Table 3.

Study methodologies.

Author/Year	Duration	Key inclusion criteria	Key exclusion criteria	Data collection/analysis summary
Wang 2025b (32)	1 month	Hypertension diagnosis, smartphone use, consent to 1-month intervention	Secondary hypertension, unable to follow up, concurrent treatment/trials, refusal of consent	Collected passive digital phenotypes and uploaded BP/heart rate data; usability assessed with MAUQ and DSSQ; analyzed in SPSS and R using t-tests, Mann–Whitney U, chi-square, and Fishers exact tests.
Ho 2025 (34)	12 months	Adults 18 to <90 years with one cardiovascular condition, prescribed medication in prior 100 days, refill gap of 7 days	No phone listed, hospice/palliative care, non-English/Spanish speakers, outside Colorado/homeless, pregnancy	Patients were identified from pharmacy data, then randomized; primary outcome was refill adherence (PDC) over 365 days, with secondary analysis of refill gap length.
Wang 2025a (26)	6- and 12-month follow-up	Adults 21 + with hypertension, with/without hyperlipidemia, enrolled in program or usual care	Prediabetes, diabetes, stroke, ischemic heart disease, nephritis, nephrosis	Compared program vs. usual care using BP, demographic, health care use, and cost data; used patient-level economic evaluation, regression, and exact matching.
Sakane 2023 (28)	12 weeks	Adults 40–64 years, BMI 25+, BP threshold met, smartphone users able to install apps and communicate online	Already receiving SHG, taking antihypertensives, contraindications to diet/exercise, pregnancy/breastfeeding, severe psychiatric disorders	Used Bluetooth devices, web questionnaires, app assessments, chatbot quizzes, and upload frequency to measure adherence and health outcomes.
Echeazarra 2021 (29)	2 years (2018–2020)	Adults 18 + with hypertension/suspected hypertension, home BP device, smartphone with internet, WhatsApp/Telegram ability, consent	Severe psychiatric disorder, severe illness, clotting disorders, motor/visual disability	Randomized trial comparing bot vs. paper records; assessed BP self-monitoring knowledge, satisfaction, and ambulatory BP outcomes.
AlFraidan 2025 (27)	90 days	Not specified	Not specified	Qualitative case study with daily AI interactions, self-reports, BP readings, thematic analysis, repeated-measures ANOVA, paired t-tests, correlation, and dynamic regression.
Antia 2025 (25)	3 months, 10 days	Hypertension diagnosis, personal Android phone, regular clinic follow-up	No internet-enabled compatible phone, not an active internet user, poor clinic adherence	Single-arm trial with baseline and follow-up questionnaires, repeated BP readings, usability/satisfaction questionnaires, paired t-tests, and regression.
Lee 2022 (31)	Nov 2019-Feb 2022	Hypertension diagnosis, University of Pennsylvania Health System employee, at least one in-person visit, text messaging use	Non-employees, unable/unwilling to use text-based monitoring, seeking care for non-hypertension conditions	Built a chatbot clinician model using iterative innovation; trained on 369 patient messages and scripted automated responses.
Rekha 2024 (30)	4 months	Patients with diabetes, hypertension, or thyroid disorders, age >18, willing to participate	Unwilling participants, psychiatric patients unable to complete questionnaires, pregnancy, breastfeeding, paediatrics	Reviewed prescriptions and interviews to identify drug-related problems using ChatGPT, Naranjo scale, and Hartwig scale; data analyzed in Excel and Prism.