Predicting outcome of internet-based treatment for depressive symptoms.

In this study we explored predictors and moderators of response to Internet-based cognitive behavioral therapy (CBT) and Internet-based problem-solving therapy (PST) for depressive symptoms. The sample consisted of 263 participants with moderate to severe depressive symptoms. Of those, 88 were randomized to CBT, 88 to PST and 87 to a waiting list control condition. Outcomes were improvement and clinically significant change in depressive symptoms after 8 weeks. Higher baseline depression and higher education predicted improvement, while higher education, less avoidance behavior and decreased rational problem-solving skills predicted clinically significant change across all groups. No variables were found that differentially predicted outcome between Internet-based CBT and Internet-based PST. More research is needed with sufficient power to investigate predictors and moderators of response to reveal for whom Internet-based therapy is best suited. © 2013 Copyright Society for Psychotherapy Research

Psychological treatment of depression: A meta-analytic database of randomized studies

Abstract Background A large number of randomized controlled studies have clearly demonstrated that psychological interventions are effective in the treatment of depression. The number of studies in this area is increasing rapidly. In this paper, we present a database of controlled and comparative outcome studies on psychological treatments of depression, based on a series of meta-analyses published by our group. The database can be accessed freely through the Internet. Description We conducted a comprehensive literature search of the major bibliographical databases (Pubmed; Psycinfo; Embase; Cochrane Central Register of Controlled Trials) and we examined the references of 22 earlier meta-analyses of psychological treatment of depression. We included randomized studies in which the effects of a psychological therapy on adults with depression were compared to a control condition, another psychological intervention, or a combined treatment (psychological plus pharmacological). We conducted nine meta-analyses of subgroups of studies taken from this dataset. The 149 studies included in these 9 meta-analyses are included in the current database. In the 149 included studies, a total of 11,369 patients participated. In the database, we present selected characteristics of each study, including characteristics of the patients (the study population, recruitment method, definition of depression); characteristics of the experimental conditions and interventions (the experimental conditions, N per condition, format, number of sessions); and study characteristics (measurement times, measures used, attrition, type of analysis and country). Conclusion The data on the 149 included studies are presented in order to give other researchers access to the studies we collected, and to give background information about the meta-analyses we have published using this dataset. The number of studies examining the effects of psychological treatments of depression has increased considerably in the past decades, and this will continue in the future. The database we have presented in this paper can help to integrate the results of these studies in future meta-analyses and systematic reviews on psychological treatments for depression

Recruiting participants for interventions to prevent the onset of depressive disorders: Possibile ways to increase participation rates

Background: Although indicated prevention of depression is available for about 80% of the Dutch population at little or no cost, only a small proportion of those with subthreshold depression make use of these services. Methods: A narrative review is conducted of the Dutch preventive services in mental health care, also addressing the problem of low participation rates. We describe possible causes of these low participation rates, which may be related to the participants themselves, the service system, and the communication to the public, and we put forward possible solutions to this problem. Results: There are three main groups of reasons why the participation rates are low: reasons within the participants (e.g., not considering themselves as being at risk; thinking the interventions are not effective; or being unwilling to participate because of the stigma associated with depression); reasons within the health care system; and reasons associated with the communication about the preventive services. Possible solutions to increasing the participation rate include organizing mass media campaigns, developing internet-based preventive interventions, adapting preventive interventions to the needs of specific subpopulations, positioning the services in primary care, integrating the interventions in community-wide interventions, and systematically screening high-risk groups for potential participants. Discussion: Prevention could play an important role in public mental health in reducing the enormous burden of depression. However, before this can be realized more research is needed to explore why participation rates are low and how these rates can be improved

Guided online treatment in routine mental health care: an observational study on uptake, drop-out and effects

<p>Abstract</p> <p>Background</p> <p>Due to limited resources patients in the Netherlands often have to wait for a minimum of six weeks after registration for mental health care to receive their first treatment session. Offering guided online treatment might be an effective solution to reduce waiting time and to increase patient outcomes at relatively low cost. In this study we report on uptake, drop-out and effects of online problem solving treatment that was implemented in a mental health center.</p> <p>Methods</p> <p>We studied all 104 consecutive patients aged 18–65 years with elevated symptoms of depression, anxiety and/or burnout who registered at the center during the first six months after implementation. They were offered a five week guided online treatment. At baseline, five weeks and twelve weeks we measured depressive (BDI-II), anxiety (HADS-A) and burnout symptoms (MBI).</p> <p>Results</p> <p>A total of 55 patients (53%) agreed to start with the online treatment. Patients who accepted the online treatment were more often female, younger and lower educated than those who refused. There were no baseline differences in clinical symptoms between the groups. There were large between group effect sizes after five weeks for online treatment for depression (<it>d</it> = 0.94) and anxiety (<it>d</it> = 1.07), but not for burnout (<it>d</it> = −.07). At twelve weeks, when both groups had started regular face-to-face treatments, we no longer found significant differences between the groups, except for anxiety (<it>d</it> = 0.69).</p> <p>Conclusion</p> <p>The results of this study show that the majority of patients prefer online guided online treatment instead of waiting for face-to-face treatment. Furthermore, online PST increases speed of recovery and can therefore be offered as a first step of treatment in mental healthcare.</p

Internet-based treatment for adults with depressive symptoms: the protocol of a randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>Depression is a highly prevalent condition, affecting more than 15% of the adult population at least once in their lives. Guided self-help is effective in the treatment of depression. The purpose of this study is to investigate the effectiveness of two Internet-based guided self-help treatments with adults reporting elevated depressive symptoms. Other research questions concern the identification of potential mediators and the search for subgroups who respond differently to the interventions.</p> <p>Methods</p> <p>This study is a randomized controlled trial with three conditions: two treatment conditions and one waiting list control group. The two treatment conditions are Internet-based cognitive behavior therapy and Internet-based problem-solving therapy. They consist of 8 and 5 weekly lessons respectively. Both interventions are combined with support by e-mail. Participants in the waiting list control group receive the intervention three months later.</p> <p>The study population consists of adults from the general population. They are recruited through advertisements in local and national newspapers and through banners on the Internet. Subjects with symptoms of depression (≥ 16 on the Center for Epidemiological Studies Depression scale) are included. Other inclusion criteria are having sufficient knowledge of the Dutch language, access to the Internet and an e-mail address.</p> <p>Primary outcome is depressive symptoms. Secondary outcomes are anxiety, quality of life, dysfunctional cognitions, worrying, problem solving skills, mastery, absence at work and use of healthcare. We will examine the following variables as potential mediators: dysfunctional cognitions, problem solving skills, worrying, anxiety and mastery. Potential moderating variables are: socio-demographic characteristics and symptom severity. Data are collected at baseline and at 5 weeks, 8 weeks, 12 weeks and 9 months after baseline. Analyses will be conducted on the intention-to-treat sample.</p> <p>Discussion</p> <p>This study evaluates two Internet-based treatments for depression, namely cognitive behavioral therapy and problem-solving therapy. The effectiveness of Internet-based problem-solving therapy suggest that this may be a worthwhile alternative to other more intensive treatment options. Strengths and limitations of this study are discussed.</p> <p>Trial registration</p> <p>Current Controlled Trials ISRCTN16823487</p

Characteristics of effective psychological treatments of depression: A metaregression analysis.

Although many meta-analyses have shown that psychological therapies are effective in the treatment of depression, no comprehensive metaregression analysis has been conducted to examine which characteristics of the intervention, target population, and study design are related to the effects. The authors conducted such a metaregression analysis with 83 studies (135 comparisons) in which a psychological treatment was compared with a control condition. The mean effect size of all comparisons was 0.69 (95% confidence interval = 0.60-0.79). In multivariate analyses, several variables were significant: Studies using problem-solving interventions and those aimed at women with postpartum depression or specific populations had higher effect sizes, whereas studies with students as therapists, those in which participants were recruited from clinical populations and through systematic screening, and those using care-as-usual or placebo control groups had lower effect sizes

Bias through selective inclusion and attrition: Representativeness when comparing provider performance with routine outcome monitoring data

Background: Observational research based on routine outcome monitoring is prone to missing data, and outcomes can be biased due to selective inclusion at baseline or selective attrition at posttest. As patients with complete data may not be representative of all patients of a provider, missing data may bias results, especially when missingness is not random but systematic. Methods: The present study establishes clinical and demographic patient variables relevant for representativeness of the outcome information. It applies strategies to estimate sample selection bias (weighting by inclusion propensity) and selective attrition bias (multiple imputation based on multilevel regression analysis) and estimates the extent of their impact on an index of provider performance. The association between estimated bias and response rate is also investigated. Results: Provider-based analyses showed that in current practice, the effect of selective inclusion was minimal, but attrition had a more substantial effect, biasing results in both directions: overstating and understating performance. For 22% of the providers, attrition bias was estimated to be in excess of 0.05 ES. Bias was associated with overall response rate (r =.50). When selective inclusion and attrition bring providers' response below 50%, it is more likely that selection bias increased beyond a critical level, and conclusions on the comparative performance of such providers may be misleading. Conclusions: Estimates of provider performance were biased by selection, especially by missing data at posttest. Results on the extent and direction of bias and minimal requirements for response rates to arrive at unbiased performance indicators are discussed

Comparing single-level and multilevel regression analysis for risk adjustment of treatment outcomes in common mental health disorders

Aim: The aim of this paper is to compare single-level and multilevel regression analysis to obtain risk-adjusted outcomes from mental health care providers. Subject and methods: The study population consisted of adult patients receiving treatment for common mental health disorders. The outcome was self-reported symptom level at post-test. Risk adjustment models were developed using single- and multilevel regression analysis. In the multilevel approach, a random intercept for each provider was included. The intraclass correlation coefficient was used to estimate the proportion of variability in treatment outcome between providers. Spearman correlation coefficient of ranks was used to compare results between the two approaches. Results: The effects of most casemix variables on outcomes were similar for the two models. The ranking of providers in both methods was also quite similar (ρ =.99). The multilevel model estimated that 5.4% of total variability in adjusted post-test scores was explained by the provider factor. Conclusions: The findings of risk adjustment of mental health outcomes are quite robust for the use of single-level or multilevel regression analysis in the current study. However, given the small but significant amount of variation in outcomes that is attributable to providers, the multilevel approach is recommended for dealing with outcomes when patients are clustered within providers

Satisfaction among Museum Visitors: The Holistic Approach Confirmed Empirical Evidence from the Anne Frank House Visitors

Abstract This paper examines whether a holistic element affected the valuations of visitors to the Anne Frank House, an en-site historical museum. The holistic approach views a museum as a whole entity and not as the sum of individual items. For the purposes of our research, we developed a new set of instruments, based on a literature survey and practical experience. We collected our data by interviewing over 2,000 visitors to the world-renowned Anne Frank House during 1998 and 1999. Our findings show that visitors clearly view this museum from a holistic perspective: overall satisfaction was greater than satisfaction regarding any individual items. In this respect, the holistic approach appeals especially to younger people, Europeans and people of higher educational backgrounds. While the conclusions of this research project apply exclusively to the Anne Frank House, the innovative approach used to measure visitor satisfaction can be applied to any en-site historica! museum or similar tourist attraction.Museums; Satisfaction; Consumer behaviour; Services

ICT4Depression: Service oriented architecture applied to the treatment of depression

FP7 ICT4Depression project aims at providing a set of tools to further improve both patient outcome and increase of access to treatment of the patients suffering from major depression. This article describes the Information Systems (IS) architecture used in the project. ICT4Depression uses a service oriented architecture as means of bringing together different kinds of information concerning the patient, the therapeutic modules he is advised to follow and the sensors used to assess his status