Community‐based personal support workers' satisfaction with job‐related training at the organization in Ontario, Canada: Implications for future training
Bibliographic record
Abstract
BACKGROUND AND AIMS: Complexity of community-based homecare for older adults has increased significantly in the past decade in Ontario, Canada. Personal support workers (PSWs), who are unregulated and vary in formal education, provide the majority of community homecare work for increasingly complex clients. This paper seeks to understand community-based PSWs' satisfaction with opportunities for job-related training at their employing organization to provide the skills and knowledge to meet the demands of their evolving role. METHODS: Data for this paper are from a cross-sectional survey of 1746 community-based PSWs in Ontario, Canada entitled, "The PSW Health and Safety Matters Survey" www.pswshaveasay.ca. This survey was part of a research project "Keeping Community Based PSWs Safe in a Changing World of Work," funded by the Ontario Ministry of Labour. The data were analyzed using descriptive statistics, correlations, multivariate regression, and thematic analysis. RESULTS: Quantitative analysis revealed most community homecare organizations offer PSWs job-related training to help them retain and update their skills and that PSWs have a moderate level of satisfaction with their job-related training. The analysis revealed that PSWs' satisfaction with organizational training is greater when the organization provides work-related training on challenging tasks, lifting and transferring tasks, and tasks delegated by nurses and supervisors. Data from the open-ended question highlighted seven key themes for desired training by PSWs: safe body mechanics for moving/lifting clients, managing aggression primarily with clients, infection control, CPR/first aid, mental illness, equipment training, and basic health and safety. CONCLUSION: Implications for factors associated with PSWs' satisfaction with opportunities for job-related training are discussed along with recommendations for mitigating variability in education and training to meet the demands of their evolving role.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".