A randomized clinical trial assessing a pragmatic intervention to improve supportive care for family caregivers of patients with lung cancer
Bibliographic record
Abstract
OBJECTIVE: Family caregivers (FCs) of cancer patients often experience high distress. This randomized clinical trial assessed the feasibility and preliminary effects of an intervention to improve FC supportive care. METHOD: A pragmatic and minimal intervention to improve FC supportive care was developed and pretested with FCs, oncology team, and family physicians to assess its relevance and acceptability. Then, FCs of lung cancer patients were randomized to the intervention or the control group. The intervention included (1) systematic FC distress screening and problem assessment in the first months after their relative cancer diagnosis, and every 2 months after; (2) privileged contact with an oncology nurse to address FC problems, provide emotional support and skills to play their caregiving role; (3) liaison with the family physician of FCs reporting high distress (distress thermometer score ≥4/10) to involve them in the provision of supportive care. Distress, the primary outcome, was measured every 3 months, for 9 months. Secondary outcomes included quality of life, caregiving preparedness, and perceived burden. At the end of their participation, a purposive sample of FC from the experimental group was individually interviewed to assess the intervention usefulness. Content analysis was performed. RESULTS: A total of 109 FCs participated in the trial. FC distress decreased over time, but this reduction was observed in both groups. Similar results were found for secondary outcomes. However, FCs who received the intervention felt better prepared in caregiving than controls (p = 0.05). All 10 interviewed FCs valued the intervention, even though they clearly underused it. Knowing they could contact the oncology nurse served as a security net. SIGNIFICANCE OF RESULTS: Although the intervention was not found effective, some of its aspects were positively perceived by FCs. As many of them experience high distress, an improved intervention should be developed to better support them.
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 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".