Dataset Information

Trajectories of Change in an Open-access Internet-Based Cognitive Behavior Program for Childhood and Adolescent Anxiety: Open Trial.

ABSTRACT:

Background

Although evidence bolstering the efficacy of internet-based cognitive behavioral therapy (iCBT) for treating childhood anxiety has been growing continuously, there is scant empirical research investigating the timing of benefits made in iCBT programs (eg, early or delayed).

Objective

This study aims to examine the patterns of symptom trajectories (changes in anxiety) across an iCBT program for anxiety (BRAVE Self-Help).

Methods

This study's participants included 10,366 Australian youth aged 7 to 17 years (4140 children aged 7-12 years; 6226 adolescents aged 12-17 years) with elevated anxiety who registered for the BRAVE Self-Help program. Participants self-reported their anxiety symptoms at baseline or session 1 and then at the commencement of each subsequent session.

Results

The results show that young people completing the BRAVE Self-Help program tend to fall into two trajectory classes that can be reliably identified in terms of high versus moderate baseline levels of anxiety and subsequent reduction in symptoms. Both high and moderate anxiety severity trajectory classes showed significant reductions in anxiety, with the greatest level of change being achieved within the first six sessions for both classes. However, those in the moderate anxiety severity class tended to show reductions in anxiety symptoms to levels below the elevated range, whereas those in the high symptom group tended to remain in the elevated range despite improvements.

Conclusions

These findings suggest that those in the high severity group who do not respond well to iCBT on a self-help basis may benefit from the additional support provided alongside the program or a stepped-care approach where progress is monitored and support can be provided as necessary.

SUBMITTER: March S

PROVIDER: S-EPMC8277375 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundHealth education can benefit people with chronic diseases. However, in previous research those benefits were small, and reinforcement to maintain them was not effective. A possible explanation is that the benefits appeared to be small and reinforcement appeared to be ineffective because those analyses mixed data from two latent groups: one group of people who needed reinforcement and one group of people who did not. The hypothesis is that mixing the data from those two different groups caused the true effects to be "diluted."MethodsTo test that hypothesis we used data from the Chronic Disease Self-Management Program in Japan, focusing on anxiety, depression, and patient-physician communication. To identify latent trajectories of change after the program, we used growth-mixture modeling. Then, to find out which baseline factors were associated with trajectory-group membership, we used logistic regression.ResultsGrowth-mixture modeling revealed two trajectories-two groups that were defined by distinct patterns of change after the program. One of those patterns was improvement followed by backsliding: decay of impact. On anxiety and depression the decay of impact was large enough to be clinically important, and its prevalence was as high as 50%. Next, logistic regression analysis revealed that being in the decay-of-impact group could be predicted from multimorbidity, low self-efficacy, and high scores on anxiety or depression at baseline. In addition, one unexpected finding was an association between multimorbidity and better patient-physician communication.ConclusionsThese results support the hypothesis that previous findings (i.e., apparently small effect sizes and apparently ineffective reinforcement) actually reflect "dilution" of large effects, which was caused by mixing of data from distinct groups. Specifically, there was one group with decay of impact and one without. Thus, evaluations of health education should include analyses of trajectory-defined groups. These results show how the group of people who are most likely to need reinforcement can be identified even before the educational program begins. Extra attention and reinforcement can then be tailored. They can be focused specifically to benefit the people with the greatest need.