train_data.csv

This dataset focuses on predicting long-term health behaviors in older adults. The dependent variable, "TTM Stage," represents the respondent's current behavioral stage based on the Transtheoretical Model (TTM), measured on a 5-point scale where 1 = precontemplation and 5 = maintenance. Independent variables cover multiple dimensions: In individual characteristics, "A1(Age)" records age as an open-ended numeric value; "A2(Gender)" uses 0 for male and 1 for female; "A3(Chronic Illness Status)" uses 0 to indicate no chronic disease and 1 for yes. For health app usage, "B1(Health App Type)" is categorized into 4 types (1 = voice assistant, 2 = virtual assistant, 3 = wearable device, 4 = others), and "B2(Weekly Usage Frequency)" is measured on a 4-point scale (1 = <1 time/week, 2 = 1–2 times/week, 3 = 3–4 times/week, 4 = daily). Based on the Health Belief Model (HBM), twelve 7-point Likert scale variables assess perceptions of susceptibility (C1-C2), severity (C3-C4), benefits (C5-C6), barriers (C7-C8), cues to action (C9-C10), and self-efficacy (C11-C12), reflecting respondents’ cognitions and attitudes toward health and health apps. Together, these variables provide comprehensive data support for random forest model analysis.