O-206 Determinants of e-waste workers’ intention to wear respiratory protective equipment at work in Hong Kong
Bibliographic record
Abstract
a:2:{s:4:"lang";s:2:"en";s:7:"content";s:2085:" Introduction E-waste workers in Hong Kong are exposed to more chemicals because more e-waste needs to be handled locally. However, studies suggested that many e-waste workers are unwilling to wear respiratory protective equipment (RPE) for different reasons. This study aimed to identify the determinants of e-waste workers’ intention to wear RPE in Hong Kong. Material and Methods We recruited 109 e-waste workers from June 2021 to September 2022. A workplace RPE intention scale (WRPIEs) was developed based on validated Robertsen’s RPE behavior intention model and Hong Kong Occupational Safety Culture Index. The WRPIEs was consolidated by exploratory factor analysis and further enhanced by confirmatory factor analysis. Multivariate linear regression was used to test the association between the identified domain factors and the intention to use RPE at work. Results Most of the participants were aged over 40 years (76%), had middle school or below educational degrees (83%), wore RPE (94%) at work, and had increased time of wearing RPE after the Covid-19 pandemic (69%). Four domain factors (containing 17 manifest variables) were confirmed, including ‘subjective norms (SN)’, ‘supportive working conditions (SWC)’, ‘autonomy’, and ‘occupational safety and health’. The enhanced WRPIEs had good indices in internal consistency reliability (Cronbach’s α ranged: 0.78–0.94), good composite reliability (range: 0.79–0.95), and model fit (SRMR=0.05, RMSEA=0.03, CFI=0.99). Among the identified domain factors, SN (β=0.36) and SWC (β=0.30) significantly increased e-waste workers’ intention to wear RPE at the workplace. Conclusions This newly validated WRPIEs scale can help capture Chinese e-waste workers’ intention to wear RPE. Results from this study also suggested that various stakeholders could enhance SN and SWC to facilitate workers’ willingness to wear PPE. (Acknowledgements: GRF/RGC-165056653 & VCDFIII-136366853. Ethics approval: CREC 2020.039; *shelly{at}cuhk.edu.hk) ";}
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.004 | 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".