Development of a Symptom Score for Dysfunctional Elimination Syndrome
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: Dysfunctional elimination syndrome is a heterogeneous syndrome with no widely accepted diagnostic criteria. Previously developed questionnaires provide incomplete psychometric assessment. We developed a discriminative questionnaire for diagnosing dysfunctional elimination syndrome and assessed its validity and reliability. MATERIALS AND METHODS: A 14-item 5-point Likert scale questionnaire was devised using literature review, expert opinions and patient input. The questionnaire was administered to 62 children 4 to 16 years old (median age 8) clinically diagnosed with dysfunctional elimination syndrome by a pediatric urologist, of whom 71% were female. It was also administered to 50 healthy controls 4 to 16 years old (median age 7), of whom 66% were female. Children with structural abnormalities were excluded from study. To assess reliability 50 participants were asked to complete the questionnaire again 1 week later. RESULTS: Median total score in cases and controls was 14 of 52 (range 4 to 30) and 6 of 52 (range 1 to 13), respectively. The difference was statistically significant (p = 0.001). Discriminant function analysis showed 80% accuracy. ROC curve showed a score of 11 as the optimum threshold with an AUC of 0.903 (95% CI 0.814-0.948). Test-retest reliability was 84.5% (p = 0.001). Factor analysis showed unloading on 4 factors, corresponding to urinary incontinence, urgency, obstructive symptoms and constipation/fecal soiling. Of participants 85% classified the questionnaire as very easy or easy to complete. CONCLUSIONS: This new questionnaire is valid and reliable for diagnosing dysfunctional elimination syndrome. It can be used as a clinical or research instrument.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it