Do psychometrics matter? The effects of advanced psychometric analyses on depression randomised trial outcomes

Depression is currently the most common mental health disorder worldwide, with an estimated 5% of the population – or 280 million people – suffering this disorder. Depression can affect how you feel, think and behave and can lead to a range of emotional and physical problems. Depression can be a significant health condition, which can inform poor interpersonal relationships, poor work functionality and, at its worst, can inform suicide ideation.

Symptoms caused by depression can vary from person to person and there are a number of effective treatments to help combat depression. These treatments can be broadly categorised as psychotherapies (talking therapy) that can help a person manage their problems by changing the way they think and behave, and pharmacotherapies, such as taking antidepressant medication. The effectiveness of these treatments is typically examined using psychometric assessment, essentially questionnaires which evaluate patients’ experiences of a range of depressive symptoms. However, despite several advanced and very complex statistical methods being developed to evaluate these questionnaires, it is unclear if using these complex techniques are important for finding changes that matter to patients and clinicians.

A recent analysis of 101 studies of 11,910 people with mostly moderate-severe depression, had some very important findings. Firstly, combination psychotherapy (talking therapy) and antidepressants were more effective than either alone. Secondly, antidepressants and psychotherapies did not differ in effects from each other. These types of multi-study analyses allow for estimation of treatment effects that cannot be achieved by single studies alone. In essence, they show that something really ‘matters’ at a population level in terms of treatment effects.

In this current study we propose to obtain already-collected data from thousands of patients who have already participated in depression treatment studies and combine into a large database. This database will be analysed using advanced psychometric techniques, and the results of these complex techniques compared. Using this large database we aim to determining whether psychometric analysis informs any differences in the original results of these depression treatment studies.

This study could make an important contribution to medical science and patient care by highlighting important differences (including gender differences) in depression symptoms and treatments, and potentially improving the accuracy with which depression is psychometrically assessed.