Mixed Methods Analysis of Unprompted Participant Text Messages in an Automated Text Message Program for Smoking Cessation Induction

Clicks: 24
ID: 327480
2026
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #101 of 170 articles by views in nicotine & tobacco research : official journal of the society for research on nicotine and tobacco

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 170 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Abstract Introduction Text messaging programs are effective for smoking cessation. Unprompted, participant-initiated text messages that are unrecognized by rules-based programs (UNRs) provide real-time reactions and feedback regarding program experiences. This mixed methods study characterizes UNRs and examines their prospective relationship with treatment outcome. Methods This is a secondary analysis of a randomized controlled cessation induction trial with adult smokers in a 4-week text message program. UNRs were defined as participant-initiated text messages not matching pre-defined expected responses or not in answer to pre-programmed queries. UNRs were qualitatively coded (if not related to a study payment issue or question) and analyzed for associations with participant and program characteristics as well as outcomes (use of evidence-based treatments [EBTs] for cessation and 7-day point prevalence abstinence from smoking). Results Participants (n=440; mean age = 47.5, 47.4% female, 16.9% motivated to quit) sent 2,264 UNRs (1,785 met criteria for coding) and 59.8% sent > 1 UNR. Sending any UNR or any codable UNR predicted greater odds of EBT use during the 7-month study period (self-reported and objectively verified, all ORs > 1.50). Sending any codable UNR (OR = 1.91 [1.09–3.33]) or a UNR acknowledging a program-initiated text (OR = 2.00 [1.18–3.37]) predicted greater odds of self-reported smoking abstinence during the follow-up. Sending a UNR conveying updates on target behaviors predicted greater odds of biochemically verified abstinence during follow-up (OR = 3.05 [1.24–7.46]). Conclusions UNRs may serve as markers of meaningful engagement and early indicators of subsequent behavioral outcomes in text messaging programs.
Reference Key
openalex_W7207733255 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Belinda Borrelli, Romano Endrighi, Gavin N. Rackoff, Madeline S. Goodman, Nicholas J. Hart, M Marianne Jurasic, Howard Cabral
Are you one of these authors? Claim your profile
Journal nicotine & tobacco research : official journal of the society for research on nicotine and tobacco
Year 2026
DOI
10.1093/ntr/ntag199
URL
https://doi.org/10.1093/ntr/ntag199
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.