Cognitive impairment and associated factors among patients with mood disorders receiving care at public hospitals in Gedeo zone, Southern Ethiopia
Bibliographic record
Abstract
BACKGROUND: Cognitive impairment is characterized by difficulty in attention, memory, problem-solving, and decision-making. It is strongly linked to mood disorders and affects work performance, social interactions, medication adherence, and overall quality of life. Despite the high burden of the problem, evidence on its prevalence and contributing factors remains scarce in low- and middle-income countries. This study aimed to determine the prevalence and associated factors of cognitive impairment among individuals with mood disorders. METHOD: A cross-sectional study was conducted at Gedeo Zone public hospitals. A systematic sampling technique was used to select a total of 422 individuals receiving care for mood disorders. The outcome variable was assessed using the Montreal Cognitive Assessment (MoCA). The data were entered into Epi Data version 4.2 and analyzed using STATA version 17. Bivariable and multivariable logistic regression analyses were performed to identify factors associated with cognitive impairment. The presence of an association was examined with an adjusted odd ratio with a 95% confidence interval and variables with P values less than 0.05 were considered a statistically significant association. RESULT: The prevalence of cognitive impairment among individuals with bipolar disorders and depressive disorders was 34.5% (95% CI: 32.7-36.9) and 38.7% (95% CI: 36.4-40.8), respectively. Having a longer duration of treatment [AOR = 1.87 (95% CI: 1.57, 2.94)], a duration of illness 10 years and above [AOR = 2.13 (95% CI 1.23, 4.48)], and severe depressive symptoms [AOR = 2.15 (95% CI 1.14, 4.97)] were significantly associated with cognitive impairment among individuals with depressive disorders. Medication non-adherence [AOR = 1.48 (95% CI: 1.34, 2.78)], a long duration of illness [AOR = 1.42 (95% CI: 1.09, 2.48)], and severe manic symptoms [AOR = 2.16 (95% CI: 1.18, 5.28)] were significantly associated with cognitive impairment among participants with bipolar disorders. CONCLUSION: This study revealed a high prevalence of cognitive impairment in patients with mood disorders. Therefore, early screening and intervention for cognitive impairment in mood disorder patients are essential to deliver holistic care and improve treatment outcomes. Integrating cognitive assessments into routine mental health evaluations can help identify early deficits and enable tailored interventions. Additionally, cognitive remediation strategies such as structured patient education, side-effect management, and medication adjustments should be prioritized to enhance adherence and overall recovery.
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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 | 0.001 | 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".