, output and use of artificial intelligence. Risk of bias was assessed using the Effective Public Health Practice Project Quality Assessment tool. Nineteen trials were included. Sample sizes ranged between 25–958, and mean participant age ranged between 9–71 years. Most interventions ( n = 15, 79%) targeted physical activity, and most trials had a low-quality rating ( n = 14, 74%). Meta-analysis results showed significant effects (all p < 0.05) of chatbots for increasing total physical activity (SMD = 0.28 [95% CI = 0.16, 0.40]), daily steps (SMD = 0.28 [95% CI = 0.17, 0.39]), MVPA (SMD = 0.53 [95% CI = 0.24, 0.83]), fruit and vegetable consumption (SMD = 0.59 [95% CI = 0.25, 0.93]), sleep duration (SMD = 0.44 [95% CI = 0.32, 0.55]) and sleep quality (SMD = 0.50 [95% CI = 0.09, 0.90]). Subgroup analyses showed that text-based, and artificial intelligence chatbots were more efficacious than speech/voice chatbots for fruit and vegetable consumption, and multicomponent interventions were more efficacious than chatbot-only interventions for sleep duration and sleep quality (all p < 0.05). Findings from this systematic review and meta-analysis indicate that chatbot interventions are efficacious for increasing physical activity, fruit and vegetable consumption, sleep duration and sleep quality. Chatbot interventions were efficacious across a range of populations and age groups, with both short- and longer-term interventions, and chatbot only and multicomponent interventions being efficacious.

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Fig. 1 PRISMA flow diagram showing the study selection process.
Fig. 1 PRISMA flow diagram showing the study selection process.CC BY · PubMed Central
Fig. 2 Meta-analysis results of the effect of chatbot interventions on total physical activity, steps and moderate-to-vigorous physical activity (using data from randomised controlled trials and single-group pre-post studies). Note: the meta-analysis of daily steps is a subset of total physical activity using Hedge’s g. 95% CI: 95% Confidence interval.
Fig. 2 Meta-analysis results of the effect of chatbot interventions on total physical activity, steps and moderate-to-vigorous physical activity (using data from randomised controlled trials and single-group pre-post studies). Note: the meta-analysis of daily steps is a subset of total physical activity using Hedge’s g. 95% CI: 95% Confidence interval.CC BY · PubMed Central
Fig. 3 Funnel plot for studies that reported physical activity outcomes. SE (SMD): Standard error (standardized mean difference).
Fig. 3 Funnel plot for studies that reported physical activity outcomes. SE (SMD): Standard error (standardized mean difference).CC BY · PubMed Central
Fig. 4 Forest plot of effect sizes of chatbots on fruit and vegetable consumption at post-intervention. Meta-analysis results of the effect of chatbot interventions on fruit and vegetable consumption (using data from randomised controlled trials and single-group pre-post studies) using Hedge’s g. 95% CI: 95% Confidence interval.
Fig. 4 Forest plot of effect sizes of chatbots on fruit and vegetable consumption at post-intervention. Meta-analysis results of the effect of chatbot interventions on fruit and vegetable consumption (using data from randomised controlled trials and single-group pre-post studies) using Hedge’s g. 95% CI: 95% Confidence interval.CC BY · PubMed Central
Fig. 5 Forest plot of effect sizes of chatbots on sleep duration and sleep quality at post-intervention. Meta-analysis results of the effect of chatbot interventions on sleep duration and sleep quality (using data from randomised controlled trials and single-group pre-post studies) using Hedge’s g. 95% CI: 95% Confidence interval.
Fig. 5 Forest plot of effect sizes of chatbots on sleep duration and sleep quality at post-intervention. Meta-analysis results of the effect of chatbot interventions on sleep duration and sleep quality (using data from randomised controlled trials and single-group pre-post studies) using Hedge’s g. 95% CI: 95% Confidence interval.CC BY · PubMed Central

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Metadata

Authors
Singh, B., Olds, T., Brinsley, J., Dumuid, D., Virgara, R., Matricciani, L., Watson, A., Szeto, K., Eglitis, E., Miatke, A., Simpson, C. E. M., Vandelanotte, C., & Maher, C.
ORCID
Venue
npj Digital Medicine
Publisher
Springer Science and Business Media LLC
Published
2023-06-23
Volume
6
Issue
1
ISSN
2398-6352
DOI
10.1038/s41746-023-00856-1
PMC
PMC10290125
Cited by
224
References
25
Language
en
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