Screening for mental disorders in heart failure patients using computer-adaptive tests

Item response theory is increasingly used in the development of psychometric tests. This paper evaluates whether these modern psychometric methods can improve self-reported screening for depression and anxiety in patients with heart failure. The mental health status of 194 patients with heart failure was assessed using six screening tools for depression (Patient Health Questionnaire -9 (9 items), Hospital Anxiety and Depression Scale (HADS) (7 items), PROMIS-Depression Short Form 8a (8 items)) and Anxiety (GAD-7 (7 items), Hospital Anxiety and Depression Scale (HADS) (7 items), PROMIS-Anxiety Short Form 8a (8 items)). An in-person structured clinical interview was used as the current gold standard to identify the presence of a mental disorder. The diagnostic accuracy of all static tools was compared when item response theory (IRT)-based person parameter were estimated instead of sum scores. Furthermore, we compared performance of static instruments with post hoc simulated individual-tailored computer-adaptive test (CATs) for both disorders and a common negative affect CAT. In general, screening for depression was highly efficient and showed a better performance than screening for anxiety with only minimal differences among the assessed instruments. IRT-based person parameters yielded the same diagnostic accuracy as sum scores. CATs showed similar screening performance compared to legacy instruments but required significantly fewer items to identify patients without mental conditions. Ideal cutoffs varied between male and female samples. Overall, the diagnostic performance of all investigated instruments was similar, regardless of the methods being used. However, CATs can individually tailor the test to each patient, thus significantly decreasing the respondent burden for patients with and without mental conditions. Such approach could efficiently increase the acceptability of mental health screening in clinical practice settings.