Digital Health and Engagement—Looking Behind the Measures and Methods

Abstract

Low real-world engagement with digital mental health therapy programs and apps is a perennial concern that is only now receiving due research attention. The study by Chien et al 1 is a welcome addition to the literature given its focus on understanding the association between patient engagement, an internet-based cognitive behavioral therapy intervention for depression and anxiety, and clinical outcomes. Using a probabilistic latent variable model to infer distinct subtypes of patients based on their interaction with the internet-based cognitive behavioral therapy program, the authors identify 5 clusters of patients: low engagers, late engagers, high engagers with rapid disengagement, high engagers with moderate decrease, and highest engagers. Overall, the results are consistent with the literature on digital health engagement: highest engagers represented just 10.6% of the sample. But low engagement measurements with digital health tools do not tell the full story. The study

Smartphone apps for depression and anxiety: a systematic review and meta-analysis of techniques to increase engagement

“…Furthermore, the quality of engagement may be more likely to affect clinical outcomes as much as or even more than the duration of engagement. The issue of defining meaningful engagement has been gaining attention and will likely influence the next steps in measuring app engagement 56 .…”

Digital Therapeutics for Obesity and Eating-Related Problems

“…Broadly, there are three types of time points for an intervention: daily, weekly, and monthly. Previous studies applying either weekly or monthly interventions showed high attrition rates [28]. In contrast, we recently showed that more intensive daily coaching could prowww.e-enm.org 225 duce a high adherence rate, with 80% of participants remaining active users until the last session of the treatment.…”

“…To date, many efforts have been made to develop various types of DTx, but still they remain unsettled in the clinical settings due to following limitations. Currently, low engagement and low efficacy of DTx are two major concerns in understanding the full scalability and competency of it [28]. Next, similar to traditional pharmaceuticals, DTx must undergo RCTs for the approval procedure to verify safety and efficacy in the premarket [2].…”

Assessing the usability and user engagement of Thought Spot - A digital mental health help-seeking solution for transition-aged youth

“…Given the null results of the RCT ( Wiljer et al, 2020 ), the research team examined how participants who were given Thought Spot engaged with the app. User engagement with mHealth technologies is a growing area of interest ( Torous et al, 2020 ) because it can help researchers understand adherence and dropout during an RCT, which can potentially affect the efficacy of an intervention ( Torous et al, 2018 ). In the literature, low adherence to internet interventions is a frequently reported observation ( Christensen et al, 2009 ; Baumel and Kane, 2018 ; Eysenbach, 2005 ; Davis and Addis, 1999 ).…”

“…Although there is a considerable amount of work that investigates this topic ( Christensen et al, 2009 ; Baumel and Kane, 2018 ; Eysenbach, 2005 ), achieving optimal levels of engagement continues to be a challenge ( Torous et al, 2018 ). Currently, there is lack of a gold-standard definition or established evaluation frameworks for user engagement of mHealth technologies ( Lo et al, 2019 ; Perski et al, 2017 ; Pham et al, 2019a ; Torous et al, 2020 ; Torous et al, 2018 ) which has led to a variability in how usage and engagement are measured. As outlined by Short et al (2018) , there are different methods for measuring user engagement, each offering different advantages and disadvantages in terms of validity and relevance.…”