Smoking cessation program preferences of individuals with chronic obstructive pulmonary disease: a qualitative study
Bibliographic record
Abstract
AIM: To explore the views of tobacco-smoking chronic obstructive pulmonary disease (COPD) and asthma-COPD overlap (ACO) patients on telehealth-based cessation programs and the role of e-cigarettes as an aid to quit smoking. BACKGROUND: Tobacco smoking accelerates the progression of COPD. Traditional smoking cessation programs often do not entirely address the unique needs of COPD patients, leading to suboptimal effectiveness for this population. This research is aimed at describing the attitudes and preferences of COPD and ACO patients toward innovative, telehealth-based smoking cessation strategies and the potential application of e-cigarettes as a quitting aid. METHODS: A qualitative exploratory approach was adopted in this study, employing both focus groups and individual interviews with English-speaking adults with diagnosed COPD or ACO. Participants included both current smokers (≥ 5 cigarettes/day) and recent ex-smokers (who quit < 12 months ago). Data were systematically coded with iterative reliability checks and subjected to thematic analysis to extract key themes. FINDINGS: A total of 24 individuals participated in this study. The emergent themes were the perceived structure and elements of a successful smoking cessation program, the possible integration of telehealth with digital technologies, and the strategic use of e-cigarettes for smoking reduction or cessation. The participants stressed the importance of both social and professional support in facilitating smoking cessation, expressing a high value for insights provided by ex-smokers serving as mentors. A preference was observed for group settings; however, the need for individualized plans was also highlighted, considering the diverse motivations individuals had to quit smoking. The participants perceived online program delivery as potentially beneficial as it could provide immediate access to support during cravings or withdrawals and was accessible to remote users. Opinions on e-cigarettes were mixed; some participants saw them as a less harmful alternative to conventional smoking, while others were skeptical of their efficacy and safety and called for further research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".