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TRUVACE RECORD VERSION
record: TRV-2026-2759
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T17:20:15.226797Z
status: published
lens: g_space
sector: health
headline: Conversational artificial intelligence interventions to support smoking cessation: A systematic review and meta-analysis
dek: Background Conversational artificial intelligence (chatbots and dialogue systems) is an emerging tool for tobacco cessation that has the potential to emulate personalised human support and increase engagement. We aimed to determine the effect of conversational artificial intelligence interventions with or without standard tobacco cessation interventions on tobacco cessation outcomes among adults who smoke, compared to no intervention, placebo intervention or an active comparator. Methods A comprehensive search o…
gain_title: A meta-analysis of three randomised trials found smokers using conversational AI-enhanced cessation interventions were 29% more likely to be abstinent at 6 months than control participants (RR 1.29, 95% CI 1.13 to 1.46).
problem_title: (none)
trace_subject: (none)
gain_reading: A meta-analysis of three randomised trials found smokers using conversational AI-enhanced cessation interventions were 29% more likely to be abstinent at 6 months than control participants (RR 1.29, 95% CI 1.13 to 1.46).
gain_evidence: participants in the conversational artificial intelligence enhanced intervention were significantly more likely to quit smoking at 6-month follow-up compared to control group participants (RR = 1.29, 95% CI (1.13, 1.46), p < 0.001)
problem_reading: (none)
problem_evidence: (none)
quick_read: A systematic review searched six databases in June 2022 and found 819 studies, of which five randomised controlled trials qualified, with a combined 58,796 participants. A pooled analysis of three of them found smokers given conversational AI-enhanced support were 29% more likely to be abstinent at 6 months than controls (RR 1.29, 95% CI 1.13 to 1.46).

The five trials tested chatbots inside smartphone apps (three trials), a social media chatbot (one) and an internet-based avatar (one). The authors say all five studies reported benefits from the conversational AI interventions.

The evidence is still thin. The studies differed in setting, methods, participants and end-points, loss to follow-up was generally high and overall risk of bias was high. The authors call the evidence limited but promising and want better-designed trials that follow standardised reporting guidelines.
limitation: The five trials differed in setting, methods, interventions, participants and end-points, loss to follow-up was generally high and risk of bias was high overall, so the authors urge caution.
tag: Evidence-backed gain
key_points: Six databases were searched in June 2022, yielding 819 studies; five randomised controlled trials published since 2005 met the inclusion criteria. | The five trials had a combined sample of 58,796 adults who smoke. | Three trials used chatbots embedded in smartphone apps, one used a social media chatbot and one used an internet-based avatar. | The primary outcome was sustained abstinence, self-reported or biochemically validated, for at least 6 months. | The pooled risk ratio for quitting at 6 months across three studies was 1.29 (95% CI 1.13 to 1.46, p < 0.001). | Two authors independently extracted data and assessed risk of bias; risk of bias was high overall and loss to follow-up was generally high.
rundown: The review compared conversational AI interventions, alone or alongside standard tobacco cessation support, with no intervention, a placebo or an active comparator. Only randomised controlled trials were eligible, and the primary outcome was abstinence sustained for at least 6 months. Secondary outcomes were point-prevalence abstinence and sustained abstinence of less than 6 months.

Of the five included trials, three were pooled in a random effects meta-analysis of 6-month quitting. Participants in the AI-enhanced arms were significantly more likely to have quit than controls (RR 1.29, p < 0.001). The authors report that every included study found benefits from the AI interventions.

The studies varied widely in setting, methodology, intervention, participants and end-points, producing high heterogeneity. High loss to follow-up and high overall risk of bias mean the results should be read with caution, according to the authors, who call for further randomised trials that follow standardised reporting guidelines.
sources:
- peer_reviewed | DIGITAL HEALTH | https://doi.org/10.1177/20552076231211634 | 2023-01-01
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