Barriers and Facilitators to the Social Participation of Individuals Aging with a Long-Term Neurological Disability: A Scoping Review
Bibliographic record
Abstract
Supporting the social participation of individuals aging with long-term neurological disabilities is key to healthy aging. However, knowledge about the factors influencing their social participation remains limited and fragmented. Following the Joanna Briggs Institute methodology, this scoping review synthesized and integrated knowledge regarding the barriers and facilitators to the social participation of individuals aging with long-term neuro-disabilities. A search in four databases (MEDLINE, CINAHL, PsycInfo, and EMBASE) resulted in 18 studies involving 2587 participants with nine neurological conditions: stroke, multiple sclerosis, spinal cord injury, traumatic brain injury, aphasia, post-polio syndrome, spina bifida, cerebral palsy, and muscular dystrophy. A total of 38 barriers, 25 facilitators, and 4 factors with mixed influence to social participation were identified. Key reported barriers included the organic system (e.g., fatigue or pain) and macro environments (e.g., inaccessible built environment). The most common facilitators involved physical dimensions in personal factors (e.g., good physical functions) and micro-environments (e.g., supportive social environment). This review highlights the need for accessible infrastructure and community support to promote inclusivity and equity. Future research should focus on community-level factors and mixed study designs to provide robust evidence to improve social participation and healthy aging in this vulnerable population.
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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 | 0.007 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".