Measurement Properties of Patient Health Questionnaire 9 and Patient Health Questionnaire 2 in Adult Patients with Atopic Dermatitis
Bibliographic record
Abstract
BACKGROUND: Few outcome measures were validated for assessing depressive symptoms in AD. Patient Health Questionnaire-9 (PHQ9) and the abridged PHQ2 are established patient-reported outcome measures of depressive symptoms. OBJECTIVE: We sought to examine the measurement properties of PHQ9 and PHQ2 in adult AD. A prospective dermatology-practice based study of 458 AD patients (age 18-97 years) was conducted. RESULTS: PHQ9 strongly correlated with Dermatology Life Quality Index, Patient-Reported Outcomes Measurement Information System (PROMIS) Sleep-Disturbance and Sleep-Related Impairment, and PROMIS Itch Questionnaire Mood and Sleep (PIQ-MS), and moderately correlated with Patient-Oriented Eczema Measure, Numeric Rating Scale (NRS) average-itch, NRS-sleep, Eczema Area and Severity Index, Scoring AD and Rajka-Langeland scores. PHQ2 had significantly weaker correlations than PHQ9 with PROMIS SD, SRI and PIQ-MS, but similar correlations with other outcomes. PHQ9 and PHQ2 had good discriminant validity. Changes from baseline in PHQ9 and PHQ2 were poorly or weakly correlated with changes of the other outcome measures. There was no differential item functioning of PHQ items. PHQ9 showed good reliability (intraclass correlation coefficient range: 0.80-0.87). PHQ2 had slightly lower reliability (0.76-0.82). CONCLUSIONS: PHQ9 and PHQ2 had similar measurement properties, but PHQ2 was more feasible to assess depressive symptoms in AD.
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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 | 0.014 | 0.029 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".