跳到主要內容

臺灣博碩士論文加值系統

(44.200.86.95) 您好!臺灣時間:2024/05/18 12:42
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

: 
twitterline
研究生:沈沛婕
研究生(外文):SHEN, PEI-JIE
論文名稱:醫療零接觸:後疫情時代民眾使用遠距醫療之意圖探討
論文名稱(外文):Zero Contact Healthcare: A Study on Intention to Use Telemedicine in the Post-Pandemic Era
指導教授:羅美玲羅美玲引用關係
指導教授(外文):LUO, MEI-LING
口試委員:林文昌黃正魁
口試委員(外文):LIN, WEN-CHANGHUANG, CHENG-KUI
口試日期:2023-06-28
學位類別:碩士
校院名稱:國立中正大學
系所名稱:資訊管理系醫療資訊管理研究所
學門:商業及管理學門
學類:醫管學類
論文種類:學術論文
論文出版年:2023
畢業學年度:111
語文別:中文
論文頁數:131
中文關鍵詞:遠距醫療保護動機理論整合科技接受模型行為意圖
外文關鍵詞:TelemedicineCOVID-19Protection motivation theoryUTAUTBehavior intention
相關次數:
  • 被引用被引用:0
  • 點閱點閱:301
  • 評分評分:
  • 下載下載:104
  • 收藏至我的研究室書目清單書目收藏:0
過去遠距醫療在台灣並沒有很大的發展,但因為 COVID-19 大流行的爆發並迅速地擴散於全台,因此政府放寬了諸多與遠距醫療相關的法律限制,增強疫情期間的應變能力。即使遠距醫療因應疫情期間被許多醫院採用,但在疫情趨緩甚至是後疫情時代的到來時,民眾對遠距醫療在醫療領域中採用的意願性也是值得探討的問題。
本研究以保護動機理論作為主要的研究架構,探討民眾在產生保護動機與採用遠距醫療的行為因素,並加入整合科技模型理論中的績效預期、努力預期以及社群影響三個構面,以了解在保護動機理論所產生的保護動機影響行為意圖與整合科技模型理論三個構面透過態度影響行為意圖中,進而探討影響民眾在後疫情時代使用遠距醫療的因素有哪些。
本研究使用網路問卷調查法,隨機抽樣總共 280 位台灣民眾,在進行資料分析後得出以下研究結果:感知威脅嚴重性與脆弱性皆會正向影響恐懼;反應效能與自我效能皆會正向影響保護動機;績效期望、努力期望與社群影響皆會正向影響態度;保護動機與態度皆會正向影響行為意圖。
In the past, telemedicine did not have a great development in Taiwan, but due to the outbreak of the COVID-19 pandemic and the rapid spread throughout Taiwan, the Taiwan authorities have relaxed many legal restrictions related to telemedicine to enhance the resilience during the pandemic. Although telemedicine has been adopted by many hospitals in response to the pandemic, it is worth exploring the willingness of the public to adopt telemedicine in the medical field when the pandemic slows down or even the post-pandemic era advents.
Through the discussion and collation of literature, this study takes the protection motivation theory as the main research framework, explores the behavioral factors of people in generating protection motivation and the use of telemedicine, then adds three components of performance expectancy, effort expectancy and social influence in the theory of UTAUT. Understanding the protective motivation influence behavior intention generated in the protection motivation theory, and integrating three aspects of UTAUT to influence behavior intention through attitude, then find the factors affecting people's use of telemedicine in the post-pandemic era.
This study used the online questionnaire survey method to randomly sample a total of 280 Taiwanese people. After data analysis, the results show that perceived threat severity and vulnerability positively affect fear. Response efficacy and self-efficacy positively affect protection motivation. Performance expectancy, effort expectancy and social influence positively influence attitudes. Protection motivation and attitude positively influence behavior intention.

圖目錄 vi
表目錄 vii
第一章 緒論 1
1.1 研究背景 1
1.2 研究動機 3
1.3 研究問題與目的 6
1.4 研究流程 8
第二章 文獻探討 9
2.1 遠距醫療(Telemedicine) 9
2.2 新型冠狀病毒肺炎(COVID-19) 12
2.3 保護動機理論(Protection Motivation Theory, PMT) 15
2.3.1 保護動機理論概論 15
2.3.2 保護動機理論相關研究 21
2.4整合性科技接受模式(Unified Theory of Acceptance and Use of Technology, UTAUT) 28
2.4.1 UTAUT模型概論 28
2.4.2 UTAUT模型相關理論 34
第三章 研究方法與設計 41
3.1 研究架構 41
3.2 研究假設 43
3.2.1 感知威脅嚴重性與感知威脅脆弱性對恐懼之影響 43
3.2.2恐懼引發對於保護動機之影響 43
3.2.3 反應效能、自我效能與反應成本對於保護動機之影響 44
3.2.4 績效預期、努力預期以及社群影響對態度之影響 44
3.2.5 保護動機對於行為意圖之影響 45
3.2.6 態度對於行為意圖之影響 45
3.3 研究變數衡量與操作型定義 47
3.4 問卷設計與發放 48
3.4.1 研究對象與範圍 48
3.4.2 研究前測 49
3.4.3 研究問卷設計與發放 49
第四章 資料分析方法 51
4.1 第一組樣本分析結果 51
4.1.1 敘述性統計分析 51
4.1.2 研究問項敘述性統計分析 57
4.1.3 共同方法變異(Common Method Biases, CMV)分析 59
4.1.4 信度(Reliability)分析 61
4.1.5 內容效度(Content Validity)分析 62
4.1.6 建構效度(Construct Validity)分析 63
4.1.7 結構方程模式分析(Structural Equation Modeling, SEM) 68
4.1.8 路徑係數與假說檢定 68
4.1.9 模型預測力檢定 70
4.1.10 相關性分析 71
4.2 第二組樣本分析結果 73
4.2.1 敘述性統計分析 73
4.2.2 研究問項敘述性統計分析 79
4.2.3 共同方法變異(Common Method Biases, CMV)分析 81
4.2.4 信度(Reliability)分析 83
4.2.5 內容效度(Content Validity)分析 84
4.2.6 建構效度(Construct Validity)分析 84
4.2.7 結構方程模式分析(Structural Equation Modeling, SEM) 89
4.2.8 路徑係數與假說檢定 89
4.2.9 模型預測力檢定 90
4.2.10 相關性分析 92
4.2.11 模型泛化(Model Generalization)檢測 94
第五章 結論與建議 96
5.1 研究結論 96
5.1.1 Study1與Study2結果比對 96
5.1.2 檢驗結果 97
5.1.3 感知威脅嚴重性與感知威脅脆弱性對恐懼的影響 98
5.1.4 恐懼對保護動機的影響 98
5.1.5 反應效能、自我效能與反應成本對保護動機的影響 99
5.1.6 績效期望、努力期望以及社群影響對態度的影響 100
5.1.7 保護動機對行為意圖的影響 101
5.1.8 態度對行為意圖的影響 102
5.2 研究貢獻 103
5.2.1 實務面 103
5.2.2 學術理論面 103
5.3 研究限制 104
5.3.1 樣本代表性不足 104
5.3.2 樣本選擇 105
5.3.3 研究與問卷設計 105
5.3.4 理論模型的適用性 106
5.4 未來的研究建議與方向 106
參考文獻 108
中文文獻 108
英文文獻 109
附錄:研究問卷 126


圖目錄

圖 1.1 2021年使用遠距醫療成年人百分比 4
圖 1.2 本研究之研究流程圖 8
圖 2.1 遠距醫療市場規模預測(2021-2027) 11
圖 2.2 全球COVID-19確診人數與死亡人數 14
圖 2.3 保護動機理論架構(1975) 16
圖 2.4 保護動機理論模型(1983) 18
圖 2.5 保護動機理論架構(2000) 19
圖 2.6 保護動機理論模型(2015) 20
圖 2.7 整合性科技接受模式模型圖 29
圖 3.1 本研究架構圖 42
圖 4.1 Study1整體研究架構結果模型 71
圖 4.2 Study2整體研究架構結果模型 91


表目錄

表 2.1 保護動機理論各構面定義(2015) 20
表 2.2 COVID-19期間與保護動機理論之相關文獻 23
表 2.3 UTAUT相關理論 28
表 2.4 績效期望之相關構面與來源模型 30
表 2.5 努力期望之相關構面與來源模型 31
表 2.6 社會影響之相關構面與來源模型 32
表 2.7 便利條件之相關構面與來源模型 33
表 2.8 近期UTAUT理論模型之相關文獻 35
表 3.1 本研究之研究假設 46
表 3.2 本研究變數之操作型定義 47
表 4.1 Study1樣本性別分析 52
表 4.2 Study1樣本年齡分析 52
表 4.3 Study1樣本教育程度分析 53
表 4.4 Study1樣本職業分析 54
表 4.5 Study1樣本居住地區分析 55
表 4.6 Study1樣本每個月平均薪資分析 55
表 4.7 Study1樣本是否使用過遠距醫療分析 56
表 4.8 Study1樣本使用遠距醫療時間分析 56
表 4.9 Study1研究問項之敘述性統計分析 57
表 4.10 Study1因素分析整體解釋變異量(部分) 60
表 4.11 Study1樣本各個構面之信度分析 61
表 4.12 Study1樣本KMO與Bartlett球型檢定 63
表 4.13 Study1樣本各個構面及問項之收斂效度 65
表 4.14 Study1樣本各構面之區別效度矩陣 67
表 4.15 Study1樣本路徑係數分析結果 69
表 4.16 Study1模型解釋能力 70
表 4.17 Study1相關係數矩陣 72
表 4.18 Study2樣本性別分析 74
表 4.19 Study2樣本年齡分析 74
表 4.20 Study2樣本教育程度分析 75
表 4.21 Study2樣本職業分析 76
表 4.22 Study2樣本居住地區分析 77
表 4.23 Study2樣本每個月平均薪資分析 77
表 4.24 Study2樣本是否使用過遠距醫療分析 78
表 4.25 Study2樣本使用遠距醫療時間分析 79
表 4.26 Study2研究問項之敘述性統計分析 79
表 4.27 Study2因素分析整體解釋變異量(部分) 82
表 4.28 Study2樣本各個構面之信度分析 83
表 4.29 Study2樣本KMO與Bartlett球型檢定 85
表 4.30 Study2樣本各個構面及問項之收斂效度 86
表 4.31 Study2樣本各構面之區別效度矩陣 88
表 4.32 Study2樣本路徑係數分析結果 89
表 4.33 Study2模型解釋能力 90
表 4.34 Study2相關係數矩陣 93
表 4.35 Study2多組分析結果表 95
表 5.1 模型假說檢驗結果 97


中文文獻

郭光明、楊晴雯、曾溥元、黃韋慈(2014)。電子病歷隱私保護政策遵循之探討-整合理性行為理論與保護動機理論觀點。

陳寬裕(2018)。結構方程模型分析實務:SPSS與SmartPLS的運用。https://books.google.com.tw/books?id=uDmnDwAAQBAJ&pg=PA480&lpg=PA480&dq=%E5%A4%9A%E7%BE%A4%E7%B5%84%E5%88%86%E6%9E%90+Model+generalization&source=bl&ots=8S1e_ubZ1v&sig=ACfU3U2w7yarh1ScCEpCBd5yquAr2f1yWA&hl=zh-TW&sa=X&ved=2ahUKEwjNhrqnuMr_AhWbHXAKHWr7DVIQ6AF6BAgjEAM#v=onepage&q=%E5%A4%9A%E7%BE%A4%E7%B5%84%E5%88%86%E6%9E%90%20Model%20generalization&f=false

侯冠宇(2021)。疫情嚴重下國人善用線上醫療資源,遠距醫療諮詢成長4.8成。DIGITIMES科技網智慧應用之解決方案。https://www.digitimes.com.tw/iot/article.asp?cat=130&cat1=40&id=0000611189_DGO2JMO77LQQ6GL1C13RN

羅真(2021)。2021遠距醫療健保給付元年,將帶給國內醫療什麼改變?康健網站。https://www.commonhealth.com.tw/article/83482

陳潔、柯皓翔(2021)。COVID-19病毒變身全解析。報導者(THE REPORTER)。https://www.twreporter.org/a/sars-cov-2-variants

國家高速網路計算中心(2023年6月)。台灣疫情報告。COVID-19全球疫情地圖。https://covid-19.nchc.org.tw/

社會創新平台(2022)。叮咚,您的醫師上線了!。https://si.taiwan.gov.tw/Home/sdgs/medicalview

醫聯網(2022)。醫聯網「疫後健康行為調查」結果公開!https://med-net.com/News/More/8f18b04a-3fc0-4c94-8400-24d42a8d5c3b

王芊淩(2022)。疫情下基層院所就診降幅最高!減少近四成民眾就醫可近性。Health&Help(HEHO)。https://heho.com.tw/archives/230116

梁元齡(2022)。疫情驅動「零接觸」醫療,線上看診意願成長7倍!康健網站。健康新知。https://www.commonhealth.com.tw/article/85843

Huang, K. (2022)。 “台灣健康醫療數位化價速起步,遠距醫療成未來新常態”。 GENE ONLINE。https://geneonline.news/telemedicine-in-taiwan-kpmg-2/


英文文獻

Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ.
Abad, C., Fearday, A., & Safdar, N. (2010). Adverse effects of isolation in hospitalised patients: a systematic review. Journal of Hospital Infection, 76(2), 97-102. https://doi.org/10.1016/j.jhin.2010.04.027
Asvinigita, L.R.M., Piartrini, P.S., Suprapti, N.W.S., & Widagda, K. (2021). Application of Theory of Reasoned Action (TRA) to Explain Continued Intention to Adopt (CIA) MHealth Services. Webology, 19. 10.14704/WEB/V19I1/WEB19332
Albelbisi, N.A., Al-Adwan, A.S., & Habibi, A. (2021). Impact of Quality Antecedents on Satisfaction Toward MOOC. Turkish Online Journal of Distance Education, 22(2), 164-175. https://doi.org/10.17718/tojde.906843
Alsaad, A., & Al-Okaily, M. (2021). Acceptance of protection technology in a time of fear: The case of Covid-19 exposure detection apps. Information Technology & People, 35(3), 1116-1135. 10.1108/ITP-10-2020-0719
Arfi, W.B., Nasr, I.B., Kondrateva, G., & Hikkerova, L. (2021). The role of trust in intention to use the IoT in eHealth: Application of the modified UTAUT in a consumer context. Technological Forecasting and Social Change, 167. https://doi.org/10.1016/j.techfore.2021.120688
Alhajri, N., Simsekler, M., Alfalasi, B., Alhashmi, M., Memon, B., Housser, E., Abdi, A.M., Balalaa, N., Ali, M., Almaashari, R., Memari, S., Hosani, M., Zaabi, Y., Almazrouei, S., & Alhashemi, H. (2022). Exploring Quality Differences in Telemedicine Between Hospital Outpatient Departments and Community Clinics: Cross-sectional Study. JMIR Med Inform, 10(2), 1-15. https://medinform.jmir.org/2022/2/e3237
Akinnuwesi, B., Uzoka, F.E., Fashoto, S.G., Mbunge, E., Odumabo, A., Amusa, O.O., Okpeku, M., & Owolabi, O. (2022). A modified UTAUT model for the acceptance and use of digital technology for tackling COVID-19. Sustainable Operations and Computers, 3, 118-135. https://doi.org/10.1016/j.susoc.2021.12.001
Bandura, A. (1977). Self-efficacy: toward a unifying theory of behavioral change. Psychological Review, 84(2), 191-215. https://doi.org/10.1037/0033-295X.84.2.191
Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37(2), 122-147. 10.1037/0003-066X.37.2.122
Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ.
Baker, A. (2001). Crossing the quality chasm: a new health system for the 21st century. BMJ: British Medical Journal, 323 (7322), 1192.
Bontis, N., Booker, L.D., & Serenko, A. (2007). The mediating effect of organizational reputation on customer loyalty and service recommendation in the banking industry. Management Decision, 45(9), 1426-1445. https://doi.org/10.1108/00251740710828681
Bish, A., Yardley, L., Nicoll, A., & Michie, S. (2011). Factors associated with uptake of vaccination against pandemic influenza: a systematic review. Vaccine, 29(38), 6472-6484. https://doi.org/10.1016/j.vaccine.2011.06.107
Boss, S., Galletta, D., Lowry, P.B., Moody, G. D., & Polak, P. (2015). What do systems users have to fear? Using fear appeals to engender threats and fear that motivate protective security behaviors. MIS Quarterly, 39(4), 837-864. https://www.jstor.org/stable/26628654
Brody, J.E. (2020). A Pandemic Benefit: The Expansion of Telemedicine. The New York Times. https://cacm.acm.org/news/244842-a-pandemic-benefit-the-expansion-of-telemedicine/fulltext?mobile=false
Bhati, A.S., Mohammadi, Z., Agarwal, M., Kamble, Z., & Donough-Tan, G. (2020). Motivating or manipulating: The influence of health protective behaviour and media engagement on post-COVID-19 travel. Current Issues in Tourism, 24(15). https://doi.org/10.1080/13683500.2020.1819970
Business Insights. (2021). Telemedicine Market Size, Share & COVID-19 Impact Analysis, By Type(Products and Service),By Modality(Store-and-forward (Asynchronous),Real-time(Synchronous), and Others), By Application(Teleradiology, Teleoathology, Teledermatology, Telecardiology, Telepsychiatry, and Others), By End User(Healthcare Facilities and Homecare), and Regional Forecast, 2020-2027. Market Research Report, 146. https://www.fortunebusinessinsights.com/industry-reports/telemedicine-market-101067
Compeau, D.R., & Higgins, C.A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189-211. https://doi.org/10.2307/249688
Catalano, G., Houston, S.H., Catalano, M.C., Butera, A. S., Jennings, S.M., Hakala, S.M., Burrows, S.L., Hickey, M.G., Duss, C.V., Skelton, D.N., & Laliotis, G. J. (2003). Anxiety and depression in hospitalized patients in resistant organism isolation. Southern Medical Journal, 96(2), 141-146. https://go.gale.com/ps/i.do?id=GALE%7CA98828109&sid=googleScholar&v=2.1&it=r&linkaccess=abs&issn=00384348&p=AONE&sw=w&userGroupName=anon%7E3712e35c
Cisler, J.M., Olatunji, B.O., & Lohr, J.M. (2009). Disgust, fear, and the anxiety disorders: A critical review. Clinical Psychology Review, 29(1), 34–46. https://doi.org/10.1016/j.cpr.2008.09.007
Campion, E.W., Dorsey, E., & Topol, E. (2016). State of telehealth. The New England Journal of Medicine, 375(2),154–161. https://doi.org/https://doi.org/10.1056/NEJMra1601705.
Chen, L., & Yang, X. (2019). Using EPPM to evaluate the effectiveness of fear appeal messages across different media outlets to increase the intention of breast Self-Examination among Chinese women. Health Communication, 34(11), 1369-1376. https://doi.org/10.1080/10410236.2018.1493416
Cryptocurrency Market Size By Component (Hardware [Graphical Processing Unit, Field Programmable Gate Array, Application-Specific Integrated Circuit], Software [Mining Software, Trading Software]), By Type (Bitcoin, Binance Coin, Ethereum, XRP, Tether, Cardono), By End-use (E-commerce & Retail, Trading, Peer-to-Peer Payment, Remittance), Industry Analysis Report, Regional Outlook, Growth Potential, Competitive Market Share & Forecast, 2021-2027. (2021, Apr). Global market insights. https://www.gminsights.com/industry-analysis/cryptocurrency-market
Cheng, M., Li, X. & Xu, J. (2022). Promoting Healthcare Workers’ Adoption Intention of Artificial-Intelligence-Assisted Diagnosis and Treatment: The Chain Mediation of Social Influence and Human–Computer Trust. International Journal of Environmental Research and Public Health, 19(20), 13311. https://doi.org/10.3390/ijerph192013311
Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319-340. https://doi.org/10.2307/249008
Davis, F.D., Bagozzi, R.P., & Warshaw, P.R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace 1. Journal of applied social psychology, 22(14), 1111-1132. https://doi.org/10.1111/j.1559-1816.1992.tb00945.x
Devon, H.A., Block, M E., Moyle-Wright, P., Ernst, D.M., Hayden, S.J., Lazzara, D.J., Savoy, S.M., & Kostas-Polston, E. (2007). A Psychometric Toolbox for Testing Validity and Reliability. Journal of Nursing Scholarship, 39(2), 155-164. https://doi.org/10.1111/j.1547-5069.2007.00161.x
Douthit, N., Kiv, S., Dwolatzky, T., & Biswas, S. (2015). Exposing some important barriers to health care access in the rural USA. Public Health, 129(6), 611-620. https://doi.org/10.1016/j.puhe.2015.04.001
Dorsey, E.R., & Topol, E.J. (2016). State of Telehealth. The New England journal of medicine, 375, 154-161. 10.1056/NEJMra1601705
de Wit, E., van Doremalen, N., Falzarano, D., & Munster, V.J. (2016). SARS and MERS: recent insights into emerging coronaviruses. Nature Reviews Microbiology, 14, 523-534. https://doi.org/10.1038/nrmicro.2016.81
De Meulenaer, S., De Pelsmacker, P., & Dens, N. (2018). Power distance, uncertainty avoidance, and the effects of source credibility on health risk message compliance. Health Communication, 33(3), 291-298. https://doi.org/10.1080/10410236.2016.1266573
Dwivedi, Y.K., Rana, N.P., Jeyaraj, A., Clement, M., & Williams, M.D. (2019). Re-examining the unified theory of acceptance and use of technology (UTAUT): Towards a revised theoretical model. Information Systems Frontiers, 21(3), 719-734. https://doi.org/10.1007/s10796-017-9774-y
Eccleston, C., Blyth, F.M., Dear, B.F., Fisher, E.A., Keefe, F.J., Lynch, M.E., Palermo, T.M., Reid, M.C., & de C Williams, A.C. (2020). Managing patients with chronic pain during the COVID-19 outbreak: considerations for the rapid introduction of remotely supported (eHealth) pain management services. Pain, 161(5), 889-893. 10.1097/j.pain.0000000000001885
Excler, J.L., Saville, M., Berkley, S., & Kim, J.H. (2021). Vaccine development for emerging infectious diseases. Nature Medicine, 27(4), 591-600. https://doi.org/10.1038/s41591-021-01301-0
Eberhardt, J., & Ling, J. (2021). Predicting COVID-19 vaccination intention using protection motivation theory and conspiracy beliefs. Vaccine, 39(42), 6269-6275. https://doi.org/10.1016/j.vaccine.2021.09.010
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Journal of Business Venturing, 5, 177-189.
Fornell, C., & Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1). https://doi.org/10.1177/002224378101800104
Floyd, D.L., Prentice‐Dunn, S., & Rogers, R.W. (2000). A meta-analysis of research on protection motivation theory. Journal of Applied Social Psychology, 30(2), 407-429.
Fairlie, R.W., Couch, K., & Xu, H. (2020). The impacts of COVID-19 on minority unemployment: first evidence from April 2020 CPS Microdata. National Bureau of Economic Research, 27246. 10.3386/w27246
Guler, I., Guillen, M.F., Macpherson, J.M. (2002). Global competition, institutions, and the diffusion of organizational practices: The international spread of ISO 9000 quality certificates. Administrative Science Quarterly, 47(2), 207-232. https://doi.org/10.2307/309480
Gao, Y., & Luo, Y. (2015). An Empirical Study of Wearable Technology Acceptance in Healthcare. Industrial Management & Data Systems, 115(9), 1704-1723. https://doi.org/10.1108/IMDS-03-2015-0087
Greenhalgh, T., Wherton, J., Shaw, S., & Morrison, C. (2020). Video consultations for covid-19. The British Medical Journal, 368. https://doi.org/10.1136/bmj.m998
Ghaddar, S., Vatcheva, K.P., Alvarado, S.G., & Mykyta, L. (2020). Understanding the Intention to Use Telehealth Services in Underserved Hispanic Border Communities: Cross-Sectional Study. Journal of Medical Internet Research, 22(9).
Guner, H.R., Hasanoglu, I., & Aktas, F. (2020). COVID-19: Prevention and control measures in community. Turkish Journal of Medical Sciences, 50(9). 10.3906/sag-2004-146.
Global Situation. (2023). World Health Organization. https://covid19.who.int/?mapFilter=cases
Higbee, K. L. (1969). Fifteen years of fear arousal: Research on threat appeals: 1953-1966. Psychological Bulletin, 72(6), 426-444. https://doi.org/10.1037/h0028430
Helmes, A.W. (2002). Application of the protection motivation theory to genetic testing for breast cancer risk. Preventive Medicine, 35(5), 453-462. https://doi.org/10.1006/pmed.2002.1110
Hair, J. F. (2009). Multivariate data analysis.
Henseler, J., Chin, W.W. (2010). A Comparison of Approaches for the Analysis of Interaction Effects Between Latent Variables Using Partial Least Squares Path Modeling. Structural Equation Modeling: A Multidisciplinary Journal, 17(1), 82-109. https://doi.org/10.1080/10705510903439003
Hung, W.S., Hu, S.C., Hsu, Y.C., Chen, K.L., Chen, K.H., Yu, M.C., & Chen, K.T. (2014). Factors affecting the use of anti-malaria preventive measures among Taiwan immigrants returning to malaria-endemic regions. Travel Medicine and Infectious Disease, 12(4), 370-377. https://doi.org/10.1016/j.tmaid.2013.07.001
Hoque, R., & Sorwar, G. (2017). Understanding Factors Influencing the Adoption of mHealth by the Elderly: An Extension of the UTAUT Model. International Journal of Medical Informatics, 101, 75-84. https://doi.org/10.1016/j.ijmedinf.2017.02.002
Hollander, J.E., & Carr, B.G. (2020). Virtually perfect? Telemedicine for COVID-19. New England Journal of Medicine, 382(18), 1679-1681. 10.1056/NEJMp2003539
Huang, C.K., Chen, S.H., Hu, C.C., & Lee, M.C. (2022). Understanding the adoption of the mask‑supply information platforms during the COVID‑19. Electronic Markets, 32, 2405-2427. https://doi.org/10.1007/s12525-022-00602-7
Husin, M., Rahman, N.A., Bujang, M.A., Ng, S.W., Juval, K., Hwong, W.Y., & Sivasampu, S. (2022). Translation and Validation of the Questionnaire on Acceptance to Telemedicine from the Technology Acceptance Model (TAM) for Use in Malaysia. BioMed Reaearch International. https://doi.org/10.1155/2022/9123887
Iyengar, K., Jain, V.K., & Vaishya, R. (2020). Pitfalls in telemedicine consultations in the era of COVID 19 and how to avoid them. Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 14(5), 797-799. https://doi.org/10.1016/j.dsx.2020.06.007
Iwasaki, A., & Grubaugh, N.D. (2020). Why does Japan have so few cases of COVID19? EMBO Molecular Medicine, 12. 10.15252/emmm.202012481
Kruse, C.S., Krowski, N., Rodriguez, B., Tran, L., Vela, J., & Brooks, M. (2017). Telehealth and patient satisfaction: a systematic review and narrative analysis. BMJ Open, 7(8). http://dx.doi.org/https://doi.org/10.1136/bmjopen-2017-016242
Kamal, S.A., Shafiq, M., & Kakria, P. (2020). Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM). Technology in Society, 60. https://doi.org/10.1016/j.techsoc.2019.101212
Kaium, M.A., Bao, Y., Alam, M.Z., & Hoque, M.R. (2020). Understanding Continuance Usage Intention of mHealth in a Developing Country. International Journal of Pharmaceutical and Healthcare Marketing, 14(2), 251-272. https://doi.org/10.1108/IJPHM-06-2019-0041
Koonin, L.M., Hoots, B., Tsang, C.A., Leroy, Z., Farris, K., Jolly, B.T., Antall, P., McCabe, B., Zelis, C.B.R., Tong, I., & Harris, A.M. (2020). Trends in the Use of Telehealth During the Emergence of the COVID-19 Pandemic — United States, January-March 2020. Morbidity and Mortality Weekly Report (MMWR), 69(43), 1595-1599. https://www.cdc.gov/mmwr/volumes/69/wr/mm6943a3.htm
Karaivanov, A., Kim, D., Lu, S.E., & Shigeoka, H. (2022). COVID-19 vaccination mandates and vaccine uptake. Nature Human Behaviour. https://doi.org/10.1038/s41562-022-01363-1
Khechine, H., Lakhal, S., & Ndjambou, P. (2016). A meta-analysis of the UTAUT model: Eleven years later. Canadian Journal of Administrative Sciences/revue Canadienne Des Sciences De L’administration, 33(2), 138-152. 10.1002/CJA
Kim, J., Yang, K., Min, J., & White, B. (2022). Hope, fear, and consumer behavioral change amid COVID‐19: Application of protection motivation theory. International Journal of Consumer Studies, 46(2), 558-574. https://doi.org/10.1111/ijcs.12700
Leventhal, H. (1970). Findings and Theory in the Study of Fear Communications. Advances in Experimental Social Psychology, 5, 119-186. https://doi.org/10.1016/S0065-2601(08)60091-X
Latour, M.S., & Rotfeld, H.J. (1997). There are threats and (maybe) fear-caused arousal: Theory and confusions of appeals to fear and fear arousal itself. Journal of Advertising, 26(3), 45-59. https://doi.org/10.1080/00913367.1997.10673528
Lu, W., Wang, X. P., Zhao, J., & Zhai, Y.K. (2020). Research on teleconsultation service quality based on multi-granularity linguistic information: The perspective of regional doctors. BMC Medical Informatics and Decision Making, 20(1), 113. https://doi.org/10.1186/s12911-020-01155-5
Liu, J., Liu, S., Zheng, T., & Bi, Y. (2021). Physicians’ perspectives of telemedicine during the COVID-19 pandemic in China: Qualitative survey study. JMIR Medical Informatics, 9(6). 10.2196/26463
Lunney, M., Thomas, C., Rabi, D., Bello, A.K., & Tonelli, M. (2021). Video visits using the Zoom for healthcare platform for people receiving maintenance hemodialysis and nephrologists: A feasibility study in Alberta, Canada. Canadian Journal of Kidney Health and Disease. https://doi.org/10.1177/20543581211008
Lee, W.I., Fu, H.P., Mendoza, N., & Liu, T.Y. (2021). Determinants impacting user behavior towards emergency use intentions of m-health services in Taiwan. Healthcare, 9(5), 535. https://doi.org/10.3390/healthcare9050535
Lu, W., Meng, Z., Wang, Y., Wang, Y., & Zhai, Y. (2022). Supply-demand matching in a complex telemedicine environment considering intermediary intervention. Computers & Industrial Engineering, 169. https://doi.org/10.1016/j.cie.2022.108194
Maddux, J.E., & Rogers, R.W. (1983). Protection Motivation and Self-Efficacy: A Revised Theory of Fear Appeals and Attitude Change. Journal of Experimental Social Psychology, 19(5), 469-479. https://doi.org/10.1016/0022-1031(83)90023-9
Moore, G.C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information systems research, 2(3), 192-222. https://doi.org/10.1287/isre.2.3.192
McCombs, M.E., & Shaw, D.L. (1993). The evolution of agenda-setting research: twenty-five years in the marketplace of ideas. Journal of communication, 43, 58. 10.1111/j.1460-2466.1993.tb01262.x
McDonald, R.P. (1996). Path Analysis with Composite Variables. Multivariate Behavioral Research, 31(2) ,239-270. https://doi.org/10.1207/s15327906mbr3102_5
Milne, S., Sheeran, P., & Orbell, S. (2000). Prediction and Intervention in Health-Related Behavior: A Meta-Analytic Review of Protection Motivation Theory. Journal of Applied Social Psychology, 30(1), 106-143. https://doi.org/10.1111/j.1559-1816.2000.tb02308.x
McNeill, A., Harris, P.R., & Briggs, P. (2016). Twitter influence on UK vaccination and antiviral uptake during the 2009 H1N1 pandemic. Frontiers in Public Health, 4(26). 10.3389/fpubh.2016.00026
Menard, P., Bott, G.J., & Crossler, R.E. (2017). User motivations in protecting information security: Protection motivation theory versus self-determination theory. Journal of Management Information Systems, 34(4), 1203-1230. https://doi.org/10.1080/07421222.2017.1394083
Makarovs, K., & Achterberg, P. (2017). Contextualizing educational differences in “vaccination uptake”: A thirty nation survey. Social Science & Medicine, 188, 1-10. https://doi.org/10.1016/j.socscimed.2017.06.039
Misra, R., Mahajan, R., Singh, N., Khorana, S., & Rana, N.P. (2022). Factors impacting behavioural intentions to adopt the electronic marketplace: findings from small businesses in India. Electronic Markets, 32, 1639-1660. https://doi.org/10.1007/s12525-022-00578-4
Nunnally, J. C. (1978). Psychometric Theory, 2nd Edition, McGraw-Hill, New York.
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric Theory, 3rd Edition, McGraw-Hill, New York.
Nouhi, M., Fayaz-Bakhsh, A., Mohamadi, E., & Shafii, M. (2012). Telemedicine and Its Potential Impacts on Reducing Inequalities in Access to Health Manpower. Telemedicine and e-Health, 18(8), 648-653. https://doi.org/10.1089/tmj.2011.0242
Olayiwola, J.N., Potapov, A., Gordon, A., Jurado, J., Magana, M.K., & Tuot, D. (2018). Electronic consultation impact from the primary care clinician perspective: Outcomes from a national sample. Journal of Telemedicine and Telecare, 25(8), 493-8. https://doi.org/10.1177/1357633X18784416
Ohannessian, R., Duong, T. A., & Odone, A. (2020). Global telemedicine implementation and integration within health systems to fight the COVID-19 pandemic: a call to action. JMIR Public Health and Surveillance, 6(2). 10.2196/18810
Osei, H.V., Kwateng, K.O., & bOATENG, K.A. (2022). Integration of personality trait, motivation and UTAUT 2 to understand e-learning adoption in the era of COVID-19 pandemic. Education and Information Technologies, 27, 10705-10730. https://doi.org/10.1007/s10639-022-11047-y
Podaskoff, P.M., MacKenzie, S.B., & Lee, J. (2003). Common Method Biases in Behavioral Research: A Critical Review of the Literature and Recommended Remedies. Journal of Applied Psycholog, 55(5), 879-903. 10.1037/0021-9010.88.5.87
Pagoto, S.L., McChargue, D.E., Schneider, K., & Werth Cook, J. (2004). Sun protection motivational stages and behavior: skin cancer risk profiles. American Journal of Health Behavior, 28(6), 531-541. https://doi.org/10.5993/AJHB.28.6.6
Posey, C., Roberts, T.L., & Lowry, P.B. (2015). The impact of organizational commitment on insiders’ motivation to protect organizational information assets. Journal of Management Information Systems, 32(4), 179-214. https://doi.org/10.1080/07421222.2015.1138374
Pan, A., Liu, L., Wang C, Guo, H., Hao, X., Wang, Q., Huang, J., He, N., Yu, H., Lin, X., Wei, S., & Wu, J.H. (2020). Association of Public Health Interventions with the Epidemiology of the COVID-19 Outbreak in Wuhan, China. Journal of the American Medical Association, 323(19), 1915-1923. 10.1001/jama.2020.6130
Prasetyo, Y.T.P., Castillo, A.M., Salonga, L.J., Sia, J.A., & Seneta, J.A. (2020). Factors affecting perceived effectiveness of COVID-19 prevention measures among Filipinos during Enhanced Community Quarantine in Luzon, Philippines: Integrating Protection Motivation Theory and extended Theory of Planned Behavior. International Journal of Infectious Diseases, 99, 312-323. https://doi.org/10.1016/j.ijid.2020.07.074
Pikkemaat, M., Thulesius, H., & Nymberg, V.M. (2021). Swedish Primary Care Physicians' Intentions to Use Telemedicine: A Survey Using a New Questionnaire - Physician Attitudes and Intentions to Use Telemedicine (PAIT). National Library of Medicine, 14, 3445-3455. 10.2147/IJGM.S319497
Puriwat, W., & Tripopsakul, S. (2021). Understanding Food Delivery Mobile Application Technology Adoption: A UTAUT Model Integrating Perceived Fear of COVID-19. Emerging Science Journal, 5. 10.28991/esj-2021-SPER-08
Rogers, R.W. (1975). Protection motivation theory of fear appeals and attitude-change. J. Psychol, 91, 93-114. 10.1080/00223980.1975.9915803
Rahi, S., Khan, M.M., & Alghizzawi, M. (2020). Factors influencing the adoption of telemedicine health services during COVID-19 pandemic crisis: An integrative research model. Enterprise Information Systems, 15(6), 769–793. https://doi.org/10.1080/17517575.2020.1850872
Rojas, F.L., Jiang, X., Montenovo, L., Simon, K.I., Weinberg, B.A., & Wing, C. (2020). Is the cure worse than the problem itself? immediate labor market effects of COVID-19 case rates and school closures in the US. National Bureau of Economic Research, 27127. 10.3386/w27127
Rothan, H.A., & Byrareddy, S.N. (2020). The epidemiology and pathogenesis of coronavirus disease (COVID-19) outbreak. Journal of Autoimmunity, 109, 102433. https://doi.org/10.1016/j.jaut.2020.102433
Raza, S.A., Qazi, W., Khan, K.A., & Salam, J. (2020). Social Isolation and Acceptance of the Learning Management System (LMS) in the time of COVID-19 Pandemic: An Expansion of the UTAUT Model. Journal of Educational Computing Research, 59(2), 183-208. https://doi.org/10.1177/0735633120960421
Scarpa, R., & Thiene, M. (2011). Organic food choices and Protection Motivation Theory: Addressing the psychological sources of heterogeneity. Food Quality and Preference, 22(6), 532-541. https://doi.org/10.1016/j.foodqual.2011.03.001
Sheeran, P., Harris, P.R., & Epton, T. (2014). Does heightening risk appraisals change people’s intentions and behavior? A meta-analysis of experimental studies. Psychol Bull, 140(2), 511-543. https://doi.org/10.1037/a0033065
Siswanto, T., Shofiati, R.,& Hartin, H. (2018). Acceptance and Utilization of Technology(UTAUT) as a Method of Technology Acceptance Model of Mitigation Disaster Website. IOP Conference Series: Earth and Environmental Science, 106, 1-6. 10.1088/1755-1315/106/1/012011
Song, X., Liu, X., & Wang, C. (2020). The role of telemedicine during the COVID-19 epidemic in China-experience from Shandong province. Critical Care, 24(1), 178.
Sah, R., Shrestha, S., Mehta, R., Sah, S.K., Rabaan, A.A., Dhama, K., & Rodriguez-Morales, A.J. (2021). AZD1222 (Covishield) vaccination for COVID-19: Experiences, challenges, and solutions in Nepal. Travel Med Infect Dis, 40. 10.1016/j.tmaid.2021.101989
Sah, R., Khatiwada, A.P., Shrestha, S., Bhuvan, K.C., Tiwari, R., Mohapatra, R.K., Dhama, K., & Rodriguez-Morales, A.J. (2021). COVID-19 vaccination campaign in Nepal, emerging UK variant and futuristic vaccination strategies to combat the ongoing pandemic. Travel Med Infect Dis, 41. https://doi.org/10.1016/j.tmaid.2021.102037
Saefudin, Kurdi, S., & Apriliyanto, N. (2022). Implementation of Quick Response (Qr) Code in Indonesian Restaurants: Integration of Protection Motivation Theory (Pmt) And Theory Of Planned Behavior (Tpb). Institute of Computer Science (IOCS), 6(2), 1920-1928. https://doi.org/10.35335/mantik.v6i2.2663
Sahut, J.M., & Lissillour, R. (2022). The adoption of remote work platforms after the Covid-19 lockdown: New approach, new evidence. Journal of Business Research, 154. https://doi.org/10.1016/j.jbusres.2022.113345
Siripipatthanakul, S., Sriboonruang, P., Limna, P., & Kaewpuang, P. (2022). Applying the TPB and the UTAUT Models Predicting Intentions to Use Telemedicine Among Thai People During the COVID-19 Pandemic. International Journal of Computing Sciences Research, 6, 1-23. 10.25147/ijcsr.2017.001.1.107
Triandis, H.C. (1979). Values, attitudes, and interpersonal behavior. Nebraska Symposium on Motivation, 27, 195-259.
Tanner, J.F., Hunt, J.B., & Eppright, D.R. (1991). The Protection Motivation Model: A Normative Model of Fear Appeals. Journal of Marketing, 55(3). https://doi.org/10.1177/002224299105500304
Thompson, R.L., Higgins, C.A., & Howell, J.M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 125-143. https://doi.org/10.2307/249443
Taylor, S., & Todd, P.A. (1995). Understanding information technology usage: A Test of Competing Models. Information systems research, 6(2), 144-176. https://doi.org/10.1287/isre.6.2.144
Taylor, S., & Todd, P. (1995). Assessing IT Usage: The Role of Prior Experience. MIS Quarterly, 19(4), 561-570. https://doi.org/10.2307/249633
Trochim, W.M., & Donnelly, J.P. (2001). Research Methods Knowledge Base. http://www.researchgate.net/publication/243783609
Tavakol,M., & Dennick, R. (2011). Making sense of Cronbach's alpha. International journal of medical education, 2, 53-55. 10.5116/ijme.4dfb.8dfd
Thomas, T.D., Singh, L.,& Gaffar, K. (2013). The utility of the UTAUT model in explaining mobile learning adoption in higher education in Guyana. International Journal of Education and Development using Information and Communication Technology(IJEDICT), 9(3), 71-85. http://ijedict.dec.uwi.edu/
TELEHEALTH.HHS.GOV. "What is telehealth?". (2022, September). Health Resources & Services Administration. https://telehealth.hhs.gov/patients/understanding-telehealth/#what-is-telehealth
Using Telehealth to Expand Access to Essential Health Services during the COVID-19 Pandemic. (2020, June). Centers for Diseases and Prevention. https://public4.pagefreezer.com/browse/CDC%20Covid%20Pages/11-05-2022T12:30/https://www.cdc.gov/coronavirus/2019-ncov/hcp/telehealth.html
Vallerand, R.J. (1997). Toward a Hierarchical Model of Intrinsic and Extrinsic Motivation. Advances in Experimental Social Psychology, 29, 271-360. https://doi.org/10.1016/S0065-2601(08)60019-2
Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540
Venkatesh, V., Thong, J.Y.L, & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Quarterly, 36 (1), pp. 157-178. https://doi.org/10.2307/41410412
Velavan, T.P., & Meyer, C.G. (2020). Estimation of risk factors for COVID-19 mortality-preliminary results. Tropical Medicine and Inter, 25(3), 278-280. 10.1111/tmi.13383
Witte, K., Berkowitz, J.M., Cameron, K.A., & McKeon, J.K. (1998). Preventing the spread of genital warts: Using fear appeals to promote self-protective behaviors. Health Education & Behavior, 25(5), 571-585. https://doi.org/10.1177/109019819802500505
Wang, J., Liu-Lastres, B., Ritchie, B.W., & Mills, D.J. (2019). Travellers’ self-protections against health risks: An application of the full Protection Motivation Theory. Annals of Tourism Research, 78, 102743. https://doi.org/10.1016/j.annals.2019.102743
Wang, P.W., Ahorsu, D.K., Lin, C.Y., Chen, I.H., Yen, C.F., Kuo, Y.J., Griffiths, M.D., & Pakpour, A.H. (2021). Motivation to Have COVID-19 Vaccination Explained Using an Extended Protection Motivation Theory among University Students in China: The Role of Information Sources. Vaccines, 9(4), 380. https://doi.org/10.3390/vaccines9040380
Wolf, C.(2022). "Who Used Telemedicine in 2021?". U.S. News & World Report. https://www.usnews.com/news/health-news/articles/2022-10-13/women-older-adults-more-likely-to-use-telemedicine-in-2021
Wu, F., Yuan, Y., Deng, Z., Yin, D., Shen, Q., Zeng, J., Xie, Y., Xu, M., Yang, M., Jiang, S., Zhang, C., Lu, H., & Sun, C. (2022). Acceptance of COVID-19 booster vaccination based on the protection motivation theory: A cross-sectional study in China. Journal of Medical Virology, 94(9), 4115-4124. https://doi.org/10.1002/jmv.27825
Yang, M., Mamun, A.A., Mohiuddin, M., Nawi, N.C., & Zainol, N.R. (2021). Cashless Transactions: A Study on Intention and Adoption of e-Wallets. Sustainability, 13(2), 831. https://doi.org/10.3390/su13020831
Zhao, X., & Cai, X. (2009). The role of risk, efficacy, and anxiety in smokers’ cancer information seeking. Health Communication, 24(3), 259-269. https://doi.org/10.1080/10410230902805932
Zhang, X., Liu, S., Wang, L., Zhang, Y., & Wang, J. (2020). Mobile health service adoption in China: Integration of theory of planned behavior, protection motivation theory and personal health differences. Online Information Review, 44(1), 1-23. https://doi.org/10.1108/OIR-11-2016-0339

QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
無相關期刊