Single-item measures for depression and anxiety: Validation of the Screening Tool for Psychological Distress in an inpatient cardiology setting
Bibliographic record
Abstract
BACKGROUND: Depression and anxiety are common among patients with cardiovascular disease (CVD) and confer significant cardiac risk, contributing to CVD morbidity and mortality. Unfortunately, due to the lack of screening tools that address the specific needs of hospitalized patients, few cardiac inpatient programs offer routine screening for these forms of psychological distress, despite recommendations to do so. AIMS: The purpose of this study was to validate single-item measures for depression and anxiety among cardiac inpatients. METHODS: Consecutive inpatients were recruited from the cardiology and cardiac surgery step-down units at a university-affiliated, quaternary-care hospital. Subjects completed a questionnaire that included: (a) demographics, (b) single-item-measures for depression and anxiety (from the Screening Tool for Psychological Distress (STOP-D)), and (c) Hospital Anxiety and Depression Scale (HADS). RESULTS: One hundred and five participants were recruited with a wide variety of cardiac diagnoses, having a mean age of 66 years, and 28% were women. Both STOP-D items were highly correlated with their corresponding validated measures and demonstrated robust receiver-operator characteristic curves. Severity scores on both items correlated well with established severity cut-off scores on the corresponding subscales of the HADS. CONCLUSIONS: The STOP-D is a self-administered, self-report measure using two independent items that provide severity scores for depression and anxiety. The tool performs very well compared with other previously validated measures. Requiring no additional scoring and being free, STOP-D offers a simple and valid method for identifying hospitalized cardiac patients who are experiencing psychological distress. This crucial first step triggers initiation of appropriate monitoring and intervention, thus reducing the likelihood of the adverse cardiac outcomes associated with psychological distress.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".