Maedeh Kheirabadi, Afshin Mousavi Chelak, S. Ziaei, Mohsen Haji Zeinolabedini
{"title":"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","authors":"Maedeh Kheirabadi, Afshin Mousavi Chelak, S. Ziaei, Mohsen Haji Zeinolabedini","doi":"10.47176/mjiri.37.134","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":18361,"journal":{"name":"Medical Journal of the Islamic Republic of Iran","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Factors Affecting Respondents’ Strategies in Answering Queries Related to the Field of Health on Social Question Answering (SQA) Websites\",\"authors\":\"Maedeh Kheirabadi, Afshin Mousavi Chelak, S. Ziaei, Mohsen Haji Zeinolabedini\",\"doi\":\"10.47176/mjiri.37.134\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":18361,\"journal\":{\"name\":\"Medical Journal of the Islamic Republic of Iran\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Medical Journal of the Islamic Republic of Iran\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.47176/mjiri.37.134\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medical Journal of the Islamic Republic of Iran","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47176/mjiri.37.134","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Medicine","Score":null,"Total":0}
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.