物聯智慧引導多元性運動介入對城鄉高齡者全人健康指標促進成效之研究

Abstract

臺灣正面臨人口結構迅速老化的嚴重衝擊，65歲以上的高齡人口數正以驚人的速度向上攀升，高齡化議題已受到我國相關單位高度重視。科技進步帶動智慧產業普及發展，在人口高齡化與生活智慧化的兩大未來趨勢下，透過智慧科技進行健康促進，改善高齡者健康是值得被探討的議題。本研究旨在探討物聯智慧引導多元性運動介入對於城鄉高齡者功能性體適能及全人健康指標之促進成效，以物聯智慧科技結合多元性運動的介入模式來實現智慧老化之理想。本研究根據縣市型態及老化指數將臺北市定義為城市地區，將嘉義縣定義為鄉村地區，並以立意抽樣選取臺北市及嘉義縣65歲以上之高齡者，將其分為T1組與T1+T2組，有效樣本數為129人，兩地區的T1+T2組進行12週物聯智慧引導多元性運動介入，T1組僅進行12週一般多元性運動介入，兩組別之運動介入為每週2次，每次2小時，並分別在第0週及第13週進行功能性體適能、生活品質問卷、憂鬱症量表與極早期失智症量表的前、後測。統計分析方法以描述性統計、卡方檢定、成對樣本t檢定、廣義預估方程式、皮爾森積差相關及多元線性迴歸分析，探討12週不同類型的運動介入後，功能性體適能及全人健康指標之差異情形及促進成效，並進一步探究功能性體適能與全人健康指標之相關性。結果發現：(一) 高齡者的教育程度及身體質量指數存在城鄉差異情形；(二) 不同類型的運動介入皆能有效促進城鄉高齡者的功能性體適能與全人健康指標；(三) 物聯智慧引導多元性運動介入對於部分功能性體適能及全人健康指標之促進成效優於一般多元性運動介入；(四) 智慧運動介入後的功能性體適能可以有效預測全人健康指標。建議未來進行高齡智慧健康促進應考量地區特性，進一步改善特定功能性體適能項目之表現以達到提升全人健康指標之目的。Taiwan is facing the severe impact of a rapidly aging population structure. The number of senior citizens over 65 years old is rising alarmingly. The issue of aging has become a major focus for relevant domestic units in our country. Technological progress has driven the popularization and development of smart industries. Amidst the twin trends of the aging population and smart living, the intersection of smart technology and elderly health demands attention. This study investigated the impact of the multi-component exercise intervention by IoT intelligence on senior fitness test and holistic health index among urban and rural elderly populations. It employed IoT smart technology and multi-component exercise intervention models to achieve the ideal of smart aging. This study classified Taipei City as an urban area and Chiayi County as a rural area based on county/city type and aging index. Elderly residents aged 65+ in Taipei City and Chiayi County were purposively sampled and divided into T1 and T1+T2 groups, the valid sample number was 129 people. The T1+T2 group in the two regions underwent 12 weeks of the multi-component exercise intervention by IoT intelligence intervention. The T1 group only underwent 12 weeks of the normal multi-component exercise intervention. The exercise intervention of the two groups was 2 times a week, 2 hours each time, and pre-and post-tests of Senior fitness test, Quality of life questionnaire, Geriatric depression scale and Ascertain dementia 8 scale were conducted at weeks 0 and 13 respectively. Statistical analysis methods used Descriptive statistics, Paired-sample t-test, Generalized estimating equation, Pearson’s product moment correlation coefficient and Multiple regression analysis to explore senior fitness test and holistic health index after 12 weeks of different types of exercise intervention. The promotion effects of T1+T2 group further explored the correlation between senior fitness test and holistic health index. This study found: (i) Differences were found between urban and rural areas in the education level and body mass index of the elderly; (ii) Different types of exercise intervention could effectively promote the senior fitness test and holistic health index of the elderly in urban and rural areas; (iii) The multi-component exercise intervention by IoT intelligence intervention was better than the normal multi-component exercise intervention in promoting some senior fitness test itemss and holistic health index; (iv) Senior fitness test after smart exercise intervention could effectively predict holistic health index. It was recommended that future smart health promotion for the elderly should consider regional characteristics to further improve the performance of specific functional fitness items as holistic health index.