Associations between psychological stress, discrimination, and oral health-related quality of life: the buffering effects of social support networks
Bibliographic record
Abstract
Stress and discrimination negatively affect quality of life, but social support may buffer their effects. This study aims: (1) to examine the associations between psychological stress, discrimination, and oral health-related quality of life (OHRQoL); and (2) to assess whether social support, stress and discrimination interact to modify their associations with OHRQoL. We used cross-sectional household-based data from a study including 396 individuals aged 14 years and over from families registered for government social benefits in a city in Southern Brazil. OHRQoL was measured with the Oral Impacts on Daily Performance (OIDP) scale; psychological stress was assessed with the Perceived Stress Scale (PSS); social support was assessed based on the number of close relatives or friends of the participant, and discrimination was assessed with a short version of the Everyday Discrimination Scale. Interactions were estimated using the relative excess of risk due to interaction (RERI). Adjusted effects were calculated with logistic regression. The prevalence of oral impacts among people with higher and lower PSS scores was 81.6% and 65.5%, respectively (p < 0.01). Social support was found to have no interactions with stress levels and discrimination. The association between social discrimination and OHRQoL (OIDP score > 0) was OR = 2.03 (95%CI: 1.23; 3.34) among people with a low level of stress, but was OR = 12.6 (95%CI: 1.31; 120.9) among those with higher levels (p = 0.09, for interaction). Individuals who reported experiencing higher levels of psychological stress and discrimination had worse OHRQoL; a synergistic effect with social support was not clear.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".