Promoting remote workers' psychological health: Effective management practices during the COVID‐19 crisis
Bibliographic record
Abstract
Abstract The aim of this study was to identify specific management practices that promote the psychological health of remote workers in the context of the COVID‐19 crisis. A two‐round Delphi study was conducted among 28 teleworkers and 22 managers. A list of 60 specific management practices was presented and participants had to identify whether each one could be used in the current remote working context and, if so, how useful it was to promote psychological health at work. Results indicate that most specific management practices usually used in a face‐to‐face setting can also be used in a remote context (85%). Practices that show consideration, establishing work structure, and allowing flexibility were also identified as the most useful to promote remote workers' psychological health during the pandemic. This study contributes to the advancement of knowledge about specific management practices, remote working, and crisis management. It also suggests specific practices that managers can adopt to promote the psychological health of their employees during a period of crisis, even while managing from a distance.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".