Evidence map›Paper›PMID 37353578›Full record

ReviewNPJ digital medicine2023

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

Ben Singh, Timothy Olds, Jacinta Brinsley, Dot Dumuid, Rosa Virgara, Lisa Matricciani, Amanda Watson, Kimberley Szeto, Emily Eglitis, Aaron Miatke and 3 more

Registry-linked trialAbstract readReview
In one paragraph

Review in NPJ digital medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06845007 (PROMBot), which is not on this map. Cited by 110 papers, 10 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
110citing papers in PubMed, 10 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT06845007 completednot on this mapstarted 2025, after this paper: background citation

PROMBot: A Web Platform for Collecting Patient-Reported Outcome Measures Via a Chatbot

TypeobservationalSponsorAna Rita LondralRan2025 to 2025Enrolled24ConditionsHypertension
3 · Its place in the literature

Who cites it

110 citing papers in PubMed, 10 syntheses or guidelines pooled it.

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50 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Ben SinghAlliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia. Ben.Singh@unisa.edu.au.ORCID http://orcid.org/0000-0002-7227-2406
Timothy OldsAlliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia.
Jacinta BrinsleyAlliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia.
Dot DumuidAlliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia.
Rosa VirgaraAlliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia.
Lisa MatriccianiAlliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia.
Amanda WatsonAlliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia.ORCID http://orcid.org/0000-0002-9058-3435
Kimberley SzetoAlliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia.ORCID http://orcid.org/0000-0001-9469-9139
Emily EglitisAlliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia.ORCID http://orcid.org/0000-0003-0586-8047
Aaron MiatkeAlliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia.
Catherine E M SimpsonAlliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia.
Corneel VandelanotteSchool of Health, Medical and Applied Sciences, Central Queensland University, Rockhampton, QLD, Australia.
Carol MaherAlliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Identifiers

PMID37353578
PMCPMC10290125

What OpenQuestion holds

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LicenceCC BY
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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.