Musculoskeletal Injuries in the Military Staff: A Systematic Review
Bibliographic record
Abstract
Incidence and epidemiology of combat injuries sustained during ... [2] Injury prevention during physical activity in the ... [3] Injuries and injury risk factors among men and ... [4] Injuries at a Canadian national taekwondo championships ... [5] Epidemiology of injuries and illnesses during the ... [6] Effects of frequency and duration of training on ... [7] Longterm disability among aviators in Japan air self-defense force ... [8] Air force special operations command special ... [9] International statistical classification ... [10] Risk factors for chronic low back pain ... [11] Effect of nicotine on bone healing in rats-A ... [12] Hole's essentials of human anatomy ... [13] Incidence and risk factors for medial tibial ... [14] Effect of foot posture, foot orthoses and footwear ... [15] A history of shoulder instability in the military ... [16] Disease and nonbattle injuries sustained by a US army brigade … [17] Self-reported musculoskeletal complaints ... [18] Military physical training-related injuries: A review ... [19] Incidence and characteristics of traumatic shoulder … [20] A description of injuries in men and women ... [21] Gender disparities within US army orthopedic ... [22] The occurrence and severity of musculoskeletal ... [23] The occurrence and severity of musculoskeletal ... [24] Risk factors for medial tibial stress syndrome ... [25] A prospective field study of U.S. Army trainees ... [26] Musculoskeletal injuries and United States army readiness part ... [27] Orthopedic injuries in US casualties treated ... [28] Recurrent shoulder instability in a young, active ... [29] Clavicle fractures in the United States military ... [30] The comparison of functional injuries of upper limbs ... [31] Prevalence of musculoskeletal symptoms among ... [32] Description and rate of musculoskeletal injuries ... [33] Injuries in Australian army full-time ... [34] Current practices in anterior cruciate ... [35] Aetiology and risk factors of musculoskeletal ... [36] Relationship between body mass index ... [37] Musculoskeletal disorders related to physical activities ... [38] Incidence of SLAP lesions in a military ... [39] Soldier 2020: Injury rates/attrition rates working ... [40] Description of Musculoskeletal ... [41] Olecranon bursitis in a military ... [42] Attrition due to orthopedic reasons during ...Aims Musculoskeletal disorders are common among military personnel and can have a negative impact on their missions.Therefore, this study aimed to investigate the prevalence and type of musculoskeletal disorders in the military. Instruments & MethodsThis study aimed to investigate diseases of the musculoskeletal disorders common among the military to review systematically.International Information PubMed, ScienceDirect, and Google Scholar and the base of internal SID, Magiran and the Bank of the Medical Sciences journal of the country searched for two languages, English and Persian, from 2000 to June 2020.Findings Factors such as gender, age, type of workforce, and whether or not training and standardization are influencing these injuries.Muscle and skeletal injuries are among the most important problems in the military, which reduces their readiness and prevents them from serving.Common areas of injury include the lower limbs, back, upper limbs, and shoulders.Irreparable factors such as gender, race, ethnicity, and modifiable factors such as physical fitness, medication use, and dietary habits, can be involved.Conclusion The incidence of musculoskeletal disorders among military personnel is inevitable.Therefore, it is necessary to try to deal with the effects of these injuries quickly, which requires careful planning and identification of the causes and grounds for these injuries.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".