移动康复评定在脊髓损伤患者水中康复评定中的应用
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摘要
目的探索移动医疗技术在脊髓损伤患者水中康复评定中的应用价值。方法 2017年11月至2018年4月,接受水中运动治疗的脊髓损伤患者72例随机分为对照组(n=36)和实验组(n=36),采用Alyn水中适应性评定量表进行评定。对照组采用纸质评定法,实验组采用移动应用程序法,评定2次。记录评定耗时和查询评定结果耗时,统计算分正确率,计算两次评分的变化值和变化率。结果实验组评定耗时和查询评定结果耗时均显著小于对照组(t> 10.492, P <0.001),百分制总分、总分变化率、百分制总分变化率的正确率均高于对照组(χ2> 4.545, P <0.05)。结论与传统纸质量表评定法相比,基于移动技术的电子化康复评定有助于提高工作效率。
Objective To explore the application of mobile medical technology in aquatic rehabilitation assessment for patients with spinal cord injury.Methods From November, 2017 to April, 2018, 72 patients with spinal cord injury accepted aquatic exercise were randomly divided into control group(n = 36) and experimental group(n = 36). All the patients were assessed with Water Orientation Assessment of Alyn(WOTA), using paper scale for the control group, mobile scale for the experimental group, twice. The time for assessment and for recall was recorded. The accuracy of results and variety between assessment was compared.Results The time for assessment and for recall was less in the experimental group than in the control group(t > 10.492,P < 0.001), with more accuracy of standard total score, the variety of total score and standard total score(χ2>4.545, P < 0.05).Conclusion Compared with the paper-based assessment, the assessment based on mobile technology may improve work efficiency.
Objective To explore the application of mobile medical technology in aquatic rehabilitation assessment for patients with spinal cord injury.Methods From November, 2017 to April, 2018, 72 patients with spinal cord injury accepted aquatic exercise were randomly divided into control group(n = 36) and experimental group(n = 36). All the patients were assessed with Water Orientation Assessment of Alyn(WOTA), using paper scale for the control group, mobile scale for the experimental group, twice. The time for assessment and for recall was recorded. The accuracy of results and variety between assessment was compared.Results The time for assessment and for recall was less in the experimental group than in the control group(t > 10.492,P < 0.001), with more accuracy of standard total score, the variety of total score and standard total score(χ2>4.545, P < 0.05).Conclusion Compared with the paper-based assessment, the assessment based on mobile technology may improve work efficiency.
引文
[1]恽晓平.康复疗法评定学[M]. 2版.北京:华夏出版社, 2014.
[2]王玉龙.康复功能评定学[M]. 2版.北京:人民卫生出版社,2017.
[3]李小华.移动医疗技术与应用[M].北京:人民卫生出版社,2015.
[4]王志威,沈丹彤,黄怀.移动医疗在神经康复中的应用进展[J].中华物理医学与康复杂志, 2016, 38(8):634-637.
[5]杨帅,于哲一,计海彪,等.移动医疗APP在髋关节置换术后社区康复训练中的作用[J].中国康复医学杂志, 2018, 33(2):215-217.
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[12] Nussbaum R, Kelly C, Quinby E, et al. A systematic review of mobile health applications in rehabilitation[J]. Arch Phys Med Rehabil, 2019, 100(1):115-127.
[13]崔尧,李建军,丛芳,等.一种基于浏览器/服务器结构的综合康复信息系统的设计与初步实现[J].中国康复理论与实践,2015, 21(1):114-116.
[14]中国康复研究中心,中国康复科学所,李建军,等.基于An‐droid平台的Alyn水中适应性评价软件:2016SR078358[CP].2015-12-15.
[15] Dale P, Whittaker L, Dixon R, et al. Acceptability of a mo‐bile health exercise-based cardiac rehabilitation intervention:a randomized trial[J]. J Cardiopulm Rehabil, 2015, 35(5):312-319.
[16] Lee C H, Yoon H J. Medical big data:promise and challeng‐es[J]. Kidney Res Clin Pract, 2017, 36(1):3-11.
[17]崔尧,丛芳,李建军,等. Alyn水中适应性测试量表2的汉化及在脊髓损伤患者中的信度与效度[J].中国康复理论与实践, 2018, 24(11):1302-1308.
[18]刘文韬,王仁佐.医疗大数据建设现状及其应用发展对策研究[J].中国发展, 2018, 18(3):80-83.
[19] Topol E.颠覆医疗:大数据时代的个人健康革命[M].张南,魏巍,何雨师,等译.北京:电子工业出版社, 2014.
[20] Tirosh R, Katz-Leurer M, Getz M D. Halliwick-based aquat‐ic assessments:reliability and validity[J]. Int J Aquatic Res Educ, 2008, 2(3):224-236.
[21]崔尧,丛芳,金龙. Halliwick理念及其在水疗康复中的应用[J].中国康复理论与实践, 2013, 19(3):239-245.
[22]崔尧,丛芳,金龙. Halliwick理念[M]//黄东峰,李建新,王宁华.综合水疗学.北京:金盾出版社, 2015:62-88.
[23]金龙,丛芳,崔尧,等. Alyn水中适应性测试量表1的汉化及信度与效度研究[J].中国康复理论与实践, 2015, 21(5):539-543.
[24]李建军.脊髓损伤神经学分类国际标准参考手册[M].北京:人民卫生出版社, 2008.
[25]美国脊髓损伤协会.脊髓损伤神经学分类国际标准(2011年修订)[J].李建军,王方永,译.中国康复理论与实践, 2011,17(10):963-972.
[26]罗伯特·卡巴科弗. R语言实战[M]. 2版.北京:人民邮电出版社, 2016.
[27] R Core Team. R:a language and environment for statistical computing. R Foundation for Statistical Computing[DB/OL].(2018-02-20). https://www.R-project.org/.
[28]张铁军,陈兴林,刘振球. R语言与医学统计图形[M].北京:人民卫生出版社, 2018.
[29]马斌荣.医学科研中的统计方法[M]. 4版.北京:科学出版社, 2012.
[30] Stütz T, Emsenhuber G, Huber D, et al. Mobile phone-sup‐ported physiotherapy for frozen shoulder:feasibility assess‐ment based on a usability study[J]. JMIR Rehabil Assist Tech‐nol, 2017, 4(2):e6.
[31] Thirumalai M, Rimmer J H, Johnson G, et al. TEAMS(TeleExercise and Multiple Sclerosis), a Tailored Telerehabilitation mHealth App:participant-centered development and usability study[J]. JMIR Mhealth Uhealth, 2018, 6(5):e10181.
[32]张文豪,李建军,高峰,等.可穿戴技术在康复医学领域中的研究进展[J].中国康复理论与实践, 2017, 23(7):792-795.
[2]王玉龙.康复功能评定学[M]. 2版.北京:人民卫生出版社,2017.
[3]李小华.移动医疗技术与应用[M].北京:人民卫生出版社,2015.
[4]王志威,沈丹彤,黄怀.移动医疗在神经康复中的应用进展[J].中华物理医学与康复杂志, 2016, 38(8):634-637.
[5]杨帅,于哲一,计海彪,等.移动医疗APP在髋关节置换术后社区康复训练中的作用[J].中国康复医学杂志, 2018, 33(2):215-217.
[6]杜新峰,章祖华.移动医疗发展的现状与前景[J].医疗卫生装备, 2015, 36(12):113-115.
[7]姜英姿.移动医疗APP在医疗服务中的应用[J].电子技术与软件工程, 2016, 5(20):78.
[8] Gallagher R, Roach K, Sadler L, et al. Mobile technology use across age groups in patients eligible for cardiac rehabilitation:survey study[J]. JMIR Mhealth Uhealth, 2017, 5(10):e161.
[9] Amira R. The promise, growth, and reality of mobile health—another data-free zone[J]. New Engl J Med, 2017, 377(21):2010-2011.
[10] Constantinescu G, Loewen I, King B, et al. Designing a mo‐bile health App for patients with dysphagia following head and neck cancer:a qualitative study[J]. JMIR Rehabil Assist Tech‐nol, 2017, 4(1):e3.
[11] Jones M, Morris J, Deruyter F. Mobile healthcare and people with disabilities:current state and future needs[J]. Int J Envi‐ron Res Public Health, 2018, 15(3):E515.
[12] Nussbaum R, Kelly C, Quinby E, et al. A systematic review of mobile health applications in rehabilitation[J]. Arch Phys Med Rehabil, 2019, 100(1):115-127.
[13]崔尧,李建军,丛芳,等.一种基于浏览器/服务器结构的综合康复信息系统的设计与初步实现[J].中国康复理论与实践,2015, 21(1):114-116.
[14]中国康复研究中心,中国康复科学所,李建军,等.基于An‐droid平台的Alyn水中适应性评价软件:2016SR078358[CP].2015-12-15.
[15] Dale P, Whittaker L, Dixon R, et al. Acceptability of a mo‐bile health exercise-based cardiac rehabilitation intervention:a randomized trial[J]. J Cardiopulm Rehabil, 2015, 35(5):312-319.
[16] Lee C H, Yoon H J. Medical big data:promise and challeng‐es[J]. Kidney Res Clin Pract, 2017, 36(1):3-11.
[17]崔尧,丛芳,李建军,等. Alyn水中适应性测试量表2的汉化及在脊髓损伤患者中的信度与效度[J].中国康复理论与实践, 2018, 24(11):1302-1308.
[18]刘文韬,王仁佐.医疗大数据建设现状及其应用发展对策研究[J].中国发展, 2018, 18(3):80-83.
[19] Topol E.颠覆医疗:大数据时代的个人健康革命[M].张南,魏巍,何雨师,等译.北京:电子工业出版社, 2014.
[20] Tirosh R, Katz-Leurer M, Getz M D. Halliwick-based aquat‐ic assessments:reliability and validity[J]. Int J Aquatic Res Educ, 2008, 2(3):224-236.
[21]崔尧,丛芳,金龙. Halliwick理念及其在水疗康复中的应用[J].中国康复理论与实践, 2013, 19(3):239-245.
[22]崔尧,丛芳,金龙. Halliwick理念[M]//黄东峰,李建新,王宁华.综合水疗学.北京:金盾出版社, 2015:62-88.
[23]金龙,丛芳,崔尧,等. Alyn水中适应性测试量表1的汉化及信度与效度研究[J].中国康复理论与实践, 2015, 21(5):539-543.
[24]李建军.脊髓损伤神经学分类国际标准参考手册[M].北京:人民卫生出版社, 2008.
[25]美国脊髓损伤协会.脊髓损伤神经学分类国际标准(2011年修订)[J].李建军,王方永,译.中国康复理论与实践, 2011,17(10):963-972.
[26]罗伯特·卡巴科弗. R语言实战[M]. 2版.北京:人民邮电出版社, 2016.
[27] R Core Team. R:a language and environment for statistical computing. R Foundation for Statistical Computing[DB/OL].(2018-02-20). https://www.R-project.org/.
[28]张铁军,陈兴林,刘振球. R语言与医学统计图形[M].北京:人民卫生出版社, 2018.
[29]马斌荣.医学科研中的统计方法[M]. 4版.北京:科学出版社, 2012.
[30] Stütz T, Emsenhuber G, Huber D, et al. Mobile phone-sup‐ported physiotherapy for frozen shoulder:feasibility assess‐ment based on a usability study[J]. JMIR Rehabil Assist Tech‐nol, 2017, 4(2):e6.
[31] Thirumalai M, Rimmer J H, Johnson G, et al. TEAMS(TeleExercise and Multiple Sclerosis), a Tailored Telerehabilitation mHealth App:participant-centered development and usability study[J]. JMIR Mhealth Uhealth, 2018, 6(5):e10181.
[32]张文豪,李建军,高峰,等.可穿戴技术在康复医学领域中的研究进展[J].中国康复理论与实践, 2017, 23(7):792-795.