Abstract: Disclosed methodologies provide improved predictors of patient treatment adherence by using person-specific subjective experience and social-environmental factors. Methodologies combine emotion and data sciences. Advanced tools capture, measure, store, and analyze self-report of subjective experiences using digital applications and platforms. Patient-specific data is obtained regarding emotional or affective determinants and social determinants for generating a calculated composite score of the patient's probability of adherence or achievement relative to target outcomes, e.g. adherence to treatment plans, wellness activities, etc. for a subject individual. Internal/subjective factors are judged by self-report measures designed to validly judge tested factors based on a patient adjusting continuously-variable graphical interfaces to capture and measure subjective experiences.