Deposit contracts involve participants depositing their own money and earning it back contingent on behavior change. Deposit contracts are empirically supported treatments for promoting health behavior, but they have a history of poor uptake. We compared the effectiveness and acceptability of technology-based versus in-person deposit contracts for promoting physical activity with 12 individuals. Participants' daily step counts were monitored using Fitbits across 6 weeks, and treatment preferences were assessed at the end of the study. The 2 types of treatments were equally effective in increasing physical activity, but the technology-based deposit contracts were preferred by most participants. Most participants also reported that their preference was related to convenience. Technology-based implementation may be one way to improve deposit contract uptake, while maintaining similar effectiveness compared to in-person procedures.
Using a humanoid robot to simulate patient behaviors in research that involves staff– or caregiver–patient interactions can be highly valuable to behavior analysts. As a first step in using a robotic patient simulator in behavior analytic research, we examined whether trainees (college-aged adults) taught to conduct a common behavioral procedure responded similarly to a humanoid robot as to a research assistant acting as a patient. In both Studies 1 and 2, we found that participants (total of 9 undergraduate students) learned to conduct preference assessments regardless of the type of patient simulator with whom they trained. Furthermore, participants’ skills extended to actual children and they rated the robot favorably after undergoing the intervention. We concluded that a robot may be a viable patient simulator in training research and discussed future directions.
Technology-based health interventions are providing unprecedented ways to improve a range of socially significant behavior. In this article, we provide behavior analysts with an overview of technology-based platforms and applications to help broaden research and practice. First, we discuss "high-tech" platforms, such as smartphones, wearable sensors, and other wireless devices. Second, we provide information about "low-tech" platforms, such as text messaging, which may be more feasible to implement than high-tech platforms. Finally, we discuss challenges and opportunities, and we provide specific guidance regarding the prescription of these assessment and intervention tools as a part of behavior analytic services.
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