The prevalence of depression and its associated factors among patients with diabetes mellitus attending a tertiary clinic in Gaborone, Botswana
Bibliographic record
Abstract
Depression is one of the commonest co-existing medical conditions among patients with diabetes mellitus (DM). A bidirectional relationship between depression and DM exists, complicating glycaemic control leading to an increase in diabetic complications. There is a dearth of information regarding the prevalence of depression and associated factors among patients with DM in Botswana.This study aimed to determine the prevalence of depression and associated factors among patients with DM. The study also assessed the association between depression and glycaemic control.A tertiary diabetic referral clinic in Gaborone, Botswana.A sample of 260 randomly selected patients with DM was recruited in this cross-sectional study. Socio-demographic and clinical characteristics of the patients were collected using a case report form. Depression was evaluated using the Patient Health Questionnaire (PHQ)-9 scale. Multivariate regression analysis was used to determine factors significantly associated with depression.The mean age (standard deviation [s.d.]) of study participants was 58.4 (11.8) years, and the majority, 160/260 (61.5%), were females. The prevalence of depression was 30.4% and significantly associated with female sex (adjusted odds ratio [AOR] = 5.529, p-value = 0.004), three or more diabetes-related hospitalisations (AOR = 3.886, p-value = 0.049) and inversely associated with systolic blood pressure (SBP) ≥ 140 mmHg (AOR = 0.11, p-value = 0.001).Depression is a common problem among patients with DM in our setting. Routine screening of depression in diabetic patients to enable early detection and treatment is recommended.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".