The Sherbrooke Questionnaire predicts use of emergency services
Bibliographic record
Abstract
BACKGROUND: the National Service Framework for Older People mandates the introduction of 'intermediate care services' to reduce emergency admissions to hospital from the population aged 75 years or more. We evaluated the predictive performance of one of the screening instruments used to identify older people who might most benefit from such services. METHODS: using multiple logistic regression, we compared responses to the six-item, self-administered Sherbrooke Questionnaire with subsequent patterns of emergency attendance and admission to hospital among the elderly population of one borough in West London. RESULTS: excess risk of both emergency attendance and admission became significant when two or more risk factors were present, and rose progressively with each additional factor, regardless of their nature. With each additional year of age, risks of emergency attendance and admission to hospital increased by 8% (95% CI = 6-10) and 9% (95% CI = 7-12), respectively. There were also significant independent risks associated with reporting memory problems (typical odds ratio (OR) 1.41, 95% CI = 1.14-1.75) and taking three or more medications (OR 1.65, 95% CI = 1.34-2.02), as well as large risks associated with attendance or admission in the year before screening. CONCLUSION: the Sherbrooke Questionnaire is a good measure of likely need for emergency visits to hospital among the elderly. However, programmes attempting to reduce such events should also take into account the individual's recent history of emergency attendance at hospital.
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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 | 0.000 | 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 | 0.000 | 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".