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The goal of this two-year R34 treatment development grant is to develop a mobile health (mHealth) application that will both advance theory in and clinical practice of homework (HW) implementation.
HW can be described as between-session exercises where the client practices specific skills learned within-session in order to promote skill acquisition, which ultimately leads to improved acute- as well as longer-term therapeutic benefits on targeted outcomes, generalization of treatment effects and maintenance of treatment gains. Despite data demonstrating that HW is critical to achieving maximal benefits from evidence-based treatments, very little theory-driven approaches have been conducted focusing on improving the HW process. Through utilizing self-determination theory as a guiding framework and integrating principles from the field of "gamification" and goal-setting, the aim is to develop a two-component mHealth HW application (My MFG).
The first component focuses on delivering HW via a highly engaging, multiplayer, interactive, cooperative, and skill-building game platform aimed at improving the "Design" and "Do" process of HW. The second component focuses on targeting factors putatively related to poor HW implementation within the "Do" process.
The process of the development of My MFG will be guided by the clinic and community development model and iterative software development process to maximize the feasibility and sustainability of My MFG within practice settings often characterized by limited resources. Findings from this study have broad implications for evidence-based treatments for youth and adult mental health disorders that emphasize HW as the link between treatment and improvements in targeted outcomes.
Full description
The aim of the proposed study is to develop a theory-informed mobile health (mHealth) application for urban caregivers attempting to improve their children's oppositional and conduct related difficulties (i.e., disruptive behavior disorders; DBDs). The majority of evidence-based treatments (EBTs) targeting youth DBDs emphasize change in specific parenting/family-level processes empirically linked to the maintenance of DBDs. Existing EBTs frequently include at-home-practice-exercises (i.e., homework; HW) to reinforce parent skill acquisition and maximize use of new skills with children at home. Poor quantity and quality of HW completed by parents significantly attenuates the effect of EBTs. This is a significant limiting-factor in many EBTs attaining full public health impact. Given the robust effect of HW on outcomes from EBTs across a range of behavioral health difficulties and populations, there is a call for moving beyond the question of whether HW is important to questions such as what processes are involved in HW implementation and how best to support these processes. Minimal investigation has been focused on these critical questions.
A model of HW has recently been proposed to better understand the process of HW implementation, as well as guide critically needed supports for at-home practice exercises.
This model proposes four HW processes:
The DADR model proposes that specific social, cognitive and behavioral factors related to the HW task, as well as to the provider and the adult caregiver may affect the quality of each phase and ultimately to the quantity and quality of HW completed. Methods to better understand, support, and impact these processes are essential to advancing theory and offering solutions to HW completion.
Through features available on smartphones (e.g., camera/video/voice recording; simple message service; internet-access; global positioning system), there are novel methods to interface with and support clients outside of defined treatment sessions. Through the use of these features, mHealth applications can be used to engage, educate, connect, track, and remind clients. These applications can use push (send communications) or pull (client's access tools on their own) mechanisms to engage the client in behavioral change activity. mHealth applications that integrate push and pull methods offer a significant opportunity to enhance outcomes across a range of health and behavioral health challenges and populations.
The goal of this two-year R34 treatment development grant is in response to RFA-MH-13-061 (Harnessing advanced health technologies to drive mental health improvement) to develop a mHealth application that will both advance theory in and clinical practice guided by the DADR model of HW implementation. Specifically we aim to utilize mHealth to improve the "Design" and "Do" process of HW within the context of the Family Groups for Youth with Behavioral Difficulties (MFG) intervention, an EBT for DBDs in youth and their families who seek assistance at outpatient mental health clinics in urban communities. To date, efforts at utilizing mHealth within the context of HW have been minimal and have not taken a systematic, theory-driven approach, thereby limiting the advance of knowledge and clinical application. Through utilizing self-determination theory as a guiding framework and integrating principles from the field of "gamification" and goal-setting, the aim is to develop a two-component MFG mHealth HW application (My MFG). The first component focuses on delivering MFG HW via a highly engaging, multiplayer, interactive, cooperative, and skill-building game platform aimed at improving the "Design" and "Do" process. The second component focuses on targeting factors putatively related to poor HW implementation within the "Do" process.
The process of the development of My MFG will be guided by the clinic and community development model and iterative software development process to maximize the feasibility and sustainability of My MFG within practice settings often characterized by limited resources. The specific aims of this project are to:
Develop My MFG through an iterative process informed by the perspectives of key stakeholders
Determine the impact of MFG plus My MFG relative to MFG-alone on the DADR process and HW quantity and quality. It is hypothesized that the MFG plus My MFG will result in:
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Data sourced from clinicaltrials.gov
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