Uptake and attrition in couple‐based interventions for cancer: perspectives from the literature
Bibliographic record
Abstract
OBJECTIVE: Recognition that patients and partners are both affected by a cancer diagnosis has led to increased interest in couple-based interventions. Although these interventions show promise for enhancing both patients' and partners' illness adjustment, couples' acceptance of these interventions is not well documented. This review explores these issues as reflected in uptake and attrition rates in published trials. METHODS: A literature search identified 17 manuscripts reporting the uptake and attrition rates of couple-based interventions for couples facing cancer. The uptake (percentage of eligible couples randomised into a trial) and the attrition (percentage of couples who dropped out of a trial) rates were extracted by cancer type, cancer stage, intervention type, intervention focus and intervention delivery method. RESULTS: Uptake and attrition rates ranged from 13.6% to 94.2% and 0% to 49.4%, respectively. Low uptake rates were noted for communication-focused interventions and those requiring both the patient and the partner to participate in the intervention simultaneously. Attrition was also high in the latter group. Uptake rates appeared slightly lower than individual-based interventions (58%-76%), as were attrition rates, although only for late stage cancer (~30% couple-based vs. ~69% individual-based). Common barriers to uptake included accessibility, competing priorities and illness severity. CONCLUSIONS: The couple-based interventions had slightly lower uptake rates than what has been previously reported for individual-based interventions; however, lower attrition suggests patients and partners may be more inclined to complete an intervention when they participate together. The findings support the need to develop strategies to improve the delivery and acceptability of couple-based interventions in clinical practice.
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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 | 0.346 | 0.587 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".