‘Walking a tight rope’: an investigation of nurse managers’ work stressors and coping experiences
Bibliographic record
Abstract
Competing demands and a nursing shortage have contributed to a managerial workforce that is overworked and a health care environment that is under constant tension. The short supply and high turnover of manager positions, upwards of 30% in some regions in Canada, have contributed to an unstable work environment. The aim of this study examined the stress experiences and coping strategies of nurse managers in an acute care setting. Semi-structured interviews of five nurse managers were included in this pilot study. Qualitative content analysis was used to analyse the transcribed text. Six descriptive themes related to work stressors were identified: fiscal responsibilities, inadequate human resources, managing others, intrapersonal distress, middle management role and competing priorities. Three descriptive themes related to coping strategies were identified: peer and superior support, cognitive coping strategies and social and personal strategies. Findings indicate that coping mechanisms lessened the work stressors experienced by managers, but it was not always evident managers felt confident in their ability to cope effectively. Senior nurse leaders play an integral role in assuming responsibility for equipping managers with appropriate preparation and support to facilitate their success and to enhance the attractiveness of the manager role to potential recruits.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".