EAP utilization patterns and employee absenteeism: Results of an empirical, 3-year longitudinal study in a national Canadian retail corporation.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite the increasing need for employee assistance program (EAP) providers and human resources (HR) departments to demonstrate outcomes resulting from the availability and use of EAP services, few empirical studies have examined the relationship between EAP utilization and objective organizational outcome measures. This study made use of a unique longitudinal archival data set to examine EAP utilization, the problems for which help was sought, and the relationship of EAP utilization to absenteeism over 3 consecutive years among all EAP-eligible (N 3,448) employees in all locations of a large national Canadian retail store. Patterns of usage were examined by gender and age with a clearly defined EAP utilization statistic. Most frequently, the reasons for help seeking were personal issues, marital/family problems, and (a distant third) work-related issues. Longitudinal hierarchical linear modeling (HLM) was used to examine the differences in yearly absentee hours between EAP users versus non-EAP users. The results showed that EAP users generally had higher rates of absenteeism than nonusers during the year in which EAP was used but (with some exceptions) did not differ from the non-EAP user groups in the year(s) before and after treatment. Implications for consulting psychology are suggested.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it