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Validity of PALMS GPS scoring of active and passive travel compared with SenseCam.
Carlson, Jordan A; Jankowska, Marta M; Meseck, Kristin; Godbole, Suneeta; Natarajan, Loki; Raab, Fredric; Demchak, Barry; Patrick, Kevin; Kerr, Jacqueline.
Afiliação
  • Carlson JA; Family and Preventive Medicine, University of California, San Diego, San Diego, CA.
Med Sci Sports Exerc ; 47(3): 662-7, 2015 Mar.
Article em En | MEDLINE | ID: mdl-25010407
PURPOSE: The objective of this study is to assess validity of the personal activity location measurement system (PALMS) for deriving time spent walking/running, bicycling, and in vehicle, using SenseCam (Microsoft, Redmond, WA) as the comparison. METHODS: Forty adult cyclists wore a Qstarz BT-Q1000XT GPS data logger (Qstarz International Co., Taipei, Taiwan) and SenseCam (camera worn around the neck capturing multiple images every minute) for a mean time of 4 d. PALMS used distance and speed between global positioning system (GPS) points to classify whether each minute was part of a trip (yes/no), and if so, the trip mode (walking/running, bicycling, or in vehicle). SenseCam images were annotated to create the same classifications (i.e., trip yes/no and mode). Contingency tables (2 × 2) and confusion matrices were calculated at the minute level for PALMS versus SenseCam classifications. Mixed-effects linear regression models estimated agreement (mean differences and intraclass correlation coefficients) between PALMS and SenseCam with regard to minutes/day in each mode. RESULTS: Minute-level sensitivity, specificity, and negative predictive value were ≥88%, and positive predictive value was ≥75% for non-mode-specific trip detection. Seventy-two percent to 80% of outdoor walking/running minutes, 73% of bicycling minutes, and 74%-76% of in-vehicle minutes were correctly classified by PALMS. For minutes per day, PALMS had a mean bias (i.e., amount of over or under estimation) of 2.4-3.1 min (11%-15%) for walking/running, 2.3-2.9 min (7%-9%) for bicycling, and 4.3-5 min (15%-17%) for vehicle time. Intraclass correlation coefficients were ≥0.80 for all modes. CONCLUSIONS: PALMS has validity for processing GPS data to objectively measure time spent walking/running, bicycling, and in vehicle in population studies. Assessing travel patterns is one of many valuable applications of GPS in physical activity research that can improve our understanding of the determinants and health outcomes of active transportation as well as its effect on physical activity.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Viagem / Software / Exercício Físico / Sistemas de Informação Geográfica / Atividade Motora Idioma: En Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Viagem / Software / Exercício Físico / Sistemas de Informação Geográfica / Atividade Motora Idioma: En Ano de publicação: 2015 Tipo de documento: Article