Supporting a physically active lifestyle in COPD: lessons from the PICk UP study
Bibliographic record
Abstract
Maintaining pulmonary rehabilitation (PR) benefits in people with COPD is challenging due to the difficulties in sustaining a physically active lifestyle. The PICk UP programme ( NCT04223362 ), a personalised community-based physical activity (PA) intervention, proved effectiveness in preventing PA decline six months post-PR. This qualitative study explored how the behavioural change techniques (BCTs) in the PICk UP intervention supported sustained PA engagement. Pre- and post-intervention semi-structured focus groups were conducted with the PICk UP participants. Reflexive thematic analysis was applied, following the “capability, opportunity, motivation, behaviour” (COM-B) framework. We included 15 individuals with COPD (14male, 70±8yrs, FEV157.1±18.1%pp). Participants identified 12 BCTs within the intervention: information about health, feedback on behaviour/ outcome, verbal persuasion, PA habit formation, restructuring of the physical/social environment, action plan, goal setting, problem solving, commitment and social support. These BCTs were categorised into 5 intervention types (education, persuasion, training, environmental restructuring and enablement), which addressed the 6 components that influence behaviour (Figure 1). Collectively, they empowered participants to maintain PA following PR. This study highlights the critical role of targeted BCTs in supporting long-term PA maintenance in individuals with COPD following PR. erj;66/suppl_69/PA2792/F1 F1 F1
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".