資料載入中.....
|
請使用永久網址來引用或連結此文件:
http://libir.tmu.edu.tw/handle/987654321/36323
|
| 題名: | 影響北部三所醫院醫護人員個人健康紀錄使用意願之因素 |
| 作者: | 陳亭羽 |
| 貢獻者: | 醫務管理學研究所 |
| 日期: | 2010 |
| 上傳時間: | 2010-10-20 11:51:50 (UTC+8) |
| 摘要: | 背景與目的：個人健康紀錄(Personal Health Record, PHR)是一個可以協助醫護人員執行醫療照護的工具，它不僅可提供正確、及時之資訊，以維護與管理個人健康，且能因此節省整體醫療浪費並提高醫療照護品質。然而醫師及護理人員對於PHR之態度及使用意願，將會影響此系統是否能夠有效發揮功效。因此，本研究應用科技接受模型(Technology Acceptance Model, TAM)等理論，由影響醫護人員的認知及態度之因素來探討其使用意願，期望從理論模型之建構作為醫療機構未來推動PHR之參考。
方法：本研究為橫斷性研究，以自填性結構問卷為研究工具，採立意取樣方式，以台北縣市三所醫院醫護人員為研究對象。問卷內容在經過效度及信度檢定後進行測試。調查期間爲99年4月19日至99年5月21日，問卷之回收結果，醫師部份，發出470份，有效問卷204份，回收率為43.40%；護理人員部份，發出1060份，有效問卷468份，問卷回收率為44.15%。問卷資料經整理後，分別使用SPSS12.0及AMOS18.0統計套裝軟體，進行描述性及結構方程模式(Structural Equation Modeling, SEM)統計分析。
結果：本研究以驗證性因素分析，並刪除變項修正以取得最佳解釋模型後，醫師部份，修正模式之卡方值為386.854、卡方值/自由度為1.653。GFI為0.864、AGFI為0.826、RMSEA為0.057，其值表示在整體模式有合理的配適度。而諸多影響醫師PHR使用意願之因素中，最顯著的為「知覺有用性」（整體效果=0.449, p<0.001)，另醫師的使用態度可解釋使用意願39.4%之變異，而相關研究變項可解釋使用態度56.3%的變異，其中知覺有用性、資料安全及主觀規範對使用態度有正向之顯著影響;而護理人員部份，修正模式之卡方值為647.356、卡方值/自由度為2.304。GFI為0.902、AGFI 為0.877、RMSEA為0.053，且RMSEA值接近0.05，表示在整體模式有合理的配適度。而影響護理人員PHR使用意願之因素中，則是以「主觀規範」為關鍵因素(整體效果=0.216, p＜0.05)，護理人員之使用態度可解釋使用意願89.2%之變異，而相關研究變項可解釋使用態度82.6%的變異，其中知覺有用性、知覺易用性、電腦自我效能及主觀規範對使用態度有正向之顯著影響。
結論：醫護人員對於個人健康紀錄之使用意願，經由本研究模型之建構，醫師資料與TAM理論部分相符，護理人員則完全符合。大部分之醫護人員均願意使用個人健康紀錄且持正向之態度，且使用態度對使用意願有正向之顯著影響。因此未來醫療機構在PHR設計上，應注重產生醫療照護之實質效益進而提升其有用性，並制訂相關的推行政策以提高使用意願。
Background and Objectives: Personal Health Record (PHR) is a tool for clinicians to provide care effectively and save medical cost by accurate and timely health information. However, whether the PHR system could be successful implemented depends on physicians and nurses’ attitude and behavior intention. This study will explore the factors affecting clinicians’ intentions of PHR which is based on Technology Acceptance Model (TAM) and related theories. The theoretical model we built could also be referred to hospital PHR implementation.
Methods: It was a cross-sectional study and conducted by structured questionnaire. We used judgmental sampling that subjects were physicians and nurses in three hospitals of northern Taiwan. After verifying validity and reliability, questionnaires were collected in the period of April 19 to June 21, 2010. A total of 204 valid questionnaires were collected from physicians (response rate: 43.40%) and 468 from nurses (44.15%). SPSS12.0 and Structural Equation Modeling (SEM) statistics software were used to analyze data and verify the hypotheses.
Result: The confirmatory factor analysis (CFA) was used to revise the factor structure and get the optimized model. The revised model of χ2, χ2/df , GFI, AGFI and RMSEA for physicians were 386.854, 1.653, 0.864, 0.826 and 0.057 respectively, which showed the theoretical model fitted the observed data well. Perceived usefulness played the most significant factor for physicians’ attitude (total effect=0.449, p<0.001). Physicians’ attitude explained 39.4% variances of their PHR behavior intention. The results also showed that perceived usefulness, security, and subjective norm influenced physicians’ attitude positively. Similarly, the theoretical model for nurses fitted the observed data well, the revised model of χ2, χ2/df , GFI, AGFI and RMSEA were 647.356, 2.304, 0.902, 0.877 and 0.053 respectively. Subjective norm played the most significant factor for nurses (total effect=0.216, p<0.05). Nurses’ attitude explained 89.2% of their PHR intention. The results also showed that perceived useful, ease of use, computer self-efficacy and subjective norm influenced nurses’ attitude positively.
Conclusions: The models constructed by our study fitted the TAM and found that physicians and nurses had the positive intention and attitude of PHR. Moreover, clinicians’ attitude influenced their behavior intention significantly (p<0.001). Therefore, the design of PHR should be focused on usefulness, and policies of healthcare organizations should offer incentives to promote the acceptance of PHR. |
| 關聯: | 120頁 |
| 描述: | 致謝 I
中文摘要 II
Abstract IV
目錄 VI
表目錄 VIII
圖目錄 IX
第一章 前言 1
第一節 研究背景與動機 1
第二節 研究重要性 4
第三節 研究目的 6
第二章 文獻探討 7
第一節 個人健康紀錄的定義及效益 7
第二節 個人健康紀錄的發展現況 10
第三節 醫療資訊的隱私安全 14
第四節 電腦自我效能 17
第五節 資訊科技接受度的理論與模式 19
第六節 總結 25
第三章 研究方法與設計 26
第一節 研究架構 27
第二節 研究假說 28
第三節 研究變項及操作型定義 29
第四節 研究材料與方法 32
第五節 資料處理及分析方法 36
第四章 研究結果 40
第一節 問卷回收情形 40
第二節 樣本基本資料分析 41
第三節 研究變項描述性統計 46
第四節 使用結構方程模式驗證研究模型 54
第五章 討論 71
第一節 研究假說驗證 71
第二節 認知及對使用態度之影響 73
第三節 其它因素對使用態度之影響 76
第四節 使用態度及使用意願 80
第五節 研究限制 82
第六章 結論與建議 83
第一節 結論 83
第二節 建議 87
參考文獻 89
中文部份 89
英文部份 93
附錄 99
附錄一：專家內容效度之專家 99
附錄二：內容效度審查結果彙整 100
附錄三：研究問卷 103
附錄四：最適模式題項內容(醫師) 109
附錄五：最適模式題項內容(護理人員) 110
附錄六：問卷題項簡稱對照表 111
附錄七：簡介影片內容 113
表目錄
表2-1 個人健康紀錄的定義彙整表 8
表2-2 醫療領域相關科技接受模式文獻彙整 23
表3-1 變項名稱、操作型定義及資料屬性 30
表3-1 變項名稱、操作型定義及資料屬性(續) 31
表3-2 原始問卷量表之信度分析 35
表3-3 本研究所採用之配適度指標一覽表 38
表4-1 各職業類別回收情形一覽表 40
表4-2 樣本基本資料分析 44
表4-3 研究變項次數分配表(醫師) 50
表4-4 研究變項次數分配表(護理人員) 52
表4-5 本研究模式配適情形(醫師) 63
表4-6 本研究模式配適情形(護理人員) 63
表4-7 SEM最適模式修正過程(醫師) 64
表4-8 SEM最適模式修正過程(護理人員) 64
表4-9 測量模式之信度和效度的評估(醫師) 65
表4-10 測量模式之信度和效度的評估(護理人員) 66
表4-11 區別效度(醫師) 67
表4-12 區別效度(護理人員) 67
表4-13 研究變項路徑分析結果(醫師) 68
表4-14 研究變項路徑分析結果(護理人員) 68
表4-15 潛在變項直接效用、間接效用與總效用(醫師) 69
表4-16 潛在變項直接效用、間接效用與總效用(護理人員) 70
表5-1 假說驗證結果(醫師) 72
表5-2 假說驗證結果(護理人員) 72
圖目錄
圖2-1 科技接受模式 20
圖2-1 計畫行為理論 22
圖3-1 本研究之研究流程圖 26
圖3-2 本研究之研究架構 27
圖3-3 結構方程模式分析流程 36
圖4-1 假設模型路徑圖(醫師) 61
圖4-2 假設模型路徑圖(護理人員) 62
中文部份
行政院衛生署(2007)。國民健康資訊建設計畫(NHIP)計畫書(96-100)。取得：2009
年11月16日，從http://www.doh.gov.tw/ufile/doc/%E5%9C%8B%E6%B0%91%E5%81%A5%E5%BA%B7%E8%B3%87%E8%A8%8A%E5%BB%BA%E8%A8%AD%E8%A8%88%E7%95%ABNHIP.pdf
行政院衛生署(2007)。電子病歷已成世界潮流。取得：2009年5月1日，從
http://www.doh.gov.tw/CHT2006/DM/DM2_p01.aspx?class_no=25&level_no=1&doc_no=49987&keyword
行政院衛生署(2007)。行政院衛生署「推廣電子病歷執行概況」介紹。取得：2009
年11月25日，從www.dgbas.gov.tw/public/Data/76281526971.pdf
朱家賢(2002)。醫師接受PACS之關鍵因素探討。未出版碩士論文。國立臺灣大
學醫療機構管理研究所，台北。
李婉怡、趙珮如(2004)。醫療產業員工對電子病歷之科技接受模式探討-以中南
部地區為例。醫務管理期刊，5(2)，243-269。
李宜昌、張培廷(2009年5月)。部落格式病患個人健康記錄網站之開發及接受
意願之探討：以照護糖尿病患為例。論文發表於2009年醫療資訊管理暨實
務研討會。台南：嘉南藥理科技大學。
吳秋鳳(2002)。護理人員使用「電子護理記錄系統」之行為研究。未出版碩士論
文。臺灣大學醫療機構管理研究所，台北。
吳逸玲(2006)。影響醫師電子病歷使用行為之研究: 以北部某區域教學醫院為
例。未出版碩士論文。中正大學資訊管理研究所，嘉義。
周怡廷、劉德明、陳致宏、潘美連(2008年，11月)。使用臨床文件架構建置個
人健康記錄交換介接平台。論文發表於2008年台灣國際醫學資訊聯合研討會。台北：陽明大學。
林俊成、林志豪(2009年，5月)。基於個人健康紀錄的醫療知識建議系統之架
構。論文發表於2009年國際資訊管理學術研討會。台北：世新大學。
林杏子(2002)。資訊專業人員隱私保護行為的自我規範機制之研究。未出版博士
論文。中山大學資訊管理研究所，嘉義。
施岳勳、連中岳、朱唯勤、蕭嘉宏、陳長輝(2008年，11月)。個人化電子病歷
之權限控管。論文發表於2008年台灣國際醫學資訊聯合研討會。台北：陽明大學。
施光庭(2005)。醫事人員對線上學習的使用意願之研究-以物理治療師為例。未
出版碩士論文。中正大學資訊管理研究所，嘉義。
洪新原、丁宏祈、黃心怡(2005)。影響醫院導入醫療網站之關鍵因素分析。醫療
資訊雜誌，14(1)，65-76。
紀彣宙、莊坤洋、黃興進(2007)。長期照護解決方案-個人健康紀錄。長期照護
雜誌。11(4)，345-355。
侯穎蕙(2009)。個人健康記錄系統使用意向之影響因素探討。未出版碩士論文。
臺灣大學醫療機構管理研究所，台北。
徐嫦娥(2005)。衛生醫療資訊發展策略地圖之建構－以台灣衛生醫療資訊為例。
未出版碩士論文。臺灣大學資訊管理研究所，台北。
徐南麗、馮容莊、林惠蘭、王明華(1993)。一般外科四類病人護理活動時間與人
力配置。榮總護理，10(2)，191-200。
陳福基、蕭世榮、陳啟元、杜素珍(2005)。影響醫院接受行動護理站因素之研究
-以南部某區域教學醫院為例。資訊管理學報，12，67-89。
張文信(2007) 。資訊科技的運用與病人安全。醫療品質雜誌，1(4)，16-19 。
張玉霞(2004)。從電子病歷探討醫療資訊隱私權之保護。未出版碩士論文。東吳
大學法律研究所，台北。
許惠媚(2004)。實施電子病歷之效益與挑戰。美和技術學院學報，23，171-179。
許文楷、黃秀慧、陳榮方(2006)。企業員工對新導入資訊科技之學習態度研究－
以ERP系統之使用者為例。教育心理學報，38(1)，19-36。
黃妙慧、張克章(2006年，8月)。國內醫療機構對病患隱私權的保護：以美國健
康保險可攜性與責任法案為分析。論文發表於2006 年網際空間資安、犯罪與法律社會學術研究暨實務研討會。台北：台灣師範大學。
黃芳銘(2003)。結構方程式模式理論與應用。台北：五南書局。
楊珺涵(2008)。醫院導入RFID醫護人員之關鍵接受因素探討。未出版碩士論文。
臺灣大學醫療機構管理研究所，台北。
蔡繡容(2000)。創業家之認知與行為意向之研究：計畫行為理論與社會認知理論
之應用。未出版碩士論文。高雄第一科技大學金融營運研究所，高雄。
劉玉山、王佳惠、郭乃文(2007)。醫院藥師提供用藥指導之態度與行為意向。北
市醫學雜誌，4(2)，167-181。
戴辛翎、林秀雯、張瓊洙、林淑愛、柯素惠、張博論(2009)。護理人員自建資訊
系統之歷程研究－以血液透析室為例。榮總護理，(26)3，244-253。
簡鈺玫(2003)。影響醫院接受行動護理站因素之研究--以南部某區域教學醫院為
例。未出版碩士論文。中正大學資訊管理研究所，嘉義。
英文部份
Adesina, A. A., & Ayo, C. K. (2010). An empirical investigation of the level of users' acceptance of e-banking in Nigeria. Journal of Internet Banking and Commerce, 15(1), 1-13.
Aggelidis, V. P., & Chatzoglou, P. D. (2009). Using a modified technology acceptance model in hospitals. Int J Med Inform, 78(2), 115-126.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in
practice: A review and recommended two-step approach. Psychological
Bulletin, 103, 411-423.
Angst, C. M., & Agarwal, R. (2009). Adoption of electronic health records in the
presence of privacy concerns: The elaboration likelihood modeland individual persuasion. MIS Quarterly: Management Information Systems, 33(2), 339-370.
Anonymous. (2008). Defining the Personal Health Information Management Role. Journal of AHIMA, 79(6), 59-63.
American Health Information Management Association.(n.d.)myPHR.Retrieved
Decemember 5, 2009, from
http://www.myphr.com/index.php/start_a_phr/what_is_a_phr/
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation
models.Journal of the Academy of Marketing Science, 16(2), 74-94.
Baker, D. B., & Masys, D. R. (1999). PCASSO: A design for secure communication of personal health information via the internet. International Journal of Medical Informatics, 54(2), 97-104.
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191-215.
Bandura, A. (1982). Self-efficacy mechanism in human agency. American
Psychologist, 37, 122-147.
Bentler, P. M., & Chou, C. P. (1987). Practical issues in structural modeling.
Sociological Methods and Research, 16, 78-117.
Boomsma, A., & Hoogland, J. J. (2001). The robustness of LISREL modeling
revisited. Psychometrika, 51, 313-325.
Brown, M. W. & Cudeck, R. (1993). Alternative ways of assessing model fit. In
K.A.Bollen and J.S. Long (Eds.), Testing strutural equation models (pp.
136-162).CA: Sage.
Burton, L. C., Anderson, G. F., & Kues, I. W. (2004). Using electronic health records to help coordinate care. Milbank Quarterly, 82(3), 457-481.
Carmines, E., & McIver, J. (1981). Analyzing models with unobserved variables:
Analysis of covariance structure. In G. Bohrnstedt and E. Borgatta (Eds.), Social Measurement: Current Issues(pp.65-115). CA: Sage.
Chen, I. J., Yang, K. F., Tang, F. I., Huang, C. H., & Yu, S. (2008). Applying the technology acceptance model to explore public health nurses' intentions towards web-based learning: A cross-sectional questionnaire survey. International Journal of Nursing Studies, 45(6), 869-878.
Clarke, J. L., Meiris, D. C., & Nash, D. B. (2006). Electronic personal health records come of age. Am J Med Qual, 21(Suppl 3), 5-15.
Coffin, R. J., & MacIntyre, P. D. (1999). Motivational influences on computer-related affective states. Computers in Human Behavior, 15(5), 549-569.
Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189.
Compeau, D. R., Higgins,C.A., & Huff, S. (1999). Social cognitive theory and
individual reactions to computing technology: A longitudinal study. MIS
Quarterly, 23(2), 145-158.
Conrad, A., & Munro, D. (2008). Relationships between computer self-efficacy, technology, attitudes and anxiety: Development of the computer technology use scale (CTUS). Journal of Educational Computing Research, 39(1), 51-73.
Cronin, C. (2006). Personal Health Records: An Overview of What Is Available To
The Public.Retrieved May 17, 2010, From http://assets.aarp.org/rgcenter/health/2006_11_phr.pdf
Dalziel, C. (2008). Factors that enhance nurses' use of health information systems to support clinical decision-making. Unpublished M.A., Royal Roads University, Canada.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly: Management Information Systems, 13(3), 319-339.
DeLone, W. H,& McLean, E. R. (1992). Information System Success: The Quest for
the Dependent Variable. Journal of Information Systems Research, 3(1),60-95.
Denton, I. C. (2001). Will patients use electronic personal health records? Responses from a real-life experience. J Healthc Inf Manag, 15(3), 251-259.
Dillon, T. W., Blankenship, R., & Crews Jr, T. (2005). Nursing attitudes and images of electronic patient record systems. CIN - Computers Informatics Nursing, 23(3), 139-145.
Gist, M. E., Schwoerer, C., & Rosen, B. (1989). Effects of alternative training
methods on self-efficacy and performance in computer software training.
Journal of Applied Psychology, 74(6), 884-891.
Goldzweig, C. L., Towfigh, A., Maglione, M., & Shekelle, P. G. (2009). Costs and benefits of health information technology: New trends from the literature. Health Affairs, 28(2), 282-293.
Ha, S., & Stoel, L. (2009). Consumer e-shopping acceptance: Antecedents in a technology acceptance model. Journal of Business Research, 62(5), 565-571.
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data
analysis (5th ed.). London: Prentice Hall.
Hewitt, B. (2010). Exploring how security features affect the use of electronic health records. International Journal of Healthcare Technology and Management, 11(1-2), 31-49.
Hillestad, R., Bigelow, J., Bower, A., Girosi, F., Meili, R., Scoville, R., et al. (2005). Can electronic medical record systems transform health care? Potential health benefits, savings, and costs. Health Affairs, 24(5), 1103-1117.
Hill, T., Smith, N. D., & Mann, M. F. (1987). Role of efficacy expectations in
predicting the decision to use advanced technologies: The case of computers.
Journal of Applied Psychology, 72, 307-313.
Igbaria, M., & Iivari, J. (1995). The effects of self-efficacy on computer
Usage.Omega, 23(6), 587-605.
Jeffs, D., & Harris, M. (1993). The personal health record. Making it work better for general practitioners. Australian family physician, 22(8), 1417-1419, 1421, 1424.
Kaelber, D. C., Jha, A. K., Johnston, D., Middleton, B., & Bates, D. W. (2008). A Research Agenda for Personal Health Records (PHRs). Journal of the American Medical Informatics Association, 15(6), 729-736.
Kahn., J. S., Aulakh., V., & Bosworth., A. (2009). What It Takes: Characteristics Of The Ideal Personal Health Record. Health Affairs, 28(2), 369-376.
Karahanna, E., & Straub, D. W. (1999). The psychological origins of perceived usefulness and ease-of-use. Information and Management, 35(4), 237-250.
Karsten, K., & Roth, R. M. (1998). The relationship of computer experience and
computer self-efficacy to performance in introductory computer literacy
courses.Journal of Research on Computing in Education, 31(1), 14-24.
Lee, M., Delaney, C., & Moorhead, S. (2007). Building a personal health record from a nursing perspective. International Journal of Medical Informatics, 76(SUPPL. 2), 308-316.
Lee, Y., Kozar, K., & T.Larsen, K. R.(2003) .The Technology Acceptance
Model:Past,Present,and Future.Communications of the Association for
Information Systems,12(50),752-780.
Marakas, G.M., Yi, M.Y., & Johnson, R.D. (1998). The Multilevel and Multifaced
Character of Computer Self-Efficacy：Toward Clarification of the Construct and anIntegrative Framework for Research. Information Systems Research, 9(2),126-163.
Markle Foundation(2003).The Personal Health Working Group Final Report.
Retrieved July 27, 2009, From http://www.connectingforhealth.org/resources/final_phwg_report1.pdf
Markle Foundation(2004) .Connecting Americans to their Healthcare: Final Report.
Retrieved July 27, 2009, From
http://www.connectingforhealth.org/resources/wg_eis_final_report_0704.pdf
Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a World-Wide-Web context. Information and Management, 38(4), 217-230.
Morrison, P. D., & Roberts, J. H. (1998). Matching Electronic Distribution Channels to Product Characteristics: The Role of Congruence in Consideration Set Formation. Journal of Business Research, 41(3), 223-229.
Neupert, P., & Mundie, C. (2009). Perspective - Personal health management systems: Applying the full power of software to improve the quality and efficiency of care. Health Affairs, 28(2), 390-392.
Nunnally, J. (1978). Psychometric theory. (2nd ed.). New York: McGraw-Hill.
Park, Y., & Chen, J. V. (2007). Acceptance and adoption of the innovative use of smartphone. Industrial Management and Data Systems, 107(9), 1349-1365.
Popovich, M. L., Aramini, J. J., & Garcia, M. (2008). Immunizations: the first step in a personal health record to empower patients. Studies in Health Technology and Informatics, 137, 286-295.
Raisinghani, M. S., & Young, E. (2008). Personal health records: key adoption issues and implications for management. Int J Electron Healthc, 4(1), 67-77.
Ralston, J. D., Carrell, D., Reid, R., Anderson, M., Moran, M., & Hereford, J. (2007). Patient Web Services Integrated with a Shared Medical Record: Patient Use and Satisfaction. Journal of the American Medical Informatics Association, 14(6), 798-806.
Soroa-Koury, S., & Yang, K. C. C. (2010). Factors affecting consumers' responses to mobile advertising from a social norm theoretical perspective. Telematics and Informatics, 27(1), 103-113.
Tam, S. F. (1996). Self-efficacy as a predictor of computer skills learning
outcomes of individuals with physical disabilities. The Journal of
Psychology, 130(1), 51-58.
Tang, P. C., Ash, J. S., Bates, D. W., Overhage, J. M., & Sands, D. Z. (2006). Personal health records: Definitions, benefits, and strategies for overcoming barriers to adoption. Journal of the American Medical Informatics Association, 13(2), 121-126.
Tassabehji, R., & Kamala, M. A. (2009). Improving e-banking security with biometrics: Modelling user attitudes and acceptance. Paper presented at the 3rd International Conference on New Technologies, Mobility and Security, NTMS 2009, Cairo.
Taylor, S., & Todd, P. (1995). Assessing IT usage: The role of prior experience. MIS Quarterly: Management Information Systems, 19(4), 561-568.
Tung, F. C., Chang, S. C., & Chou, C. M. (2008). An extension of trust and TAM model with IDT in the adoption of the electronic logistics information system in HIS in the medical industry. Int J Med Inform, 77(5), 324-335.
Van Deursen, T., Koster, P., & Petkovi, M. (2008). Reliable personal health records. Paper presented at the Studies in Health Technology and Informatics, Lansdale ,PA.
Vijayasarathy, L. R. (2004). Predicting consumer intentions to use on-line shopping: The case for an augmented technology acceptance model. Information and Management, 41(6), 747-762.
Whetstone, M., & Randeree, E. (2008). Personal health records: Addressing consumer needs for access. International Journal of Healthcare Technology and Management, 9(3), 258-274.
Wilkins, M. A. (2009). Factors influencing acceptance of electronic health records in hospitals. Perspect Health Inf Manag, 6, 1f.
Wu, Shen, Lin, Greenes, & Bates. (2008). Testing the technology acceptance model for evaluating healthcare professionals' intention to use an adverse event reporting system. International Journal for Quality in Health Care, 20(2), 123.
Wu, Z. (2009). Chinese customer's attitude and adopt intention on mobile commerce. Paper presented at the Proceedings of the 2009 6th International Conference on Service Systems and Service Management, ICSSSM '09, Xiamen.
Yang, K., & Jolly, L. D. (2009). The effects of consumer perceived value and subjective norm on mobile data service adoption between American and Korean consumers. Journal of Retailing and Consumer Services, 16(6), 502-508.
Yi, M. Y., Jackson, J. D., Park, J. S., & Probst, J. C. (2006). Understanding information technology acceptance by individual professionals: Toward an integrative view. Information and Management, 43(3), 350-363.
Zhang, A., Yue, X., & Zhang, Y. (2009). Adoption of mobile video: An empirical study in Beijing. Paper presented at the Proceedings - International Conference on Management and Service Science, MASS 2009, Wuhan. |
| 顯示於類別: | [醫務管理學系暨研究所] 博碩士論文
|
在TMUIR中所有的資料項目都受到原著作權保護.
|
