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Patricia A. Hageman, Carol H. Pullen and Michael Yoerger

–2008) . Journal of Rural Health, 28 , 392 – 397 . PubMed ID: 23083085 doi:10.1111/j.1748-0361.2012.00411.x 10.1111/j.1748-0361.2012.00411.x Bevans , M. , Ross , A. , & Cella , D. ( 2014 ) Patient-Reported Outcomes Measurement Information System (PROMIS): Efficient, standardized tools to measure self-reported

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Lennart Raudsepp and Eva-Maria Riso

). The Cronbach’s alpha of GDS-15 in the present study was .84. Covariates Age and sex were obtained from the population register. Self-reported health was measured using one item with response options ranging from “very bad” to “very good” ( Thogersen-Ntoumani et al., 2011 ). Further, participants were

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Margaret Delaney, Meghan Warren, Brian Kinslow, Hendrik de Heer and Kathleen Ganley

NHANES study design and methodology are available at: https://wwwn.cdc.gov/Nchs/Nhanes/analyticguidelines.aspx . Analyses were completed from 2011 to 2018. Participants completed questionnaires in the home that collected self-reported health information (e.g., demographics, physical activity, disability

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Jing Liao, Sanmei Chen, Sha Chen and Yung-Jen Yang

 = .007). There were no statistically significant group differences in self-reported health status and diagnosed chronic disease. Most participants were married, and the participants dancing over 5 years were slightly less likely to have children (93.8% vs. 98.9%, p  = .02) and live with children if they

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Lukas D. Linde, Jessica Archibald, Eve C. Lampert and John Z. Srbely

history of chronic back pain or major knee injury as determined by self-reported health history questionnaire. All procedures were conducted in accordance with the standards set out by the Declaration of Helsinki (2000) for research involving human participants. Participants supplied informed consent

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Baruch Vainshelboim, Zhongming Chen, Ricardo M. Lima and Jonathan Myers

the exercise test using the Veterans Affairs Computerized Patient Record System and self-report health history. Of the 5540 participants who completed the baseline evaluation, 846 participants were excluded: women (n = 352), those with a history of any malignancy (n = 76), incomplete or prematurely

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Kathleen S. Wilson and Kevin S. Spink

, Grady WR . Assessment of factors affecting the validity of self-reported health-risk behavior among adolescents: evidence from the scientific literature . J Adolesc Health . 2003 ; 33 ( 6 ): 436 – 57 . PubMed ID: 14642706 doi: 10.1016/S1054-139X(03)00052-1 8. Byrne BM . Structural Equation

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Neng Wan, Ming Wen, Jessie X. Fan, O. Fahina Tavake-Pasi, Sara McCormick, Kirsten Elliott and Emily Nicolosi

(69%) mentioned that they felt they had not been active enough and wanted to do more (Table  2 ). Table 2 Selected Health Characteristics of Participants in This Study Indicator No. of participants % Self-reported health  Poor 2 5.6  Fair 6 16.7  Good 16 44.4  Very good 9 25.0  Excellent 3 8.3 Self

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Tamara Vehige Calise, William DeJong, Timothy Heren, Chloe Wingerter and Harold W. Kohl III

included self-reported health status (1 = “poor” and 5 = “excellent”); smoking status; height and weight (converted into body mass index, kg/m 2 ); fruit and vegetable intake; sedentary behavior (hours per day spent watching television, reading, or playing video games); and meeting the 2008 Physical

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Shirit Kamil-Rosenberg, Mary L. Greaney, Tsivia Hochman and Carol Ewing Garber

The data analyzed for this study were collected as part of the Behavioral Risk Factor Surveillance System (BRFSS) conducted in 2011 ( CDC, 2009 ). The BRFSS is a random digit dialing telephone-based health survey used to collect self-reported health information from adults 18 years of age and older in