Activating patient continuity of care through nonverbal signal: The role of physicians’ voice in online depression treatment

IF 6.8 3区管理学 Q1 BUSINESS

Electronic Commerce Research and Applications Pub Date : 2026-09-01 Epub Date: 2026-10-05 DOI:10.1016/j.elerap.2026.101645

Wenjie Pan, Jianqiang Wang, Xiaokang Wang, Zhiya Zuo, Fei Xiao

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引用次数: 0

Abstract

Depression treatment requires continuity of care (CoC), yet patient adherence remains challenging. As a critical form of healthcare e-commerce, online medical consultations (OMCs) have emerged as a promising avenue to facilitate CoC for patients with depression. However, the predominantly text-based nature of OMCs may constrain the transmission of nonverbal cues that are essential for mental health care. This study examines how voice messaging in OMCs affects CoC among patients with depression. Guided by signaling theory, we collected secondary data from a Chinese OMC platform and employed fixed-effects models to examine the effect of voice message count (signal intensity) on CoC and the moderating effects of physicians’ voice characteristics (signal clarity), including pitch, pause, and speed. We find that more voice messages are associated with higher CoC, consistent with voice functioning as a signal of physician effort and availability. Signal clarity moderates this effect: higher vocal pitch, fewer pauses, and slower speed each amplify the impact of voice count on CoC, indicating that signal intensity translates into patient adherence more effectively when signal clarity is high. These results extend signaling theory by identifying the interplay between signal intensity and signal clarity in shaping receiver responses in the OMC context and offer insights for leveraging voice to strengthen patient CoC in digital mental health care and promote platform sustainability in digital health e-commerce.

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通过非语言信号激活患者的护理连续性：医生的声音在在线抑郁症治疗中的作用

抑郁症治疗需要持续护理（CoC），但患者的依从性仍然具有挑战性。作为医疗保健电子商务的一种重要形式，在线医疗咨询（omc）已成为促进抑郁症患者CoC的一种有希望的途径。然而，omc主要基于文本的性质可能会限制非语言线索的传递，而非语言线索对精神卫生保健至关重要。本研究探讨语音信息如何影响抑郁症患者的CoC。在信号理论的指导下，我们收集了来自中国OMC平台的二次数据，并采用固定效应模型来检验语音信息计数（信号强度）对CoC的影响以及医生语音特征（信号清晰度）（包括音高、停顿和速度）的调节作用。我们发现更多的语音信息与更高的CoC相关，这与语音作为医生努力和可用性的信号相一致。信号清晰度缓和了这种影响：更高的音调、更少的停顿和更慢的语速都会放大声音计数对CoC的影响，这表明当信号清晰度高时，信号强度更有效地转化为患者的依从性。这些结果通过识别信号强度和信号清晰度之间的相互作用，扩展了信号理论，从而形成了OMC背景下接收者的反应，并为利用语音加强数字精神卫生保健中的患者CoC和促进数字健康电子商务平台的可持续性提供了见解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Electronic Commerce Research and Applications 工程技术-计算机：跨学科应用

CiteScore

10.10

自引率

8.30%

发文量

审稿时长

63 days

期刊介绍： Electronic Commerce Research and Applications aims to create and disseminate enduring knowledge for the fast-changing e-commerce environment. A major dilemma in e-commerce research is how to achieve a balance between the currency and the life span of knowledge. Electronic Commerce Research and Applications will contribute to the establishment of a research community to create the knowledge, technology, theory, and applications for the development of electronic commerce. This is targeted at the intersection of technological potential and business aims.