Wrist-worn monitors claim to provide accurate measures of heart rate and energy expenditure. People wishing to lose weight use these devices to monitor energy balance, however the accuracy of these devices to measure such parameters has not been established. To determine the accuracy of four wrist-worn devices (Apple Watch, Fitbit Charge HR, Samsung Gear S and Mio Alpha) to measure heart rate and energy expenditure at rest and during exercise. Twenty-two healthy volunteers (50% female; aged 24 ± 5.6 years) completed ~1-hr protocols involving supine and seated rest, walking and running on a treadmill and cycling on an ergometer. Data from the devices collected during the protocol were compared with reference methods: electrocardiography (heart rate) and indirect calorimetry (energy expenditure). None of the devices performed significantly better overall, however heart rate was consistently more accurate than energy expenditure across all four devices. Correlations between the devices and reference methods were moderate to strong for heart rate (0.67–0.95 [0.35 to 0.98]) and weak to strong for energy expenditure (0.16–0.86 [-0.25 to 0.95]). All devices underestimated both outcomes compared to reference methods. The percentage error for heart rate was small across the devices (range: 1–9%) but greater for energy expenditure (9–43%). Similarly, limits of agreement were considerably narrower for heart rate (ranging from -27.3 to 13.1 bpm) than energy expenditure (ranging from -266.7 to 65.7 kcals) across devices. These devices accurately measure heart rate. However, estimates of energy expenditure are poor and would have implications for people using these devices for weight loss.

This systematic review and meta-analysis assessed the effectiveness of physical activity interventions on undergraduate students’ mental health. Seven databases were searched and a total of 59 studies were included. Studies with a comparable control group were meta-analysed, and remaining studies were narratively synthesized. The included studies scored very low GRADE and had a high risk of bias. Meta-analyses indicated physical activity interventions are effective in reducing symptoms of anxiety (n = 20, standardized mean difference (SMD) = −0.88, 95% CI [−1.23, −0.52]), depression (n = 14, SMD = −0.73, 95% CI [−1.00, −0.47]) and stress (n = 10, SMD = −0.61, 95% CI [−0.94, −0.28]); however, there was considerable heterogeneity (anxiety, I² = 90.29%; depression I² = 49.66%; stress I² = 86.97%). The narrative synthesis had mixed findings. Only five studies reported being informed by a behavioural change theory and only 30 reported intervention fidelity. Our review provides evidence supporting the potential of physical activity interventions in enhancing the mental health of undergraduate students. More robust intervention design and implementation are required to better understand the effectiveness of PA interventions on mental health outcomes.

Ication from wrist accelerometer data. Methods Three samples were used: 1) free living (n = 13, ages 20–60 yr); 2) laboratory based (n = 25, ages 30–65 yr); and 3) hospital inpatients (n = 10, ages 60–90 yr). All participants wore a GENEActiv on their wrist and activPAL on their thigh. The free-living sample wore an additional GENEActiv on the thigh and completed the Multimedia Activity Recall for Children and Adults. The laboratory-based sample wore the monitors while seated at a desk for 7 h, punctuated by 2 min of walking every 20 min. The free-living and inpatient samples wore the monitors for 24 h. Posture was classified from wrist-worn accelerometry using the Sedentary Sphere concept. Results Sitting time did not differ between the wrist GENEActiv and the activPAL in the free-living sample and was correlated in the three samples combined (rho = 0.9, P < 0.001), free-living and inpatient samples (r ≃ 0.8, P < 0.01). Mean intraindividual agreement was 85% ± 7%. In the laboratory-based and inpatient samples, sitting time was underestimated by the wrist GENEActiv by 30 min and 2 h relative to the activPAL, respectively (P < 0.05). Posture classification disagreed during reading while standing, cooking while standing, and brief periods during driving. Posture allocation validity was excellent when the GENEActiv was worn on the thigh, evidenced by the near-perfect agreement with the activPAL (96% ± 3%). Conclusions The Sedentary Sphere enables determination of the most likely posture from the wrist-worn GENEActiv. Visualizing behaviors on the sphere displays the pattern of wrist movement and positions within that behavior....