未來研究建議

第五章結論與建議

第四節未來研究建議

統合分析方法論的發展，加上相應之統計分析軟體相繼問世，本研究得以系統化地回顧健康資訊尋求相關研究，釐清當前相關研究面臨之重大議題，彌平懸而未決之爭議，建立健康資訊尋求之一般性模型。基於研究過程及發現，本節提出以下建議供後續研究參酌。

一、納入不同統計量之文獻進行分析

本研究除了探討健康資訊尋求之重要預測因素，並期望能透過相關研究假設，建立健康資訊尋求之一般性模型，因此僅將提供各因素間之相關係數矩陣的研究文獻，納入本次統合分析之中。本研究在蒐集健康資訊尋求行為相關研究文獻的過程中，也發現相當數量之文獻是提供了勝算比（odds ratio）此一統計量，

若能經過適當的資料轉換過程，即可將不同原始統計量之相關文獻納入同一統合分析中，不僅可以涵蓋更廣泛之相關文獻，提升分析結果之強韌性，亦可能發現更多的預測因素。

二、依據樣本特性進行分群

由於多數研究文獻之受訪者樣本並未鎖定特定族群，以致於在進行編碼時，

僅能將這類文獻納入「未限定」之分組，造成調節變數分析之限制，即使分析結果呈現顯著，也無法進一步描述或推論。建議後續研究若能發展出適當的分類架構，進行研究文獻分組及組間差異考驗，不僅可發現更多的調節變數，亦有助於

探討及說明造成差異之成因。

三、探討情緒反應之預測效果的調節變數

情緒反應之預測效果量的變異不同質，本研究以來自樣本性質、文獻性質、

研究特色及研究方法等層面之變數進行調節效果分析，但各變數下之不同分組均未呈現明顯的組間差異。建議後續研究可結合不同統計量之相關文獻後，再以相同變數進行差異分析，或是探討其他關於研究情境之可能調節變數。

四、健康資訊尋求統合模型之延伸及擴展

本研究共探討了11 項健康資訊尋求行為之預測因素，但基於對健康資訊尋求一般性模型之認知，本研究僅將受訪者自陳式心理變項納入統合模型中。未來或可將本研究已探討的預測變項納入統合模型之建構，如媒體使用、知識素養、

患病經驗等；甚至是本研究未納入之人口統計變數或資訊尋求環境因素，如性別、教育程度、收入、控制源、社會支持或自我建構等，不僅能彰顯統合分析式結構方程模式在理論模型建構之效用與價值，亦能有效擴展一般性模型之可應用性。此外，具有明確健康資訊需求的人們，除為了避免新增之資訊反而徒增更多憂慮而迴避資訊，是否有其他因素可預測資訊迴避之產生，亟需更多相關研究投入此議題之探討，進一步瞭解各因素之預測機制及效果。

五、關注獲取健康資訊後的效益

本研究係以健康資訊尋求行為做為最終的反應變數，但資訊尋求後所導致的成效或結果，則受到公共衛生及醫療健康領域之重視，若能延伸探討資訊尋求後所帶來之具體成效，有助於瞭解人們與資訊互動後的結果。這些具體效益或可包含：(1)個人認知成效，例如增加知識、正確醫療決策等；(2)情感成效，如降低焦慮、恐懼、沮喪或增加希望，以及(3)行為成效，例如與專業人員討論、增加自我照護能力與接受醫療處置，以及產生有益健康之行為，甚至是改善生理健康情形

等。

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在文檔中健康資訊尋求之預測因素探討與認知模型建構：統合分析之取徑 (頁 171-200)

第五章 結論與建議

第四節 未來研究建議

第五章結論與建議

第四節未來研究建議