Validation of PROMIS anxiety item bank computer adaptive test among patients with heart failure
Bibliographic record
Abstract
Introduction Anxiety is highly prevalent among patients with heart failure (HF), negatively affecting health related quality of life (HRQOL). The Patient-Reported Outcomes Measurement Information System (PROMIS) anxiety item bank computer adaptive testing (CAT) precisely assesses anxiety symptom severity. This study aims to assess construct validity and reliability of PROMIS-Anxiety CAT among patients hospitalized for HF. Methods A cross-sectional convenience sample of adult patients hospitalized for HF, who completed PROMIS-A CAT, generalized anxiety disorder 7 (GAD-7), and other questionnaires electronically. Convergent validity was assessed by Spearman's rank correlation between PROMIS-A CAT, GAD-7, and other legacy measures. Known group analysis compared PROMIS-A CAT and GAD-7 scores between groups expected to have different levels of anxiety. Reliability of PROMIS-A CAT was calculated on the individual and group level from standard error of measurement, according to item response theory. Area under receiver-operating characteristics (ROC) curve and Youden's J statistic were used to identify a T -score cut-off for moderate/severe anxiety. Results Of 333 participants, 87 (26%) had moderate/severe anxiety based on GAD-7 score (≥ 10). Participants completed on average (median [IQR]) 4(1) vs. 7(0) items, with PROMIS-A CAT and GAD-7, respectively. PROMIS-A CAT T -scores were strongly correlated with GAD-7 scores (rho = 0.78) and moderately correlated with other legacy measures. Known-group analysis provided further support for construct validity of PROMIS-A CAT. Individual reliability for PROMIS-A CAT T -scores was >0.9 for 87% of the sample; mean reliability was 0.91. Based on ROC and Youden's J analyses, a T -score of 60 can be used to identify individuals with moderate/severe anxiety. Conclusion These results support the validity and reliability of PROMIS-A CAT among patients hospitalized for HF.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".