Investigating the Paradoxes of Workplace Well-being: A Systematic Literature Review
Bibliographic record
Abstract
Research examining how corporate wellness programs (CWPs) can ease employee stress is on the rise; however, much of existing research neglects the contextual factors that may undermine well-being (WB) or does not fully consider the tension between how WB may compete with outcomes like job performance. Applying Job Demands-Resources (JD-R) and Conservation of Resources (COR) theory, we examine how pursuits of WB may paradoxically be competing with other employee resources in a loss spiral that can outpace gains. We conduct a large-scale systematic literature review of 156 articles using the Covidence software to better understand WB and workplace outcomes, contextual planning and evaluation components of CWPs, and the theory used when examining CWPs. Our review finds that replenishing and adapting resources to offset loss spirals will improve physical and psychological WB under the right context, outcome planning and execution. While CWPs reliably enhance WB, workplace variables did not always yield the same outcome. We propose that part of the paradox may be reconciled by considering how congruent a CWP’s design is with its intended outcomes, most notably job performance and satisfaction. Our review offers theoretical and practical considerations to guide future research aimed at supporting both WB and workplace gains.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.024 | 0.117 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.022 | 0.020 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".