Purpose: To investigate potential time drift between devices when using Global Positioning Systems (GPS) and accelerometers in field-based research. Methods: Six Qstarz BT-Q1000XT GPS trackers, activPAL3 accelerometers, and ActiGraph GT3X+ and GT3X accelerometers were tested over 1–3 waves, each lasting 9–14 days. Once per day an event marker was created on each pair of devices concurrently. The difference in seconds between the time stamps for each event marker were calculated between each pair of GPS and activPAL devices and GPS and ActiGraph devices. Mixed-effects linear regression tested time drift across days and waves and between two rooms/locations (in an inner room vs. on a windowsill in an outer room). Results: The GPS trackers remained within one second of the computer clock across days and waves and between rooms. The activPAL devices drifted an average of 8.38 seconds behind the GPS devices over 14 days (p < .001). The ActiGraph GT3X+ devices drifted an average of 11.67 seconds ahead of the GPS devices over 14 days (p < .001). The ActiGraph GT3X devices drifted an average of 28.83 seconds behind the GPS devices over 9 days (p < .001). Time drift did not differ across waves but did differ between rooms and across devices. Conclusions: Time drift between the GPS and accelerometer models tested was minimal and is unlikely to be problematic when addressing many common research questions. However, studies that require high levels of precision when matching short (e.g., 1-second) time intervals may benefit from consideration of time drift and potential adjustments.
Chelsea Steel, Carolina Bejarano and Jordan A. Carlson
Tracy Nau, Karen Lee, Ben J. Smith, William Bellew, Lindsey Reece, Peter Gelius, Harry Rutter and Adrian Bauman
Background: The value of a systems thinking approach to tackling population physical inactivity is increasingly recognized. This study used conceptual systems thinking to develop a cognitive map for physical activity (PA) influences and intervention points, which informed a standardized approach to the coding and notation of PA-related policies in Australia. Methods: Policies were identified through desktop searches and input from 33 nominated government representatives attending 2 national PA policy workshops. Documents were audited using predefined criteria spanning policy development, strategic approaches to PA, implementation processes, and evaluation. Data were analyzed using descriptive statistics. Results: The audit included 110 policies, mainly led by the health or planning/infrastructure sectors (n = 54, 49%). Most policies purporting to promote PA did so as a cobenefit of another objective that was not focused on PA (n = 63, 57%). An intention to monitor progress was indicated in most (n = 94, 85%); however, fewer than half (n = 52, 47%) contained evaluable goals/actions relevant to PA. Descriptions of resourcing/funding arrangements were generally absent or lacked specific commitment (n = 67, 61%). Conclusions: This study describes current PA-relevant policy in Australia and identifies opportunities for improving coordination, implementation, and evaluation to strengthen a whole-of-system and cross-agency approach to increasing population PA.
Meredith C. Peddie, Matthew Reeves, Millie K. Keown, Tracy L. Perry and C. Murray Skeaff
Background: Regular activity breaks positively impact markers of cardiometabolic health when performed in a laboratory. However, identifying compliance to a free-living regular activity breaks intervention is challenging, particularly if intensity is prescribed. Methods: This study had two parts. In Part A, 20 participants performed activity breaks similar to those shown to impart health benefits while wearing an ActiGraph and activPAL accelerometer, and a heart rate monitor. In Part B, the threshold found to identify these activities was used to identify the activity breaks performed by 78 sedentary, university employees wearing an ActiGraph accelerometer for seven days. Results: A cut-point of 1,000 vector magnitude counts per minute accurately identified activity breaks performed in the laboratory. Applying this cut-point to data collected in free living, sedentary participants identified, on average, seven activity breaks were being performed during work-hours. Conclusions: Using a cut-point of 1,000 vector magnitude counts per minute will identify activity breaks of a similar intensity to those found to elicit acute cardiometabolic benefit. Sedentary university employees may benefit from interventions to increase the number of activity breaks performed across their entire day.
Zachary Zenko and Panteleimon Ekkekakis
Studies of automatic associations of sedentary behavior, physical activity, and exercise are proliferating, but the lack of information on the psychometric properties of relevant measures is a potential impediment to progress. The purpose of this review was to critically summarize measurement practices in studies examining automatic associations related to sedentary behavior, physical activity, and exercise. Of 37 studies, 27 (73%) did not include a justification for the measure chosen to assess automatic associations. Additional problems have been noted, including the nonreporting of psychometric information (validity, internal consistency, test–retest reliability) and the lack of standardization of procedures (e.g., number, type of stimuli). The authors emphasize the need to select measures based on conceptual arguments and psychometric evidence and to standardize measurement procedures. To facilitate progress, the review concludes with a proposal for conceptually appropriate validation criteria to be used in future studies.
Nicholas D. Gilson, Caitlin Hall, Andreas Holtermann, Allard J. van der Beek, Maaike A. Huysmans, Svend Erik Mathiassen and Leon Straker
Background: This systematic review assessed evidence on the accelerometer-measured sedentary and physical activity (PA) behavior of nonoffice workers in “blue-collar” industries. Methods: The databases CINAHL, Embase, MEDLINE, PubMed, and Scopus were searched up to April 6, 2018. Eligibility criteria were accelerometer-measured sedentary, sitting, and/or PA behaviors in “blue-collar” workers (≥10 participants; agricultural, construction, cleaning, manufacturing, mining, postal, or transport industries). Data on participants’ characteristics, study protocols, and measured behaviors during work and/or nonwork time were extracted. Methodologic quality was assessed using a 12-item checklist. Results: Twenty studies (representing 11 data sets), all from developed world economies, met inclusion criteria. The mean quality score for selected studies was 9.5 (SD 0.8) out of a maximum of 12. Data were analyzed using a range of analytical techniques (eg, accelerometer counts or pattern recognition algorithms). “Blue-collar” workers were more sedentary and less active during nonwork compared with work time (eg, sitting 5.7 vs 3.2 h/d; moderate to vigorous PA 0.5 vs 0.7 h/d). Drivers were the most sedentary (work time 5.1 h/d; nonwork time 8.2 h/d). Conclusions: High levels of sedentary time and insufficient PA to offset risk are health issues for “blue-collar” workers. To better inform interventions, research groups need to adopt common measurement and reporting methodologies.
Edgard Melo Keene von Koenig Soares, Guilherme E. Molina, Daniel Saint Martin, João Luís A. E. Sadat P. Leitão, Keila E. Fontana, Luiz F. Junqueira Jr., Timóteo Leandro de Araújo, Sandra Mahecha Matsudo, Victor K. Matsudo and Luiz Guilherme Grossi Porto
Background: The World Health Organization recommends 150 minutes of moderate to vigorous physical activity (PA) throughout the week. However, the weekly frequency of PA and how to combine moderate and vigorous PA to define who reaches the recommended PA are controversial. PA level might be highly different based on the recommendation and/or the criteria employed. Methods: Demographic data and PA level evaluated by International Physical Activity Questionnaire from 3 random and representative samples from 1 state, 1 city, and 1 local organization in Brazil were analyzed (n = 2961). Nine criteria from different recommendations were used to define PA level. Prevalence estimates and 95% confidence intervals of sufficient PA were calculated for each criterion and compared with the referent (World Health Organization guideline). Total agreement, sensitivity, and specificity were also calculated with 95% confidence interval. Results: When a weekly frequency of PA was required, the prevalence of sufficient PA decreased by 11% (P < .05). For all criteria, doubling the vigorous PA minutes was similar to simply adding them to moderate PA. These findings are consistent regardless of sex, age, and educational level. Conclusion: Prevalence estimates and agreement between different PA recommendations were significantly affected when a minimum frequency was required but did not change when vigorous PA minutes were doubled.
Philip von Rosen and Maria Hagströmer
Background: This study investigates the association between self-rated health and the time spent in sedentary behavior (SB), low light-intensity physical activity (LLPA), high light-intensity physical activity (HLPA), and moderate to vigorous physical activity (MVPA), by controlling for demographics, socioeconomic status, and chronic diseases. Methods: A total of 1665 participants (55% women) completed a questionnaire about demographics, chronic diseases, and anthropometric characteristics and provided objective physical activity data on time in SB, LLPA, HLPA, and MVPA, using an ActiGraph 7164 accelerometer. Association between self-rated health and activity data was explored in a compositional data analysis. Results: The multinomial logistic regression analysis showed a significantly lower time spent in MVPA in proportion to time in other movement behaviors (SB, LLPA, and HLPA) for participants who rated their health as alright or poor compared with excellent (P < .001). Participants with poor, compared with excellent health, spent about a third of the time in MVPA (17 vs 50 min), marginally higher time in HLPA (134 vs 125 min), more time in LLPA (324 vs 300 min), and similar time in SB (383 vs 383 min), accounting for confounders and time in other movement behaviors. Conclusions: Promoting MVPA, as opposed to time in other movement behaviors, is suggested to be beneficial for excellent self-rated health.
Sanaz Nosrat, James W. Whitworth, Nicholas J. SantaBarbara, Shira I. Dunsiger and Joseph T. Ciccolo
Depressive symptoms and fatigue are prevalent among people living with human immunodeficiency virus. Resistance exercise is known to stimulate a positive affective response. Objective: To examine the acute psychological effects of resistance-exercise intensity among Black/African-American people living with human immunodeficiency virus and experiencing depressive symptoms. Methods: A total of 42 participants were randomized into a moderate- (n = 21) or high-intensity (n = 21) group. Assessments were collected before exercise (PRE), at the midpoint (MID), immediately following (POST) exercise, and 15 (DELAY 15) and 30 (DELAY 30) min after. Results: In the moderate-intensity group, affect improved PRE to POST, PRE to DELAY 15 and DELAY 30, and perceived distress decreased from PRE to all time points. In the high-intensity group, affect declined PRE to MID, and perceived distress decreased PRE to DELAY 15 and DELAY 30. Perceived activation increased PRE to MID, and POST in both groups (ps < .01). Conclusions: The moderate-intensity group compared with the high-intensity group is more effective at improving affect and energy and at reducing distress.
Patiño Alvaro, Brunella Oré-Ramos and Roger V. Araujo-Castillo
Julián Gandía, Xavier García-Massó, Adrián Marco-Ahulló and Isaac Estevan
Feedback is one of the most influential factors for motor skills learning. Physical Education teachers commonly use verbal cues to provide knowledge of process (KP) when teaching motor skills, but the ideal presentation frequency for KP in adolescents is unclear. The aim of this study was to compare the effectiveness of the frequency of KP (i.e., 100%, 67%, 0%) on dynamic balance. Thirty adolescents, age 14–15 years, participated in the study. Performance on a stabilometer platform was used to assess dynamic balance. Participants received feedback after each trial (100%), in two out of three trials (67%), or no feedback during 12 30-s trials of practice. Adolescents who received feedback (67% or 100%) required lower mean velocity to maintain similar dynamic balance performance (i.e., root mean square). Moreover, adolescents receiving 100% feedback had a higher α-scaling than those who did not received it. During the post-test and the retention, both 67% and 100% KP frequencies were effective at improving postural control, compared to the no feedback control.