Communication Patterns and Patient Satisfaction in Online Cardiovascular Consultations: A Mixed-Methods Analysis (Preprint)

BACKGROUND Background: Digital health technologies have made online physician-patient communication pivotal for cardiovascular disease (CVDs) management. CVDs, major global causes of morbidity and mortality, require long-term follow-up and entail patients’ dual biomedical and psychosocial needs. Patient-centered care (PCC) is foundational but challenged by nonverbal cue loss in text-based online settings. Existing research lacks disease-specific insights into communication patterns in CVDs telemedicine, and how such patterns influence patient satisfaction. OBJECTIVE Objective: This study aims to identify typical communication patterns in online CVDs consultations, analyze their compositional features, and examine their association with patient satisfaction, thereby providing practical implications for optimizing remote cardiovascular care. METHODS Design: Mixed methods study design answered the study questions. RESULTS Results: A total of 2559 doctor utterances and 2738 patient utterances were coded using the Roter Interaction Analysis System (RIAS). Four distinct communication patterns were identified: Relation-Supported, Deep Empathy, High-Task Integrated, and Efficiency-Oriented. Representative dialogues for each pattern were excerpted and presented to illustrate their differing combinations of emotional engagement and task focus. Compared with the Efficiency-Oriented pattern, the Deep Empathy (OR = 13.731, 95% CI: 2.493-75.624, P = 0.003), Relation-Supported (OR = 7.929, 95% CI: 3.352-18.752, P