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TRUVACE RECORD VERSION
record: TRV-2026-2761
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T17:20:23.907702Z
status: published
lens: g_space
sector: health
headline: Effectiveness and Acceptability of Conversational Agents for Smoking Cessation: A Systematic Review and Meta-analysis
dek: 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…
gain_title: 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).
problem_title: (none)
trace_subject: (none)
gain_reading: 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).
gain_evidence: A meta-analysis with randomized controlled trials reporting on abstinence yielded a sample-weighted odds ratio of 1.66 | favoring CAs over comparison groups
problem_reading: (none)
problem_evidence: (none)
quick_read: 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.

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.
limitation: 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.
tag: Evidence-backed gain
key_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.
rundown: 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:
- peer_reviewed | Nicotine and Tobacco Research | https://doi.org/10.1093/ntr/ntac281 | 2022-12-12
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