The Male Face of Caregiving
Bibliographic record
Abstract
The purpose of this scoping review was to examine the empirical evidence published since 2007 on men as family caregivers of persons with dementia. Searches were conducted on Academic Search Complete, Ageline, CINAHL, Embase, Medline, PsychINFO, Social Work Abstracts, and Web of Science using database-specific controlled (i.e., MeSH terms) vocabulary related to dementia, men, and caregiving. Studies published in English between 2007 and 2012 that provided evidence of the experiences of male family caregivers of persons with dementia were included in the review. A total of 30 articles were selected for inclusion. Studies were grouped into three major themes for review: men's experiences of caregiving, relational factors, and outcomes of caregiving. The reviewed studies build on and support previous findings related to stress, burden, accessing services, and the importance of relational factors to men's caregiving experiences. However, there is a need for a framework that explains these findings in relation to masculinities. Such a framework would provide the necessary unifying context for a more powerful explanatory account. Furthermore, there appears to be the potential for great benefit in fully linking men's caregiver research to men's health issues as a means to articulate strategies to sustain the health and well-being of men caregivers. This seems especially relevant in light of the closing gender gap in life expectancy, which will ultimately see many men providing direct care to their partners.
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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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".