The influence of facility design and human resource management on health care professionals
Bibliographic record
Abstract
BACKGROUND: Cost control of health care services is a strategic concern for organizations. To lower costs, some organizations reduce staffing levels. However, this may not be worth the trade-off, as the quality of services will likely be reduced, morale among health care providers tends to suffer, and patient satisfaction is likely to decline. PURPOSE: The potential synergy between human resource management and facility design and operation was investigated to achieve the goal of providing cost containment strategies without sacrificing the quality of services and the commitment of employees. METHODOLOGY: About 700 health care professionals from 10 acute-care hospitals participated in this cross-sectional study. The authors used structural equation modeling to test whether employees' evaluations of their physical work environment and human resource practices were significantly associated with lower job-related anxiety, higher job satisfaction, and higher organizational commitment. FINDINGS: The analysis found that employees' evaluations of their physical work environment and human resource practices influenced their job-related feelings and attitudes. Perceived organizational support mediated this relationship. The study also found a small but positive interaction effect between the physical work environment and human resource practices. The influence of physical work environment was small, mainly because of the high predictive value of human resource practices and strong confounding variables included in the analysis. This study specifically showed the role of facility design in reducing job-related anxiety among caregivers. PRACTICE IMPLICATIONS: Preliminary evidence is provided that facility design can be used as a managerial tool for improving job-related attitudes and feelings of employees and earning their commitment. Providing a healthy and safe work environment can be perceived by employees as an indication that the organization respects them and cares about their well-being, which might be reciprocated with higher levels of motivation and commitment toward the organization.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".