Health‐related stigma of noncommunicable neurological disease in rural adult populations: A scoping review
Bibliographic record
Abstract
Stigma is a widely recognised public health issue. Many people with neurological disease and their families experience stigmatisation, adding to their burden of illness. Rural populations are typically small, lack anonymity, and often have a higher proportion of older adults with inadequate access to specialised services and resources. Although generally isolated, rural areas can offer benefits such as a sense of familiarity and interconnectedness. The purpose of this scoping review was to map the existing evidence on stigma associated with non-communicable neurological disease in rural adult populations and identify key findings and gaps in the literature. Our literature search of peer-reviewed English language articles published from 1 January 1992 to 22 June 2017 was conducted across five databases yielding 8,209 results. After duplicate removal, pairs of reviewers independently screened 6,436 studies according to inclusion criteria developed a priori; 36 articles were identified for inclusion in this review. Study characteristics were described and illustrated by frequency distribution, findings were grouped thematically, and each of the five types of stigma were identified (social, self, health professional, associative, structural). Four factors influencing stigma (knowledge, familiarity, beliefs, and rurality) and four overarching stigma-related themes (concealment; exclusion; disempowerment, discrimination, and unequal opportunities; and issues related to healthcare systems and providers) emerged. In urban-rural comparison studies, rural residents were generally less knowledgeable about the neurological disease and more stigmatised. The impact of other factors (i.e., gender, age, and education) on stigma varied and are stated where associations were reported. Three main gaps were identified including: low attention to stigma related to neurological diseases other than epilepsy, limited cross-cultural comparisons of stigma related to neurological disease, and inclusion of gender as a variable in the analysis of stigma-related outcomes in only half of the reviewed studies. Further research is recommended.
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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 | 0.009 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".