本研究的目的在了解中高齡者網路即時通訊軟體採用之意圖與行為，並探討背景變項在其採用意圖與行為之差異情形，續綜合科技接受模式、主觀規範、知覺樂趣與專注，探究模式對於解釋使用意圖與行為的合適性。本研究採自陳式問卷調查法，以臺北市與新北市社區大學與高齡者學習機構中四十歲以上成人為樣本，有效樣本共197份，資料分別以描述性統計、獨立樣本t檢定、單因子變異數分析、皮爾森積差相關與路徑分析來進行統計分析。結果發現，中高齡者對網路即時通訊軟體具有中高程度的評價，在使用過程中頗為專注且享有頗多的樂趣，使用意圖亦為中高程度。超過六成者有實際使用行為，頻率較不密集，平均使用時間多不超過一小時。不同教育程度在軟體的操作易用程度上有著差異情形，經濟狀況較佳者在科技接受程度與使用行為上有較佳的表現。模式對中高齡者網路即時通訊軟體之使用意圖有76.6%的解釋量，對使用頻率僅有10.6%的解釋量，對使用時間之解釋量則僅有.9.1%。本研究建議可廣設公共電腦設備以及不同程度之電腦課程，提供中高齡者更多的接觸管道與學習機會；對於成人教育者則須提供培訓課程，使教師在教學現場能夠因應中高齡者個別差異與學習狀況的變化，增刪課程內容或是提供適當之教學引導，促進中高齡者良好的學習與使用經驗，對電腦與網際網路使用有更佳的印象，從而能將之運用於生活中。

This study aimed to understand the instant messenger (IM) behavioral intention and usage of older adults. Subjective norm, perceived enjoyment and concentration were added to the technology acceptance model in order to understand the explanation power to behavioral intention and usage. Subjects were adult aged over forty who enrolled in computer classes of community colleges and other adult educational organizations in Taipei City and New Taipei City. A total of 197 questionnaires were completed and analyzed. According to the results, older adults contained positive attitude and behavioral intention towards IM. Over sixty percentages of subjects had actual usage. However, the frequency was not intensive and the time spent on IM was mostly under an hour. With perceived ease of use, perceived usefulness, perceived enjoyment and concentration, the proposed model could explain 76.6% of the variance in behavioral intention. Nevertheless, the model could only explain 10.6% of the variance in using frequency. Significant differences were found in perceived ease of use in terms of education level and economic status. Moreover, older adults with better economic status used IM more often and spent more time on it. Based on these findings, setting up courses at different levels and public computer and internet apparatus were recommended to facilitate older adults’ access to computers and to learning. Providing training courses to lecturers was also suggested in order to advance teaching skills of lecturers.

壹、 中文部分
方士源（2010）。社區大學資訊科技課程學員學習動機、學習阻礙與學習滿意度之研究。佛光大學社會教育學研究所碩士論文，宜蘭縣。
江盈慧（2010）。從學習風格探析高齡者資訊通訊科技的使用。國立中山大學教育研究所碩士論文，高雄市。
行政院（2009）。98年個人家戶數位落差調查報告。取自http://www.rdec.gov.tw/public/Attachment/91215951771.pdf，2010年8月20日。
周玉慧、莊義利（2000）。晚年生活壓力、社會支持與老人身心健康之變遷：長期資料分析。人文及社會科學集刊，12（2），頁281-317。
林佳慧（2007）。高齡者電腦經驗與其生活滿意度及電腦態度關係之研究。國立暨南大學成人與繼續教育研究所碩士論文，南投縣。
林迪意、莊明諺（2004）。年齡、工作記憶與電腦態度在電子郵件技能學習之預測效應。應用心理研究，22，頁105-120。
林勤敏（2001）。資訊科技與高齡學習之探討。資訊素養與終身學習社會研討會論文集。國立台灣師範大學社會教育學系，台中市。
邱顯貴（2008）。影響使用即時通訊軟體行為意圖之研究。資訊、科技與社會學報，8（1），頁1-19。
洪新原、康贊清、柯清德（2004）。即時通訊與電子郵件溝通成效之實驗研究。2004科技整合管理國際研討會論文集。臺北市。
翁嘉苓（2010）。高齡者參與學習動機和老化態度對參與行為影響之研究。國立臺北大學金融與合作經營學系碩士論文，臺北市。
統計處（2010a）。內政統計通報─98年底人口結構分析。取自 http://sowf.moi.gov.tw/stat/week/week9904.doc，2010年10月25日。
統計處（2010b）。內政部統計月報─現住人口按五歲年齡組分。取自http://sowf.moi.gov.tw/stat/month/m1-06.xls，2010年12月15日。
統計處（2005）。民國94年老人狀況調查結果摘要分析。取自 http://sowf.moi.gov.tw/stat/Survey/94old.doc，2010年10月25日。
莊淑富（2003）。高齡者參與電腦學習動機之研究。國立中正大學成人與繼續教育研究所碩士論文，嘉義縣。
莊鎮嘉（2007）。即時通訊軟體採用認知因素與使用者滿意度之關係研究。雲林科技大學資訊管理系碩士論文，雲林縣。
陳育慧（2002）。社會支持對中老年失能者憂鬱狀況之直接與間接影響。台北醫學院公共衛生學研究所碩士論文，臺北市。
陳淑美、林佩萱（2010）。親子世代的財務支援、照顧需要對老人居住安排與生活滿意度影響之研究。住宅學報，19（1），頁29-58。
創世紀市場研究顧問（2006）。IM普及率破九成 附加功能玩行銷。取自http://www.insightxplorer.com/news/news_03_24_06.html，2010年11月20日。
曾秀卿（1998）。高齡者非理性信念、社會支持與情緒困擾之關係研究。國立高雄師範大學成人教育研究所碩士論文，高雄市。
曾淑芬（2006）。高齡者電腦網路使用行為與生活滿意度關係之研究。國立中正大學中高齡者教育所碩士論文，嘉義縣。
黃建中（2001）。銀髮族其家庭社會角色對創新科技使用決策之影響。國立成功大學企業管理學系碩士論文，台南市。
黃誌坤、王明鳳（2009）。高齡者上網環境友善情形之調查研究。社區發展季刊，頁485-504。
葉美春、阮明淑（2007）。使用者採用知識管理系統之影響因素研究─理論模型的比較取向。圖書資訊學刊，5（1/2），頁69-90。
熊曉芳（1999）。社區獨居老人健康狀況、社會支持及相關因素探討。國立臺灣大學護理學研究所碩士論文，臺北市。
劉明珠（2010）。中高齡者使用網際網路與人際互動之研究。元智大學社會暨政策科學學系碩士論，桃園縣。
鄭淑玲（2009）。運用科技接受模式探討銀髮族對於數位相機接受度之研究。南開科技大學福祉科技與服務管理所碩士論文，南投縣。
盧淑敏（2003）。探討社會支持對獨居老人健康狀況、壓力感受及心理社會健康功能之影響。國立台北護理學院護理研究所碩士論文，臺北市。
薛承泰（2008）。臺灣家庭變遷與老人居住型態：現況與未來。社區發展季刊，121，頁47-56。
魏碧梅（2004）。台灣網際網路使用者對即時通訊之認知與實際使用狀況。國立政治大學資訊管理學系碩士論文，臺北市。
蘇伯方（2004）。即時通訊軟體採用模式之研究。國立中山大學傳播管理研究所碩士論文，高雄市。
貳、 英文部分
Adams, N., Stubbs, D., & Woods, V. (2005). Psychological barriers to Internet usage among older adults in the UK. Medical Informatics & the Internet in Medicine, 30(1), 3-17.
Arning, K., & Ziefle, M. (2007). Understanding age differences in PDA acceptance and performance. Computers in Human Behavior, 23(6), 2904-2927.
Boulton-Lewis, G. M., Buys, L., Lovie-Kitchin, J., Barnett, K., & David, L. N. (2007). Ageing, Learning, and Computer Technology in Australia. Educational Gerontology, 33(3), 253-270.
Chung, H., & Nam, C. S. (2007). An analysis of the variables predicting instant messenger use. New Media & Society, 9(2), 212-234.
Connidis, I. A. (2010). Family ties & Aging (2ed ed.). Los Angeles: Pine Forge Press.
Csikszentmihalyi, M. (1990). Flow: the psychology of opitmal experience. New York: Harper & Row.
Davis, F. D. (1993). User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. International Journal of Man-Machine Studies, 38(3), 475-487.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
Davis, F. D. (1986). A Technology Acceptance Model for Empirically Testing New End-User Information Systems: Theory and Results. Massachusetts Institute of Technology, Massachusetts.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and Intrinsic Motivation to Usee Computers in the Workplace. Journal of Applied Social Psychology, 22(14), 1111-1132.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35(8), 982-1003.
Davis, F. D., & Venkatesh, V. (2004). Toward preprototype user acceptance testing of new information systems: implications for software project management. Engineering Management, IEEE Transactions on, 51(1), 31-46.
Dong, J. Q. (2009). User Acceptance of Information Technology Innovations in the Chinese Cultural Context. Asian Journal of Technology Innovation, 17(2), 129-149.
Dong, J. Q., & Zhang, X. (2011). Gender differences in adoption of inforamtion systems: New findings from China. Computers in Human Behavior, 27, 384-390.
Eisma, R., Dickinson, A., Goodman, J., Syme, A., Tiwari, L., & Newell, A. F. (2004). Early user involvement in the development of information technology-related products for older people. Universal Access in the Information Society, 3(2), 131-140.
Erikson, E. H. (1968). Identity :Youth and Crisis. New York: Norton.
Fallows, D. (2005). How Women and Men Use the Internet. Washington, D.C.: Pew Internet & American Life Project.
Fishbein, M., & Ajzen, I. (1975). Belief, attitue, intention and behavior: an introduction to theory and research. MA: Addison-Wesley.
Fokkema, T., Bekke, S. t., & Dykstra, P. A. (2008). Solidarity between parents and their adult children in europe. Amsterdam: Netherlands Interdisciplinary Demographic Institute.
Fox, S. (2004). Older Americans and the Internet. Washington, D.C.: Pew Internet & American Life Project.
Gatto, S. L., & Tak, S. H. (2008). Computer, Internet, and E-mail Use Among Older Adults: Benefits and Barriers. Educational Gerontology, 34(9), 800-811.
Gefen, D., & Straub, D. W. (1997). Gender differences in the perception and use of E-mail: an extension to the technology acceptance model. MIS Quarterly, 21, 389-400.
Hank, K. (2007). Proximity and Contacts Between Older Parents and Their Children: A European Comparison. Journal of Marriage and Family, 69(1), 157-173.
Karavidas, M., Lim, N. K., & Katsikas, S. L. (2005). The effects of computers on older adult users. Computers in Human Behavior, 21(5), 697-711.
Kirk, R. E. (1995). Experimental Design: Procedures for the Behavioral Sciences (3rd ed.). Califonia: Brooks/Cole Publishing Company.
Lee, M. C. (2010). Explaingin and predicting user’s continuance intention toward e-learning: A extension of the expectation-conformation model. Computers & Education, 54, 506-516.
Levinson, D. J. (1978). The Seasons of a man's life. New York: Knopf.
Lu, Y., Zhou, T., & Wang, B. (2009). Exploring Chinese users' acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Computers in Human Behavior, 25(1), 29-39.
Mathieson, K. (1991). Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior. Information Systems Research, 2(3), 173-191.
Melenhorst, A.-S., Rogers, W. A., & Caylor, E. C. (2001). The Use of Communication Technology by Older Adults: Exploring the Benefits from the User's Perspective. Paper presented at the the Human Factors and Ergonomics Society 45th Annual Meeting, Minneapolis, USA.
Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a World-Wide-Web context. Information & Management, 38, 217-230.
Morrell, R. W., Mayhorn, C. B., & Bennett, J. (2000). A survey of World Wide Web use in middle-aged and older adults. Human Factors, 42(2), 175-182.
Morris, A., Goodman, J., & Brading, H. (2007). Internet use and non-use: views of older users. Universal Access in the Information Society, 6(1), 43-57.
Nayak, L., Priest, L., & White, A. (2010). An application of the technology acceptance model to the level of Internet usage by older adults. Universal Access in the Information Society, 9(4), 367-374.
Pan, S., & Jordan-Marsh, M. (2010). Internet use intention and adoption among Chinese older adults: From the expanded technology acceptance model perspective. Computers in Human Behavior, 26(5), 1111-1119.
Pew Internet & American Life Project. (2001). Wired Seniors: Four million Americans aged 65 and over are online, sending email to family members and surfing for important information. Retrieved Dec 3rd, 2010, from http://www.pewinternet.org/Press-Releases/2001/Wired-Seniors-Four-million-Americans-aged-65-and-over-are-online-sending-email-to-family-m.aspx.
Ryu, M.-H., Kim, S., & Lee, E. (2009). Understanding the factors affecting online elderly user's participation in video UCC services. Computers in Human Behavior, 25(3), 619-632.
Selwyn, N. (2004). The information aged: A qualitative study of older adults' use of information and communications technology. Journal of Aging Studies, 18(4), 369-384.
Sheehy, G. (1995). New Passages: Mapping your life across time. New York: Random House.
Shiu, E., & Lenhart, A. (2004). How Americans use instant essaging. Retrieved Nov. 20th, 2010, from http://www.pewtrusts.org/uploadedFiles/wwwpewtrustsorg/Reports/Society_and_the_Internet/pew_internet_instant_message_090104.pdf.
Slegers, K., van Boxtel, M. P., & Jolles, J. (2007). The Effects of Computer Training and Internet Usage on the Use of Everyday Technology by Older Adults: A Randomized Controlled Study. Education Gerontology, 33(2), 91-110.
Stark-Wroblewski, K., Edelbaum, J. K., & Ryan, J. J. (2007). Senior Citizens Who Use E-mail. Educational Gerontology, 33(4), 293-307.
Taylor, S., & Todd, P. A. (1995). Understanding Information Technology Usage: A Test of Competing Models. Information Systems Research, 6(2), 144-176.
Thayer, S. E., & Ray, S. (2006). Online Communication Preferences across Age, Gender, and Duration of Internet Use. CyberPsychology & Behavior, 9(4), 432-440.
The Wireless Village initiative. (2002). The mobile IMPS initiative white paper. Retrieved Nov. 20th, 2010, from http://www.openmobilealliance.org/tech/affiliates/wv/wv_white_paper.pdf
Tomassini, C., Grundy, E., Kalogirou, S., Gaymu, J., Martikainen, P., Binet, A., et al. (2005). North, South and West: differnetials in parent-child contacts among the older populations of Finland, France and Italy. Paper presented at the International Union for the Scientific Study of Population XXV International Population Conference Tours. Retrieved Oct. 10th, 2010,from http://iussp2005.princeton.edu/download.aspx?submissionId=50359.
Trevino, L. K., & Webster, J. (1992). Flow in computer-mediated communication: Electronic mail and voice mail evaluation and impacts. Communication Research, 19(5), 539-573.
Turner, P., Turner, S., & Van De Walle, G. (2007). How older people account for their experiences with interactive technology. Behaviour & Information Technology, 26(4), 287-296.
Venkatesh, V. (2000). Determinants of perceived ease of use: integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342-365.
Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273-314.
Venkatesh, V., & Brown, S. A. (2001). A longitudinal investigation of personal computers in homes: adoption determinants and emerging challenges. MIS Quarterly, 25(1), 71-102.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science, 46(2), 186-204.
Venkatesh, V., & Morris, M. G. (2000). Why don't men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115-139.
Venkatesh, V., Morris, M. G., & Davis, G. B. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425-478.
Wagner, N., Hassanein, K., & Head, M. (2010). Computer use by older adults: A multi-disciplinary review. Computers in Human Behavior, 26(5), 870-882.
White, H., Mcconnell, E., Clipp, E., Branch, L. G., Sloane, R., Pieper, C., & Box, T. L. (2002). A randomized controlled trial of the psychosocial impact of providing internet training and access to older adults. Aging & Mental Health, 6(3), 213-221.
White, J., & Weatherall, A. (2000). A ground theory analysis of older adults and information technology. Educational Gerontology, 26(4), 371-386.
Zaman, M., rajan, M. A., & Dai, Q. (2010). Experiencing flow with instant messaging and its facilitating role on creative behaviors. Computers in Human Behavior, 26, 1009-1018.
Zhou, T., & Lu, Y. (2011). Examining mobile instant messaging user loyalty from the perspectives of network externalities and flow experience. Computers in Human Behavior, 27, 883-889.