博碩士論文 110421059 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:59 、訪客IP:3.141.42.239
姓名 戴崇宇(Chung-Yu Dai)  查詢紙本館藏   畢業系所 企業管理學系
論文名稱 行動照護對慢性病患者血壓影響之研究
(Impact of mHealth on Blood Pressure in Patients with Chronic Diseases)
相關論文
★ 以第四方物流經營模式分析博連資訊科技股份有限公司★ 探討虛擬環境下隱性協調在新產品導入之作用--以電子組裝業為例
★ 動態能力機會擷取機制之研究-以A公司為例★ 探討以價值驅動之商業模式創新-以D公司為例
★ 物聯網行動支付之探討-以Apple Pay與支付寶錢包為例★ 企業資訊方案行銷歷程之探討-以MES為例
★ B2C網路黏著度之探討-以博客來為例★ 組織機制與吸收能力關係之研究-以新產品開發專案為例
★ Revisit the Concept of Exploration and Exploitation★ 臺灣遠距醫療照護系統之發展及營運模式探討
★ 資訊系統與人力資訊科技資源對供應鏈績效影響之研究-買方依賴性的干擾效果★ 資訊科技對知識創造影響之研究-探討社會鑲嵌的中介效果
★ 資訊科技對公司吸收能力影響之研究-以新產品開發專案為例★ 探討買賣雙方鑲嵌關係影響交易績效之機制 ─新產品開發專案為例
★ 資訊技術運用與協調能力和即興能力 對新產品開發績效之影響★ 團隊組成多元性影響任務衝突機制之研究─ 以新產品開發專案團隊為例
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   [檢視]  [下載]
  1. 本電子論文使用權限為同意立即開放。
  2. 已達開放權限電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。
  3. 請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。

摘要(中) 高血壓是心血管疾病、腦中風、糖尿病、腎臟病等重大慢性病的共同危險因子,也是目前全球疾病負擔(globalburdenofdisease)排名的首位。在台灣,18歲以上國人的高血壓盛行率達26.8%,且盛行率會隨年齡增加而上升。在科技進步迅速的數位時代,使用行動照護(mHealth)便是一個可以很有效率的監控自身身體狀況的方式,當然血壓也不例外。截至2021年,在主要手機平台上架的mHealthapp的數量已經超過了35萬個。然而,在台灣卻鮮少有研究者針對mHealth對於慢性病病患血壓的影響來進行研究。因此,本研究透過與台灣本地的醫院合作,收集了66位慢性病病患的健康資料,並以多元線性回歸模型來分析病患的血壓與「是否使用mHealth」、「使用頻率」以及「使用天數」之間的關聯性。我們的研究結果發現,在使用mHealth的情況下,量測次數越多,血壓也會越低。但相反的,我們也發現使用mHealth本身與mHealth的使用天數與病患的血壓並沒有顯著的關聯性。因此,我們認為要發揮mHealth最大效益的前提,就是病患要持續穩定的進行自主量測。
摘要(英) Hypertension is a common risk factor for major chronic diseases such as cardiovasculardisease, stroke, diabetes, and kidney disease. It currently ranks as the leading contributor to theglobal burden of disease. In Taiwan, the prevalence of hypertension among individuals aged 18and above is 26.8%, and the prevalence increases with age. In this era of rapid technologicaladvancement, mobile health (mHealth) has emerged as an effective means of monitoring one′shealth status, including blood pressure. As of 2021, there are over 350,000 mHealth appsavailable on major mobile platforms. However, there is limited research in Taiwan thatspecifically examines the impact of mHealth on blood pressure among patients with chronicdiseases. Therefore, this study collaborated with local hospitals in Taiwan to collect health datafrom 66 patients with chronic diseases and used a multiple linear regression model to analyzethe relationship between patients′ blood pressure and their use of mHealth, frequency of use,and duration of use. Our research findings indicate that with the use of mHealth, highermeasurement frequency is associated with lower blood pressure. Conversely, we found nosignificant association between the use of mHealth itself or the duration of use and patients′blood pressure. Therefore, we believe that for mHealth to be maximally beneficial, patientsneed to consistently and independently monitor their blood pressure.
關鍵字(中) ★ 行動醫療
★ 應用程式
★ 血壓
★ 高血壓
★ 病患自我管理
關鍵字(英) ★ mHealth
★ mobile app
★ blood pressure
★ hypertension
★ patient self-management
論文目次 中文摘要 ..................................................................................................................................... i
Abstract ...................................................................................................................................... ii
CONTENTS .............................................................................................................................. iii
LIST OF FIGURES ................................................................................................................. iv
LIST OF TABLES .................................................................................................................... iv
Chapter 1 Introduction ......................................................................................................... 1
Chapter 2 Hypothesis & Related Work ................................................................................ 4
2.1 Benefit of mHealth ..................................................................................................... 4
2.2 The Frequency of Blood Pressure Measurements: ................................................. 4
2.3 The Time Staying with The Program ...................................................................... 5
Chapter 3 Methods ................................................................................................................ 7
3.1 Data Background ....................................................................................................... 7
3.2 Data Processing .......................................................................................................... 9
3.3 Analyzing Data ......................................................................................................... 11
3.4 White Coat Effect ..................................................................................................... 12
Chapter 4 Results & Discussion ......................................................................................... 13
4.1 Descriptive Statistics ................................................................................................ 13
4.2 Results of Multiple Linear Regression ................................................................... 13
4.2.1 Systolic Blood Pressure ................................................................................................................... 13
4.2.2 Diastolic Blood Pressure ................................................................................................................. 15
4.3 Results of Paired Sample T-test .............................................................................. 15
4.4 Results of White Coat Effect ................................................................................... 16
4.5 Discussion ................................................................................................................. 17
Chapter 5 Conclusion ......................................................................................................... 18
5.1 Conclusion ................................................................................................................ 18
5.2 Limitations and Future Directions ......................................................................... 19
Reference.................................................................................................................................. 21
Appendix .................................................................................................................................. 26
參考文獻 1. GBD 2019 Diseases and Injuries Collaborators. Global burden of 369 diseases and
injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global
Burden of Disease Study 2019. Lancet 2020;396:1204–1222.
2. GBD 2016 Causes of Death Collaborators. Global, regional, and national agesex specific
mortality for 264 causes of death, 1980–2016: a systematic analysis for the Global
Burden of Disease Study 2016. Lancet 2017;390:1151–1210.
3. NCD Risk Factor Collaboration (NCD-RisC). Worldwide trends in blood pressure from
1975 to 2015: a pooled analysis of 1479 population-based measurement studies with 191
million participants. Lancet 2017;389:37–55.
4. GBD 2019 Risk Factors Collaborators. Global burden of 87 risk factors in 204 countries
and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study
2019. Lancet 2020;396:1223–1249.
5. Wolf-Maier K, Cooper RS, Kramer H, Banegas JR, Giampaoli S, Joffres MR, Poulter N,
Primatesta P, Stegmayr B, Thamm M. Hypertension treatment and control in five
European Countries, Canada, and the United States. Hypertension 2004;43:10–17.
6. van Kleef ME, Spiering W. Hypertension: overly important but under-controlled. Eur J
Prev Cardiol 2017;24:36–43.
7. Nerenberg, K. A., Zarnke, K. B., Leung, A. A., Dasgupta, K., Butalia, S., McBrien,
K., ... & Canada, H. (2018). Hypertension Canada’s 2018 guidelines for diagnosis, risk
assessment, prevention, and treatment of hypertension in adults and children. Canadian
Journal of Cardiology, 34(5), 506-525.
8. Williams, B., Mancia, G., Spiering, W., Agabiti Rosei, E., Azizi, M., Burnier, M., ... &
Desormais, I. (2018). 2018 ESC/ESH Guidelines for the management of arterial hypertension: The Task Force for the management of arterial hypertension of the
European Society of Cardiology (ESC) and the European Society of Hypertension (ESH).
European heart journal, 39(33), 3021-3104.9. Whelton, P. K., Carey, R. M., Aronow, W. S., Casey, D. E., Collins, K. J., Dennison
Himmelfarb, C., ... & Wright, J. T. (2018). 2017
ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA guideline for the
prevention, detection, evaluation, and management of high blood pressure in adults: a
report of the American College of Cardiology/American Heart Association Task Force
on Clinical Practice Guidelines. Journal of the American College of Cardiology, 71(19),
e127-e248.
10. Patnode CD, Evans CV, Senger CA, Redmond N, Lin JS. Behavioral counseling to
promote a healthful diet and physical activity for cardiovascular disease prevention in
adults without known cardiovascular disease risk factors: updated evidence report and
systematic review for the US Preventive Services Task Force. JAMA 2017;318:175–193.
11. Schwingshackl L, Chaimani A, Schwedhelm C, Toledo E, Pu¨nsch M, Hoffmann G,
Boeing H. Comparative effects of different dietary approaches on blood pressure in
hypertensive and pre-hypertensive patients: a systematic review and network metaanalysis.
Crit Rev Food Sci Nutr 2019;59:2674–2687.
12. Pickering TG, Miller NH, Ogedegbe G, Krakoff LR, Artinian NT, Goff D; American
Heart Association; American Society of Hypertension; Preventive Cardiovascular Nurses
Association. Call to action on use and reimbursement for home blood pressure
monitoring: a joint scientific statement from the American heart association, American
society of hypertension, and preventive cardiovascular nurses association. J Cardiovasc
Nurs. 2008;23:299–323. doi: 10.1097/01.JCN.0000317429.98844.04
13. Elliott WJ. What factors contribute to the inadequate control of elevated blood pressure?
J Clin Hypertens (Greenwich). 2008;10(1 suppl 1):20–26.14. Burnier M, Egan BM. Adherence in hypertension. Circ Res. 2019;124:1124–1140. doi:
10.1161/CIRCRESAHA.118.313220
15. Leon N, Surender R, Bobrow K, Muller J, Farmer A. Improving treatment adherence for
blood pressure lowering via mobile phone SMS messages in South Africa: a qualitative
evaluation of the SMS-text Adherence SuppoRt (StAR) trial. BMC Fam Pract.
2015;16:80. doi: 10.1186/s12875-015-0289-7
16. Kamal AK, Shaikh Q, Pasha O, et al. A randomized controlled behavioral intervention
trial to improve medication adherence in adult stroke patients with prescription tailored
Short Messaging Service (SMS)-SMS4Stroke study. BMC Neurol. 2015;15:212. doi:
10.1186/s12883-015-0471-5
17. Petrella RJ, Stuckey MI, Shapiro S, Gill DP. Mobile health, exercise and metabolic risk:
a randomized controlled trial. BMC Public Health. 2014;14:1082. doi: 10.1186/1471-
2458-14-1082
18. Wang W, Li D, Shi W, Zhang J, Sui J. Research on the application of mobile health D2C
model in the management of hypertensive disease in grassroots community. Chin J Gen
Practic. 2017;7:1194–1197.
19. Rehman H, Kamal AK, Morris PB, Sayani S, Merchant AT, Virani SS. Mobile health
(mHealth) technology for the management of hypertension and hyperlipidemia: slow
start but loads of potential. Curr Atheroscler Rep. 2017; 19(3):12.
20. The penetration rate of mobile phone. Iran: Irna. Cited 2020 10 Jan.
21. Global smartphone penetration data. Accessed 10 Jan 2020.
22. Diez-Canseco F, Zavala-Loayza JA, Beratarrechea A, Kanter R, Ramirez-Zea M,
Rubinstein A, Martinez H, Miranda JJ. Design and multi-country validation of text
messages for an mHealth intervention for primary prevention of progression to
hypertension in Latin America. JMIR Mhealth Uhealth. 2015; 3(1):e19.23. Estrin, D., and Sim, I. 2010. “Open mHealth Architecture: An Engine for Health Care
Innovation.” Science (330:6005), pp.759-76
24. Manyika, J., Chui, M., Bughin, J., Dobbs, R., Bisson, P., and Marrs, A. 2013.
“Disruptive Technologies: Advances That Will Transform Life, Business, and the Global
Economy,” Report, McKinsey Global Institute.
25. Steinhubl, S. R., Muse, E. D. & Topol, E. J. Can mobile health technologies transform
health care? J. Am. Med. Assoc. 310, 2395–2396 (2013).
26. de Jongh, T., Gurol-Urganci, I., Vodopivec-Jamsek, V., Car, J. & Atun, R. Mobile phone
messaging for facilitating self-management of long-term illnesses. Cochrane Database
Syst. Rev. 12, CD007459 (2012).
27. Bonoto, B. C. et al. Efficacy of mobile apps to support the care of patients with diabetes
mellitus: a systematic review and meta-analysis of randomized controlled trials. JMIR
MHealth UHealth 5, e4 (2017).
28. Widmer, R. J. et al. Digital health interventions for the prevention of cardiovascular
disease: a systematic review and meta-analysis. Mayo Clin. Proc. 90, 469–480 (2015).
29. Ambrosius, Walter T, Kaycee M Sink, Capri G Foy, Dan R Berlowitz, Alfred K Cheung,
William C Cushman, Lawrence J Fine, et al. "The Design and Rationale of a Multicenter
Clinical Trial Comparing Two Strategies for Control of Systolic Blood Pressure: The
Systolic Blood Pressure Intervention Trial (Sprint)." Clinical Trials 11, no. 5 (2014):
532-46.
30. National Heart, Lung, and Blood Institute. "Landmark Nih Study Shows Intensive Blood
Pressure Management May Save Lives." Press release 11 (2015).
31. Whelton, Paul K, Robert M Carey, Wilbert S Aronow, Donald E Casey, Karen J Collins,
Cheryl Dennison Himmelfarb, Sondra M DePalma, et al. "2017 Acc/Aha/
Aapa/Abc/Acpm/Ags/Apha/Ash/Aspc/Nma/Pcna Guideline for the Prevention,Detection, Evaluation, and Management of High Blood Pressure in Adults: A Report of
the American College of Cardiology/American Heart Association Task Force on Clinical
Practice Guidelines." Journal of the American College of Cardiology 71, no. 19 (2018):
e127-e248.
32. Patel, Pragna, Pedro Ordunez, Donald DiPette, Maria Cristina Escobar, Trevor Hassell,
Fernando Wyss, Anselm Hennis, et al. "Improved Blood Pressure Control to Reduce
Cardiovascular Disease Morbidity and Mortality: The Standardized Hypertension
Treatment and Prevention Project." The Journal of Clinical Hypertension 18, no. 12
(2016): 1284-94.
33. Yue Dai, YaliWang, Yanxia Xie, Jia Zheng, Rongrong Guo, Zhaoqing Sun, Liying
Xing , Xingang Zhang, Yingxian Sun , and Liqiang Zheng, “Short-Term and Long-Term
Blood Pressure Changes and the Risk of All-Cause and Cardiovascular Mortality”
BioMed Research International (2019)
34. Anindya Ghose, Xitong Guo, Beibei Li, Yuanyuan Dang, “Empowering Patients Using
Smart Mobile Health Platforms: Evidence From a Randomized Field Experiment” MIS
Quarterly Vol. 46 No. 1 pp. 151-191 / March (2022)
35. George Stergiou, Anastasios Kollias, Gianfranco Parati, Eoin O’Brien, “The Weak
Cornerstone of Hypertension Diagnosis” Office Blood Pressure Measurement (2023)
36. Elisabete Pinto “Blood pressure and aging” National Library of Medicine (2007)
指導教授 陳炫碩(Shiuann-Shuoh Chen) 審核日期 2024-7-19
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明