Domains of wheelchair users’ socio-emotional experiences: Design insights from a scoping review
Bibliographic record
Abstract
BACKGROUND: Physical accessibility is not the only concern for wheelchair users (WUs); they also face barriers to social presence, such as challenges in social engagement and negative stereotypes. Identifying key domains in the literature that impact their social and emotional experiences is essential to addressing these issues. OBJECTIVE: This scoping review sought to explore the key domains of WUs' socio-emotional experiences, as a foundation for providing design-oriented insights to enhance their social presence. METHODS: A literature search was conducted using the Web of Science, PubMed, Scopus, and PsycINFO databases, along with a manual search of three relevant journals. Articles in English, based on original empirical studies that focused on the socio-emotional experiences of adult WUs (>18), were included. RESULTS: Of the 48 articles included, most were from Canada (n = 11), Sweden (n = 9), the U.S. (n = 7), and the U.K. (n = 6), with limited studies from other countries. Among the six domains explored, Independence & Autonomy (26 %) was the most frequently reported, while Self-Identity & Body Image (9 %) and Social Stigma & Discrimination (5 %) were the least. Three interconnected themes emerged to guide design insights: Theme I - Foundations: Autonomy & Control, Theme II - Connections: Social Participation & Support, and Theme III - Reflection: Self- & Social-Identity. CONCLUSION: While independence and agency are key concerns, little research has focused on perceptual issues like self- and social-identity, often highlighted in the media. This area can be refined by recognizing the crucial role of design in aesthetically shaping WUs' social representation in public settings.
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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 | 0.040 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.027 | 0.022 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".