Prevalence and determinants of depression among patients under the care of traditional health practitioners in a Kenyan setting: Policy implications
Bibliographic record
Abstract
In Kenya, there is paucity of information on depression among traditional health practitioner (THP) patients, particularly in rural areas. The aim of this study was to estimate prevalence and identify determinants of major depressive disorder (MDD) among patients of THP in rural Kenya using the World Health Organization (WHO) Mental Health Gap Action Programme Intervention Guideline (mhGAP-IG). All adult patients seeking care from trained THPs (either traditional healers such as diviners and herbalists or faith healers, who use treatments such as prayers, laying hands on patients, or providing holy water and ash to their patients) over a period of 3 months (September 2014 to November 2014) were screened for depression using mhGAP-IG and their sociodemographic characteristics recorded. Overall, the prevalence of depression among THP patients was 22.9%. Being older, female, single, divorced or separated, as well as unemployment and lack of education were found to be significant determinants of depression. Patients with MDD frequently presented with suicidal behavior (32.9%, OR = 5.94, p < .0001) compared to those that had at least one psychotic symptom (26.3%, OR = 3.65, p < .0001). A measure of the accuracy of THPs' assessment of MDD showed 86% specificity and 46% sensitivity and the area under receiver operating characteristics (ROC) curve was 0.686. Our findings shed light on the prevalence of depression among THP patients and thus highlight the need for further research on diagnostic tools for use among THPs in order to avoid substandard care and promote reliance on more evidence-based methods of care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".