The association between adherence and outcome in an Internet intervention for depression

Fuhr, K; Schröder, Johanna; Berger, Thomas; Moritz, Steffen; Meyer, Björn; Lutz, Wolfgang; Hohagen, Fritz; Hautzinger, Martin; Klein, Jan Philipp

doi:10.1016/j.jad.2017.12.028

Cited by 84 publications

(78 citation statements)

References 48 publications

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“…In one study that involved weekly email contacts with clinicians, the dropout rate was zero as every participant completed postintervention assessments, whereas in another study of mostly male slot machine gamblers with comorbid depression, a dropout rate as high as 56% was reported. A previous individual patient meta-analysis that included data from several deprexis studies suggested that male gender, lower educational level and comorbid anxiety predicted dropout risk [46], whereas a large deprexis trial showed that older age and greater depressive symptom severity were associated with reduced dropout risk [47]. Despite these intriguing emerging findings, more research is needed to illuminate the factors that predict adherence and dropout risk.…”

Section: Comparisons With Other Studiesmentioning

confidence: 99%

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Effectiveness of a tailored, integrative Internet intervention (deprexis) for depression: Updated meta-analysis

et al. 2020

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Digitally delivered interventions for depression vary in many aspects, including their therapeutic orientation, depth of content, interactivity, individual tailoring, inclusion of multimedia, cost, and effectiveness. However, their effectiveness is rarely examined in intervention-specific meta-analyses. An earlier meta-analysis of eight randomized controlled trials (RCT) demonstrated the effectiveness of a tailored, integrative digital intervention (deprexis), which is delivered via the Internet. This updated meta-analysis of twelve deprexis-specific RCT with a total of N = 2901 participants confirmed the effectiveness of deprexis for depression reduction at post-intervention (g = 0.51, 95% CI: 0.40-0.62, I 2 = 26%). Results were analogous when study quality, screening and randomization procedure were taken into account. Clinician guidance, developer-involvement, setting (community vs. clinical), and initial symptom severity did not have statistically significant effects on the effect size, and there was no evidence of publication bias. Thus, these findings demonstrate that deprexis can facilitate clinically relevant reduction of depressive symptoms over 8-12 weeks across a broad range of initial symptom severity, and that the intervention can be combined with other forms of depression treatment. There is now a need to study the intervention's implementation in routine care settings as well as its long-term effectiveness and cost-effectiveness in diverse cultural and linguistic settings.Funding: Funding Statement: Gaia AG, Hamburg, provided support in the form of salaries for authors [B.M. and O.B.], but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the Despite such encouraging findings, caution is warranted for several reasons, and sweeping conclusions suggesting that all Internet interventions for depression are effective would be misguided. Of note, meta-analytic evidence showing that such interventions are effective on average does not mean that these interventions are all equally effective or, indeed, that any one intervention is effective at all. Internet interventions for depression differ substantially in their accessibility, therapeutic orientation, depth of content, interactivity, individual tailoring, inclusion of multimedia, self-monitoring tools, homework assignments, and cost [4]. Worryingly, many such interventions for depression are not evidence-based because they are never evaluated in randomized clinical trials (RCTs); this was the case for 20 out of 32 identified programs in a recent review [4].Given this substantial heterogeneity among Internet interventions for depression, one might expect that they also differ in terms of their effectiveness, although head-to-head trials are rare. In one large trial that included two Internet interventions for depression (Beating the Blues and MoodGYM), neither of them was effective when added to primary care in the United Kingdom [5]. A recent meta-analysis of self-guided depressio...

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Section: Comparisons With Other Studiesmentioning

confidence: 99%

“…Emerging evidence suggests that deprexis can be cost effective in the sense that its use may reduce the need for other costly treatments over time [48,49]. Additionally, more is becoming known about treatment moderators, mediators, response predictors and patterns of change [50][51][52][53][54].…”

Section: Implications For Clinical Practice and Researchmentioning

confidence: 99%

Effectiveness of a tailored, integrative Internet intervention (deprexis) for depression: Updated meta-analysis

et al. 2020

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“…Evidence from Internet‐based group CBT in BN indicated that dropout was predicted by treatment motivation (Watson et al, ). In GSH‐I for patients with eating disorder symptoms, improvements of the motivational state of change were predicted by high levels of patients' adherence (Leung, Ma, & Russell, ), operationalized as the frequency of utilizing specific treatment components (Donkin et al, ; Fuhr et al, ). At the same time, adherence was positively associated with better quality of life after GSH‐I for adults with BED (Carrard et al, ) and predicted decreased eating disorder psychopathology following an Internet‐based prevention program for women with bulimic symptoms (Manwaring et al, ).…”

Section: Introductionmentioning

confidence: 99%

Adherence as a predictor of dropout in Internet‐based guided self‐help for adults with binge‐eating disorder and overweight or obesity

Puls

Schmidt

Herpertz

et al. 2019

Intl J Eating Disorders

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Objective: Internet-based guided self-help (GSH-I) is an efficacious treatment for adults with binge-eating disorder (BED) and overweight or obesity. Although broadly accessible, high dropout from GSH-I has been reported. However, little is known about the factors explaining dropout from GSH-I, including patients' adherence to treatment.Method: Within a randomized trial on the treatment of BED, adherence to 4-month GSH-I was objectively assessed in N = 89 patients with BED and overweight or obesity. Objective adherence and subjective treatment evaluation were evaluated as predictors of dropout from GSH-I, defined as having accessed 5 or less of 11 modules.Cutoffs with optimal sensitivity and specificity were derived using Receiver Operating Characteristics curves analysis, and baseline sociodemographic and clinical correlates were determined.Results: According to our definition, n = 22 (24.7%) patients were defined as dropouts. Results of the full logistic regression model accounted for 72% of the variance in dropout and all objective adherence parameters (i.e., number of messages exchanged, days with a completed food diary, and days spent per module), but not patients' subjective GSH-I evaluation significantly predicted dropout. Specifically, not completing the food diary in week 7 had maximized sensitivity and specificity in predicting dropout. Patients' body mass index was positively associated with the number of messages exchanged between patients and coaches. No other associations between baseline variables and objective adherence were found.Martina de Zwaan and Anja Hilbert contributed equally to this study.

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“…Dropout rates for Web-based interventions are up to 50% in guided interventions and up to 74% in unguided interventions [6,7]. With such high dropout rates, these interventions may provide only limited outcomes regardless of their proven efficacy [8,9]. …”

Section: Introductionmentioning

confidence: 99%

A Process Evaluation of a Web-Based Mental Health Portal (WalkAlong) Using Google Analytics

et al. 2018

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BackgroundDespite the increasing amount of research on Web-based mental health interventions with proven efficacy, high attrition rates decrease their effectiveness. Continued process evaluations should be performed to maximize the target population’s engagement. Google Analytics has been used to evaluate various health-related Web-based programs and may also be useful for Web-based mental health programs.ObjectiveThe objective of our study was to evaluate WalkAlong.ca, a youth-oriented mental health web-portal, using Google Analytics to inform the improvement strategy for the platform and to demonstrate the use of Google Analytics as a tool for process evaluation of Web-based mental health interventions.MethodsGoogle Analytics was used to monitor user activity during WalkAlong’s first year of operation (Nov 13, 2013-Nov 13, 2014). Selected Google Analytic variables were overall website engagement including pages visited per session, utilization rate of specific features, and user access mode and location.ResultsThe results included data from 3076 users viewing 29,299 pages. Users spent less average time on Mindsteps (0 minute 35 seconds) and self-exercises (1 minute 08 seconds), which are important self-help tools, compared with that on the Screener tool (3 minutes 4 seconds). Of all visitors, 82.3% (4378/5318) were desktop users, followed by 12.7 % (677/5318) mobile phone and 5.0% (263/5318) tablet users. Both direct traffic (access via URL) and referrals by email had more than 7 pages viewed per session and longer than average time of 6 minutes per session. The majority of users (67%) accessed the platform from Canada.ConclusionsEngagement and feature utilization rates are higher among people who receive personal invitations to visit the site. Low utilization rates with specific features offer a starting place for further exploration of users in order to identify the root cause. The data provided by Google Analytics, although informative, can be supplemented by other evaluation methods (ie, qualitative methods) in order to better determine the modifications required to improve user engagement. Google Analytics can play a vital role in highlighting the preferences of those using Web-based mental health tools.

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The association between adherence and outcome in an Internet intervention for depression

Cited by 84 publications

References 48 publications

Effectiveness of a tailored, integrative Internet intervention (deprexis) for depression: Updated meta-analysis

Effectiveness of a tailored, integrative Internet intervention (deprexis) for depression: Updated meta-analysis

Adherence as a predictor of dropout in Internet‐based guided self‐help for adults with binge‐eating disorder and overweight or obesity

A Process Evaluation of a Web-Based Mental Health Portal (WalkAlong) Using Google Analytics

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