隨著科技發展速度加快以及人口老化現象的顯著，與「高齡者科技產品使用」相關的議題逐漸地被廣泛討論。其中，選單導引任務（Navigation task）為高齡者在手機使用過程中所面臨的主要困難之一。由於認知功能退化以及缺乏手機使用相關知識，高齡者的導引任務績效往往比年輕使用者來的更差。過去的研究曾以使用者心智模型（Mental model）與實體設計間差異的觀點探討這個問題。本研究也採用此觀點解釋高齡者的導引任務困難，並嘗試以一致性模型（Coherence model）與心理尺度化方法（Psychological scaling）縮短選單結構與心智模型間的差異，以此解決導引任務績效問題。
研究共分為四個階段。首先，邀請30位台北與新竹地區65歲以上高齡者進行訪談，找出目前高齡者需要的功能。研究結果顯示，高齡者需要能夠提升生活中安全感以及輔助生理與認知退化的手機功能。
　　接著，邀請13位台北與新竹地區65歲以上的高齡非使用者進行功能相關性分類。受試者的分類結果經過階層式群集分析（Hierarchical clustering）後以樹狀圖（Dendrogram）呈現，而他們提供的分類理由則以親和圖（Affinity diagram）整理，成為選單命名依據。分類結果顯示，在高齡非使用者的心中，手機的功能可以分為兩個群集。第一個群集內有：電話號碼尋找、新增電話、刪除電話、未接電話以及快速鍵撥號，此群集代表與「電話相關」的功能；第二個群集內有：緊急求救、防盜追蹤、自動重新撥號、鈴聲音樂與音量調整、螢幕亮度調整以及時間與日期設定，而這個群集代表受試者過去未接觸過的「進階功能」。這個結果也顯示了高齡者認知的手機功能心理距離與實體選單配置並不相同。
　　最後，邀請16位高齡使用者及非使用者進行導引任務的績效測試及訪談。結果顯示，以一致性模型為基礎的選單可以使高齡者更準確地預測「某功能在哪一個子選單下」，但卻無法提升他們的操作時間。

With the accelerated technology innovation as well as increasing aging population, the discussion about older users’ technology adaptation has become more and more extensive. Among all of the difficulties, navigation problem on mobile phones hinders older users from adapting quickly and easily. Due to the elderly’s physical limitation and lack of mobile phone-related knowledge, their navigation performances are usually worse than younger users’. In this research, navigation difficulty was explained with the viewpoint of mental model, and solved with the concept of coherence model and psychological scaling.
There were four stages in the research. First of all, 30 older users were invited to a functional requirement investigation. The result shows that the elderly view the mobile phone as a device for elevating sense of safety. They also need functions assisting both physical and cognitive degeneration.
Then, 13 older people (without mobile phone using experience) were invited to conduct the functional card sorting. The result of card sorting was analyzed with hierarchical clustering. After sorting the card, participants were also required to provide their sorting criteria, and the criteria were summarized with affinity diagram to become the name of the submenu. The output dendrogram of hierarchical clustering shows that the mobile phone functions are devided into two clusters. They are functions with which the participants have not exposured and functions related to telephone use. These two clusters were named as advanced functions and phone-related functions respectively.
Finally, 16 older participants’ task completed rate, operation time and additional steps were measured on the original menu and the menu design based on coherence model. The result is that the menu design based on coherence model can make participants’ menu structure predicton more correct, but it has no influence on reducing the operation time.

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