Using anchoring vignettes to assess the comparability of self‐rated feelings of sadness, lowness or depression in France and Vietnam
Bibliographic record
Abstract
General measures of self-rated health are collected routinely in national health surveys and widely used in the analyses of determinants of health and health care utilization. However, these subjective assessments can be influenced by health expectations (contextualized beliefs about health) that may vary systematically across individuals and be associated with their socio-demographic characteristics. Our objective is to contrast the impact of health expectations associated with respondent characteristics (reporting heterogeneity) on self-rated feelings of sadness, lowness or depression obtained from general population samples in France and Vietnam. Based on self ratings and ratings in response to common anchoring vignettes depicting different levels of depression, we used nationally representative data from the World Health Survey conducted in France (2002) and Vietnam (2002-2003) and a modification of the standard probit model to test and adjust for reporting heterogeneity associated with individual characteristics. We find evidence of reporting heterogeneity within France and Vietnam and across the two countries. In particular we find that, when adjusted for reporting heterogeneity, sex is no longer significantly associated with self-rated feelings of sadness, lowness or depression in France. Given the absence of clear biological markers in the definitions of depressive disorders and the substantial impact reporting heterogeneity is shown to have, measures of depressive disorders based on self-reports should be interpreted with caution.
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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 | 0.025 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".