Effectiveness and components of self-management interventions in adult cancer survivors: a protocol for a systematic review and planned meta-analysis
Bibliographic record
Abstract
BACKGROUND: Self-management interventions have been proposed as effective strategies to improve health and well-being and promote optimal coping in cancer survivors. Several reviews have shown benefits of self-management interventions on a variety of patient-reported outcomes. Effective self-management strategies in other chronic disease populations are typically based on theories of behavior change, but the extent of theoretical underpinnings in cancer self-management programs has not been evaluated to date. Our aim is to expand on previous reviews by evaluating the effectiveness of self-management interventions in cancer survivors as well as the theoretical components of such interventions. METHODS: We will conduct a systematic review of self-management interventions for adults who have completed primary treatment for their solid or hematological cancer. Interventions tested using experimental or quasi-experimental methods, with any type of comparator, will be included. A search strategy will be designed with a health sciences librarian and then performed using MEDLINE, EMBASE, PsycINFO, CINAHL, Scopus, the Cochrane database of systematic reviews, the National Institutes of Health clinical trials registry, and the Cochrane CENTRAL registry of controlled trials. Data synthesis will include a narrative and tabular summary of the results. Appropriate statistical analysis may include a meta-analysis using random effects methods to determine the effectiveness of self-management interventions and a meta-regression to evaluate how characteristics of the interventions are associated with the intervention effect. Risk of bias will be evaluated using the Cochrane risk of bias tool or the Risk of Bias in Non-randomized studies tool (RoBANS). DISCUSSION: The results of this systematic review will add to previous reviews and expand the existing knowledge base of the effectiveness and active components of self-management interventions for adult cancer survivors. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42018085300.
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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 | 0.081 | 0.118 |
| Meta-epidemiology (narrow) | 0.008 | 0.005 |
| Meta-epidemiology (broad) | 0.027 | 0.040 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.064 | 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, 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".