Association between perceived social stigma against mental disorders and use of health services for psychological distress symptoms in the older adult population: validity of the STIG scale
Bibliographic record
Abstract
OBJECTIVES: To document the reliability, construct and nomological validity of the perceived Social Stigmatisation (STIG) scale in the older adult population. DESIGN: Cross-sectional survey. SETTING: Primary medical health services clinics. PARTICIPANTS: Probabilistic sample of older adults aged 65 years and over waiting for medical services in the general medical sector (n = 1765). MEASUREMENTS: Perceived social stigma against people with a mental health problem was measured using the STIG scale composed of seven indicators. RESULTS: A second-order measurement model of perceived social stigma fitted adequately the observed data. The reliability of the STIG scale was 0.83. According to our results, 39.6% of older adults had a significant level of perceived social stigma against people with a mental health problem. RESULTS showed that the perception of social stigma against mental health problems was not significantly associated with a respondent gender and age. RESULTS also showed that the perception of social stigma against the mental health problems was directly associated with the respondents' need for improved mental health (b = -0.10) and indirectly associated with their use of primary medical health services for psychological distress symptoms (b = -0.07). CONCLUSION: RESULTS lead us to conclude that social stigma against mental disorders perceived by older adults may limit help-seeking behaviours and warrants greater public health and public policy attention. Also, results lead us to conclude that physicians should pay greater attention to their patients' attitudes against mental disorders in order to identify possible hidden mental health problems.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".