Factors Influencing Post-Occupational-Injury Employment Trajectories of Nurses Aged 50+: A Life-Story Study Protocol (Preprint)
Bibliographic record
Abstract
BACKGROUND The aging of the workforce, particularly among women aged 50 and over, is accompanied by an increase in workforce participation. In the healthcare sector, these aging workers are particularly vulnerable to occupational injuries, such as musculoskeletal disorders and burnout, which can lead to disability. The process of returning to work after an occupational injury is complex, as these workers have to choose between returning to work or opting for retirement. However, the factors determining their choice remain poorly documented, which limits interventions aimed at promoting their reintegration into the workplace or transition to retirement. OBJECTIVE Objective: The aim of this study is to identify the factors that influence the employment trajectories nurses aged 50 and over after an occupational injury. METHODS Methods: We will carry out this study in two complementary stages: stage 1- Qualitative life-story study: we will conduct semi-structured interviews with approximately 20 nurses aged 50 and over who have experienced an occupational injury. Through these interviews, we will explore factors related to various systems: the worker (e.g., health condition, perception of work); the work environment (e.g., demands, schedules); the healthcare system (e.g., accessibility to care, relationships with professionals); and the compensation system (e.g., insurance support). We will analyze the data using a thematic approach. This stage will generate recommendations to support both a smooth return to work and a successful transition to retirement for nurses. Stage 2 - Nominal group: we will organize a nominal group to validate the recommendations developed from Stage 1. We will recruit four groups of four participants, each representing one of the following systems: nurses, healthcare professionals, employers’ representatives, and insurers’ representatives. We will ask three questions to assess the relevance, clarity, and completeness of the recommendations. We will analyze the responses using descriptive statistics and qualitative content analysis. RESULTS Results: Data collection began in June 2025 and is expected to continue for 5 months. CONCLUSIONS Conclusion: The results of this study will make it possible to identify the facilitators and obstacles that influence the employment trajectories of nurses aged 50 and over following an occupational injury, and to formulate concrete recommendations to promote return to work or transition to retirement.
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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 | 0.012 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.036 | 0.010 |
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".