隨著人類平均壽命增加，使全球步入高齡化社會，罹患慢性病的人口也日漸增加，根據衛生署統計全台灣有將近一千零二十萬的慢性病患，且全台十大死因當中有九個為慢性病所導致。相關醫療照護問題及醫院、藥局之間的合作關係接連出現新挑戰，除了透過醫療技術、飲食作息來改善慢性疾病症狀外，亦需探索創新的服務設計來改善問題。
新穎的醫療技術雖然成功地延長了人類的壽命，但是慢性病患者的日常用藥仍存在許多問題。根據世界衛生組織統計，僅30%~60%的慢性病患者有確實遵照醫生囑咐服用藥物，其低下的用藥依從性將增加罹患併發症的風險，或是加速病況惡化，亦為將來的醫療照護體系造成更多財務負擔。傳統的用藥方式例如：藥袋、藥盒或提醒方式易讓患者產生焦慮不安、處於弱者的負面心態。有神經質人格特質的患者較容易感覺到壓力、緊張、焦慮的情緒，或是表達未有明確醫療證據的身體不適感或長期或複雜的用藥過程中感覺到挫折、較容易擔心藥品的副作用，因此導致錯過或忽略正確的用藥時間，間接影響醫療效果不彰或患者的生活信心下降。
傳統的用藥干預實驗著重研究「衛生教育、簡化用藥方案或是相關照護者介入」對依從性的影響，較少從人格特質的面向切入。本研究透過深度訪談了解病患者的用藥現況及體驗，經過質性分析整理出四大主題，包含基本病理資訊、低用藥依從性之原因、藥品管理習慣及生活型態。另外參考說服科技（Persuasive Technology）及心理學中的自我肯定理論（Self-affirmation）架構，針對具有神經質人格特質之患者設計用藥提醒訊息，並招募參與者進行干預實驗。透過 LINE 接收提醒訊息，於測後訪談中採用卡片分類法，了解其對訊息的理解邏輯、激勵患者用藥依從性的動力來源，並歸納有效訊息的重點元素，包含提及正向的價值觀、個人角色、社會關係等概念，較能喚起參與者對自我形象完整保護。本研究的結果，跳脫出傳統衛教知識的干預內容，能作為未來用藥提醒訊息設計的切入參考。

According to the statistics of the National Health Insurance Department, nearly 10.2 million people have a chronic illness in Taiwan. Other surprising numbers from the World Health Organization (WHO), only 30%-60% of patients follow treatment instruction. A low adherence rate on medication might accelerate illness deterioration and increase the financial burden on the health care system. Traditional treatment and intake, such as medicine bags, pillboxes or monotonous reminders, can easily cause anxious or negative emotion, and indirectly lead to poor medical effects.
In previous studies, researchers often focused on education or simplify the medication regimens, less from the perspective of personality traits. Therefore, what kind of design principles are most effective for interventions are yet to be tested in multiple chronic conditions.
In this study, we firstly investigated the medication intake behavior by deep-interview and aggregated into four categories, including pathological information, causes of low adherence rate, medication management behavior, and lifestyle. Secondly, designed the reminders for patients who have neuroticism personality traits based on persuasive technology and self-affirmation theory. Third, by sending a variety of persuasive messages for fourteen days. A post-test interview and card-sorting are conducted to understand what kind of messages could better motivate behavior. When messages convey the meaning of values, individual roles, social relationships could arouse patients’ responses to protect self-integrity. The result of this study is different from the traditional intervention design,it offers guidelines for future reminders design.

第一章、緒論
第一節：研究背景與動機 7
第二節：研究目的 11
第三節：預期貢獻 12
第四節：論文架構 12

第二章、文獻回顧
第一節：藥物依從性之定義與測量方法 14
第二節：先前改善依從性之干預方法 16
第三節：國外慢性病用藥干預措施的研究 17
第四節：理論為基礎的干預設計 22
第五節：人格特質與用藥依從性的關係 25
第六節：小結 26

第三章、訪談之研究方法與分析結果
第一節：研究方法 - 深度訪談法 28
第二節：訪談分析 31
第三節：結果與討論 42

第四章、 干預實驗之設計與分析結果
第一節：用藥干預實驗之設計 44
第二節：實驗流程及招募 48
第三節：干預實驗之成果、受測者感受 49
第四節：結果與討論 57

第五章、研究結論與建議
第一節：研究結論與討論 60
第二節：研究貢獻 62
第三節：研究建議 64

參考文獻
中文文獻 66
英文文獻 66

附錄
附錄一：藥師訪談計畫與大綱 72
附錄二：慢性病患者訪談計畫與大綱- 實驗前 73
附錄三：慢性病患者訪談計畫與大綱- 實驗後 74

中文文獻
1. 國民健康署（二零一九年九月二十五日）高血壓不是中老年人專利!36萬青壯高血壓大軍，近24萬自己不知道。「段落四」取自：https://taiwangov.com/KUJah
2. Author, A. (200, November 17). Message [Msg 1]. Message posted to news address.
3. 例 如：Chalmers, D. (2000, November 17). Seeing with sound [Msg 1]. Message posted to news://sci.psychology.consciousness 林美娟. (2013). 高齡化社會價值之研究. 台灣經濟論衡, 高齡化社會價值之研究, 44–62.
4. 內政部戶政司（2019）。《內政部統計年報》 。〈05.年齡別死亡數〉取自：https://www.moi.gov.tw/files/site_stuff/321/2/year/year.html
5. 衛生福利部（二零零一年七月十一日）。〈老化海嘯襲台灣，23鄉鎮超高齡，89%老人有慢性病！〉。取自：https://taiwangov.com/43bdk
6. 資策會（二零一九年十月二十三日）〈LINE 一支獨秀，延伸付物接受度高-通訊APP使用概況〉。取自：https://mic.iii.org.tw/aisp/ReportS.aspx?id=CDOC20191018001
7. LINE台灣官方BLOG（二零一九年月二十五日）〈LINE的使用大數據首次公開！台灣用戶使用LINE的方式原來是這樣〉。取自：http://official-blog.line.me/tw/archives/81291901.html

英文文獻
1. Alsharbi, B., & Richards, D. (2017). Using Virtual Reality Technology to Improve Reality for Young People with Chronic Health Conditions. 11–15.
2. Arias, J. T., Higuita, J. C., & Castrillón, O. D. (2010). The Big Five Personality Test. Cuadernos de Admnistracion, 23(41), 81–105. https://doi.org/10.1017/S1477175612000073
3. Banerjee, P. (2004). About Face 2.0: The Essentials of Interaction Design: Alan Cooper and Robert Reimann Published by John Wiley & Sons, 2003, 576 pp, ISBN 0764526413. Information Visualization, 3(3), 223–225. https://doi.org/10.1057/palgrave.ivs.9500066
4. Barwitz, N., & Maas, P. (2018). Understanding the Omnichannel Customer Journey: Determinants of Interaction Choice. Journal of Interactive Marketing, 43, 116–133. https://doi.org/10.1016/j.intmar.2018.02.001
5. Bosworth, H. B., Granger, B. B., Mendys, P., Pharm, D., Brindis, R., Ho, M., Johnson, M., Kimmel, S. E., Liu, L. Z., & Musaus, J. (2011). Medication adherence : A call for action. American Heart Journal, 162(3), 412–424. https://doi.org/10.1016/j.ahj.2011.06.007
6. Bruce, J. M., Hancock, L. M., Arnett, P., & Lynch, S. (2010). Treatment adherence in multiple sclerosis: Association with emotional status, personality, and cognition. Journal of Behavioral Medicine, 33(3), 219–227. https://doi.org/10.1007/s10865-010-9247-y
7. Chang, F.-F. (2010). The Five Steps of Qualitative Data Analysis: Climbing up a Ladder of Abstraction. Journal of Elementary Education, 35, 87–120.
8. Charlson, M. E., Wells, M. T., Peterson, J. C., Boutin-Foster, C., Ogedegbe, G. O., Mancuso, C. A., Hollenberg, J. P., Allegrante, J. P., Jobe, J., & Isen, A. M. (2014). Mediators and moderators of behavior change in patients with chronic cardiopulmonary disease: The impact of positive affect and self-affirmation. Translational Behavioral Medicine, 4(1), 7–17. https://doi.org/10.1007/s13142-013-0241-0

9. Christensen, A. J., & Smith, T. W. (1995). Personality and patient adherence: Correlates of the five-factor model in renal dialysis. Journal of Behavioral Medicine, 18(3), 305–313. https://doi.org/10.1007/BF01857875
10. Cleary, M. (2019). The Big-Five Trait Taxonomy. Journal of Chemical Information and Modeling, 53(9), 1689–1699. https://doi.org/10.1017/CBO9781107415324.004
11. Dowshen, N., Kuhns, L. M., Johnson, A., Holoyda, B. J., & Garofalo, R. (2012). Improving adherence to antiretroviral therapy for youth living with HIV/AIDS: A pilot study using personalized, interactive, daily text message reminders. Journal of Medical Internet Research, 14(2), 168–175. https://doi.org/10.2196/jmir.2015
12. Dunbar-Jacob, J., & Mortimer-Stephens, M. K. (2001). Treatment adherence in chronic disease. Journal of Clinical Epidemiology, 54(12 SUPPL. 1), 57–60. https://doi.org/10.1016/S0895-4356(01)00457-7
13. Fischer, M. A., Stedman, M. R., Liberman, J. N., Brennan, T. A., Jain, S. H., & Shrank, W. H. (2010). Healthcare Information Technology Interventions to Improve Cardiovascular and Diabetes Medication Adherence. December, 82–92.
14. Fjeldsoe, B. S., Marshall, A. L., & Miller, Y. D. (2009). Behavior Change Interventions Delivered by Mobile Telephone Short-Message Service. American Journal of Preventive Medicine, 36(2), 165–173. https://doi.org/10.1016/j.amepre.2008.09.040
15. Free, C., Phillips, G., Felix, L., Galli, L., Patel, V., & Edwards, P. (2010). The effectiveness of M-health technologies for improving health and health services : a systematic review protocol. 5–7.
16. Free, C., Phillips, G., Watson, L., Galli, L., Felix, L., Edwards, P., Patel, V., & Haines, A. (2013). The Effectiveness of Mobile-Health Technologies to Improve Health Care Service Delivery Processes : A Systematic Review and Meta-Analysis. 10(1). https://doi.org/10.1371/journal.pmed.1001363
17. George, J., Elliott, R. A., & Stewart, D. C. (2008). A Systematic Review of Interventions to Improve Medication Taking in Elderly Patients Prescribed Multiple Medications. 25(4), 307–324.
18. Graziano, W., & Eisenberg, E. (1964). Agreableness : Adimension of personality.
19. Hsu, N.-C., Lin, Y.-F., Shu, C.-C., Yang, M.-C., & Ko, W.-J. (2013). Noncancer Palliative Care. American Journal of Hospice and Palliative Medicine®, 30(4), 334–338. https://doi.org/10.1177/1049909112449068
20. Ish, A. S. H. (2014). 二、 arb 類藥品. 125–131.
21. Khonsari, S., Subramanian, P., Chinna, K., Latif, L. A., Ling, L. W., & Gholami, O. (2015). Effect of a reminder system using an automated short message service on medication adherence following acute coronary syndrome. European Journal of Cardiovascular Nursing, 14(2), 170–179. https://doi.org/10.1177/1474515114521910
22. Krousel-Wood, M., Islam, T., Webber, L. S., Re, R. N., Morisky, D. E., & Muntner, P. (2009). New medication adherence scale versus pharmacy fill rates in seniors with hypertension. American Journal of Managed Care, 15(1), 59–66.
23. Lahey, B. B. (2009). Public Health Significance of Neuroticism. American Psychologist, 64(4), 241–256. https://doi.org/10.1037/a0015309
24. Lavsa, S. M., Holzworth, A., & Ansani, N. T. (2011). Selection of a validated scale for measuring medication adherence. Journal of the American Pharmacists Association, 51(1), 90–94. https://doi.org/10.1331/JAPhA.2011.09154
25. Lee, M. L., & Dey, A. K. (2014). Real-time feedback for improving medication taking. Conference on Human Factors in Computing Systems - Proceedings, 2259–2268. https://doi.org/10.1145/2556288.2557210
26. Lemon, K. N., & Verhoef, P. C. (2016). Understanding customer experience throughout the customer journey. Journal of Marketing, 80(6), 69–96. https://doi.org/10.1509/jm.15.0420
27. Lindsey Dayer, PharmD, Seth Heldenbrand, PharmD, P. A., & Paul O. Gubbins, PharmD, and Bradley C. Martin, PharmD, P. (2000). Smartphone medication adherence apps: Potential benefits to patients and providers. J Am Pharm Assoc (2003). 2013 ; 53(2): 172–181. Doi:10.1331/JAPhA.2013.12202., 53(5), 1–8. https://doi.org/10.1331/JAPhA.2013.12202.Smartphone
28. Márquez Contreras, E., de la Figuera von Wichmann, M., Gil Guillén, V., Ylla-Catalá, A., Figueras, M., Balaña, M., & Naval, J. (2004). [Effectiveness of an intervention to provide information to patients with hypertension as short text messages and reminders sent to their mobile phone (HTA-Alert)]. Atencion Primaria, 34(8), 399–405. https://doi.org/10.1157/13068215
29. Matsuzawa, Y., Lee, Y. S. C., Fraser, F., Langenbahn, D., Shallcross, A., Powers, S., Lipton, R., Simon, N., & Minen, M. (2019). Barriers to Behavioral Treatment Adherence for Headache: An Examination of Attitudes, Beliefs, and Psychiatric Factors. Headache, 59(1), 19–31. https://doi.org/10.1111/head.13429
30. McCrae, R. R., & Costa, P. T. (1987). Validation of the Five-Factor Model of Personality Across Instruments and Observers. Journal of Personality and Social Psychology, 52(1), 81–90. https://doi.org/10.1037/0022-3514.52.1.81
31. McGee-Lennon, M. R., Wolters, M. K., & Brewster, S. (2011). User-centred multimodal reminders for assistive living. Conference on Human Factors in Computing Systems - Proceedings, 2105–2114. https://doi.org/10.1145/1978942.1979248
32. Mental, P., Nurse, H., Mental, P., & Nurse, H. (2013). An Introduction to the Five-Factor Model and Its Applications. 1–3.
33. Morrissey, E. C., Corbett, T. K., Walsh, J. C., & Molloy, G. J. (2016). Behavior change techniques in apps for medication adherence: A content analysis. American Journal of Preventive Medicine, 50(5), e143–e146. https://doi.org/10.1016/j.amepre.2015.09.034
34. Oliver P.John, & Sanjay Srivastava. (1999). The Big-Five Trait Taxonomy: History, Measurement, and Theoretical Perspectives. Journal of Chemical Information and Modeling, 53(9), 1689–1699. https://doi.org/10.1017/CBO9781107415324.004
35. Piotrowicz, W., & Cuthbertson, R. (2014). Introduction to the Special Issue Information Technology in Retail: Toward Omnichannel Retailing. International Journal of Electronic Commerce, 18(4), 5–16. https://doi.org/10.2753/JEC1086-4415180400
36. Preference, P., Hugtenburg, J., Timmers, L., & Elders, P. J. M. (2013). Definitions , variants , and causes of nonadherence with medication : a challenge for tailored interventions. July. https://doi.org/10.2147/PPA.S29549
37. Schwarz, H. (2014). 9. Important Issues. Vying for Truth - Theology and the Natural Sciences, 207–228. https://doi.org/10.13109/9783666540288.207
38. Sherman, D. K., & Cohen, G. L. (2006). The Psychology of Self-defense: Self-Affirmation Theory. Advances in Experimental Social Psychology, 38(06), 183–242. https://doi.org/10.1016/S0065-2601(06)38004-5
39. Tajfel, H. (1974). Social identity and intergroup behaviour. Social Science Information, 13(2), 65–93. https://doi.org/10.1177/053901847401300204
40. Thakkar, J., Kurup, R., Laba, T. L., Santo, K., Thiagalingam, A., Rodgers, A., Woodward, M., Redfern, J., & Chow, C. K. (2016). Mobile telephone text messaging for medication adherence in chronic disease a meta-analysis. JAMA Internal Medicine, 176(3), 340–349. https://doi.org/10.1001/jamainternmed.2015.7667
41. Whittaker, R., & Chb, M. B. (2012). Issues in mHealth : Findings From Key Informant Interviews Corresponding Author : 14, 1–9. https://doi.org/10.2196/jmir.1989