The expression of depression among Javanese patients with major depressive disorder: A concept mapping study
Bibliographic record
Abstract
In this study, we explored the presentation of clinical depression in Java, Indonesia. Interviews were conducted with 20 Javanese patients (male and female) with major depressive disorder from both lower and higher socioeconomic levels. The recruited participants came from provincial and private mental health hospitals in the cities of Solo, Yogykarta (Jogja), Jakarta, and Malang on the island of Java, Indonesia. Concept mapping methodology using multidimensional scaling and hierarchical cluster analysis was used to identify underlying themes in the expression of depressive phenomena in this Indonesian population. The results identified themes that grouped into six clusters: interpersonal relationships, hopelessness, physical/somatic, poverty of thought, discourage, and defeat. Findings give support to the view that culture influences the expression of Indonesian depressive phenomenology, which nevertheless has some common roots with Western clinical pictures of the disorder. Cultural influences may mask symptoms of the disorder to clinicians. Diagnostic and assessment tools must be carefully selected to ensure they address culturally specific expressions of depression.
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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 | 0.002 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".