Perceptions of health workers regarding the occupational health services rendered at Onandjokwe hospital, Namibia
Bibliographic record
Abstract
Objective: Health care workers are exposed to a variety of health hazards in their daily work. This exposure puts them at risk of acquiring occupational related diseases, including psychological stress, which can lead to mental illness, absenteeism and job dissatisfaction. In view of the potential risks and occupational hazard, a comprehensive health and safety programme for all employees is mandatory to minimize injury among the employees and therefore for the institution to fully harness the potential of its employees. The programme should indicate management goals, objectives and policy implementation, as well as responsibility and accountability for each role player. The aim of this study was to determine the challenges facing health workers regarding the occupational health services (OHS) at Onandjokwe Hospital in Northern Namibia. The objectives of the study were to determine the existing situation relating to the OHS rendered at Onandjokwe Hospital and to explore and describe the perceptions of health workers regarding OHS at the hospital.Methods: The study employed both quantitative and qualitative methodology that included the use of a checklist for collection of quantitative data on evidences of practice of OHS in different departments of the hospital; interviews and focus group discussions for collection of the data on the workers’ perception on OHS in the hospital. Epi-info software version 3.5.1 was used to analyses the quantitative data while Tech’s method of qualitative analysis was used for the qualitative data.Results: The study revealed that the provision of OHS in the hospital was extremely limited. Many key documents guiding the provision of effective OHS were found to be lacking in several hospital departments. Limited training had been conducted and as a result, there was low awareness on OHS among the employees in the hospital. Both management and staff cited lack of key personnel to drive the process as an important impediment to strengthening OHS in the hospital.Conclusions: The main recommendations that arose from the research include the need for the hospital management to comply with the guidelines on Occupational health, acquire and avail key guiding documents for occupational health practice in all the departments; provision of necessary resources for OHS including OHS staff and implementation of OHS programme to safeguard the health of the employees.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".