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1.
BMC Sports Sci Med Rehabil ; 15(1): 163, 2023 Nov 28.
Artigo em Inglês | MEDLINE | ID: mdl-38017586

RESUMO

BACKGROUND: To assess physical activity (PA) there is a need of objective, valid and reliable measurement methods like accelerometers. Before these devices can be used for research, they need to be calibrated and validated for specific age groups as the locomotion differs between children and adults, for instance. Therefore, the aim of the present study was the calibration and validation of the Move4 accelerometer for children aged 8-13 years. METHODS: 53 normal weighted children (52% boys, 48%girls) aged 8-13 years (mean age = 10.69 ± 1.46, mean BMI = 17.93 kg/m- 2, 60th percentile), wore the Move4 sensor at four different body positions (thigh, hip, wrist and the Move4ecg including heart rate measurement at the chest). They completed nine activities that considered the four activity levels (sedentary behavior (SB), light PA (LPA), moderate PA (MPA) and vigorous PA (VPA)) within a test-retest design. Intensity values were determined using the mean amplitude deviation (MAD) as well as the movement acceleration intensity (MAI) metrics. Determination of activities and energy expenditure was validated using heart rate. After that, cut-off points were determined in Matlab by using the Classification and Regression Trees (CART) method. The agreement for the cut-off points between T1 and T2 was analyzed. RESULTS: MAD and MAI accelerometer values were lowest when children were lying on the floor and highest when running or doing jumping jacks. The mean correlation coefficient between acceleration values and heart rate was 0.595 (p = 0.01) for MAD metric and 0.611 (p = 0.01) for MAI metric, indicating strong correlations. Further, the MAD cut-off points for SB-LPA are 52.9 mg (hip), 62.4 mg (thigh), 86.4 mg (wrist) and 45.9 mg (chest), for LPA-MPA they are 173.3 mg (hip), 260.7 mg (thigh), 194.4 mg (wrist) and 155.7 mg (chest) and for MPA-VPA the cut-off points are 543.6 mg (hip), 674.5 mg (thigh), 623.4 mg (wrist) and 545.5 mg (chest). Test-retest comparison indicated good values (mean differences = 9.8%). CONCLUSION: This is the first study investigating cut-off points for children for four different sensor positions using raw accelerometer metrics (MAD/MAI). Sensitivity and specificity revealed good values for all positions. Nevertheless, depending on the sensor position, metric values differ according to the different involvement of the body in various activities. Thus, the sensor position should be carefully chosen depending on the research question of the study.

2.
Front Psychol ; 14: 1227612, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-37780145

RESUMO

Objective: The present study aims to understand the familial decision-making process on transport mode choice in adolescents with a focus on the parental perspective within this process. Background: Active travel contributes to adolescents' overall physical activity and its positive health effects. Based on the social-learning theory, especially parents are assigned a central role for adolescents' travel behavior. The aim of the present study was to examine how parents are involved in the decision-making process on transport mode choice in adolescents. Method: The study is part of the cross-sectional mixed-methods ARRIVE study which includes semi-structured interviews with mothers (n = 12) and fathers (n = 7) of 11- to 14-year-old German adolescents. The interviews focused on travel behavior in adolescents and the decision-making process on transport mode choice from the parental perspective. All interviews were analyzed inductively using Thematic Analysis. Results: Our study revealed that parents do not primarily decide for or against active travel in adolescents, but are mostly involved in the decision-making process, especially in case of a deviation from the main transport mode. Different forms of parental involvement in the decision-making process were identified. Some parents acted as main decision makers which is the highest form of involvement while others gave their children complete freedom of choose a transport mode for themselves. These parents accepted their child's choice fully which shows a low involvement in the decision-making process. Conclusion: The results provide a deeper understanding of the familial decision-making process on travel behavior in adolescents. The results indicate an occasionally parental involvement in the decision-making process on the mainly used transport mode by adolescents, and that mothers and fathers are always involved when deviating from the main mode. Implications: Further research should investigate changes in travel behavior from childhood to young adulthood to understand long-term travel decisions in families. Due to the findings that parents are often involved in the decision-making process on transport mode choice and that they mainly reported safety concerns as barriers to their children's active travel, further research should focus especially on the social and physical environment of adolescents.

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