Stress Related Factors Among Nurses Working in Accident and Emergency in a Selected Federal Government Hospital in South-South Nigeria
Bibliographic record
Abstract
Stress bears a negative effect on nurses’ lives and work which includes relationships, such as family life and social relationship. This is because nurses spend more time by the patients and in the healthcare setting than any other healthcare professional. This study examined the stress related factors among nurses working in Accident and Emergency (A&E) Department of one the federal hospitals in South-south Nigeria. The study had four (4) specific objectives and four (4) hypotheses. The study adopted a descriptive research design. Convenient sampling technique was used to recruit fifty-seven (57) nurses who are currently working or have worked in the A&E unit of the hospital. Data collection was with structured questionnaire aided by two research assistants. Permission was obtained from the ethics committee of the hospital. Findings revealed that 49 (86%) do not observe break during their shift and a further 50 (88%) go home completely exhausted. 54 (95%) of the respondents viewed that the workload in A & E is enormous. Staff shortage accounted for 56 (98.5%) of stressors. 47 (83%) of the perception of stressors from respondents are due to problems in interaction with the administration. The study identified various coping mechanisms nurses adopt to combat stressful shifts. Findings reveals that friends 49 (86%), work associates 54 (92.5%), faith 55 (96.5/%) and personal time alone 56 (98.5%) were sources of coping with the stress. The test of hypothesis showed that positive calculated r-value is greater than the critical r-value of 0.269 at 0.05 alpha level with 55 degree of freedom. Thus, there is a significant relationship between stress-related factors and stress among nurses. Conclusion was based on the findings of this study which was recommended amongst others that hospitals should provide a counsellor through employee assistance programs to help nurses during burnout.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".