Digital smoking therapy showed an early quitting advantage, with later benefit uncertain
Trials comparing digital acceptance and commitment therapy with other active interventions found higher early quit rates. Differences at later follow-ups were not statistically significant, leaving sustained benefit unresolved.
Based on the published abstract. The full paper may contain additional methods, results and limitations.
The 30-second takeaway
Acceptance and commitment therapy, a psychological intervention delivered through technology in these trials, improved early quitting rates compared with active alternatives. Later quit-rate differences were uncertain, and the number of cigarettes smoked daily did not show a statistically significant reduction. The early result therefore does not establish a lasting advantage over other interventions.
The authors identify a limited study pool and a need for more long-term research. The abstract does not describe the active alternatives in detail or provide absolute quit rates, which limits practical interpretation.
What researchers found
Digital acceptance and commitment therapy versus active alternatives
At ≤3 months: risk ratio 1.42, 95% confidence interval 1.07–1.89. This ratio compares quit rates, rather than an absolute percentage-point difference.
Early and later results differed
The pooled early comparison favored the digital therapy. At the later assessments, the estimates remained uncertain rather than demonstrating a clear advantage. Nonsignificant differences also do not prove that the competing interventions worked equally well.
Engagement is a separate outcome
Participants used the digital therapy interventions more, according to a separate pooled measure. Greater intervention use is distinct from sustained smoking cessation. An app-delivered subgroup also favored therapy, but this does not establish superiority over other delivery methods.
The original publication
Effect of technology-based acceptance and commitment therapy for smoking cessation: A systematic review and meta-analysis.
Xia X, Gong C, Li Y et al.
Int J Nurs Stud · 2025
- PubMed ID
- 40633297
- Record checked
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