The suspension-training intervention delivered twice a week was beneficial for upper body pulling muscular endurance and the Functional Movement Screen score. Future interventions using this modality in youth would benefit from larger, more diverse samples (through schools or community fitness centers) and a longer intervention length.
Simple SummaryDog owners are more physically active than non-dog owners, but the direction of the relationship between dog ownership and increased physical activity is unknown. In other words, it is unclear whether acquiring a dog causes a person to become more active, or whether more physically active people choose to acquire dogs. Given that regular physical activity is critical for the prevention and management of numerous chronic diseases, research supporting the hypothesis that dogs make people more active could inform programs and policies that encourage responsible dog ownership. In the BuddyStudy, we used dog fostering to mimic dog acquisition, and examined how taking a dog into one’s home affected physical activity and psychosocial well-being. Nearly half of study participants saw large increases in physical activity and nearly three-quarters saw improvements in mood after fostering for six weeks. More than half met someone new in their neighborhood because of their foster dog. Most participants adopted their foster dog after the six-week foster period, and some maintained improvements in physical activity and well-being at 12 weeks. The results of this pilot study are promising and warrant a larger investigation.AbstractDog owners are more physically active than non-dog owners, but evidence of a causal relationship between dog acquisition and increased physical activity is lacking. Such evidence could inform programs and policies that encourage responsible dog ownership. Randomized controlled trials are the ‘gold standard’ for determining causation, but they are prohibited in this area due to ethical concerns. In the BuddyStudy, we tested the feasibility of using dog fostering as a proxy for dog acquisition, which would allow ethical random assignment. In this single-arm trial, 11 participants fostered a rescue dog for six weeks. Physical activity and psychosocial data were collected at baseline, 6, and 12 weeks. At 6 weeks, mean change in steps/day was 1192.1 ± 2457.8. Mean changes on the Center for Epidemiologic Studies Depression Scale and the Perceived Stress Scale were −4.9 ± 8.7 and −0.8 ± 5.5, respectively. More than half of participants (55%) reported meeting someone new in their neighborhood because of their foster dog. Eight participants (73%) adopted their foster dog after the 6-week foster period; some maintained improvements in physical activity and well-being at 12 weeks. Given the demonstrated feasibility and preliminary findings of the BuddyStudy, a randomized trial of immediate versus delayed dog fostering is warranted.
BackgroundCommercial activity trackers are growing in popularity among adults and some are beginning to be marketed to children. There is, however, a paucity of independent research examining the validity of these devices to detect physical activity of different intensity levels.ObjectivesThe purpose of this study was to determine the validity of the output from 3 commercial youth-oriented activity trackers in 3 phases: (1) orbital shaker, (2) structured indoor activities, and (3) 4 days of free-living activity.MethodsFour units of each activity tracker (Movband [MB], Sqord [SQ], and Zamzee [ZZ]) were tested in an orbital shaker for 5-minutes at three frequencies (1.3, 1.9, and 2.5 Hz). Participants for Phase 2 (N=14) and Phase 3 (N=16) were 6-12 year old children (50% male). For Phase 2, participants completed 9 structured activities while wearing each tracker, the ActiGraph GT3X+ (AG) research accelerometer, and a portable indirect calorimetry system to assess energy expenditure (EE). For Phase 3, participants wore all 4 devices for 4 consecutive days. Correlation coefficients, linear models, and non-parametric statistics evaluated the criterion and construct validity of the activity tracker output.ResultsOutput from all devices was significantly associated with oscillation frequency (r=.92-.99). During Phase 2, MB and ZZ only differentiated sedentary from light intensity (P<.01), whereas the SQ significantly differentiated among all intensity categories (all comparisons P<.01), similar to AG and EE. During Phase 3, AG counts were significantly associated with activity tracker output (r=.76, .86, and .59 for the MB, SQ, and ZZ, respectively).ConclusionsAcross study phases, the SQ demonstrated stronger validity than the MB and ZZ. The validity of youth-oriented activity trackers may directly impact their effectiveness as behavior modification tools, demonstrating a need for more research on such devices.
Twenty minutes after eating, %BF increased due to elevations in impedance and body mass. As such, when precision is critical, we recommend adhering to the pretest fasting guidelines to avoid meal-induced alterations in %BF estimates. In addition, use of a consistent testing schedule may minimize normal %BF variation over time.
BackgroundActivity trackers are widely used by adults and several models are now marketed for children.ObjectiveThe aims of this study were to (1) perform a content analysis of behavioral change techniques (BCTs) used by three commercially available youth-oriented activity trackers and (2) obtain feedback describing children’s perception of these devices and the associated websites.MethodsA content analysis recorded the presence of 36 possible BCTs for the MovBand (MB), Sqord (SQ), and Zamzee (ZZ) activity trackers. In addition, 16 participants (mean age 8.6 years [SD 1.6]; 50% female [8/16]) received all three trackers and were oriented to the devices and websites. Participants were instructed to wear the trackers on 4 consecutive days and spend ≥10 min/day on each website. A cognitive interview and survey were administered when the participant returned the devices. Qualitative data analysis was used to analyze the content of the cognitive interviews. Chi-square analyses were used to determine differences in behavioral monitoring and social interaction features between websites.ResultsThe MB, SQ, and ZZ devices or websites included 8, 15, and 14 of the possible 36 BCTs, respectively. All of the websites had a behavioral monitoring feature (charts for tracking activity), but the percentage of participants indicating that they “liked” those features varied by website (MB: 8/16, 50%; SQ: 6/16, 38%; ZZ: 11/16, 69%). Two websites (SQ and ZZ) included an “avatar” that the user could create to represent themselves on the website. Participants reported that they “liked” creating and changing their avatar (SQ: 12/16, 75%, ZZ: 15/16, 94%), which was supported by the qualitative analyses of the cognitive interviews. Most participants (75%) indicated that they would want to wear the devices more if their friends were wearing a tracker. No significant differences were observed between SQ and ZZ devices in regards to liking or use of social support interaction features (P=.21 to .37).ConclusionsThe websites contained several BCTs consistent with previously identified strategies. Children “liked” the social aspects of the websites more than the activity tracking features. Developers of commercial activity trackers for youth may benefit from considering a theoretical perspective during the website design process.
Dog training may strengthen the dog–owner bond, a consistent predictor of dog walking behavior. The Stealth Pet Obedience Training (SPOT) study piloted dog training as a stealth physical activity (PA) intervention. In this study, 41 dog owners who reported dog walking ≤3 days/week were randomized to a six-week basic obedience training class or waitlist control. Participants wore accelerometers and logged dog walking at baseline, 6- and 12-weeks. Changes in PA and dog walking were compared between arms with targeted maximum likelihood estimation. At baseline, participants (39 ± 12 years; females = 85%) walked their dog 1.9 days/week and took 5838 steps/day, on average. At week 6, intervention participants walked their dog 0.7 more days/week and took 480 more steps/day, on average, than at baseline, while control participants walked their dog, on average, 0.6 fewer days/week and took 300 fewer steps/day (difference between arms: 1.3 dog walking days/week; 95% CI = 0.2, 2.5; 780 steps/day, 95% CI = −746, 2307). Changes from baseline were similar at week 12 (difference between arms: 1.7 dog walking days/week; 95% CI = 0.6, 2.9; 1084 steps/day, 95% CI = −203, 2370). Given high rates of dog ownership and low rates of dog walking in the United States, this novel PA promotion strategy warrants further investigation.
Purpose: Develop a direct observation (DO) system to serve as a criterion measure for the calibration of models applied to free-living (FL) accelerometer data. Methods: Ten participants (19.4 ± 0.8 years) were video-recorded during four, one-hour FL sessions in different settings: 1) school, 2) home, 3) community, and 4) physical activity. For each setting, 10-minute clips from three randomly selected sessions were extracted and coded by one expert coder and up to 20 trained coders using the Observer XT software (Noldus, Wageningen, the Netherlands). The coder defines each whole-body movement which was further described with three modifiers: 1) locomotion, 2) activity type, and 3) MET value (used to categorize intensity level). Percent agreement was calculated for intra- and inter-rater reliability. For intra-rater reliability, the criterion coder coded all 12 clips twice, separated by at least one week between coding sessions. For inter-rater reliability, coded clips by trained coders were compared to the expert coder. Intraclass correlations (ICCs) were calculated to assess the agreement of intensity category for intra- and inter-rater comparisons described above. Results: For intra-rater reliability, mean percent agreement ranged from 91.9 ± 3.9% to 100.0 ± 0.0% across all variables in all settings. For inter-rater reliability, mean percent agreement ranged from 88.2 ± 3.5% to 100.0 ± 0.0% across all variables in all settings. ICCs for intensity category ranged from 0.74–1.00 and 0.81–1.00 for intra- and inter-rater comparisons, respectively. Conclusion: The DO system is reliable and feasible to serve as a criterion measure of FL physical activity in young adults to calibrate accelerometers, subsequently improving interpretation of surveillance and intervention research.
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