Clinical Testing of a Real-Time Behavior Measurement Tool: Measuring Outcomes for CHAnge

Behavior problems occur frequently and are a persistent source of treatment needs in individuals with intellectual and developmental disabilities (IDD). Problem behaviors such as aggression, self-injurious behaviors (SIB), destruction of property, and irritability can result in harm to self or others, interfere with social relationships, disrupt important family processes, and compromise positive individual and family adaptation. The impact of problem behaviors can have long term impacts for the individual, including reduced exposure to education, reduced quantity and quality of social interactions, and increased likelihood of more restrictive learning and living environments. Individuals with IDD who exhibit severe aggression are more likely to be placed in residential treatment facilities and to be placed on antipsychotic medications. Challenging behaviors have also repeatedly been shown to be strongly associated with poorer mental and physical health in caregivers. While there is a long history of both behavioral and pharmacologic interventions for aggression and SIB, the evidence base is considered slim compared to other fields in health care. A key challenge for clinicians and researchers in the IDD field is determining the efficacy of treatments to meet the complex needs of their patients. The ability to adequately assess the efficacy of any pharmacological or behavioral treatment has been limited by the lack of objective, real-time measurement tools. While there are many measures of behavior, including behavioral observation tools designed to assess the frequency, severity, and functions of specific behaviors, these measures are often limited. Most behavior measures rely either on recall (e.g., parent rating scales), or trained observers who, in addition to requiring specific training in behavior observation techniques also, as a factor of their presence, may change the behaviors and/or outcomes. The limitations inherent in these traditional measurement techniques have at best made it difficult to test the true efficacy of a clinical intervention, and, at worst, potentially resulted in the failure of clinical trials for medications which may have shown positive results with more sensitive and objective outcome measures.

MOCHA was developed in response to these challenges as an innovative yet simple method to capture behaviors in real time. MOCHA is available for both iOS and android platforms and can be sent remotely via a link to an individual's phone. MOCHA allows parents or teachers to record a behavior event simply by opening an app on their phone or tablet. A series of questions about the event allow for a brief yet comprehensive description of the event for use in understanding potential antecedents and functions of the behavior. Data is securely uploaded to a remote server at RTI whenever the participant is online. MOCHA was originally developed and piloted through internal funding to Dr. Wheeler at RTI International. The pilot study of four parents and three teachers of children with IDD was conducted primarily to establish feasibility and acceptability data and to engage stakeholders in a user-centered design approach to the development of the tool. Results from the pilot suggest that MOCHA is an acceptable and feasible tool to capture behaviors during or shortly after a behavior event. All parents and teachers in the pilot endorsed that MOCHA was easy to learn, clear and understandable, easy to answer questions, easy to use and a useful tool. Participants also reported the ability to record the behaviors and answer all follow up questions either when the behavior occurred or shortly after. In order to optimize the potential for MOCHA as an outcome measure there is a need to test its utility for measuring behaviors over time and in response to treatment.

The aims for this next phase of feasibility of MOCHA are as follows:

Aim 1. Expand the current MOCHA application to include additional clinically relevant features. Several features were suggested by participants in the development study to improve the usability of MOCHA. Specifically, the ability to personalize the target behaviors ahead of data collection; the use of a sync-able, wearable external event marker (EEM); and a feedback feature with graphed data to assist with monitoring behavior over time were requested features. Fortunately, MOCHA was developed using the Personal Health Informatics Toolkit (PHIT), a RTI developed, configurable, mHealth platform for developing apps and facilitating research. The PHIT platform has been used successfully for other apps with features such EEM and physiological sensors, similar to the features the investigators are proposing. Further, RTI has become an international leader in clinical informatics and provides shared resources and access to experts through its iSHARE (Integrating Signals and Human Response) program. Capitalizing on these resources, our first goal will be to develop and integrate these proposed features, using user-centered design procedures and engaging stakeholders in development.

Aim 2. Test the use of the MOCHA application to measure change in behaviors over time and in response to intervention. In order to assess the ability to use MOCHA the investigators will provide MOCHA to 10 families of individuals with IDD who are receiving intervention services through an established behavioral medicine clinic. The primary purpose of this aim is to examine the feasibility of the MOCHA app for use in recording frequency, intensity, and occurrence of behaviors and considering that information with parent perception/report.

Aim 3. Explore the ability to sync MOCHA with physiological data via wearable sensors. An ultimate vision of the MOCHA system includes the ability for the app to provide "ground truth" observable behavior that occurs in conjunction with physiological changes. Although full testing of a syncable system is outside the budgetary and time restrictions of this funding mechanism, the investigators propose to move this vision closer to reality by a) identifying wearable sensors that are acceptable and tolerable to the population and b) testing the feasibility of time syncing physiological markers with MOCHA identified behaviors.