The Importance Of Online Psychological Interventions

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Online psychological interventions are growing rapidly in use (Spijkerman, Pots, & Bohlmeijer, 2016). Heralded for their ability to reduce the diagnosis to treatment gap, online interventions represent a step forward in mental health care. Such interventions allow for the large scale dissemination of treatment because of their ease of accessibility, relative low cost (Wang et al., 2005), and employment of anonymity (Leykin, Aguilera, Torres, Pérez-Stable, & Muñoz, 2012). Various OI’s have been shown to impact outcomes such as anxiety, depressive symptoms, and well-being (Pasarelu, Andersson, Nordgren, & Dobrean, 2016; Andersson & Titov, 2014; Andersson & Cuijpers, 2009; Muresan, Montgomery, & David, 2012; Spijkerman, Pots, & Bohlmeijer,…show more content…
Attrition Attrition remains a relevant problem in online interventions. One reason OI’s may have such large drop-out rates is the ease with which participants can quit the intervention. In laboratory studies participants are often required to reach out directly to researchers in order to remove themselves from the experiment. OI’s are usually freely accessible, and as such, are easy to sign up for, and easy to stop using. Eysenbach coined the term ‘the law of attrition’ to refer to the pattern that users in OI’s often drop out or cease using the application before completing the program (Eysenbach, 2005). Two types of attrition are common in open-access trials: dropout attrition (losing participants to follow up) and non-usage attrition (Eysenbach, 2005). ‘The law of attrition’ has been demonstrated time and time again in online interventions; with an average of 70% of users in an online CBT site failing to complete even one activity (Christensen, Griffiths, Mackinnon, & Brittliffe, 2006). Others have experienced similar low retention rates; Peter Farvolden and colleagues found that as few as 1% of users completed a full course of online therapy (Farvolden, Denisoff, Selby, Bagby, & Rudy, 2005). High attrition reduces the effectiveness of treatment for participants and leads to challenges in data analysis (Acacia; Eysenbach, 2005; Christensen, Griffiths, & Jorm, 2004). Schueller and Parks (2012) demonstrated high
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