脚踝
医学
逻辑回归
脚(韵律)
不稳定性
物理疗法
金标准(测试)
人口
物理医学与康复
外科
内科学
机械
语言学
环境卫生
物理
哲学
作者
Matthew Donahue,Janet E. Simon,Carrie L. Docherty
标识
DOI:10.3113/fai.2011.1140
摘要
Background: Since functional ankle instability (FAI) lacks a “gold standard” measure, a variety of self-reported ankle instability measures have been created. The purpose of this study was to determine which ankle instability measure identifies individuals who meet a minimum acceptable criterion for FAI. Methods: Participants volunteered from a large university population which included 242 participants (104 males, 138 females; 21.4 ± 1.4 years). The predictor variables were seven ankle instability questionnaires: Ankle Instability Instrument (AII), Ankle Joint Functional Assessment Tool (AJFAT), Chronic Ankle Instability Scale (CAIS), Cumberland Ankle Instability Tool (CAIT), Foot and Ankle Ability Measure (FAAM), Foot and Ankle Instability Questionnaire (FAIQ), and Foot and Ankle Outcome Score (FAOS). The outcome variable (MC_FAI) was created based on the minimum acceptable criteria for FAI. This was established as at least one ankle sprain and an episode of giving way. Data were modeled using chi-square and multinomial logistic regression. Results: The regression model revealed all of the questionnaires were more useful at identifying participants who did not meet the minimum criteria for FAI (No MC_FAI = 95.7%, MC_FAI = 55.6%, overall = 84.6%). Based on the Wald criterion, the full model was reduced to the CAIT, AII, and FAAM. The reduced model revealed the CAIT (X 2 = 8.756, p = 0.003) and AII (X 2 = 31.992, p = 0.001) as the only variables that had a significant relationship with the outcome variable. Conclusion: The model illustrates no single measure was able to predict if individuals met the minimally accepted criteria for FAI. However, a significantly accurate prediction of ankle stability status was produced by combining the CAIT and AII. Clinical Relevance: Based on the results we recommend that researchers and clinicians use both the CAIT and AII to determine ankle stability status.
科研通智能强力驱动
Strongly Powered by AbleSci AI