aceModerate evidence
Published recordHealthGood Space
More
Systematic review and meta-analysis of the effectiveness of chatbots on lifestyle behaviours
- Truvace record
- TRV-2026-2756raw data (JSON)
- Version
- v1Published
- First published
- Evidence type
- Systematic review or meta-analysis
- Sources
- 1 sourcePeer-reviewed
- sha256
- 2b70d2196560…check it
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 sl…
The gain
A systematic review and meta-analysis of 19 trials with 3,567 participants found chatbot interventions raised daily steps by 735, fruit and vegetable intake by about 1 serving a day and sleep by 45 minutes a night.
What this doesn’t fix
Over half of the studies (58%) had 75 or fewer participants and most ran six weeks or less with none longer than a year; participants were mostly self-referred and may be more tech-savvy.
Sources
1 on file- npj Digital Medicinedoi:10.1038/s41746-023-00856-1
What the review found when it combined the studies
These are the review’s own pooled results, copied from its abstract. Truvace did not recalculate them.
Moderate-to-vigorous physical activity increase in minutes per week with chatbot interventions
Mean difference 103 (95% CI 48.20 to 159.24)
2 studies · 184 people · search to 1 September 2022
The review’s own words
Meta-analysis using mean differences showed the increase in MVPA was 103 (95% CI = 48.20, 159.24) minutes per week
Total physical activity with chatbot interventions (randomised and pre-post trials)
SMD 0.28 (95% CI 0.16 to 0.40)
10 studies · 1,603 people · search to 1 September 2022
The review’s own words
Meta-analyses of RCTs and pre-post trials showed significant effects of chatbot-based interventions for increasing total physical activity (SMD = 0.28 [95% CI = 0.16, 0.40], 10 studies, 1603 participants, I 2 = 12%, p < 0.01 [Hedge’s g])
Sleep duration with chatbot interventions
SMD 0.44 (95% CI 0.32 to 0.55)
3 studies · 1,184 people · search to 1 September 2022
The review’s own words
Significant increases were observed for sleep duration (SMD = 0.44 [95% CI = 0.32, 0.55], 3 studies, 1184 participants, I 2 = 0%, p < 0.01 [Hedge’s g])
Daily steps with chatbot interventions (randomised and pre-post trials)
SMD 0.28 (95% CI 0.17 to 0.39)
6 studies · 1,276 people · search to 1 September 2022
The review’s own words
daily steps (SMD = 0.28 [95% CI = 0.17, 0.39], 6 studies, 1276 participants, I 2 = 0%, p < 0·01 [Hedge’s g])
Fruit and vegetable consumption with chatbot interventions (randomised and pre-post trials)
SMD 0.59 (95% CI 0.25 to 0.93)
4 studies · 289 people · search to 1 September 2022
The review’s own words
There was a significant effect of chatbot interventions for increasing fruit and vegetable consumption in meta-analyses of RCTs and pre-post studies (SMD = 0.59 [95% CI = 0.25, 0.93], 4 studies, 289 participants, I 2 = 42%, p < 0.01, Fig. 4 )
Daily steps increase with chatbot interventions, mean difference
Mean difference 735 (95% CI 441 to 1029)
6 studies · 1,276 people · search to 1 September 2022
The review’s own words
the increase in daily steps was 735 (95% CI = 441, 1029, p < 0.01 [Hedge’s g]) steps per day
Total physical activity with chatbot interventions in randomised trials only
SMD 0.27 (95% CI 0.07 to 0.46)
6 studies · 641 people · search to 1 September 2022
The review’s own words
Meta-analyses of RCTs showed a significant and consistent effect in favour of chatbot interventions for total physical activity (SMD = 0.27 [95% CI = 0.07, 0.46], 6 studies, 641 participants, I 2 = 14%, p < 0.01 [Hedge’s g])
Sleep quality with chatbot interventions
SMD 0.50 (95% CI 0.09 to 0.90)
4 studies · 1,302 people · search to 1 September 2022
The review’s own words
sleep quality (SMD = 0.50 [95% CI = 0.09, 0.90], 4 studies, 1302 participants, I 2 = 80%, p = 0.02, Fig. 5 )
Moderate-to-vigorous physical activity with chatbot interventions
SMD 0.53 (95% CI 0.24 to 0.83)
2 studies · 184 people · search to 1 September 2022
The review’s own words
MVPA (SMD = 0.53 [95% CI = 0.24, 0.83], 2 studies, 184 participants, I 2 = 0%, p < 0.01 [Hedge’s g])
Sleep duration increase in minutes per night with chatbot interventions
Mean difference 45 (95% CI 33.2 to 56.9)
3 studies · 1,184 people · search to 1 September 2022
The review’s own words
Meta-analyses of sleep duration using mean differences showed the effect equated to an increase in sleep duration by 45 (95% CI = 33.2, 56.9) minutes per night.
Code checks every number above against the review’s text before it is shown. The short labels are an AI model’s reading of that text, so the review’s own sentence sits under each one. A pooled figure is only as strong as the studies behind it. How Truvace uses pooled results
Cite this record
v1Truvace Impact Record TRV-2026-2756, v1: “Systematic review and meta-analysis of the effectiveness of chatbots on lifestyle behaviours.” Truvace, 2026-11-12. /record/TRV-2026-2756 (accessed on the day you copy it). sha256 2b70d2196560280b…
Change history
1 versionEvery change made to this record since it was first published, and why. Nothing has changed since it went up.
Certified into the record
Check this record hasn’t been altered
How to check it yourself, without trusting this page
Download any version from /api/record/TRV-2026-2756 and hash its canonical field yourself, for example with shasum -a 256. You should get its content_hash. Each version’s text also ends with prev:and the hash of the version before it (version 1 points to 64 zeros). If anyone had changed a single character of any version after it was saved, those hashes wouldn’t line up.