Knowledge and practice of solid healthcare waste management among waste handlers in hospitals in Southern Ghana: a qualitative study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Despite Ghana's healthcare waste management guidelines, improper solid waste management remains a public health concern. This study sought to assess the knowledge, and practices of waste handlers involved in solid healthcare waste management in selected health facilities in Accra, Ghana. METHODS: This study employed a descriptive phenomenology study design. All 31 waste handlers from Korle Bu Teaching Hospital, Tema General Hospital, and Shai-Osudoku Hospital participated in this study. We employed a focus group discussion guide, transcribed the audio-recorded interviews, and then uploaded the data into NVivo 14 software for coding. We synthesized the output into themes, sub-themes, and verbatim quotes to support the sub-themes. RESULTS: The waste handlers were able to describe the different types of healthcare waste, but they were unable to label the colour codes according to the national colours used to identify the waste as hazardous or non-hazardous. In many cases, there was no attempt at managing infectious and sharp wastes, which resulted in needle pricks, falls, or even injuries due to poor transport systems. Most of the waste handlers lacked infection-fighting vaccinations. CONCLUSIONS: For effective healthcare waste management, which heavily relies on waste handlers, it is essential to improve personal protective equipment, vaccinations, colour-coded containers, and a supply of disinfectants/soap to prevent infections. Hospital administrators must receive training on the importance of these logistics to streamline the work of waste handlers and promote public health.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it