Protocol for mapping psychosocial screening to resources in pediatric oncology: a pilot randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: A pediatric cancer diagnosis and its treatment can have a detrimental effect on the mental health of children and their families. Screening to identify psychosocial risk in families has been recognized as a standard of care in pediatric oncology, but there has been limited clinical application of this standard thus far. A significant impediment to the implementation of psychosocial screening is the dearth of information on how to translate psychosocial screening to clinical practice, and specifically, how to follow-up from screening results. This manuscript aims to describe a protocol of a new intervention examining the feasibility and acceptability of mapping via a Psychosocial Navigator (PSN) psychosocial screening results to specific recommendations of resources for families based on measured risk for psychosocial distress and mental health symptoms. METHODS: The pilot randomized control trial (RCT) consists of dyads of youth (10-17 years) newly diagnosed with cancer and their primary caregiver. This RCT includes two arms (intervention and control group), with each group completing measurements near diagnosis and 1 year later. After the initial assessment, dyads in the intervention group receive monthly screening results and recommendations from the study PSN that are tailored to these results. The patient's primary healthcare team (nurse, social worker, oncologist) also receive the risk, distress, and mental health results as well as the recommendations from the PSN. DISCUSSION: This study addresses a significant barrier to the implementation of psychosocial screening in pediatric oncology: specifically, the limited knowledge of how to follow-up from screening results. Findings from this pilot will inform a future definitive RCT to test the effectiveness of the intervention on patient and family mental health outcomes. This project has implications for enhancing clinical care in pediatric oncology, as well as other pediatric populations. STRENGTHS AND LIMITATIONS OF THIS STUDY: This is the first study of screening and follow-up using a psychosocial navigator. This study involves both patient and caregiver report. The small sample size necessitates a future larger study to investigate the effects of intervention. TRIAL REGISTRATION: NCT04132856 , Registered 10 October 2019-retrospectively registered.
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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 | 0.034 | 0.040 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.079 | 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".