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Record W3207279543 · doi:10.1002/cncr.33986

Self‐help smoking cessation intervention for Spanish‐speaking Hispanics/Latinxs in the United States: A randomized controlled trial

2021· article· en· W3207279543 on OpenAlexfundno aff
Vani N. Simmons, Steven K. Sutton, Patricia Medina-Ramírez, Úrsula Martínez, Karen O. Brandon, Margaret M. Byrne, Cathy D. Meade, Lauren R. Meltzer, Thomas H. Brandon

Bibliographic record

VenueCancer · 2021
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsnot available
FundersUniversity at BuffaloUniversity of TorontoMoffitt Cancer CenterFlorida International UniversityFlorida Department of HealthNational Cancer InstituteNational Institutes of HealthYale UniversityPfizerRoswell Park Cancer Institute
KeywordsMedicineAbstinenceConfidence intervalRandomized controlled trialSmoking cessationDemographyOdds ratioLogistic regressionInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Hispanic/Latinx smokers living in the United States face unique challenges in quitting smoking. This study evaluated the efficacy of a culturally relevant, Spanish-language, extended self-help smoking cessation intervention among Hispanic smokers. METHODS: A 2-arm parallel randomized controlled trial was conducted with Hispanic/Latinx smokers living in the United States who preferred health information in Spanish and smoked 5 or more cigarettes per week. Participants were randomly allocated to receive Libre del Cigarrillo (LDC), which consisted of 11 booklets and 9 pamphlets mailed monthly over 18 months, or the usual care (UC), which was a single Spanish-language self-help booklet from the National Cancer Institute. The primary outcome was self-reported 7-day point prevalence smoking abstinence assessed 6, 12, 18, and 24 months after the baseline. Eight prespecified moderators of the intervention were evaluated. Cost-effectiveness was also evaluated. All statistical tests were 2-sided. RESULTS: Data from all participants randomized to LDC (n = 714) or UC (n = 703) were used for analyses after multiple imputation to manage missing data. Generalized estimating equation analyses indicated that LDC abstinence rates were higher (P < .001) across all assessments. Logistic regression analyses revealed that at 24 months, the abstinence rate was greater for LDC (33.1%) than UC (24.3%; odds ratio, 1.54; 95% confidence interval, 1.18-2.02; P = .002). Men exhibited a strong intervention effect at all assessments (P values < .001), whereas the intervention effect for women was observed only at 6 and 12 months (P values < .018). In comparison with UC, the incremental cost per quitter in the LDC arm was $648.43 at 18 months and $683.93 at 24 months. CONCLUSIONS: A culturally relevant, Spanish-language intervention was efficacious and cost-effective for smoking cessation. LAY SUMMARY: Research is needed to develop interventions for ethnic minority smokers. The aim of the current study was to test a Spanish-language adaptation of a validated and easily implemented self-help smoking cessation intervention in a nationwide randomized controlled trial. The findings demonstrated that the intervention produced greater smoking abstinence in comparison with a standard self-help booklet. Participants also were more satisfied with the intervention, and it was cost-effective. Efforts aimed at promoting tobacco abstinence in this underserved population could have significant public health implications, including potential reductions in cancer health disparities associated with tobacco smoking.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.039
GPT teacher head0.345
Teacher spread0.306 · 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 designRandomized trial
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

Citations26
Published2021
Admission routes1
Has abstractyes

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