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標題: | 延伸TRAM模式以預測飲食與健康應用軟體的使用意願: 健康意識的重要性 Extending TRAM Model to Predict Usage Intention of the Dietary and Fitness Apps: Does Health Consciousness Matter? |
作者: | Mei-Fang Chen 陳美芳 |
指導教授: | 林能白 |
關鍵字: | 科技準備接受模式,飲食與健康應用軟體,健康意識, Technology Readiness Acceptance Model (TRAM),Dietary and Fitness apps,Health Consciousness, |
出版年 : | 2017 |
學位: | 博士 |
摘要: | 隨著過重以及肥胖的比率逐年增加,公共衛生研究人員致力於利用新科技發展創新的方法以幫助人們達到健康的體重。行動科技與健康促進應用軟體(apps)提供一個即時蒐集、傳遞、評估、客製化回饋以及在適時提供建議以有效改善人們健康自我管理以及健康行為改變的機會。使用行動科技以及行動健康應用軟體的趨勢,吸引了實務工作者、研究者以及政策制定者的注意。儘管健康相關的應用軟體(apps) 在健康自我管理介入上是相對有效果的工具,但對於究竟是甚麼因素影響個人是否會使用這類健康相關的應用軟體的所知仍相當有限。
理論在公共衛生介入以及研究上扮演一個非常重要的角色。先前的研究以科技接受模式(Technology Acceptance Model, TAM)或是科技準備接受模式(Technology Readiness Acceptance Model (TRAM)為基礎,解釋人們之所以會使用飲食與健康應用軟體(apps)的意願,但卻未能考量健康意識(health consciousness)這個認知因素。本研究以科技準備接受模式(Technology Readiness Acceptance Model, TRAM)為基礎,提出一個包括健康意識在內的延伸科技準備接受模式以補足先前研究未將認知因素納入的缺口並改善影響個人對飲食與健康應用軟體(apps)使用意願的預測能力。 本研究一共在台灣蒐集了994份網路自陳式問卷供研究分析之用。線性結構模式分析結果顯示將健康意識納入的延伸科技準備接受模式的預測能力比原來的科技準備接受模式好。科技準備的促進因素,樂觀與創新,對於知覺飲食與健康應用軟體(apps)的易用性有正面影響;樂觀對於知覺飲食與健康應用軟體(apps)的有用性有正面影響。科技準備的抑制因素,不舒服,對於知覺飲食與健康應用軟體(apps)的易用性有負面影響。科技接受模式中的知覺飲食與健康應用軟體(apps)的易用性與有用性對於飲食與健康應用軟體(apps)的態度有正面影響;此一態度會進而影響對於飲食與健康應用軟體(apps)的使用意願。 本研究結果提供公共衛生部門、應用軟體開發業者以及相關行銷推廣人員一些管理意涵與建議。 With increasing rates of overweight and obesity, public health researchers are engaging in developing innovative method by new technology to help people to achieve healthy weights. Mobile technology and health promotion apps provide a good opportunity to collect and deliver people's individualized health information as well as real-time assessment, tailored feedback, and advice at the appropriate time to improve self-management and health behavior change over time. A growing trend for the use of mobile technology and mHealth has attracted the attention of practitioners, researchers and policymakers globally. Despite that health-related apps are relatively effective tools in health self-management interventions, a better understanding of what factors determine individuals to use such health-related apps are still limited. Theory plays a critical role in public health interventions and research. Previous studies adopted the Technology Acceptance Model (TAM) or Technology Readiness Acceptance Model (TRAM) independently to explain people's intention to use the mhealth apps and without taking into account people's cognition factor, health consciousness. This study proposed an extended research framework of TRAM which includes an individual’s health consciousness to fill the gap of previous studies and to improve the prediction power of an individual's usage intention of the dietary and fitness apps. A total of 994 participants who completed self-reported online questionnaire surveys in Taiwan. The results of structural equation modeling (SEM) indicated that the prediction power of the proposed extended TRAM model which includes health consciousness has better prediction power than that of the original TRAM model. The drivers of an individual's technology readiness, optimism and innovativeness, have positive impacts on his or her perceived ease of using the dietary and fitness apps. An individual's optimism also has positive impact on his or her perceived usefulness of using the dietary and fitness apps. One of the inhibitors of an individual's technology readiness, discomfort, has negative impact on his or her perceived ease of using the dietary and fitness apps. The components of TAM model, an individual's perceived ease of usefulness of using the dietary and fitness apps, has positive contributions on his or her attitude toward using the dietary and fitness apps, which in turn has positive contribution to his or her intention to use the dietary and fitness apps. Based on the study results, this study can provide some managerial implications and suggestions for the public health sector, the dietary and fitness developers and the promotion marketers. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/21037 |
DOI: | 10.6342/NTU201700172 |
全文授權: | 未授權 |
顯示於系所單位: | 健康政策與管理研究所 |
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