Characterising the physical demands of critical tasks across the Royal Australian Air Force.

BACKGROUND: Militaries have historically utilised generic physical fitness tests to assess physical readiness, but there has been a recent shift to develop physical employment standards (PES) based on actual job demands. OBJECTIVE: The purpose of this investigation was to characterise the physical demands of critical tasks performed by Royal Australian Air Force (RAAF) personnel to inform PES development. METHODS: Job task analysis were performed for 27 RAAF trades. Criterion tasks were identified through a systematic approach involving workshops and field-observations. The identified tasks were assessed for dominant physical capacity and grouped into movement-based clusters. Psychophysiological measures were collected from personnel performing the tasks. RESULTS: Of 87 criterion tasks, 92% were characterised as manual handling dominant. Across these 87 tasks the principal physical capacities were: muscular strength (59%), muscular endurance (52%) and cardiorespiratory endurance (39%). The most common movement clusters were Lift to Platform (44%) and Lift and Carry (38%). Lift to Platform tasks required lifting to a median height of 1.32 m (1.20 -1.65 m) and a median mass of 25.0 kg (21.0 -28.9 kg) per person. Median carry mass was 25.0 kg (22.4 -36.1 kg) per person and distance was 26.0 m (17.5 -50.0 m). Median task mean 'Vdot;O2, HR and RPE were 1.8 L.min- 1 (1.5-2.2 L.min- 1), 137 b.min- 1 (120-144) and 13 (12-14). CONCLUSIONS: The high proportion of manual handling criterion tasks emphasises the importance of these activities and the underlying physical capacities for RAAF personnel. Current fitness assessments are unlikely to predict job task performance.

The test-retest reliability of physiological and perceptual responses during treadmill load carriage.

PURPOSE: Understanding the test-retest reliability of physiological responses to load carriage influences the interpretation of those results. The aim of this study was to determine the test-retest reliability of physiological measures during loaded treadmill walking at 5.5 km h-1 using the MetaMax 3B. METHODS: Fifteen Australian Army soldiers (9 male, 6 female) repeated two 12-min bouts of treadmill walking at 5.5 km h-1 in both a 7.2 kg Control condition (MetaMax 3B, replica rifle) and a 23.2 kg Patrol condition (Control condition plus vest) across three sessions, separated by one week. Expired respiratory gases and heart rate were continuously collected, with the final 3 min of data analysed. Ratings of Perceived Exertion and Omnibus-Resistance Exercise Scale were taken following each trial. Reliability was quantified by coefficient of variation (CV), intra-class correlation coefficients (ICC), smallest worthwhile change (SWC), and standard error of the measurement. RESULTS: Metabolic and cardiovascular variables were highly reliable (≤ 5% CV; excellent-moderate ICC), while the respiratory variables demonstrated moderate reliability (< 8% CV; good-moderate ICC) across both conditions. Perceptual ratings had poorer reliability during the Control condition (12-45% CV; poor ICC) than the Patrol condition (7-16% CV; good ICC). CONCLUSIONS: The test-retest reliability of metabolic and cardiovascular variables was high and relatively consistent during load carriage. Respiratory responses demonstrated moderate test-retest reliability; however, as the SWC differed with load carriage tasks, such data should be interpreted independently across loads. Perceptual measures demonstrated poor to moderate reliability during load carriage, and it is recommended that they only be employed as secondary measures.

Overnight heart rate variability responses to military combat engineer training.

The study aimed to determine if overnight heart rate variability (HRV) is reflective of workload and stress during military training. Measures of cognitive load, perceived exertion, physical activity, nocturnal HRV, cognitive performance and sleep were recorded for a 15-day assessment period in 32 combat engineers. The assessment period consisted of 4 phases, PRE, FIELD, BASE and RECOVERY that exposed trainees to periods of sleep deprivation and restriction. The FIELD phase was characterised by an increase in mood disturbance, perceived exertion, physical activity, HRV and a reduction in sleep quantity (p < 0.05). Measures of HRV returned to PRE-values quicker than subjective wellbeing responses. The combination of sleep duration (ß = -0.002, F = 13.42, p < 0.001) and physical activity (metabolic equivalents, ß = -0.483, F = 5.95, p = 0.017), the main stressors of the exercise, provided a significant effect in the best predictive model of HRV. The different recovery rates of HRV and subjective wellbeing suggest a different physiological and psychological response.

Subjective Measures of Workload and Sleep in Australian Army Recruits; Potential Utility as Monitoring Tools.

INTRODUCTION: Subjective measures may offer practitioners a relatively simple method to monitor recruit responses to basic military training (BMT). Yet, a lack of agreement between subjective and objective measures may presents a problem to practitioners wishing to implement subjective monitoring strategies. This study therefore aims to examine associations between subjective and objective measures of workload and sleep in Australian Army recruits. MATERIALS AND METHODS: Thirty recruits provided daily rating of perceived exertion (RPE) and differential RPE (d-RPE) for breathlessness and leg muscle exertion each evening. Daily internal workloads determined via heart rate monitors were expressed as Edwards training impulse (TRIMP) and average heart rate. External workloads were determined via global positioning system (PlayerLoadTM) and activity monitors (step count). Subjective sleep quality and duration was monitored in 29 different recruits via a customized questionnaire. Activity monitors assessed objective sleep measures. Linear mixed-models assessed associations between objective and subjective measures. Akaike Information Criterion assessed if the inclusion of d-RPE measures resulted in a more parsimonious model. Mean bias, typical error of the estimate (TEE) and within-subject repeated measures correlations examined agreement between subjective and objective sleep duration. RESULTS: Conditional R2 for associations between objective and subjective workloads ranged from 0.18 to 0.78, P < 0.01, with strong associations between subjective measures of workload and TRIMP (0.65-0.78), average heart rate (0.57-0.73), and PlayerLoadTM (0.54-0.68). Including d-RPE lowered Akaike Information Criterion. The slope estimate between objective and subjective measures of sleep quality was not significant. A trivial relationship (r = 0.12; CI -0.03, 0.27) was observed between objective and subjective sleep duration with subjective measures overestimating (mean bias 25 min) sleep duration (TEE 41 min). CONCLUSIONS: Daily RPE offers a proxy measure of internal workload in Australian Army recruits; however, the current subjective sleep questionnaire should not be considered a proxy measure of objective sleep measures.

Characterising Psycho-Physiological Responses and Relationships during a Military Field Training Exercise.

Over a 15-day period, that included an eight-day field trial, the aims of this study were to (1) quantify the physical workload, sleep and subjective well-being of soldiers in training; (2a) Explore relationships between workload and well-being, and (2b) sleep and well-being; (3) Explore relationships between workload, sleep, and well-being. METHODS: Sixty-two Combat Engineer trainees (59 male, 3 female; age: 25.2 ± 7.2 years) wore an ActiGraph GT9X to monitor daily energy expenditure, physical activity, and sleep. Rating of perceived exertion (RPE), sleep quality, and fatigue were measured daily, subjective well-being was reported days 1, 5, 9, 13 and 15. Multi-level models were used for the analysis. RESULTS: Well-being was affected by a combination of variables including workload, subjective sleep quality, sleep duration, and sleep efficiency. RPE and subjective sleep quality were consistently significant parameters within the models of best fit. CONCLUSIONS: Perceptions of well-being were lower during the field training when physical workload increased, and sleep decreased. Energy expenditure was comparatively low, while daily sleep duration was consistent with field training literature. Subjective assessments of workload and sleep quality were consistently effective in explaining variations in well-being and represent an efficient approach to monitor training status of personnel.

A Comprehensive Analysis of Injuries During Army Basic Military Training.

INTRODUCTION: The injury definitions and surveillance methods commonly used in Army basic military training (BMT) research may underestimate the extent of injury. This study therefore aims to obtain a comprehensive understanding of injuries sustained during BMT by employing recording methods to capture all physical complaints. MATERIALS AND METHODS: Six hundred and forty-six recruits were assessed over the 12-week Australian Army BMT course. Throughout BMT injury, data were recorded via (1) physiotherapy reports following recruit consultation, (2) a member of the research team (third party) present at physical training sessions, and (3) recruit daily self-reports. RESULTS: Two hundred and thirty-five recruits had ≥1 incident injury recorded by physiotherapists, 365 recruits had ≥1 incident injury recorded by the third party, and 542 recruits reported ≥1 injury-related problems via the self-reported health questionnaire. Six hundred twenty-one, six hundred eighty-seven, and two thousand nine hundred sixty-four incident injuries were recorded from a total of 997 physiotherapy reports, 1,937 third-party reports, and 13,181 self-reported injury-related problems, respectively. The lower extremity was the most commonly injured general body region as indicated by all three recording methods. Overuse accounted for 79% and 76% of documented incident injuries from physiotherapists and the third party, respectively. CONCLUSIONS: This study highlights that injury recording methods impact injury reporting during BMT. The present findings suggest that traditional injury surveillance methods, which rely on medical encounters, underestimate the injury profile during BMT. Considering accurate injury surveillance is fundamental in the sequence of injury prevention, implementing additional injury recording methods during BMT may thus improve injury surveillance and better inform training modifications and injury prevention programs.

Factors Predicting Training Delays and Attrition of Recruits during Basic Military Training.

Ensuring a balance between training demands and recovery during basic military training (BMT) is necessary for avoiding maladaptive training responses (e.g., illness or injury). These can lead to delays in training completion and to training attrition. Previously identified predictors of injury and attrition during BMT include demographic and performance data, which are typically collected at a single time point. The aim of this study was to determine individual risk factors for injury and training delays from a suite of measures collected across BMT. A total of 46 male and female recruits undertaking the 12-week Australian Army BMT course consented to this study. Injury, illness, attrition, and demographic data were collected across BMT. Objective measures included salivary cortisol and testosterone, step counts, cardiorespiratory fitness, and muscular endurance. Perceptions of well-being, recovery, workload, fatigue, and sleep were assessed with questionnaires. Baseline and mean scores across BMT were evaluated as predictors of injury and attrition using generalized linear regressions, while repeated-measures ANOVA was used for the group comparisons. From the 46 recruits, 36 recruits completed BMT on time; 10 were delayed in completion or discharged. Multiple risk factors for injury during BMT included higher subjective ratings of training load, fatigue, and stress, lower sleep quality, and higher cortisol concentrations. Higher ratings of depression, anxiety, and stress, and more injuries were associated with a higher risk of delayed completion. Higher concentrations of testosterone and higher levels of fitness upon entry to BMT were associated with reduced risk of injury and delayed completion of BMT. Ongoing monitoring with a suite of easily administered measures may have utility in forewarning risk of training maladaptation in recruits and may complement strategies to address previously identified demographic and performance-based risk factors to mitigate injury, training delays, and attrition.

Quantification of Recruit Training Demands and Subjective Wellbeing during Basic Military Training.

Purpose: Assess and describe the physical demands and changes in subjective wellbeing of recruits completing the 12 week Australian Army Basic Military Training (BMT) course. Methods: Thirty-five recruits (24.8 ± 6.8 y; 177.4 ± 10.1 cm, 75.6 ± 14.7 kg) consented to daily activity monitoring and weekly measures of subjective wellbeing (Multi-component Training Distress Scale, MTDS). The physical demands of training were assessed via wrist worn activity monitors (Actigraph GT9X accelerometer). Physical fitness changes were assessed by push-ups, sit-ups and multi-stage shuttle run in weeks 2 and 8. Results: All objective and subjective measures significantly changed (p < 0.05) across the 12 week BMT course. In parallel, there was a significant improvement in measures of physical fitness from weeks 2 to 8 (p < 0.001). The greatest disturbance to subjective wellbeing occurred during week 10, which was a period of field training. Weeks 6 and 12 provided opportunities for recovery as reflected by improved wellbeing. Conclusions: The physical demands of training varied across the Australian Army 12 week BMT course and reflected the intended periodization of workload and recovery. Physical fitness improved from week 2 to 8, indicating a positive training response to BMT. Consistent with findings in sport, wellbeing measures were sensitive to fluctuations in training stress and appear to have utility for individual management of personnel in the military training environment.

Recovery of Cognitive Performance Following Multi-Stressor Military Training.

OBJECTIVE: This project aimed to assess the impact of an 8-day military training exercise on cognitive performance, and track its recovery in periods of reduced training load and partially restored sleep. BACKGROUND: Military personnel often work in challenging multi-stressor environments, where sleep loss is inevitable. Sleep loss can impair multiple cognitive domains, which can have disastrous consequences in military contexts. METHOD: A total of 57 male and female soldiers undergoing the Australian Army combat engineer Initial Employment Training course were recruited and tracked over a 16-day study period which included an 8-day field-based military training exercise. Cognitive performance was assessed via a computerised battery at seven time points across four sequential study periods; 1) baseline (PRE), 2) military field training exercise which included total sleep deprivation (EX-FIELD), 3) training exercise at simulated base with restricted sleep opportunities (EX-BASE), and 4) a 3-day recovery period (REC). Subjective load, fatigue, and sleep were evaluated continuously via questionnaire and actigraphy. RESULTS: Psychomotor speed, reaction time, visual tracking and vigilance were impaired following the EX-FIELD period (p < 0.05). The majority of affected measures recovered 2 days following EX-FIELD, being no different in EX-BASE compared to PRE. CONCLUSION: The sensitivity of the cognitive tests to sleep restriction, and recovery, indicates they can help assess operational readiness in military personnel. Future studies should explore other indicators of, and strategies to preserve, operational readiness in military personnel. APPLICATION: This study highlights the impact of work-induced fatigue on cognitive performance, and would interest authorities seeking to preserve operational readiness.

Impact of military training stress on hormone response and recovery.

OBJECTIVES: Military personnel are required to train and operate in challenging multi-stressor environments, which can affect hormonal levels, and subsequently compromise performance and recovery. The aims of this project were to 1) assess the impact of an eight-day military training exercise on salivary cortisol and testosterone, 2) track the recovery of these hormones during a period of reduced training. METHODS: This was a prospective study whereby 30 soldiers (n = 27 men, n = 3 women) undergoing the Australian Army combat engineer 'Initial Employment Training' course were recruited and tracked over a 16-day study period which included an eight-day military training exercise. Non-stimulated saliva samples were collected at waking, 30 min post waking, and bedtime on days 1, 5, 9, 13, 15; measures of subjective load were collected on the same days. Sleep was measured continuously via actigraphy, across four sequential study periods; 1) baseline (PRE: days 1-4), 2) field training with total sleep deprivation (EX-FIELD: days 5-8), 3) training at simulated base camp with sleep restriction (EX-BASE: days 9-12), and 4) a three-day recovery period (REC: days 13-15). RESULTS: Morning cortisol concentrations were lower following EX-FIELD (p<0.05) compared to the end of REC. Training in the field diminished testosterone concentrations (p<0.05), but levels recovered within four days. Bedtime testosterone/cortisol ratios decreased following EX-FIELD and did not return to pre-training levels. CONCLUSIONS: The sensitivity of testosterone levels and the testosterone/cortisol ratio to the period of field training suggests they may be useful indicators of a soldier's state of physiological strain, or capacity, however inter-individual differences in response to a multi-stressor environment need to be considered.

Chronicity of sleep restriction during Army basic military training.

OBJECTIVES: To investigate: (i) the chronicity and phasic variability of sleep patterns and restriction in recruits during basic military training (BMT); and (ii) identify subjective sleep quality in young adult recruits prior to entry into BMT. DESIGN: Prospective observational study. METHODS: Sleep was monitored using wrist-worn actigraphy in Army recruits (n = 57, 18-43 y) throughout 12-weeks of BMT. The Pittsburgh Sleep Quality Index (PSQI) was completed in the first week of training to provide a subjective estimate of pre-BMT sleep patterns. A mixed-effects model was used to compare week-to-week and training phase (Orientation, Development, Field, Drill) differences for rates of sub-optimal sleep (6-7 h), sleep restriction (≤6 h), and actigraphy recorded sleep measures. RESULTS: Sleep duration was 06:24 ±â€¯00:18h (mean ±â€¯SD) during BMT with all recruits experiencing sub-optimal sleep and 42% (n = 24) were sleep restricted for ≥2 consecutive weeks. During Field, sleep duration (06:06 ±â€¯00:36h) and efficiency (71 ±â€¯6%; p < 0.01) were reduced by 15-18 min (minimum - maximum) and 7-8% respectively; whereas, sleep latency (30 ±â€¯15 min), wake after sleep onset (121 ±â€¯23 min), sleep fragmentation index (41 ±â€¯4%) and average awakening length (6.5 ±â€¯1.6 min) were greater than non-Field phases (p < 0.01) by 16-18 min, 28-33 min, 8-10% and 2.5-3 min respectively. Pre-BMT global PSQI score was 5 ±â€¯3, sleep duration and efficiency were 7.4 ±â€¯1.3 h and 88 ±â€¯9% respectively. Sleep schedule was highly variable at pre-BMT (bedtime: 22:34 ±â€¯7:46 h; wake time: 6:59 ±â€¯1:42 h) unlike BMT (2200-0600 h). CONCLUSIONS: The chronicity of sub-optimal sleep and sleep restriction is substantial during BMT and increased training demands exacerbate sleep disruption. Exploration of sleep strategies (e.g. napping, night-time routine) are required to mitigate sleep-associated performance detriments and maladaptive outcomes during BMT.

The physiological demand of a task simulation varies when developed by independent groups of experiential experts.

OBJECTIVE: To investigate the disparity in the specification and physiological demand of a task simulation when developed by two independent panels of experiential experts. DESIGN: Independent groups design. METHODS: Two groups of experiential experts from the Royal Australian Air Force (RAAF) worked independently to design, and then complete a simulation of a generic occupational task; the establishment of a security control point. Task duration, oxygen consumption, and cardiac frequency were measured whilst each panel completed the task simulation. Maximal acceptable work duration (MAWD) and the percentage of MAWD (%MAWD) were also calculated. Independent t-tests were used to determine differences (P < 0.05) between the measured variables. RESULTS: No differences were observed in the average oxygen consumption (1.26 ± 0.25 L min-1 and 1.28 ± 0.29 L min-1 respectively; P = 0.84), or cardiac frequency (134 ± 16.4 beats·min-1 and 125 ± 8.5 beats·min-1 respectively; P = 0.12) between Panel 1 and Panel 2. However, there was a significant difference between panels with respect to task duration (Panel 1: 15.5 ± 3.68 min; Panel 2: 34.20 ± 9.60 min; P < 0.01), and the %MAWD (Panel 1: 5.32 ± 3.17%, Panel 2: 12.15 ± 9.40%, P = 0.04). CONCLUSIONS: The physiological demand of a task simulation is dependent upon the group of experts consulted to develop the simulation. It is critical that input from a wide representation of experiential experts is considered when developing task simulations to avoid bias towards the perceptions of the experts consulted.

Sleep of recruits throughout basic military training and its relationships with stress, recovery, and fatigue.

OBJECTIVE: Studies in basic military training (BMT) examining sleep are largely cross-sectional, and do not investigate relationships between sleep, stress, recovery and fatigue. The aims of this study were to (1a) quantify changes in recruits' sleep quantity and quality over 12 weeks of BMT; (1b) quantify changes in recruits' perceptions of stress, fatigue and recovery over BMT; and (2) explore relationships between sleep, and perceptions of stress, fatigue and recovery. METHODS: 45 recruits (37 male; 8 female, age: 25.2 ± 7.2 years, height: 176.2 ± 10.0 cm, mass: 76.8 ± 15.0 kg) wore ActiGraph GT9X's for 12 weeks of BMT, collecting sleep duration, efficiency and awakenings. Subjective sleep quality, fatigue were measured daily, with stress and recovery measured weekly. Multi-level models assessed relationships between sleep, and stress, recovery, and fatigue. RESULTS: Objective daily means for sleep duration were 6.3 h (± 1.2 h) and 85.6% (± 5.5%) for sleep efficiency. Main effects were detected for all mean weekly values (p < 0.05). Sleep quality showed the strongest relationships with stress, recovery and fatigue. The best model to explain relationships between, stress, recovery and fatigue, included sleep quality, sleep duration, sleep efficiency and awakenings. CONCLUSIONS: The reported mean sleep duration of 6.3 h per night may negatively impact training outcomes across BMT. Combining both subjective and objective measures of sleep best explained relationships between sleep metrics stress, fatigue and recovery. Perceived sleep quality was most strongly related to change in stress, recovery, or post-sleep fatigue.

Comparison of Military Recruit and Incumbent Physical Characteristics and Performance: Potential Implications for Through-Career Individual Readiness and Occupational Performance.

ABSTRACT: Drain, JR, Debenedictis, T, Bulmer, S, and Michael, S. comparison of military recruit and incumbent physical characteristics and performance: Potential implications for through-career individual readiness and occupational performance. J Strength Cond Res 36(9): 2536-2543, 2022-After basic military training, physical training practices among incumbent personnel differ substantially, potentially precipitating varied physical capacity and operational readiness. The purpose of this retrospective investigation was to compare physical characteristics and physical performance between recruits and incumbent personnel. Data were collected for 222 army recruits (REC: 197 men/25 women) nearing completion of basic training and 280 incumbent army personnel from combat arms (CA: 142 men) and noncombat arms trades (NCA: 113 men/25 women). Height, mass, and body mass index (BMI) were recorded together with performance measures including predicted V̇ o2 max and 1 repetition maximum box lift. Compared with REC, male incumbents were older (21.8 ± 0.6 vs. 27.6 ± 1.2 years; mean ± 95% confidence interval), had greater body mass (77.6 ± 1.3 vs. 82.6 ± 1.5 kg) and BMI (24.2 ± 0.3 vs. 25.8 ± 0.5 kg·m -2 ), similar relative V̇ o2 max, and lower box lift (49.7 ± 1.4 vs. 47.2 ± 2.4 kg). Male CA demonstrated greatest physical performance while male NCA demonstrated the highest BMI and poorest physical performance. Compared with REC, female incumbents were older (22.8 ± 1.6 vs. 31.9 ± 4.4 years), had similar body mass, higher BMI (24.1 ± 0.7 vs. 26.1 ± 2.4 kg·m -2 ), as well as lower V̇ o2 max (42.0 ± 1.3 vs. 37.9 ± 2.1 ml·kg· -1 ·min -1 ) and box lift (27.8 ± 2.1 vs. 23.3 ± 2.4 kg). More than 97% of men and approximately 75% of women were able to achieve the box lift and V̇ o2 max baseline standards. The older age category (26 + vs. 18-25 years) typically demonstrated higher BMI and lower physical performance. Through-career maintenance of physical capacity is important for military personnel to support individual readiness and occupational performance, preserve health, and mitigate musculoskeletal injury risk.

The influence of a basic military training diet on whole blood fatty acid profile and the Omega-3 Index of Australian Army recruits.

This study described the whole blood fatty acid profile and Omega-3 Index (O3I) of Australian Army recruits at the commencement and completion of basic military training (BMT). Eighty males (17-34 y, 77.4 ± 13.0 kg, 43.5 ± 4.3 mL/kg/min) and 37 females (17-45 y, 64.3 ± 8.8 kg, 39.3 ± 2.7 mL/kg/min) volunteered to participate (N = 117). Whole blood samples of each recruit were collected using a finger prick in weeks 1 and 11 (n = 82) and analysed via gas chromatography for the relative proportions of each fatty acid (mean [95% confidence interval]). The macronutrient characteristics of the diet offerings was also determined. At commencement there was a low omega-3 status (sum of omega-3; 4.95% [4.82-5.07]) and O3I (5.03% [4.90-5.16]) and no recruit recorded an O3I >8% (desirable). The omega-6/omega-3 (7.04 [6.85-7.23]) and arachidonic acid/eicosapentaenoic acid (AA/EPA) (18.70 [17.86-19.53]) ratios for the cohort were also undesirable. The BMT mess menu provided a maximum of 190 mg/day of EPA and 260 mg/day of docosahexaenoic acid (DHA). The O3I of the recruits was lower by week 11 (4.62% [4.51-4.78], p < 0.05), the omega-6/omega-3 increased (7.27 [7.07-7.47], p < 0.05) and the AA/EPA remained elevated (17.85 [16.89-18.81]). In conclusion, Australian Army recruits' omega-3 status remained undesirable during BMT and deserves nutritional attention. Novelty: Australian Army recruits' Omega-3 Index, at the commencement of BMT, was reflective of the Western-style diet. The BMT diet offered minimum opportunity for daily EPA and DHA consumption. Every recruit experienced a further reduction of their Omega-3 Index during BMT.

Monitoring work and training load in military settings - what's in the toolbox?

Military personnel are required to complete physically demanding tasks when performing work and training, which may be quantified through the physical stress imposed (external load) or the resultant physiological strain (internal load). The aim of this narrative review is to provide an overview of the techniques used to monitor work and training load in military settings, summarise key findings, and discuss important practical, analytical, and conceptual considerations. Most investigations have focused upon measuring external and internal load in military training environments; however, limited data exist in operational settings. Accelerometry has been the primary tool used to estimate external load, with heart rate commonly used to quantify internal load. Supplemental to heart rate, psychophysiological and biochemical measures have also been investigated to elucidate aspects of internal load. Broadly, investigations have revealed that military training requires personnel to perform relatively large volumes of physical activity (e.g. averaging ∼15,000 steps·day-1) of typically low-moderate intensity activity (<6 MET), although considerable temporal and inter-individual variability is observed from these gross mean estimates. There are limitations associated with these measures and, at best, estimates of external and internal load can only be inferred. These limitations are particularly pertinent for military tasks such as load carriage and manual material handling, which often involve complex activities performed individually or in teams, in a range of operational environments, with multiple layers of protection, over a protracted duration. Comprehensively quantifying external and internal loads during these functional activities poses substantial practical and analytical challenges.

Is muscular strength a critical physical attribute for the apprehension of a simulated non-compliant suspect?

This investigation determined the influence of technique and experience on arm retraction force required to apprehend a non-compliant suspect. Phase-One: Nine experienced RAAF military-police completed four apprehension simulations, peak arm retraction force was measured; i) Control(CON), ii) Pressure-Point(PP), iii) Targeted-Striking(TS) and iv) 2-Person(2Per) techniques. Phase-Two: Experienced (EXP, n = 8) or Inexperienced (INEXP, n = 22) military-police completed CON, PP and Pressure-Point + Coaching(PP + C). Strength was assessed in INEXP. EXP produced more force (178.7 N ± 25.9) than INEXP during CON, but no participant successfully apprehended the suspect. All EXP were successful with PP, arm retraction force 357 N (CI: 233.7,480.2) was lower compared to CON, but no difference was observed between PP and CON for INEXP. PP + C, 82% of INEXP were successful, force declined 138.2 N (CI: 67.8,208.5) compared to CON. All EXP required PP for successful apprehension. INEXP required PP + C for apprehension success. Muscular strength had a limited relationship with arm retraction force. Practitioner summary: For law enforcement personnel, apprehension of a suspect is a critical and physically demanding task, where success is associated with muscular strength and technique. We observed success in the apprehension of a simulated suspect by military law enforcement personnel was primarily determined by participant skill and experience and not muscular strength.

Associations between inflammatory markers and well-being during 12 weeks of basic military training.

PURPOSE: Stress, anxiety and physical exertion are all closely linked to well-being, and each can alter immune function. Diminished well-being has been observed during military training, however there is mixed evidence regarding whether concomitant changes in inflammatory markers occur, with these phenomena indicating potential maladaptive responses to imposed training loads. The aims of this project were (1) assess changes in inflammation and subjective well-being across a 12-week basic military training (BMT) program, and (2) evaluate relationships between circulating inflammatory markers and well-being. METHODS: A total of 37 men and women undergoing 12 weeks of BMT in Australia were recruited. Well-being was assessed via questionnaire (DASS-21), and plasma samples were collected for the analysis of inflammatory cytokines [interleukin (IL)-4, IL-6, IL-1ß, IL-8, IL-10, and tumor necrosis factor (TNF)-α] at weeks 1, 4, 8 and 12. Data were analysed using general linear mixed models. RESULTS: Depression, anxiety and stress subscale scores all significantly improved (all P ≤ 0.001), and TNF-α decreased (P = 0.031) across time. Compared to baseline (week 1), significant decreases in associations between depression and IL-10, anxiety and IL-10, and stress and IL-10, IL-4 IL-6 and TNF-α (all P < 0.05), were detected across BMT. CONCLUSION: The BMT program appears to support improved well-being over the 12 weeks, with minimal perturbation to inflammatory markers. Biomarkers and well-being displayed consistent associations and may have utility as psychophysiological indicators of health status in military research, however for now, subjective measures may represent more cost-effective proxies for ongoing monitoring of military personnel.

Treadmill load carriage overestimates energy expenditure of overground load carriage.

This study compared physiological and biomechanical responses between treadmill and overground load carriage. Thirty adults completed six 10-minute walking trials across three loads (0, 20, and 40% body mass) and two surfaces (treadmill and overground). Relative oxygen consumption was significantly greater on the treadmill for 20% (1.54 ± 0.20 mL⋅kg-1⋅min-1) and 40% loads (1.08 ± 0.20 mL⋅kg-1⋅min-1). All other physiological and perceptual responses were significantly higher in the treadmill condition and with increases in load. Stance time was longer (0%: 0.05 s; 20%: 0.02 s, 40%: 0.05 s, p < 0.001) and cadence was lower (0%: 1 step·min-1; 20%: 2 steps·min-1; 40%: 3 steps·min-1, p < 0.05) on the treadmill. Peak lower limb joint angles were similar between surfaces except for ankle plantar flexion, which was 8˚ greater on the treadmill. The physiological responses to treadmill-based load carriage are generally not transferable to overground load carriage and caution must be taken when conducting treadmill-based load carriage research to inform operational-based scenarios. Practitioner Summary: Literature is limited when comparing the physiological and biomechanical responses to treadmill and overground load carriage. Using a repeated measures design, it was shown that although walking kinematics are generally similar between surfaces, there was a greater physiological demand while carrying a load on a treadmill when compared with overground. Abbreviations: BM: body mass; e.g: for example; HR: heart rate; HRmax: heart rate maximum; Hz: hertz; kg: kilograms; km·h-1: kilometres per hour; L⋅min-1: litres per minute; m: metres; MD: mean difference; mL·kg-1·min-1: millilitres per kilogram per minute; mL⋅min-1: millilitres per minute; η2p: partial-eta squared; OG: overground; RPE: rating of perceived exertion; s: seconds; SD: standard deviation; SE: standard error; steps·min-1: steps per minute; TM: treadmill; V̇CO2: volume of carbon dioxide; V̇E: ventilation; V̇O2: volume of oxygen; V̇O2max: maximum volume of oxygen; y: years.