Measuring change in psychiatric symptoms using the Neuropsychiatric Inventory: Nursing Home version
Bibliographic record
Abstract
BACKGROUND: The Neuropsychiatric Inventory-Nursing Home version (NPI-NH) is a modified version of the Neuropsychiatric Inventory (NPI). Accurate interpretation of change in the symptom ratings on the NPI-NH, as with any measure, is a concern for both clinicians and researchers. The purpose of this article is to present data for the interpretation of reliable change in the NPI-NH scores for acute geriatric neuropsychiatry patients. METHOD: Fifty-two geriatric psychiatry inpatients were administered the NPI-NH twice, at a 72-hour interval. Standard errors of difference scores were used to calculate confidence intervals for each of the NPI-NH subscales and the total score. RESULTS: Based on the calculations described above, estimates of reliable change on the individual subscales ranged from plus or minus 1.29 points on the Euphoria/Elation subscale to 5.13 points on the Anxiety subscale. Statistically meaningful change on the Agitation and the Apathy subscales was established at 4.0 and 4.3 points, respectively. A change in the total score of plus or minus 22 points is required to exceed the possible range of measurement error, at a 0.80 confidence interval (CI). CONCLUSIONS: Overall, the results of this study indicate that the clinician evaluating elderly psychiatric inpatients should interpret a change in the total score of less than 22 points with caution, because it may be due to measurement error.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".