Adherence in internet interventions for anxiety and depression.
ABSTRACT Open access websites which deliver cognitive and behavioral interventions for anxiety and depression are characterised by poor adherence. We need to understand more about adherence in order to maximize the impact of Internet-based interventions on the disease burden associated with common mental disorders.
The aims of this paper are to review briefly the adherence literature with respect to Internet interventions and to investigate the rates of dropout and compliance in randomized controlled trials of anxiety and depression Web studies.
A systematic review of randomized controlled trials using Internet interventions for anxiety and depression was conducted, and data was collected on dropout and adherence, predictors of adherence, and reasons for dropout.
Relative to reported rates of dropout from open access sites, the present study found that the rates of attrition in randomized controlled trials were lower, ranging from approximately 1 - 50%. Predictors of adherence included disease severity, treatment length, and chronicity. Very few studies formally examined reasons for dropout, and most studies failed to use appropriate statistical techniques to analyze missing data.
Dropout rates from randomized controlled trials of Web interventions are low relative to dropout from open access websites. The development of theoretical models of adherence is as important in the area of Internet intervention research as it is in the behavioral health literature. Disease-based factors in anxiety and depression need further investigation.
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ABSTRACT: Although relatively new, the field of e-mental health is becoming more popular with more attention given to researching its various aspects. However, there are many areas that still need further research, especially identifying attrition predictors at various phases of assessment and treatment delivery.Journal of Medical Internet Research 01/2014; 16(10):e232. · 4.67 Impact Factor
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ABSTRACT: A number of psychoeducational programs based on cognitive behavioral therapy (CBT) to alleviate psychological distress have been developed for implementation in clinical settings. However, while these programs are considered critical components of stress management education in a workplace setting, they are required to be brief and simple to implement, which can hinder development. The intent of the study was to examine the effects of a brief training program based on CBT in alleviating psychological distress among employees and facilitating self-evaluation of stress management skills, including improving the ability to recognize dysfunctional thinking patterns, transform dysfunctional thoughts to functional ones, cope with stress, and solve problems. Of the 187 employees at an information technology company in Tokyo, Japan, 168 consented to participate in our non-blinded randomized controlled study. The training group received CBT group education by a qualified CBT expert and 1 month of follow-up Web-based CBT homework. The effects of this educational program on the psychological distress and stress management skills of employees were examined immediately after completion of training and then again after 6 months. Although the training group did exhibit lower mean scores on the Kessler-6 (K6) scale for psychological distress after 6 months, the difference from the control group was not significant. However, the ability of training group participants to recognize dysfunctional thinking was significantly improved both immediately after training completion and after 6 months. While the ability of participants to cope with stress was not significantly improved immediately after training, improvement was noted after 6 months in the training group. No notable improvements were observed in the ability of participants to transform thoughts from dysfunctional to functional or in problem-solving skills. A sub-analysis of participants who initially exhibited clinically significant psychological distress (K6 score ≥5) showed that the mean K6 score was significantly improved immediately after training completion for the training group compared to the control group (-2.50 vs -0.07; mean difference 2.43, 95% CI 0.55-4.31; d=0.61), with this effect remaining even after 6 months (-3.49 vs -0.50; mean difference 2.99, 95% CI 0.70-5.29; d=0.60). Our results suggest that a brief stress management program that combines group CBT education with Web-based CBT homework moderately alleviates the distress of employees with clinically significant psychological distress. In addition, the program might help improve employees' ability to evaluate their own stress management skills.JMIR research protocols. 01/2014; 3(4):e70.
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ABSTRACT: Engagement has emerged as a significant cross-cutting concern within the development of Web-based interventions. There have been calls to institute a more rigorous approach to the design of Web-based interventions, to increase both the quantity and quality of engagement. One approach would be to use log-data to better understand the process of engagement and patterns of use. However, an important challenge lies in organizing log-data for productive analysis. Our aim was to conduct an initial exploration of the use of visualizations of log-data to enhance understanding of engagement with Web-based interventions. We applied exploratory sequential data analysis to highlight sequential aspects of the log data, such as time or module number, to provide insights into engagement. After applying a number of processing steps, a range of visualizations were generated from the log-data. We then examined the usefulness of these visualizations for understanding the engagement of individual users and the engagement of cohorts of users. The visualizations created are illustrated with two datasets drawn from studies using the SilverCloud Platform: (1) a small, detailed dataset with interviews (n=19) and (2) a large dataset (n=326) with 44,838 logged events. We present four exploratory visualizations of user engagement with a Web-based intervention, including Navigation Graph, Stripe Graph, Start-Finish Graph, and Next Action Heat Map. The first represents individual usage and the last three, specific aspects of cohort usage. We provide examples of each with a discussion of salient features. Log-data analysis through data visualization is an alternative way of exploring user engagement with Web-based interventions, which can yield different insights than more commonly used summative measures. We describe how understanding the process of engagement through visualizations can support the development and evaluation of Web-based interventions. Specifically, we show how visualizations can (1) allow inspection of content or feature usage in a temporal relationship to the overall program at different levels of granularity, (2) detect different patterns of use to consider personalization in the design process, (3) detect usability issues, (4) enable exploratory analysis to support the design of statistical queries to summarize the data, (5) provide new opportunities for real-time evaluation, and (6) examine assumptions about interactivity that underlie many summative measures in this field.Journal of Medical Internet Research 01/2014; 16(11):e252. · 4.67 Impact Factor