Ethnocultural Identity Clarity and the Associations with Psychological Distress and Stigma of Depression
Bibliographic record
Abstract
Background: Canadian universities are becoming more multicultural in the past decades. Students also report high level of depressive and anxiety symptoms, as well as their related stigma. Past studies that explored the associations between cultural variables and psychological well-being often categorized a participant as coming from a single ethnocultural group, disregarding the individual cultural processes that a multicultural individual experiences. We explored two ethnocultural variables: 1) ethnocultural groups (the cultural group that a person identifies with), and 2) cultural identity clarity (how much a multicultural person is clear on who they are culturally), and how they were associated with psychological distress and the level of public stigma of depression. Methods: After literature search, related questionnaires were identified, and additional questions were compiled into a single survey package. A total of 4,215 Queen’s University students were invited to participate in the study. We first evaluated the performance of the Cultural Identity Clarity Scale. We then explored the association between cultural identity clarity and psychological distress using the modified Poisson regression. The relationship between ethnocultural group and stigma of depression was explored using ordinal logistic regression. All models were adjusted for demographic variables that were relevant to the post-secondary environment. Results: Our final sample size was 750 students. The Cultural Identity Clarity Scale performed well among our sample, with good reliability and convergent validity. Multicultural students who were clearer on who they were culturally experienced a lower risk of being psychologically distressed compared to those who were less clear on who they were. We also found that the levels of stigma of depression were different depending on the identified ethnocultural group among multicultural international students. Conclusion: Our findings suggested that ethnocultural factors may be implicated in psychological well-being and stigma of mental illness in post-secondary settings. We propose future research to focus on the individual multicultural process alongside the exploration of ethnocultural groups when conducting research around the multicultural population. We also recommended a mental health service approach that is culturally inclusive and specific, as well as an anti-stigma program that is more targeted to address the cultural components of stigma.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".