Well-being of professional older adults' caregivers in Alberta's assisted living and long-term care facilities: a cross-sectional study
Bibliographic record
Abstract
For the care need of older adults, long-term care (LTC) and assisted living (AL) facilities are expanding in Alberta, but little is known about the caregivers' well-being. The purpose of the study was to investigate the physical health conditions, mental and emotional health (MEH), health behaviour, stress levels, quality of life (QOL), and turnover and absenteeism (TAA) among professional caregivers in Alberta's LTC and AL facilities.This cross-sectional survey involved 933 conveniently selected caregivers working in Alberta's LTC and AL facilities. Standardised questions were selected from the Canadian Community Health Survey, Patient Health Questionnaire-9, and Short Form-36 QOL survey revalidated and administered to the participants. The new questionnaire was used to assess the caregivers' general health condition (GHC), physical health, health behaviour, stress level, QOL, and TAA. Data were analysed using descriptive statistics, Cronbach alpha, Pearson's correlation, one-way analysis of variance, and multiple linear regression.Of 1385 surveys sent to 39 facilities, 933 valid responses were received (response rate = 67.4%). The majority of the caregivers were females (90.8%) who were ≥ 35 years (73.6%), worked between 20 to 40 h weekly (67.3%), and were satisfied with their GHC (68.1%). The Registered Nurses had better GHC (mean difference [MD] = 0.18, p = 0.004) and higher TAA than the Health Care Aides (MD = 0.24, p = 0.005). There were correlations between caregivers' TAA and each of MEH (r = 0.398), QOL (r = 0.308), and stress (r = 0.251); p < 0.001. The most significant predictors of TAA were the propensity to quit a workplace or the profession, illness, job stress, and work-related injury, F (5, 551) = 76.62, p < 0.001, adjusted R2 = 0.998.Reducing the caregivers' job stressors such as work overload, inflexible schedule, and poor remuneration, and improving their quality of life, health behaviour, and mental, emotional, and physical health conditions may increase their job satisfaction and reduce turnover and absenteeism.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".