“Taking back control together”: Definition of a new intervention designed to support parents confronted with childhood cancer
Bibliographic record
Abstract
Parental distress is a major issue in pediatric oncology. The literature shows that intervention programs aimed at supporting parents are effective in reducing parental distress following their child’s cancer diagnosis. However, most programs bear limitations, most often related to their focus on the individual (rather than the family), and their dissemination possibilities. TAKING BACK CONTROL TOGETHER is an integrative program which was developed to respond to these limitations and take the best of effective existing components. In line with development standards from behavioral medicine (ORBIT model), this 6-sessions program aims to reduce parental distress by reinforcing both Problem Solving Skills Techniques (PSST) in 4 individual sessions and communication within the couple and dyadic coping in 2 sessions with the parent couple. The program was first developed in French-language and is now being adapted in English. Because the program addresses both individual PSST and dyadic coping, it is expected to yield more benefits for parents than existing interventions. After this first phase of definition, the program should be pre-tested for refinement, and pilot-tested. This article aims to present the definition of this program, including handbooks for caregivers and parents, as well as worksheets and electronic resources.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".