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Peer Support: a Human Factor to Enhance Engagement in Digital Health Behavior Change Interventions
Karen L Fortuna1,2, Jessica M Brooks3, Emre Umucu4
1The Geisel School of Medicine at Dartmouth, 2 Pillsbury Street, Suite 401, Concord, NH 03301, USA.
Abstract:
The purpose of this report is to develop a theoretical model based on empirical evidence that can serve as a foundation for the science of peer-support factors that facilitate engagement in digital health interventions for people with serious mental illness (SMI). A review of the literature on how peer-support specialist interaction with consumers with SMI in digital health behavior change interventions enhances engagement. Unlike relationships with other health providers, peer-to-consumer relationships are based on reciprocal accountability -meaning that peer-support specialists and consumer mutually help and learn from each other. Under the recovery model of mental illness, reciprocal accountability suggests autonomy, flexible expectations, shared lived experience, and bonding influence engagement in digital interventions. Separate yet related components of reciprocal accountability in the context of digital health intervention engagement include (1) goal setting, (2) task agreement, and (3) bonding. Hope and sense of belonging are hypothesized moderators of peer-support factors in digital health interventions. Peer-support factors help people with SMI learn to live sucessfully both in the clinic and community. Peer-support specialists add value and complement traditional mental health treatment through their professional training and lived experience with a mental illness. The proposed model is a pioneering step towards understanding how peer-support factors impact engagement in digital health behavior change interventions among people with a lived experience of SMI. The model presents proposed factors underlying the reciprocal accountability processes in the context of digital health intervention engagement. This model and related support factors can be used to examine or identify research questions and hypotheses.
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