The Mediating Role of Burnout in the Anxiety and Work Engagement Relationship
Bibliographic record
Abstract
Pandemic-related pressures and responsibilities increase the likelihood of burnout for all health care professionals. The consequences of burnout are significant, as it has been linked to high anxiety, increased turnover, decreased employee morale, higher absenteeism, and lower quality of service. To date, most research explores burnout’s relationship with these variables in isolation. This study explores the anxiety, burnout, and employee engagement relationships among community pharmacists during the global pandemic. Pharmacists in the Canadian province of Saskatchewan completed an online questionnaire that asked questions related to their levels of anxiety, burnout, and work engagement among other control variables. The relationships among the variables were explored via SPSS and the moderation and mediation PROCESS macro. The findings suggest that burnout fully mediates the anxiety and employee engagement relationship, suggesting that anxiety alone is not enough to reduce employee engagement. The results confirm burnout’s relationship with anxiety and lack of engagement and provide a more specific understanding of burnout’s antecedents and consequences, offering important insight for academics and practitioners. Due to the positive implications of eliminating burnout and the importance of employee engagement to organisational performance, managers should seek to reduce workplace stress to avoid burnout and disengagement.
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 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 | 0.022 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".