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      e-CBT (myCompass), Antidepressant Medication, and Face-to-Face Psychological Treatment for Depression in Australia: A Cost-Effectiveness Comparison

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          The economic cost of depression is becoming an ever more important determinant for health policy and decision makers. Internet-based interventions with and without therapist support have been found to be effective options for the treatment of mild to moderate depression. With increasing demands on health resources and shortages of mental health care professionals, the integration of cost-effective treatment options such as Internet-based programs into primary health care could increase efficiency in terms of resource use and costs.


          Our aim was to evaluate the cost-effectiveness of an Internet-based intervention (myCompass) for the treatment of mild-to-moderate depression compared to treatment as usual and cognitive behavior therapy in a stepped care model.


          A decision model was constructed using a cost utility framework to show both costs and health outcomes. In accordance with current treatment guidelines, a stepped care model included myCompass as the first low-intervention step in care for a proportion of the model cohort, with participants beginning from a low-intensity intervention to increasing levels of treatment. Model parameters were based on data from the recent randomized controlled trial of myCompass, which showed that the intervention reduced symptoms of depression, anxiety, and stress and improved work and social functioning for people with symptoms in the mild-to-moderate range.


          The average net monetary benefit (NMB) was calculated, identifying myCompass as the strategy with the highest net benefit. The mean incremental NMB per individual for the myCompass group was AUD 1165.88 compared to treatment as usual and AUD 522.58 for the cognitive behavioral therapy model.


          Internet-based interventions can provide cost-effective access to treatment when provided as part of a stepped care model. Widespread dissemination of Internet-based programs can potentially reduce demands on primary and tertiary services and reduce unmet need.

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          Most cited references 73

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          Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: implications for clinical practice.

          Selective serotonin reuptake inhibitors (SSRIs) are widely used to treat depression, but the rates, timing, and baseline predictors of remission in "real world" patients are not established. The authors' primary objectives in this study were to evaluate the effectiveness of citalopram, an SSRI, using measurement-based care in actual practice, and to identify predictors of symptom remission in outpatients with major depressive disorder. This clinical study included outpatients with major depressive disorder who were treated in 23 psychiatric and 18 primary care "real world" settings. The patients received flexible doses of citalopram prescribed by clinicians for up to 14 weeks. The clinicians were assisted by a clinical research coordinator in the application of measurement-based care, which included the routine measurement of symptoms and side effects at each treatment visit and the use of a treatment manual that described when and how to modify medication doses based on these measures. Remission was defined as an exit score of or=50% in baseline QIDS-SR score. Nearly 80% of the 2,876 outpatients in the analyzed sample had chronic or recurrent major depression; most also had a number of comorbid general medical and psychiatric conditions. The mean exit citalopram dose was 41.8 mg/day. Remission rates were 28% (HAM-D) and 33% (QIDS-SR). The response rate was 47% (QIDS-SR). Patients in primary and psychiatric care settings did not differ in remission or response rates. A substantial portion of participants who achieved either response or remission at study exit did so at or after 8 weeks of treatment. Participants who were Caucasian, female, employed, or had higher levels of education or income had higher HAM-D remission rates; longer index episodes, more concurrent psychiatric disorders (especially anxiety disorders or drug abuse), more general medical disorders, and lower baseline function and quality of life were associated with lower HAM-D remission rates. The response and remission rates in this highly generalizable sample with substantial axis I and axis III comorbidity closely resemble those seen in 8-week efficacy trials. The systematic use of easily implemented measurement-based care procedures may have assisted in achieving these results.
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            Computer Therapy for the Anxiety and Depressive Disorders Is Effective, Acceptable and Practical Health Care: A Meta-Analysis

            Background Depression and anxiety disorders are common and treatable with cognitive behavior therapy (CBT), but access to this therapy is limited. Objective Review evidence that computerized CBT for the anxiety and depressive disorders is acceptable to patients and effective in the short and longer term. Method Systematic reviews and data bases were searched for randomized controlled trials of computerized cognitive behavior therapy versus a treatment or control condition in people who met diagnostic criteria for major depression, panic disorder, social phobia or generalized anxiety disorder. Number randomized, superiority of treatment versus control (Hedges g) on primary outcome measure, risk of bias, length of follow up, patient adherence and satisfaction were extracted. Principal Findings 22 studies of comparisons with a control group were identified. The mean effect size superiority was 0.88 (NNT 2.13), and the benefit was evident across all four disorders. Improvement from computerized CBT was maintained for a median of 26 weeks follow-up. Acceptability, as indicated by adherence and satisfaction, was good. Research probity was good and bias risk low. Effect sizes were non-significantly higher in comparisons with waitlist than with active treatment control conditions. Five studies comparing computerized CBT with traditional face-to-face CBT were identified, and both modes of treatment appeared equally beneficial. Conclusions Computerized CBT for anxiety and depressive disorders, especially via the internet, has the capacity to provide effective acceptable and practical health care for those who might otherwise remain untreated. Trial Registration Australian New Zealand Clinical Trials Registry ACTRN12610000030077
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              Computer-based psychological treatments for depression: a systematic review and meta-analysis.

              The aim of the paper was to systematically review the literature on computer-based psychological treatments for depression and conduct a meta-analysis of the RCT studies, including examining variables which may effect outcomes. Database and hand searches were made using specific search terms and inclusion criteria. The review included a total of 40 studies (45 published papers), and 19 RCTs (23 published papers) were included in a standard meta-analysis. The review describes the different computer-based treatments for depression, their design, communication types employed: synchronous, asynchronous, and face-to-face (F:F); alongside various types and frequency of support delivered. The evidence supports their effectiveness and highlights participant satisfaction. However, pertinent limitations are noted. Across 19 studies the meta-analysis revealed a moderate post-treatment pooled effect size d=.56 (95% confidence interval [CI] -.71, -.41), Z=7.48, p<.001). Supported interventions yielded better outcomes, along with greater retention. The results reported statistically significant clinical improvement and recovery post-treatment. The review and meta-analysis support the efficacy and effectiveness of computer-based psychological treatments for depression, in diverse settings and with different populations. Further research is needed, in particular to investigate the influence of therapist factors in supported treatments, the reasons for dropout, and the maintenance of gains post-treatment. Copyright © 2012 Elsevier Ltd. All rights reserved.

                Author and article information

                J Med Internet Res
                J. Med. Internet Res
                Journal of Medical Internet Research
                JMIR Publications Inc. (Toronto, Canada )
                November 2015
                11 November 2015
                : 17
                : 11
                1Black Dog Institute University of New South Wales SydneyAustralia
                Author notes
                Corresponding Author: Daniela Solomon d.solomon@
                ©Daniela Solomon, Judith Proudfoot, Janine Clarke, Helen Christensen. Originally published in the Journal of Medical Internet Research (, 11.11.2015.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on, as well as this copyright and license information must be included.

                Original Paper
                Original Paper


                computer-assisted therapy, self-help, depression, cost-utility analysis


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