Depression, and Drug Adherence in Type 2 Diabetes Mellitus in Primary Care in the Kingdom of Bahrain
Bibliographic record
Abstract
Depression stands out as the predominant risk factor among Type 2 diabetes (T2DM) patients. Depression and its association with drug adherence in T2DM patients are lacking in Bahrain. The current study aimed to examine the association depression in relation to drug adherence in T2DM in primary care centers in the Kingdom of Bahrain. This was a cross-sectional study that enrolled 455 people with T2DM. Data on demographics, risk behavior, and diabetes details were noted. Measuring tools such as patient health questionnaire (PHQ-9) to measure depression severity, and General Medication Adherence Scale (GMAS) were used to assess medical adherence respectively. Categorical variables and continuous variables were presented in a frequency table and mean ± SD/ Median (Min, Max) respectively. The data was analyzed using SPSS 24.0 software. The statistical significance threshold was set at p=0.05. The study involved participants with an average age of 54.5 ± 11.5 (M±SD) years. The frequency of depression based on PHQ-9 and medical adherence as per GMAS among T2DM patients was 30.5% and 79.1% respectively. There was a significant association between the prevalence of depression and adherence (x2 =25.03; P=0.001). Age (r=-0.121; P= 0.010), education (r=-0.096; P=0.040), family income (r=-0.101; P=0.031), physical activity (r=-0.193; P=0.001), and self-rated diabetes control within the last visit (r=-0.200; P=0.001) were significantly negatively correlated with PHQ – 9 scale. Likewise, age (r=-0.231; p=0.001), education (r=-0.123; p=0.008), nationality (r=-0.185; p=0.001), physical activity (r=-0.108; p=0.021), and self-rated diabetes control within the last visit (r=-0.139; p=0.003) were significantly negatively correlated with the GMAS scale. Our findings suggest that medical adherence is linked to depression. Age, height, education, family income, physical activity, and self-rated diabetes control in the previous visit are all important factors that are correlated to depression and drug adherence.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 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".