Globally, falls from height (FFH) are a substantial public health jeopardy and are among the important leading causes of serious and fatal injuries for construction workers. A comprehensive understanding of the causal factors in FFH incidents is urgently required; however, the literature appears to lack a scientific review of FFH. In this study, 297 articles that contribute to the topic of fall incidents were reviewed. Seventy-five (75) articles met the criteria for relevance and were aggregated in a database to support a critical review. A synthesis of macro-variables approach was adopted rather than a structured meta-analysis. Such a method of analysis provides the flexibility to combine previous studies' findings. The most common factors associated with FFH are risky activities, individual characteristics, site conditions, organizational characteristics, agents (scaffolds/ladders) and weather conditions. The outcomes contributed to identifying the most significant research area for safety enhancement by improving engineering facilities, behaviour investigations and FFH prevention methods.

Despite its efficacy and cost-effectiveness, exercise-based cardiac rehabilitation is undertaken by less than one-third of clinically eligible cardiac patients in every country for which data is available. Reasons for non-participation include the unavailability of hospital-based rehabilitation programs, or excessive travel time and distance. For this reason, there have been calls for the development of more flexible alternatives. We developed a system to enable walking-based cardiac rehabilitation in which the patient's single-lead ECG, heart rate, GPS-based speed and location are transmitted by a programmed smartphone to a secure server for real-time monitoring by a qualified exercise scientist. The feasibility of this approach was evaluated in 134 remotely-monitored exercise assessment and exercise sessions in cardiac patients unable to undertake hospital-based rehabilitation. Completion rates, rates of technical problems, detection of ECG changes, pre- and post-intervention six minute walk test (6 MWT), cardiac depression and Quality of Life (QOL) were key measures. The system was rated as easy and quick to use. It allowed participants to complete six weeks of exercise-based rehabilitation near their homes, worksites, or when travelling. The majority of sessions were completed without any technical problems, although periodic signal loss in areas of poor coverage was an occasional limitation. Several exercise and post-exercise ECG changes were detected. Participants showed improvements comparable to those reported for hospital-based programs, walking significantly further on the post-intervention 6 MWT, 637 m (95% CI: 565–726), than on the pre-test, 524 m (95% CI: 420–655), and reporting significantly reduced levels of cardiac depression and significantly improved physical health-related QOL. The system provided a feasible and very flexible alternative form of supervised cardiac rehabilitation for those unable to access hospital-based programs, with the potential to address a well-recognised deficiency in health care provision in many countries. Future research should assess its longer-term efficacy, cost-effectiveness and safety in larger samples representing the spectrum of cardiac morbidity and severity.

To validate a nondifferential global positioning system (GPS) to measure speed, displacement, and position during human locomotion. Three healthy participants walked and ran over straight and curved courses for 59 and 34 trials, respectively. A nondifferential GPS receiver provided speed data by Doppler shift and change in GPS position over time, which were compared with actual speeds determined by chronometry. Displacement data from the GPS were compared with a surveyed 100-m section, and static positions were collected for 1 h and compared with the known geodetic point. GPS speed values on the straight course were closely correlated with actual speeds (Doppler shift: r = 0.9994, P < 0.001, Delta GPS position/time: r = 0.9984, P < 0.001). Actual speed errors were lowest using the Doppler shift method (90.8% of values within +/- 0.1 m x s(-1)). Speed was slightly underestimated on a curved path, though still highly correlated with actual speed (Doppler shift: r = 0.9985, P < 0.001, Delta GPS distance/time: r = 0.9973, P < 0.001). Distance measured by GPS was 100.46 +/- 0.49 m, and 86.5% of static points were within 1.5 m of the actual geodetic point (mean error: 1.08 +/- 0.34 m, range 0.69-2.10 m). Nondifferential GPS demonstrated a highly accurate estimation of speed across a wide range of human locomotion velocities using only the raw signal data with a minimal decrease in accuracy around bends. This high level of resolution was matched by accurate displacement and position data. Coupled with reduced size, cost, and ease of use, this method offers a valid alternative to differential GPS in the study of overground locomotion.

Aim: Prediction intervals are a useful measure of uncertainty for meta‐analyses that capture the likely effect size of a new (similar) study based on the included studies. In comparison, confidence intervals reflect the uncertainty around the point estimate but provide an incomplete summary of the underlying heterogeneity in the meta‐analysis. This study aimed to estimate (i) the proportion of meta‐analysis studies that report a prediction interval in sports medicine; and (ii) the proportion of studies with a discrepancy between the reported confidence interval and a calculated prediction interval.Methods: We screened, at random, 1500 meta‐analysis studies published between 2012 and 2022 in highly ranked sports medicine and medical journals. Articles that used a random effect meta‐analysis model were included in the study. We randomly selected one meta‐analysis from each article to extract data from, which included the number of estimates, the pooled effect, and the confidence and prediction interval.Results: Of the 1500 articles screened, 866 (514 from sports medicine) used a random effect model. The probability of a prediction interval being reported in sports medicine was 1.7% (95% CI = 0.9%, 3.3%). In medicine the probability was 3.9% (95% CI = 2.4%, 6.6%). A prediction interval was able to be calculated for 220 sports medicine studies. For 60% of these studies, there was a discrepancy in study findings between the reported confidence interval and the calculated prediction interval. Prediction intervals were 3.4 times wider than confidence intervals.Conclusion: Very few meta‐analyses report prediction intervals and hence are prone to missing the impact of between‐study heterogeneity on the overall conclusions. The widespread misinterpretation of random effect meta‐analyses could mean that potentially harmful treatments, or those lacking a sufficient evidence base, are being used in practice. Authors, reviewers, and editors should be aware of the importance of prediction intervals.