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研究生:張竣維
研究生(外文):Chun-Wei Chang
論文名稱:運用conjoint analysis法建置健康照護用Application之評估模式
論文名稱(外文):The Use of Conjoint Analysis to Construct Healthcare Application Assessment Model
指導教授:呂學毅呂學毅引用關係
指導教授(外文):Hsueh-Yi, Lu
學位類別:碩士
校院名稱:國立雲林科技大學
系所名稱:工業工程與管理研究所碩士班
學門:工程學門
學類:工業工程學類
論文種類:學術論文
論文出版年:2013
畢業學年度:101
語文別:中文
論文頁數:113
中文關鍵詞:聯合分析法行動醫療照護健康照護App
外文關鍵詞:Healthcare AppsmhealthConjoint analysis
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由於老年人口比例增長,導致醫療照護需求增加,加上智慧型行動裝置App近年來蓬勃發展,許多健康照護用App類型如雨後春筍般產生,用以輔助醫療照護、疾病情監控、或健康管理,以促進民眾健康及減少醫療資源使用,但快速發展的背後,隱藏著許多對民眾使用上的風險及有害內容。使用者可能因不了解誤用後果而造成傷害。因此,應有一套評估模式來幫助民眾、醫療院所、或政府相關部門進行醫療照護用App的評估與過濾。有鑑於此,本研究之目的將探討如何衡量一個針對慢性病患健康照護用App的好壞,運用Conjoint Analysis建置一套多屬性評估模型。
本研究的評估模式建置分為2個階段,第一階段為找尋評估慢性病健康照護App時會影響受測者偏好的屬性與水準。第二階段為設定屬性水準之權重,分為兩個步驟,第一步驟為問卷設計,了解每位受測者的偏好結構;第二步驟為資料分析,將受測者評估過之問卷回收並運用統計分析方法求得每個屬性水準的相對重要性。
研究結果發現『醫療資訊紀錄與展示』、『疾病相關提醒與警示』以及『與醫護人員溝通』這3項功能對於受測者在評估健康照護App時具有顯著影響。此外在付費意願上,本研究發現教育程度與年齡皆對於付費意願有相關性;最後模型驗證的結果發現與模型評估的結果與受測者評估的結果具有相關性。
Due to the growth in the proportion of the elderly population, the demand for medical care increases rapidly. Also, the appearance of healthcare applications not only makes an opportunity to assist people in health care, health monitoring, and self-management but also promote public health and reduce the use of medical resources. However, as the rapid growth of the health-related app services, there could be involved some risks or harmful content in the applications. People may get harm without the understanding of misuse. In order to avoid the harmful content and risks, a healthcare App assessment model is necessary to help people, medical institutes, or the relevant government department in filtering the use of healthcare Apps. Therefore, the purpose of this study is to construct a healthcare App assessment model with conjoint analysis.
The process of constructing a healthcare Apps assessment model will divide into three stages, the first stage is to find the attributes and levels which affect people’s prefer in evaluating the healthcare Apps as well as define the success definition about a healthcare App. The second stage is setting the weight of the levels. This stage will separates in two parts. The first part is about the design of the survey. The second part is the data analysis.


The results indicate that the App functions “Medical information record and display”, “Disease-related alert and reminder” and “Communication with medical specialists” will affect the evaluation of Apps. Furthermore, the result shows that the level of education and age are related to the will of payment. The result of model evaluation indicates that result of model is statistical related with the evaluation of people.
摘要 ………………………………………………………………………………………………………………I
Abstract …………………………………………………………………………………………………………….II
目錄 ……………………………………………………………………………………………………………IV
圖目錄 ……………………………………………………………………………………………………………VI
表目錄 ……………………………………………………………………………………………………………VII
第一章、 緒論 1
1.1 研究背景 1
1.2 研究動機 3
1.3 研究目的 5
1.4 研究範圍 6
第二章、 文獻探討 7
2.1 行動裝置 7
2.2 應用程式 11
2.3 Mobile Health (行動健康照護) 11
2.2.1 健康照護用App之定義與規範 13
2.2.2 慢性病人的健康管理APP 16
2.3 A Theory of Complex Decision Making(複雜決策理論) 17
2.4 Conjoint Analysis 19
2.4.1 conjoint analysis的原理以及目的 20
2.4.2 conjoint analysis模式產生之步驟 22
第三章、 研究方法 30
3.1 研究流程 30
3.2 研究方法說明 31
3.3 研究架構 31
3.4 研究進行步驟 32
3.5 第一階段:建立模型內屬性 34
3.5.1 決定屬性與水準: 34
3.6 第二階段: 設定屬性水準權重 41
3.6.1 第一步驟:問卷設計 41
3.6.2 第二步驟:資料分析 52
3.7 第三階段: 模型驗證 55
第四章、 結果 57
4.1 人口統計變項 57
4.2 聯合分析結果 59
4.2.1 全樣本分析 59
4.2.2 性別 60
4.2.3 年齡 62
4.2.4 有無慢性病 63
4.2.5 填寫者類型 65
4.2.6 有無醫療背景 67
4.2.7 教育程度 68
4.2.8 醫療App使用經驗 70
4.3 卡方分析結果 73
4.3.1 付費意願-年齡 73
4.3.2 付費意願-性別 74
4.3.3 付費意願-月收入 75
4.3.4 付費意願-每日智慧型手機使用時間 76
4.3.5 付費意願-醫療APP使用經驗 78
4.3.6 付費意願-教育程度 79
4.4 模式驗證 81
第五章、 結果討論與建議 83
5.1 全樣本 83
5.2 性別 84
5.3 年齡 84
5.4 教育程度 85
5.5 填寫者類型 86
5.6 醫療背景差異 87
5.7 醫療App使用經驗 87
5.8 醫療App付費意願 89
5.9 填寫者是否有慢性病 90
5.10 人口統計變項與付費意願相關討論 91
5.11 模式驗證結果討論 92
5.12 未來建議 92
5.13 研究限制 93
參考文獻 ……………………………………………………………………………………………………………94
附錄 研究問卷 99
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