Health behavior models for informing digital technology interventions for individuals with mental illness.

ABSTRACT

OBJECTIVE: Theoretical models offer valuable insights for designing effective and sustainable behavioral health interventions, yet the application of theory for informing digital technology interventions for people with mental illness has received limited attention. We offer a perspective on the importance of applying behavior theories and models to developing digital technology interventions for addressing mental and physical health concerns among people with mental illness. METHOD: In this commentary, we summarize prominent theories of human behavior, highlight key theoretical constructs, and identify opportunities to inform digital health interventions for people with mental illness. We consider limitations with existing theories and models, and examine recent theoretical advances that can specifically guide development of digital technology interventions. RESULTS: Established behavioral frameworks including health belief model, theory of planned behavior, transtheoretical model, and social cognitive theory consist of important and overlapping constructs that can inform digital health interventions for people with mental illness. As digital technologies continue to evolve and enable longitudinal data collection, real-time behavior monitoring, and adaptive features tailored to users' changing needs over time, there are new opportunities to broaden our understanding of health behaviors and mechanisms of behavior change. Recent advances include dynamic models of behavior, persuasive system design, the behavioral intervention technology model, and behavioral models for just-in-time adaptive interventions. CONCLUSION AND IMPLICATIONS FOR PRACTICE Behavior theories offer advantages for guiding use of digital technologies. Future researchers must explore how theoretical models can effectively advance efforts to develop, evaluate, and disseminate digital health interventions targeting individuals with mental illness. (PsycINFO Database Record