Precarious work among personal support workers in the Greater Toronto Area: a respondent-driven sampling study
Bibliographic record
Abstract
<h3>Background:</h3> The COVID-19 pandemic has highlighted the role of personal support workers (PSWs) in health care, as well as their work conditions. Our study aimed to understand the characteristics of the PSW workforce, their work conditions and their job security, as well as to explore the health of PSWs and the impact of precarious employment on their health. <h3>Methods:</h3> Our community-based participatory action research focused on PSWs in the Greater Toronto Area. We administered an online, cross-sectional survey between June and December 2020 using respondent-driven sampling. Data on sociodemographics, employment precarity, worker empowerment and health status were collected. We assessed the association between precarious employment and health using multivariable logistic regression models. <h3>Results:</h3> We contacted 739 PSWs, and 664 consented to participate. Overall, 658 (99.1%) completed at least part of the survey. Using data adjusted for our sampling approach, the participants were predominantly Black (76.5%, 95% confidence interval [CI] 68.2%–84.9%), women (90.1%, 95% CI 85.1%–95.1%) and born outside of Canada (97.4%, 95% CI 94.9%–99.9%). Most worked in home care (43.9%, 95% CI 35.2%–52.5%) or long-term care (34.5%, 95% CI 27.4%–42.0%). Although most participants had at least some postsecondary education (unadjusted proportion = 83.4%, <i>n</i> = 529), more than half were considered low income (55.1%, 95% CI 46.3%–63.9%). Most participants were precariously employed (86.5%, 95% CI 80.7%–92.4%) and lacked paid sick days (89.5%, 95% CI 85.8%–93.3%) or extended health benefits (74.1%, 95% CI 66.8%–81.4%). Nearly half of the participants described their health as less than very good (46.7%, 95% CI 37.9%–55.5%). Employment precarity was significantly associated with higher risk of depression (odds ratio 1.02, 95% CI 1.01–1.03). <h3>Interpretation:</h3> Despite being key members of health care teams, most PSWs were precariously employed with low wages that keep them in poverty; the poor work conditions they faced could be detrimental to their physical and mental health. Equitable strategies are needed to provide decent work conditions for PSWs and to improve their health.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".