Cross-country variations in the caregiver role: evidence from the ENTWINE-iCohort study
Bibliographic record
Abstract
BACKGROUND: Globally, economically developed countries face similar ageing demographics and the challenge of a 'care gap', yet they vary due to different care and formal support systems, and different cultural and societal norms around illness and care. The aim of this exploratory study was to examine cross-country variations in caregiver motivations, willingness, values, meaning in life, illness beliefs, and experiences of wellbeing, gain, health-related quality of life, burden and depression, across 6 European countries and Israel. Cross-country differences in the above-mentioned informal caregiver experiences are rarely described. METHODS: An online survey (ENTWINE-iCohort) was conducted using validated measures wherever possible. This paper utilises data from 879 caregivers and seven countries (Greece, Italy, the Netherlands, Poland, Sweden, the UK, and Israel). RESULTS: No consistent finding supporting the concurrent relationship between caregiver support policies/country culture and caregiver motivations/willingness was found. Caregivers in countries typically characterised by individualist cultures reported lower familism, higher self-enhancement values, and greater perceived illness threat compared to more collectivist countries. Search for meaning was higher in poorer countries than in wealthier countries. Higher negative caregiver experiences (e.g., burden) and lower positive experiences (e.g., wellbeing) were generally observed in countries with underdeveloped caregiver support as compared to countries with more developed formal support systems. CONCLUSIONS: Cross-country variations can be explained to varying degrees by national policies around care (or their absence) and country cultural contexts. The results emphasise the importance of formal support services for achieving positive caregiver experiences, and help inform the development of policies and measures to support caregivers in Europe and Israel.
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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 | 0.019 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".