Accessibility Difficulties, and Utilization of Healthcare Services Among Jordanian Roma with Chronic Diseases
Bibliographic record
Abstract
Purpose: To examine factors that affect healthcare utilization among Roma population with chronic diseases in Jordan. It also explores behavior-seeking health care among them, their characteristics and ability to access healthcare. Design/Methodology/Approach: A cross-sectional descriptive survey performed, data collection done through in-person interviews using a structured questionnaire based on the Canadian Community Health Survey. Andersen’s behavioral model was implemented to examine the influences of predisposing, enabling, need, and outcome factors on healthcare utilization using binary logistic regression, and predictors for accessibility difficulties using multiple linear regression, Findings: 98.8% of the participants stated that they had difficulties in getting the care needed for diagnosis, treatment, or consultation, and 24.8% said that they didn’t utilize healthcare services last year. The number of chronic diseases and satisfaction level with the healthcare services significantly increase utilization, on the other hand; age, health insurance, resident location, number of chronic diseases and their duration as well as satisfaction with the healthcare are significantly affect accessibility difficulties to healthcare services. Practical implications: Provide mobile health units to reach remote settlements, that provide efficient healthcare services that met their health needs, and to be integrated with local health system. Societal implications: Efforts to involve Roma children in education. Establishing vocational training programs ended with employments. Establish sufficient and reasonable housing, to be side by side to the other population. Originality/value: This study is considered as the first to address the Jordanian Roma health status, utilization and accessibility to healthcare services, the end results help in suggesting different approaches to improve health and promote health equity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".