Development of a Worry Questionnaire for Nursing Home Residents
Bibliographic record
Abstract
This paper describes a new measure, the Worry Questionnaire for Nursing Home Residents (WQNHR), designed to assess the frequency of specific worries. It was administered to 67 residents. Psychometric evaluation showed an average item-to-total correlation of 0.20 (range = 0.15 to 0.58), an internal consistency estimate of 0.79, and a test-re-test reliability coefficient of 0.80. The WQNHR showed good convergent validity with other measures of worry obtained from residents, good discriminant validity with measures of health, but poor discriminant validity with self-ratings of depression. Psychometric results also indicated that the WQNHR performed better for residents with higher cognitive functioning. In addition, a collateral form (WQNHR-C) was administered to family or friends; however, it was not significantly correlated with the WQNHR. Overall, the WQNHR is a promising screening instrument for assessing worry in nursing home residents.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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".