Caregiver Choice and Caregiver Outcomes: A Longitudinal Study of Irish Spousal Dementia Caregivers
Bibliographic record
Abstract
BACKGROUND: The perception of choice in becoming a caregiver may impact on caregiver psychological and physical health. We determined the proportion of spousal dementia caregivers who felt they had a choice, and examined whether lack of choice in taking up the caregiving role and the perceived degree of choice in caregiving predicted caregiver health and wellbeing and care-recipient placement in long-term care at 1-year follow-up. METHODS: We performed secondary analyses of data from DeStress, a longitudinal study of 251 spousal dementia caregivers in Ireland. We used multivariate logistic and linear regression analyses to examine whether lack of choice (a dichotomous item) and/or the perceived degree of choice (a 9-point scale) at baseline predicted caregiver health (number of chronic health conditions; self-reported health) and wellbeing (e.g., burden, anxiety, depression, stress, and positive aspects of caregiving) and care status (continued care at home or placement in long-term care) at follow-up. RESULTS: = 3.22; Median = 9; Mode = 9), indicating they provided care voluntarily. Caregivers who reported a greater degree of choice were more likely to still be providing care at home at follow-up and to identify benefits from providing care. Neither choice nor degree of choice predicted any other caregiver outcomes. CONCLUSION: For the vast majority of spousal dementia caregivers, taking up the caregiving role is not perceived as a choice; yet, most report performing this role voluntarily. Thus, facilitating greater choice may not necessarily diminish the key contribution family caregivers make to the care system. Although we found no evidence that caregiver choice predicted more positive caregiver health and wellbeing, the perception of choice is important in and of itself, and may benefit caregivers by facilitating the identification of positive aspects of care and be a factor in delaying care-recipient placement in long-term care. Future research should be especially mindful of how caregiver choice is assessed and how this may affect the resulting prevalence of choice.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".