BACKGROUND
Mental health and alcohol use problems are among the most common causes of disease burden in young Australians and lead to significant lifetime burden. Yet comorbidity remains significantly underdetected and undertreated in health settings. Digital mental health tools designed to identify at-risk individuals, encourage help-seeking or deliver treatment for comorbidity, have the potential to address this existing service gap. However, despite a strong body of evidence that digital mental health programs provide an effective treatment option for a range of mental health and alcohol use problems in young adults, research shows that uptake rates can be low. It is, thus, important to understand the factors that influence treatment satisfaction and quality of life outcomes for young adults who access eMental health interventions for comorbidity.
OBJECTIVE
This study sought to understand the factors that influence treatment satisfaction and quality of life outcomes for young adults who access eMental health interventions for comorbid alcohol and mood disorders. The aim was to determine the importance of personality (i.e., Big Five personality traits and intervention attitudes) and affective factors (i.e., depression, anxiety, and stress levels) in predicting intervention trial engagement at sign-up, satisfaction with the online tool, and quality of life at the conclusion of the iTreAD trial (internet Treatment for Alcohol and Depression).
METHODS
Australian adults (N = 411) aged between 18 and 30 years who screened positive for depression and alcohol use problems signed up to the iTreAD project between August 2014 and October 2015. During registration, participants provided information about their personality, current affective state, treatment expectations and basic demographic information. Subsequent follow-up surveys were used to gauge ongoing trial engagement. The last follow-up questionnaire, completed at 64 weeks, assessed participants’ satisfaction with the online treatment and quality of life experiences.
RESULTS
Multiple linear regression analyses were employed to detect the relative influence of predictor variables on trial engagement, treatment satisfaction, and quality of life outcomes. Analyses revealed that the overall predictive effects of personality and affective factors were 20% or lower. Conscientiousness, neuroticism, and state-based anxiety constituted unique predictors of engagement with the iTreAD study, and state-based depression uniquely predicted variance in quality of life reports at the time of study completion. None of the selected predictors explained variances in treatment satisfaction.
CONCLUSIONS
Findings suggest that traditional predictors of engagement observed in face-to-face research may not be easily transferable to digital health interventions, particularly those aimed at comorbid mental health concerns and alcohol misuse among young adults. More research is needed to identify what determines engagement in this cohort in order to optimally design and execute digital intervention studies with multiple treatment aims.
CLINICALTRIAL
ACTRN12614000310662
INTERNATIONAL REGISTERED REPORT
RR2-10.1186/s12889-015-2365-2
Factors predicting trial engagement, treatment satisfaction, and health-related quality of life during the iTreAD project: Secondary analysis of an online treatment and social networking trial for binge drinking and depression in young adults. (Preprint)
