Why is it so hard to identify (consistent) predictors of treatment outcome in psychotherapy? – clinical and research perspectives

Abstract

Background Anxiety and depression are two of the most debilitating psychological disorders worldwide today. Fortunately, effective treatments exist. However, a large proportion of patients do not recover from treatment, and many still have symptoms after completing treatment. Numerous studies have tried to identify predictors of treatment outcome. So far, researchers have found few or no consistent predictors applicable to allocate patients to relevant treatment. Methods We set out to investigate why it is so hard to identify (consistent) predictors of treatment outcome for psychotherapy in anxiety and depression by reviewing relevant literature. Results Four challenges stand out; a) the complexity of human lives, b) sample size and statistical power, c) the complexity of therapist-patient relationships, and d) the lack of consistency in study designs. Together these challenges imply there are a countless number of possible predictors. We also consider ethical implications of predictor research in psychotherapy. Finally, we consider possible solutions, including the use of machine learning, larger samples and more realistic complex predictor models. Conclusions Our paper sheds light on why it is so hard to identify consistent predictors of treatment outcome in psychotherapy and suggest ethical implications as well as possible solutions to this problem.

Return of Negative Interpretation Bias After Positive Interpretation Training as a Dynamic Predictor of Treatment Outcome in Fear of Public Speaking

“…Numerous studies have focused on trying to predict treatment outcomes in anxiety disorders, aiming to identify patients who will benefit more versus less, and ultimately optimize treatment for those benefitting less (e.g., Hoyer et al, 2016;Porter & Chambless, 2015). Despite these efforts, no consistent predictors have been identified (Eilertsen & Eilertsen, 2023;Schneider et al, 2015).…”

“…The large majority of studies investigated static, trait-like measures (e.g., demographic variables, comorbid disorders, personality characteristics, motivation to change) to predict changes in psychopathology following treatment, which showed inconsistent results (Eilertsen & Eilertsen, 2023;Schneider et al, 2015). However, there is growing recognition of the dynamic nature of psychopathology.…”