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Research shows that online unguided self-help interventions focused on psycho-education, skills training and lifestyle can prevent mild mood complaints from turning into a full-blown depression. These encouraging results are found even though the adherence to these types of interventions is generally low.
With this project, the investigators examine whether effectiveness and adherence to online unguided self-help interventions can be increased by additional motivational guidance elements. This is examined by adding three additional components to the intervention: 1) A coach who provides online feedback once a week to provide support. 2) Mobile application to monitor mood and related factors and to receive automated personalized messages, 3) Content based on the principles of motivational interviewing. A secondary aim is to compare the additional effects of the individual components against the additional costs.
Full description
Given the substantial prevalence rate of Major Depression and its extreme burden among the general population, depression prevention is a high priority on the Dutch public health agenda. The aim of the Depression Prevention Program of the Dutch Ministry of Health, Welfare and Sport (Meerjarenprogramma (MJP, VWS 2017) entails a decrease in major depression prevalence of 30% by the year 2030. One solution to the problem is to offer online self-help interventions focusing on psycho-education, skills-training and lifestyle with the aim to improve mood. These interventions have proven to be effective and can prevent mood problems to sustain and/or worsen (van Zoonen et al., 2014). Self-help interventions are easily accessible and acceptable, and they can reach a population at low costs and on a large scale (Riper et al. 2010).
Still, while online self-help interventions can be effective (Karyotaki et al., 2017), engagement barriers exist, adherence rates are generally low, and integration into daily life routines is difficult to achieve (Karyotaki et al., 2015), which may jeopardize the potential population health impact of these interventions. From this perspective there is a clear optimization need of evidence-based online self-help interventions to increase their impact on the general population. One way to increase adherence and engagement, and subsequently the effectiveness of such interventions, is to administer the intervention with the help of (motivational) guidance elements. Guided interventions are known to increase adherence, engagement and effectiveness of interventions and can be operationalized in various ways (Mohr, Cuijpers & Lehman, 2011; Kelders, 2017). Examples for types of guidance are human coaches, computerized coaches, chat support functions, personalized messages, and many more. While those motivational guidance elements can help the self-help interventions effectiveness, they come with higher costs as they need, for example, an infrastructure of therapists or coaches. It is therefore of high value to find the optimal balance between the effectiveness of the intervention and the necessary support components to establish a product with the potential to be implemented at scale.
The first objective of this study is to examine whether the effectiveness of an online self-help intervention ("Moodbuster Life") for adults who want to improve their mood can be optimized by three different motivational guidance components. The motivational components are: 1) A coach who provides online feedback once a week to provide support. 2) Mobile application to monitor mood and related factors and to receive automated personalized messages, 3) Content based on the principles of motivational interviewing.
Secondary aims are (1) to investigate whether adherence to the online self-help intervention can be improved by three different motivational components and (2) to compare the additional effects of one component against additional costs defined as extra time investment (in the platform and beyond) and financial costs (service costs, costs incurred by participants).
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307 participants in 8 patient groups
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Claire van Genugten, Phd
Data sourced from clinicaltrials.gov
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