What does a Single-item Measure of Self-rated Mental Health tell us? Systematic Review of Literature and Analysis of the Canadian Community Health Survey
Bibliographic record
Abstract
A single-item measure of self-rated mental health (SRMH) asks respondents to rate their mental health on a 5-point scale from ‘excellent’ to ‘poor’. SRMH is being used increasingly in research and on population health surveys. However, little is known about this item, as there are no literature reviews and few formal validation studies. The aim of this study is to understand what SRMH measures by conducting the first known systematic review of SRMH literature, followed by analysis of the Canadian Community Health Survey (CCHS 1.2). Results of the systematic review reveal SRMH has relationships with mental health scales, mental disorders, self-rated health, health problems, service utilization, and service satisfaction. Analysis of CCHS 1.2 data finds SRMH is associated with psychiatric diagnoses, distress, physical health, and sociodemographic characteristics. Both studies conclude SRMH is measuring mental health and more; however, there needs to be more research to understand the specifics of these relationships.
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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 | 0.069 | 0.210 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.008 |
| Bibliometrics | 0.022 | 0.022 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".