The effect of interactive factors on online health consultation review deviation: An empirical investigation

背景(考古学) 医学 多项式logistic回归 在线讨论 逻辑回归 数字健康 医疗保健 家庭医学 计算机科学 万维网 机器学习 古生物学 经济 生物 经济增长 内科学
作者
Yifan He,Xitong Guo,Tianshi Wu,Doug Vogel
出处
期刊:International Journal of Medical Informatics [Elsevier BV]
卷期号:163: 104781-104781 被引量:6
标识
DOI:10.1016/j.ijmedinf.2022.104781
摘要

One-to-one online consultation is a common type of online health consultation. In choosing doctors for these consultations, patients rely on online reviews. Yet the deviation between online doctor reviews and the true quality of doctor-provided online services calls the usefulness of online doctor reviews into question, and the methods for reducing this deviation via doctor-patient communication remain unclear.The purpose of this study is to test the effects of interactive factors on online doctor review deviation and to further explore deviation across doctor specialties in the context of one-to-one online health consultations.We collect our data from a well-known Chinese online health consultation platform. The dataset includes 60,693 one-to-one online health consultation communication flows and corresponding online doctor reviews. We construct an online doctor review deviation matrix and use logistic regression and multinomial logistic regression models to examine the effects of interactive factors on online doctor review deviation.Our findings indicate that, in the context of a one-to-one online health consultation, a quicker response time and a lower response-question ratio could reduce deviation in online doctor reviews. Single modalities, such as the use of voice messages and uploading of photos, could reduce online doctor review deviation, especially in terms of patient overestimation. Medical information, including structural medical history and prescription information, could decrease online doctor review deviation. Moreover, the use of voice messages in surgery patient treatment can reduce online doctor review deviation more than in internal medicine.Interaction frequency, message delivery methods, and medical information can influence the deviation of online doctor reviews. Furthermore, the effects of voice messages vary across doctor specialties. This study offers theoretical and practical implications for the design of online health consultation platforms and the usage of online doctor reviews.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
科研通AI6.2应助OTW采纳,获得10
刚刚
BioGO完成签到,获得积分10
1秒前
姜茂才完成签到,获得积分10
1秒前
Ava应助zmuzhang2019采纳,获得10
2秒前
易水完成签到 ,获得积分10
2秒前
王欣瑶完成签到 ,获得积分10
2秒前
hanhan发布了新的文献求助10
3秒前
杨丹完成签到 ,获得积分10
4秒前
JamesPei应助饭好次吗采纳,获得10
4秒前
NexusExplorer应助xpxpxpx采纳,获得10
6秒前
7秒前
Sutera发布了新的文献求助10
8秒前
Gladys完成签到,获得积分10
9秒前
Bandage完成签到,获得积分10
11秒前
11秒前
12秒前
orixero应助HYQ采纳,获得10
13秒前
南烟关注了科研通微信公众号
13秒前
13秒前
久处完成签到,获得积分10
14秒前
邪恶青年完成签到 ,获得积分10
16秒前
愉快电脑发布了新的文献求助30
16秒前
Kvolu29完成签到,获得积分10
16秒前
xpxpxpx发布了新的文献求助10
16秒前
pbb发布了新的文献求助10
16秒前
18秒前
18秒前
doudou完成签到,获得积分10
18秒前
18秒前
VVV完成签到 ,获得积分10
19秒前
duoduo完成签到,获得积分10
20秒前
lzh1353730567发布了新的文献求助10
21秒前
钱念波完成签到,获得积分10
21秒前
南烟发布了新的文献求助10
22秒前
duoduo发布了新的文献求助10
22秒前
淡然胡萝卜完成签到,获得积分10
23秒前
Hello应助科研人采纳,获得10
23秒前
24秒前
24秒前
25秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
基于锂离子电池正极材料回收的绿色溶剂开发及工程化应用研究 500
Auslegungsgeschichte 500
Transdermal drug delivery systems market size report 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7641991
求助须知:如何正确求助?哪些是违规求助? 9215108
关于积分的说明 19767614
捐赠科研通 7207484
什么是DOI,文献DOI怎么找? 3276290
关于科研通互助平台的介绍 2438062
邀请新用户注册赠送积分活动 2274060