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Title:Diagnosis of underlying physical fitness trait of adults’ selfreported physical function
Author(s):Yang, Yan
Director of Research:Zhu, Weimo
Doctoral Committee Chair(s):Zhu, Weimo
Doctoral Committee Member(s):Chiu, Chung-Yi; Gershon, Richard; Sydnor, Synthia
Department / Program:Kinesiology & Community Health
Discipline:Kinesiology
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Physical function
physical fitness
diagnostic modeling
DINA
self-reported questionnaire
CDM
PROMIS
Abstract:Physical function decline is a common trajectory with aging. Physical function questionnaires have been widely used in occupational/physical therapy to assess adults’ physical function. However, most research only focuses on physical function itself. Rich patterns or profile information of the underlying physical fitness embedded in physical function questionnaires were overlooked. In addition, the associations between chronic diseases and physical fitness trait deficiencies are still less well known. Therefore, the main purpose of this study is to apply a diagnostic model that can help diagnose adults’ underlying physical fitness traits based on their self-reported physical function. This study invited three experts in the areas of physical function and physical fitness to develop a Q-matrix to be used in the diagnostic model development. Three diagnostic models were employed with the developed Q-matrix to an existing dataset (Patient-Reported Outcomes Measurement Information System [PROMIS], N = 942, 51.17% women). The most appropriate diagnostic model was selected and participants’ physical fitness trait statuses were estimated. Descriptive analyses and multiple logistic regressions were conducted to identify associations between physical fitness trait deficiencies and age/chronic diseases. A secondary data source of physical function questionnaires and performance-based fitness tests from a Chinese Parkinson’s disease group (N = 45, 60% women) was used to cross-validate the diagnostic model. The results showed that the prevalence of several physical fitness trait deficiencies gradually increased with aging, even after controlling for other demographic variables including sex, race, education level completed, marital status, family income, body weight status, and chronic diseases. The odds of all five physical fitness trait deficiencies were significantly higher in obese individuals than in normal weight individuals. This study found significant relationships between some chronic diseases and physical fitness trait deficiencies. The validation results confirmed that the diagnostic model selected by this study can be used to diagnose people with deficiencies in lower-body muscular strength, upper-body flexibility, aerobic endurance, balance, and fine motor skill. This study contributes to exercise intervention and program design by paying attention to stressing the importance of physical fitness diagnoses.
Issue Date:2018-03-13
Type:Text
URI:http://hdl.handle.net/2142/101123
Rights Information:Copyright 2018 Yan Yang
Date Available in IDEALS:2018-09-04
2020-09-05
Date Deposited:2018-05


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