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Record W3182068244 · doi:10.1158/1538-7755.asgcr21-17

Abstract 17: Adaptation and Assessment of a Text Message Cessation Intervention for Tobacco Users in Viet Nam

2021· article· en· W3182068244 on OpenAlexaff
Donna Shelley, Nan Jiang, Charles M. Cleland, Trang Nguyen, Lorien C. Abroms, Nam Nguyen

Bibliographic record

VenueCancer Epidemiology Biomarkers & Prevention · 2021
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsYork University
Fundersnot available
KeywordsSmoking cessationFocus groupVietnameseShort Message ServiceMedicinePsychological interventionIntervention (counseling)Context (archaeology)mHealthPsychologyNursingComputer science

Abstract

fetched live from OpenAlex

Abstract Purpose: Text message (i.e., short message service, SMS) smoking cessation interventions have demonstrated efficacy, but most evaluations were conducted in high-income countries. We assessed the feasibility, acceptability and preliminary efficacy of a smoking cessation SMS intervention adapted to the sociocultural context, language and communication styles of Vietnamese smokers. Methods: Participants were current adult cigarette-only or dual cigarette and waterpipe users. We adapted a message library from two SMS smoking cessation programs with proven efficacy in increasing quit rates in the US. The iterative adaptation process included focus groups with 58 smokers to provide data on culturally relevant patterns of tobacco use and to assess message preferences. We then pilot tested (n=40) a 6-week SMS intervention using brief text surveys to obtain real time feedback on messages and conducted post-test interviews (n=10) to inform further adaptation. Finally, we randomized 100 smokers to the SMS intervention (including bidirectional messages and key words to generate additional support) vs. weekly text assessments of tobacco use. Surveys assessed engagement and acceptability at 6 weeks, cessation at 6 and 12 weeks. Results: Significant modifications were made in terms of content (e.g. preference for negative framing of health risks, and focus on enhancing refusal skills) and tone (e.g., preferences for action-oriented advice for craving management). We found high rates of engagement (e.g. 82% usually or always read messages) and satisfaction with the SMS program (e.g. 70% satisfied, 24% very satisfied). Conclusion: Intervention participants suggested enhancing the program with additional telephone support, extending the length of the program, and adding images and more interactive content. This pilot study provided support for the feasibility and acceptability of culturally-adapted SMS smoking cessation treatment among smokers in Viet Nam. It also showed promising early efficacy in promoting abstinence. Future studies are needed to assess whether, with additional modifications, the program is associated with long-term abstinence. Citation Format: Donna Shelley, Nan Jiang, Charles Cleland, Trang Nguyen, Lorien Abroms, Nam Nguyen. Adaptation and Assessment of a Text Message Cessation Intervention for Tobacco Users in Viet Nam [abstract]. In: Proceedings of the 9th Annual Symposium on Global Cancer Research; Global Cancer Research and Control: Looking Back and Charting a Path Forward; 2021 Mar 10-11. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2021;30(7 Suppl):Abstract nr 17.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.106
GPT teacher head0.432
Teacher spread0.326 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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