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研究生:謝宜倫
研究生(外文):Yi-Lun Sie
論文名稱:以訊息說服性觀點探討資訊管道影響母乳哺育意圖之研究
論文名稱(外文):The Effects of Persuasive Messages from Information Sources on Breastfeeding Intention
指導教授:楊文惠楊文惠引用關係
指導教授(外文):Wen-Hui Yang
學位類別:碩士
校院名稱:中國醫藥大學
系所名稱:醫務管理學系碩士班
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:2015
畢業學年度:103
語文別:中文
論文頁數:80
中文關鍵詞:母乳哺育訊息說服資訊管道結構方程模式多群組分析
外文關鍵詞:BreastfeedingPersuasive MessagesInformation SourcesStructural Equation ModelMultiple Group Analysis
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  • 收藏至我的研究室書目清單書目收藏:1
許多研究說明母乳哺育的好處,此觀念在我國政策下已逐漸重新讓民眾接受,但哺育率仍有待提升,本研究目的為了解母親在接收母乳哺育衛教資訊時,對於不同資訊管道之來源可信度、論點品質、認知反應、情感反應以及母乳哺育意圖的關係,並比較不同母乳哺育衛教資訊管道對於母乳哺育意圖之說服效果。
本研究採初級資料進行分析,為橫斷性的研究,以自編結構式問卷至中部某醫學中心之小兒科與健兒門診,針對擁有兩歲以下嬰幼兒的母親進行問卷發放,發放372份,回收355份有效問卷,使用結構方程模式與多群組分析進行統計分析,以AMOS18.0評估測量模式,進行驗證修改後,以檢定整體理論模式與配適度,提出本研究之結構方程模式。
研究結果顯示,母乳哺育衛教資訊管道之來源可信度對於情感反應與認知反應為正相關且顯著,而母乳哺育衛教資訊管道之論點品質對於認知反應為正相關且顯著,情感反應與認知反應對於母乳哺育意圖呈現正相關且顯著;利用來源可信度誘發情感反應產生母乳哺育意圖為最佳說服路徑,其中以親朋好友管道之說服效果最好,以整體來看為醫護專業人員管道之訊息說服效果最佳。
建議宣導母乳哺育,應由醫護專業人員作為主要訊息傳播者,宣導內容以圖片、畫面呈現方式為主,使母親誘發情感反應進而產生母乳哺育意圖;建議政府應定期為嬰幼兒母親舉辦經驗分享會,使嬰幼兒母親產生共鳴,進而達到推行母乳哺育之效果,提升母乳哺育率。


Purposes: Various studies show the benefits of breastfeeding. Under the government policy in Taiwan, breastfeeding is being gradually accepted among mothers, but the breastfeeding rate still needs to be improved. This study aimed to find the relationship between source credibility, argument quality, cognitive response, affective response, and breastfeeding intention, while mothers seek information about breastfeeding from many different information sources. We also compare persuading effects of different information sources on breastfeeding intention.
Methods: This study analyzed the primary data, which collected from the participants. Mother who have infant would measure by a self-edited questionnaire at pediatrics outpatient and athlete’s outpatient in a medical center. 355 valid questionnaires were collected. Structural Equation Modeling and Multiple Group Analysis are used AMOS 18.0 statistical software is further utilized for verification and revision to test the full theoretical model and the sample fitness, so as to propose the Structural Equation Modeling corresponding to this study.
Results: In the result of the full model, the analysis found, source credibility could positively affect cognitive response and affective response significantly; argument quality could positively affect cognitive response significantly. Affective response and cognitive response could positively affect breastfeeding intention significantly. The best persuasive messages way to increase intentions to breastfeed is from source credibility through affective response to breastfeeding intention. Among this impacting path of different information sources, relatives and friends of mothers have the best persuasive effect on breastfeeding intention. However, among multi-impacting paths of different information sources, the information sources through the medical providers have the best persuasive effect to increase mother’s intention to breastfeed.
Conclusions: This study suggests that medical providers should be the major promoters of breastfeeding. Using pictures and media screen to present the information that make mothers to be affective response to breastfeeding. The health care organizations should hold some health education regarding breastfeeding for mothers to share their experience on breastfeeding to induce the intention of breastfeeding, and to promote breastfeeding rate ultimately.


摘要 i
Abstract ii
致謝 iv
目錄 v
表目錄 vii
圖目錄 viii
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 3
第二章 文獻探討 4
第一節 母乳哺育的重要性 4
第二節 衛教資訊管道 5
第三節 訊息說服性與反應機制 7
第四節 研究假設推導 10
第五節 文獻小結 13
第三章 研究設計與方法 14
第一節 研究架構 15
第二節 研究對象與資料來源 16
第三節 研究工具 17
第四節 研究變項定義 19
第五節 分析方法 25
第四章 結果 27
第一節 描述性統計 27
第二節 重複測量單因子變異數分析 36
第三節 結構方程模式 38
第四節 多群組分析 47
第五章 討論 50
第一節 資訊管道之說服性、反應機制以及母乳哺育意圖的關係 50
第二節 不同衛教資訊管道對於母乳哺育意圖之說服效果 54
第三節 推敲可能性模式之學術討論 56
第六章 結論與建議 58
第一節 結論 58
第二節 建議 60
第三節 研究限制 63
第四節 未來研究發展與建議 63
參考文獻 64
附錄一 不同資訊管道影響母乳哺育意圖之問卷 73
附件二 匿名問卷研究說明書 78
附錄三 研究倫理同意書 80


A, Reynolds. (2001). Breastfeeding and brain development. Pediatric Clinics of North America, 49, 159-173.
Ahn, T., Ryu, S., & Han, I. (2007). The impact of Web quality and playfulness on user acceptance of online retailing. Information and Management, 44, 263–275.
Arora, R., Stoner, C., & Arora, A. (2003). Using framing and credibility to incorporate exercise and fitness in individuals’ lifestyle. Journal of Consumer Marketing, 23, 199–207.
B. STERNTHAL, L. W. PHILLIPS & R. DHOLAKIA. (1978). The Persuasive Effect of Scarce Credibility: A Situational Analysis. The Trustees of Columbia University, 285-314.
Ball, T.M. & Bennett, D.M. (2001). The economic impact of breastfeeding. Pediatric Clinics of North America, 48(1), 253-262.
Bartington, S., Griffiths, L. J., Tate, A. R., & Dezateux, C. (2006). Are breastfeeding rates higher among mothers delivering in Baby Friendly accredited maternity units in the UK?. International Journal of Epidemiology, 35(5), 1178-1186.
Batra, R., & Stephens, D. (1994). Attitudeinal effects of ad-evoked moods and emotions: The moderating role of motivation. Psychology and Marketing, 11, 199–215.
Bhattacherjee, A., & Sanford, C. C. (2006). Influence processes for information technology acceptance. MIS Quarterly, 30, 805–825.
Broadfoot, M., Britten, J., Tappin, D. M., & MacKenzie, J. M. (2005). The baby friendly hospital initiative and breast feeding rates in Scotland. Archives of Disease in Childhood-Fetal and Neonatal Edition, 90(2), F114-F116.
BT, Johnson. (1994). Effects of outcome-relevant involvement and prior information on persuasion. J. Exp. Soc. Psychol, 30, 556–579.
Chang, J. H., & Chan, W. T. (2002). Analysis of factors associated with initiation and duration of breast-feeding: a study in Taitung Taiwan. Acta Pediatrica Taiwan, 44(1), 29-34.
Christakis, N. A., & Fowler, J. H. (2007). The spread of obesity in a large social network over 32 years. New England Journal of Medicine, 357(4), 370-379.
Christakis, N. A., & Fowler, J. H. (2008). The collective dynamics of smoking in a large social network. New England Journal of Medicine, 358(21), 2249-2258.
Christopher M., Christiane, Z., Carole, F., & Kathie, B. . (2005). An evaluation of a social marketing campaign to reduce the number of London women who have never been screened for cervical cancer. Journal of Medical Screening, 12(4), 204-205.
Crites, S. L., Fabrigar, L. R., & Petty, R. E. (1994). Measuring the affective and cognitive properties of attitudes: Conceptual and methodological issues. Personality and Social Psychology Bulletin, 20(6), 619-634.
Colon-Ramos, U., Atienza, A. A., Weber, D., Taylor, M., Uy, C., & Yaroch, A. (2009). Practicing what they preach: health behaviors of those who provide health advice to extensive social networks. Journal of Health Communication, 14(2), 119-130.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35, 982–1003.
Dutta-Bergman, M.J. (2004). Primary sources of health information: Comparisons in the domain of health attitudes, health cognitions, and health behaviors. Health Communication, 16(3), 273-288.
Edwards, K. (1990). The interplay of at ect and cognition in attitude formation and change. Journal of Personality and Social Psychology, 59, 202-216.
Eroglu, S. A., Machleit, K. A., and Davis, L. M. (2001). Atmospheric qualities of online retailing: A conceptual model and implications. Journal of Business Research, 54(2), 177-184.
Flynn, B. S., Worden, J. K., Bunn, J. Y., Connolly, S. W., & Dorwaldt, A. L. . (2011). Evaluation of smoking prevention television messages based on the elaboration likelihood model. Health Education Research, 26(6), 976-987.
Folkes, V. S. (1988). Recent attribution research in consumer behavior: A review and new directions. Journal of Consumer Research, 548-565.
Forgas, J. P. (2007). When sad is better than happy: Negative affect can improve the quality and effectiveness of persuasive messages and social influence strategies. Journal of Experimental Social Psychology, 43, 513–528.
Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual
performance. MIS Quarterly, 19, 213–236.
H., Sandvik. (1999). Health information and interaction on the internet: a survey of female urinary incontinence. British Medical Journal, 319(7201), 29-32.
Henningsen, D. D., & Henningsen, M. L. M. (2003). Examining social influence in information-sharing contexts. Small Group Research, 34, 391–412.
Hoyle, R. H., & Panter, A. T. (1995). Structural equation modeling: Concepts, issues, and applications. Sage Publications.
Jackson, R., Baird, W., Davis-Reynolds, L., Smith, C., Blackburn, S., & Allsebrook, J. (2008). Qualitative analysis of parents’ information needs and psychosocial experiences when supporting children with health care needs. Health Information & Libraries Journal, 25(1), 31-37.
Jones, L. W., Sinclair, R. C., & Courneya, K. S. (2003). The effects of source credibility and message framing on exercise intentions, behaviors, and attitudes: An integration of the elaboration likelihood model and prospect theory. Journal of Applied Social Psychology, 33, 179–196.
Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13, 205–223.
Labbok, M.H. (2001). Effects of breastfeeding on the mother. Pediatric Clinics of North America, 48(1), 143-158.
Lavidge, Robert J. & Gary A. Steiner. (1961). A Model for Predictive Measurements of Advertising Effectiveness. Journal of Marketing, 25(6), 59-62.
Lazarus, R. S. (1991). Cognition and motivation in emotion. American Psychologist, 46, 352–367.
Lee, Park, & Han (2008), “The Effect of Negative Online Consumer Reviews on Product Attitude: An Information Processing View,” Electronic Commerce Research and Applications, 7 (2), 341-352.
Lee, M. K. O., Cheung, C. M. K., & Chen, Z. (2005a). Acceptance of Internet-based learning medium: The role of extrinsic and intrinsic motivation. Information and Management, 42, 1095–1104.
Lee, M. K. O., Cheung, C. M. K., & Chen, Z. (2005b). Acceptance of Internet-based learning medium: The role of extrinsic and intrinsic motivation. Information and Management Science, 42, 1095–1104.
Leung, T., Tam, W., Hung, E., Fok, T., & Wong, G. (2003). Sociodemographic and atopic factors affecting breastfeeding intention in Chinese mothers. Journal of Pediatrics, 39, 460-464.
Li, C. Y. . (2013). Persuasive messages on information system acceptance: A theoretical extension of elaboration likelihood model and social influence theory. Computers in Human Behavior, 29(1), 264-275.
Little, T. D. (1997). Mean and covariance structures(MACS) analysis of cross-cultural data : Practice and theoretical issues. Multivariate Behavioral Research, 32, 53-76.
Li, H., Sarathy, R., & Xu, H. (2011). The role of affect and cognition on online consumers'' decision to disclose personal information to unfamiliar online vendors. Decision Support Systems, 51(3), 434-445.
Li, W., Gao, L., & Ke, Y. (2014). SOCIAL COMMERCE: THE CRITICAL ROLE OF ARGUMENT STRENGTH AND SOURCE DYNAMISM OF EWOM.
Luo, P., Zheng, X., Chen, X., Li, Y., Wang, J., Deng, L., & Zheng, X. (2014). Sex differences in affective response to different intensity of emotionally negative stimuli: An event-related potentials study. Neuroscience letters, 578, 85-89.
MacCallum, R., Browne, M. W.,& Sugawara, H. M. (1996). Power analysis
and determination of sample size for covariance structure modeling. Psychological method, 1(2), 130-149.
MacCracken, G. (1989). Who is the celebrity endorser?Cultural foundations of the endorsement process. Journal of Consumer Research, 16, 310–321.
Mak, B., Schmitt, B. H., & Lyytinen, K. (1997). User participation in knowledge update of expert systems. Information and Management, 32, 55–63.
Martin, R. M., Gunnell, D., & Smith, G. D. (2005). Breastfeeding in infancy and blood pressure in later life: Systematic review and meta-analysis. American Journal of Epidemiology, 161(1), 15-26.
Megehee, C. M. (2009). Advertising time expansion, compression, and cognitive processing influences on consumer acceptance of message and brand. Journal of Business Research, 62(4), 420-431.
Moon, J., & Kim, Y. (2001). Extending the TAM for a world-wide-web context. Information and Management, 38, 217–230.
Owen-Smith, V., Howe, A., & Richardson, J. (2003). Television soap consumption reduction? Journal of Business Research, 62(2), 260-268.
Parboteeah, D. V., Valacich, J. S., and Wells, J. D. (2009). The influence of website characteristics on a consumer''s urge to buy impulsively. Information Systems Research, 20(1), 60-78.
Pecchioni, L. L., & Sparks, L. (2007). Health information sources of individuals with cancer and their family members. Health communication, 21(2), 143-151.
Peck, J., & Wiggins, J. (2006). It just feels good: Customers’ affective response to touch and its influence on persuasion. Journal of Marketing, 70, 56–69.
Pediatics, American Academic of. (2005). Breastfeeding and the use of human milk. Pediatrics, 115(2), 496-506.
Petty, R. E. & Cacioppo, J. T. (1984a). Source Factors and the Elaboration Likelihood Model of Persuasion. Advances in Consumer Research, 11(1), 668-672.
Petty, R. E. & Cacioppo, J. T. (1984b). The Effects of Involvement on Responses to Argument Quantity and Quality: Central and Peripheral Routes of Persuasion. Journal of Personality and Social Psychology, 46(1), 69-81.
Petty, R. E., & Cacioppo, J. T. (1981). Attitudes and persuasion: Classic and contemporary approaches. Dubuque, Dubuque, IA: William C. Brown.
Petty, R. E., & Cacioppo, J. T. (1986a). The elaboration likelihood model of persuasion. In L. Berkovitz. Advances in experimental social psychology 19, 123–205.
Petty, R. E., & Cacioppo, J. T. (1986b). The elaboration likelihood model of persuasion.In L. Berkovitz (Ed.). Advances in experimental social psychology, 19, 123–205.
Petty, R. E., & Wegener, D. T. (1998). Attitude change: Multiple roles for persuasion variables. Handbook of Social Psychology, 1, 323–390.
Petty, R. E., Cacioppo, J. T., and David, S. (1983). Central and Peripheral Routes to Advertising Effectiveness: The Moderating Role of Involvement. Journal of Consumer Research, 1(10), 135-146.
Priester JR, Petty RE. (2003). The influence of spokesperson trustworthiness on message elaboration, attitude strength, and advertising effectiveness. Journal of Consumer Psychology, 13, 408–421.
PW, H. (1990). Protective effect of breast feeding against infection., 300(6716), 6-11.
Radey, M., & Randolph, K.A. (2009). Parenting sources: How do parents differ in their efforts to learn about parenting? Family Relations, 58(5), 536-548.
Redmond, N., Baer, H. J., Clark, C. R., Lipsitz, S., & Hicks, L. S. (2010). Sources of health information related to preventive health behaviors in a national study. American journal of preventive medicine, 38(6), 620-627.
Rogers, E. M. (1995). Diffusion of innovations.New York: The Free Press.
Rosen, C. S. (2000). Integrating stage and continuum models to explain processing of exercise messages and exercise initiation among sedentary college students. Health Psychology, 19, 172–180.
Rucker, D. D., & Petty, R. E. (2006). Increasing effectiveness of communications to consumers: Recommendations based on the elaboration likelihood and attitude certainty perspectives. Journal of Public Policy and Marketing, 25, 39–52.
Saadeh, R. (1993). Innocenti Declaration, Breast-feeding. The technical basis and recommendations for action.World Health Organization: Geneva. 113-115.
Sanchez, R. A., & Hueros, A. D. (2010). Motivational factors that influence the
acceptance of Moodle using TAM. Computers in Human Behavior, 26(6), 1632–1640.
Sangl JA, & Wolf LF. (1996). Role of consumer information in today''s health care system. Health Care Financ, 18(1), 1-8.
Schiffman, L. G. & Kanuk L. L. (2000). Consumer Behavior, 7th, Upper Saddle River, NJ: Prentice-Hall.
Schreiber, J. B. (2008). Core reporting practices in structural equation modeling. Research in Social and Administrative Pharmacy, 4(2), 83-97.
Scott WG, Scott HM, & Auld TS. (2005). Consumer access to health information on the internet: health policy implications. Aust New Zealand Health Policy, 2(13).
Singh, S., Dalal, N., 1999. Web Homepages as Advertisements. Communications of the ACM 42(8), 91-98.
Simmons, M. R. (1998). A Study of High School Students'' Attitudes toward the Environment and Completion of an Environmental Science Course. Canada: New-Brunswick: Reports Research (143).
Stephenson, M. T., Benoit, W. L., & Tschida, D. A. (2001). Testing the mediating role of cognitive responses in the elaboration likelihood model. Communication Studies, 52, 324–337.
Sussman, S. W., & Siegal, W. S. (2003). Informational influence in organizations: an integrated approach to knowledge adoption. Information Systems Research, 14(1), 47-65.
Sussman, S. W., & Siegel, W. S. (2003). Informational influence in organizations: An integrated approach to knowledge adoption. Information Systems Research, 14, 47–65.
Tam, K. Y., & Ho, S. Y. (2005). Web personalization as a persuasion atrategy: An elaboration likelihood model perspective. Information Systems Research, 16(3), 271–291.
Theng, Y., Teo, P. F., & Truc, P. H. (2010). Investigating sociability and affective responses of elderly users through digitally-mediated exercises: A case of the Nintendo Wii. IFIP Advances in Information and Communication Technology, 332, 152–162.
Venkatesh, V., & Brown, S. A. (2001). A longitudinal investigation of personal computers in homes: Adoption determinants and emerging challenges. MIS Quarterly, 25, 71–102.
Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Science, 27, 451–481.
Warner, D., & Procaccino, J.D. (2004). Toward wellness: Women seeking health information. Journal of the American Society for Information Science and Technology, 55(8), 709-730.
Winkler, J., Bingham, A., Coffey, P., & Penn, H. W. (2008). Women''s participation in a cervical cancer screening program in northern. Health Education Research, 23 (1), 10-24.
Zhang, P. (2013). The affective response model: a theoretical framework of affective concepts and their relationships in the ICT context. MIS Quarterly, 37(1), 247-274.
方世榮(譯)(1998)。行銷管理學(原作者 PhilipKotler)。台北:東華書局。
王淑芳、陳季員、陳彰惠(2007)。台灣地區專業人員母乳哺育教育現況及未來發展-三角交叉研究。志為護理-慈濟護理雜誌,6(6),92-102。
田治平(2006)。角色代言人言在推敲可能性模式的影響途徑。中央大學企業管理研究所,桃園縣。
吳明隆、張毓仁(2010)。結構方程模式-實務應用秘笈。臺北市:五南。
宋欣怡(2001)。民眾就醫選擇資訊的需求研究。台灣大學公共衛生學院衛生政策與管理研究所,新北市。
李鳳雪、王國明、高毓秀(2012)。初產婦背景因素對母乳哺餵經驗與自我效能之影響。助產雜誌(54),56-67。
林建煌(2007)。消費者行為概論。台北:華泰文化。
林豐政、曾志仁(2014)。線上遊戲顧客滿意度指標模式之研究-以角色扮演遊戲類型為例。智慧科技與應用統計學報,12(2),87-107。
邱皓政(2008)。結構方程模式的檢定力分析與樣本數決定。αβγ 量化研究學刊,2(1),139-173。
姚聖潔、鄭欽龍(2012)。遊憩品質認知對遊客滿意及重遊與推薦意圖關係之分析-以鳳凰自然教育園區為例。中華林學季刊,45(4),409-421。
徐嘉君(1999)。登山活動參與者行為意向之研究。私立中國文化大學觀光事業研究所,台北市。
袁影、杜柯凝(2010)。新生兒母親最關心的育兒知識需求調查。吉林醫學,31, 5573-5574。
國民健康署(2000)。公共場所母乳哺育條例。取自: http://mammy.hpa.gov.tw/kbcontent.asp?f=atmk&cid=394。
國民健康署婦幼及生育保健組(2012)。母乳哺育國內現況。取自: http://mammy.hpa.gov.tw/kbcontent.asp?cid=354。
張偉豪(2011)。SEM論文寫作不求人,台北市;鼎茂。
黃芳銘(2010)。結構方程模式理論與應用。台北市:五南。
陳素娟(2011)。衛生單位女性員工於職場持續哺餵母乳的相關因素與其預測因子。高雄醫學大學護理學研究所學位論文,1-99。
陳雅娟(2010)。醫療機構專業人員之人格特質、社會交換、專業服務接觸行為意圖對病患滿意度的影響。成功大學工程管理碩士在職專班學位論文,1-119。
陳順宇(2004)。多變量分析,臺北市:華泰書局。
陳順宇(2007)。結構方程模式Amos 操作。臺北市:心理。
陳純德、陳美如(2014)。部落客意見領袖信任轉移影響之研究:推敲可能性模式觀點。 電子商務學報,16(3),247-275。
馮曉蘋(2005)。母乳哺育計畫與個別行動者接軌的可能:從母乳支持團體的觀點分析。南華大學,社會學研究所碩士論文。
施俊明、吳裕益(2008)。「大學生身心健康量表」構念效度驗證之研究。教育研究與發展期刊,4(4),201-230。
黃冠英(2006)。台灣大學生網路健康資訊使用調查,國立中山大學。
蕭至惠(2012)。懷舊廣告果真為銷售萬靈丹?-從集體懷舊觀點探討懷舊廣告對台灣嬰兒潮世代的影響。行銷科學學報,8(2),117-146。
蘇郁珊(2011)。台北市嬰幼兒教保人員對哺餵母乳之認知與行為及相關因素研究。 國立臺北護理健康大學嬰幼兒保育系,台北市。
莊錦娥(2014)。探討產後婦女母乳哺育與生活品質之相關性。中國醫藥大學醫務管理學系碩士在職專班學位論文,台中市。


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