Predicting engagement with an online psychosocial intervention for psychosis: Exploring individual- and intervention-level predictors

• Published in: Internet Interventions
• Main Authors: Chelsea Arnold, Kristi-Ann Villagonzalo, Denny Meyer, John Farhall, Fiona Foley, Michael Kyrios, Neil Thomas
• Format: Article
• Language: English
• Published: Elsevier 2019-12-01
• Online Access: http://www.sciencedirect.com/science/article/pii/S221478291930034X

Background: Individuals with psychosis demonstrate positive attitudes towards utilising digital technology in mental health treatment. Although preliminary research suggests digital interventions are feasible and acceptable in this population, little is known about how to best promote engagement with these resources. Candidate predictors include therapist support, sources of motivation and recovery style. Understanding what factors predict engagement will aid more effective design and implementation of digital interventions to improve clinical benefits. Objective: This study aimed to investigate demographic, psychological, and treatment variables that predict overall and type of engagement with a psychosocial, online intervention for individuals with psychosis. Methods: Ninety-eight participants with a history of psychosis were given access to a web program containing modules on self-management and recovery, which they were asked to use flexibly at their own pace. Activity was automatically logged by the system. Baseline measures of demographics, recovery style and motivation were administered, and participants were randomised to receive either website access alone, or website access plus weekly, asynchronous emails from an online coach over 12 weeks. Log and baseline assessment data were used in negative binomial regressions to examine predictors of depth and breadth of use over the intervention period. A logistic regression was used to examine the impact of predictor variables on usage profiles (active or passive). Results: Depth and breadth of engagement were positively predicted by receiving email support, low levels of externally controlled motivations for website use, older age, and having a tertiary education. There was a significant interaction between level of controlled motivation and condition (+/−email) on breadth and depth of engagement: receiving asynchronous emails was associated with increased engagement for individuals with low, but not high, levels of externally controlled motivations. Receiving email support and more autonomous motivations for treatment predicted more active use of the website. Conclusions: Asynchronous email support can promote engagement with online interventions for individuals with psychosis, potentially enabling self-management of illness and improving clinical outcomes. However, those using online interventions due to external motivating factors, may have low levels of engagement with the intervention, irrespective of coaching provided. These findings may guide design and implementation of future online interventions in this population. Keywords: Digital technology, Digital mental health, Engagement, Intervention, Psychosis