Improving the Well-Being of People With Advanced Cancer and Their Family Caregivers: Protocol for an Effectiveness-Implementation Trial of a Dyadic Digital Health Intervention (FOCUSau)
Bibliographic record
Abstract
Background Advanced cancer significantly impacts patients’ and family caregivers’ quality of life. When patients and caregivers are supported concurrently as a dyad, the well-being of each person is optimized. Family, Outlook, Communication, Uncertainty, Symptom management (FOCUS) is a dyadic, psychoeducational intervention developed in the United States, shown to improve the well-being and quality of life of patients with advanced cancer and their primary caregivers. Originally, a nurse-delivered in-person intervention, FOCUS has been adapted into a self-administered web-based intervention for European delivery. Objective The aims of this study are to (1) adapt FOCUS to the Australian context (FOCUSau); (2) evaluate the effectiveness of FOCUSau in improving the emotional well-being and self-efficacy of patients with advanced cancer and their primary caregiver relative to usual care control group; (3) compare health care use between the intervention and control groups; and (4) assess the acceptability, feasibility, and scalability of FOCUSau in order to inform future maintainable implementation of the intervention within the Australian health care system. Methods FOCUS will be adapted prior to trial commencement, using an iterative stakeholder feedback process to create FOCUSau. To examine the efficacy and cost-effectiveness of FOCUSau and assess its acceptability, feasibility, and scalability, we will undertake a hybrid type 1 implementation study consisting of a phase 3 (clinical effectiveness) trial along with an observational implementation study. Participants will include patients with cancer who are older than 18 years, able to access the internet, and able to identify a primary support person or caregiver who can also be approached for participation. The sample size consists of 173 dyads in each arm (ie, 346 dyads in total). Patient-caregiver dyad data will be collected at 3 time points—baseline (T0) completed prerandomization; first follow-up (T1; N=346) at 12 weeks post baseline; and second follow-up (T2) at 24 weeks post baseline. Results The study was funded in March 2022. Recruitment commenced in July 2024. Conclusions If shown to be effective, this intervention will improve the well-being of patients with advanced cancer and their family caregivers, regardless of their location or current level of health care support. Trial Registration ClinicalTrials.gov NCT06082128; https://clinicaltrials.gov/study/NCT06082128 International Registered Report Identifier (IRRID) PRR1-10.2196/55252
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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 | 0.035 | 0.028 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.063 | 0.010 |
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".