A systematic mixed studies review of health behaviour change interventions in colorectal cancer survivors
Bibliographic record
Abstract
AIMS: To explore available health behaviour change interventions in improving key health behaviours in colorectal cancer survivors and patient perspectives about these interventions. DESIGN: A systematic mixed studies review was conducted. DATA SOURCES: Databases searched included Ovid Medline, Ovid Embase, EBSCO PsychoInfo and EBSCO CINAHL. A grey literature search was also completed using Google Scholar and the TRIP database. Identified studies were published between 2003 - 2018. REVIEW METHODS: A parallel-results convergent synthesis design using narrative syntheses was used. Data analysis was conducted following a process of constant comparison. Quality appraisal was conducted using recognized tools appropriate to different study designs. RESULTS: Sixteen unique studies were identified from an initial search of 354 records. There was a pattern of successful physical activity and dietary change associated with behaviour change interventions of varying intensity, modality and length, but sparse description of intervention content was common. Participants preferred clear explanations of health behaviour importance and for interventions to be administered in sessions either with, or led by, other patients. CONCLUSION: The available evidence tentatively suggests that behaviour change interventions can improve the health behaviours of colorectal cancer survivors. However, more research focused on identifying key intervention elements is needed. Patients indicated clear preferences for specific intervention content and delivery, but further research is needed to allow for the appropriate incorporation of patient preferences into the design of such interventions. IMPACT: This review highlights the potential for interventions to improve health behaviours evidenced to influence short and long-term health outcomes in colorectal cancer survivors. However, the examination of the impact of these interventions and patient perspectives indicated a paucity of research. This is an important finding in demonstrating additional research is necessary to improve the support available to a growing group of patients with complex health needs.
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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 | 0.036 | 0.139 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.012 |
| Bibliometrics | 0.021 | 0.020 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".