Health Equity and Health Inequity of Disabled People: A Scoping Review
Bibliographic record
Abstract
Health equity is an important aspect of wellbeing and is impacted by many social determinants. The UN Convention on the Rights of Persons with Disabilities (CRPD) is a testament to the lack of health equity and the many health inequity issues based on social determinants experienced by disabled people. The health equity/health inequity situation of disabled people is even worse if their identities intersect with those of other marginalized groups. Many societal developments and discussions including discussions around the different sustainability pillars can influence the health equity/health inequity of disabled people. The general aim of this study was to better understand the academic engagement with the health equity and health inequity of disabled people beyond access to healthcare. To fulfill our aim, we performed a scoping review of academic abstracts using a hit count manifest coding and content analysis approach to abstracts obtained from SCOPUS, the 70 databases of EBSCO-HOST, Web of Science, and PubMed. Health equity and health inequity abstracts rarely cover disabled people as a group, less with many specific groups of disabled people, and even less or not at all with the intersectionality of disabled people belonging to other marginalized groups. Many social determinants that can influence the health equity and health inequity of disabled people were not present. Ability-based concepts beyond the term ableism, intersectionality-based concepts, and non-health based occupational concepts were not present in the abstracts. Our qualitative content analysis of the 162 abstracts containing health equity and disability terms and 177 containing health inequity and disability terms found 65 relevant abstracts that covered problems with health equity disabled people face, 17 abstracts covered factors of health inequity, and 21 abstracts covered actions needed to deal with health inequity. Our findings suggest a need as well as many opportunities for academic fields and academic, policy, and community discussions to close the gaps in the coverage of health equity and health inequity of disabled people.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.029 | 0.029 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".