Barriers to access and utilization of healthcare services for minority-language speakers with neurodevelopmental disorders: A scoping review
Bibliographic record
Abstract
Introduction Minority-language speakers in the general population face barriers to accessing healthcare services. This scoping review aims to examine the barriers to healthcare access for minority-language speakers who have a neurodevelopmental disorder. Our goal is to inform healthcare practitioners and policy makers thus improving healthcare services for this population. Inclusion criteria Information was collected from studies whose participants include individuals with a neurodevelopmental disorder (NDD) who are minority-language speakers, their family members, and healthcare professionals who work with them. We examined access to healthcare services across both medical and para-medical services. Method Searches were completed using several databases. We included all types of experimental, quasi-experimental, observational and descriptive studies, as well as studies using qualitative methodologies. Evidence selection and data extraction was completed by two independent reviewers and compared. Data extraction focused on the barriers to accessing and to utilizing healthcare for minority-language speakers with NDDs. The search process and ensuing results were fully reported using a diagram from the Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for scoping review. Results Following the database search, a total of 28 articles met our final selection criteria and two articles were hand-picked based on our knowledge of the literature, for a total of 30 articles. These studies revealed that minority-language speakers with NDDs and their families experience several barriers to accessing and utilizing healthcare services. These barriers, identified at the Systems, Provider and Family Experience levels, have important consequences on children's outcomes and families' well-being. Discussion While our review outlined several barriers to access and utilization of healthcare services for minority-language speakers with NDDs and their families, our findings give rise to concrete solutions. These solutions have the potential to mitigate the identified barriers, including development and implementation of policies and guidelines that support minority-language speakers, practitioner training, availability of referral pathways to appropriate services, access to tools and other resources such as interpretation services, and partnership with caregivers. Further research needs to shift from describing barriers to examining the efficacy of the proposed solutions in mitigating and eliminating identified barriers, and ensuring equity in healthcare for minority-language speakers with NDDs.
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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 | 0.025 | 0.142 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.019 | 0.017 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 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".