Evaluating the Humpty Dumpty Fall Scale
Bibliographic record
Abstract
BACKGROUND: The Humpty Dumpty Falls Prevention Program was developed to address an unmet need to identify pediatric patients at risk of a fall event. PURPOSE: The aim of this study was to evaluate the performance of the Humpty Dumpty Fall Scale-Inpatient (HDFS) across a diverse, international pediatric population. In addition, the characteristics of patients who experienced a fall were analyzed. METHODS: A retrospective, cross-sectional design was used to assess fall risk across 16 hospitals and 2238 pediatric patients. Multiple and simple logistic regressions were performed to evaluate association of individual scale items and total score with falls during hospitalization. Reliability, sensitivity, and specificity of the HDFS were also assessed. RESULTS: Several of the HDFS items were significantly associated with the risk of falls in the pediatric population, but specificity of the tool is a concern to consider for future tool enhancement. CONCLUSIONS: Characteristics for further refinement of the HDFS were identified.
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 | 0.003 | 0.001 |
| 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".