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  1. NTU Theses and Dissertations Repository
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請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/98471
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor詹瀅潔zh_TW
dc.contributor.advisorYing-Chieh Chanen
dc.contributor.author郭紀子zh_TW
dc.contributor.authorChi-Tz Kuoen
dc.date.accessioned2025-08-14T16:14:47Z-
dc.date.available2025-08-15-
dc.date.copyright2025-08-14-
dc.date.issued2025-
dc.date.submitted2025-08-01-
dc.identifier.citation中文部分
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/98471-
dc.description.abstract本研究旨在探討居住特徵對社區防疫韌性的影響,特別關注 COVID-19 大流行期間,不同類型社區在面對公共衛生危機時之應變與恢復能力。所謂社區防疫韌性,係指社區面對突發傳染病等公共衛生威脅時,其所展現之吸納衝擊、快速調適與恢復至原有功能之能力,與居民的防疫態度、防疫行為及社區治理密切相關。近年來,隨著都市化進程加速,集合式住宅等不同居住型態在規模、屋齡、房價、物業管理模式等物理與制度特性上展現差異,此外,居民社經地位、年齡、性別等人口特徵亦可能成為影響防疫行為的潛在因素。因此,本研究即試圖從居住特徵視角,系統性地分析社區防疫韌性的關鍵因素影響,並提出建議。
本研究設計中,自變項為「社區特徵」(如社區規模、社區運作模式、是否設有管理委員會或物業管理組織)、「居民特徵」(如性別、年齡、教育程度、職業狀態等),依變項則分別為居民防疫認知程度及實際防疫預防行為之執行情形。研究透過兩階段問卷調查,分別於臺灣與中國南京市進行實證資料蒐集:第一階段針對臺灣不同居住特徵,分析其與防疫認知及行為執行之相關性;第二階段則探討南京市相似變項對居民防疫行為之影響。
研究結果顯示,社區防疫韌性確實受到多重居住特徵交互影響。在臺灣地區方面,主要發現如下:1.小型社區對防疫教育與環境維護之重視程度,及防疫措施執行率均高於中、大型社區。2.中型社區對防疫設備之設置較為積極;中型社區若設有管委會,反而降低居民對防疫措施關注度。3.大型社區則在出入控管方面表現較為嚴謹。4.平時即具備防災意識與社區參與傾向之居民,在疫情期間更積極投入防疫行動。5.1995年之前建立的舊社區,居民對防疫措施重要性的認知高於新社區;然而新興社區在人員進出追蹤的機制上,則展現更高關注。在南京市方面,研究顯示:1.居民特徵(性別、年齡、教育程度、職業狀態)、社區特徵(規模、屋齡、房價、是否有物業管理)等二者皆顯著影響防疫行為。2.女性、年長者、在職者以及高教育程度者,於疫情期間防疫行動力較高。3.中小型、屋齡較新、房價較高之社區,居民會採取較為積極之防疫作為。4.有物業管理的社區,其居民展現出更佳的預防行為表現。5.整體而言,社區特徵的影響大於居民個人特徵因素,尤以房價與社區規模為最具解釋力的變項,其次為物業管理制度與社區屋齡。
綜合上述,本研究驗證了居住特徵對防疫韌性之影響力,進一步揭示社區環境與社會結構因素在公共衛生危機應對中的關鍵角色。研究成果由臺灣與中國南京市於疫情期間社區層級防疫表現之經驗資料,對於從「居住特徵」視角深入理解社區防疫韌性提供新穎實證。居住特徵既可能成為社區脆弱性來源,亦能透過制度設計與社區治理,轉化為具韌性的資源。故建議未來公共衛生政策應強化社區基層治理體系,並於都市規劃與建築設計中納入防疫韌性概念,同時發展多元化、因地制宜之社區互助與管理機制。從文獻蒐集比對過程看出,此研究為亞洲地區首度系統性探討居住特徵與防疫韌性關聯性之實證研究,具理論開創性與實務參考價值,惟仍建議未來可擴展至更多國家與地區進行跨文化、跨地區比較,並採用縱貫性長期追蹤研究法,以豐富全球社區防疫治理之知識體系。
zh_TW
dc.description.abstractThis study aims to investigate the impact of residential characteristics on community epidemic resilience, with a particular focus on the adaptive and recovery capacities of different types of communities in response to public health crises during the COVID-19 pandemic. Community epidemic resilience refers to a community’s ability to absorb shocks, rapidly adjust, and restore its original functions when facing sudden infectious disease threats. This capability is closely related to residents' epidemic prevention attitudes and behaviors, as well as community governance. In recent years, accelerated urbanization has led to variations in residential types such as collective housing, which differ in physical and institutional attributes including scale, building age, housing prices, and property management models. Additionally, residents’ socio-demographic characteristics, such as socioeconomic status, age, and gender, may serve as potential factors influencing epidemic prevention behaviors. Therefore, this study systematically analyzes key factors affecting community epidemic resilience from the perspective of residential characteristics and proposes relevant recommendations.
The study design includes independent variables of “community characteristics” (e.g., community size, operational model, presence of management committees or property management organizations) and “resident characteristics” (e.g., gender, age, education level, employment status). The dependent variables are residents’ levels of epidemic prevention awareness and the actual implementation of preventive behaviors. Empirical data were collected through a two-stage survey conducted in Taiwan and Nanjing, China: the first stage analyzed the correlation between community characteristics and epidemic awareness and behavior in various Taiwanese communities; the second stage examined the influence of similar variables on residents’ epidemic prevention behaviors in Nanjing.
Results indicate that community epidemic resilience is indeed influenced by the interaction of multiple residential characteristics. In Taiwan, major findings include: (1) small communities exhibit higher emphasis on epidemic education, environmental maintenance, and implementation rates of prevention measures compared to medium and large communities; (2) medium-sized communities are more proactive in installing prevention equipment, but the presence of a management committee in such communities reduces residents’ attention to prevention measures; (3) large communities demonstrate stricter access control; (4) residents with pre-existing disaster awareness and community participation tendencies engage more actively in epidemic prevention during the pandemic; (5) older communities established before 1995 have residents with higher awareness of the importance of prevention measures, whereas newer communities show greater concern for personnel access tracking mechanisms. In Nanjing, findings reveal: (1) both resident characteristics (gender, age, education, employment status) and community characteristics (size, building age, housing price, presence of property management) significantly affect epidemic prevention behaviors; (2) females, older adults, employed individuals, and those with higher education levels exhibit stronger preventive actions during the pandemic; (3) residents in small to medium-sized, newer, and higher-priced communities tend to adopt more proactive prevention measures; (4) communities with property management demonstrate better preventive behavior performance among residents; (5) overall, community characteristics exert a greater influence than individual resident factors, with housing price and community size being the most explanatory variables, followed by property management systems and building age.
In summary, this study validates the influence of residential characteristics on epidemic resilience and further elucidates the critical role of community environment and social structural factors in responding to public health emergencies. Drawing on empirical data from community-level epidemic prevention performance in Taiwan and Nanjing during the pandemic, the findings offer novel evidence for understanding community epidemic resilience from the perspective of residential characteristics. Residential characteristics may serve as sources of community vulnerability but can also be transformed into resilient assets through institutional design and community governance. Therefore, it is recommended that future public health policies strengthen grassroots community governance systems, incorporate epidemic resilience concepts into urban planning and architectural design, and develop diversified, locally tailored community mutual aid and management mechanisms. Based on literature review and comparative analysis, this study represents the first systematic empirical investigation of the relationship between residential characteristics and epidemic resilience in Asia, bearing theoretical innovation and practical significance. Nevertheless, future research is encouraged to expand cross-cultural and cross-regional comparative studies involving more countries and regions and to adopt longitudinal tracking methodologies to enrich the global knowledge base on community epidemic governance.
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dc.description.tableofcontents口試委員會審定書i
誌謝 ii
中文摘要 v
英文摘要 vii
第一章 緒論 1
1.1研究背景與動機1
1.2研究目的 3
1.3名詞界定 3
1.4研究流程及步驟 6

第二章 文獻回顧 10
2.1人口爆炸與城市化 10
2.2 居住集中化 11
2.3冠狀病毒「COVID-19」大流行 13
2.4「COVID-19」各國政府防疫指引 14
2.5「COVID-19」各國社區防疫策略 18
2.6社區與健康的關係 21
2.7居住特徵與健康的關係 22
2.8計畫行為理論(Theory of Planned Behavior,TPB) 29
2.9 韌性城市、韌性社區、社區防疫韌性 30
2.10本章小節 31

第三章 研究方法 33
3.1研究設計與研究架構 33
3.2研究工具 35
3.2.1問卷的效度檢定 38
3.2.2問卷的信度檢定 39
3.3 研究對象 46
3.4本章小結 50

第四章 資料處理與統計分析 51
4.1描述性統計方法 51
4.2推論性統計方法 52
4.3臺灣社區資料處理與分析 54
4.3.1臺灣社區居民防疫認知描述性統計 54
4.3.2影響臺灣社區居民防疫認知的推論性統計 56
4.3.3小結 63
4.4南京市社區資料處理與分析 69
4.4.1南京市社區防疫行為的描述性統計 69
4.4.2南京市社區居民COVID-19預防防疫行為調查 70
4.4.3南京市社區防疫行為的推論性統計 73
4.4.4 南京市人口和社區特徵對防疫行為的影響推論性統計 74
4.4.5小結 79
4.5 研究結果與討論 79
4.5.1第一階段研究,COVID-19疫情爆發初期--臺灣社區 79
4.5.2第二階段研究,結束「清零政策」,COVID-19疫情末期--南京市社區 84
4.6研究限制 86
4.6.1台灣地區 86
4.6.2南京市 87
4.6.3線上問卷調查方式 87
4.7本章小結 87
第五章 結論與建議 89
5.1研究結論 89
5.2後續研究建議 92
5.3研究貢獻 93
5.4本章小結 94
參考文獻 95
中文部分 95
英文部分 98
論文附錄 112
附錄一 集合住宅特性與防疫措施對居民防疫認知之影響問卷 112
附錄二 社區居民防疫行為調查問卷 124

圖次
圖1、研究流程圖 9
圖2、影響社區社區防疫韌性之研究架構 34
圖3、第一階段 問卷架構 36
圖4、第二階段 問卷架構 38
圖5、南京市行政區劃圖 49
圖6、南京市人口和社區特徵對社區防疫行為影響 75
圖7、多元回歸模型(Multiple Regression)、隨機森林(Random Forest)和支持向量機(SVM)的均方根誤差(RMSE)比較 78
圖8 、本研究社區防疫韌性相關概念圖 92
 
表次
表1、美國、歐洲和亞洲機構的 Covid-19 防疫指南計分 18
表2、COVID-19 期間世界各國社區防疫策略探討 19
表3、社區居住特徵與防疫策略之對應分析 28
表4、居住特徵視角下的社區防疫韌性研究專家內容效度名單 39
表5、社區防疫行為量表概念分類 40
表6、防疫措施重要性認知的信度分析結果 45
表7、社區居民防疫行為調查信度分析結果 45
表8、 全臺灣研究對象抽樣比例 47
表9、描述性統計方法 51
表10、推論性統計方法 54
表11、防疫措施重要性認知統計結果 55
表12、敘述性統計結果 55
表13、防疫重要性認知與社區規模差異配對T檢定 57
表14、各項自變數與防疫執行率(E ratio)相關係數表 58
表15、社區防疫行為迴歸結果 64
表16、不同規模社區的截尾回歸模型 66
表17、有無管理委員會的截斷回歸模型 68
表18、南京市受訪社區民眾人口學特徵 69
表19、南京市社區居民COVID-19預防行為調查 71
表20、逐步演算法中通過AIC選擇的解釋變數彙總 76
表21、臺灣及南京兩地研究比較 89
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dc.language.isozh_TW-
dc.subject居住特徵zh_TW
dc.subject社區防疫韌性zh_TW
dc.subject公共衛生zh_TW
dc.subject社區治理zh_TW
dc.subjectCOVID-19zh_TW
dc.subjectcommunity epidemic resilienceen
dc.subjectresidential characteristicsen
dc.subjectpublic healthen
dc.subjectcommunity governanceen
dc.subjectCOVID-19en
dc.title居住特徵視角下的社區防疫韌性zh_TW
dc.titleCommunity Epidemic Prevention Resilience from the Perspective of Residential Characteristicsen
dc.typeThesis-
dc.date.schoolyear113-2-
dc.description.degree博士-
dc.contributor.coadvisor陳柏翰zh_TW
dc.contributor.coadvisorPo-Han Chenen
dc.contributor.oralexamcommittee黃世孟;張陸滿;曾惠斌;王維志;楊亦東zh_TW
dc.contributor.oralexamcommitteeShi-meng Huang;Luh-Maan Chang;Hui-Ping Tserng;Wei-Chih Wang;Yi-Dong Yangen
dc.subject.keyword社區防疫韌性,居住特徵,COVID-19,社區治理,公共衛生,zh_TW
dc.subject.keywordcommunity epidemic resilience,residential characteristics,COVID-19,community governance,public health,en
dc.relation.page127-
dc.identifier.doi10.6342/NTU202502583-
dc.rights.note同意授權(全球公開)-
dc.date.accepted2025-08-04-
dc.contributor.author-college工學院-
dc.contributor.author-dept土木工程學系-
dc.date.embargo-lift2025-08-15-
顯示於系所單位:土木工程學系

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