Although researchers have examined eating disorders in female athletes, few such studies have been done with athletes who are retired, and even fewer have been quantitative. Thus, the authors empirically tested an established eating disorder theoretical model with 218 former NCAA Division-I female collegiate athletes who had been retired for 2–6 years. In retirement, participants completed measures of general sociocultural pressures related to body and appearance, thin-ideal internalization, body dissatisfaction, dietary restraint, negative affect, and bulimic symptomatology. Through structural equation modeling, the authors examined the direct and indirect relationships among the latent variables while controlling for body mass index and years since retirement. The model fit the data well, supporting the hypothesized direct and indirect relationships among the variables and explaining 54% of the variance in bulimic symptomatology. Despite no longer being exposed to sport pressures that contribute to eating disorders, female athletes experience such symptoms long into retirement.
Stephanie L. Barrett and Trent A. Petrie
Xiangyu Liu, Meiyu Zhou, Chenyun Dai, Wei Chen and Xinming Ye
Surface electromyogram-based finger motion classification has shown its potential for prosthetic control. However, most current finger motion classification models are subject-specific, requiring calibration when applied to new subjects. Generalized subject-nonspecific models are essential for real-world applications. In this study, the authors developed a subject-nonspecific model based on motor unit (MU) voting. A high-density surface electromyogram was first decomposed into individual MUs. The features extracted from each MU were then fed into a random forest classifier to obtain the finger label (primary prediction). The final prediction was selected by voting for all primary predictions provided by the decomposed MUs. Experiments conducted on 14 subjects demonstrated that our method significantly outperformed traditional methods in the context of subject-nonspecific finger motion classification models.
Laura C. Healy, Nikos Ntoumanis and Calum A. Arthur
Using a person-centered approach, the aim of this study was to examine how student-athletes’ motives for multiple-goal pursuit relate to indices of well- and ill-being. Student-athletes (N = 362) from British universities identified the most important sporting and academic goals that they were pursuing over the academic year. The participants rated their extrinsic, introjected, identified, and intrinsic goal motives for each goal and completed measures of well- and ill-being. Latent profile analysis revealed six distinct profiles of goal motives, with variations in both the strength of motives and the motivational quality. Follow-up analyses revealed between-profile differences for well- and ill-being; students with more optimal goal motive profiles reported higher and lower well- and ill-being, respectively, than those with less optimal goal motives. To experience well-being benefits when pursuing multiple goals, student-athletes should strive for their academic and sporting goals with high autonomous and low controlled goal motives.
Michele Verdonck, Jacquie Ripat, Peita-Maree Clark, Florin Oprescu, Marion Gray, Lisa Chaffey and Bridie Kean
Wheelchair basketball (WCBB) often includes reverse integration (RI), defined as the inclusion of athletes without impairment in a sport traditionally aimed at athletes with an impairment. This study explored how RI in WCBB was understood by internal stakeholders. Data were gathered from athletes, coaches, and administrators at an Australian club competition and at a Canadian elite training center. Analysis of semistructured interviews with 29 participants led to the identification of eight themes. Collectively, the findings showed that RI was embedded within WCBB, RI was considered to be a way to advance the growth and improve the quality of WCBB as well as a way to increase awareness of WCBB and disability. There were some concerns that RI may not be equitable, as WCBB is a “disability sport.” Stakeholders’ perspectives on RI could provide useful information for sport policymakers, managers, administrators, sports organizations, and athletes interested in further developing WCBB.
Keith V. Osai, Travis E. Dorsch and Shawn D. Whiteman
Organized youth sport is a relatively common family context in which sibling dynamics are not well understood. The present study was designed to address two contrasting mechanisms of socialization—modeling and differentiation—in examining older siblings’ influence on younger siblings’ sport participation. American youth (N = 221) age 10–15 years (M = 12.38, SD = 1.01) who were active sport participants completed an online survey measuring individual and family demographics, sibling relationship qualities, and parent–child relationship dimensions. The participants reported on their most proximal older siblings, all of whom were within 4 years of age. The analyses suggest that sibling differentiation dynamics decreased the likelihood of playing the same primary sport as an older sibling for (a) the same biological sex, close in age to siblings; (b) the same biological sex, further in age from siblings; and (c) mixed biological sex, wide in age from siblings. The “Discussion” section highlights the practical value of understanding the impact of sibling influence processes on the individual, sibling dyad, and family system.
Jessica Gorzelitz, Chloe Farber, Ronald Gangnon and Lisa Cadmus-Bertram
Background: The evidence base regarding validity of wearable fitness trackers for assessment and/or modification of physical activity behavior is evolving. Accurate assessment of moderate- to vigorous-intensity physical activity (MVPA) is important for measuring adherence to physical activity guidelines in the United States and abroad. Therefore, this systematic review synthesizes the state of the validation literature regarding wearable trackers and MVPA. Methods: A systematic search of the PubMed, Scopus, SPORTDiscus, and Cochrane Library databases was conducted through October 2019 (PROSPERO registration number: CRD42018103808). Studies were eligible if they reported on the validity of MVPA and used devices from Fitbit, Apple, or Garmin released in 2012 or later or available on the market at the time of review. A meta-analysis was conducted on the correlation measures comparing wearables with the ActiGraph. Results: Twenty-two studies met the inclusion criteria; all used a Fitbit device; one included a Garmin model and no Apple-device studies were found. Moderate to high correlations (.7–.9) were found between MVPA from the wearable tracker versus criterion measure (ActiGraph n = 14). Considerable heterogeneity was seen with respect to the specific definition of MVPA for the criterion device, the statistical techniques used to assess validity, and the correlations between wearable trackers and ActiGraph across studies. Conclusions: There is a need for standardization of validation methods and reporting outcomes in individual studies to allow for comparability across the evidence base. Despite the different methods utilized within studies, nearly all concluded that wearable trackers are valid for measuring MVPA.
Kayla J. Nuss, Nicholas A. Hulett, Alden Erickson, Eric Burton, Kyle Carr, Lauren Mooney, Jacob Anderson, Ashley Comstock, Ethan J. Schlemer, Lucas J. Archambault and Kaigang Li
Objective: To validate and compare the accuracy of energy expenditure (EE) and step counts measured by ActiGraph accelerometers (ACT) at dominant and nondominant wrist and hip sites. Methods: Thirty young adults (15 females, age 22.93 ± 3.30 years) wore four ActiGraph wGT3X accelerometers while walking and running on a treadmill for 7 min at seven different speeds (1.7, 2.5, 3.4, 4.2, 5.0, 5.5, and 6.0 mph). The EE from each ACT was calculated using the Freedson Adult equation, and the “worn on the wrist” option was selected for the wrist data. Indirect calorimetry and manually counted steps were used as criterion measures. Mean absolute percentage error and two one-sided test procedures for equivalence were used for the analyses. Results: All ACTs underestimated the EE with mean absolute percentage errors over 30% for wrist placement and over 20% for hip placement. The wrist-worn ACTs underestimated the step count with mean absolute percentage errors above 30% for both dominant and nondominant placements. The hip-worn ACTs accurately assessed steps for the whole sample and for women and men (p < .001 to .05 for two one-sided tests procedures), but not at speeds slower than 2.0 mph. Conclusion: Neither hip nor wrist placements assess EE accurately. More algorithms and methods to derive EE estimates from wrist-worn ACTs must be developed and validated. For step counts, both dominant and nondominant hip placements, but not wrist placements, lead to accurate results for both men and women.
Ryan Eckert, Jennifer Huberty, Heidi Kosiorek, Shannon Clark-Sienkiewicz, Linda Larkey and Ruben Mesa
Introduction: The delivery of online interventions in cancer patients/survivors has increased. The measurement of participation in online interventions is important to consider, namely, the challenges of the remote assessment of activity. The purpose of this study was to report the measures used to assess intervention compliance and other physical activity participation in two online yoga studies, the relationship between the multimethod measures used, and the ability of cancer patients to complete these measures. Methods: The methods described are of two online yoga studies (feasibility and pilot). Cancer patients were asked to participate in 60 min/week of online yoga for 12 weeks, complete a weekly yoga log, wear a Fitbit daily for 12 weeks, and complete a weekly physical activity log. Finally, Clicky®, a web analytics software, was used to track online yoga participation. Results: Eighty-four people participated across both studies, with 63/84 participating in online yoga, averaging 57.5 ± 33.2 min/week of self-reported yoga participation compared to 41.4 ± 26.1 min/week of Clicky® yoga participation (Lin concordance = 0.28). All 84 participants averaged 95.5 ± 111.8 min/week of self-reported moderate/vigorous physical activity compared with 98.1 ± 115.9 min/week of Fitbit-determined moderate/vigorous physical activity (Lin concordance = 0.33). Across both studies, 82.9% of the yoga logs were completed, the Fitbit was worn on 75.2% of the days, and 78.7% of the physical activity logs were completed. Conclusions: Weak relationships between self-report and objective measures were demonstrated, but the compliance rates were above 75% for the study measures. Future research is needed, investigating the intricacies of self-report physical activity participation in remote interventions and the validation of a gold standard measurement for online interventions.
Fahim A. Salim, Fasih Haider, Dees Postma, Robby van Delden, Dennis Reidsma, Saturnino Luz and Bert-Jan van Beijnum
Bryson Carrier, Andrew Creer, Lauren R. Williams, Timothy M. Holmes, Brayden D. Jolley, Siri Dahl, Elizabeth Weber and Tyler Standifird
The purpose of this study was to determine the validity of the Garmin fēnix® 3 HR fitness tracker. Methods: A total of 34 healthy recreational runners participated in biomechanical or metabolic testing. Biomechanics participants completed three running conditions (flat, incline, and decline) at a self-selected running pace, on an instrumented treadmill while running biomechanics were tracked using a motion capture system. Variables extracted were compared with data collected by the Garmin fēnix 3 HR (worn on the wrist) that was paired with a chest heart rate monitor and a Garmin Foot Pod (worn on the shoe). Metabolic testing involved two separate tests; a graded exercise test to exhaustion utilizing a metabolic cart and treadmill, and a 15-min submaximal outdoor track session while wearing the Garmin. 2 × 3 analysis of variances with post hoc t tests, mean absolute percentage errors, Pearson’s correlation (R), and a t test were used to determine validity. Results: The fēnix kinematics had a mean absolute percentage errors of 9.44%, 0.21%, 26.38%, and 5.77% for stride length, run cadence, vertical oscillation, and ground contact time, respectively. The fēnix overestimated (p < .05) VO2max with a mean absolute percentage error of 8.05% and an R value of .917. Conclusion: The Garmin fēnix 3 HR appears to produce a valid measure of run cadence and ground contact time during running, while it overestimated vertical oscillation in every condition (p < .05) and should be used with caution when determining stride length. The fēnix appears to produce a valid VO2max estimate and may be used when more accurate methods are not available.