Not Aware or Don’t Dare! The Use and Efficacy of Employer-Sponsored Mental Wellbeing Programs
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
Employee well-being is a matter of significant concern for both workers and organizations. While many organizations implement costly Stress Management Interventions (SMIs) to improve employee well-being, their efforts are limited by debates as to which SMIs (if any) are effective and how “effectiveness” should be evaluated. The lack of research identifying key predictors of awareness and use of different types of SMIs makes it difficult for researchers and practitioners to draw conclusions with respect to SMI efficacy. Our research addresses these gaps in our understanding by using a contextual effects perspective and a large ( n = 1627) sample of employees working in a diversity of jobs within a single organization to identify the key predictors of employee awareness and use of five available SMIs and explore the link between use of these five SMIs and perceived stress. The following conclusions are supported by the findings from this study: (1) the organizational perceived culture is a better predictor of SMI awareness than individual employee attributes or employee well-being, (2) the predictors of SMI awareness are different from those predicting use, (3) employees who would most benefit from access to SMIs are less aware of what organizational benefits are available, and (4) predictions of awareness, use, and efficacy vary depending on SMI type. Using both theory and the results from our research we propose a comprehensive framework that conceptualizes SMI efficacy as a process not an outcome.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it