The experiences and needs of unpaid family caregivers for persons living with dementia in rural settings: A qualitative systematic review
Bibliographic record
Abstract
PURPOSE: Unpaid family caregivers provide extensive support for community-dwelling persons living with dementia, impacting family caregivers' health and wellbeing. Further, unpaid family caregiving in rural settings has additional challenges because of lower access to services. This systematic review examines qualitative evidence to summarize the experiences and needs of rural unpaid family caregivers of persons living with dementia. METHODS: CINAHL, SCOPUS, EMBASE, Web of Science, PsychINFO, ProQuest, and Medline were searched for articles investigating the experience and needs of rural family caregivers of persons living with dementia. Eligibility criteria were: 1) original qualitative research; 2) written in the English language; 3) focused on the perspectives of caregivers of community-dwelling persons with dementia; 4) focused on rural settings. Study findings were extracted from each article and a meta-aggregate process was used to synthesize the findings. FINDINGS: Of the 510 articles screened, 36 studies were included in this review. Studies were of moderate to high quality and produced 245 findings that were analyzed to produce three synthesized findings: 1) the challenge of dementia care; 2) rural limitations; 3) rural opportunities. CONCLUSIONS: Rurality is perceived as a limitation for family caregivers in relation to the scope of services provided but can be perceived as a benefit when caregivers experience trustworthy and helpful social networks in rural settings. Implications for practice include establishing and empowering community groups to partner in the provision of care. Further research must be conducted to better understand the strengths and limitations of rurality on caregiving.
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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 | 0.020 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".