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標題: | Covid-19疫情期間民眾使用通訊診療行為意圖的影響因素 The Factors Associated with the Inclination to Use Online Doctor Consultation Amid the Covid-19 Pandemic |
作者: | 詹乃竹 Nai-Chu Chan |
指導教授: | 郭年真 NIEN-CHEN KUO |
關鍵字: | 整合型科技接受模式,UTAUT模型,通訊診療,行為意圖,新冠肺炎, Unified Theory of Acceptance and Use of Technology,UTAUT Model,Telemedicine,Behavioral Intention,Covid-19, |
出版年 : | 2024 |
學位: | 碩士 |
摘要: | 研究背景:遠距照護服務在國際間快速發展,尤其是COVID-19疫情的影響功不可沒,除需求人口的增加及國際趨勢外,台灣政府也看見了通訊診療發展的必要性,逐步在法規上放寬通訊診療適用的情境,然過往針對通訊診療受限於法規限制,民眾對於通訊診療的認知不足,或是僅提供一個對於通訊診療服務的概述供民眾想像,因此無法合適地測量整影響民眾使用通訊診療之因素,然而經歷Covid-19過後,透過政府大量的文宣傳播,台灣國人普遍對於通訊診療有初步認識,部分民眾甚至具有使用經驗,提供研究者切入的時機點,以更全面的探討影響使用者使用通訊診療意圖的影響因素。
研究目的: 以整合型科技接受 (unified theory of acceptance and use of technology, UTAUT) 模式為研究架構,探討影響民眾使用通訊診療的預測因子,提供台灣未來發展通訊診療服務之初探,並驗證以簡化後的UTAUT問卷題項施測之模型解釋力。 研究方法: 本研究為次級資料分析,資料來自郭年真老師國科會研究計畫(MOST110-2410-H002-115-SS3 )之問卷回收數據,研究對象為2022年12月台灣年滿20歲以上之成年民眾,總收樣之樣本數為1,494。統計分析部分使用單變項分析呈現樣本社會人口學結構及研究變項的次數分配。雙變相分析使用卡方檢定列聯表方式,呈現社會人口學變項與使用意願的關係。最後,多變相分析的部分,先利用多重插補法方式,使用社會人口學變項及就醫選擇等變項作為預測變項,並對「績效預期」、「努力預期」、「社會影響」、「便利條件」、「焦慮」變項之題項進行遺漏值插補,採用偏最小平方法的結構方程模型(PLS-SEM)進行影響因素的路徑係數分析,驗證研究架構中各變項與台灣成年民眾使用通訊診療意圖之間的關係與模型解釋力,並檢驗性別、年齡及經驗對「績效預期」、「努力預期」、「社會影響」、「便利條件」、「焦慮」變項間的調節作用。 研究結果:本研究的描述性統計結果顯示,樣本中的女性多於男性,且樣本年齡偏高。超過半數的受訪者教育程度在「高中、職」以上,自覺身體健康狀態良好並有全職工作。超過九成的受訪者平時有使用手機的習慣,但僅有三成曾經使用過通訊診療服務。在雙變項分析中,結果顯示「男性」、「65歲至69歲」、「國小以下教育程度」、「有兼職工作或具學生身分」、「月收入未滿2萬元」、以及自評健康狀態為「非常差」的組別中,擁有最高的使用通訊診療意願。多變項分析結果顯示,以簡化問卷題目施測之模型解釋力為0.38,「績效預期」、「努力預期」和「便利條件」這三個變項分數對台灣成年民眾使用通訊診療的意圖具有顯著正相關。而「焦慮」分數則與「使用意圖」分數呈顯著負相關。此外,研究結果發現,這些變項之間的關係不受年齡、性別和使用經驗影響,顯示調節效果不具統計顯著性。 結論:本研究顯示,「績效預期」、「努力預期」和「便利條件」是推動台灣民眾使用通訊診療服務的重要因素,而減少民眾使用「焦慮」則有助於提高其使用意圖。未來的政策制定和系統設計應著重於提升這些關鍵因素,以促進通訊診療服務的普及和使用。而使用簡化過的問卷驗證UTAUT模型,模型的解釋力為0.38,符合Cohen (1988) 對行為科學解釋力的標準,且與其他遠距醫療與通訊診療相關研究的解釋力相當,顯示本研究使用的問卷題項在驗證UTAUT模型方面具有一定的有效性。 Background: The international growth of telehealth services, significantly accelerated by the COVID-19 pandemic, is remarkable. Beyond the rising demand and global trends, the Taiwanese government has recognized the importance of advancing telemedicine and has gradually eased regulations to support its implementation. Historically, public awareness of telemedicine in Taiwan has been limited due to regulatory constraints, providing only a broad overview rather than a detailed assessment of factors influencing its use. However, the extensive promotion during the COVID-19 pandemic has led to a general understanding of telemedicine among the Taiwanese public, with some individuals even gaining practical experience. This creates an ideal opportunity for researchers to explore the factors that influence users' intentions to adopt telemedicine. Objective: This study aims to explore the predictive factors influencing the intention to use telemedicine in Taiwan, using the Unified Theory of Acceptance and Use of Technology (UTAUT) model as the research framework. Additionally, the study seeks to verify the explanatory power of a simplified UTAUT questionnaire. Methods: This secondary data analysis utilized questionnaire data from Professor Nien-Chen Kuo’s National Science and Technology Council project (MOST110-2410-H002-115-SS3). The study population comprised Taiwanese adults aged 20 and above as of December 2022, with a total sample size of 1,494. Descriptive statistics were used to present the sociodemographic structure and frequency distribution of research variables. Bivariate analysis employed chi-square tests to illustrate the relationship between sociodemographic variables and the intention to use telemedicine. For multivariate analysis, multiple imputation was first used with sociodemographic variables and healthcare choices as predictors to impute missing values for "performance expectancy," "effort expectancy," "social influence," "facilitating conditions," and "anxiety." The study then used Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze the path coefficients of factors, verifying the relationships between variables and the explanatory power of the model, and examining the moderating effects of gender, age, and experience on these variables. Results: Descriptive statistics revealed that the sample consisted of more females than males, with an older age distribution. Over half of the respondents had an education level above high school, perceived their health status as good, and had full-time jobs. Over 90% of respondents regularly used mobile phones, but only 30% had used telemedicine services. Bivariate analysis indicated that the groups with the highest intention to use telemedicine included "males," "ages 65-69," "education level below elementary school," "part-time workers or students," "monthly income below 20,000 TWD," and those who rated their health status as "very poor." Multivariate analysis showed that the simplified questionnaire's model had an explanatory power of 0.38. The scores for "performance expectancy," "effort expectancy," and "facilitating conditions" were positively correlated with the intention to use telemedicine among Taiwanese adults, while "anxiety" was negatively correlated with usage intention. Furthermore, the relationships between these variables were not significantly moderated by age, gender, or experience, indicating no statistically significant moderation effects. Conclusions: This study demonstrates that "performance expectancy," "effort expectancy," and "facilitating conditions" are crucial factors driving the intention of Taiwanese individuals to use telemedicine services, while reducing "anxiety" can further enhance their intention to use these services. Future policy formulation and system design should focus on enhancing these key factors to promote the widespread use of telemedicine services. The explanatory power of the simplified UTAUT questionnaire was 0.38, meeting Cohen's (1988) behavioral science standards and aligning with the explanatory power of related studies on telehealth and telemedicine. This indicates that the questionnaire used in this study is valid for verifying the UTAUT model. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/94910 |
DOI: | 10.6342/NTU202403900 |
全文授權: | 同意授權(限校園內公開) |
顯示於系所單位: | 健康政策與管理研究所 |
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