Older Thai Peoples’ Perceptions and Experiences of Major Depression
Bibliographic record
Abstract
BACKGROUND: Depressive disorders are common mental health problems and may be disabling among the general older population. Although older people have significant symptoms of depression, the symptoms are likely to be underreported. The condition often co-exist along with somatic ill and has often been unrecognized. The aim of the study was to explore and understand the perceptions and experiences of older Thai people diagnosed with major depressive disorder.METHODS: A qualitative inductive research design was used and latent content analysis was utilized. The data were collected through face-to-face, in-depth interviews. Fourteen older people diagnosed with major depressive disorder were selected for participant using purposive sampling. FINDINGS: Older Thai peoples’ perceptions and experiences of depression were abstracted into two themes. First theme was leading a life in detachment, which included three subthemes: living with meaninglessness, holding distress with one’s self, and feeling judged by surrounded people. The second theme was inconvenience of approaching mental health treatment, which included two subthemes: sensing an unapproachable health care service, and lacking knowledge about clinical depression.CONCLUSION: Older Thai peoples’ perceptions and experiences of major depression were affected with high level suspected existential loneliness that might even be worse in a collect oriented society as in the Thai context. Further, it seem hard to approach the mental health care. The central reason for this is interpreted as lack of mental health literacy, and in this case, specifically, knowledge on depression. Future studies should focus on relatives’ experiences of living with an older family member that suffered from major depression, and on the state of mental health literacy in the rural Thai population.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".