Influence of somatic symptoms on patient health questionnaire‐9 depression scores among patients with systemic sclerosis compared to a healthy general population sample
Bibliographic record
Abstract
OBJECTIVE: Depression symptom measures that include somatic symptoms may inflate severity estimates among medically ill patients, including patients with systemic sclerosis (SSc; scleroderma). The 9-item Patient Health Questionnaire (PHQ-9) is increasingly used to assess depressive symptoms in medical settings, but it is not known whether PHQ-9 scores are influenced by somatic symptoms common in medical illness. The objective was to assess whether SSc patients had higher somatic symptom scores on the PHQ-9 than non-medically ill respondents from the general population matched on cognitive/affective scores. METHODS: SSc patients from the Canadian Scleroderma Research Group Registry were matched with respondents from a random population survey of Alberta, Canada residents who were without chronic disease on total PHQ-9 cognitive/affective scores (5 items), sex, and, as close as possible, age. PHQ-9 somatic scores (4 items) were compared between SSc patients and healthy Alberta survey respondents using t-tests for unadjusted analyses and analysis of covariance to adjust for age differences that remained after matching. RESULTS: Somatic symptoms accounted for 64% of the total PHQ-9 scores for 762 matched SSc patients (n = 837 total) compared to 56% for 762 matched Alberta population survey respondents (n = 3,304 total), a mean difference of 1.0 point, or 19% of the total scores for the SSc patients (Hedges's g = 0.38). After adjusting for age, the mean difference increased to 1.4 points, reflecting 25% of the SSc patients' total scores (Hedges's g = 0.55). CONCLUSION: PHQ-9 scores among patients with SSc may include a small to moderate amount of variance from somatic symptoms that are not necessarily related to depression.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".