Depressive Symptoms among Kuwaiti Population Attending Primary Healthcare Setting: Prevalence and Influence of Sociodemographic Factors
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to estimate the prevalence of depressive disorders and the influence of sociodemographic characteristics on primary healthcare (PHC) setting in Kuwait. SUBJECTS AND METHODS: A cross-sectional survey was conducted in PHC setting in Kuwait using the Beck Depression Inventory second edition questionnaire (BDI II) as a screening instrument, together with a sociodemographic questionnaire. A representative sample drawn from the target population consisted of 2,320 subjects of Kuwaiti nationality randomly selected from 18 PHC centers covering all Kuwait governorates during the period from April 2003 to January 2004. The target age group was 21-64 years. Participants were asked to complete the BDI II questionnaire consisting of 21 items reflecting the depressive disorder independently. Sociodemographic data such as sex, age, marital status, children, occupation, educational status, chronic diseases and social problems were included in the questionnaire. The optimum cutoff score for BDI II was estimated. RESULTS: A total of 2,320 participants completed the questionnaire, 1,082 (46.8%) male and 1,237 (53.2%) female; 860 (37.1%) screened positive for depressive symptoms, among whom 352 (15.3%) were male and 508 (21.7%) female. Of all participants, 163 (7.0%) were severely depressed, 314 (13.5%) moderately depressed and 383 (16.5%) mildly depressed. Depressive disorder was more prevalent among women than men, young than old, more among highly educated individuals, working participants, married individuals, and parents with 3 or more children. CONCLUSION: Depressive disorder is a highly prevalent condition among Kuwaiti patients attending PHC setting. Chronic diseases and social problems are risk factors for depressive disorder.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".