Refinement of the Symptom Screening in Pediatrics Tool (SSPedi)
Bibliographic record
Abstract
BACKGROUND: Objective was to evaluate and refine a new instrument for paediatric cancer symptom screening named the Symptom Screening in Pediatrics Tool (SSPedi). METHODS: Respondents were children 8-18 years of age undergoing active cancer treatment and parents of eligible children. Respondents completed SSPedi once and then responded to semi-structured questions. They rated how easy or difficult SSPedi was to complete. For items containing two concepts, we asked respondents whether concepts should remain together or be separated into two questions. We also asked about each item's importance and whether items were missing. Cognitive probing was conducted in children to evaluate their understanding of items and the response scale. After each group of 10 children and 10 parents, responses were reviewed to determine whether modifications were required. Recruitment ceased with the first group of 10 children in which modifications were not required. RESULTS: Thirty children and 20 parents were required to achieve a final version of SSPedi. Fifteen items remain in the final version; the score ranges from 0 to 60. CONCLUSIONS: Using opinions of children with cancer and parents of paediatric cancer patients, we successfully developed a symptom screening tool that is easy to complete, is understandable and demonstrates content validity.
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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 | 0.017 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".