DEVELOPING A SCALE TO MEASURE NEGLECT SEVERITY: THE HEALTH-RELATED SEVERITY IN ELDER NEGLECT SCALE
Bibliographic record
Abstract
Abstract Caregiver neglect in older persons can vary dramatically in severity, with differential impact on an older adult’s health. Assessing severity is critical for research and clinical practice but has received focus until recently. To address this gap, we developed a scale to describe the health-related severity of elder neglect using an expert consensus method. In development, the experts conceptualized severity as: (1) the level of risk that neglectful behaviors would cause morbidity or mortality and (2) related timeframe. Additionally, the experts recommended that the scale identify risk for future neglect. The scale was designed iteratively, and, after finalization, we assessed face and construct validity. The final scale was found to have validity. It has 5 levels: not present, not present / potential risk, present / mild, present / moderate, present / severe. Each level has a description to guide assessment. For example, present / mild is described as: “caregiving behaviors not optimal, with potential to create morbidity, but low concern for immediate danger,” present / moderate is: “caregiving behaviors with significant potential to create morbidity within the next 4 weeks,” and present / severe is “caregiving behaviors creating immediate danger of morbidity or mortality -- insufficient access to shelter, food, medication – with alternative living situation or ED visit / hospitalization recommended.” The description of not present / potential risk is: “though neglect not currently occurring, factors present that raise concern for future neglect risk.” Assessing neglect severity using this scale may improve understanding of the phenomenon and inform intervention.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.016 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".