Evidence map›Paper›PMID 37311061›Full record

ArticleMilitary medicine2023

Musculoskeletal Complaint Epidemiology in Australian Special Operation Forces Trainees.

Lisa Wolski, Joanne Stannard, Liam Toohey, Alison Fogarty, Michael Drew

Abstract read
In one paragraph

Article in Military medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Rehabilitating Soldiers for Load Carriage Tasks: An International Perspective.International journal of environmental research and public health · 2025
    Review
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Lisa WolskiAustralian Defence Force, Australian Army, Sydney, NSW 2173, Australia.ORCID 0000-0002-5828-1090
Joanne StannardAustralian Defence Force, Australian Army, Adelaide, SA 5111, Australia.ORCID 0000-0001-6418-4134
Liam TooheyAustralian Institute of Sport, Bruce, ACT 2617, Australia.ORCID 0000-0003-3312-7027
Alison FogartyDefence Science and Technology Group, Melbourne, VIC 3207, Australia.ORCID 0000-0002-0938-8684
Michael DrewDepartment of Defence, Joint Health Command, Canberra, ACT 2600, Australia.ORCID 0000-0002-7686-3780

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionElite military trainees are burdened by high numbers of musculoskeletal (MSK) injuries and are a priority military population for injury prevention. This research aims to describe the MSK complaint epidemiology of trainees undertaking special forces (SF) training in the Australian Defence Force (ADF). One barrier to accurate injury surveillance in military populations is that traditional surveillance methods rely on personnel engaging with the military healthcare system to collect injury data. This approach is likely to underestimate the injury burden as it is known that many military personnel, particularly trainees, avoid reporting their injuries because of various motives. Subsequently, the insights from surveillance systems may underestimate the injury burden and limit the ability to inform prevention requirements. This research aims to actively seek MSK complaint information directly from trainees in a sensitive manner to mediate injury-reporting behaviors. MATERIALS AND

methodsThis descriptive epidemiology study included two consecutive cohorts of ADF SF trainees from 2019 to 2021. Musculoskeletal data items and their respective recording methods were based on international sports injury surveillance guidelines and adapted to a military context. Our case definition encompassed all injuries or physical discomforts as recordable cases. A unit-embedded physiotherapist retrospectively collected MSK complaint data from selection courses and collected prospective data over the training continuum. Data collection processes were external to the military health care system to mediate reporting avoidance and encourage injury reporting. Injury proportions, complaint incidence rates, and incidence rate ratios were calculated and compared between training courses and cohorts.

resultsIn total, 334 MSK complaints were reported by 103 trainees (90.4%), with a complaint incidence rate of 58.9 per 1,000 training weeks (95% CI, 53.0-65.5). Of these MSK complaints, 6.4% (n = 22) resulted in time loss from work. The lumbar spine (20.6%, n = 71) and the knee (18.9%, n = 65) were the most frequently affected body parts. Most of the MSK complaints were reported during selection courses (41.9%), followed by field survival and team tactics (23.0%) and urban operations courses (21.9%). Physical training accounted for 16.5% of complaints. Fast-roping training was associated with more severe MSK complaints.

conclusionsMusculoskeletal complaints are highly prevalent in ADF SF trainees. Complaints are more frequently reported in selection and qualification training courses than in physical training. These activities are priorities for focused research to understand injury circumstances in ADF elite training programs to inform injury prevention strategies. A strength of our study is the data collection methods which have provided greater MSK complaint information than past research; however, much work remains in conducting consistent and accurate surveillance. Another strength is the use of an embedded physiotherapist to overcome injury-reporting avoidance. Embedded health professionals are recommended as continued practice for ongoing surveillance and early intervention.

Indexed as

Athletic InjuriesMilitary PersonnelMusculoskeletal DiseasesAustraliaHumansProspective StudiesRetrospective Studies

Identifiers

PMID37311061
PMCPMC10629990

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.