The Psychosocial Work Environment, Employee Mental Health and Organizational Interventions: Improving Research and Practice by Taking a Multilevel Approach
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
Although there have been several calls for incorporating multiple levels of analysis in employee health and well-being research, studies examining the interplay between individual, workgroup, organizational and broader societal factors in relation to employee mental health outcomes remain an exception rather than the norm. At the same time, organizational intervention research and practice also tends to be limited by a single-level focus, omitting potentially important influences at multiple levels of analysis. The aims of this conceptual paper are to help progress our understanding of work-related determinants of employee mental health by the following: (1) providing a rationale for routine multilevel assessment of the psychosocial work environment; (2) discussing how a multilevel perspective can improve related organizational interventions; and (3) highlighting key theoretical and methodological considerations relevant to these aims. We present five recommendations for future research, relating to using appropriate multilevel research designs, justifying group-level constructs, developing group-level measures, expanding investigations to the organizational level and developing multilevel approaches to intervention design, implementation and evaluation. Copyright © 2014 John Wiley & Sons, Ltd.
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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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.010 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| 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