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Validation of a Clinically Feasible Activity Monitor Which Measures Body Postures and Movements in Adults With Lower-Limb Amputation Who Wear a Prosthesis

Willemijn M.J. van Rooij, H.J.G. van den Berg-Emons, Herwin L.D. Horemans, Malou H.J. Fanchamps, Fred A. de Laat, and Johannes B.J. Bussmann

Purpose: A simple single-unit activity monitor (Activ8), which is based on a tri-axial accelerometer, measures specific body postures and movements, and has potential for research and clinical practice to monitor and optimize physical behavior of people with chronic conditions. However, the validity of the Activ8 in people with lower-limb amputation is unknown. Studying validity in this specific group is needed because they often have postures and movements that differ from the normal population, and which might affect validity. Therefore our study aimed to validate the Activ8 to measure body postures and movements in people with a lower-limb amputation. Methods: Thirty people with a unilateral lower-limb amputation and who are able to walk with a prosthesis completed two activity protocols in a simulated home setting: one with basic activities (only one posture or movement) and one with functional activities from daily living. Outcomes of the Activ8 (used in thigh-fixed position and pocket position) were compared to outcomes of video observation (the reference method). Primary analyses focused on the agreement in duration of merged measures of physical activity (walking, running, cycling, standing) and sedentary behavior (lying/sitting) with the Activ8 used in thigh-fixed position. Additional analyses included the detection of specific types of physical activity, the effects of amputation level and cause, and the validity of the Activ8 in pocket position. Results: Overall percentage time differences between Activ8 (thigh-fixed position) and video observation for merged measures of physical activity and sedentary behavior outcomes were −2.7% and 2.3%, respectively. These percentages were −1.6% and 1.3% for the basic protocol, and −3.9% and 3.6% for the functional protocol, respectively. For specific postures and movements, differences were larger (ranging from −12.6% to 7.1%). Conclusion: The Activ8 activity monitor has acceptable validity to measure physical activity and sedentary behavior in people with a unilateral lower-limb amputation.

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Reported and Device-Based Physical Activity By Race/Ethnic Groups in Young-Old Women

Andrea Stewart, Barbara Sternfeld, Brittney S. Lange-Maia, Kelly R. Ylitalo, Alicia Colvin, Carrie A. Karvonen-Gutierrez, Sheila A. Dugan, Robin R. Green, and Kelley Pettee Gabriel

Purpose: To examine racial/ethnic differences in participant-reported and device-based estimates of sedentary and physical activity behaviors and correlations between measurement methods in midlife and young-old women. Methods: Data are from 1,257 Study of Women’s Health Across the Nation participants, aged 60–72 who agreed to participate in an accelerometer protocol and had valid wear time (46% White, 26% Black, 12% Chinese, 10% Japanese, 6% Hispanic). Measures from the Kaiser Physical Activity Scale (KPAS) and ActiGraph wGT3X-BT were summarized overall and by race/ethnic groups. Partial Spearman rank order correlation coefficients between the KPAS and accelerometer were computed overall and by race/ethnic groups. Fisher’s z transformation-derived confidence intervals were calculated to evaluate differences in observed correlations in the various race/ethnic groups, compared to White women. Results: Participants spent an average of 7.5 ± 2.1 h·d−1 in sedentary behaviors, 4.5 ± 1.1 h·d−1 and 2.3 ± 0.8 h·d−1 in low or high light intensity physical activity, respectively, and 56 ± 35 min·d−1 in moderate-to-vigorous intensity physical activity. Time spent in each category differed by race/ethnic group. Overall, correlation coefficients comparing the KPAS domain-specific and total physical activity scores with accelerometry were low to moderate (range: 0.062–0.462), and few statistically significant differences in correlations were noted for race/ethnic groups, compared to White women. Conclusions: Study findings complement prior studies describing sedentary and physical activity behaviors using multi-methods in a diverse population of older women, and provide additional evidence on the convergent validity of the KPAS by race/ethnic groups.

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University Student’s Perceptions of Self-Tracking Devices, Data Privacy, and Sharing Digital Data for Research Purposes

Marianne I. Clark and Matthew W. Driller

Purpose: Wearable physical activity monitors present new ethical considerations for researchers and research ethics boards. Best practice guidelines are needed for research involving wearable monitors and should consider how these devices may impact participants outside of the research context. This study examines the perceptions of university students who wore activity monitors for research purposes in order to inform such guidelines. Methods: Focus groups were held with university students who wore digital self-tracking devices for a study examining sleep and physical activity. Questions focused on motivations to wear a physical activity monitor for research, understandings of how personal digital data generated by self-tracking devices are used and accessed, and perceptions of privacy. Results: 83% of students trusted the research process and were motivated to contribute to scientific knowledge by wearing a digital tracking device. Most (83%) understood how their data were used and accessed for research purposes, but 79% were less clear on how data might be accessed and used by third parties. 79% of participants also agreed that different data carries different social and personal implications and thus should not be treated the same by researchers. Conclusions: Protocols for research involving wearable monitors should include briefing/debriefing sessions to clarify data privacy, storage, and use issues. Researchers should also consider how wearing these devices might prompt unexpected emotional and other responses and the social implications of use for participants. The concept of privacy requires further exploration in the context of digital data collection using commercial devices.

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Alternative Wear-Time Estimation Methods Compared to Traditional Diary Logs for Wrist-Worn ActiGraph Accelerometers in Pregnant Women

Samantha F. Ehrlich, Amanda J. Casteel, Scott E. Crouter, Paul R. Hibbing, Monique M. Hedderson, Susan D. Brown, Maren Galarce, Dawn P. Coe, David R. Bassett, and Assiamira Ferrara

Background: This study sought to compare three sensor-based wear-time estimation methods to conventional diaries for ActiGraph wGT3X-BT accelerometers worn on the non-dominant wrist in early pregnancy. Methods: Pregnant women (n = 108) wore ActiGraph wGT3X-BT accelerometers for seven days and recorded their device on and off times in a diary (criterion). Average daily wear-time estimates from the Troiano and Choi algorithms and the wGT3X-BT accelerometer wear sensor were compared against the diary. The Hibbing 2-regression model was used to estimate time spent in activity (during periods of device wear) for each method. Wear-time and time spent in activity were compared with multiple repeated measures ANOVAs. Bland Altman plots assessed agreement between methods. Results: Compared to the diary (825.5 minutes [795.1, 856.0]), the Choi (843.0 [95% CI: 812.6, 873.5]) and Troiano (839.1 [808.7, 869.6]) algorithms slightly overestimated wear-time, whereas the sensor (774.4 [743.9, 804.9]) underestimated it, although only the sensor differed significantly from the diary (p < .0001). Upon adjustment for average daily wear-time, there were no statistically significant differences between the wear-time methods in regards to minutes per day of moderate-to-vigorous physical activity (MVPA), vigorous physical activity, and moderate physical activity. Bland Altman plots indicated the Troiano and Choi algorithms were similar to the diary and within ≤0.5% of each other for wear-time and MVPA. Conclusions: The Choi or Troiano algorithms offer a valid and efficient alternative to diaries for the estimation of daily wear-time in larger-scale studies of MVPA during pregnancy, and reduce burden for study participants and research staff.

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Physical Activity Monitor Accuracy for Overground Walking and Free-Living Conditions Among Pregnant Women

Christopher P. Connolly, Jordana Dahmen, Robert D. Catena, Nigel Campbell, and Alexander H.K. Montoye

Purpose: We aimed to determine the step-count validity of commonly used physical activity monitors for pregnancy overground walking and during free-living conditions. Methods: Participants (n = 39, 12–38 weeks gestational age) completed six 100-step overground walking trials (three self-selected “normal pace”, three “brisk pace”) while wearing five physical activity monitors: Omron HJ-720 (OM), New Lifestyles 2000 (NL), Fitbit Flex (FF), ActiGraph Link (AG), and Modus StepWatch (SW). For each walking trial, monitor-recorded steps and criterion-measured steps were assessed. Participants also wore all activity monitors for an extended free-living period (72 hours), with the SW used as the criterion device. Mean absolute percent error (MAPE) was calculated for overground walking and free-living protocols and compared across monitors. Results: For overground walking, the OM, NL, and SW performed well (<5% MAPE) for normal and brisk pace walking trials, and also when trials were analyzed by actual speeds. The AG and FF had significantly greater MAPE for overground walking trials (11.9–14.7%). Trimester did affect device accuracy to some degree for the AG, FF, and SW, with error being lower in the third trimester compared to the second. For the free-living period, the OM, NL, AG, and FF significantly underestimated (>32% MAPE) actual steps taken per day as measured by the criterion SW (M [SD] = 9,350 [3,910]). MAPE for the OM was particularly high (45.3%). Conclusion: The OM, NL, and SW monitors are valid measures for overground step-counting during pregnancy walking. However, the OM and NL significantly underestimate steps by second and third trimester pregnant women in free-living conditions.

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Consequences of Choosing Different Settings When Processing Hip-Based Accelerometry Data From Older Adults: A Practical Approach Using Baseline Data From the SITLESS Study

Jason J. Wilson, Mathias Skjødt, Ilona McMullan, Nicole E. Blackburn, Maria Giné-Garriga, Oriol Sansano-Nadal, Marta Roqué i Figuls, Jochen Klenk, Dhayana Dallmeier, Emma McIntosh, Manuela Deidda, Mark A. Tully, Paolo Caserotti, and On behalf of the SITLESS Group*

Accurately measuring older adults’ physical activity (PA) and sedentary behavior (SB) using accelerometers is essential, as both are important markers of health. This study aimed to highlight how steps taken during data processing may affect key hip-based accelerometry outcomes in older adults, using a selection of baseline accelerometry data (n = 658) from the SITLESS study. Different analytical parameters tested included wear-time algorithms, use of low-frequency extension (LFE) filter, epoch length, and minimum and maximum daily wear-time thresholds. These were compared against vertical axis counts per minute (CPM), vector magnitude (VM) CPM, SB, light PA, moderate-to-vigorous PA, step counts, and wear-time percentage. Differences in settings across the analytical parameters were assessed using paired sample t-tests and repeated measures ANOVAs using Bonferroni correction. Using the “Choi” versus “Troiano” wear-time algorithm resulted in a higher percentage wear-time. Most SB and PA outcomes were significantly different across wear-time algorithms (p < .001). This was similar when using the LFE filter versus normal filter (p < .001). Using 10-second epoch length increased daily SB time (between +75.7 and +79.2 minutes) compared to 60-second. Most SB and PA outcomes significantly changed comparing minimum-wear-time thresholds of 360, 480, 600, and 720 minutes per day (p < .001). Applying a log-diary with a ≥1140-minute threshold had a significant impact on vertical axis CPM, VM CPM, SB, and light PA outcomes (p < .001). This study demonstrates the potential variability in the number of participants being included in studies and reported SB and PA levels when processing older adults’ accelerometry data dependent on the analytical procedures utilized.

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