Dementia in rural settings: a scoping review exploring the personal experiences of people with dementia and their carers
Bibliographic record
Abstract
Abstract Rural areas tend to be inhabited by more older people and thus have a higher prevalence of dementia. Combined with lower population densities and more sparse geography, rural areas pose numerous barriers and costs relating to support and resource provision. This may leave people with dementia in rural places at a significant disadvantage, leading to a heavy reliance on informal support networks. The present study explores the personal experiences of people living with dementia and carers living in rural areas, seeking to discover both benefits and challenges, as well as recommendations within the literature for improving the lives of those affected by dementia in rural areas. A scoping review following the framework of Arksey and O'Malley identified 60 studies that describe or discuss the personal experience of dementia (either by the person with dementia or carer), in relation to living in rural or remote geographical areas. Four overarching themes were derived, namely the possible benefits of living in a rural community (supportive rural communities), sources of strength described by people affected by dementia in rural areas (managing and coping), detrimental aspects of living in a rural community (rural community challenges) and difficulties with dementia care services. Three further themes yielded recommendations for improving the experience of dementia in rural areas. This review highlights some potential opportunities related to living in rural areas for people living with dementia. These often come with parallel challenges, reflecting a delicate balance between being well-supported and being in crisis for those living in rural areas. Given the limited access to formal services, supporting people with dementia in rural areas requires input and innovation from the people, organisations and services local to those communities.
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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 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".