The GT3X+ worn at the wrist promotes greater compliance than at the hip. Minutes in SB and PA calculated from raw accelerations at the hip and wrist provide contrasting estimates and cannot be directly compared. Wear-time for the wrist (15.6 to 17.4 h.d) was greater than the hip (15.2 to 16.8 h.d) across several wear-time criteria (all P < 0.05). Moderate-strong associations were found between time spent in SB (r = 0.39), LPA (r = 0.33), MPA (r = 0.99), VPA (r = 0.82) and MVPA (r = 0.81) between the two device placements (All P < 0.001). The wrist device detected more minutes in LPA, MPA, VPA and MVPA whereas the hip detected more SB (all P = 0.001). Estimates of time in SB and all activity outcomes from the wrist and hip lacked equivalence. One hundred and eighty-eight 9-12-year-old children wore a wrist- and hip-mounted accelerometer for 7 days. Data were available for 160 (hip) and 161 (wrist) participants. Time spent in SB and PA was calculated using GGIR. This study examined the compliance of children wearing wrist- and hip-mounted ActiGraph GT3X+ accelerometers and compared estimates of sedentary behaviour (SB) and physical activity (PA) between devices.
The purpose of this study was to evaluate the agreement between several activity measures using raw acceleration data from accelerometers worn concurrently on the dominant and non-dominant wrist. Fifty-five adults (31·9 ± 9·7 years, 26 males) wore two ActiGraph GT3X+ monitors continuously for 1 day, one on their non-dominant wrist and the other on their dominant wrist. Paired t-tests were undertaken with sequential Holm-Bonferroni corrections to compare wear time, moderate-vigorous physical activity (MVPA), time spent in 10-min bouts of MVPA (MVPA ) and the average magnitude of dynamic wrist acceleration (ENMO). Level of agreement between outcome variables from the wrists was examined using intraclass correlation coefficients (ICC, single measures, absolute agreement) with 95% confidence intervals and limits of agreement (LoA). Time spent across acceleration levels in 40 mg resolution were also examined. There were no significant differences between the non-dominant and dominant wrist for ENMO, wear time, MVPA or MVPA . Agreement between wrists was strong for most outcomes (ICC ≥0·92) including wear time, ENMO, MVPA, MVPA and the distribution of time across acceleration levels. Agreement was strong in the low acceleration bands (ICC = 0·970 and 0·922) with a mean bias of 3·08 min (LoA -55·18 to 61·34) and -5·43 (LoA -43·47 to 32·62). In summary, ENMO, MVPA, MVPA , wear time and the distribution of time across acceleration levels compared well at the group level. The LOA from the two lowest acceleration levels suggest further work over a longer monitoring period is needed to determine whether outputs from each wrist are comparable.
This study examined differences in physical activity (PA) estimates provided from raw and counts processing methods. One hundred and sixty-five children (87 girls) wore a hip-mounted ActiGraph GT3X+ accelerometer for 7 days. Data were available for 129 participants. Time in moderate PA (MPA), vigorous PA (VPA) and moderate-vigorous PA (MVPA) were calculated using R-package GGIR and ActiLife. Participants meeting the wear time criteria for both processing methods were included in the analysis. Time spent in MPA (-21.4 min.d-1 , 95%CI-21 to-20) and VPA (-36 min.d-1 , 95%CI-40 to-33) from count data were higher (P<0.001) than raw data. Time spent in MVPA between the two processing methods revealed significant differences (All P<0.001). Bland-Altman plots suggest that the mean bias for time spent in MPA, VPA and MVPA were large when comparing raw and count methods. Equivalence tests showed that estimates from raw and count processing methods across all activity intensities lacked equivalence. Lack of equivalence and poor agreement between raw and count processing methods suggest the two approaches to estimate PA are not comparable. Further work to facilitate the comparison of findings between studies that process and report raw and count physical activity data may be necessary.
Findings suggest that the combination of BMI with either WC or WHtR may provide an added benefit in the assessment of cardiometabolic risk amongst pre-adolescents.
Newcomers to Canada with low proficiency in English or French often face challenges in the workforce (Kustec, 2012). While language classes provide workplace language training, not all newcomers are able to attend face-to-face classes (Shaffir & Satzewich 2010), suggesting a need for outside the classroom, occupation-specific language training. The use of technology has been shown to be advantageous for second language (L2) learning (Stockwell, 2007), especially when used outside the classroom (i.e., mobile-assisted language learning), as mobile technology affords learners greater control and flexibility over their own learning (Yang, 2013). This paper reports on a study investigating the development of a blended curriculum for L2 learners employed in customer service. A technology-mediated module was designed and developed within a task-based language teaching framework to provide workplace-linguistic support on mobile devices, enabling learners to access the language instruction they needed, when they needed it. The module contents and usability were assessed by high-beginner English proficiency newcomers employed in customer service (n=4) and their volunteer teachers (n=4). Results confirm the overall benefits of using language learning technology in providing instruction that meets participant language needs, ensuring opportunities for individualized training. Implications for designing, implementing, and researching technology-mediated modules are discussed.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.