Sports Medicine最新文献

{"title":"There is No Supporting Evidence for a Far Transfer of General Perceptual or Cognitive Training to Sports Performance.","authors":"Job Fransen","doi":"10.1007/s40279-024-02060-x","DOIUrl":"https://doi.org/10.1007/s40279-024-02060-x","url":null,"abstract":"<p><p>In this opinion piece I reiterate the concepts of near and far transfer as previously described in the psychological literature. I show that despite very limited evidence, many technologies, tools and methods make questionable claims of eliciting far transfer from generic perceptual and/or cognitive training to sports performance. Specifically, this commentary illustrates with studies on stroboscopic vision, neurofeedback training and executive functions that the claims made for the beneficial effects of these training methods are currently unsubstantiated. I conclude that greater scrutiny by researchers is needed in order to assist practitioners to make better-informed decisions about tools, methods and technologies that may aid sports performance.</p>","PeriodicalId":21969,"journal":{"name":"Sports Medicine","volume":null,"pages":null},"PeriodicalIF":9.3,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141437566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Menstrual Health Manager (MHM): A Resource to Reduce Discrepancies Between Science and Practice in Sport and Exercise.","authors":"Claire E Badenhorst","doi":"10.1007/s40279-024-02061-w","DOIUrl":"https://doi.org/10.1007/s40279-024-02061-w","url":null,"abstract":"<p><p>Inadequate research on female health and performance; the complexity of the research; low menstrual health literacy of athletes, coaches, and support staff; and ethical and cultural sensitivities are all recognized as barriers to effective health monitoring for females in sports. Frameworks have been developed for academics to follow to help improve the quality of female-specific research. However, a similar resource that enables correct terminology, and use of health monitoring techniques has not been provided for sporting organizations, coaches, support staff or athletes. Therefore, this critical commentary presents a new resource, the Menstrual Health Manager. This resource may be used to determine the level of menstrual health monitoring detail that may be used by organisations, coaches or athletes, and specifies what reproductive health details the data will provide. This resource aims to provide organizations and coaches with a means of understanding the data that inform their decisions for female athletes. Utilization of this resource may aid in the consistent use of terminology and methods for female-specific health monitoring in both sports and research.</p>","PeriodicalId":21969,"journal":{"name":"Sports Medicine","volume":null,"pages":null},"PeriodicalIF":9.3,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141432853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intensity Zones and Intensity Thresholds Used to Quantify External Load in Competitive Basketball: A Systematic Review","authors":"Matthew C. Tuttle, Cody J. Power, Vincent J. Dalbo, Aaron T. Scanlan","doi":"10.1007/s40279-024-02058-5","DOIUrl":"https://doi.org/10.1007/s40279-024-02058-5","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Background</h3><p>Despite widespread use of intensity zones to quantify external load variables in basketball research, the consistency in identifying zones and accompanying intensity thresholds using predominant monitoring approaches in training and games remains unclear.</p><h3 data-test=\"abstract-sub-heading\">Objectives</h3><p>The purpose of this work was to examine the external load intensity zones and thresholds adopted across basketball studies using video-based time-motion analysis (TMA), microsensors, and local positioning systems (LPS).</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>PubMed, MEDLINE, and SPORTDiscus databases were searched from inception until 31 January 2023 for studies using intensity zones to quantify external load during basketball training sessions or games. Studies were excluded if they examined players participating in recreational or wheelchair basketball, were reviews or meta-analyses, or utilized monitoring approaches other than video-based TMA, microsensors, or LPS.</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>Following screening, 86 studies were included. Video-based TMA studies consistently classified jogging, running, sprinting, and jumping as intensity zones, but demonstrated considerable variation in classifying low-intensity (standing and walking) and basketball-specific activities. Microsensor studies mostly utilized a single, and rather consistent, threshold to identify only high-intensity activities (&gt; 3.5 m·s⁻² for accelerations, decelerations, and changes-in-direction or &gt; 40 cm for jumps), not separately quantifying lower intensity zones. Similarly, LPS studies predominantly quantified only high-intensity activities in a relatively consistent manner for speed (&gt; 18.0 m·s⁻¹) and acceleration/deceleration zones (&gt; 2.0 m·s⁻²); however, the thresholds adopted for various intensity zones differed greatly to those used in TMA and microsensor research.</p><h3 data-test=\"abstract-sub-heading\">Conclusions</h3><p>Notable inconsistencies were mostly evident for low-intensity activities, basketball-specific activities, and between the different monitoring approaches. Accordingly, we recommend further research to inform the development of consensus guidelines outlining suitable approaches when setting external load intensity zones and accompanying thresholds in research and practice.</p>","PeriodicalId":21969,"journal":{"name":"Sports Medicine","volume":null,"pages":null},"PeriodicalIF":9.8,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141334240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sex Differences in Energy Metabolism: A Female-Oriented Discussion","authors":"Barbara N. Sanchez, Jeff S. Volek, William J. Kraemer, Catherine Saenz, Carl M. Maresh","doi":"10.1007/s40279-024-02063-8","DOIUrl":"https://doi.org/10.1007/s40279-024-02063-8","url":null,"abstract":"<p>The purpose of this review is to delineate aspects of energy metabolism at rest and during exercise that may be subject to sex differences and the potential underlying mechanisms involved. It focuses on distinct aspects of female physiology with an oriented discussion following the reproductive life stages of healthy, eumenorrheic females, including premenopausal time frames, pregnancy, perimenopause, and menopause. Finally, this review aims to address methodological challenges surrounding sexual dimorphism in energy metabolism investigations and confounding factors in this field. During resting conditions, females tend to have higher rates of non-oxidative free fatty acid clearance, which could contribute to lower respiratory exchange ratio measures. At the same time, carbohydrate energy metabolism findings are mixed. In general, females favor lipid energy metabolism during moderate-intensity exercise, while men favor carbohydrate energy metabolism. Factors such as age, dietary intake, genetics, and methodological decisions confound study findings, including properly identifying and reporting the menstrual cycle phase when female subjects are eumenorrheic. Pregnancy presents a unique shift in physiological systems, including energy metabolism, which can be observed at rest and during exercise. Changes in body composition and hormonal levels during the post-menopausal period directly impact energy metabolism, specifically lipid metabolism. This change in physiological state factors into the evidence showing a reduction in our understanding of sex differences in lipid metabolism during exercise in older adults. This review reveals a need for a focused understanding of female energy metabolism that could help exercise and nutrition professionals optimize female health and performance across the lifespan.</p>","PeriodicalId":21969,"journal":{"name":"Sports Medicine","volume":null,"pages":null},"PeriodicalIF":9.8,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141334229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"N of 1: Optimizing Methodology for the Detection of Individual Response Variation in Resistance Training","authors":"Zac P. Robinson, Eric R. Helms, Eric T. Trexler, James Steele, Michael E. Hall, Chun-Jung Huang, Michael C. Zourdos","doi":"10.1007/s40279-024-02050-z","DOIUrl":"https://doi.org/10.1007/s40279-024-02050-z","url":null,"abstract":"<p>Most resistance training research focuses on inference from average intervention effects from observed group-level change scores (i.e., mean change of group A vs group B). However, many practitioners are more interested in training responses (i.e., causal effects of an intervention) on the individual level (i.e., causal effect of intervention A vs intervention B for individual X). To properly examine individual response variation, multiple confounding sources of variation (e.g., random sampling variability, measurement error, biological variability) must be addressed. Novel study designs where participants complete both interventions and at least one intervention twice can be leveraged to account for these sources of variation (i.e., <i>n</i> of 1 trials). Specifically, the appropriate statistical methods can separate variability into the signal (i.e., participant-by-training interaction) versus the noise (i.e., within-participant variance). This distinction can allow researchers to detect evidence of individual response variation. If evidence of individual response variation exists, researchers can explore predictors of the more favorable intervention, potentially improving exercise prescription. This review outlines the methodology necessary to explore individual response variation to resistance training, predict favorable interventions, and the limitations thereof.</p>","PeriodicalId":21969,"journal":{"name":"Sports Medicine","volume":null,"pages":null},"PeriodicalIF":9.8,"publicationDate":"2024-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141326880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sex Differences in Recovery Trajectories of Assessments for Sport-Related Concussion Among NCAA Athletes: A CARE Consortium Study.","authors":"Jaclyn B Caccese, Christina L Master, Thomas A Buckley, Sara P D Chrisman, James R Clugston, James T Eckner, Elsa Ermer, Stacey Harcum, Tamerah N Hunt, Divya Jain, Louise A Kelly, T Dianne Langford, Landon B Lempke, Jane McDevitt, Allyssa K Memmini, Anne E Mozel, Susan M Perkins, Margot Putukian, Patricia R Roby, Adam Susmarski, Steven P Broglio, Thomas W McAllister, Michael McCrea, Paul F Pasquina, Carrie Esopenko","doi":"10.1007/s40279-023-01982-2","DOIUrl":"10.1007/s40279-023-01982-2","url":null,"abstract":"<p><strong>Objectives: </strong>The purpose of this study was to determine sex differences in recovery trajectories of assessments for sport-related concussion using Concussion Assessment, Research and Education (CARE) Consortium data.</p><p><strong>Methods: </strong>National Collegiate Athletic Association athletes (N = 906; 61% female) from sex-comparable sports completed a pre-season baseline assessment and post-sport-related concussion assessments within 6 h of injury, 24-48 h, when they initiated their return to play progression, when they were cleared for unrestricted return to play, and 6 months post-injury. Assessments included the Standardized Assessment of Concussion, Balance Error Scoring System, Brief Symptom Inventory-18, Immediate Post-concussion Assessment and Cognitive Testing (ImPACT), Sport Concussion Assessment Tool-3 symptom evaluation, Clinical Reaction Time, King-Devick test, Vestibular Ocular Motor Screen, 12-item Short-Form Health Survey, Hospital Anxiety and Depression Scale, and Satisfaction with Life Scale.</p><p><strong>Results: </strong>Only the Vestibular Ocular Motor Screen Total Symptom Score at the 24-48 h timepoint (p = 0.005) was statistically significantly different between sexes. Specifically, female athletes (mean = 60.2, 95% confidence interval [CI] 51.5-70.4) had higher Vestibular Ocular Motor Screen Total Symptom Scores than male athletes (mean = 36.9, 95% CI 27.6-49.3), but this difference resolved by the time of return-to-play initiation (female athletes, mean = 1.8, 95% CI 1.1-2.9; male athletes, mean = 4.1, 95% CI 1.5-10.9).</p><p><strong>Conclusions: </strong>Sport-related concussion recovery trajectories for most assessments were similar for female and male National Collegiate Athletic Association athletes except for Vestibular Ocular Motor Screen symptoms within 48 h of sport-related concussion, which was greater in female athletes. Female athletes had a greater symptom burden across all timepoints, suggesting that cross-sectional observations may indicate sex differences despite similar recovery trajectories.</p>","PeriodicalId":21969,"journal":{"name":"Sports Medicine","volume":null,"pages":null},"PeriodicalIF":9.3,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138831557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"What We Do Not Know About Stretching in Healthy Athletes: A Scoping Review with Evidence Gap Map from 300 Trials.","authors":"José Afonso, Renato Andrade, Sílvia Rocha-Rodrigues, Fábio Yuzo Nakamura, Hugo Sarmento, Sandro R Freitas, Ana Filipa Silva, Lorenzo Laporta, Maryam Abarghoueinejad, Zeki Akyildiz, Rongzhi Chen, Andreia Pizarro, Rodrigo Ramirez-Campillo, Filipe Manuel Clemente","doi":"10.1007/s40279-024-02002-7","DOIUrl":"10.1007/s40279-024-02002-7","url":null,"abstract":"<p><strong>Background: </strong>Stretching has garnered significant attention in sports sciences, resulting in numerous studies. However, there is no comprehensive overview on investigation of stretching in healthy athletes.</p><p><strong>Objectives: </strong>To perform a systematic scoping review with an evidence gap map of stretching studies in healthy athletes, identify current gaps in the literature, and provide stakeholders with priorities for future research.</p><p><strong>Methods: </strong>Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 and PRISMA-ScR guidelines were followed. We included studies comprising healthy athletes exposed to acute and/or chronic stretching interventions. Six databases were searched (CINAHL, EMBASE, PubMed, Scopus, SPORTDiscus, and Web of Science) until 1 January 2023. The relevant data were narratively synthesized; quantitative data summaries were provided for key data items. An evidence gap map was developed to offer an overview of the existing research and relevant gaps.</p><p><strong>Results: </strong>Of ~ 220,000 screened records, we included 300 trials involving 7080 athletes [mostly males (~ 65% versus ~ 20% female, and ~ 15% unreported) under 36 years of age; tiers 2 and 3 of the Participant Classification Framework] across 43 sports. Sports requiring extreme range of motion (e.g., gymnastics) were underrepresented. Most trials assessed the acute effects of stretching, with chronic effects being scrutinized in less than 20% of trials. Chronic interventions averaged 7.4 ± 5.1 weeks and never exceeded 6 months. Most trials (~ 85%) implemented stretching within the warm-up, with other application timings (e.g., post-exercise) being under-researched. Most trials examined static active stretching (62.3%), followed by dynamic stretching (38.3%) and proprioceptive neuromuscular facilitation (PNF) stretching (12.0%), with scarce research on alternative methods (e.g., ballistic stretching). Comparators were mostly limited to passive controls, with ~ 25% of trials including active controls (e.g., strength training). The lower limbs were primarily targeted by interventions (~ 75%). Reporting of dose was heterogeneous in style (e.g., 10 repetitions versus 10 s for dynamic stretching) and completeness of information (i.e., with disparities in the comprehensiveness of the provided information). Most trials (~ 90%) reported performance-related outcomes (mainly strength/power and range of motion); sport-specific outcomes were collected in less than 15% of trials. Biomechanical, physiological, and neural/psychological outcomes were assessed sparsely and heterogeneously; only five trials investigated injury-related outcomes.</p><p><strong>Conclusions: </strong>There is room for improvement, with many areas of research on stretching being underexplored and others currently too heterogeneous for reliable comparisons between studies. There is limited representation of elite-level athletes (~ 5%","PeriodicalId":21969,"journal":{"name":"Sports Medicine","volume":null,"pages":null},"PeriodicalIF":9.3,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11239752/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140060527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DNA Methylation in the Adaptive Response to Exercise.","authors":"Adam J Bittel, Yi-Wen Chen","doi":"10.1007/s40279-024-02011-6","DOIUrl":"10.1007/s40279-024-02011-6","url":null,"abstract":"<p><p>Emerging evidence published over the past decade has highlighted the role of DNA methylation in skeletal muscle function and health, including as an epigenetic transducer of the adaptive response to exercise. In this review, we aim to synthesize the latest findings in this field to highlight: (1) the shifting understanding of the genomic localization of altered DNA methylation in response to acute and chronic aerobic and resistance exercise in skeletal muscle (e.g., promoter, gene bodies, enhancers, intergenic regions, un-annotated regions, and genome-wide methylation); (2) how these global/regional methylation changes relate to transcriptional activity following exercise; and (3) the factors (e.g., individual demographic or genetic features, dietary, training history, exercise parameters, local epigenetic characteristics, circulating hormones) demonstrated to alter both the pattern of DNA methylation after exercise, and the relationship between DNA methylation and gene expression. Finally, we discuss the changes in non-CpG methylation and 5-hydroxymethylation after exercise, as well as the importance of emerging single-cell analyses to future studies-areas of increasing focus in the field of epigenetics. We anticipate that this review will help generate a framework for clinicians and researchers to begin developing and testing exercise interventions designed to generate targeted changes in DNA methylation as part of a personalized exercise regimen.</p>","PeriodicalId":21969,"journal":{"name":"Sports Medicine","volume":null,"pages":null},"PeriodicalIF":9.3,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140336855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Standard Error/Standard Deviation Mix-Up: Potential Impacts on Meta-Analyses in Sports Medicine.","authors":"Gavin Sandercock","doi":"10.1007/s40279-023-01989-9","DOIUrl":"10.1007/s40279-023-01989-9","url":null,"abstract":"<p><strong>Background: </strong>A recent review found that 45% of meta-analyses included statistical errors, of which, the most common was the calculation of effect sizes based on standard error (SE) rather than standard deviation (SD) [the SE/SD mix-up].</p><p><strong>Objectives: </strong>The first aim of this study was to assess the impact of the SE/SD mix-up on the results of one highly cited meta-analysis. Our second aim was to identify one potential source of the SE/SD mix-up, by assessing how often SE is reported as a measure of sample variability in randomised controlled trials in sports medicine.</p><p><strong>Methods: </strong>We checked for potential SE/SD mix-ups in a 2015 meta-analysis of randomised controlled trials reporting the effects of recreational football interventions on aerobic fitness in adults. We corrected effect sizes affected by SE/SD mix-ups and re-analysed the data according to the original methodology. We compared pooled estimates of effect sizes from our re-analysis of corrected values with those of the original study. To assess how often SE was reported instead of SD as a measure of sample variance, we text mined results of randomised controlled trials from seven sports medicine journals and reported the proportion reporting of SE versus SD.</p><p><strong>Results: </strong>We identified potential SE/SD mix-ups in 9/16 effect sizes included in the meta-analysis describing the effects of football-based interventions versus non-exercise control. The published effect size was standardised mean difference (SMD) = 1.46 (95% confidence interval [CI] 0.91, 2.01). After correcting for SE/SD mix-ups, our re-analysis produced a smaller pooled estimate (SMD = 0.54 [95% CI 0.37, 0.71]). The original pooled estimate for trials comparing football versus running interventions was SMD = 0.68 (95% CI 0.06, 1.4). After correcting for SE/SD mix-ups and re-analysis, the effect was no longer statistically significant (SMD = 0.20 [95% CI - 0.10, 0.49)]). We found that 19.3% of randomised controlled trials reported SE rather than SD to describe sample variability. The relative frequency of the practice ranged from 0 to 25% across the seven journals sampled.</p><p><strong>Conclusions: </strong>We found the SE/SD mix-up had inflated estimates for the effects of football on aerobic fitness. Meta-analysts should be vigilant to avoid miscalculating effect sizes. Authors, reviewers and editors should avoid and discourage (respectively) the practice of reporting SE as a measure of sample variability in sports medicine research.</p>","PeriodicalId":21969,"journal":{"name":"Sports Medicine","volume":null,"pages":null},"PeriodicalIF":9.3,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11239727/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139547046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Associations Between Physical Characteristics and Golf Clubhead Speed: A Systematic Review with Meta-Analysis.","authors":"Alex Brennan, Andrew Murray, Margo Mountjoy, John Hellstrom, Dan Coughlan, Jack Wells, Simon Brearley, Alex Ehlert, Paul Jarvis, Anthony Turner, Chris Bishop","doi":"10.1007/s40279-024-02004-5","DOIUrl":"10.1007/s40279-024-02004-5","url":null,"abstract":"<p><strong>Background: </strong>Historically, golf does not have a strong tradition of fitness testing and physical training. However, in recent years, both players and practitioners have started to recognise the value of a fitter and healthier body, owing to its potential positive impacts on performance, namely clubhead speed (CHS).</p><p><strong>Objective: </strong>The aim of this meta-analysis was to examine the associations between CHS (as measured using a driver) and a variety of physical characteristics.</p><p><strong>Methods: </strong>A systematic literature search with meta-analysis was conducted using Medline, SPORTDiscus, CINAHL and PubMed databases. Inclusion criteria required studies to have (1) determined the association between physical characteristics assessed in at least one physical test and CHS, (2) included golfers of any skill level but they had to be free from injury and (3) been peer-reviewed and published in the English language. Methodological quality was assessed using a modified version of the Downs and Black Quality Index tool and heterogeneity assessed via the Q statistic and I². To provide summary effects for each of the physical characteristics and their associations with CHS, a random effects model was used where z-transformed r values (i.e. z_r) were computed to enable effect size pooling within the meta-analysis.</p><p><strong>Results: </strong>Of the 3039 studies initially identified, 20 were included in the final analysis. CHS was significantly associated with lower body strength (z_r = 0.47 [95% confidence intervals {CI} 0.24-0.69]), upper body strength (z_r = 0.48 [95% CI 0.28-0.68]), jump displacement (z_r = 0.53 [95% CI 0.28-0.78]), jump impulse (z_r = 0.82 [95% CI 0.63-1.02]), jumping peak power (z_r = 0.66 [95% CI 0.53-0.79]), upper body explosive strength (z_r = 0.67 [95% CI 0.53-0.80]), anthropometry (z_r = 0.43 [95% CI 0.29-0.58]) and muscle capacity (z_r = 0.17 [95% CI 0.04-0.31]), but not flexibility (z_r = - 0.04 [95% CI - 0.33 to 0.26]) or balance (z_r =  - 0.06 [95% CI - 0.46 to 0.34]).</p><p><strong>Conclusions: </strong>The findings from this meta-analysis highlight a range of physical characteristics are associated with CHS. Whilst significant associations ranged from trivial to large, noteworthy information is that jump impulse produced the strongest association, upper body explosive strength showed noticeably larger associations than upper body strength, and flexibility was not significant. These findings can be used to ensure practitioners prioritise appropriate fitness testing protocols for golfers.</p>","PeriodicalId":21969,"journal":{"name":"Sports Medicine","volume":null,"pages":null},"PeriodicalIF":9.3,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11239735/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139997443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}