Defining and reporting activity patterns: a modified Delphi study.

BACKGROUND: Despite significant interest in assessing activity patterns in different populations, there has been no consensus concerning the definition and operationalisation of this term. This has limited the comparability, interpretability, and synthesis of study findings to date. The aim of this study was to establish a consensus regarding the way in which activity patterns and activity pattern components are defined and reported. METHODS: The activity patterns literature was searched to identify experts to be invited to participate and to develop a proposed definition of activity patterns and activity pattern components. A three-round modified Delphi survey was conducted online (November 2021 to May 2022). In Round 1, participants were asked to rate their agreement with a proposed activity patterns definition, which also included six activity pattern components (e.g., activity intensity, activity bout, transitions), six examples of activity patterns (e.g., frequency of postural transitions in discrete time periods) and eight items for reporting activity patterns in future research (n = 21 items). Open-ended questions enabled participants to provide further comments and suggestions for additional items. Consensus was defined a priori as ≥ 80% participants rating their agreement with an item. In Round 2, participants were asked to rate their agreement with 25 items (13 original items, eight amended, and four new). In Round 3, participants rated their agreement with 10 items (five original items, four amended, and one new). RESULTS: Twenty experts in activity patterns research participated in Round 1, with response rates of 80% and 60% in Rounds 2 and 3, respectively. The proposed activity pattern definition, all activity pattern components definitions, four of the six activity pattern examples, and 10 items in the activity patterns reporting framework achieved consensus. The removal of one activity component item between Rounds 1 and 2 achieved consensus. CONCLUSION: This modified Delphi study achieved consensus for defining and reporting activity patterns for the first time. This consensus definition enables standardisation of activity patterns terminology, which is important given the significant interest in quantifying how individuals accumulate their physical activity and sedentary behaviour across the lifespan to inform the development of future public health guidelines and interventions efforts.

Exploring activity compensation amongst youth and adults: a systematic review.

BACKGROUND: Globally, significant efforts have focused on increasing physical activity and reducing sedentary behaviour in youth and adults across a range of settings (e.g., schools, workplaces, community, and home). Despite this, interventions have had varied efficacy and typically have failed to sustain changes in behaviours over time. One explanation that has been put forth to explain the mixed success of interventions is activity compensation. However, little is known about activity compensation, including whether compensation occurs, and perceptions and potential mechanisms of activity compensation. Understanding activity compensation would assist in tailoring and targeting of potential intervention strategies. The primary aim of this review was to synthesise research that has investigated activity compensation in youth and adults. The secondary aim was to identify potential reasons for and/or awareness of compensatory changes that may have occurred. METHODS: An electronic search of the EBSCOhost (via Academic Search Complete, CINAHL Complete, Education Source, Health Source: Nursing/Academic Edition, PsycINFO, SPORTdiscus with Full Text), MEDLINE Complete, Global Health, EMBASE, Scopus and Web of Science databases up to May 2021 was conducted. Quality assessment of included quantitative studies used a modified compensation-specific McMaster Quality Assessment Tool. RESULTS: A total of 44 studies met the inclusion criteria (22 = adult populations; 22 = youth populations) and were classified as (1) quantitative (n = 31); (2) combination of quantitative and behavioural (n = 11); (3) behavioural only (n = 1); and (4) qualitative (n = 1). Of the 42 studies that included a quantitative component, 11 (26%) reported compensation occurred. Within the 13 studies examining specific behaviours, 35 behaviours were assessed, and evidence of compensation was inconsistent. Compensation mechanisms included fatigue, time constraints, lack of motivation, drive to be inactive, fear of overexertion, and autonomous motivation. CONCLUSION: Little evidence of compensation was reported in the included quantitative studies; however, inconsistencies between studies makes comparisons difficult. There was considerable variability in the types of behaviours assessed in quantitative studies, and few studies examined potential compensatory mechanisms. Future research, using compensation specific study designs, methods, and analytic techniques, within different population sub-groups, should address these evidence gaps.

Intervention effects on children's movement behaviour accumulation as a result of the Transform-Us! school- and home-based cluster randomised controlled trial.

BACKGROUND: It is unknown if and how children's movement behaviour accumulation patterns change as a result of physical activity and/or sedentary behaviour interventions. It is important to establish the effectiveness of interventions targeting changes in such accumulation patterns. This study aimed to investigate the effect of the Transform-Us! school- and home-based intervention program on children's movement behaviour accumulation patterns, focusing on sporadic accumulation versus time in bouts. METHODS: Baseline and post-intervention (18 months) accelerometer data from the Transform-Us! 2 × 2 factorial design cluster randomised controlled trial was used (Melbourne, 2010-2012; analytical sample n = 267; aged 8-9 years). Linear mixed models were fitted to examine effects of three different interventions (targeting increases in physical activity [PA-I], reductions in sedentary time [SB-I], or both [PA + SB-I]) compared to a usual practice (control) group on post-intervention movement behaviour accumulation compositions with eight components, including sporadic time and bouts of sedentary time, and light-, moderate- and vigorous-intensity physical activity. RESULTS: Intervention effects on distribution of time in the post-intervention waking movement behaviour accumulation composition (adjusted for baseline composition) were small and not significant. However, visual inspection of the change in compositions over time revealed that only groups with a sedentary behaviour intervention component (SB-I and PA + SB-I) reduced time in sedentary bouts, compared to the overall sample compositional mean. In addition, the SB-I group was the only group with an increase in vigorous-intensity physical activity. The combined intervention group (PA + SB-I) was characterized by the largest proportional increase in MPA bouts. The usual practice group was characterized by the largest proportional increases in both sporadic and bouts of sedentary time. CONCLUSIONS: This study showed some early evidence to suggest that the "break up your sitting" message may result in greater impact than the "move more" message. Future research, including larger sample sizes, should investigate if this type of messaging is indeed more effective in changing movement behaviours and ultimately child health. TRIAL REGISTRATION: International Standard Randomized Controlled Trial Number ISRCTN83725066 ; Australian New Zealand Clinical Trials Registry Number ACTRN12609000715279 .

School-related sedentary behaviours and indicators of health and well-being among children and youth: a systematic review.

BACKGROUND: The purpose of this systematic review was to examine the associations between school-related sedentary behaviours and indicators of health and well-being in children and youth (~ 5-18 years) attending school. METHODS: This review was conducted to inform the development of School-Related Sedentary Behaviour Recommendations. Peer-reviewed, published, or in-press articles in English were included. Reviews, meta-analyses, and case studies were excluded; all other study designs were eligible. Further, articles had to meet the a priori study criteria for population, intervention, comparator (PROSPERO ID: CRD42021227600). Embase, MEDLINE® ALL, and PsycINFO were searched. Risk of bias was assessed for individual experimental studies using the Cochrane risk of bias assessment tool, and in observational studies based on the GRADE framework and in line with previous systematic reviews examining sedentary behaviours in children. Overall quality of evidence was assessed using the GRADE framework for each outcome category and study design. Results were synthesized narratively, grouped by study design and outcome category. Further, several high-level summaries were conducted to help interpret results. RESULTS: Evidence was synthesized from 116 reports, including 1,385,038 participants and 1173 extracted associations. More school-related sedentary behaviour was favourably associated with nearly one-third of extracted associations for cognitive (33%) and social-emotional (32%) indicators (e.g., less anxiety), but unfavourably associated with other movement behaviours (e.g., less physical activity) (35%). Active lessons were favourable (72%), compared to more school-related sedentary behaviours, when examining associations for all health and well-being indicators. More homework was favourable across all health and well-being indicators in 4% of extracted associations for primary school children, and 25% of extracted associations for secondary school children. However, ≥2 h/day of homework appeared to be unfavourable for health and well-being. Limitations for synthesized studies included generally low quality of evidence and a lack of studies in South American, African, or low-middle income countries. CONCLUSIONS: Findings can help inform policy makers, schools, and teachers, regarding the amount of homework assigned and the introduction of active lessons into the classroom to enhance health and well-being of children. More research is needed examining school-related sedentary behaviours and indicators of health and well-being in low- and middle-income countries.

The Influence of Sitting, Standing, and Stepping Bouts on Cardiometabolic Health Markers in Older Adults.

Aside from total time spent in physical activity behaviors, how time is accumulated is important for health. This study examined associations between sitting, standing, and stepping bouts, with cardiometabolic health markers in older adults. Participants from the Mitchelstown Cohort Rescreen Study (N = 221) provided cross-sectional data on activity behaviors (assessed via an activPAL3 Micro) and cardiometabolic health. Bouts of ≥10-, ≥30-, and ≥60-min sitting, standing, and stepping were calculated. Linear regression models were fitted to examine the associations between bouts and cardiometabolic health markers. Sitting (≥10, ≥30, and ≥60 min) and standing (≥10 and ≥30 min) bouts were detrimentally associated with body composition measures, lipid markers, and fasting glucose. The effect for time spent in ≥60-min sitting and ≥30-min standing bouts was larger than shorter bouts. Fragmenting sitting with bouts of stepping may be targeted to benefit cardiometabolic health. Further insights for the role of standing need to be elicited.

Count- versus MAD-based accelerometry-assessed movement behaviors and associations with child adiposity and fitness.

Estimations of time spent sedentary and in various physical activity intensities may vary according to data reduction methods applied. This study compared associations between children's accelerometer data and adiposity and fitness markers using open source (mean amplitude deviation, MAD) and proprietary (counts) data reduction methods. Complete-case accelerometer, adiposity (Body Mass Index z-score, waist circumference), and fitness (cardiorespiratory, musculoskeletal) data from 118 children (10.4 ± 0.6 years, 49% girls) were analyzed. Estimates of sedentary behavior, light-, moderate-, vigorous- (VPA), and moderate- to vigorous-intensity (MVPA) physical activity were calculated using count- and MAD-based data reduction methods. Linear regression models between time in movement behaviours and fitness and adiposity markers were conducted. Significant differences in estimates of time spent in all intensities were observed between MAD-based and count-based methods. Both methods produced evidence to suggest that sedentary behavior was detrimentally, and physical activity (any intensity) was beneficially, associated with waist circumference. MVPA and VPA were beneficially associated with fitness markers using both data reduction measures. Overall, findings suggest that estimates of sedentary time and physical activity were not comparable. However, the strength and direction of the associations obtained between the different data reduction methods and adiposity and fitness outcomes were fairly comparable, with both methods finding stronger associations for VPA compared to MVPA. This suggests that future studies may be able to pool data using different data reduction approaches when examining associations between activity and health risk factors, albeit with caution.

Is replacing sedentary time with bouts of physical activity associated with inflammatory biomarkers in children?

This study aimed to investigate the theoretical impact of reallocating a specific amount of sedentary time with an equal amount of (a) total and (b) ≥1-minute bout-accumulated time spent in different activity intensities, on inflammatory biomarkers in 8- to 9-year-old children. Accelerometry and inflammatory biomarker baseline data from the Transform-Us! Study (complete cases n = 149) were utilized. Isotemporal linear models with the Gaussian distribution and identity link functions were used to assess associations between the activity replacements and seven individual inflammatory biomarkers, including C-reactive protein (CRP), and Interleukin (IL)-2, IL-6, IL-8, and IL-10, as well as combined inflammatory and pro-inflammatory composite scores. Eighty-five percent of children met physical activity recommendations. Replacing 10 minutes of sedentary time per day with VPA, regardless of how this was accumulated, was beneficially associated with CRP and both combined composite scores. In contrast, replacing 10 min/day of sedentary time with ≥ 1-minute MPA bouts was detrimentally associated with CRP and the inflammatory composite score. Substitutions with other activity intensities were not significantly associated with any individual inflammatory biomarkers, or combined inflammatory and pro-inflammatory composite scores. In healthy and active school-aged children, evidence of the theoretical impact of replacing sedentary time with physical activity, regardless of intensity or accumulation, on markers of systemic inflammation was limited. Longitudinal research is needed to investigate the long-term impacts of reallocating sedentary time with physical activity, and particularly VPA, for inflammatory biomarkers in children, including those with increased risk of inflammation.

Reallocating sedentary time with total physical activity and physical activity bouts in children: Associations with cardiometabolic biomarkers.

This cross-sectional study examined theoretical effects of reallocating sedentary time (SED) with total physical activity, and physical activity bouts of varying intensities, on children's cardiometabolic biomarkers. Baseline data from the Transform-Us! trial (Melbourne, Australia) was used. Participant data were included if accelerometer and blood biomarker data were complete (n = 169; 8.7 [0.4] years; 56% girls). Isotemporal substitution models assessed the impact of replacing 10 minutes of SED with 10 minutes of total physical activity or physical activity in bouts of varying intensities on cardiometabolic biomarkers. In adjusted models, replacing 10 minutes of SED with vigorous-intensity physical activity (VPA) was associated with lower triglycerides in the whole sample. Replacing SED with VPA was associated with better high-density lipoprotein cholesterol (HDL-C) and triglycerides in children with healthy weight. Replacing SED with MPA was associated with better homoeostatic model assessment of insulin resistance (HOMA-IR) and HDL-C, in children with healthy weight and overweight, respectively. Substituting SED with VPA specifically accumulated in ≥1-min bouts was detrimentally associated with HOMA-IR in children with healthy weight but beneficially with the cardiometabolic summary score in the overweight sample. This suggests that replacing SED with MPA or VPA may have some benefits on cardiometabolic health.

Which specific modes of exercise training are most effective for treating low back pain? Network meta-analysis.

OBJECTIVE: Examine the effectiveness of specific modes of exercise training in non-specific chronic low back pain (NSCLBP). DESIGN: Network meta-analysis (NMA). DATA SOURCES: MEDLINE, CINAHL, SPORTDiscus, EMBASE, CENTRAL. ELIGIBILITY CRITERIA: Exercise training randomised controlled/clinical trials in adults with NSCLBP. RESULTS: Among 9543 records, 89 studies (patients=5578) were eligible for qualitative synthesis and 70 (pain), 63 (physical function), 16 (mental health) and 4 (trunk muscle strength) for NMA. The NMA consistency model revealed that the following exercise training modalities had the highest probability (surface under the cumulative ranking (SUCRA)) of being best when compared with true control: Pilates for pain (SUCRA=100%; pooled standardised mean difference (95% CI): -1.86 (-2.54 to -1.19)), resistance (SUCRA=80%; -1.14 (-1.71 to -0.56)) and stabilisation/motor control (SUCRA=80%; -1.13 (-1.53 to -0.74)) for physical function and resistance (SUCRA=80%; -1.26 (-2.10 to -0.41)) and aerobic (SUCRA=80%; -1.18 (-2.20 to -0.15)) for mental health. True control was most likely (SUCRA≤10%) to be the worst treatment for all outcomes, followed by therapist hands-off control for pain (SUCRA=10%; 0.09 (-0.71 to 0.89)) and physical function (SUCRA=20%; -0.31 (-0.94 to 0.32)) and therapist hands-on control for mental health (SUCRA=20%; -0.31 (-1.31 to 0.70)). Stretching and McKenzie exercise effect sizes did not differ to true control for pain or function (p>0.095; SUCRA<40%). NMA was not possible for trunk muscle endurance or analgesic medication. The quality of the synthesised evidence was low according to Grading of Recommendations Assessment, Development and Evaluation criteria. SUMMARY/CONCLUSION: There is low quality evidence that Pilates, stabilisation/motor control, resistance training and aerobic exercise training are the most effective treatments, pending outcome of interest, for adults with NSCLBP. Exercise training may also be more effective than therapist hands-on treatment. Heterogeneity among studies and the fact that there are few studies with low risk of bias are both limitations.

Day-level sedentary pattern estimates derived from hip-worn accelerometer cut-points in 8-12-year-olds: Do they reflect postural transitions?

Improving sedentary measurement is critical to understanding sedentary-health associations in youth. This study assessed agreement between the thigh-worn activPAL and commonly used hip-worn ActiGraph accelerometer methods for assessing sedentary patterns in children. Both devices were worn by 8-12-year-olds (N = 195) for 4.6 ± 1.9 days. Two ActiGraph cut-points were applied to two epoch durations: ≤25 counts (c)/15 s, ≤75c/15s, ≤100c/60s, and ≤300c/60s. Bias, mean absolute deviation (MAD), and intraclass correlation coefficients (ICCs) tested agreement between devices for total sedentary time and 11 sedentary pattern variables (usual bout duration, sedentary time accumulated in various bout durations, breaks/day, break rate, and alpha). For most sedentary pattern variables, ActiGraph 25c/15s, 75c/15s, and 100c/60s had poor ICCs, with bias and MAD >20%. ActiGraph 300c/60s had a better agreement than the other cut-points, but all ICCs were <0.587. ActiGraph underestimated sedentary time in longer bouts and usual bout duration, and overestimated sedentary time in shorter bouts, breaks/day, and alpha. For total sedentary time, ActiGraph 25c/15s, 300c/60s, and 75c/15s had good/fair ICCs, with bias and MAD <20%. Sedentary patterns derived from two commonly used ActiGraph cut-points did not appear to reflect postural changes. These differences between measurement devices should be considered when interpreting findings from sedentary pattern studies.

Using compositional data analysis to explore accumulation of sedentary behavior, physical activity and youth health.

PURPOSE: The study aimed to describe youth time-use compositions, focusing on time spent in shorter and longer bouts of sedentary behavior and physical activity (PA), and to examine associations of these time-use compositions with cardiometabolic biomarkers. METHODS: Accelerometer and cardiometabolic biomarker data from 2 Australian studies involving youths 7-13 years old were pooled (complete cases with accelerometry and adiposity marker data, n = 782). A 9-component time-use composition was formed using compositional data analysis: time in shorter and longer bouts of sedentary behavior; time in shorter and longer bouts of light-, moderate-, or vigorous-intensity PA; and "other time" (i.e., non-wear/sleep). Shorter and longer bouts of sedentary time were defined as <5 min and ≥5 min, respectively. Shorter bouts of light-, moderate-, and vigorous-intensity PA were defined as <1 min; longer bouts were defined as ≥1 min. Regression models examined associations between overall time-use composition and cardiometabolic biomarkers. Then, associations were derived between ratios of longer activity patterns relative to shorter activity patterns, and of each intensity level relative to the other intensity levels and "other time", and cardiometabolic biomarkers. RESULTS: Confounder-adjusted models showed that the overall time-use composition was associated with adiposity, blood pressure, lipids, and the summary score. Specifically, more time in longer bouts of light-intensity PA relative to shorter bouts of light-intensity PA was significantly associated with greater body mass index z-score (zBMI) (ß = 1.79; SE = 0.68) and waist circumference (ß = 18.35, SE = 4.78). When each activity intensity was considered relative to all higher intensities and "other time", more time in light- and vigorous-intensity PA, and less time in sedentary behavior and moderate-intensity PA, were associated with lower waist circumference. CONCLUSION: Accumulating PA, particularly light-intensity PA, in frequent short bursts may be more beneficial for limiting adiposity compared to accumulating the same amount of PA at these intensities in longer bouts.

Cross-Sectional Associations of Total Daily Volume and Activity Patterns across the Activity Spectrum with Cardiometabolic Risk Factors in Children and Adolescents.

Sedentary and physical activity patterns (bouts/breaks) may be important for cardiometabolic health in early life. This study aimed to examine cross-sectional associations of total daily volume and patterns across the activity spectrum with cardiometabolic risk factors in youth aged 7-13 years. Objectively measured accelerometer and cardiometabolic risk factor data were pooled from two studies (n = 1219; 69% valid accelerometry). Total daily volume of sedentary time and light-, moderate-, and vigorous-intensity physical activity was determined. Time in sustained bouts and median bout lengths of all intensities and breaks in sedentary time were also calculated. Outcomes included body mass index, waist circumference, blood pressure, blood lipids, and a cardiometabolic summary score. Regression models revealed beneficial associations between total daily volumes of moderate- and vigorous-intensity physical activity and cardiometabolic risk. Time spent in ≥1 min vigorous-intensity physical activity bouts was beneficially associated with cardiometabolic risk, yet this disappeared after adjusting for total vigorous-intensity physical activity and confounders. Time accumulated in light- (≥1 min; ≥5 min) and moderate-intensity (≥1 min) physical activity bouts was detrimentally associated with cardiometabolic risk. Total daily volume and activity patterns may have implications for cardiometabolic risk early in life. Sporadic physical activity may be more beneficial for health than sustained physical activity.

Activity Accumulation and Cardiometabolic Risk in Youth: A Latent Profile Approach.

INTRODUCTION: This cross-sectional study aimed to i) identify and characterize youth according to distinct physical activity (PA) and sedentary (SED) accumulation patterns, and ii) investigate associations of these derived patterns with cardiometabolic risk factors. METHODS: ActiGraph accelerometer data from 7- to 13-yr-olds from two studies were pooled (n = 1219; 843 (69%) with valid accelerometry included in analysis). Time accumulated in ≥5- and ≥10-min SED bouts, ≥1- and ≥5-min bouts of light, and ≥1-min bouts of moderate and vigorous PA was calculated. Frequency of breaks in SED was also obtained. Latent profile analysis was used to identify groups of participants based on their distinct accumulation patterns. Linear and logistic regression models were used to test associations of group accumulation patterns with cardiometabolic risk factors, including adiposity indicators, blood pressure, and lipids. Total PA and SED time were also compared between groups. RESULTS: Three distinct groups were identified: "prolonged sitters" had the most time in sustained SED bouts and the least time in vigorous PA bouts; "breakers" had the highest frequency of SED breaks and lowest engagement in sustained bouts across most PA intensities; and "prolonged movers" had the least time accumulated in SED bouts and the most in PA bouts across most intensities. Although breakers engaged in less time in PA bouts compared with other groups, they had the healthiest adiposity indicators. No associations with the remaining cardiometabolic risk factors were found. CONCLUSION: Youth accumulate their daily activity in three distinct patterns (prolonged sitters, breakers, and prolonger movers), with those breaking up sitting and least time in prolonged PA bouts across the day having a lower adiposity risk. No relationships with other cardiometabolic risk factors were identified.

Associations between activity patterns and cardio-metabolic risk factors in children and adolescents: A systematic review.

INTRODUCTION: Total volumes of physical activity and sedentary behaviour have been associated with cardio-metabolic risk profiles; however, little research has examined whether patterns of activity (e.g., prolonged bouts, frequency of breaks in sitting) impact cardio-metabolic risk. The aim of this review was to synthesise the evidence concerning associations between activity patterns and cardio-metabolic risk factors in children and adolescents aged 5-19 years. MATERIALS AND METHODS: A systematic search of seven databases was completed in October 2017. Included studies were required to report associations between objectively-measured activity patterns and cardio-metabolic risk factors in children and/or adolescents, and be published between 1980 and 2017. At least two researchers independently screened each study, extracted data, and undertook risk of bias assessments. RESULTS: From the 15,947 articles identified, 29 were included in this review. Twenty-four studies were observational (cross-sectional and/or longitudinal); five were experimental. Ten studies examined physical activity patterns, whilst 19 studies examined sedentary patterns. Only one study examined both physical activity and sedentary time patterns. Considerable variation in definitions of activity patterns made it impossible to identify which activity patterns were most beneficial to children's and adolescents' cardio-metabolic health. However, potential insights and current research gaps were identified. DISCUSSION AND CONCLUSION: A consensus on how to define activity patterns is needed in order to determine which activity patterns are associated with children's and adolescents' cardio-metabolic risk. This will inform future research on the impact of activity patterns on children's and adolescents' short- and longer-term health.

Nurses' occupational physical activity levels: A systematic review.

BACKGROUND: Nurses' physical performance at work has implications both for nurses' occupational health and patient care. Although nurses are the largest healthcare workforce, are present 24-hours a day, and engage in many physically demanding tasks, nurses' occupational physical activity levels are poorly understood. OBJECTIVES: The aim of this systematic review was to examine nurses' occupational physical activity levels, and explore how nurses accumulate their physical activity during a shift. DESIGN: This narrative systematic review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) Statement. DATA SOURCES: EBSCOHost (MEDLINE, CINAHL, Age Line, Academic Search Complete, Global Health, Health Business Centre, Health Policy Reference Centre, Health Source (Consumer and Nursing/Academic Edition) and SPORTDiscus), Embase, Informit, ProQuest Health and Medical, Science Direct, Scopus, and Web of Science databases. REVIEW METHODS: A systematic search of seven databases were completed to locate peer-reviewed journal articles documenting nurses' occupational physical activity levels from January 1990. Papers were included if they were original research papers; measured physical activity objectively and/or subjectively; reported nurses' occupational physical activity; and were published in English. Articles were excluded if nurses' data were not reported separately from other professional groups. Two researchers independently screened the articles, extracted data, and undertook the methodological quality assessments. RESULTS: Fifteen studies met the inclusion criteria. Nursing work predominantly comprised of light-intensity physical activity. In nine studies how nurses' accumulated occupational physical activity were documented and showed that the majority of a nurses' shift was spent standing or walking whilst completing direct patient care tasks. However, the definition of the nursing populations studied were often poorly reported, and few researchers reported the validity and the reliability of the measurement tools used. CONCLUSIONS: Nurses' occupational physical activity levels largely consist of light-intensity physical activity interspersed with moderate-intensity tasks. It is not known whether physical activity during one shift affects the activity levels in the following shift. This systematic review is the first step towards understanding the physical demands of nursing work, and how nurses' physical activity may impact workplace wellbeing and patient safety. LIMITATIONS: A meta-analysis was not possible due to the variability in how physical activity outcomes were presented. Several studies had heart rate outcomes that were converted, where possible, by the authors into physical activity outcomes. REGISTRATION: This systematic review is registered with PROSPERO; Registration number: CRD42016045427.

Working Memory Capacity Limits Motor Learning When Implementing Multiple Instructions.

Although it is generally accepted that certain practice conditions can place large demands on working memory (WM) when performing and learning a motor skill, the influence that WM capacity has on the acquisition of motor skills remains unsubstantiated. This study examined the role of WM capacity in a motor skill practice context that promoted WM involvement through the provision of explicit instructions. A cohort of 90 children aged 8 to 10 years were assessed on measures of WM capacity and attention. Children who scored in the lowest and highest thirds on the WM tasks were allocated to lower WM capacity (n = 24) and higher WM capacity (n = 24) groups, respectively. The remaining 42 participants did not participate in the motor task. The motor task required children to practice basketball shooting for 240 trials in blocks of 20 shots, with pre- and post-tests occurring before and after the intervention. A retention test was administered 1 week after the post-test. Prior to every practice block, children were provided with five explicit instructions that were specific to the technique of shooting a basketball. Results revealed that the higher WM capacity group displayed consistent improvements from pre- to post-test and through to the retention test, while the opposite effect occurred in the lower WM capacity group. This implies that the explicit instructions had a negative influence on learning by the lower WM capacity children. Results are discussed in relation to strategy selection for dealing with instructions and the role of attention control.