Validation of co–Symptom Screening in Pediatrics Tool: a novel dyadic approach to symptom screening in pediatric patients receiving cancer treatment
Bibliographic record
Abstract
BACKGROUND: Co-Symptom Screening in Pediatrics Tool (co-SSPedi) is a dyadic (child-guardian) approach to symptom assessment. Objectives were to evaluate the reliability and validity of co-SSPedi for pediatric patients receiving cancer treatments. METHODS: This multicenter study included dyads of patients aged 4-18 years of age with cancer or undergoing hematopoietic cell transplant and their guardians. Two groups were enrolled. The more symptomatic group included those receiving active treatment for cancer or undergoing hematopoietic cell transplant where patients were in hospital or clinic for 4 consecutive days. The less symptomatic group included those receiving maintenance therapy for acute lymphoblastic leukemia or who had completed cancer treatments. At baseline, all dyads completed co-SSPedi, and guardians completed measures of mucositis, nausea, pain, quality of life, and overall symptoms. In the more symptomatic group, dyads completed co-SSPedi and a global symptom change scale on day 4. RESULTS: There were 501 dyads included: 301 in the more symptomatic group and 200 in the less symptomatic group. Median time to complete co-SSPedi was less than 3 minutes in both groups. Test-retest reliability intraclass correlation coefficient was 0.85 (95% confidence interval [CI] = 0.77 to 0.90). For internal consistency, total co-SSPedi Cronbach alpha was 0.81 (95% CI = 0.78 to 0.83). For known groups validation, mean difference in total co-SSPedi scores between the more symptomatic and less symptomatic groups was 7.8 (95% CI = 6.7 to 8.8; P < .0001). For convergent validation and responsiveness, all hypothesized relationships were demonstrated. CONCLUSIONS: Co-SSPedi is a novel approach to dyadic symptom assessment that is reliable, valid, and responsive in pediatric patients aged 4-18 years.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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".