Genetic, Epidemiological, and Clinical Risk Factors for Perinatal Anxiety and Depression in Dubai: Protocol for a 2-Point Prospective Observational Study
Bibliographic record
Abstract
BACKGROUND: Perinatal anxiety and depression can significantly impact maternal well-being, infant development, and mother-child bonding. There is a relative lack of research on the overall burden of and risk factors for perinatal and postpartum depression and anxiety in the Middle Eastern region. OBJECTIVE: We aimed to investigate genetic, epidemiological, and clinical risk factors for anxiety and depression in antenatal and postnatal mothers. METHODS: This study is a 2-point, cross-sectional, observational study of pregnant women at a tertiary care hospital in Dubai, United Arab Emirates. We will evaluate the point prevalence of depression and anxiety with the Edinburgh Postnatal Depression Scale, the Generalized Anxiety Disorder 7 scale, and the Holmes-Rahe Stress Inventory and analyze the risk factors in affected and unaffected women. The women will be evaluated with structured interviews, initially in the antenatal period (between 20 to 26 weeks) and again in the postnatal period (between 6 weeks to 6 months after delivery). Whole-genome sequencing will be conducted to comprehensively map genomes and detect variants associated with depression and anxiety after the initial interview. Social factors such as family characteristics and partner support, as well as lifestyle factors such as exercise, vitamin D intake, and obstetric factors, along with intrapartum and neonatal events affecting maternal mental health, will also be assessed. RESULTS: We will assess the prevalence of depression, anxiety, stress, and risk factors in the antenatal and postnatal period between July 2025 and June 2026 at Dubai Hospital. The association of genetic, social, and demographic risk factors with depression and anxiety will be compared in women who screen positive for depression and anxiety and those who screen negative. CONCLUSIONS: This research aims to identify genetic variants associated with perinatal anxiety and depression in Middle Eastern women and to develop a comprehensive risk assessment tool for identifying women at high risk for perinatal anxiety and depression. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/68346.
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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 | 0.016 | 0.012 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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".