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Web-Based Fully Automated Self-Help With Different Levels of Therapist Support for Individuals With Eating Disorder Symptoms: A Randomized Controlled Trial

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      Abstract

      BackgroundDespite the disabling nature of eating disorders (EDs), many individuals with ED symptoms do not receive appropriate mental health care. Internet-based interventions have potential to reduce the unmet needs by providing easily accessible health care services.ObjectiveThis study aimed to investigate the effectiveness of an Internet-based intervention for individuals with ED symptoms, called “Featback.” In addition, the added value of different intensities of therapist support was investigated.MethodsParticipants (N=354) were aged 16 years or older with self-reported ED symptoms, including symptoms of anorexia nervosa, bulimia nervosa, and binge eating disorder. Participants were recruited via the website of Featback and the website of a Dutch pro-recovery–focused e-community for young women with ED problems. Participants were randomized to: (1) Featback, consisting of psychoeducation and a fully automated self-monitoring and feedback system, (2) Featback supplemented with low-intensity (weekly) digital therapist support, (3) Featback supplemented with high-intensity (3 times a week) digital therapist support, and (4) a waiting list control condition. Internet-administered self-report questionnaires were completed at baseline, post-intervention (ie, 8 weeks after baseline), and at 3- and 6-month follow-up. The primary outcome measure was ED psychopathology. Secondary outcome measures were symptoms of depression and anxiety, perseverative thinking, and ED-related quality of life. Statistical analyses were conducted according to an intent-to-treat approach using linear mixed models.ResultsThe 3 Featback conditions were superior to a waiting list in reducing bulimic psychopathology (d=−0.16, 95% confidence interval (CI)=−0.31 to −0.01), symptoms of depression and anxiety (d=−0.28, 95% CI=−0.45 to −0.11), and perseverative thinking (d=−0.28, 95% CI=−0.45 to −0.11). No added value of therapist support was found in terms of symptom reduction although participants who received therapist support were significantly more satisfied with the intervention than those who did not receive supplemental therapist support. No significant differences between the Featback conditions supplemented with low- and high-intensity therapist support were found regarding the effectiveness and satisfaction with the intervention.ConclusionsThe fully automated Internet-based self-monitoring and feedback intervention Featback was effective in reducing ED and comorbid psychopathology. Supplemental therapist support enhanced satisfaction with the intervention but did not increase its effectiveness. Automated interventions such as Featback can provide widely disseminable and easily accessible care. Such interventions could be incorporated within a stepped-care approach in the treatment of EDs and help to bridge the gap between mental disorders and mental health care services.Trial RegistrationNetherlands Trial Registry: NTR3646; http://www.trialregister.nl/trialreg/admin/ rctview.asp?TC=3646 (Archived by WebCite at http://www.webcitation.org/6fgHTGKHE)

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      Most cited references 52

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      Statistical procedures for missing data have vastly improved, yet misconception and unsound practice still abound. The authors frame the missing-data problem, review methods, offer advice, and raise issues that remain unresolved. They clear up common misunderstandings regarding the missing at random (MAR) concept. They summarize the evidence against older procedures and, with few exceptions, discourage their use. They present, in both technical and practical language, 2 general approaches that come highly recommended: maximum likelihood (ML) and Bayesian multiple imputation (MI). Newer developments are discussed, including some for dealing with missing data that are not MAR. Although not yet in the mainstream, these procedures may eventually extend the ML and MI methods that currently represent the state of the art.
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        The prevalence and correlates of eating disorders in the National Comorbidity Survey Replication.

        Little population-based data exist on the prevalence or correlates of eating disorders. Prevalence and correlates of eating disorders from the National Comorbidity Replication, a nationally representative face-to-face household survey (n = 9282), conducted in 2001-2003, were assessed using the WHO Composite International Diagnostic Interview. Lifetime prevalence estimates of DSM-IV anorexia nervosa, bulimia nervosa, and binge eating disorder are .9%, 1.5%, and 3.5% among women, and .3% .5%, and 2.0% among men. Survival analysis based on retrospective age-of-onset reports suggests that risk of bulimia nervosa and binge eating disorder increased with successive birth cohorts. All 3 disorders are significantly comorbid with many other DSM-IV disorders. Lifetime anorexia nervosa is significantly associated with low current weight (body-mass index or =40). Although most respondents with 12-month bulimia nervosa and binge eating disorder report some role impairment (data unavailable for anorexia nervosa since no respondents met criteria for 12-month prevalence), only a minority of cases ever sought treatment. Eating disorders, although relatively uncommon, represent a public health concern because they are frequently associated with other psychopathology and role impairment, and are frequently under-treated.
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          Internet-based cognitive behaviour therapy for symptoms of depression and anxiety: a meta-analysis.

          We studied to what extent internet-based cognitive behaviour therapy (CBT) programs for symptoms of depression and anxiety are effective. A meta-analysis of 12 randomized controlled trials. The effects of internet-based CBT were compared to control conditions in 13 contrast groups with a total number of 2334 participants. A meta-analysis on treatment contrasts resulted in a moderate to large mean effect size [fixed effects analysis (FEA) d=0.40, mixed effects analysis (MEA) d=0.60] and significant heterogeneity. Therefore, two sets of post hoc subgroup analyses were carried out. Analyses on the type of symptoms revealed that interventions for symptoms of depression had a small mean effect size (FEA d=0.27, MEA d=0.32) and significant heterogeneity. Further analyses showed that one study could be regarded as an outlier. Analyses without this study showed a small mean effect size and moderate, non-significant heterogeneity. Interventions for anxiety had a large mean effect size (FEA and MEA d=0.96) and very low heterogeneity. When examining the second set of subgroups, based on therapist assistance, no significant heterogeneity was found. Interventions with therapist support (n=5) had a large mean effect size, while interventions without therapist support (n=6) had a small mean effect size (FEA d=0.24, MEA d=0.26). In general, effect sizes of internet-based interventions for symptoms of anxiety were larger than effect sizes for depressive symptoms; however, this might be explained by differences in the amount of therapist support.
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            Author and article information

            Affiliations
            1Rivierduinen Eating Disorders Ursula LeidenNetherlands
            2Institute of Psychology, Leiden University LeidenNetherlands
            3Leiden University Medical Center Department of Psychiatry LeidenNetherlands
            4Institute of Education and Child Studies, Leiden University LeidenNetherlands
            Author notes
            Corresponding Author: Jiska J. Aardoom j.aardoom@ 123456rivierduinen.nl
            Contributors
            , ORCID: http://orcid.org/0000-0002-4023-6814
            Journal
            J Med Internet Res
            J. Med. Internet Res
            JMIR
            Journal of Medical Internet Research
            JMIR Publications (Toronto, Canada )
            1439-4456
            1438-8871
            June 2016
            17 June 2016
            : 18
            : 6
            27317358
            4930527
            v18i6e159
            10.2196/jmir.5709
            (Editor), (Reviewer), (Reviewer), (Reviewer), (Reviewer), (Reviewer), (Reviewer), (Reviewer), (Reviewer), (Reviewer),
            ©Jiska J. Aardoom, Alexandra E. Dingemans, Philip Spinhoven, Joost R. van Ginkel, Mark de Rooij, Eric F. van Furth. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 17.06.2016.

            This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0/), 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 http://www.jmir.org/, as well as this copyright and license information must be included.

            Categories
            Original Paper
            Original Paper

            Medicine

            ehealth, eating disorders, internet-based, therapist support, self-monitoring, self-help

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