Feasibility Randomised Control Trial of OptiMal: A Self-Management Intervention for Cancer Survivors
Bibliographic record
Abstract
Purpose: Cancer survivors can experience symptoms such as fatigue, pain and distress that persist for many months following treatment. These enduring symptoms often impact on participation in self-care activities, returning to school and/or work, and leisure and social activities. Self-management support is increasingly recognised as a core aspect of cancer survivorship care to reduce the impact of persistent symptoms. The purpose of this study was to examine the feasibility and potential effectiveness of a group-based self-management intervention, OptiMal, to improve the physical and psychological health of cancer survivors. OptiMal is a six-week intervention comprising weekly sessions on fatigue, stress and physical activity, diet and effective communication strategies. Methods: A feasibility randomised control trial was undertaken. Individuals up to two years after cancer treatment were randomised to OptiMal or usual care. Feasibility was examined through recruitment and retention metrics. Potential effectiveness was tested through patient-reported outcomes collected at baseline and three months post-intervention. Descriptive and inferential statistics were used to analyse study data. Results: Recruitment for this study was 32.5% (80/246 eligible individuals) with 77.5% retention at three-month follow-up (82.5% for intervention group and 72.5% for control group). Of those who attended the intervention, 19 (73%) attended all OptiMal sessions, indicating high adherence to the intervention. The majority of participants had breast cancer and were between 12 and 24 months post-treatment. The intervention group (n = 29) had statistically significant greater improvements in anxiety (p = 0.04) and health-related quality of life (health index score: p = 0.023, visual analogue score: p = 0.035) at three months post-intervention than the control group. Conclusions: Recruitment and retention in this study was similar to other cancer trials and the high adherence rate indicates that OptiMal is an acceptable self-management intervention for cancer survivors and warrants further investigation. OptiMal is intended to address symptoms reported across different cancer types. However, a limitation of this study was that the majority of participants had breast cancer, and therefore, generalisability of findings cannot be assumed for other cancer types. Future studies of OptiMal therefore need to use different strategies to recruit survivors of other cancer types.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".