Phil Newman

BACKGROUND Musculoskeletal conditions have high, and increasing, incidence and prevalence. Although there are many clinical guidelines available for common conditions, most are poor quality and sparsely adopted into practice. OBJECTIVE We aim to improve patient outcomes by developing robust Best Practice Guidelines (BPG) to get research findings into practice for a range of common musculoskeletal conditions. METHODS Mixed methods with systematic review of high-quality studies and qualitative elicitation of both patient’s perspectives and expert clinical reasoning through in-depth interviews will form the basis for the BPGs. A segregated convergent synthesis, informed throughout by stakeholder engagement, will guide the format and structure of the BPGs. RESULTS NA CONCLUSIONS Ethical approval for the qualitative studies and implementation events will be obtained from university and health service research ethics committees. Educational packages for each BPG condition will be hosted online and be available for students, clinicians, and education providers. Dissemination will follow traditional routes including publications and presentations; alongside innovative approaches such as collaboration with higher education institutions, online hosting, adoption by professional bodies, and a social media campaign. Implementation will occur adaptively in multiple national contexts to reflect local requirements and resources, deploying participatory and implementation methods that are contextually and culturally appropriate. CLINICALTRIAL NA

Introduction: Musculoskeletal conditions have high, and increasing, incidence and prevalence. Although there are many clinical guidelines available for common conditions, most are poor quality and sparsely adopted into practice. We aim to improve patient outcomes by developing robust Best Practice Guidelines (BPG) to get research findings into practice for a range of common musculoskeletal conditions. Methods and analysis: Mixed methods with systematic review of high-quality studies and qualitative elicitation of both patient’s perspectives and expert clinical reasoning through in-depth interviews will form the basis for the BPGs. A segregated convergent synthesis, informed throughout by stakeholder engagement, will guide the format and structure of the BPGs. Ethics, outputs and dissemination: Ethical approval for the qualitative studies and implementation events will be obtained from university and health service research ethics committees. Educational packages for each BPG condition will be hosted online and be available for students, clinicians, and education providers. Dissemination will follow traditional routes including publications and presentations; alongside innovative approaches such as collaboration with higher education institutions, online hosting, adoption by professional bodies, and a social media campaign. Implementation will occur adaptively in multiple national contexts to reflect local requirements and resources, deploying participatory and implementation methods that are contextually and culturally appropriate. KEY MESSAGES: What is already known on this topic – Clinical guidelines for the management of musculoskeletal conditions are common, but have limitations regarding quality, applicability, editorial independence, and patient perspective. They are rarely adopted into clinical practice. What this study adds – We have developed a robust (supported by Patient and Participant Involvement) mixed-methods approach that integrates the three components of evidence-based medicine: synthesis of high-quality evidence, patients’ perspectives/values, and expert clinical reasoning. We have also developed an education, dissemination, and implementation approach to facilitate international adoption of these guidelines. How this study might affect research, practice or policy – The guideline development methods will integrate the three pillars of evidence-based practice and ensure they are robust and clinically applicable. Creation of educational material combined with an implementation and dissemination plan will support adoption into clinical practice of different countries and cultures, designed to lead to improved patient outcomes.

Objectives: Bone stress injuries (BSI) result in lengthy rehabilitation periods for professional and pre-professional ballet dancers. For dancers who sustain BSI, there is a high chance of recurrence, which may affect future dance participation and career opportunities. This research engaged stakeholders from a classical ballet company to co-create BSI prevention strategies. Design: Participatory action research. Methods: Stakeholder-researchers (n = 17) within a professional ballet company participated in four sequential focus group meetings. Their roles included: Artistic staff, current/former dancers, clinicians, community engagement, events, marketing, facilities management, and philanthropy. Meetings were recorded, transcribed, and coded thematically. Finally, the group drafted a BSI prevention proposal for the organisation. Results: Stakeholder-researchers felt improving health literacy for recreational dancers in the community was important, as there may be an onflow of poor health behaviours from the community level into to pre-professional and professional settings. Priorities for prevention in the professional setting were improving access to onsite health services, annual health evaluations, refining safeguarding policies, and investigating wearable technology. Priorities for the community included targeted BSI education for dancers, teachers, and families. The artistic process, poor nutrition, stress, lack of load monitoring strategies, and glorification of dancing despite injury, are barriers to BSI prevention in both professional and community settings. Systemic barriers such as funding, and community access to dance-informed health practitioners were identified. Dancers may not utilise health services for ‘athletes’, because they identify strongly as artists. Conclusion: Stakeholder-researchers collaborated through PAR to identify and prioritise strategies for BSI prevention. Health literacy surveys and ongoing systematic injury surveillance were recommended to evaluate intervention effects.

Purpose: Fast jet aircrew (FJA – aka fighter pilots, fighter aircrew) commonly suffer musculoskeletal complaints, particularly of the neck, which degrades operational capability and workforce health. Establishing injury aetiology is a prerequisite for developing effective preventative interventions. Our objective was to examine the aetiology of neck-related musculoskeletal complaint episodes (NRMCEs) among FJA across a range measures including physical capacity, psycho-social recovery-stress states, workload measures, and strength and conditioning (S&C) participation. Methods: 279 Royal Australian Air Force (RAAF) FJA were followed over four 5-month reporting periods. Forty-four baseline measures and 26 weekly measures were analysed for their effect on weekly risk of NRMCEs. Mixed-effects logistic regression was used, potential confounders were adjusted for, and non-linear relationships were examined. Results: 320 new NRMCEs were included with mean weekly prevalence of 4.1% (SD 2.3) and mean 5-month reporting period prevalence of 22.4% (range 15.3–28.5%). Previous neck pain, higher worry scores, larger acute flying workloads, more weekly flights, and larger acute and chronic S&C workloads, were factors identified to increase weekly risk of NRMCE. Significant non-linear effects were identified for chronic flying workloads, acute and chronic sleep quality scores, and absolute isometric strength of neck rotation and trunk flexion. Demographics, flying history, anthropometry measures, neck and trunk range of motion, and S&C participation, however, did not affect weekly risk of new NRMCE. Conclusion: These findings provide crucial support for the design of targeted prevention programs for FJA, ensuring they are both effective and efficient, which will in turn optimise operational capability.

Background: Elite swimming performance is determined by a complex interplay of anthropometric, physiological, biomechanical, and technical factors. Previous research highlights how the 100-m freestyle demands explosive power, technical proficiency, and tactical acumen, yet factors that distinguish world-class swimmers from their closely performing (inter)national-level counterparts remain elusive. Purpose: To identify race-performance factors differentiating world-class swimmers in the 100-m freestyle. Methods: World-best to national-level (N = 204) male swimmers competing at long-course events between 2019 and 2024 were analyzed using high-definition video and race-analysis software. Key performance metrics including stroke rate and length, turn efficiency, underwater phase duration, and velocity at 5-m intervals were extracted. Using a machine-learning random forest algorithm, the most salient factors distinguishing between world-class (0%–2.5% off world record), international-level (2.5%–5% off), and national-level (5%–10% off) performance categories were identified. Results: Analyses revealed a model classification accuracy of 89.5% with swim velocities at 65- to 70- and 70- to 75-m race segments most strongly associated with performance-level differentiation. These 2 race segments scored twice as high as all the other top 10 features. Shapley additive explanations (SHAP) analysis confirmed the importance of midrace velocities, while partial dependence plots identified the necessary velocity range values likely associated with national- to world-class performance levels. Conclusions: The combination of race analysis and machine learning creates the opportunity for targeted intervention for coaches and sport scientists working with high-performing 100-m male swimmers.

Introduction: A systematic approach to collecting and reporting injury data in military settings is necessary to maximize the impact of musculoskeletal injury–related research. An international consensus on recommended core data set of elements to capture and report is necessary. The purpose was to summarize the process and results from an international consensus study to establish recommended common minimum data elements for surveillance and Reporting Of Musculoskeletal injuries in the MILitary (ROMMIL). Methods: A 10-step hybrid consensus process was performed. Knowledge users were embedded in the process for co-creation of pertinent questions, data elements, and voting. Evidence synthesis included a scoping review on the barriers and facilitators to implementing injury prevention programs, followed by a knowledge user survey. A sequential three round Delphi study refined and validated the final elements in the recommendation checklist. Consensus recommendations were presented to an international audience of stakeholders. Participants voted on each statement with 0 representing no importance, 5 somewhat important, and 10 maximum importance. Results: The consensus recommendation includes one data principle of keeping continuous data continuous and 33 minimum data elements. Data elements include demographics, lifestyle, service branch, musculoskeletal/surgical history, exposure, and injury characteristics. The data principle endorsed by knowledge users recommends that continuous variables (e.g., age, weight, exposure) remain continuous and not categorized into groups. Dissenting viewpoints are detailed to provide fair and balanced consensus recommendations. Conclusions: The ROMMIL checklist could be leveraged by clinicians, researchers, and knowledge users working in military settings when comparing and harmonizing data across studies, service branches, and countries. The ROMMIL checklist will support improved data synthesis to better inform evidence-based practice in military medicine, and the ability to generate more useful prognostic models to quantify injury risk.

Background The objective was to summarize the methodology used to develop the international minimum data elements for surveillance and Reporting of Musculoskeletal Injuries in the MILitary (ROMMIL) statement. This is a recommended list of elements to be collected and reported when conducting injury surveillance research in military settings. Methods A Delphi methodology was employed to reach consensus. Preliminary steps included conducting a literature review and surveying a convenience sample of military stakeholders to 1) identify barriers and facilitators of military musculoskeletal injury (MSKI) prevention programs, 2) identify relevant knowledge gaps, and 3) establish future research priorities. A sequential three-round Delphi consensus survey followed, including relevant stakeholders from militaries around the world, using results to conduct an asynchronous knowledge user meeting (mixture of in-person and live video conference and recording) to explore the level of agreement among subject matter experts. Knowledge users, including former and current military service members, civilian practitioners working in military health networks, and international subject matter experts having experience with policy, execution, or clinical investigation of MSKI mitigation programs, MSKI diagnoses, and MSKI risk factors in military settings. For each round, participants scored questions on a Likert scale of 1-5. Scores ranged from No Importance (1) to Strong Importance (5). Results Literature review and surveys helped inform the scope of potential variables. Three rounds were necessary to reach minimum consensus. Ninety-five, 65, and 42 respondents participated in the first, second and third rounds, respectively. Conclusions Achieving consensus across relevant knowledge users representing military organizations globally can be challenging. This paper details the methodology employed to reach consensus for a core minimum data elements checklist for conducting MSKI research in military settings and improve data harmonization and scalability efforts. These methods can be used as a resource to assist in future consensus endeavors of similar nature.

Background/Objectives: Currently, there is no strong evidence to support interventions for medial tibial stress syndrome (MTSS), a common running injury associated with tibial loading. Vertical ground reaction force (vGRF) and axial tibial acceleration (TA) are the most common methods of estimating tibial loads, yet clinical recommendations for technique modification to reduce these metrics are not well documented. This study investigated whether changes to speed, cadence, stride length, and foot-strike pattern influence vGRF and TA. Additionally, machine-learning models were evaluated for their ability to estimate vGRF metrics. Methods: Sixteen runners completed seven 1 min trials consisting of preferred technique, ±10% speed, ±10% cadence, forefoot, and rearfoot strike. Results: A 10% speed reduction decreased peak tibial acceleration (PTA), vertical average loading rate (VALR), vertical instantaneous loading rate (VILR), and vertical impulse by 13%, 10.9%, 9.3%, and 3.2%, respectively. A 10% cadence increase significantly reduced PTA (11.5%), VALR (15.6%), VILR (13.5%), and impulse (3.5%). Forefoot striking produced significantly lower PTA (26.6%), VALR (68.3%), and VILR (68.9%). Habitual forefoot strikers had lower VALR (58.1%) and VILR (47.6%) compared to rearfoot strikers. Machine-learning models predicted all four vGRF metrics with mean average errors of 9.5%, 10%, 10.9%, and 3.4%, respectively. Conclusions: This study demonstrates that small-scale modifications to running technique effectively reduce tibial load estimates. Machine-learning models offer an accessible, affordable tool for gait retraining by predicting vGRF metrics without reliance on IMU data. The findings support practical strategies for reducing MTSS risk.