Mapping genetic research in non-communicable disease publications in selected Arab countries: first step towards a guided research agenda
Bibliographic record
Abstract
BACKGROUND: In the Arab world, intervention and policy response to non-communicable diseases (NCD) has been weak despite extensive epidemiological evidence highlighting the alarmingly increased prevalence of chronic diseases. Generating genetic information is one key component to promote efficient disease management strategies. This study undertook a scoping review to generate the profile of the undertaken research on genetics of NCD publications in selected Arab countries. An analysis of the research produced examined the extent, range, nature, topic and methods of published research. The study aimed at identifying the gaps in genetic NCD research to inform policy action for NCD prevention and control. METHODS: The scoping review was conducted based on the five-stage methodological framework and included countries in Arab region selected to represent various economies and epidemiological transitions. RESULTS: The search identified 555 articles that focus on genetics-NCD research in the selected Arab countries over the duration of this study (January 2000 to December 2013). The most commonly conducted research was descriptive and clinically focused, rather than etiologically focused. Country-specific carrier and risk screening studies were not among the top research designs. The genetic component of certain highly heritable diseases, as well as diabetes, obesity, hypertension, chronic lung dysfunction and metabolic syndrome were all under investigated. CONCLUSIONS: This scoping review identified gaps for further research in the context of bioinformatics and genome-wide association studies. Genetic research in the Arab region has to be redirected towards NCDs with the highest morbidity, heritability and health burden within each country. A focused research plan to include community genetics is required for its proper integration in the Arab community.
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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 | 0.044 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".