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John J. Davis IV, Blaise E. Oeding, and Allison H. Gruber

Background: Running is a popular form of exercise, and its physiological effects are strongly modulated by speed. Accelerometry-based activity monitors are commonly used to measure physical activity in research, but no method exists to estimate running speed from only accelerometer data. Methods: Using three cohorts totaling 72 subjects performing treadmill and outdoor running, we developed linear, ridge, and gradient-boosted tree regression models to estimate running speed from raw accelerometer data from waist- or wrist-worn devices. To assess model performance in a real-world scenario, we deployed the best-performing model to data from 16 additional runners completing a 13-week training program while equipped with waist-worn accelerometers and commercially available foot pods. Results: Linear, ridge, and boosted tree models estimated speed with 12.0%, 11.6%, and 11.2% mean absolute percentage error, respectively, using waist-worn accelerometer data. Errors were greater using wrist-worn data, with linear, ridge, and boosted tree models achieving 13.8%, 14.0%, and 12.8% error. Across 663 free-living runs, speed was significantly associated with run duration (p = .009) and perceived run intensity (p = .008). Speed was nonsignificantly associated with fatigue (p = .07). Estimated speeds differed from foot pod measurements by 7.25%; associations and statistical significance were similar when speed was assessed via accelerometry versus via foot pod. Conclusion: Raw accelerometry data can be used to estimate running speed in free-living data with sufficient accuracy to detect associations with important measures of health and performance. Our approach is most useful in studies where research grade accelerometry is preferable to traditional global positioning system or foot pod-based measurements, such as in large-scale observational studies on physical activity.

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Bruno Rodrigues, Jorge Encantado, Eliana Carraça, João Martins, Adilson Marques, Luís Lopes, Eduarda Sousa-Sá, Dylan Cliff, Romeu Mendes, and Rute Santos

Background: We aim to systematically review the literature on measurement properties of self- and proxy-reported questionnaires measuring 24-hour movement behaviors in children and adolescents. Methods: PubMed, PsycINFO, SPORTDiscus, and EMBASE were searched until June 2021. Studies were included if the sample size for validity studies had 50 participants (minimum) and included, at least, both validity and test–retest reliability results of questionnaires. The review followed an adaptation of the Consensus-based Standards for the selection of health Measurement INstruments guidelines, to evaluate the quality of measurements properties of the questionnaires (content, convergent and criterion validity, reliability, measurement error, and responsiveness), as well as the risk of bias of each measurement property. Results: This review included 29 studies, describing 37 questionnaires. Sixty-eight percent showed “adequate” content validity. None of the questionnaires showed overall “adequate” criterion validity, and the risk of bias was “very low” for 92%. One questionnaire showed “adequate” convergent validity, and 73% of the studies were classified with a “high risk of bias.” Seven questionnaires showed “adequate” reliability, and 27.3% of the studies were rated with a “very low risk of bias.” None of the questionnaires showed “adequate” criterion validity and reliability, simultaneously. Conclusions: Existing questionnaires have insufficient measurement properties, and none considered the 24-hour movement behavior paradigm. These results highlight the need for better questionnaires of movement behavior combinations, to improve the monitoring and surveillance systems of 24-hour movement behaviors in this population.

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Sarah M. Espinoza, Marla E. Eisenberg, Alina Levine, Iris W. Borowsky, Daheia J. Barr-Anderson, Melanie M. Wall, and Dianne Neumark-Sztainer

Background: We investigated the percentage of insufficiently active adolescents who became young adults meeting moderate to vigorous physical activity (MVPA) guidelines. We also explored adolescent psychosocial and environmental factors that predicted MVPA guideline adherence in young adulthood. Methods: Participants included N = 1001 adolescents (mean age = 14.1 y) reporting < 7 hours per week of MVPA and followed (8 y later) into young adulthood through Project EAT. We examined mean weekly hours of MVPA, MVPA change between adolescence and young adulthood, and the proportion of participants meeting MVPA guidelines in young adulthood. With sex-stratified logistic regression, we tested 11 adolescent psychosocial and environmental factors predicting meeting MVPA guidelines in young adulthood. Results: Overall, 55% of insufficiently active adolescents became young adults meeting MVPA guidelines. On average, participants reported 3.0 hours per week of MVPA, which improved to 3.8 hours per week in young adulthood. Among female participants, higher MVPA in adolescence and stronger feelings of exercise compulsion predicted greater odds of meeting adult MVPA guidelines (odds ratioMVPA = 1.18; odds ratiocompulsion = 1.13). Among female and male participants, perceived friend support for activity in adolescence predicted greater odds of meeting adult MVPA guidelines (odds ratiofemale = 1.12; odds ratiomale = 1.26). Conclusions: Insufficiently active adolescents can later meet adult guidelines. Interventions that increase perceived friend support for activity may benefit individuals across development.