Development of mini-SSPedi for children 4–7 years of age receiving cancer treatments
Bibliographic record
Abstract
BACKGROUND: The Symptom Screening in Pediatrics Tool (SSPedi) is valid for assessing symptoms in children aged 8-18 years receiving cancer treatments. The objective was to develop a new self-report symptom screening tool for children receiving cancer treatments who are 4-7 years of age (mini-SSPedi), based on SSPedi. METHODS: Respondents were children with cancer or pediatric hematopoietic stem cell transplantation (HSCT) recipients who were 4-7 years of age. We included the same 15 symptoms contained in SSPedi. Using cognitive interviewing, we developed mini-SSPedi in three phases and made decisions based upon respondent understanding. First, we developed questionnaire structure regarding recall period, concept of bother and response option format. Second, we determined wording of each symptom. Third, we evaluated the entire mini-SSPedi instrument for understanding and ease of completion. RESULTS: We enrolled 100 participants in total and included 30, 40 and 30 in each of the three phases. Questionnaire structure was satisfactory with a recall period of "today" and a faces-based 3-point Likert scale. Bother was well-understood. Five symptoms required modification to achieve satisfactory understanding while the remaining 10 SSPedi symptoms did not require modification. Among the last 10 children enrolled, all understood each mini-SSPedi item and none thought mini-SSPedi was hard to complete. CONCLUSION: We developed a symptom screening tool for children with cancer and pediatric HSCT recipients between 4 and 7 years of age that is understandable and easy to complete. Future work will evaluate the psychometric properties of mini-SSPedi and develop an electronic version of the instrument.
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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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".