Abstract
Tactical populations, inclusive of firefighters, military, and law enforcement, play a significant role in maintaining the safety and well-being of the general public. Tactical personnel face unique occupational demands that result in an increased risk of injury. Injuries in these populations have multiple downstream effects, such as increased risk of further injury, time away from work, and higher organisational costs. Adequate physical fitness is vital to ensure that the physically demanding occupational tasks undertaken by this population (e.g., suspect pursuit, victim drag, load carriage) are performed effectively. Furthermore, physical fitness has been demonstrated to assist in maintaining long term physical and mental health of personnel. Training and methods to increase physical fitness, while resulting in positive benefits, are also a means of increasing injury risk. It is therefore necessary to identify strategies to balance the positive (e.g., improved physical fitness, health benefits) and negative (e.g., injury risk) of physical training.Methodologies which aim to reduce injury risk while improving physical fitness are of vital importance to both tactical populations and the general public which they aim to protect. Optimal training load, one which enhances fitness while not exposing individuals to unnecessarily high injury risk, is an important element in training tactical personnel. Monitoring training load is crucial to ensure an appropriate level for positive adaptation, while not being too excessive to pose as a source of injury risk itself. The tracking of training load is possible through a variety of methods, with many seeing growing popularity in the sporting realm, due to their ability to decrease injury risk and enhance fitness development. Despite the growing popularity in the sporting world, little research has explored these options in depth within tactical populations. Given the known differences between athletes and tactical personnel, it is unclear if this sports-based training load monitoring approach would be suitable for implementation within tactical contexts. The aim of this thesis was to explore the potential for the use of training load monitoring systems currently utilised by sport teams within tactical populations. The overarching research question posed was what impact training load had on injury risk in tactical personnel and, if training load was found to have an effect, how could tactical populations pragmatically optimise training load. To answer this question a series of studies were developed.
Chapters I and II provide an introduction to the research topic and overview of this thesis, respectively. A narrative review, which explored the concept of tracking training load in tactical populations, was conducted and is reported in Chapter III. The narrative review notes that methods to optimise training load have existed throughout history, such as the use of periodisation (manipulation of training volume and intensity) within strength and conditioning programs. Recently, this training load management approach has progressed to the monitoring and adjustment of training programs based on individual variables while incorporating a multitude of tracking tools (e.g., Global Positioning System (GPS) devices, heart rate monitors, and subjective questionnaires). The Acute:Chronic Workload Ratio (ACWR), one method to track these variables, is noted as having gained popularity in the sports world. ACWRs relates a longer term (chronic) training load based on a 3-6 week rolling average to a short term (acute) training load based on the most recent training week.
To investigate relationships between the ACWR and injury risk a systematic review, reported in Chapter IV, was conducted. The review found that while the ACWR had significant relationships to injury risk, high levels of variability were found within the research. These variations included various methods of reporting injury risk, (e.g., relative risk and odds ratios), application of the ACWR to different variables (e.g., total distance, high-speed running distance, and acceleration efforts), and a lack of consistency when reporting ACWR ranges. In the two years following publication of the systematic review further research has been conducted on the ACWR discussing its methodological limitations, which are explored in Chapter V. The ACWR suffers from conceptual flaws that detract from its ability to predict injury risk, as well as statistical faults that can lead to a high rate of Type 1 errors (false positives). Additionally, the ACWR is constructed in a way where results won’t be seen until the fifth week of training, potentially limiting its impact in tactical populations with short training academies.
To explore the potential for load monitoring systems to be utilised in tactical populations, both prospective and retrospective data were collected from a law enforcement academy. The three key variables of load monitoring systems (training load, fitness, and injuries) are profiled within Chapters VI, VII, and VIII respectively. Chapter VI profiled the typical training load of a law enforcement recruit class. Utilising a linear mixed model, this chapter demonstrated the total distance covered significantly increased from Week 1 and Weeks 2 (mean difference = 9.65 km, p-value < 0.01), 3 (9.64 km, < 0.01), 4 (11.65 km, < 0.01), 5 (9.69 km, < 0.01), and 6 (10.07 km, < 0.01). It was also found that increases in physical training occurred during the first five weeks of law enforcement academy training, rising from zero hours of training to between three and six hours per week. The majority of training was found to be aerobic (low intensity, long duration) and multi-modal (a combination of aerobic, anaerobic and muscular conditioning).
Chapter VII profiled the fitness changes of recruits (n = 715) and concluded that under the current academy training program, recruits significantly improved their physical fitness by the end of the academy period. Compared to muscular strength and power, larger improvements were seen in muscular endurance and aerobic conditioning, likely due to physical training programs focusing on methods of training that facilitate improvements in these fitness measures. A profile of recruit injuries (n = 4340) was conducted in Chapter VIII, demonstrating that 76.1% of injuries were musculoskeletal (i.e., damage to ligaments and muscular injuries), commonly affecting the lower limb (47.9%). These injuries occurred most often during physical training and defensive tactics (75.8%), with a high number of injuries (33.9%) happening during the first five weeks of academy training, particularly Week 2 (10.9%). These chapters suggest a relationship between the current training load of recruits and injuries suffered, with sizeable changes in distance covered and physical training hours corresponding with large amounts of injuries occurring during the early stages of academy training.
Chapters IX and X discuss the further exploration of the relationship between training load and injury risk and includes a more in-depth analysis of the change in fitness in this population. Chapter IX presents the results of a generalised linear mixed model examining training load and injury risk. Distance covered was a variable of interest, given that the most common injuries occurred due to repetitive loading of the lower limb. The results of this model found that distance covered per week (OR [95%CI] = 1.08 [1.04, 1.12]), week of training (0.94 [0.91, 0.98]), and sex (0.55 [0.34, 0.91]) were significantly associated with injury risk. While fitness was not a significant predictor of injury in the model reported in Chapter IX, Chapter X discusses how recruits who started the academy with lower initial physical fitness were able to experience greater levels of fitness improvement (determined by effect size) when compared to recruits with higher initial fitness levels. Recruits with higher initial fitness may have failed to improve in their respective measures of fitness due to a sub-standard training load (in relation to their higher levels of fitness) and, as such, require a higher workload to see larger improvements in physical fitness. The current training structure utilises an “one size fits no one” group training approach that applies a standard training load to a population of varying fitness levels. This may under-stimulate recruits with high fitness and overtrain recruits with lower levels of fitness. Identification of an optimal and more individualised training load ensures a fit and effective working force while mitigating the negative occupational and individual effects of injuries.
There are several findings of note from this thesis. The current, group-based training method, with a focus on aerobic conditioning and multimodal training elicits positive adaptations in aerobic fitness of law enforcement recruits. These adaptations are greater in those with less fitness, and lower for those who possessed greater levels of fitness upon entry to the academy. Injuries occurred most commonly to the lower limb and were soft tissue in nature. These injuries were commonly suffered during physical training and defensive tactics training, where large distances were covered.
A training load monitoring system such as the ACWR is not suitable for this population; its shortcomings are discussed in Chapter V. Of note, is the ACWR’s inability to capture the beginning of academy training where injuries most often occur, potentially due to the transition from civilian to academy life. Furthermore, utilising a system which relies on individual load monitoring, such as GPS analysis, heart rate telemetry, or subjective ratings may also not be cost, resource or time effective in this environment.
Despite these shortcomings, using distance as a variable of load monitoring enabled a model to be created whereby distances over 30km led to a higher risk of injury within this population. Several recommendations have arisen based on the research findings, which, while specific to the population studied, can be applied across multiple tactical populations.
Adjustment of the current group training methodology in tactical populations may provide a more optimal training load. These adjustments can contain appropriate principles of population-specific periodisation, allowing for a smooth progression of training, and the use of ability-based training, where recruits are given a training stimulus corresponding to their fitness level and provided a more individualised program. Incorporating the use of population-specific periodisation and ability-based training programs may be viable options for academies to provide a more optimal training load across a large number of recruits with various levels of physical fitness. The use of alternative means of training, including interval, strength, power, and speed training may enable enhancement of other occupationally important fitness attributes while concurrently decreasing overall distance covered and therefore contributing to injury risk mitigation. The upskilling of current academy staff on these principles, and use of certified strength and conditioning professionals could further improve the effectiveness of these strategies. The utilisation of these principles could potentially reduce injury risk while increasing fitness levels among law enforcement recruits. Given the inherent differences between tactical populations, further research will need to be conducted to analyse how these strategies can be specifically applied to currently serving law enforcement officers, as well as military and fire
| Date of Award | 15 Jun 2022 |
|---|---|
| Original language | English |
| Supervisor | Ben Schram (Supervisor), Elisa Fontenelle Dumans Canetti (Supervisor) & Rob Orr (Supervisor) |