A web-based intervention to promote physical activity in adolescents and young adults with cystic fibrosis: protocol for a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Regular participation in physical activity by people with cystic fibrosis (CF) promotes positive clinical and health outcomes including reduced rate of decline in lung function, fewer hospitalizations and greater wellbeing. However adherence to exercise and activity programs is low, in part due to the substantial daily therapy burden for young people with CF. Strict infection control requirements limit the role of group exercise programs that are commonly used in other clinical groups. Investigation of methods to promote physical activity in this group has been limited. The Active Online Physical Activity in Cystic fibrosis Trial (ActionPACT) is an assessor-blinded, multi-centre, randomized controlled trial designed to compare the efficacy of a novel web-based program (ActivOnline) compared to usual care in promoting physical activity participation in adolescents and young adults with CF. METHODS: Adolescents and young adults with CF will be recruited on discharge from hospital for a respiratory exacerbation. Participants randomized to the intervention group will have access to a web-based physical activity platform for the 12-week intervention period. ActivOnline allows users to track their physical activity, set goals, and self-monitor progress. All participants in both groups will be provided with standardised information regarding general physical activity recommendations for adolescents and young adults. Outcomes will be assessed by a blinded assessor at baseline, after completion of the intervention, and at 3-months followup. Healthcare utilization will be assessed at 12 months from intervention completion. The primary outcome is change in moderate-to-vigorous physical activity participation measured objectively by accelerometry. Secondary outcomes include aerobic fitness, health-related quality of life, anxiety and depression and sleep quality. DISCUSSION: This trial will establish whether a web-based application can improve physical activity participation more effectively than usual care in the period following hospitalization for a respiratory exacerbation. The web-based application under investigation can be made readily and widely available to all individuals with CF, to support physical activity and exercise participation at a time and location of the user's choosing, regardless of microbiological status. TRIAL REGISTRATION: Clinical trial registered on July 13, 2017 with the Australian and New Zealand Clinical Trials Register at (ACTRN12617001009303).
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".