The early retiree divests the health workforce: a quantitative analysis of early retirement among Canadian Registered Nurses and allied health professionals
Bibliographic record
Abstract
BACKGROUND: Early retirement (before age 65) is the norm among registered nurses (RNs) and allied health professionals (AHPs) employed in Canada's public system. As a country whose population is rapidly aging, it is in Canada's best interest to try and extend the work lives of RNs and AHPs. OBJECTIVES: (1) To test the predictive validity of our conceptual model of early retirement among publicly employed, Canadian RNs and AHPs and (2) to compare, across professions, model fit and factor significance METHODS: We conducted multivariable logistic regression in two data sets, one consisting of 483 retired RNs and the other of 177 retired AHPs. The number of AHP respondents limited our ability to comprehensively test the model. RESULTS: Eighty-five percent of RNs and 77% of AHPs had retired early. (1) Results indicate that 25% of variance in RN early retirement and 19% of variance in AHP early retirement was explained by included variables. (2) Organizational restructuring increased odds of early retirement by more than 100% among RNs and AHPs. Among RNs (but not AHPs), both financial possibility and caregiving responsibilities predicted early retirement at statistically significant levels, while a "desire to stop working" predicted retirement at or after 65 years of age. CONCLUSIONS: Clearly, there is much more to learn about RN and AHP pathways to early retirement. Further research, ideally research exploring the role of workplace characteristics, attitudes, and beliefs towards retirement and work-related factors, could deepen our understanding of the phenomenon of RN/AHP early retirement.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".