2010-08-012024-05-13https://scholars.lib.ntu.edu.tw/handle/123456789/646362摘要：精確評量中風病患之行動功能，是病患行動功能復健與療效驗證之關鍵基礎，但常被臨床專家，甚至研究人員忽略。尤其目前多數行動功能評估工具，具有4 項缺點：(1)評估層面狹隘，未完整包含廣義的行動功能（如移位、爬、行走、跑、跳等）。(2)無法精確、快速地評量患者行動功能。(3)所得之分數為順序量尺而非等距量尺，無法有效量化病人行動功能。(4)欠缺驗證最小重要差異值(minimal important difference) 及建構行動功能階層 (functional mobility stages)，所得數據之臨床意義不易解釋。這些缺點，嚴重影響臨床效能與療效判斷。最新研究顯示：結合項目反應理論(item response theory)之Rasch 模式及電腦適性測驗(computerized adaptive test, CAT)嶄新測驗理論與施測技術，將可有效解決上述缺點。因為Rasch 模式可決定量表各項目所代表之功能高低排序暨產生具備等距量尺的分數，也可建構功能恢復階層；而配合CAT 技術則可提昇評量之效率且不犧牲評量精準度。故本研究將運用Rasch 模式及CAT 技術，發展「中風病人行動功能電腦適性測驗系統(A Computerized Adaptive testing system formeasuring Mobility impairment in Patients with Stroke, CAMPS)，以包含各種行動功能層面，且快速、精確評量中風病人之行動功能狀態及復原。本計畫預計以3 年6 階段完成CAMPS 之發展，含(1)建構CAMPS 項目（至少60 題）、(2)項目測試（300 位個案）、(3)項目分析、(4)模擬分析、(5)建立CAT施測平台、及(6)實地測試CAMPS/心理計量驗證（追蹤測試100 位個案）等。項目分析與心理計量特性驗證包含：Rasch 假設驗證、單一建構(unidimensionality)、同時效度、預測效度及反應性(responsiveness)。另將估計CAMPS 之最小重要差異值與建構行動功能階層。我們亦將比較CAMPS 與傳統行動功能評估工具，以確認CAMPS 之心理計量與效率是否優於傳統評估工具。本研究將發展出國際上，可能是第一套中風病人行動功能電腦適性測驗系統，且此系統將具備4 項特點：(1)評估內容完整涵蓋各種行動功能層面。(2)可快速、精準施測，提昇臨床使用之效率與可行性。(3)具備等距量尺、心理計量特性良好及涵蓋完整功能高低之項目等特質，可提供臨床或研究人員臨床決策與療效驗證之評量工具。(4) CAMPS 之最小重要差異值及行動功能階層，將有效協助臨床及研究人員解釋評估所得數據之臨床意義。這些優點，將可提升臨床與研究效能。<br> Abstract: Precise and efficient measurement of mobility function is crucial, but oftenneglected, for rehabilitation and outcome measurement in stroke patients. However,the current mobility measures have 4 possible flaws: (1) the domains measured arelimited (not including all the mobility tasks, e.g., transfer, crawling, walking, running,jumping); (2) the measures are unable to assess mobility function in a both preciseand efficient fashion; (3) the scores rendered from the measures are ordinal, notinterval, and thus unable to quantify mobility function effectively; (4) the value ofminimal important difference and the cut-off scores of the functional mobility stagesare lacking, limiting data interpretation. These flaws poorly affect clinical decisionmaking and outcome measurement.Recent research has shown that combining both item response theory (e.g.,Rasch modeling) and computerized adaptive testing (CAT) can overcome theaforementioned flaws. Rasch modeling can arrange the items measuring a singledimension in a hierarchical order and render interval scores, and it can also estimatecut-off scores for functional recovery stages. CAT can allow measurement in a timelyfashion without losing precision of measurement. Thus, we aim to develop a CATsystem for measuring Mobility in Patients with Stroke (CAMPS) on the basis ofRasch modeling in order to measure mobility function.This project, which will be completed over a period of 3 years, will be dividedinto 6 stages: (1) development of items for the CAMPS (> 60 items), (2) item testingon 300 subjects, (3) item analysis using Rasch analysis, (4) simulation analysis, (5)development of a web-based testing platform for the CAMPS, and (6) investigation ofpsychometric properties (including concurrent validity, predictive validity, andresponsiveness) and estimation of MID of the CAMPS on 100 subjects. We willestimate cut-off scores for functional stages for the CAMPS. We will also compare thepsychometric properties and efficiency of the CAMPS with a traditional mobilitymeasure to determine whether the CAMPS is better than the traditional mobilitymeasure.Our CAMPS might be the first CAT for measuring mobility function in the world.The CAMPS will have 4 advantages: (1) the content will cover the entire spectrum ofmobility function; (2) the CAMPS will be able to measure mobility in a timely andprecise fashion; (3) the score of CAMPS will be an interval score and thus able toeffectively quantify mobility function; and (4) the values of minimal importantdifference and cut-off scores of functional stages will be valuable for users to interpretthe scores of CAMPS. The CAMPS will help clinicians and researchers in decisionmaking and outcome measurement.