چه کسی بیشتر از درمان شناختی اینترنتی تحت درمان با درمانگر در عمل بالینی بیشترین بهره را می برد؟ پیش بینی های علامت تغییر و رها کردن

Internet-delivered cognitive behavioral therapy (ICBT) is effective for treating anxiety and depression, but not for all patients. Predictors of dropout and outcomes from ICBT remain unclear and the literature could benefit from study of response to ICBT among larger community samples using advanced statistical techniques. In this study, we sought to identify predictors of dropout and symptom change in a large community sample (n = 1201) who received therapist-assisted transdiagnostic ICBT targeting anxiety and/or depression. Logistic regression was used to assess dropout, and showed that those who fully completed ICBT lessons (n = 880) were older and endorsed lower psychological distress at intake than those who only partially completed ICBT lessons (n = 321). During the course of therapy, patients responded to the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7 at six time points. Autoregressive latent trajectory models were fitted to this data to assess the ability of demographic variables, program engagement, psychological and medical service usage, and psychological distress to explain individual variance in initial symptom levels and symptom change over time. Higher symptom scores at pre-treatment were predictive of greater symptom improvement. Symptom improvement was greater in those who were off work on disability and those without higher post-secondary education. Clinical implications are discussed.