Assessing knowledge, attitude, and practice of healthcare personnel regarding biomedical waste management: a systematic review of available tools
Bibliographic record
Abstract
Biomedical waste (BMW) management is an important commitment of hospitals both in terms of the possible infectious risk and from the financial point of view. Monitoring the knowledge, attitude, and practice (KAP) of healthcare professionals on this topic represents a source of information on BMW management. The aim of this study is to perform a systematic review to identify the reliable and valid tools able to assess the KAP of professionals in healthcare centers to manage BMW. Two databases (PubMed and Scopus) were searched on 10 May 2018 for cross-sectional studies with tools on BWM management, including original research studies from peer-reviewed journals, case studies, and review studies. Information on validation and reliability were collected. Methodological quality was assessed using the Newcastle–Ottawa scale for cross-sectional studies. Fifty-three articles were included, of which 19 presented a questionnaire on BMW for healthcare workers. Nine proposed a validated questionnaire: four reported Cronbach’s alpha, which ranged from 0.62 to 0.86. Results further emphasize the prevalence of Asian studies facing the problem of assessing KAP about BMW management using specific tools. Overall, 14 questionnaires were designed in Asia, two in Africa, one in America, one in Australia, and one questionnaire was elaborated in Europe, in Spain. This systematic review highlighted the need of creation of validated and methodologically high-quality questionnaires. Therefore, there is the need of new cross-sectional studies to investigate these problems, improving generalization, and facilitating international comparison of research findings.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".