Graduation-stage physical fitness as a predictor of operational performance and injury risk among police recruits: a prospective cohort study

Abstract

Objectives

This study examined whether physical fitness at the point of police academy graduation predicts early-career outcomes, including job performance and musculoskeletal injury risk.

Methods

In a 12-month prospective cohort study, 240 police recruits (74.2% male; mean age 22.1 years) were assessed during the final week of academy training. Graduation-stage fitness was summarised by a composite fitness index (0–100; higher=better) from sex-standardised domain scores. Job performance was assessed using the Behaviourally Anchored Rating Scale (BARS) at 12 months, while injury incidence was monitored via official records, compensation claims and self-reported events. Multivariable linear regression and Cox proportional hazards models were used to examine associations, adjusting for age, sex, body mass index, baseline physical activity (measured by International Physical Activity Questionnaire–Short Form) and pre-existing musculoskeletal conditions.

Results

Graduation-stage fitness significantly predicted BARS-rated job performance (β=0.21; 95% CI 0.12 to 0.30; p<0.001), with specific effects in communication (p=0.042) and use-of-force judgement (p=0.017). Each 1-point increase in fitness score was associated with an 11% reduction in injury hazard (HR 0.89; 95% CI 0.83 to 0.95; p<0.001). High-fitness recruits remained injury-free significantly longer (median 9 vs 4 months; log-rank p<0.001).

Conclusions

Graduation-stage physical fitness is a strong and actionable predictor of early-career success and injury resilience in law enforcement. These findings support incorporating fitness assessments at academy exit into operational readiness protocols, guiding evidence-based deployment decisions and targeted postacademy conditioning programmes.

WHAT IS ALREADY KNOWN ON THIS TOPIC

• Prior research has established that physical fitness is an essential factor for police officer performance and injury prevention. However, most studies have focused on entry-level fitness assessments, which fail to capture the dynamic nature of post-training adaptations and their relationship with real-world performance outcomes.

WHAT THIS STUDY ADDS

• This study demonstrates that graduation-stage fitness, assessed after 10 months of academy training, is a strong predictor of early-career job performance and injury risk in law enforcement recruits. Superior fitness at graduation was significantly associated with higher Behaviourally Anchored Rating Scale ratings and longer injury-free intervals.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

• These findings suggest that post-training fitness assessments could be integrated into police recruitment and training protocols to better predict deployment readiness and reduce injury risk. This approach may inform more effective, data-driven fitness standards and interventions within law enforcement agencies.

Introduction

Police officers operate in dynamic, high-stakes environments requiring sustained physical exertion and critical decision-making under pressure. Core duties such as pursuing suspects, executing high-risk warrants and responding to emergencies demand proficiency in muscular endurance (eg, sustained hands-on control and load carriage), aerobic fitness, agility and coordination.^{1 2} These physical challenges contribute to a high prevalence of musculoskeletal injuries, particularly in the back, shoulders and lower extremities, resulting in reduced operational capacity and increased institutional costs.^{3 4}

To mitigate these risks and enhance operational readiness, police academies have instituted structured physical training programmes targeting muscular endurance, aerobic fitness, muscular power, speed and flexibility. Empirical studies confirm that baseline physical fitness predicts successful academy completion, with measures such as timed runs and push-up counts correlating with training outcomes.^{5 6} However, while entry-level fitness assessments are widely used, their predictive validity for long-term occupational outcomes remains limited.

The Tactical Athlete Framework conceptualises police officers as occupational athletes who must meet both physical and cognitive demands.^{7 8} Within this model, physical fitness is considered an operational resource akin to situational awareness and technical skill. Studies have shown that higher levels of physical conditioning are associated with superior performance in policing tasks, ^{9 10} aligning with the Job Demands-Resources (JD-R) Model, which posits that personal resources buffer job demands and enhance resilience.¹¹

Despite this, the literature disproportionately focuses on entry-level assessments, often neglecting the dynamic adaptations resulting from academy training. Entry tests primarily evaluate current performance for academy suitability and risk stratification and may not capture variability in training response, motivation or resilience.¹² Many academy assessments rely on isolated physiological components rather than integrated task simulations. In this study, we leveraged the graduation-stage timing and prospective follow-up to evaluate how these standard components predict real-world outcomes, while recognising that validated task-specific simulations would further strengthen ecological validity. Academy entry assessments are designed to evaluate immediate suitability, stratify near-term injury risk and inform training prescription within the academy, rather than to predict long-term occupational outcomes.^{13 14}

We, therefore, focus on graduation-stage fitness, capturing both initial capacity and training adaptation, as the predictor of first-year outcomes. Graduation-stage tests mirror operational demands (eg, sprint speed for foot pursuits, lower-limb power for obstacle negotiation and muscular endurance for sustained hands-on control), providing an ecologically valid indicator of job readiness.^{8 15} These assessments encompass improvements in neuromuscular coordination, endurance and functional strength, factors critical to operational performance. Yet few studies have adopted longitudinal designs capable of tracking fitness outcomes from academy graduation through field deployment.¹⁶

Injury risk during early service is another critical concern.¹⁷ Musculoskeletal injuries are prevalent among new officers, often stemming from abrupt movements, load carriage and slips during pursuits.18,20 Approximately 89% of such injuries involve sprains and strains in the back, knees or shoulders.²¹ Higher fitness levels, particularly aerobic capacity and muscular strength, are inversely associated with injury incidence.^{20 22 23}

However, most injury prediction models rely on entry or mid-training data, failing to capture the protective value of graduation-stage fitness.²⁴ This omission is especially problematic given that injury rates often peak in the initial months of service due to increased physical and psychological stressors.^{25 26}

Our primary objective was to test whether graduation-stage fitness predicts injury risk and job performance during the first year of deployment. We did not intend to estimate academy training effects (ie, pre–post change), and standardised entry-level performance tests were not consistently available across cohorts. Accordingly, all inferences pertain to the predictive value at graduation, not to within-academy improvements.

The present study addresses these limitations through a prospective, multisource, longitudinal design examining whether physical fitness at police academy graduation predicts two key outcomes during the first year of service: (1) job performance, as evaluated via the Behaviourally Anchored Rating Scale (BARS) and (2) musculoskeletal injury incidence and timing. Our conceptual framework, grounded in the Tactical Athlete and JD–R perspectives, conceptualises graduation-stage fitness as a modifiable operational resource with direct effects on first-year job performance (BARS) and time to first musculoskeletal injury, while early-career policing demands (eg, workload, shift schedules, acute stressors) potentially moderate these paths (figure 1). Because these contextual variables were not harmonised in this cohort, they were not entered in the statistical models and are depicted as dashed arrows in figure 1.

Figure 1. Conceptual framework for the predictive role of graduation-stage physical fitness in early-career police outcomes. Graduation-stage fitness is specified to have direct effects on two endpoints during the first 12 months of deployment: job performance (BARS) and time to first musculoskeletal injury. Early-career policing context (eg, workload, shift schedules, acute stressors) is shown as a potential moderator (dashed arrows); these contextual variables were not harmonised in this cohort and were not included in statistical models. BARS, Behaviourally Anchored Rating Scale; JD-R, Job Demands-Resources.

This investigation tests two primary hypotheses: (1) Higher graduation-stage fitness scores predict superior first-year job performance and (2) Higher graduation-stage fitness is associated with reduced injury risk and longer injury-free intervals.

By clarifying the role of post-training physical fitness in occupational success and resilience, this study contributes to the optimisation of police recruitment, training standards and injury prevention strategies grounded in empirical evidence.

Methods

Research design

This study employed a prospective, longitudinal cohort design to evaluate whether physical fitness at the point of police academy graduation serves as a reliable predictor of two key early-career outcomes: (1) job performance and (2) musculoskeletal injury incidence during the first year of active-duty service. This study assessed physical readiness at the point of academy completion, allowing us to explore the relationship between predictor variables and outcomes over time, addressing the limitations of previous cross-sectional studies.

Graduation-stage physical fitness was assessed during the final week of the standardised 10-month training programme using a nationally normed, multi-component test battery. Baseline physical activity was measured via the International Physical Activity Questionnaire–Short Form (IPAQ-SF) at the time of academy entry to capture pretraining activity levels. In this manuscript, ‘baseline’ denotes academy entry. Entry-stage performance test results were not harmonised across cohorts and thus were not analysed; our predictive models use graduation-stage fitness as the exposure and adjust for entry-stage physical activity (IPAQ-SF) as a behavioural covariate. Participants were subsequently followed for 12 months following deployment to operational units.

Job performance was assessed twice during the follow-up period (6 and 12 months postgraduation) using the BARS, completed by supervisors who were unaware of fitness status. Injury data were triangulated from three independent sources: (1) official departmental injury logs; (2) workers’ compensation records and (3) quarterly self-reported injury surveys. Detailed anchors, scoring rubric and pilot reliability (internal consistency, inter-rater) are provided in online supplemental S1.

To control for confounding, additional variables were documented at baseline, including age, sex, body mass index (BMI), baseline physical activity and medical clearance status, defined as the presence of any pre-existing musculoskeletal condition at the time of academy entry.

The study was non-interventional and relied exclusively on routinely collected administrative and observational data within institutional contexts.

This design is theoretically grounded in the Tactical Athlete Framework and aligns with the conceptual model outlined in figure 1, wherein post-training fitness is positioned as a core determinant of occupational readiness and resilience. We apply the Tactical Athlete perspective as a multidomain readiness model encompassing cardiorespiratory, neuromuscular, mobility and load-carriage demands pertinent to policing.

Participants and recruitment

Participants were recruited from a provincial-level police academy in eastern China. Eligibility criteria were designed to ensure baseline homogeneity in health status and training exposure. Inclusion criteria were: (1) aged between 21 and 23 years; (2) no prior diagnosis of musculoskeletal, cardiovascular or chronic medical conditions; (3) enrolled in the 10-month standardised academy programme and (4) provision of informed consent for a 12-month follow-up postgraduation. Sex (male/female) was recorded at enrolment and used as a covariate in adjusted analyses.

Exclusion criteria included incomplete training records or active functional limitations that could confound fitness or injury outcomes or preclude safe participation. Pre-existing musculoskeletal conditions at academy entry did not constitute an exclusion if medically cleared; medical clearance status (presence/absence of any pre-existing musculoskeletal condition at entry) was recorded and included as a covariate in the final models.

A priori sample size was calculated in G*Power (V.3.1), targeting a small to moderate effect size (f=0.20), α=0.05, and power (1—β) = 0.80 for a linear regression with five covariates, yielding a minimum of 199 recruits. To allow for a 15% attrition rate, informed by published police-academy cohorts, we enrolled 240 recruits via consecutive convenience sampling.

Recruitment was conducted during the penultimate month of academy training, coordinated by institutional personnel. All eligible recruits attended a standardised orientation session that included a verbal briefing, written consent and the opportunity for individual consultation. To improve demographic representation and generalisability, participants were stratified by sex at enrolment.

To reduce attrition and ensure data completeness, multiple retention strategies were implemented, including periodic digital reminders, access to individualised fitness progress summaries and assurance of confidentiality. The full cohort was prospectively monitored from graduation/deployment (T₀) to 12 months postdeployment (T₄), with data collected at five predefined intervals (see figure 2). Time 0 (T₀) was defined as the date of graduation/deployment; all participants were observed for 12 months from T₀ (right-censoring at 12 months).

Figure 2. Research flow chart and assessment timeline. T₀ denotes graduation/deployment; all participants were observed for 12 months from T₀ with right-censoring at 12 months. Fitness was assessed in the final week of the academy; BARS was collected at 6 and 12 months; injuries were ascertained continuously and summarised at 3/6/9/12 months. BARS, Behaviourally Anchored Rating Scale; BMI, body mass index; IPAQ, International Physical Activity Questionnaire.

Measures and variables

Graduation-stage physical fitness

Graduation-stage physical fitness, the primary independent variable, was assessed during the final week of the 10-month police academy programme. A standardised, multicomponent battery was administered in accordance with the National Student Physical Fitness Standards of China. The battery comprised seven components reflecting distinct physical domains: (1) BMI (kg/m²); (2) vital capacity assessed via calibrated spirometry (mL); (3) 50 m sprint time (s) for speed; (4) sit-and-reach (cm) for flexibility; (5) standing long jump (cm) for lower-limb explosive power; (6) muscular endurance (sex-specific): pull-ups (repetitions; males) indexing upper-body pulling muscular endurance (and relative strength) and 1 min sit-ups (repetitions; females) indexing trunk flexor (core) muscular endurance; (7) aerobic endurance: 1000 m run (males) or 800 m run (females).

Each component was scored using sex-specific national norms, and scores were rescaled to generate a composite fitness index ranging from 0 to 100. Based on composite scores, participants were classified into four categories: excellent (≥90), good (80–89), pass (60–79) and fail (<60). All assessments were conducted under standardised laboratory-like conditions by trained personnel using calibrated equipment. Inter-rater reliability exceeded ICC=0.90, based on pilot evaluations conducted at the same institution. These standardised components complement, rather than replace, integrated task simulations; in this cohort, only the academy’s standardised battery was available, and we, therefore, examined its graduation-stage predictive validity for field outcomes.

Testing protocol and scoring: All assessments were conducted in a single morning session in an indoor facility after a standardised warm-up, which included a 10 min light jog and dynamic mobility exercises. The testing order was as follows: height/weight (BMI), vital capacity, sit-and-reach, 50 m sprint, standing long jump, muscular endurance (sex-specific) and the timed run (1000 m for males and 800 m for females). Recovery between attempts was at least 3 min. Trials and scoring: For vital capacity, two trials were performed and the best value was used. For the sit-and-reach, two trials were done, and the best measurement was recorded. The 50 m sprint was performed twice, and the lowest time was used (reverse-coded). Standing long jump was conducted with two trials, and the best jump was recorded. Pull-ups were assessed with a single maximal-repetition trial for males. Females performed a 1 min timed sit-up test. For the run, only one timed trial was conducted (reverse-coded). All equipment was calibrated before testing.

Job performance

Occupational performance was evaluated at 6 months (T₂) and 12 months (T₄) postdeployment using a customised BARS, developed in collaboration with senior field supervisors. The BARS includes six core dimensions: (1) operational decision-making, (2) situational awareness, (3) communication, (4) teamwork and coordination, (5) stress resilience and (6) use-of-force judgement.²⁷ Each domain was rated on a 5-point Likert scale (1=unsatisfactory, 5=outstanding), with the total BARS score ranging from 6 to 30. Rating anchors were based on empirically derived behavioural descriptors relevant to field operations.

Instrument validity was verified via expert panel review (n=5), and a pilot cohort at the same academy (n=20) confirmed strong internal consistency (Cronbach’s α=0.84) and inter-rater reliability (ICC_(2,k) = 0.86; two-way random, absolute agreement, average-measures). Pilot participants were operational patrol officers rated by their direct supervisors using draft anchors. Detailed anchors and the pilot rubric are provided in online supplemental S1. These coefficients are consistent with reliability ranges reported in prior policing BARS studies.^{28 29} Detailed anchors and the pilot rubric are provided in online supplemental S1. To minimise observer bias, supervisors were blinded to participants’ fitness status at the time of evaluation. For sensitivity analyses, secondary performance metrics, including response time averages, arrest frequency and disciplinary infractions, were extracted from administrative databases.

Injury incidence

Musculoskeletal injuries sustained during active-duty deployment were tracked using a triangulated surveillance approach, integrating: (1) Official injury reports submitted by supervisors to department records; (2) Workers’ compensation claims processed through formal institutional channels and (3) Quarterly self-report surveys administered at 3, 6, 9 and 12 months (T₁–T₄) to capture unreported or minor injuries.

Injury was operationally defined as any acute or cumulative musculoskeletal condition resulting in one or more of the following: (1) ≥1 day of restricted duty; (2) documented medical consultation and (3) verified physiological impairment.

Data capture and verification: Self-reports used a structured form capturing date, anatomical region, mechanism category (eg, slip/trip/fall, overexertion, blunt contact), duty status and healthcare utilisation. Reports were cross-checked against official logs and compensation claims; discrepancies were resolved by record review or participant contact. ‘Physiological impairment’ required documentation by a physician or physiotherapist (eg, examination findings, imaging or formal work-restriction notes). Severity was classified using an adapted Orchard Sports Injury Classification System scheme (grades I–III) and applied consistently across sources, with adjudication by a study clinician when needed.^{30 31}

Injury outcomes were coded both as a binary variable (injured vs non-injured) and as time-to-event (months to first injury) for Cox regression analysis. To adjust for potential confounding, five covariates were included in all models: age (continuous), sex (male/female), BMI (measured at graduation), baseline physical activity at academy entry (IPAQ-SF; MET-min/week),³² and medical clearance status (presence of any pre-existing musculoskeletal condition at entry). These variables were selected based on prior evidence linking them to physical performance and injury vulnerability in tactical populations.¹

Statistical analysis

All analyses were conducted in SPSS V.28.0 and R V.4.3.1. Descriptive statistics characterised the sample (means, SDs and ranges for continuous variables; counts and percentages for categorical variables). Normality was screened via Shapiro-Wilk tests and Q–Q plots. For non-parametric between-group contrasts, we report the rank-biserial effect size r alongside p values.

Composite fitness construction: Each component was recorded in raw units and z-standardised within sex (time-based tests reverse-coded so higher=better). The composite index was computed as the mean of available domain z-scores (≥80% of components required), excluding BMI (treated as an anthropometric covariate). For interpretability, the composite was linearly rescaled to 0–100 (higher=better). Equal weighting was specified a priori to reflect distinct domains without imposing unverifiable weights. A worked example and domain mapping are provided in online supplemental S2.

Job performance model: To examine the association between graduation-stage fitness and BARS ratings, we fitted multivariable hierarchical linear regression. Block 1 (covariates): age, sex, BMI at graduation, baseline physical activity (IPAQ-SF at academy entry) and history of musculoskeletal condition at entry. Block 2 (predictors of interest): the composite fitness index and domain-specific subscores (eg, aerobic endurance, muscular endurance (sex-specific harmonised), flexibility, sprint, standing long jump, vital capacity). Model diagnostics included VIF (>5), residual plots for homoscedasticity and Cook’s distance. We report adjusted R², standardised β coefficients and 95% CI.

Injury model: To evaluate the relationship between fitness and time-to-first injury, we used Cox proportional hazards models with right-censoring at 12 months. The proportional hazards assumption was verified using Schoenfeld residuals. Results are presented as HR with 95% CI; the composite fitness index is modelled continuously (per 1 SD) as the central predictor. Kaplan-Meier curves were displayed by sample quartiles (Q1–Q4) of the composite fitness index. A complementary dichotomised plot at 80 points (≥80 vs <80) is provided in (online supplemental figure S1). All inferential Cox models treated fitness as a continuous predictor (per 1−SD).

Reporting principle: In the main text, we report the adjusted association for the central predictor and list covariates controlled; full covariate coefficients are provided in (online supplemental table S3). For visualisation, Kaplan-Meier curves by composite-fitness quartile (Q1–Q4) were compared using the log-rank test.

Exploratory sex-stratified models and a sex×composite fitness interaction tested effect modification. Missing data >5% were handled via multiple imputation under a missing at random assumption. All tests were two-tailed (α=0.05). Effect sizes were interpreted using conventional thresholds for occupational health research.^{33 34} We used the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline (1) to draft this manuscript and completed the STROBE checklist and (2) during revision.³⁵ The completed checklist is available as Supplement A. No AI system was used for data processing, statistical analysis or result interpretation.

Results

Descriptive statistics

Of the 240 recruits who completed the graduation fitness assessment, 216 (90.0%) completed the 12-month follow-up (male: 160/178, 74.07%; female: 56/62, 25.93%). Attrition was 10.0% (24/240), due to voluntary withdrawal (n=15) or incomplete follow-up data (n=9); no cases were related to serious injury, minimising attrition bias. Attrition by sex did not differ (male 18/178, 10.1% vs female 6/62, 9.7%; p=0.992). Unless otherwise stated, BARS refers to the average of the 6-month and 12-month ratings.

Over 12 months, 51 participants sustained ≥1 injury. The most frequent types were sprain/strain (22/51; 43.1%) and overuse (12/51; 23.5%), followed by contusion/laceration (9/51; 17.6%); fractures comprised 3/51 (5.9%), and other/unspecified 5/51 (9.8%). Injuries most often involved the lower limb (28/51; 54.9%), then the lumbar/back (9/51; 17.6%) and upper limb (8/51; 15.7%). A complete breakdown by type and anatomical region is provided in (online supplemental table S1). Operational event context (eg, foot pursuit, apprehension) was incompletely captured in routine records and is therefore not analysed here.

As shown in table 1, the mean composite fitness score at graduation was 79.87 (SD=4.16). Officers who remained injury-free exhibited significantly higher fitness scores (mean=80.45, SD=3.98) compared with their injured peers (mean=77.96, SD=4.22; t₍₂₁₄₎ = 3.86, p<0.001). BMI also differed significantly between groups (p<0.001), with higher BMI associated with increased injury incidence. No significant differences were observed in other individual fitness components, including vital capacity, sprint time, flexibility, strength or run time (p>0.3 for all).

Table 1. Baseline demographic and fitness characteristics of police recruits stratified by injury occurrence during the first year of service.

Variable	Overall, N=216*	Injury		Between-group test (effect size)	P value†
		No N=165 (76%)*	Yes N=51 (24%)*
Sex				0.00	>0.999
Female	56 (25.93%)	43 (26.06%)	13 (25.49%)
Male	160 (74.07%)	122 (73.94%)	38 (74.51%)
Age	22 (22, 22)	22 (22, 22)	22 (22, 22)	4484.00	0.337
BMI score	84 (60, 100)	96 (60, 100)	60 (60, 60)	6315.00	<0.001
Fitness score	79.87 (4.16)	80.45 (3.98)	77.96 (4.22)	3.86	<0.001
Vital capacity	79 (70, 91)	79 (70, 91)	79 (70, 87)	4308.50	0.797
Sprint 50 m	80 (71, 90)	80 (71, 90)	81 (70, 90)	4257.50	0.899
Sit and reach	79.50 (70, 88)	80 (70, 88)	78 (70, 88.50)	4114.50	0.812
Standing long jump	82.50 (70.75, 90)	82 (71, 90)	83 (69.50, 89)	4333.00	0.749
Muscular endurance (sex-specific)	78.50 (68.75, 90)	78 (68, 90)	81 (71, 88.50)	3821.50	0.323
Run time	79.35 (8.56)	79.70 (8.62)	78.20 (8.34)	1.10	0.273
Fitness level					<0.001
Excellent	44 (20.37%)	41 (24.85%)	3 (5.88%)
Good	88 (40.74%)	79 (47.88%)	9 (17.65%)
Pass	84 (38.89%)	45 (27.27%)	39 (76.47%)
Fail	0 (0%)	0 (0%)	0 (0%)
BARS total score	23 (21, 26)	23 (21, 26)	22 (19, 23)	5508.00	<0.001
Operational decision making	4 (3, 4)	4 (3, 4)	4 (3, 4)	4232.00	0.946
Situational awareness	4 (3.75, 4)	4 (3, 4)	4 (4, 4)	3996.00	0.535
Communication	4 (4, 4)	4 (4, 4)	4 (3, 4)	4959.50	0.031
Teamwork and coordination	4 (4, 4)	4 (4, 4)	4 (4, 4)	3904.50	0.314
Stress resilience	4 (3, 4)	4 (3, 4)	4 (3, 4)	4037.00	0.634
Use of force judgement	4 (3, 4)	4 (3, 4)	3 (3, 4)	5254.00	0.004
Time to injury	–	–	5 (4, 9)	–	NS

^*n (%); Median (IQR); Mean (SD).

^†Pearson’s χ2 test; Wilcoxon rank sum test; two sample t-test; Fisher’s exact test for count data with simulated p value (based on 2000 replicates).

BARS, Behaviourally Anchored Rating Scale; BMI, body mass index; NS, not significant.

Fitness level classifications further underscored this disparity: 24.85% of non-injured officers were rated as ‘excellent’, versus only 5.88% among injured officers. Conversely, 76.47% of the injured group were classified as ‘pass’, compared with just 27.27% in the non-injured group (p<0.001).

In terms of job performance, the overall median BARS score was 23 (IQR: 21–26). Injured officers had significantly lower total BARS scores (median=22) than non-injured counterparts (median=23; p<0.001). Among BARS subdomains, communication (p=0.031) and use-of-force judgement (p=0.004) were significantly lower in the injured group. Other dimensions, including operational decision-making, situational awareness, teamwork and stress resilience, did not differ significantly. The injured versus non-injured difference corresponds to a standardised effect of r=0.22 (rank-biserial), indicating a small-to-moderate magnitude; no minimum clinically important difference has been established for policing BARS. The median time to first injury among injured officers was 5 months (IQR: 4–9), reinforcing the vulnerability of the early deployment phase.

Sex-stratified summaries for the full follow-up sample are provided in online supplemental Table S2. Effect directions were consistent across sexes, and the exploratory sex×composite fitness interaction was non-significant (power-limited).

Predictive analyses

Job performance outcomes (BARS)

To evaluate whether graduation-stage physical fitness predicted job performance in the first year of service, multivariable linear regression models were conducted using total BARS scores as the outcome variable. After adjusting for age, sex, BMI, baseline physical activity (measured via IPAQ-SF at academy entry), and pre-existing musculoskeletal conditions, graduation fitness emerged as a significant independent predictor. As shown in table 2, each one-point increase in composite fitness score corresponded to a 0.21-point increase in BARS total score (β=0.21; 95% CI 0.12 to 0.30; p<0.001).

Table 2. Multivariable linear regression models predicting first-year job performance (BARS scores) from graduation-stage physical fitness.

Outcome variable	β coefficient	SE	95% CI	P value
Total BARS score	0.21	0.045	(0.12 to 0.30)	<0.001*
Subdomain scores
Operational decision-making	0.07	0.049	(–0.02 to 0.16)	0.128
Situational awareness	0.04	0.038	(–0.03 to 0.11)	0.255
Communication	0.15	0.074	(0.01 to 0.29)	0.042*
Teamwork and coordination	0.06	0.059	(–0.05 to 0.17)	0.309
Stress resilience	0.09	0.061	(–0.03 to 0.20)	0.145
Use-of-force judgement	0.19	0.080	(0.03 to 0.35)	0.017*

All models adjusted for age, sex, BMI, baseline physical activity (IPAQ-SF) and pre-existing musculoskeletal conditions at academy entry.

^*p<0.05.

BARS, Behaviourally Anchored Rating Scale; BMI, body mass index; GPS, Global Positioning System; ICC, Intraclass Correlation Coefficient; IMU, Inertial Measurement Unit; IPAQ-SF, International Physical Activity Questionnaire–Short Form; VIF, Variance Inflation Factor.

Exploratory analyses of BARS subdomains revealed significant associations between higher fitness and enhanced performance in communication (β=0.15; p=0.042) and use-of-force judgement (β=0.19; p=0.017). No statistically significant effects were observed in the other four subdomains (p>0.05). All models demonstrated acceptable multicollinearity (VIF<1.7) and robust SEs.

Injury risk outcomes (Cox model)

In the adjusted Cox model, each 1–SD increase in composite fitness was associated with a lower injury hazard (HR 0.89, 95% CI 0.83 to 0.95), adjusting for age, sex, BMI at graduation, baseline physical activity at entry and pre-existing musculoskeletal condition. We refrain from interpreting individual covariates in the main text; full adjusted estimates are provided in (online supplemental table S3).

Kaplan-Meier curves by composite-fitness quartiles (Q1–Q4) showed graded separation, with higher-fitness quartiles remaining injury-free longer (log-rank χ²=10.10, df=3, p=0.018; figure 3). A complementary dichotomised display (≥80 vs <80) is shown in (online supplemental figure S1). The exploratory sex×composite fitness interaction was non-significant. Sensitivity analyses focusing on fitness subdomains yielded consistent inferences; aerobic endurance (run time; reverse-coded) showed the strongest signal (HR 0.91, 95% CI 0.85 to 0.98, p=0.013).

Figure 3. Kaplan-Meier curves for time to first injury by composite fitness quartiles at graduation. Curves are right-continuous; log-rank χ² = 10.10, df=3, p=0.018. Quartiles were defined from empirical sample percentiles; inferential Cox models treated fitness as a continuous predictor (per 1−SD).

Discussion

Summary of key findings

This study examined whether physical fitness at the point of police academy graduation functions as a predictive indicator of early-career occupational outcomes in a cohort of law enforcement recruits. Employing a 12-month prospective, multisource design and adjusting for key covariates, two principal findings were observed.

First, higher graduation-stage composite fitness scores were significantly associated with enhanced job performance during the first year of deployment, as measured by the BARS. Notably, superior fitness predicted higher overall performance ratings, with significant effects concentrated in Communication and Use-of-Force Judgement subdomains. These associations remained robust after adjusting for sex, age, BMI, baseline physical activity (measured at academy entry) and the presence of pre-existing musculoskeletal conditions at enrolment.

Second, greater physical fitness at graduation was inversely related to the risk of musculoskeletal injury over the follow-up period. Each 1−SD increase in composite fitness was associated with an 11% lower injury hazard (HR 0.89, 95% CI 0.83 to 0.95). Kaplan-Meier survival curves corroborated this relationship, showing that higher-fitness recruits experienced significantly longer injury-free intervals compared with their lower-fitness peers.

Collectively, these results emphasise the role of post-training fitness as a dynamic operational resource, reflecting both acquired physiological adaptations and readiness for real-world occupational demands. The findings substantiate the proposed conceptual framework, in which graduation-stage physical capacity operates as a holistic predictor of first-year resilience and performance within the policing profession.

Comparison with prior research

The current findings are broadly consistent with extant literature in tactical populations regarding the critical role of physical fitness in promoting occupational readiness and injury resilience. Consistent with previous studies, elevated aerobic endurance, muscular strength and mobility capacities were associated with improved early-career job performance among police recruits.^{9 36} The observed associations between graduation-stage fitness and elevated BARS subdomain scores, specifically in communication and use-of-force judgement, extend the work of Lockie et al,³⁷ who found that postacademy conditioning was positively correlated with tactical decision-making and behavioural efficacy under operational stress.

The present study also reinforces injury risk patterns observed in longitudinal research among military and fire service cohorts. For example, Jones and Knapik²³ and Lyons et al²⁰ demonstrated that low cardiorespiratory and neuromuscular conditioning increased susceptibility to musculoskeletal injury during early deployment phases. Distinctively, the current research employed a time-to-event analytical framework within a policing cohort, revealing that recruits with subthreshold fitness scores (<80) were injured significantly earlier than their higher-fitness peers. This approach quantifies the timing of first injury, an aspect that cross-sectional designs are not designed to address.

Importantly, this study contributes to a growing critique of overreliance on entry-level fitness assessments as fixed proxies for long-term operational capacity.¹³ Entry-level fitness studies appropriately target outcomes within the academy period (eg, graduation, training injuries). Our contribution is complementary, focusing on graduation-stage fitness as a predictor of postdeployment outcomes. By shifting focus to graduation-stage fitness, the research operationalises physical conditioning as a dynamic, trainable resource, incorporating the physiological adaptations accrued through structured academy training. This approach aligns with emerging models in occupational physiology and performance science, which emphasise the interactive role of training adaptation, motivation and resilience in shaping readiness trajectories.³⁸

Consistent with Dawes et al,⁹ positioning assessments at graduation may offer greater ecological alignment with early-career demands because they reflect both initial capacity and training adaptations. We did not directly compare entry-stage versus graduation-stage tests; therefore, no claims of superiority are made. Our findings bolster this view by demonstrating that graduation fitness not only predicts occupational outcomes more reliably but does so independently of demographic modifiers.

BMI was included as an adjustment covariate; we do not interpret covariate coefficients in the main text (full adjusted estimates are provided in online supplemental table S3. The absence of a significant sex×fitness interaction suggests that the association between graduation-stage fitness and outcomes generalises across sexes. This reinforces the conceptual utility of graduation-stage physical fitness as a universal indicator of deployment readiness, supporting its potential integration into standardised postacademy evaluation protocols.¹

Theoretical and practical implications

The findings of this study hold considerable theoretical and practical implications for the understanding and application of physical fitness as a dynamic occupational resource in early-career law enforcement.

Theoretically, the results reinforce and extend key propositions of both the Tactical Athlete Framework and the JD-R Model. In the JD-R framework, physical fitness may be conceptualised as a trainable resource capable of buffering job demands, such as unpredictable workload, shift variability and threat exposure.³⁹ The significant associations between graduation-stage fitness and both job performance and injury reduction support the resource-enhancement pathway of the JD-R model: greater physical capacity enhances resilience under strain, thereby improving adaptive functioning and reducing negative outcomes.⁴⁰ This positions physical conditioning not merely as a personal attribute, but as a modifiable organisational resource that can be strategically developed and monitored.

Moreover, this study supports the Tactical Athlete paradigm by empirically validating the idea that law enforcement officers operate within high-performance, high-risk occupational environments that demand sustained physical readiness. The evidence here highlights the graduation point, the culmination of structured academy conditioning, as a critical inflection point for evaluating operational fitness. Unlike traditional static assessments at entry, post-training evaluations capture training adaptation and preparedness more accurately, offering a functionally relevant proxy for deployment readiness. This temporal specificity contributes to recent calls for more dynamic models of tactical readiness that incorporate developmental trajectories and transitional stressors.³⁸

Practically, these findings offer direct implications for police training systems and policy. The predictive validity of graduation-stage fitness supports its integration into deployment eligibility protocols, supplementing traditional assessments focused on cognitive or behavioural criteria. Moreover, given the independent predictive value of fitness for injury risk, agencies may consider adopting graduation-based stratification models, wherein recruits with lower scores are provided with targeted postacademy conditioning or injury prevention interventions prior to full deployment.

The generalisability of these effects, demonstrated by the absence of significant moderation by sex or BMI, further supports the scalability and equity of graduation-stage assessments. These can be applied uniformly across cohorts, minimising demographic bias while still capturing individual variation in adaptation. Such tools also facilitate data-driven human resource management, enabling agencies to make more informed decisions regarding assignment type, workload modulation or early-career mentorship based on validated performance risk indicators.

Our battery indexed upper-body pulling endurance in males (pull-ups) and trunk flexor endurance in females (sit-ups). These legacy tests were harmonised via within-sex standardisation to form a common muscular endurance domain within the composite. Because operational tasks do not differ by sex, unified, sex-common test batteries would further strengthen construct equivalence and interpretability in future cohorts. Beyond statistical associations, there are plausible mechanisms by which physical capacity shapes field performance.

Lower grip/forearm strength may diminish confidence and effectiveness in hands-on control, increasing reliance on force escalation when facing resistance.⁴¹ Lower overall fitness accelerates fatigue, which can impair motor control, situational awareness and inhibitory decision-making under acute stress.⁴² These pathways align with our results: recruits with higher graduation-stage composite fitness achieved higher BARS ratings, including use-of-force judgement and exhibited reduced injury hazard over 12 months. Together, these findings support conditioning strategies that enhance muscular endurance (including forearm/grip) and delay fatigue onset as part of operational readiness.

In sum, this study advocates for a paradigm shift from static entry assessments towards dynamic post-training evaluations in tactical readiness. Rather than relying on static, entry-level benchmarks, it advocates for an outcome-oriented, temporally aligned model that leverages training-induced gains to forecast real-world performance and mitigate injury risk. This approach integrates physiological, psychological and contextual dimensions of occupational preparedness and aligns with best practices in modern performance science and workforce optimisation.

Limitations and future directions

This study has several limitations that warrant consideration. First, no pre–post inference could be made. We lacked harmonised entry-level performance tests across cohorts and, therefore, did not quantify within-academy fitness changes. Our findings speak to prediction from graduation-stage fitness rather than the effects of academy training. Future cohorts could pair standardised entry-stage and graduation-stage batteries to examine both change scores and predictive validity within the same design. Second, participants were drawn from a single metropolitan academy in China. Local training protocols and institutional norms may limit generalisability. Replication across regions and countries is needed to confirm external validity. Third, the composite fitness score, while practical, may mask differential contributions of specific domains. Although aerobic capacity predicted injury risk, the sample was underpowered for detailed subdomain analyses. Larger samples could clarify domain-specific effects. Additionally, grip strength was not directly measured; we did not include handgrip dynamometry, precluding a direct test of the proposed grip strength to use-of-force pathway. Future cohorts should incorporate grip/forearm strength and endurance measures and scenario-based, hands-on control assessments to evaluate these mechanisms more explicitly.

Fourth, injury data included self-reports, which are subject to recall bias. Routine reporting did not consistently record contextual triggers (eg, foot pursuit, apprehension). Consequently, we could not stratify injuries by operational context, which may obscure pathway-specific risks. While data were triangulated with official sources, future cohorts should integrate standardised incident logs (context, mechanism, time-stamp) and sensor-based monitoring to couple events with exposure (eg, duty load carriage, accelerometry/IMU-derived impacts and bursts, heart-rate/internal load, GPS during foot pursuits). Aligning sensor traces with incident time-stamps can corroborate mechanisms (slip/trip, overexertion, blunt contact) and quantify dose–response (workload spikes, fatigue), enabling context-specific risk models. Fifth, the 12-month follow-up captures only early career transitions. Longer-term studies are needed to assess whether graduation-stage fitness predicts outcomes beyond the first year.

Finally, we lacked harmonised measures of stress, sleep, resilience and shift schedules, which plausibly influence fitness maintenance, fatigue and injury risk, creating scope for residual confounding. Future cohorts should integrate rostered shift data, brief validated questionnaires (eg, sleep quality, perceived stress) and wearable proxies (sleep duration/continuity, external load) to support more complete risk adjustment and pathway-specific analyses. Multidimensional frameworks that integrate physiological and psychological readiness may further enhance future predictive models.

Conclusions

This prospective cohort study demonstrated that physical fitness at police academy graduation independently predicts early-career job performance and musculoskeletal injury risk. Higher fitness scores were associated with superior operational ratings, particularly in communication and use-of-force judgement, and longer injury-free intervals during the first year of deployment. These associations remained robust after controlling for demographic and behavioural covariates.

By emphasising post-training fitness rather than entry-level assessments, the study supports a dynamic model of readiness consistent with the Tactical Athlete and JD-R frameworks. Graduation-stage assessments offer ecologically valid indicators of operational capacity and injury resilience.

These findings have direct implications for law enforcement policy and training systems. Specifically, integrating graduation-stage fitness benchmarks into deployment protocols can support evidence-based personnel assignment, reduce preventable injury-related costs and enhance early-career officer support. Policymakers may consider mandating post-training physical evaluations as a condition for field readiness certification, alongside targeted conditioning or injury prevention interventions for at-risk recruits. Future research should explore long-term effects, domain-specific predictors and integration with cognitive and psychosocial metrics to develop comprehensive tactical performance models.