Measuring quality of life at work for healthcare and social services workers: A systematic review of available instruments
Bibliographic record
Abstract
Quality of life at work is an important and widely discussed concept in the literature. Several instruments can be used to measure it, but with regard to healthcare and social services, the existing instruments are not well known. A review of available instruments intending to capture the quality of life of healthcare and social services workers (QoLHSSW) is necessary to better assess their working conditions and promote programs/guidelines to improve these conditions. The aim of this study was to identify the existing instruments used in measuring QoLHSSW and explore their characteristics. Particular attention was given to instruments adapted to the province of Quebec, Canada, which enabled the determination of which instruments are adapted for the measurement of QoLHSSW in Quebec and possibly elsewhere. A systematic review of the literature was conducted according to the JBI methodological guide. The articles' selection procedure was performed according to the PRISMA flowchart. The search was conducted up to October 28, 2021, and then updated on January 25, 2023, in four databases: PsycINFO, Medline, Embase, and CINAHL. The selection and extraction were performed independently by two researchers. The analysis of the quality of the studies was performed with the COnsensus-based Standards for the selection of health Measurement Instruments. From a total of 8178 entries, 13 articles corresponding to 13 instruments were selected. Among these instruments, the common aspects that were considered were work conditions, job satisfaction, stress at work, relationship/balance, and career development. Most instruments used a 5-point Likert scale. Various validation methods were used, including reporting Cronbach's alpha for overall scale reliability; factor analysis to test construct validity; different model fit indices to test model superiority; different language comparisons to test cross-cultural validity; and qualitative expert reviews to assess content validity.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".