Abstract / Description of output
BACKGROUND: Understanding and improving outcomes for people with anxiety or depression often requires large sample sizes. To increase participation and reduce costs, such research is typically unable to utilise "gold-standard" methods to ascertain diagnoses, instead relying on remote, self-report measures.
AIMS: Assess the comparability of remote diagnostic methods for anxiety and depression disorders commonly used in research.
METHOD: Participants from the UK-based GLAD and COPING NBR cohorts (N = 58,400) completed an online questionnaire between 2018 and 2020. Responses to detailed symptom reports were compared to DSM-5 criteria to generate symptom-based diagnoses of major depressive disorder (MDD), generalised anxiety disorder (GAD), specific phobia, social anxiety disorder, panic disorder, and agoraphobia. Participants also self-reported any prior diagnoses from health professionals, termed self-reported diagnoses. "Any anxiety" included participants with at least one anxiety disorder. Agreement was assessed by calculating accuracy, Cohen's kappa, McNemar's chi-squared, sensitivity, and specificity.
RESULTS: Agreement between diagnoses was moderate for MDD, any anxiety, and GAD, but varied by cohort. Agreement was slight to fair for the phobic disorders. Many participants with self-reported GAD did not receive a symptom-based diagnosis. In contrast, symptom-based diagnoses of the phobic disorders were more common than self-reported diagnoses.
CONCLUSIONS: Agreement for MDD, any anxiety, and GAD was higher for cases in the case-enriched GLAD cohort and for controls in the general population COPING NBR cohort. For anxiety disorders, self-reported diagnoses classified most participants as having GAD, whereas symptom-based diagnoses distributed participants more evenly across the anxiety disorders. Further validation against gold standard measures is required.