Evaluation of a Caregiver-Friendly Workplace Program Intervention on the Health of Full-Time Caregiver Employees
Bibliographic record
Abstract
OBJECTIVE: To evaluate effectiveness of a workplace educational intervention at improving health-related outcomes in carer-employees. METHODS: A pre-post test design compared with health of a sample (n = 21) of carer-employees before (T1) and after (T2) a workplace intervention, as well as a final timepoint (T3) 12 months after T1. An aggregate health score was used to measure health and consisted three scales; depression (CES-D), psychosocial (CRA), and self-reported health (SF-12), where higher scores indicated higher frequency of adverse health symptoms. Three random-slope models were created via the linear mixed modeling method (LMM) to illustrate changes in reported health. RESULTS: All three LMM models reported a reduction in participants' health score, particularly between T1 and T2, indicating a decrease in reported adverse health symptoms. CONCLUSION: The intervention was successful in improving the health of carer-employees.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".