Baseline nutrition risk as measured by SCREEN-8 predicts self-reported 12-month healthcare service use of older adults 3 years later
Bibliographic record
Abstract
This study investigated whether nutrition risk, as measured by SCREEN-8 at baseline, was associated with self-reported healthcare service use in the past 12 months among community-dwelling older adults who were interviewed 3 years later. Data from the Canadian Longitudinal Study on Aging were used. SCREEN-8 assessed nutrition risk among community-dwelling persons ages 55+. Multivariable logistic regression determined if baseline SCREEN-8 score was associated with the following healthcare services reported to occur in the 12 months preceding the 3-year follow-up period: (i) overnight hospital admission ( n = 13 623), (ii) emergency room visit ( n = 13 614), (iii) contacting a family doctor ( n = 13 616), (iv) visiting dental professional ( n = 13 288), and (v) visiting a doctor due to an infection ( n = 13 171) after adjusting for demographic and health variables. Those with higher SCREEN-8 scores (lower nutrition risk) had significantly lower odds of reporting: (i) an overnight hospital admission (χ2 (27, 13 587) = 10.59, p < 0.001); (ii) visiting a hospital emergency room (χ2 (27, 13 578) = 9.64, p < 0.001); and (iii) visiting a doctor due to an infection (χ2 (27, 13 135) = 10.32, p < 0.001) at 3-year follow-up. Less nutrition risk was significantly associated with higher odds of reporting visiting a dental professional (χ2 (27, 13 252) = 17.88, p < 0.001). Baseline nutrition risk was not significantly associated with visiting a family doctor at the 3-year follow-up. SCREEN-8 predicted future self-reported 12-month healthcare service use among older adults in expected directions.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".