Systematic review of self‐management interventions for older adults with cancer
Bibliographic record
Abstract
AIM: The purpose of this systematic review was to determine the effectiveness of self-management interventions for older adults with cancer and to determine the effective components of said interventions. METHODS: We conducted a systematic review of self-management interventions for older adults (65+) with cancer guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analysis statement. We conducted an exhaustive search of the following databases: Ageline, AMED, ASSIA, CINAHL, Cochrane, Embase, Medline, PsychINFO, and Sociological Abstracts. We assessed for quality using the Cochrane Risk of Bias tool and Down & Black for quasi-experimental studies, with data synthesized in a narrative and tabular format. RESULTS: Sixteen thousand nine hundred and eight-five titles and abstracts were screened, subsequently 452 full-text papers were reviewed by two independent reviewers, of which 13 full-text papers were included in the final review. All self-management interventions included in this review measured Quality of Life; other outcomes included mood, self-care activity, supportive care needs, self-advocacy, pain intensity, and analgesic intake; only one intervention measured frailty. Effective interventions were delivered by a multidisciplinary teams (n = 4), nurses (n = 3), and mental health professionals (n = 1). Self-management core skills most commonly targeted included: problem solving; behavioural self-monitoring and tailoring; and settings goals and action planning. CONCLUSIONS: Global calls to action argue for increased emphasize on self-management but presently, few interventions exist that explicitly target the self-management needs of older adults with cancer. Future work should focus on explicit pathways to support older adults and their caregivers to prepare for and engage in cancer self-management processes and behaviours.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".