In the Absence of Effects: An Individual Patient Data Meta-Analysis of Non-response and Its Predictors in...

Background: Negative effects of psychological treatments have recently received increased attention in both research and clinical practice. Most investigations have focused on determining the occurrence and characteristics of deterioration and other adverse and unwanted events, such as interpersonal issues, indicating that patients quite frequently experience such incidents in treatment. However, non-response is also negative if it might have prolonged an ongoing condition and caused unnecessary suffering. Yet few attempts have been made to directly explore non-response in psychological treatment or its plausible causes. Internet-based cognitive behavior therapy (ICBT) has been found effective for a number of diagnoses but has not yet been systematically explored with regard to those patients who do not respond. Methods: The current study collected and aggregated data from 2,866 patients in 29 clinical randomized trials of ICBT for three categories of diagnoses: anxiety disorders, depression, and other (erectile dysfunction, relationship problems, and gambling disorder). Raw scores from each patient variable were used in an individual patient data meta-analysis to determine the rate of non-response on the primary outcome measure for each clinical trial, while its potential predictors were examined using binomial logistic regression. The reliable change index (RCI) was used to classify patients as non-responders. Results: Of the 2,118 patients receiving treatment, and when applying a RCI of z ≥ 1.96, 567 (26.8%) were classified as non-responders. In terms of predictors, patients with higher symptom severity on the primary outcome measure at baseline, Odds Ratio (OR) = 2.04, having a primary anxiety disorder (OR = 5.75), and being of male gender (OR = 1.80), might have higher odds of not responding to treatment. Conclusion: Non-response seems to occur among approximately a quarter of all patients in ICBT, with predictors related to greater symptoms, anxiety disorders, and gender indicating increasing the odds of not responding. However, the results need to be replicated before establishing their clinical relevance, and the use of the RCI as a way of determining non-response needs to be validated by other means, such as by interviewing patients classified as non-responders.