影响受访者在社会问题解答(SQA)网站上回答与健康领域相关的问题的策略的因素

Q2 Medicine
Maedeh Kheirabadi, Afshin Mousavi Chelak, S. Ziaei, Mohsen Haji Zeinolabedini
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引用次数: 0

摘要

背景介绍对信息行为各个方面的研究已经吸引了许多研究人员的关注。本研究采用结构方程建模法来确定影响受访者在社交问题解答(SQA)网站上回答健康相关问题的策略的因素。研究方法本定量应用调查的研究对象包括在国内外 SQA 网站上回答健康相关问题的所有受访者,采用 SPSS SAMPLE POWER 软件和便利抽样法从中抽取 431 人作为样本。数据收集采用了 "受访者动机与策略问卷 "和 "社会支持问卷"。这些问卷的项目均采用 5 点李克特量表计分。采用结构方程模型法对概念研究模型进行了评估,并在 SPSS 26.0 和 AMOS 24.0 中对收集到的数据进行了分析。结果作者确定并分析了影响受访者策略的因素以及这些因素之间的关系。动机、社会支持、性别、年龄、收入、教育水平、每周活动量和响应时间对响应策略有效,因子载荷分别为 0.61、0.56、0.50、0.53、0.31、0.66、0.53 和 0.65。在结构方程模型中,反应策略的变量决定系数为 0.55,且显著。最后,可以根据自变量预测反应策略。结论为了提高响应策略,必须促进有效的响应行为,这是由影响响应策略的因素决定的。在本研究结果的帮助下,相关在线服务(如专家答疑和数字参考资料服务)的质量可以得到提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Factors Affecting Respondents’ Strategies in Answering Queries Related to the Field of Health on Social Question Answering (SQA) Websites
Background: The study of various aspects of information behavior has attracted the attention of many researchers. This study used the structural equation modeling method to identify factors affecting respondents’ strategies in answering health-related questions on social question answering (SQA) websites. Methods: The study population in this quantitative-applied survey included all respondents answering health-related questions on national and international SQA websites, among whom 431 individuals were selected as the sample using SPSS SAMPLE POWER software and convenience sampling. The data were collected using the Respondents’ Motivations and Strategies Questionnaire and the Social Support Questionnaire. The items of these questionnaires are scored on a 5-point Likert scale. The conceptual research model was evaluated using the structural equation modeling method, and the collected data were analyzed in SPSS 26.0 and AMOS 24.0. Results: The authors identified and analyzed the factors influencing respondents' strategies and the relationships between these factors. Motivations, social support, sex, age, income, level of education, amount of activity per week, and response time are effective on response strategies with factor loadings of 0.61, 0.56, 0.50, 0.53, 0.31, 0.66, 0.53, and 0.65, respectively. The variable determination coefficient of response strategies in the structural equation model is reported to be 0.55 and significant. Finally, response strategies can be predicted based on the independent variables. Conclusion: In order to enhance response strategies, it is important to promote effective response behaviors, as determined by the components that influence response strategies. The quality of related online services, such as expert question-answering and digital reference services, can be improved with the help of the present findings.
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来源期刊
CiteScore
2.40
自引率
0.00%
发文量
90
审稿时长
8 weeks
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