The Architecture of Choice: Using Psychosocial Variables to Dynamically Tailor Interventions

Abstract

Individual healthcare choices are strongly influenced by psychosocial factors such as values, goals, and self-perceptions. By using validated instruments to measure and map psychosocial variables, it is possible to produce digital interventions that are dynamically tailored to an individual's unique decision-making context. Each of us has our own distinct set of influences, circumstances, and core beliefs that drive our healthcare decision-making. One important variable is perceived self-efficacy (PSE), an element of Bandura's Social Cognitive Theory (SCT)1. PSE focuses on a patient's personal confidence beliefs about his or her capacity to undertake specific health behaviours that may lead to desired outcomes. In the context of chronic illness, PSE is predictive of quality of life and successful disease self-management2. Because self-efficacy beliefs are modifiable and can impact health status, motivation levels, goal achievement, adherence and persistence, intervention approaches that focus on boosting PSE can empower patients and improve chronic disease outcomes. Indeed, self-management programs designed specifically to improve PSE by incorporating self-confidence, goal-setting or control-enhancing strategies can produce more favorable outcomes for patients than with standard interventions3. This talk will highlight examples where PSE and human connections are used in practice across a variety of contexts including maternal health, type 2 diabetes, and chronic kidney disease.