Examining the health and functioning status of medical laboratory professionals in Ontario, Canada: an exploratory study during the COVID-19 pandemic
Bibliographic record
Abstract
OBJECTIVES: This study aims to explore the overall and specific aspects of the functioning of medical laboratory professionals (MLPs) in Ontario, Canada during the COVID-19 pandemic. DESIGN: A cross-sectional analysis where a questionnaire was used to assess the mental status of MLPs. SETTING: An online questionnaire administered in Ontario, Canada. PARTICIPANTS: 632 MLPs (medical laboratory technologists, technicians and assistants) were included. MAIN OUTCOME MEASURES: We employed the WHO Disability Assessment Schedule V.2.0 (WHODAS V.2.0) Questionnaire to assess functioning/disability and Copenhagen Psychosocial Questionnaire, third edition for psychosocial workplace factors. Multiple regression analysis examined the relationship between overall and specific domain functioning scores and psychosocial workplace factors. RESULTS: Of the total 632 participants, the majority were female gender and Caucasian. It was found that health (β=2.25, p<0.001, CI: 1.77 to 2.73), management of environmental conditions (β=0.65, p<0.001, CI: 0.33 to 0.98), fear of unemployment (β=-0.72, p<0.001, CI: -1.09 to -0.35) and frequency of stress (β=-1.86, p<0.001, CI: -2.33 to -1.40), in addition to bullying exposure (β=0.56, p<0.01, CI: 0.15 to 0.98) and threats of violence exposure (β=0.90, p<0.01, CI: 0.25 to 1.54), significantly decreased functioning overall and within the specific WHODAS V.2.0 functioning domains. CONCLUSION: This study provides preliminary evidence of the overall and specific aspects of functioning among the MLPs during the COVID-19 pandemic. Besides, these findings can support and guide the improvement of workplace practices and policies among MLPs in the future.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".