Approaches to Anti-sedentary Behaviour in Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
Background: Decreasing sedentary behaviour has emerged as a distinct health target in individuals with chronic obstructive pulmonary disease (COPD), but effective approaches to reducing it are unclear. Objective: To explore the perspectives of people with COPD and healthcare professionals on reducing sedentary behaviour in people with COPD, to develop and test a sedentary behaviour reduction intervention for people with COPD, and to examine the feasibility of an alternate exercise modality (dance) to decrease sedentary behaviour for people with COPD. Methods: Two qualitative research studies, informed by the Theoretical Domains Framework, were conducted with 14 people with COPD (Study 1) and 16 healthcare professionals (Study 2). The feasibility of the “Get Up for Your Health” behaviour change reduction intervention, which was informed by the findings from Study 1, was tested in Study 3 using a single group, pre- and post-intervention design, among those with COPD enrolled on a PR program. Study 4 was a single group, pre-and post- study, which involved examining the feasibility of dance as an alternate exercise modality in individuals with COPD. Results: Study 1 revealed a lack of knowledge on the concept of sedentary behaviour among study participants. It identified behavioural determinants that could be targeted for a reduction in sedentary behaviour among people with COPD. Study 2 found that healthcare professionals need more education on sedentary behaviour with information about the determinants of behaviour relating to healthcare professionals targeting a reduction in sedentary behaviour in people with COPD. In study 3, the “Get Up for Your Health” intervention, emerged as being feasible, with an enrolment rate of 75%, a completion rate of 90%, adherence to wearing the activity monitor of 84% and participant satisfaction of 90%. The impact of the intervention on sitting time was unclear. In study 4, a dance program was safe and feasible, with an enrolment rate of 49%, a mean attendance rate of 78%, an absence of adverse events and a high participant satisfaction Conclusion: The current thesis provides important information for future sedentary behaviour research to support people with COPD.
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 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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".