Thematic Analysis of Smoking Cessation and Future Cessation Interventions for Cancer Survivors: Convenience Sampling Study
Bibliographic record
Abstract
Background: Smoking after a cancer diagnosis has significant health consequences, and there are substantial benefits if cancer survivors cease smoking. However, there are few smoking cessation interventions for cancer survivors that have been effective, and they are highly resource intensive. Thus, novel low resource cessation interventions are needed. One such intervention modality that has not been tested among cancer survivors is using pre-recorded videos to deliver information about skills and resources to achieve smoking cessation. Objective: This study aimed to assess barriers to smoking cessation, interest in a video-based smoking cessation intervention, and video content preferences (eg, topic, video length, age and gender of video presenter, presenter type [peer, medical professional]) among individuals with cancer who smoke cigarettes. Methods: Participants were recruited from a cancer center in the southeast United States that houses an opt-out tobacco treatment program in which tobacco treatment specialists proactively call all patients who have a current smoking status in their medical record. Patients were informed about the study, and their contact information was sent to the study team. Verbal consent was obtained from individuals who were cancer survivors, who were currently smoking, and who agreed to participate; semi-structured qualitative interviews were conducted (n=10). Participants were asked questions about smoking history, previous quit attempts, barriers to quitting smoking, previous experience with and openness to watching videos about quitting smoking, and participant preferences related to video content and presentation. Interviews were transcribed and coded by two reviewers, and a codebook was developed. A thematic analysis was then conducted. Results: Results indicated that all participants had previously tried to quit smoking, but other substance use (5/10; 50%), negative affect (eg, depression [4/10; 40%], anxiety [1/10; 10%], stress [2/10; 20%], and loneliness [1/10; 10%]), the social environment (eg, being around others who smoke [2/10; 20%] and risky social situations [2/10; 20%]), and habits surrounding smoking were significant barriers for cessation. All participants were open to watching smoking cessation videos and expressed a desire to see a peer with lived experience in the videos. Most (8/10; 80%) participants did not have preferences related to the age or gender of video presenters. Many participants had difficulty articulating content preferences for the videos. Conclusions: Cancer survivors who smoke may not be aware of their knowledge gaps related to smoking cessation, and videos may be an acceptable way to provide evidence-based information to fill knowledge gaps.
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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 | 0.032 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".