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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (1): 76-87    DOI: 10.11925/infotech.2096-3467.2017.1038
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Studying Social Interaction of Online Medical Question-Answering Service
Zhang Liyi, Li Huiran()
School of Information Management, Wuhan University, Wuhan 430072, China
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Abstract  

[Objective] To explore the impacts of social interaction on online medical question-answering service. [Methods] We proposed a new research model to study online medical question-answering usage. We collected data with questionnaire and examined the proposed model with the Smart PLS 3.0. A total of 371 valid samples were obtained and analyzed. [Results] We found that users were happy after contributing information online. The usefulness and ease of use during human-machine interaction, as well as the cognitive-trust and affection-trust posed positive effect to patients’ usage of online medical question-answering services. We also found the information and emotion support had different impacts on cognitive and affection trust, which led to different behaviors of patient-doctor and patient-patient interactions. [Limitations] Impacts of different diseases and information functions (direct or indirect) on the interaction should be further studied. [Conclusions] Human-human and human-machine interactions have positive effects on patient’s intention of using online medical question-answering services.
Key words： Online Medical Question-Answering      Interaction Perception      Usage Intention      Trust     
Received: 20 October 2017      Published: 05 February 2018
ZTFLH:  G203  
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Liyi Zhang
Huiran Li

Cite this article:

Zhang Liyi,Li Huiran. Studying Social Interaction of Online Medical Question-Answering Service. Data Analysis and Knowledge Discovery, 2018, 2(1): 76-87.

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https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2017.1038     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2018/V2/I1/76

描述变量 描述内容 频数 百分比
性别 男 170 45.8%
女 201 54.2%
年龄 18-24岁 183 49.3%
25-34岁 120 32.3%
35-49岁 57 15.4%
50岁及以上 11 3.0%
受教育
程度		 高中及以下 51 13.7%
专科 59 15.9%
本科 159 42.9%
研究生 102 27.5%
职业 学生 145 39.1%
企业职员 128 34.5%
政府/事业单位职员 43 11.6%
专业人士 11 3.0%
企业管理者 16 4.3%
其他职业 28 7.5%
互联网
使用经验		 10年以上 157 42.3%
8-10年 142 38.3%
5-7年 64 17.3%
2-4年 5 1.3%
2年以下 3 0.8%
慢性病 是 69 18.6%
否 302 81.4%
变量 测量问项 因子载荷 Cronbach's α CR AVE R2
感知自我效能
(PSEF)		 PSEF1 0.917 0.918 0.948 0.859
PSEF2 0.920
PSEF3 0.943
感知利他愉悦
(PH)		 PH1 0.837 0.909 0.932 0.734
PH2 0.861
PH3 0.840
PH4 0.869
PH5 0.876
认知信任
(CT)		 CT1 0.916 0.894 0.934 0.825 0.657
CT2 0.920
CT3 0.889
情感信任
(AT)		 AT1 0.879 0.845 0.906 0.763 0.645
AT2 0.855
AT3 0.886
(患-医交互)
感知信息支持
(PDIS)		 PDIS1 0.843 0.883 0.920 0.741
PDIS2 0.884
PDIS3 0.864
PDIS4 0.852
(患-医交互)
感知情感支持
(PDES)		 PDES1 0.823 0.829 0.898 0.746
PDES2 0.880
PDES3 0.886
(患-患交互)
感知信息支持
(PPIS)		 PPIS1 0.843 0.897 0.929 0.765
PPIS2 0.905
PPIS3 0.889
PPIS4 0.860
(患-患交互)
感知情感支持
(PPES)		 PPES1 0.896 0.871 0.921 0.795
PPES2 0.894
PPES3 0.885
感知易用性
(PEOU)		 PEOU1 0.856 0.889 0.923 0.750
PEOU2 0.859
PEOU3 0.877
PEOU4 0.874
感知有用性
(PU)		 PU1 0.895 0.906 0.941 0.842
PU2 0.917
PU3 0.940
使用意愿
(UI)		 UI1 0.902 0.903 0.939 0.838 0.809
UI2 0.919
UI3 0.925
PSEF PH CT AT PDIS PDES PPIS PPES PEOU PU UI
PSEF 0.927
PH 0.720 0.857
CT 0.650 0.805 0.908
AT 0.650 0.823 0.850 0.874
PDIS 0.628 0.734 0.778 0.757 0.861
PDES 0.619 0.718 0.620 0.667 0.665 0.863
PPIS 0.740 0.763 0.776 0.743 0.845 0.788 0.874
PPES 0.659 0.749 0.709 0.741 0.804 0.700 0.828 0.892
PEOU 0.589 0.787 0.764 0.776 0.736 0.659 0.735 0.684 0.866
PU 0.604 0.790 0.848 0.789 0.761 0.617 0.764 0.687 0.785 0.918
UI 0.671 0.816 0.844 0.825 0.816 0.636 0.773 0.719 0.790 0.835 0.915
假设 路径 结论
H1 感知自我效能->使用意愿 成立
H2 感知利他愉悦->使用意愿 成立
H3 认知信任->使用意愿 成立
H4 情感信任->使用意愿 成立
H5a 感知患-医信息支持->认知信任 成立
H5b 感知患-医信息支持->情感信任 成立
H5c 感知患-医情感支持->认知信任 不成立
H5d 感知患-医情感支持->情感信任 成立
H6a 感知患-患信息支持->认知信任 成立
H6b 感知患-患信息支持->情感信任 不成立
H6c 感知患-患情感支持->认知信任 不成立
H6d 感知患-患情感支持->情感信任 成立
H7 感知易用性->使用意愿 成立
H8 感知有用性->使用意愿 成立
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