Purpose: To investigate a new power-to-body-mass (BM) ratio 3-min all-out cycling test (3MT_%BM) for determining critical power (CP) and finite work capacity above CP (W ′).Methods: The gas-exchange threshold (GET), maximal oxygen uptake (VO_2max), and power output evoking VO_2max (W_peak) and GET (W_GET) for cycle ergometry were determined in 12 participants. CP and W′ were determined using the original “linear factor” 3MT (3MT_rpm^2) and compared with CP and W′ derived from a procedure, the 3MT_%BM, using the subject’s body mass and self-reported physical activity rating (PA-R), with values derived from linear regression of the work–time model and power–inverse-time model (1/time) data from 3 separate exhaustive squarewave bouts.Results: The VO_2max, VO_2GET, W_peak, and W_GET values estimated from PA-R and a non-exercise-regression equation did not differ (P > .05) from actual measurements. Estimates of CP derived from the 3MT_%BM (235 ± 56 W), 3MT_rpm^2 (234 ± 62 W), work–time (231 ± 57 W), and 1/time models (230 ± 57 W) did not differ (F = 0.46, P = .72). Similarly, estimates of W′ between all methods did not differ (F = 3.58, P = .07). There were strong comparisons of the 3MT_%BM to 1/time and work–time models with the average correlation, standard error of the measurement, and CV% for critical power being .96, 8.74 W, and 4.64%, respectively.Conclusion: The 3MT_%BM is a valid, single-visit protocol for determining CP and W′.

This study aimed to examine the level of shooting accuracy demonstrated by law enforcement recruits upon completion of their law enforcement firearms training in comparison with novice shooters. One hundred and ninety-five male and 52 female law enforcement recruits volunteered. Participants were separated by firearms experience into the following groups: expert (completed law enforcement firearms course, n = 83), intermediate (recreational experience, n = 71) and novice (minimal/no experience, n = 93). All subjects were tested for accuracy at target locations from 3 to 75 ft. For all locations, no difference was found in accuracy between expert and intermediate groups (p > 0.30). Experts and intermediates had better results than novices on all locations (p < 0.05) except from 3 to 15 ft. Alarmingly, experts were only 10% more accurate than novices between 3 and 15 ft. Finally, novices and intermediate shooters were more likely to hit head locations from 3 ft (57%), whereas experts mainly hit the body location (78%). The results of this study indicate that officers had no advantage over intermediate shooters and a small advantage over novices.

Solomonson, AA, Dicks, ND, Kerr, WJ, and Pettitt, RW. Influence of load carriage on high-intensity running performance estimation. J Strength Cond Res 30(5): 1391–1396, 2016—Load carriage is a necessary burden for tactical athletes. A combination of training modes, including aerobic conditioning and progressive load carriage, may lead to improved performance. The critical speed (CS) concept enables the practitioner to prescribe high-intensity interval training (HIIT) time limits (TLIMs) from a single 3-minute all-out exercise test (3 MT). We sought to examine the effect of a standard load carriage (18.86 kg) on CS and the finite running capacity > CS (D′). A group of trained subjects (age: 26 ± 5 years, height: 181 ± 4 cm, body mass [BM]: 90 ± 14 kg) completed a loaded and unloaded (UL) 3 MT. The CS was reduced by 0.66 ± 0.24 m·s−1 (p < 0.01) in the loaded condition. There was a small nonsignificant increase in D′ (21.25 ± 39.53 m, p = 0.07). The higher the % load carriage relative to BM is, the greater decline in CS (r = 0.83, p < 0.01). A revised CS with load carriage from the UL 3 MT may be calculated using: adjusted CS = original CS + ([−0.0638 × %load]) + 0.6982. Our results indicate that revised CS and TLIMs for fixed distance, fixed time, or fixed speed HIIT prescriptions may be derived from a UL 3 MT. Such calculations would enable more expeditious training for tactical athletes. We recommend further research involving implementation of HIIT using this new method.

Introduction: Police officers must perform various tasks in unpredictable work environments and potentially volatile situations. This study aimed to determine if cardiovascular fitness, body composition, and physical activity levels could predict performance in a Midwest Police Department’s Physical Readiness Assessment (PRA).Methods: Researchers collected data from thirty incumbent police officers (33.9 ± 8.3 years, female = 5). Anthropometric data included height, body mass, body fat percentage (BF%), fat-free mass (FFM), and maximal hand grip strength. The police officers also completed a physical activity rating (PA-R) scale to estimate maximal oxygen consumption (V˙O_2max) and the International Physical Activity Questionnaire (IPAQ). Police officers then conducted their department’s PRA. Stepwise linear regression analyses were used to determine the relationship between predictor variables and PRA performance. Pearson’s product-moment correlations investigated relationships between anthropometric, physical fitness, and physical activity variables and PRA performance using SPSS (v.28). The significance level was set at p < 0.05.Results: Descriptive data for the sample includes BF%: 27.85 ± 7.57%, FFM: 65.73 ± 10.72 kg, hand grip strength: 55.51 ± 11.07 kg, weekday sedentary time (WST): 328 ± 28.26 min, weekend day sedentary time (WDST): 310 ± 28.92 min, daily moderate-to-vigorous physical activity (MVPA): 29.02 ± 39.41 min, PRA: 273.6 ± 51.4 s and estimated V˙O_2max: 43.26 ± 6.35 mL kg⁻¹ min⁻¹. The stepwise regression analyses indicated that BF% was predictive of PRA time (R² = 0.32, p < 0.01); estimated V˙O_2max predictive of PRA time (R² = 0.45, p < 0.001). There were significant correlations between BF % and PRA time (r = 0.57, p < 0.001), PA-R and MVPA (r = 0.71, p < 0.001), %BF % and WDST (r = −0.606, p < 0.001), hand grip and FFM (r = 0.602, p < 0.001) and PA-R and PRA time (r = −0.36, p < 0.05).Discussion: The results of this exploratory study highlight that higher estimated V˙O_2max and lower BF% were the best predictors for faster PRA completion times, accounting for 45% and 32% of the variance, respectively. The findings of this study support the need for wellness and fitness initiatives in law enforcement agencies focused on increasing cardiovascular fitness and physical activity while decreasing BF% to ensure optimal performance in policing and overall health.

Physical inactivity, coupled with increasing obesity levels, in firefighters plays a key role in aggregated cardiovascular events. The purpose of this study was to investigate device-measured physical activity (PA) for firefighters while on- and off-duty to have a clearer understanding of their overall PA level. Methods: Twenty-nine career firefighters participated in this non-experimental, within-subjects study by wearing an accelerometer to assess PA intensities and step-count. Obesity was classified using body mass index (BMI). Dependent t-tests were used to examine mean differences in PA intensities when on- and off-duty. Pearson product-moment correlations were used to assess the association between PA intensities when on and off-duty. Results: According to the World Health Organization BMI categorizations, 20 firefighters were overweight, 9 were obese, and, thus, none were normal weight. Only light PA (LPA) was statistically significant (p = 0.026) for on- and off-duty days with a small-to-medium effect size (d = 0.47), meaning that on average, firefighters performed more minutes of LPA when on-duty compared to off. There was a significant difference between on- (9060.2 ± 2636.4) and off-duty (7495.3 ± 2835.8) daily step counts (p = 0.011). Conclusion: As the results demonstrate, there is a dire need for increased PA levels in firefighters while on- and off-duty.