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Chatbots helped more people quit smoking, a review of 13 studies finds
Study title: Effectiveness and Acceptability of Conversational Agents for Smoking Cessation: A Systematic Review and Meta-analysis
- Evidence type
- Systematic review or meta-analysis
- Sample
- n = 8,236
- Sources
- 1 sourcePeer-reviewed
- Published
- 2 min read
- Truvace record
- TRV-2026-2761cite or check it
Study title: Effectiveness and Acceptability of Conversational Agents for Smoking Cessation: A Systematic Review and Meta-analysis
A systematic review and meta-analysis of conversational agents, AI programs that simulate conversation, for smoking cessation found they improved quitting outcomes. Pooling randomized controlled trials that reported abstinence gave an odds ratio of 1.66 (95% CI 1.33 to 2.07, p < .001) favoring the agents over comparison groups.
Read the study abstract
INTRODUCTION: Conversational agents (CAs; computer programs that use artificial intelligence to simulate a conversation with users through natural language) have evolved considerably in recent years to support healthcare by providing autonomous, interactive, and accessible services, making them potentially useful for supporting smoking cessation. We performed a systematic review and meta-analysis to provide an overarching evaluation of their effectiveness and acceptability to inform future development and adopti…
The gain
A systematic review and meta-analysis of randomized trials found people using conversational agents for smoking cessation had 1.66 times the odds of abstinence of comparison groups (95% CI 1.33 to 2.07).
In brief
The search of eight databases yielded 1245 publications. Thirteen studies with a total of 8236 participants were eligible for the review, and six went into the random-effects meta-analyses. All 13 reported positive effects on cessation-related outcomes, and user feedback pointed to high overall acceptability.
The authors call the evidence promising but early. The included studies varied in design and were of mixed quality, evidence of publication bias was found, and the agents often lacked a theoretical foundation, with a clear need for relational communication in future designs.
Main points
- Eight databases were searched, including Medline, EMBASE, PsycInfo, Web of Science, ACM Digital Library and IEEE Xplore, yielding 1245 publications.
- Thirteen studies with a combined 8236 participants were included in the systematic review.
- Six studies were used for random-effects meta-analyses.
- Randomized trials reporting abstinence gave a sample-weighted odds ratio of 1.66 (95% CI 1.33 to 2.07, p < .001) favoring conversational agents.
- All included studies reported positive effects on cessation-related outcomes.
- Narrative synthesis showed overall high acceptability, though user feedback identified some barriers.
- The review is described as the first systematic review of conversational agents for smoking cessation.
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.
Smoking abstinence with conversational agent interventions compared with control groups
Odds ratio 1.66 (95% CI 1.33 to 2.07)
7,625 people
The review’s own words
The sample-weighted odds ratio indicated that CA interventions significantly increased the odds of abstinence compared to control groups (odds ratio = 1.66, 95% CI = 1.33% to 2.07%, p < .001) (see Figure 2 ).
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
The full story
The review covered studies of conversational agents, computer programs that use artificial intelligence to simulate conversation through natural language, used to support people trying to quit smoking. Searches ran across eight databases spanning health, psychology, computing and communication literature.
Of 1245 publications found, 13 studies met the criteria for the systematic review and six supported random-effects meta-analyses. The headline result came from randomized controlled trials reporting abstinence, with an odds ratio of 1.66 favoring the agents.
The authors flag weaknesses in the evidence base: diverse designs, mixed quality, publication bias and little theoretical grounding. They call for standardized reporting and design of agents, and for relational communication in future versions.
Sources
1 on file- Nicotine and Tobacco Researchdoi:10.1093/ntr/ntac281
Talk it over
Who gets this benefit, and who was left out of the study or story?
Chatbots helped more people quit smoking, a review of 13 studies findshttps://truvace.com/item/effectiveness-and-acceptability-of-conversational-agents-for-smoking-cessation-a
Who gets this benefit, and who was left out of the study or story?
The gain A systematic review and meta-analysis of randomized trials found people using conversational agents for smoking cessation had 1.66 times the odds of abstinence of comparison groups (95% CI 1.33 to 2.07).
Answer in the threadHow do we know? What can this kind of evidence show, and what can’t it?
The evidence This rests on a systematic review or meta-analysis with a sample of 8,236, from Nicotine and Tobacco Research.
Answer in the threadWhat does it leave open? What else would you want to know before acting on it?
The record’s own caveat The included studies were diverse in design with mixed quality, evidence of publication bias was identified, and the authors say reporting and agent design need standardization for a more comprehensive evaluation.
Answer in the threadHave you seen AI used this way where you study, work or live? Did it go the same way?
Answer in the thread
The questions are the same on every record. The details under them are taken from this record as written.
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