The Life Satisfaction of Informal Caregivers in Europe: Regime Type, Intersectionality, and Stress Process Factors
Bibliographic record
Abstract
Abstract This research assessed the role of welfare state/family care regimes, intersecting social locations and stress process factors in influencing the life satisfaction of informal caregivers of care recipients with age-related needs or disabilities within a European international context. Empirical analyses were conducted with a sample of informal caregivers residing in Denmark, Sweden, France, Germany, Italy, Greece and the United Kingdom (n=6,007). Ordinary least squares and ordered logit regression models revealed that welfare state/family care regime, intersecting social locations, and stress process factors were independently associated with the life satisfaction of informal caregivers. Furthermore, there was some evidence to suggest that social location and stress process factors intervened in some of the relationships between regime type and life satisfaction. There was also some evidence that stress process factors intervened in the relationships between social location factors and life satisfaction. Overall, the results provide support for integrating welfare state/family care regime type and intersectionality factors into the stress process model as applied to the context of informal caregiving. The results also have policy and practice implications with regards to which social location and stress process factors explain specific disparities in life satisfaction between informal caregivers residing in different welfare state/family care regimes.
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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 | 0.002 | 0.005 |
| 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 | 0.001 |
| 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".