In this issue we feature the paper, “Methods for Activity Monitor Validation Studies: An Example With the Fitbit Charge,” by Kathryn DeShaw and colleagues ( 2018 ). Kathryn is a doctoral student working under the direction of Dr. Greg Welk at Iowa State University. This paper examines free
Franco M. Impellizzeri and Samuele M. Marcora
We propose that physiological and performance tests used in sport science research and professional practice should be developed following a rigorous validation process, as is done in other scientific fields, such as clinimetrics, an area of research that focuses on the quality of clinical measurement and uses methods derived from psychometrics. In this commentary, we briefly review some of the attributes that must be explored when validating a test: the conceptual model, validity, reliability, and responsiveness. Examples from the sport science literature are provided.
Levi Frehlich, Christine Friedenreich, Alberto Nettel-Aguirre, Jasper Schipperijn and Gavin R. McCormack
( Aadland & Ylvisåker, 2015 ) and has been validated in adults using indirect calorimetry ( Santos-Lozano et al., 2013 ) and doubly labelled water ( Chomistek et al., 2017 ) as criterion measures. GPS Monitoring GPS monitors (model: Qstarz BT-Q1000XT ® ; Qstarz International Inc., Taiwan) captured the
Alan K. Bourke, Espen A. F. Ihlen and Jorunn L. Helbostad
The measurement of physical activity patterns has the potential to reveal underlying causes of changes in modifiable risk-factors associated with health and well-being. Accurate classification of physical activity (PA) in free-living situations requires the use of a validated measurement system to
Lise Gauvin and W. Jack Rejeski
This research describes the development and validation of a measure designed to assess feeling states that occur in conjunction with acute bouts of physical activity—the Exercise-Induced Feeling Inventory (EFI). The EFI consists of 12 items that capture four distinct feeling states: revitalization, tranquility, positive engagement, and physical exhaustion. The multidimensional structure of the EFI is supported by confirmatory factor analysis. The subscales have good internal consistency, share expected variance with related constructs, are sensitive to exercise interventions, and appear responsive to the different social contexts in which activity may occur. After describing the psychometric properties of the EFI, several directions for theory-based research are proposed.
Ryan D. Burns, James C. Hannon, Timothy A. Brusseau, Patricia A. Eisenman, Pedro F. Saint-Maurice, Greg J. Welk and Matthew T. Mahar
Cardiorespiratory endurance is a component of health-related fitness. FITNESSGRAM recommends the Progressive Aerobic Cardiovascular Endurance Run (PACER) or One mile Run/Walk (1MRW) to assess cardiorespiratory endurance by estimating VO2 Peak. No research has cross-validated prediction models from both PACER and 1MRW, including the New PACER Model and PACER-Mile Equivalent (PACER-MEQ) using current standards. The purpose of this study was to cross-validate prediction models from PACER and 1MRW against measured VO2 Peak in adolescents. Cardiorespiratory endurance data were collected on 90 adolescents aged 13–16 years (Mean = 14.7 ± 1.3 years; 32 girls, 52 boys) who completed the PACER and 1MRW in addition to a laboratory maximal treadmill test to measure VO2 Peak. Multiple correlations among various models with measured VO2 Peak were considered moderately strong (R = .74–0.78), and prediction error (RMSE) ranged from 5.95 ml·kg-1, min-1 to 8.27 ml·kg-1.min-1. Criterion-referenced agreement into FITNESSGRAM’s Healthy Fitness Zones was considered fair-to-good among models (Kappa = 0.31–0.62; Agreement = 75.5–89.9%; F = 0.08–0.65). In conclusion, prediction models demonstrated moderately strong linear relationships with measured VO2 Peak, fair prediction error, and fair-to-good criterion referenced agreement with measured VO2 Peak into FITNESSGRAM’s Healthy Fitness Zones.
Thomas A. Bergandi, Marsha G. Shryock and Thomas G. Titus
The purpose of this study was to develop and validate a sport-specific version of Nideffer’s (1976a) Test of Attentional and Interpersonal Style (TAIS), specifically in regard to the sport of basketball. Collegiate basketball players (N = 43) participated in the research, 20 males and 23 females. The subjects were administered two instruments, the original TAIS and the Basketball Concentration Survey (BCS). The items contained in the BCS were a conversion of the 59 pertinent items contained in the original. The instruments were administered early in the season and the results were correlated with nine seasonal performance variables ranging from field-goal percentage to total number of steals. The results show the BCS to have significant reliability as well as significantly accounting for performance variability. The BCS had highly significant correlations with seven of the nine performance variables.
Donna W. Lockner, Vivian H. Heyward, Sharon E. Griffin, Martim B. Marques, Lisa M. Stolarczyk and Dale R. Wagner
The Segal fatness-specific bioelectrical impedance (BIA) equations are useful for predicting fat-free mass (FFM). Stolarczyk et al, proposed a modified method of averaging the two equations for individuals who are neither lean nor obese, thus eliminating the need to know % BF a priori. To cross-validate this modification, we compared FFM determined using the averaging method versus hydrostatic weighing for 76 adults. Per the averaging method, accuracy for males was excellent (r = .91, SEE = 2.7kg, E = 2.7kg), with 78% of individuals within ± 3.5% BF predicted by hydrostatic weighing. Accuracy for females was lower (r = .88, SEE = 3.0kg, E = 3.1 kg), with %BF of 51% within ±3.5% of the reference method. The relative ease and practicality of the averaging method and the results of this study indicate this method may be useful with a diverse group.
Weiyun Chen, Kristin Hendricks and Weimo Zhu
The purpose of this study was to design and validate the Basketball Offensive Game Performance Instrument (BOGPI) that assesses an individual player’s offensive game performance competency in basketball. Twelve physical education teacher education (PETE) students playing two 10-minute, 3 vs. 3 basketball games were videotaped at end of a basketball unit in one physical education teaching methods course. Two investigators independently coded each player’s offensive game behaviors with BOGPI. The interrater reliability of the BOGPI was 99% and the alpha reliability coefficient for the total scale of the BOGPI was .95. The content validity evidence of the BOGPI was established by six experienced experts’ judgment. The results of this study indicate that the BOGPI is a theoretically sound and psychometrically supported measure that can be used by researchers and teacher educators to assess the preservice teachers’ offensive game performance ability in basketball.
Edward MeAuley and Kerry S. Courneya
This paper documents the development and validation of the three-factor Subjective Exercise Experiences Scale (SEES), a measure of global psychological responses to the stimulus properties of exercise. Two of these factors correspond to the positive and negative poles associated with psychological health, Positive Weil-Being and Psychological Distress, whereas the third factor represents subjective indicants of Fatigue. The three-factor structure originally established by exploratory factor analysis using young adults was also supported in middle-aged exercising adults using confirmatory factor analytic techniques. Moreover, convergent and discriminant validity for the SEES subscales was demonstrated by examining relations with measures of affect regularly employed in exercise domain. The SEES may represent a useful starting point for more thoroughly examining exercise and subjective responses at the global level, and these dimensions of the scale may represent possible antecedents of specific affective responsivity.