The Digital Marshmallow Test (DMT) Diagnostic and Monitoring Mobile Health App for Impulsive Behavior: Development and Validation Study

Michael Sobolev, Rachel Vitale, Hongyi Wen, James Kizer, Robert Leeman, J P Pollak, Amit Baumel, Nehal P Vadhan, Deborah Estrin, Frederick Muench, Michael Sobolev, Rachel Vitale, Hongyi Wen, James Kizer, Robert Leeman, J P Pollak, Amit Baumel, Nehal P Vadhan, Deborah Estrin, Frederick Muench

Abstract

Background: The classic Marshmallow Test, where children were offered a choice between one small but immediate reward (eg, one marshmallow) or a larger reward (eg, two marshmallows) if they waited for a period of time, instigated a wealth of research on the relationships among impulsive responding, self-regulation, and clinical and life outcomes. Impulsivity is a hallmark feature of self-regulation failures that lead to poor health decisions and outcomes, making understanding and treating impulsivity one of the most important constructs to tackle in building a culture of health. Despite a large literature base, impulsivity measurement remains difficult due to the multidimensional nature of the construct and limited methods of assessment in daily life. Mobile devices and the rise of mobile health (mHealth) have changed our ability to assess and intervene with individuals remotely, providing an avenue for ambulatory diagnostic testing and interventions. Longitudinal studies with mobile devices can further help to understand impulsive behaviors and variation in state impulsivity in daily life.

Objective: The aim of this study was to develop and validate an impulsivity mHealth diagnostics and monitoring app called Digital Marshmallow Test (DMT) using both the Apple and Android platforms for widespread dissemination to researchers, clinicians, and the general public.

Methods: The DMT app was developed using Apple's ResearchKit (iOS) and Android's ResearchStack open source frameworks for developing health research study apps. The DMT app consists of three main modules: self-report, ecological momentary assessment, and active behavioral and cognitive tasks. We conducted a study with a 21-day assessment period (N=116 participants) to validate the novel measures of the DMT app.

Results: We used a semantic differential scale to develop self-report trait and momentary state measures of impulsivity as part of the DMT app. We identified three state factors (inefficient, thrill seeking, and intentional) that correlated highly with established measures of impulsivity. We further leveraged momentary semantic differential questions to examine intraindividual variability, the effect of daily life, and the contextual effect of mood on state impulsivity and daily impulsive behaviors. Our results indicated validation of the self-report sematic differential and related results, and of the mobile behavioral tasks, including the Balloon Analogue Risk Task and Go-No-Go task, with relatively low validity of the mobile Delay Discounting task. We discuss the design implications of these results to mHealth research.

Conclusions: This study demonstrates the potential for assessing different facets of trait and state impulsivity during everyday life and in clinical settings using the DMT mobile app. The DMT app can be further used to enhance our understanding of the individual facets that underlie impulsive behaviors, as well as providing a promising avenue for digital interventions.

Trial registration: ClinicalTrials.gov NCT03006653; https://www.clinicaltrials.gov/ct2/show/NCT03006653.

Keywords: ResearchKit; active task; ecological momentary assessment; impulse control; impulsivity; mHealth; mobile health; self-control; self-regulation.

Conflict of interest statement

Conflicts of Interest: AB has received payment for consulting, from Pro-Change Behavior Systems. All other authors have no conflicts to declare.

©Michael Sobolev, Rachel Vitale, Hongyi Wen, James Kizer, Robert Leeman, J P Pollak, Amit Baumel, Nehal P Vadhan, Deborah Estrin, Frederick Muench. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 22.01.2021.

Figures

Figure 1
Figure 1
Digital Marshmallow Test (DMT) mobile apps for Apple (iOS) and Android.
Figure 2
Figure 2
Active performance tasks and self-report in the Digital Marshmallow Test (DMT) app.
Figure 3
Figure 3
Photographic Affect Meter (PAM) for ecological momentary assessment.
Figure 4
Figure 4
Example of an active task: mobile Balloon Analogue Risk Task (mBART).

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