Utility of the Patient Health Questionnaire‐9 to Assess Suicide Risk in Patients With Systemic Sclerosis
Bibliographic record
Abstract
OBJECTIVE: Item 9 of the Patient Health Questionnaire-9 (PHQ-9), which inquires about both passive thoughts of death and active ideas of self-harm, has been used to assess suicide risk in arthritis. The objectives of this study were 1) to determine the proportion of systemic sclerosis (SSc; scleroderma) patients who responded "yes" to item 9 who endorsed active suicidal ideation in response to more direct questions during a structured clinical interview, and 2) to report whether the PHQ-8, which does not include item 9 from the PHQ-9, performs similarly to the PHQ-9. METHODS: Patients were recruited from the Canadian Scleroderma Research Group Registry. The PHQ-9 and Composite International Diagnostic Interview (CIDI) depression module were administered during a phone interview. Scores on the PHQ-8 were calculated by removing item 9 from the PHQ-9. Item 9 responses were compared to suicidal ideation and intent in the last year based on the CIDI. Scores on the PHQ-8 and PHQ-9 were compared using Pearson's correlations. RESULTS: There were 345 patients interviewed, of whom 31 (9.0%) endorsed item 9 of the PHQ-9. Of those, based on the CIDI, 14 (45.2%) had passive thoughts of suicide or death. Only 1 patient (3.2%) had thoughts about suicide in some detail at any point in the last 12 months. The correlation between PHQ-9 and PHQ-8 scores was 0.998. CONCLUSION: Item 9 appears to identify many patients who do not report active suicidal ideation. The PHQ-8 may be a better option for assessment of depressive symptoms than the PHQ-9 in patients with SSc.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".