研究生: |
游騏瑄 Yu, Chi-Hsuan |
---|---|
論文名稱: |
應用創新慢性腎臟病健康照護機器人進行數位學習之使用者經驗探討 Exploring the User Experience of an Innovative Robot-based Digital Education for Patients with Chronic Kidney Disease |
指導教授: |
郭鐘隆
Guo, Jong-Long |
口試委員: |
郭鐘隆
Guo, Jong-Long 黃久美 Huang, Chiu-Mieh 李子奇 Lee,Tzu-Chi |
口試日期: | 2022/01/18 |
學位類別: |
碩士 Master |
系所名稱: |
健康促進與衛生教育學系 Department of Health Promotion and Health Education |
論文出版年: | 2022 |
畢業學年度: | 110 |
語文別: | 中文 |
論文頁數: | 108 |
中文關鍵詞: | 人工智慧 、機器人 、慢性腎臟病 、數位學習 、個人涉入程度 、系統可用性 |
英文關鍵詞: | Artificial Intelligence, robot, chronic kidney disease, digital learning, personal involvement inventory, system usability |
研究方法: | 準實驗設計法 |
DOI URL: | http://doi.org/10.6345/NTNU202200286 |
論文種類: | 學術論文 |
相關次數: | 點閱:277 下載:74 |
分享至: |
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
背景:人工智慧(Artificial Intelligence, AI)科技的發展之下,機器人的發展日漸蓬勃,且已經被應用在許多智慧健康服務的業務上。隨者慢性腎臟病罹病人數越來越多,隨之而來的護理人力短缺、衛教時間不足,以及沉重的健保、財政負擔,都是臺灣正面臨的重大議題。為了提升病人的照護品質、自我健康管理的能力,應用創新科技在健康促進與衛生教育的領域已是刻不容緩。
目的:本研究旨在探討慢性腎臟病病患使用慢性腎臟病健康照護機器人進行數位學習的使用者經驗。
方法:共計招募慢性腎臟病病患92人。參與者接受20分鐘的創新衛教後會進行問卷填寫。了解其在系統可用性得分、個人涉入程度、學習動機跟學習成效的表現。問卷蒐集完畢後,以結構方程模型-偏最小平方法(Partial Least Squares Structural Equation Modeling, PLS-SEM)進行統計及分析。
結果:使用者在系統可用性得分74.701分,介於「good」到「excellent」之間,顯示使用者能接受慢性腎臟病健康照護機器人的使用。並在個人涉入程度、學習動機及學習成效的變項都有高度的回饋。使用者經驗中的系統可用性與個人涉入程度可以與學習動機及學習成效建立PLS-SEM結構模型。本研究假設14條直接路徑,共10條顯著,分別是「系統可用性」與「個人涉入程度」到「學習動機」的四個構面(T=4.416, P<.01; T=5.422, P<.01; T=6.621, P<.01; T=6.003, P<.01; T=3.500, P<.01; T=4.173, P<.01; T=2.427, P<.05; T=3.306, P<.01);以及學習動機的「引起注意」及「感到滿意」構面到「學習成效」(T=2.729, P<.05; T=2.092, P<.05)。間接路徑的8條假設路徑上,共2條顯著,分別為「系統可用性」透過「引起注意」及「感到滿意」到學習成效(T=2.402, P<.05; T=2.101, P<.05)。
結論:研究對象使用本研究工具「慢性腎臟病健康照護機器人」後,在系統可用性的得分上呈現高於平均的可接受程度,在系統可用性高的情境下,使用者可能因為工具能引起使用者興趣並維持注意力,或是使用者操作後能獲得內在或外在的成就感,進而提高使用後的學習成效。結果顯示本研究工具可應用在實際情境上,未來可以將研究擴及不僅是慢性腎臟病患者的使用,並比較不同情境下,使用次數、時間、使用者在資訊吸收上的情形。
Background:In the era of AI, robotic technology has emerged and be used in smart healthcare services. With the increasing of patients with chronic kidney disease (CKD), patient education for CKD carriers the substantial responsibility upon economic burden, because the lack of time and nursing shortage on health education are both big issues in Taiwan. It is a critical strategy to use technology improving the patients' self-management and the health education situation on site.
Objectives: The study explored the user experience of an application of CKD Education Robot on Patients with CKD.
Methods: The study recruited a total of 92 participants. The participants received a 20-minute digital education. All the participants completed the measurements consisted of System Usability Scale (SUS), Revised Personal Involvement Inventory (RPII), ARCS (Attention-Relevance-Confidence-Satisfaction) model of Motivation (ARCS) and learning effectiveness of health education programs after education. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to analyze the collected data. The data was analyzed with Smart PLS 3.3.3.
Results: Based on the responses concerning System Usability, Revised Personal Inventory Involvement, ARCS and Learning Effect in the context of the CKD Education Robot, most participants agree or strong agree that the Education Robot were acceptable and motivational, they can involvement in the using process. We well built a structural model. SUS and RPII significantly influenced each construct of ARCS model (T=4.416, P<.01; T=5.422, P<.01; T=6.621, P<.01; T=6.003, P<.01; T=3.500, P<.01; T=4.173, P<.01; T=2.427, P<.05; T=3.306, P<.01), while Attention and Satisfaction significantly influenced Learning Effect (T=2.729, P<.05; T=2.092, P<.05). In addition, indirect affects were observed from System Usability to Learning Effect via Attention and Satisfaction respectively (T=2.402, P<.05; T=2.101, P<.05).
Conclusion: The study reveals that the CKD Education Robot were positively accepted by the participating patients. The users improve learning effect in context of high system usability, with sense of achievement, or in arousing their interest and maintaining their attention. This indicates that the robotic education material is applicable for patients’ education with CKD. In the future, we can expand the study into not only patients with CKD and compare the differences in deferent using situation.
王正華、陳寬裕(2017)。論文統計分析實務:SPSS與AMOS的運用(三版)。臺北市:五南書局。
王健全(2018,12月)。未來工作世界之人力發展趨勢與因應。台灣勞工季刊,56,1-15。http://labor-elearning.mol.gov.tw/base/10001/door/%B4%C1%A5Z%C0%C9%AE%D7%B0%CF/145_no56.pdf
王聖銘、黃絜如、葉永森、林書瑄、林聿儒(2016)。悅趣化學習之ARCS學習動機設計與評估─以「能源戰爭」嚴肅遊戲為例。https://www.eduhk.hk/gccce2016/proceedings/MainConferenceIndividualPapers/C3-4.pdf
朱祐萱、林清壽(2019)。銀髮族使用Zenbo機器人服務體驗洞察研究 [Study on Service Experience Insight of Use of Zenbo Robot by Silver-haired People]。福祉科技與服務管理學刊,7(1),50-72。 https://doi.org/10.6283/jocsg.201903_7(1).467
林明彥、黃尚志 (2007)。台灣慢性腎臟病/末期腎臟病流行病學過去、現在與未來。腎臟與透析,19(1),1-5。
周宇翔、王舒芸(2019)。機器人在社區照顧關懷據點應用與挑戰之初探研究 [Preliminary Study on Application and Challenges of Robots in Community Care Centers]。福祉科技與服務管理學刊,7(3)262-279。https://doi.org/10.6283/jocsg.201909_7(3).262
邱皓政(2011)。量化研究與統計分析(第五版)。五南。
邱皓政(2010)。量化研究與統計分析:SPSS(PASW)資料分析範例解釋。五南。
洪碩延、王政弘、徐佳煌(2016)。翻轉教學應用在設計課程之學習系統建置與評估 [Establishment and Assessment of Design Course Learning System for Flipped Classroom]。文化創意產業研究學報,6(1),27-35。https://doi.org/10.6639/jccir.2016.0601.04
胡蓮欣、黃文盛、吳良治(2019)。 AI大時代:從人工智慧在核醫心臟學的應用預見AI在醫療領域之變革。臨床醫學月刊,84(6),783-793。https://doi.org/10.6666/ClinMed.201912_84(6).0130
徐雅玲(2018)。利用多模態模型混合CNN和LSTM影音特徵以自動化偵測急診病患疼痛程度〔未出版之碩士論文,國立清華大學電機工程學系所〕。AiritiLibrary。
高靖秋(2011)。 台灣護理人力面面觀 [Multi-aspects of Nursing Manpower in Taiwan]。澄清醫護管理雜誌,7(3),41-46。https://doi。org/10。30156/ccmj。201107。0005
夏至賢、賴槿峰、蘇育生、黃悅民(2020)。以ARCS動機模式及問題導向學習法應用於機器人教育探討。
張偉豪(2011)。論文寫作SEM不求人。三星統計。
陳嘉葳、謝楠楨、邱淑芬、郭俐蘭、葉美玲(2020)。針灸護理行動APP開發與成效初探 [Development and Effects of Mobile Application for Acupuncture Care]. 長庚護理, 31(4), 465-475. https://doi.org/10.6386/cgn.202012_31(4).0002
陳俞琪(2010)。運用充能概念於慢性腎臟病個案管理照護模式之成效探討。https://etd.lib.nctu.edu.tw/cgi-bin/gs32/ymgsweb.cgi?o=dymcdr&s=id=%22GYP221098256%22.&searchmode=basic
陳俞琪、張博論(2016)。應用健康資訊科技於慢性腎臟病持續性照護之契機與反思。護理雜誌,63(2),12-18。
陳振山、黃教琪(2019)。Application of Robotic Arm for Medical Surgery Positioning Aid [應用機器手臂於醫療手術定位輔助]。中華科技大學學報(77),1-21。
曾偉凱(2019)。運用ARCS動機模式於懸浮微粒汙染遊戲式學習創作之研究〔未發表之碩士論文,樹德科技大學應用設計研究所〕。AiritiLibrary.
陳瑞仁、賴鈺婷、顏宏旗(2021)。應用人工智慧建構醫療服務即時衛教機器人 [Apply Artificial Intelligence to Develop a Medical Service and Health Education Chatbot]。醫務管理期刊,22(2),136-150。https://doi.org/10.6174/jhm.202106_22(2).136
陳寬裕(2020)。16小時學會結構方程模型:SmartPLS初階應用。五南線上學院。https://www.wunan.com.tw/tch_course?seq=2049&mode=preview
陳寬裕(2018)。結構方程模型分析實務: Spss與SmartPLS的運用(初版)。臺北市:五南書局。
陳蕙倫(2018)。Artificial Intelligence in Healthcare [人工智能於醫療保健的領域]。Journal of Biomedical & Laboratory Sciences,30(2),33-37。
葉明莉(2016)。機器人與健康照護應用 [Robots and Application in Healthcare]。領導護理,17(4),3-12。 https://doi。org/10。29494/ln。201612_17(4)。0001
溫欣儒(2020)。專為上班族打造工作也能兼顧健康-智慧AI隨時監控健康人生。禪天下(181),76-79。
廖珮如(2020)。人口老化:勞動力短缺之衝擊與挑戰。人文與社會科學簡訊,21(2),74-83。
衛生福利部(2018)。2017老人狀況調查報告。https://dep.mohw.gov.tw/dos/cp-1767-38429-113.html
衛生福利部(2015)。慢性腎臟病防治-104年全民健康保險初期慢性腎臟病醫療給付改善方案。https://www.nhi.gov.tw/Resource/webdata/26254_1_Early%20CKD計畫.pdf
衛生福利部統計處(2021)。民國109年國人死因統計結果。https://www.mohw.gov.tw/cp-16-61533-1.html
衛生福利部中央健康保險署(2020)。慢性腎臟病防治。https://www.nhi.gov.tw/Content_List.aspx?n=D5CC89AE36D48E5E&topn=787128DAD5F71B1A
衛生福利部國民健康署(2021)。5成以上慢性腎臟病患者輕忽三高控制。https://www.mohw.gov.tw/cp-16-58578-1.html
衛生福利部國民健康署(2018)。慢性腎臟病健康管理手冊。https://www.hpa.gov.tw/Pages/EBook.aspx?nodeid=1157
蕭文龍(2020)。統計分析入門與應用:SPSS中文版+ SmartPLS 3(PLS-SEM)(第三版)。臺北市: 碁峯資訊。
Anderson, J.C., & Gerbing, D.W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103, 411-423. https://doi.org/10.1037/0033-2909.103.3.411
Bagozzi, R. and Yi, Y. (1988) On the Evaluation of Structural Equation Models. Journal of the Academy of Marketing Sciences, 16, 74-94.http://dx.doi.org/10.1007/BF02723327
Bangor, A., Kortum, P., & Miller, J. (2009). Determining what individual SUS scores mean: adding an adjective rating scale. Journal of Usability Studies, 4 (3), 114–123.
Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the a nalysis of covariance structures. Psychological Bulletin, 88 (3), 588-606.
Bloch, P., & Richins, M. (1983). A Theoretical Model of the Study of Product Importance Perception. Journal of Marketing, 47. https://doi.org/10.2307/1251198
Brooke, J. (1995). SUS: A quick and dirty usability scale. Usability Eval. Ind., 189.
Brooke, J. (2013). SUS: a retrospective. Journal of Usability Studies, 8, 29-40.
Chin, W. W. (2010). How to Write Up and Report PLS Analyses. In V. Esposito Vinzi, W. W. Chin, J. Henseler, & H. Wang (Eds.), Handbook of Partial Least Squares: Concepts, Methods and Applications (pp. 655-690). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-32827-8_29
Chin, W. W., Marcolin, B. L., & Newsted, P. R. (1996). A partial least squares latent variable modelling approach for measuring interaction effects: Results from a Monte Carlo simulation study and voice mail emotion/adoption study. Paper presented at the 17th International Conference on Information Systems, Cleveland, OH.
Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Routledge. https://doi.org/10.4324/9780203771587
Dautenhahn, K., Nehaniv, C. L., Walters, M. L., Robins, B., Kose-Bagci, H., Mirza, N. A., & Blow, M. (2009). KASPAR–A Minimally Expressive Humanoid Robot for Human–Robot Interaction Research. Applied Bionics and Biomechanics, 6, 708594. https://doi.org/10.1080/11762320903123567
Deterding, S. (2012). Gamification: designing for motivation. interactions, 19(4), 14–17. https://doi.org/10.1145/2212877.2212883
Dicheva, D., Irwin, K., Dichev, C., & Talasila, S. (2015). A course gamification platform supporting student motivation and engagement. 2014 International Conference on Web and Open Access to Learning, ICWOAL 2014. https://doi.org/10.1109/ICWOAL.2014.7009214
Feil-Seifer, D., & Matarić, M. (2005). Defining Socially Assistive Robotics. 9th International Conference on Rehabilitation Robotics, 2005. ICORR 2005., 2005, 465-468, https://doi.org/10.1109/ICORR.2005.1501143.
Flynn, L. R., & Goldsmith, R. E. (1993). Application of the Personal Involvement Inventory in marketing. Psychology & Marketing, 10 (4), 357–366. https://doi.org/10.1002/mar.4220100409
Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312
Gefen, David & Straub, Detmar & Boudreau, Marie-claude. (2000). Structural Equation Modeling And Regression: Guidelines For Research Practice. Communications of the Association for Information Systems. 4. https://doi.org/10.17705/1CAIS.00407.
Gordon, N. (2014). Flexible Pedagogies: technology-enhanced learning. https://doi.org/10.13140/2.1.2052.5760
Gordon, N., Brayshaw, M., & Grey, S. (2015). Motivating and Engaging Students Through Technology. In.
Greenwald, A. G., & Leavitt, C. (1984). Audience Involvement in Advertising: Four Levels. Journal of Consumer Research, 11 (1), 581-592. https://doi.org/10.1086/208994
Guo, F. Y., & Principal, U. X. (2012). Not Just Usability-The Four Elements of User Experience. uxstrategized.com. http://uxstrategized.com/White_Paper_Four_Elements_of_User_Experience.pdf
Haenlein, M. & Kaplan, A. M. (2004). A beginner’s guide to partial least squares analysis. Understanding Statistics, 3(4), 283–297.
Hair, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. (2014). Partial Least Squares Structural Equation Modeling (PLS-SEM): An Emerging Tool for Business Research. European Business Review, 26, 106-121. https://doi.org/10.1108/EBR-10-2013-0128
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a Silver Bullet. Journal of Marketing Theory and Practice, 19(2), 139-152. https://doi.org/10.2753/MTP1069-6679190202
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1995). Multivariate data analysis. Creative Education,(3)2.
Hee, O. C. (2014). Validity and Reliability of the Customer-Oriented Behaviour Scale in the Health Tourism Hospitals in Malaysia. International Journal of Caring Sciences, 7(3), 771-775.
Hoorn, J. F., & Chien, S.-Y. (2018). From Lonely to Resilient through Humanoid Robots: Building a New Framework of Resilience. Journal of Robotics, 2018, 17. https://doi.org/10.1155/2018/8232487
Hsieh, Y.-Z., Lin, S.-S., Luo, Y.-C., Jeng, Y.-L., Tan, S.-W., Chen, C.-R., & Chiang, P.-Y. (2020). ARCS-Assisted Teaching Robots Based on Anticipatory Computing and Emotional Big Data for Improving Sustainable Learning Efficiency and Motivation. Sustainability, 12 (14), 5605. https://www.mdpi.com/2071-1050/12/14/5605
Hulland, J. (1999), Use of partial least squares (PLS) in strategic management research: a review of four recent studies. Strat. Mgmt. J., 20: 195-204. https://doi.org/10.1002/(SICI)1097-0266(199902)20:2<195::AID-SMJ13>3.0.CO;2-7
Hu, Y. (2008). Motivation, usability, and their interrelationships in a self-paced online learning environment. http://hdl.handle.net/10919/28856
International Organization for Standardization. (2018). Ergonomics of human-system interaction — Part 11: Usability: Definitions and concepts ISO 9241-11:2018. https://www.iso.org/obp/ui/#iso:std:iso:9241:-11:ed-2:v1:en
International Organization for Standardization. (2010). Ergonomics of human-system interaction -- Part 210: Human-centred design for interactive systems ISO 9241-210:2010. https://www.iso.org/obp/ui/#iso:std:iso:9241:-210:ed-1:v1:en
Ishiguro, K., & Majima, Y. (2016). Utilization of Communication Robot in Patient Education. Studies in health technology and informatics, 225, 913-914. https://doi.org/10.3233/978-1-61499-658-3-913
Jokelova, A. (2012). Effects of Relevance- and Confidence-enhancing motivational strategies, suggested strategies, and statements on academic performance and course satisfaction in undergraduate students of a blended public speaking course [Ph.D., University of South Alabama]. https://eric.ed.gov/?id=ED551611
Jones B.D. (2020) Motivating and Engaging Students Using Educational Technologies. In: Bishop M.J., Boling E., Elen J., Svihla V. (eds) Handbook of Research in Educational Communications and Technology. Springer, Cham. https://doi.org/10.1007/978-3-030-36119-8_2
Jöreskog, K.G., & Sörbom D. (1989). LISREL 7: A Guide to the Program and Applications. Chicago: SPSS, Inc.
Keller, J. M. (2016). Motivation, Learning, and Technology: Applying the ARCS-V Motivation Model. Participatory Educational Research, 3, 1-15. https://doi.org/10.17275/per.16.06.3.2
Keller, J. M. (2010). Motivational Design for Learning and Performance: The ARCS Model Approach. https://doi.org/10.1007/978-1-4419-1250-3
Keller, J. M. (1987). Development and use of the ARCS model of instructional design. Journal of instructional development, 10 (3), 2. https://doi.org/10.1007/BF02905780
Keller, J. M. (1984). The use of the ARCS model of motivation in teacher training. Aspects of educational technology, 17, 140-145.
Khan, G. F., Sarstedt, M., Shiau, W.-L., Hair, J. F., Ringle, C. M., & Fritze, M. P. (2019). Methodological research on partial least squares structural equation modeling (PLS-SEM). Internet Research, 29(3), 407-429. https://doi.org/10.1108/IntR-12-2017-0509
Kiesler, S., Powers, A., Fussell, S., & Torrey, C. (2008). Anthropomorphic Interactions with a Robot and Robot–like Agent. Social Cognition - SOC COGNITION, 26, 169-181.
Knippenberg, E., Timmermans, A., Palmaers, S., & Spooren, A. (2020). Use of a technology-based system to motivate older adults in performing physical activity: a feasibility study. https://doi.org/10.21203/rs.3.rs-53576/v2
Kujala, Sari. (2003). User involvement: A review of the benefits and challenges. Behaviour & IT. 22. 1-16. https:// doi.org/10.1080/01449290301782.
Liang, J., Xian, D., Liu, X., Fu, J., Zhang, X., Tang, B., & Lei, J. (2018). Usability Study of Mainstream Wearable Fitness Devices: Feature Analysis and System Usability Scale Evaluation. JMIR Mhealth Uhealth, 6 (11), e11066. https://doi.org/10.2196/11066
Malik, S. (2014). Effectiveness of Arcs Model of Motivational Design to Overcome Non Completion Rate of Students in Distance Education. Turkish Online Journal of Distance Education, 15. https://doi.org/10.17718/tojde.18099
Mcquarrie, E. F., & Munson, J. (1992). A Revised Product Involvement Inventory: Improved Usability and Validity. Advances in Consumer Research North American Advances. 1992, 19 (1), 108-115. https://www.acrwebsite.org/volumes/7277/volumes/v19/NA-19
Means, T. B. (1997). Enhancing Relevance: Embedded ARCS Strategies vs. Purpose. Educational Technology Research and Development, 45(1), 5-17.
Melkas, H., Hennala, L., Pekkarinen, S., & Kyrki, V. (2020). Impacts of robot implementation on care personnel and clients in elderly-care institutions. International Journal of Medical Informatics, 134, 104041. https://doi.org/https://doi.org/10.1016/j.ijmedinf.2019.104041
Mittal, B. (2006). Measuring Purchase Decision Involvement. Psychology and Marketing, 6, 147-162. https://doi.org/10.1002/mar.4220060206
Moyle, W., Jones, C., Sung, B., Bramble, M., O’Dwyer, S., Blumenstein, M., & Estivill-Castro, V. (2016). What Effect Does an Animal Robot Called CuDDler Have on the Engagement and Emotional Response of Older People with Dementia? A Pilot Feasibility Study. International Journal of Social Robotics, 8 (1), 145-156. https://doi.org/10.1007/s12369-015-0326-7
Nehrujee, A., Vasanthan, L., Lepcha, A., & Balasubramanian, S. (2019). A Smartphone-based gaming system for vestibular rehabilitation: A usability study. J Vestib Res, 29(2-3), 147-160. https://doi.org/10.3233/ves-190660
Nunnally, J.C. and Bernstein, I.H. (1994) The Assessment of Reliability. Psychometric Theory, 3, 248-292.
Petty, R., & Cacioppo, J. (1981). Issue Involvement As a Moderator of the Effects on Attitude of Advertising Content and Context. Advances in Consumer Research. 1981, 8 (1), 20-24. https://www.acrwebsite.org/volumes/9252/volumes/v08/NA-08
Savic, B. S., Pagon, M., & Robida, A. (2007). Predictors of the level of personal involvement in an organization: a study of Slovene hospitals. Health Care Manage Rev, 32(3), 271-283. https://doi.org/10.1097/01.HMR.0000281628.22526.0a
Schilling, I., Herbon, C., Jilani, H., Rathjen, K. I., & Gerhardus, A. (2020). [Patient and public involvement in clinical research: An introduction]. Z Evid Fortbild Qual Gesundhwes, 155, 56-63. https://doi.org/10.1016/j.zefq.2020.06.007
Schumacker, R. E., & Lomax, R. G. (2004). A beginner's guide to structural equation modeling (2nd ed.). Lawrence Erlbaum Associates Publishers.
Seraj, M., & Chui Yin, W. (2012, 12-14 June 2012). A study of User Interface Design principles and requirements for developing a Mobile learning prototype. 2012 International Conference on Computer & Information Science (ICCIS), 2012, 1014-1019.https://doi.org/10.1109/ICCISci.2012.6297174.
Small, R., & Gluck, M. (1994). The Relationship of Motivational Conditions to Effective Instructional Attributes: A Magnitude Scaling Approach. Educational Technology, 34 (8), 33-40. http://www.jstor.org/stable/44428228
Sorell, T., & Draper, H. (2014). Robot carers, ethics, and older people. Ethics and Information Technology, 16 (3), 183-195. https://doi.org/10.1007/s10676-014-9344-7
Statsoft (2013). Structural Equation Modeling. Statsoft Electronic Statistics Textbook. http://www.statsoft.com/textbook/structural-equation-modeling/
Stevens, P. E., Levin, A., & Kidney Disease: Improving Global Outcomes Chronic Kidney Disease Guideline Development Work Group Members. (2013). Evaluation and management of chronic kidney disease: synopsis of the kidney disease: improving global outcomes 2012 clinical practice guideline. Annals of internal medicine, 158 (11), 825–830. https://doi.org/10.7326/0003-4819-158-11-201306040-00007
Tapus, A. (2009). Improving the Quality of Life of People with Dementia through the Use of Socially Assistive Robots. 2009 Advanced Technologies for Enhanced Quality of Life, 2009, 81-86, https://doi.org/10.1109/AT-EQUAL.2009.26.
Ullman, J. B., & Bentler, P. M. (2003). Structural equation modeling. In J. A. Schinka & W. F. Velicer (Eds.), Handbook of psychology: Research methods in psychology, 2, 607–634. John Wiley & Sons Inc.
Wang, J., & Wang, X. (2012). Structural equation modeling: Applications using Mplus: John Wiley & Sons. Chichester, West Sussex, U.K. : Wiley/Higher Education Press.
Wen, C. P., Cheng, T. Y., Tsai, M. K., Chang, Y. C., Chan, H. T., Tsai, S. P., Chiang, P. H., Hsu, C. C., Sung, P. K., Hsu, Y. H., & Wen, S. F. (2008). All-cause mortality attributable to chronic kidney disease: a prospective cohort study based on 462 293 adults in Taiwan. Lancet (London, England), 371(9631), 2173–2182. https://doi.org/10.1016/S0140-6736(08)60952-6
Williams, L.J. and Hazer, J.T. (1986) Antecedents and Consequences of Satisfaction and Commitment in Turnover Models: A Reanalysis Using Latent Variable Structural Equation Methods. Journal of Applied Psychology, 71, 219-231. http://dx.doi.org/10.1037/0021-9010.71.2.219
Wong, K. (2013). Partial least square structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin, 24, 1-32. https://doi.org/10.12691/jbms-4-6-3.
World Health Organization (2018). Ageing and health. https://www.who.int/newsroom/fact-sheets/detail/ageing-and-health.
Ying, M.-H., & Yang, K.-T. (2013). A Game-based Learning System using the ARCS Model and Fuzzy Logic. Journal of Software., 8(9), 2155-2162. https://doi.org/10.4304/jsw.8.9.2155-2162
Zaichkowsky, J. L. (1994). The Personal Involvement Inventory: Reduction, Revision, and Application to Advertising. Journal of Advertising, 23 (4), 59-70. https://doi.org/10.1080/00913367.1943.10673459
Zaichkowsky, J. (1986). Conceptualizing Involvement. Journal of Advertising, 15 (2):4-14, 34. https://doi.org/10.1080/00913367.1986.10672999
Zaichkowsky, J. (1985). Measuring the Involvement Construct. Journal of Consumer Research, 12, 341-352. https://doi.org/10.1086/208520
Zsiga, K., Edelmayer, G., Rumeau, P., Péter, O., Tóth, A., & Fazekas, G. (2013). Home care robot for socially supporting the elderly: focus group studies in three European countries to screen user attitudes and requirements. Int J Rehabil Res, 36 (4), 375-378. https://doi.org/10.1097/MRR.0b013e3283643d26