Evaluation of the Efficacy of a Smoking Cessation Intervention for Cervical Cancer Survivors and Women With High-Grade Cervical Dysplasia: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: The prevalence of smoking among cervical cancer survivors is strikingly high, yet no smoking cessation interventions to date have specifically targeted this population. This paper describes the study design, methods, and data analysis plans for a randomized clinical trial designed to evaluate the efficacy of a theoretically and empirically based Motivation And Problem Solving (MAPS) approach for promoting and facilitating smoking cessation among cervical cancer survivors. MAPS is a comprehensive, dynamic, and holistic intervention that incorporates empirically supported cognitive behavioral and social cognitive theory-based treatment strategies within an overarching motivational framework. MAPS is designed to be appropriate for all smokers regardless of their motivation to change and views motivation as dynamically fluctuating from moment to moment throughout the behavior change process. OBJECTIVE: This 2-group randomized controlled trial compares the efficacy of standard treatment to MAPS in facilitating smoking cessation among women with a history of high-grade cervical dysplasia or cervical cancer. METHODS: Participants (N=202) are current smokers with a history of high-grade cervical dysplasia or cervical cancer recruited nationally and randomly assigned to one of two treatment conditions: (1) standard treatment (ST) or (2) MAPS. ST consists of repeated letters referring participants to their state's tobacco cessation quitline, standard self-help materials, and free nicotine replacement therapy when ready to quit. MAPS has all ST components along with 6 proactive telephone counseling sessions delivered over 12 months. The primary outcome is abstinence from tobacco at 18 months. Secondary outcomes include abstinence over time across all assessment points, abstinence at other individual assessment time points, quit attempts, cigarettes per day, and use of state quitlines. Hypothesized treatment mechanisms and cost-effectiveness will also be evaluated. RESULTS: This study was approved by the institutional review boards at the University of Texas MD Anderson Cancer Center, the University of Oklahoma Health Sciences Center, and Moffitt Cancer Center. Participant enrollment concluded at Moffitt Cancer Center in January 2020, and follow-up data collection was completed in July 2021. Data analysis is ongoing. CONCLUSIONS: This study will yield crucial information regarding the efficacy and cost-effectiveness of a MAPS approach for smoking cessation tailored to the specific needs of women with a history of high-grade cervical dysplasia or cervical cancer. Findings indicating that MAPS has substantially greater efficacy than existing evidence-based tobacco cessation treatments would have tremendous public health significance. TRIAL REGISTRATION: ClinicalTrials.gov NCT02157610; https://clinicaltrials.gov/ct2/show/NCT02157610. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/34502.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.057 | 0.054 |
| Meta-epidemiology (narrow) | 0.008 | 0.004 |
| Meta-epidemiology (broad) | 0.014 | 0.008 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.078 | 0.013 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".