Translating Evidence‐Based Self‐Management Interventions Using a Stepped‐Care Approach for Patients With Cancer and Their Caregivers: A Pilot Sequential Multiple Assignment Randomized Trial Design
Bibliographic record
Abstract
BACKGROUND: Self-directed interventions are cost-effective for patients with cancer and their family caregivers, but barriers to use can compromise adherence and efficacy. AIM: Pilot a Sequential Multiple Assignment Randomized Trial (SMART) to develop a time-varying dyadic self-management intervention that follows a stepped-care approach in providing different types of guidance to optimize the delivery of Coping-Together, a dyadic self-directed self-management intervention. METHODS: 48 patients with cancer and their caregivers were randomized in Stage 1 to: (a) Coping-Together (included a workbook and 6 booklets) or (b) Coping-Together + lay telephone guidance. At 6 weeks, change in distress level was assessed, and non-responding dyads were re-randomized in Stage 2 to (a) continue with their Stage 1 intervention or (b) be stepped-up. Benchmarks for acceptability, feasibility, and clinical significance (anxiety and quality of life (QOL)) were assessed via surveys and study logs. RESULTS: Feasibility was supported by a low refusal rate at ≤ 30% and < 10% missing data. Men and women were enrolled in at least a 40:60 ratio for caregivers, but less for patients. Recruitment was slow at 1 dyad/week. Acceptability was supported by a low attrition rate (12.5%) and with 87% of participants finding the booklets helpful. Telephone guidance in Stage 1 increased adherence to Coping-Together; however, in Stage 1, participants benefited more from the self-directed format than the guidance. All patients who were stepped-up in Stage 2 benefited from their new assignment; this trend was less clear for caregivers. SIGNIFICANCE: Findings suggest a 3-step approach to dyadic self-management support that warrants further testing. TRIAL REGISTRATION: Clinical Trials Registration #: NCT04255030.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".