The effectiveness of health care provider physical activity recommendations in cancer survivors: a systematic review and meta-analysis protocol
Bibliographic record
Abstract
BACKGROUND: Cancer survivors face a range of negative physical and psychological effects that can be mitigated by participating in physical activity. Despite this, most do not meet recommended levels. Health care providers may be in a unique position to promote participation in physical activity among cancer survivors. The aim of this systematic review and meta-analysis is to synthesize the findings from randomized controlled trials and controlled clinical trials investigating the effectiveness of health care provider-administered physical activity recommendations on participation in physical activity among cancer survivors. METHODS/DESIGN: Ten electronic databases (CINAHL, CENTRAL, Education Source, EMBASE, LILACS, MEDLINE, OTSeeker, PEDro, PsycINFO, SPORTDiscus) will be searched to identify relevant studies. The electronic searches will be supplemented by scanning the reference lists of relevant articles retrieved during these searches to ensure all potentially relevant studies are identified. Two reviewers will independently screen all titles and abstracts resulting from the searches to identify potentially eligible studies. They will then screen the full-text articles passing the first screen to identify studies for inclusion using predetermined inclusion/exclusion criteria, extract data from studies meeting all criteria, and assess the risk of bias of these studies. Results will be summarized narratively and statistically. DISCUSSION: By summarizing the best available evidence for the effectiveness of health care provider physical activity recommendations for increasing participation in physical activity among cancer survivors, the results of this systematic review and meta-analysis will help determine if making physical activity recommendations effectively changes cancer survivors behaviour. It will also help to identify knowledge gaps and highlight areas in need of additional research.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.101 | 0.126 |
| Meta-epidemiology (narrow) | 0.008 | 0.007 |
| Meta-epidemiology (broad) | 0.025 | 0.032 |
| Bibliometrics | 0.016 | 0.014 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.058 | 0.007 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".