Please wait a minute...
Advanced Search
数据分析与知识发现  2017, Vol. 1 Issue (4): 46-56     https://doi.org/10.11925/infotech.2096-3467.2017.04.06
  研究论文 本期目录 | 过刊浏览 | 高级检索 |
信息生态视域下移动医疗APP用户持续使用意愿分析*
张敏1(), 罗梅芬1, 聂瑞1, 张艳2
1武汉大学信息资源研究中心 武汉 430072
2中国科学院大学公共政策与管理学院 北京 100049
Analyzing Continuance Intention of Health APP Users Based on Information Ecology
Zhang Min1(), Luo Meifen1, Nie Rui1, Zhang Yan2
1Center for Studies of Information Resources, Wuhan University, Wuhan 430072, China
2School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China
全文: PDF (777 KB)   HTML ( 5
输出: BibTeX | EndNote (RIS)      
摘要 

目的】探究影响移动医疗APP持续使用意愿的因素及其内在作用机理。【方法】从信息生态的研究视角出发, 分析信息、信息人、信息技术和信息环境4类影响因素, 并基于期望确认模型提出研究假设构建研究模型。【结果】选取多个移动医疗APP用户为实验者, 采用“日志追踪实验+调查问卷”的方式收集288份有效数据并利用SmartPLS2.0对模型进行检验。结果表明, 期望确认模型中的关系在移动医疗情境下均成立; 信息准确性和一致性、信息人的感知健康威胁、信息技术的易用性和响应性、信息环境的直接和间接网络外部性均会正向促进移动医疗APP的期望确认和感知有用性; 而信息人的电子健康素养则会正向促进期望确认, 负向抑制感知有用性。【局限】实验样本数量有待扩充, 得出的结论有待进一步推广。【结论】用户的移动医疗APP持续使用行为是信息、信息人、信息技术和信息环境共同作用的结果。

服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
张敏
罗梅芬
聂瑞
张艳
关键词 移动医疗持续使用意愿信息生态    
Abstract

[Objective] This paper aims to explore the factors affecting the continuance intention of mobile health application users. [Methods] From the perspective of information ecology, we first analysed information, users, technology and information environment factors. Then we proposed a new research hypotheses model based on the expectation confirmation model (ECM). [Results] We collected user behaviour data from server logs of multiple mobile health applications and questionnaires. A total of 288 valid samples were obtained and examined with SmartPLS2.0. We found that, all original relationships from the ECM existed in the mobile environment. The accuracy and consensus of information, perceived health threats, responding time and ease of use, as well as the direct / indirect network externality of the environment all positively correlated to the confirmation and perceived usefulness of mobile health applications. The eHealth literacy of users increased confirmation but restrained perceived usefulness. [Limitations] The sample size needed to be expanded, and the conclusions should to be promoted. [Conclusions] User’s continuance behaviour of mobile health APP is influenced by the information, users, technology and environment.

Key wordsMobile Health    Continuance Intention    Information Ecology
收稿日期: 2016-12-07      出版日期: 2017-05-24
ZTFLH:  F49  
基金资助:*本文系国家自然科学基金项目“Web2.0环境下基于社会化网络瓶颈限制的信息扩散最大化研究”(项目编号: 71203166)、武汉大学自主科研项目(人文社会科学)“危机伤害情境下网络声誉演化与修复机制研究”和武汉大学自主科研项目(人文社会科学)“70后”学者学术发展计划专题项目“数字人文和语义挖掘”的研究成果之一
引用本文:   
张敏, 罗梅芬, 聂瑞, 张艳. 信息生态视域下移动医疗APP用户持续使用意愿分析*[J]. 数据分析与知识发现, 2017, 1(4): 46-56.
Zhang Min,Luo Meifen,Nie Rui,Zhang Yan. Analyzing Continuance Intention of Health APP Users Based on Information Ecology. Data Analysis and Knowledge Discovery, 2017, 1(4): 46-56.
链接本文:  
http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.2096-3467.2017.04.06      或      http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/Y2017/V1/I4/46
  研究模型
变量名 问项数 问项来源
持续使用意愿(Continuance Intention, CONI) 3 Da?han & Akkoyunlu (2016)[ 31]
满意(Satisfaction, SATI) 3 Da?han & Akkoyunlu (2016)[31]
期望确认(Expectation Confirmation, EXPE) 3 Da?han & Akkoyunlu (2016)[31]
感知有用性(Perceived Usefulness, PU) 3 Davis(1989)[18]
准确性(Accuracy, ACCU) 3 Shin, et al. (2016)[32]
一致性(Consensus, CONS) 3 Chou, et al. (2015)[20]
感知健康威胁(Perceived Health Threat, PHT) 6 Johnston & Warkentin (2010)[33]; Sun, et al. (2013)[34]
电子健康素养(eHealth Literacy, EHLI) 8 Norman, et al. (2006)[35]
响应性(Responsiveness, RESP) 4 Parasuraman, et al. (1988)[26]
易用性(Perceived Ease of Use, PEOU) 4 Davis(1989)[18]
直接网络外部性(Direct Network Externalities, DNE) 3 Zhou (2015)[30]
间接网络外部性(Indirect Network Externality, INE) 3 Zhou (2015)[30]
  问卷变量设计
类别 选项 人数 比例(%)
性别 155 53.8
133 46.2
年龄 18岁以下 17 5.9
18-25岁 228 79.2
26-35岁 18 6.3
36-45岁 12 4.2
46-60岁 11 3.8
60岁以上 2 0.7
教育程度 初中及以下 8 2.8
高中或高职高专 52 18.1
大专 29 10.1
本科 187 64.9
硕士 9 3.1
博士及以上 3 1.0
  样本描述统计
变量 问项 因子负载 AVE CR $\alpha $值
持续使用意愿CONT CONT1 0.9559 0.9000 0.9643 0.9444
CONT2 0.9468
CONT3 0.9434
电子健康素养EHLI EHLI1 0.8604 0.7765 0.9653 0.9588
EHLI2 0.8970
EHLI3 0.8987
EHLI4 0.8986
EHLI5 0.8922
EHLI6 0.8926
EHLI7 0.8426
EHLI8 0.8655
期望确认EXPE EXPE1 0.9343 0.8587 0.9480 0.9177
EXPE2 0.9165
EXPE3 0.9291
一致性CONS CONS1 0.9156 0.8269 0.9348 0.8953
CONS2 0.8972
CONS3 0.9152
准确性ACCU ACCU1 0.9152 0.8634 0.9499 0.9208
ACCU2 0.9341
ACCU3 0.9381
间接网络外部性INE INE1 0.9165 0.8316 0.9368 0.8988
INE2 0.9052
INE3 0.9142
易用性PEOU PEOU1 0.8935 0.8420 0.9552 0.9373
PEOU2 0.9192
PEOU3
PEOU4
0.9420
0.9151
感知健康
威胁PHT
PHT1 0.7830 0.6443 0.9156 0.8896
PHT2 0.8553
PHT3 0.7964
PHT4 0.7723
PHT5 0.7805
PHT6 0.8252
感知有用性PU PU1 0.9053 0.8367 0.9389 0.9024
PU2 0.9273
PU3 0.9114
响应性RESP RESP1 0.8894 08117 0.9452 0.9226
RESP2 0.9058
RESP3 0.9230
RESP4 0.8851
直接网络外部性DNE DNE1 0.8782 0.8341 0.9378 0.9006
DNE2 0.9331
DNE3 0.9277
满意SATI SATI1 0.9184 0.8532 0.9458 0.9139
SATI2 0.9174
SATI3 0.9352
  测量模型信度和聚合效度相关指标
CONT EHLI EXPE CONS ACCU INE PEOU PU RESP DNE SATI PHT
CONT 0.9487
EHLI 0.5584 0.8812
EXPE 0.8428 0.6356 0.9267
CONS 0.6347 0.6877 0.7204 0.9093
ACCU 0.6761 0.6566 0.7664 0.8001 0.9292
INE 0.5748 0.5718 0.6408 0.6949 0.6845 0.9119
PEOU 0.5543 0.7137 0.6504 0.7680 0.7228 0.6295 0.9176
PU 0.7197 0.6005 0.7677 0.8315 0.8201 0.7306 0.7292 0.9147
RESP 0.6319 0.6438 0.7419 0.7841 0.7785 0.7442 0.7135 0.7959 0.9009
DNE 0.6242 0.5182 0.6400 0.6378 0.6173 0.6475 0.4931 0.6532 0.6386 0.9133
SATI 0.8295 0.7095 0.9046 0.7564 0.8236 0.7038 0.7047 0.8101 0.7809 0.6495 0.9237
PHT 0.5384 0.4538 0.5253 0.5260 0.4729 0.5006 0.3752 0.5341 0.5151 0.4977 0.5142 0.8027
  测量模型区别效度指标
  模型检验
(注: ***: p<0.001, **: p<0.01, *: p<0.05)
[1] Lester R T, Kop M V D, Taylor D, et al. M-health: Connecting Patients to Improve Population and Public Health[J]. British Columbia Medical Journal, 2011, 53(5): 218-219.
[2] Guo X T, Zhang X F, Sun Y Q.The Privacy-Personalization Paradox in mHealth Services Acceptance of Different Age Groups[J]. Electronic Commerce Research and Applications, 2016, 16: 55-65.
doi: 10.1016/j.elerap.2015.11.001
[3] 易观智库. 2016年中国移动医疗市场年度研究分析报告[R/OL]. [2016-11-10].
[3] (Analysys. Annual Research and Analysis Report of China Mobile Medical Market in 2016 [R/OL]. [2016-11-10].
[4] Akter S, D’Ambra J, Ray P. Development and Validation of an Instrument to Measure User Perceived Service Quality of mHealth[J]. Information & Management, 2013, 50(4): 181-195.
doi: 10.1016/j.im.2013.03.001
[5] 刘咏梅, 车小玲, 卫旭华. 消费者对移动医疗的初始信任研究[J]. 信息系统学报, 2014, 14(1): 15-30.
[5] (Liu Yongmei, Che Xiaoling, Wei Xuhua.Research on Consumers’ Initial Trust for Mobile Health[J]. China Journal of Information Systems, 2014, 14(1): 15-30.)
[6] Zhang X, Guo X, Lai K H, et al.Understanding Gender Differences in m-Health Adoption: A Modified Theory of Reasoned Action Model[J]. Telemedicine & e-Health, 2014, 20(1): 39-46.
doi: 10.1089/tmj.2013.0092 pmid: 24161004
[7] Guo X, Han X, Zhang X, et al.Investigating m-Health Acceptance from a Protection Motivation Theory Perspective: Gender and Age Differences[J]. Telemedicine and e-Health, 2015, 21(8): 661-669.
doi: 10.1089/tmj.2014.0166 pmid: 25919800
[8] Rai A, Chen L, Pye J, et al.Understanding Determinants of Consumer Mobile Health Usage Intentions, Assimilation, and Channel Preferences[J]. Journal of Medical Internet Research, 2013, 15(8): e149.
doi: 10.2196/jmir.2635 pmid: 3742412
[9] Hung M C, Jen W Y.The Adoption of Mobile Health Management Services: An Empirical Study[J]. Journal of Medical Systems, 2012, 36(3): 1381-1388.
doi: 10.1007/s10916-010-9600-2 pmid: 20878452
[10] Cho J.The Impact of Post-Adoption Beliefs on the Continued Use of Health Apps[J]. International Journal of Medical Informatics, 2016, 87: 75-83.
doi: 10.1016/j.ijmedinf.2015.12.016 pmid: 26806714
[11] Hsiao C H, Tang K Y.Examining a Model of Mobile Healthcare Technology Acceptance by the Elderly in Taiwan[J]. Journal of Global Information Technology Management, 2015, 18(4): 292-311.
doi: 10.1080/1097198X.2015.1108099
[12] 殷猛, 李琪. 基于保护动机理论的健康APP用户使用研究[J]. 现代情报, 2016, 36(7): 63-70.
doi: 10.3969/j.issn.1008-0821.2016.07.012
[12] (Yin Meng, Li Qi.An Empirical Study on the Intention of Healthcare Application Usage Based on the PMT[J]. Journal of Modern Information, 2016, 36(7): 63-70.)
doi: 10.3969/j.issn.1008-0821.2016.07.012
[13] Oliver R L.A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions[J]. Journal of Marketing Research, 1980, 17(4): 460-469.
doi: 10.2307/3150499
[14] Bhattacherjee A.Understanding Information Systems Continuance: An Expectation-Confirmation Model[J]. MIS Quarterly, 2001, 25(3): 351-370.
doi: 10.2307/3250921
[15] Nardi B A, O’Day V L. Information Ecologies: Using Technology with Heart[M]. Cambridge: MIT Press, 1999.
[16] 王晰巍, 曹茹烨, 杨梦晴, 等. 微信用户信息共享行为影响因素模型及实证研究——基于信息生态视角的分析[J]. 图书情报工作, 2016, 60(15): 6-13.
doi: 10.13266/j.issn.0252-3116.2016.15.001
[16] (Wang Xiwei, Cao Ruye, Yang Mengqing, et al.An Empirical Study of Influence Factors on WeChat User Information Sharing Behavior: Based on the Perspective of Information Ecology[J].Library and Information Service, 2016, 60(15): 6-13.)
doi: 10.13266/j.issn.0252-3116.2016.15.001
[17] 王晰巍, 刘铎. 企业信息生态系统的要素及评价指标构建研究[J]. 图书情报工作, 2010, 54(16): 22-25.
[17] (Wang Xiwei, Liu Duo.Research of the Elements and Evaluation Index Construction of Enterprise Information Ecological System[J]. Library and Information Service, 2010, 54(16): 22-25.)
[18] Davis F D. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology[J]. MIS Quarterly, 1989, 13(3): 319-340.
doi: 10.2307/249008
[19] Johnson E J, Payne J W.Effort and Accuracy in Choice[J]. Management Science, 1985, 31(4): 395-414.
[20] Chou C H, Wang Y S, Tang T I.Exploring the Determinants of Knowledge Adoption in Virtual Communities: A Social Influence Perspective[J]. International Journal of Information Management, 2015, 35(3): 364-376.
doi: 10.1016/j.ijinfomgt.2015.02.001
[21] Gudigantala N, Song J, Jones D.User Satisfaction with Web-based DSS: The Role of Cognitive Antecedents[J]. International Journal of Information Management, 2011, 31(4): 327-338.
doi: 10.1016/j.ijinfomgt.2010.10.009
[22] Rogers R W.A Protection Motivation Theory of Fear Appeals and Attitude Change[J]. Journal of Psychology Interdisciplinary & Applied, 1975, 91(1): 93-114.
doi: 10.1080/00223980.1975.9915803 pmid: 28136248
[23] Norman C D, Skinner H A. eHealth Literacy: Essential Skills for Consumer Health in a Networked World[J]. Journal of Medical Internet Research, 2006, 8(2): e9.
doi: 10.2196/jmir.8.2.e9 pmid: 1550701
[24] Barak A, Hen L, Nissim M B, et al.A Comprehensive Review and a Meta-Analysis of the Effectiveness of Internet-Based Psychotherapeutic Interventions[J]. Journal of Technology in Human Services, 2008, 26(2-4): 109-160.
doi: 10.1080/15228830802094429 pmid: 0026877
[25] McCrone P, Knapp M, Proudfoot J G, et al. Cost- Effectiveness of Computerised Cognitive-Behavioural Therapy for Anxiety and Depression in Primary Care: Randomised Controlled Trial[J]. The British Journal of Psychiatry, 2004, 185(1): 55-62.
doi: 10.1192/bjp.185.1.55 pmid: 15231556
[26] Parasuraman A, Zeithaml V A, Berry L L.SERVQUAL: A Multiple-Item Scale for Measuring Consumer Perceptions of Service Quality[J]. Journal of Retailing, 1988, 64(1): 12-40.
doi: 10.1016/0737-6782(88)90045-8
[27] Du J, Lu J, Wu D, et al.User Acceptance of Software as a Service: Evidence from Customers of China’s Leading E-Commerce Company, Alibaba[J]. Journal of Systems & Software, 2013, 86(8): 2034-2044.
doi: 10.1016/j.jss.2013.03.012
[28] Wu J H, Wang S C, Lin L M.Mobile Computing Acceptance Factors in the Healthcare Industry: A Structural Equation Model[J]. International Journal of Medical Informatics, 2007, 76(1): 66-77.
doi: 10.1016/j.ijmedinf.2006.06.006 pmid: 16901749
[29] Katz M L, Shapiro C. Network Externalities, Competition, and Compatibility[J]. American Economic Review, 1985, 75(3): 424-440.
[30] Zhou T.The Effect of Network Externality on Mobile Social Network Site Continuance[J]. Program, 2015, 49(3): 289-304.
doi: 10.1108/PROG-10-2014-0078
[31] Dağhan G, Akkoyunlu B.Modeling the Continuance Usage Intention of Online Learning Environments[J]. Computers in Human Behavior, 2016, 60(C): 198-211.
doi: 10.1016/j.chb.2016.02.066
[32] Shin B, Lee S, Lee H G.Examining an Extended Duality Perspective Regarding Success Conditions of IT Service[J]. International Journal of Information Management, 2016, 36(2): 226-239.
doi: 10.1016/j.ijinfomgt.2015.11.012
[33] Johnston A C, Warkentin M.Fear Appeals and Information Security Behaviors: An Empirical Study[J]. MIS Quarterly, 2010, 34(3): 549-566.
doi: 10.1515/libr.2010.017
[34] Sun Y Q, Wang N, Guo X T, et al.Understanding the Acceptance of Mobile Health Services: A Comparison and Integration of Alternative Models[J]. Journal of Electronic Commerce Research, 2013, 14(2): 183-200.
doi: 10.1108/10662241311331781
[35] Norman C D, Skinner H A. eHEALS: The eHealth Literacy Scale[J]. Journal of Medical Internet Research, 2006, 8(4): e27.
doi: 10.2196/jmir.8.4.e27 pmid: 17213046
[36] Cho J, Quinlan M M, Park D, et al.Determinants of Adoption of Smartphone Health Apps among College Students[J]. American Journal of Health Behavior, 2014, 38(6): 860-870.
doi: 10.5993/AJHB.38.6.8 pmid: 25207512
[1] 朱光,刘虎,杜欣蒙. 隐私忧虑背景下的移动医疗APP使用意愿研究*——基于三方博弈的视角[J]. 数据分析与知识发现, 2019, 3(5): 93-106.
[2] 王晰巍, 赵丹, 杨梦晴, 魏俊巍. 行业网站搜索引擎优化指标及实证研究——基于信息生态视角的分析[J]. 现代图书情报技术, 2015, 31(3): 75-83.
[3] 李北伟, 徐越, 单既民, 魏昌龙, 张鑫琦, 富金鑫. 中国购物网站网络信息生态链研究[J]. 现代图书情报技术, 2013, 29(9): 67-73.
[4] 张军. 网络信息链的分析流程与重构方法[J]. 现代图书情报技术, 2009, 3(3): 62-68.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
版权所有 © 2015 《数据分析与知识发现》编辑部
地址:北京市海淀区中关村北四环西路33号 邮编:100190
电话/传真:(010)82626611-6626,82624938
E-mail:jishu@mail.las.ac.cn