Predictors of Adherence by Adolescents to a Cognitive Behavior Therapy Website in School and Community-Based Settings

Abstract

Background There have been no previous studies of the variables that predict adherence to online depression and anxiety intervention programs among adolescents. However, research of traditionally delivered intervention programs for a variety of health conditions in adolescence suggests that health knowledge, type and level of symptomatology, race, socioeconomic status, treatment setting, and support may predict adherence. ObjectiveThe aim was to compare adherence rates and identify the predictors of adherence to a cognitive behavior therapy website in two adolescent samples that were offered the program in different settings and under different conditions of support. MethodsThe first adolescent sample consisted of 1000 school students who completed the MoodGYM program in a classroom setting over five weeks as part of a randomized controlled trial. The second sample consisted of 7207 adolescents who accessed the MoodGYM program spontaneously and directly through the open access URL. All users completed a brief survey before the start of the program that measured background characteristics, depression history, symptoms of depression and anxiety, and dysfunctional thinking. Results Adolescents in the school-based sample completed significantly more online exercises (mean = 9.38, SD = 6.84) than adolescents in the open access community sample (mean = 3.10, SD = 3.85; t1088.62 = −28.39, P < .001). A multiple linear regression revealed that school-based setting (P < .001) and female gender (P < .001) were predictive of greater adherence, as were living in a rural area (P < .001) and lower pre-test anxiety (P = .04) scores for the school-based sample and higher pre-test depression scores (P = .01) for the community sample. A history of depression (P = .33) and pre-test warpy thoughts scores (P = .35) were not predictive of adherence in the school-based or community sample. Conclusion Adherence is greater in monitored settings, and the predictors of adherence differ between settings. Understanding these differences may improve program effectiveness and efficiency.