A Randomized Control Trial on the Effects of MoBeGo, a Self-Monitoring App for Challenging Behavior

Oct 15, 2026

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This study examines the effects of MoBeGo, a mobile self-monitoring app, on third- to eighth-grade students with challenging behavior. Student–teacher pairs (N=57) were randomly assigned to MoBeGo or business-as-usual. Direct behavioral observation covered prebaseline, baseline, intervention, and postintervention phases. Multivariate multilevel modeling showed improved student outcomes during intervention, including less disruptive behavior and greater academic engagement, with postintervention effects for disruptive behavior. Limitations, future directions, and practice implications are addressed.

LanguageEnglish

CategoryHealthcare

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Pages15

Reading Time38 min

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Abstract

Purpose and design

Measurement and analysis

Key findings

Limitations and implications

A Randomized Control Trial on the Effects of MoBeGo, a Self-Monitoring App for Challenging Behavior Allison Bruhn, PhD 1, Joseph Wehby, PhD2, Lesa Hoffman, PhD 1, Sara Estrapala, PhD3, Ashley Rila, PhD 1, Eleanor Hancock, MA2, Alyssa Van Camp, PhD2, Amanda Sheaffer, PhD2, and Bailey Copeland, MA2 Behavioral Disorders 2022, Vol. 48(1) 29–43 © Hammill Institute on Disabilities 2022 Article reuse guidelines: [sagepub.com/journals-permissions](sagepub.com/journals-permissions)[ ](sagepub.com/journals-permissions)[DOI: 10.1177/01987429221093987](DOI: 10.1177/01987429221093987)[ ](DOI: 10.1177/01987429221093987)[journals.sagepub.com/home/bhd](journals.sagepub.com/home/bhd) Abstract The purpose of this study was to examine the effects of MoBeGo, a mobile self-monitoring app, on the initial and sustained academic engagement and disruptive behavior of third- to eighth-grade students with challenging behavior. Student– teacher pairs (N = 57) were randomly assigned to the treatment (MoBeGo) or control (business-as-usual) condition. We conducted systematic direct observation of students’ behavior throughout prebaseline, baseline, intervention, and postintervention conditions of the study. Multivariate multilevel models revealed differential improvement for the MoBeGo group in student outcomes (less disruptive behavior; more academic engagement) from baseline to intervention, as well as successful postintervention effects for disruptive behavior. Limitations, future directions, and implications for practice are discussed. Keywords challenging behavior(s), behavioral interventions, randomized trial experimental design Challenging behavior in K–12 classrooms may be displayed by a range of students, including those with typical development and those with disabilities (e.g., emotional/ behavioral disorders [EBD], learning disabilities, attention-deficit/hyperactivity disorder [ADHD]) . Students with challenging classroom behaviors may appear inattentive and distracted during instructional activities or disruptive to themselves and others. When these behaviors are persistent and pervasive, students’ learning is likely impeded as instruction is constantly interrupted (Gage et al., 2018) . Furthermore, students who are disengaged are more at risk of academic failure and dropout, particularly in the absence of early intervention (Sprague & Walker, 2000) . To this end, self-monitoring interventions have been recommended for helping students learn to regulate their behavior (Briesch et al., 2019) . Selfmonitoring is the act of students thinking about their behavior and then recording data about the extent to which the behavior occurred (Briesch et al., 2019). Traditionally, self-monitoring has been done using a simple piece of paper and pencil along with a cueing device (e.g., kitchen timer), but recent technological developments have allowed students to use mobile apps to prompt and record their behaviors (Bruhn & Wills, 2018) . Theoretically, as students become more aware and intentional about exercising control over their own behavior, this type of selfassessment and self-recording should lead to behavioral change (Bandura, 1991) . Although self-monitoring alone may result in improved behavior (Briesch & Briesch, 2016), recent systematic reviews have shown these interventions are often multifaceted. That is, they are frequently packaged interventions, which include additional components such as prompting (Briesch et al., 2019), goal-setting (Bruhn, Gilmour, et al., 2022), graphing (Briesch et al., 2019; McDougall et al., 2017), feedback (Briesch et al., 2019; Bruhn et al., 2015; Bruhn, Gilmour, et al., 2022), and reinforcement (Brieschet al., 2019; Bruhn et al., 2015; Bruhn, Gilmour, et al., 2022; Sheffield & Waller, 2010) . For example, in a review of 56 single-case design studies of self-monitoring in K–12 1 University of Iowa, Iowa City, USA 2Vanderbilt University, Nashville, TN, USA 3University of Missouri, Columbia, U

FAQs

What was the purpose of this study?

To examine how MoBeGo, a mobile self-monitoring app, affects both initial and sustained academic engagement and disruptive behavior in students with challenging behavior.

How were participants assigned in the trial?

Student–teacher pairs (N=57) were randomly assigned to either the MoBeGo treatment condition or a control condition using business-as-usual.

What did the results show about MoBeGo’s effects?

Multivariate multilevel models indicated differential improvement for the MoBeGo group during intervention, including less disruptive behavior and more academic engagement, with successful postintervention effects for disruptive behavior.

Oct 15, 2026

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