The push and pull factors related to early retirees’ mental health status: A comparative study between Italy and Spain
Bibliographic record
Abstract
In recent years, early retirement has attracted increasing attention in the literature. Using a larger Italian-Spanish sample, this study examines the push and pull factors related to early retirees' mental health status, as well as the moderating effects of perceived self-efficacy on the relationships between reasons for early retirement and mental health. Analyses revealed that poor retirees' mental health is positively correlated to the push factor Pressure from Employer and negatively related to the pull factor Pursue Own Interests. Thus, mental health status is better for Italian retirees than for their Spanish counterparts. The Italian sample shows that Pursue Own Interests was negatively related to poorer mental health particularly under the low self-efficacy condition. Findings suggest that mental health depends on both the motivating reasons that lead people to retire early and the personal resources available to them to manage this psychosocial transition.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".