The Brussels Infant and Toddler Stool Scale
Bibliographic record
Abstract
OBJECTIVES: The Bristol Stool Form Scale (BSFS) is inadequate for non-toilet trained children. The Brussels Infant and Toddler Stool Scale (BITSS) was developed, consisting of 7 photographs of diapers containing stools of infants and toddlers. We aimed to evaluate interobserver reliability of stool consistency assessment among parents, nurses, and medical doctors (MDs) using the BITSS. METHODS: In this multicenter cross-sectional study (2016-2017), BITSS photographs were rated according to the BSFS. The reliability of the BITSS was evaluated using the overall proportion of perfect agreement and the linearly weighted κ statistic. RESULTS: A total of 2462 observers participated: 1181 parents (48.0%), 624 nurses (25.3%), and 657 MDs (26.7%). The best-performing BITSS photographs corresponded with BSFS type 7 (87.5%) and type 4 (87.6%), followed by the BITSS photographs representing BSFS type 6 (75.0%), BSFS type 5 (68.0%), BSFS type 1 (64.8%), and BSFS type 3 (64.6%). The weakest performing BITSS photograph corresponded with BSFS type 2 (49.7%). The overall weighted κ-value was 0.72 (95% CI 0.59-0.85; good agreement). Based on these results, photographs were categorized per stool group as hard (BSFS type 1-3), formed (BSFS type 4), loose (BSFS types 5 and 6), or watery (BSFS type 7) stools. According to this new categorization system, correct allocation for each photograph ranged from 83 to 96% (average: 90%). The overall proportion of correct allocations was 72.8%. CONCLUSIONS: BITSS showed good agreement with BSFS. Using the newly categorized BITSS photographs, the BITSS is reliable for the assessment of stools of non-toilet trained children in clinical practice and research. A multilanguage translated version of the BITSS can be downloaded at https://bitss-stoolscale.com/.
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.
How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".