Blanca Roman-Viñas, Fabio Zazo, Jesús Martínez-Martínez, Susana Aznar-Laín and Lluís Serra-Majem
Jesús Viciana, Daniel Mayorga-Vega and Alejandro Martínez-Baena
Primary and secondary school ages have been considered key moments to address the decrease of moderate-tovigorous physical activity (MVPA). Individual (eg, age, gender, and weight status) and contextual factors (moments of the day) need to be considered for a better explanation of the phenomenon. The quantity and quality of physical activity in Physical Education (PE), school recess (SR), and after school (AS) time need to be taken into account to solve the low levels of MVPA in youth.
A sample of adolescents (N = 231, 14.6 ± 1.2 years old) was studied using accelerometry to determine the objective MVPA level in PE, SR, and AS.
Results indicated statistically significant differences on MVPA between contexts (AS > PE > SR, P < .001) as well as regarding the individual factors: age (older > younger in PE and younger > older in SR time; P < .001), gender (boys > girls in all contexts, P < .001), and weight status (overweight > nonoverweight in AS, P < .01).
Because students did not meet the daily MVPA recommendations, some strategies have been provided in each of the contexts analyzed.
José Emilio Jiménez-Beatty Navarro, José Luis Graupera Sanz, Jesus Martínez del Castillo, Antonio Campos Izquierdo and María Martín Rodríguez
This study aimed to ascertain by means of a new scale older adults’ motives for engaging in physical activity, in a probability and representative sample of an older urban population. The sample size was 630 older adults, ranging from 65 to 94 years in age, randomly selected using multistage sampling. The participants completed a 17-item questionnaire, as well as answering questions on demographic variables, type of demand for physical activity, and physician’s recommendation. A principal-component analysis was performed. The relationships among the four factors (physical health, social relationships, competence, and physician’s advice) show a clearly motivational structure. Significant relationships have also been found between physician’s recommendation and type of demand. The findings suggest that programs promoting physical activity in older adults should have different characteristics from those aimed at general adult populations.
Merrill D. Funk, Cindy L. Salazar, Miriam Martinez, Jesus Gonzalez, Perla Leyva, David Bassett Jr. and Murat Karabulut
Fifty-two participants walked on a treadmill at 4.8 km/h for 500 steps while wearing four Samsung Galaxy S4 smartphones on the arm, waist, pocket, and hand while each phone simultaneously ran five popular smartphone apps. Actual steps were measured using a hand tally device. Steps were recorded from each smartphone app and compared to the tally counter using repeated measures analysis of variance (ANOVA) tests, and equivalence testing. Of the 20 step measurements recorded (five apps at four locations), all but four (Accupedo at the arm, waist, and pocket; S-Health at the pocket) produced mean underestimations of step counts. ANOVAs showed significant differences between the phone at the hand location for all apps compared to the tally counter (p < .05); three apps had differences at the waist (p < .01), Runtastic had differences at the arm (p < .001), and no differences occurred between the pocket location and the hand tally counter for any of the apps (p > .05). The 90% confidence interval for all apps, except for G-Fit, fell within the equivalence zone for the phone in the pocket while the phone at the hand location included only S-Health within the equivalence zone. Using a Samsung Galaxy S4 smartphone to measure steps at a 4.8 km/h walking pace while carrying the phone in the hand may produce significant errors. However, using the S-Health app while carrying a phone in the pocket appears to provide the most accurate step count in a controlled environment.