Training Load and Its Role in Injury Prevention, Part I: Back to the Future

培训(气象学) 过程(计算) 运动员 幻觉 应用心理学 心理学 控制(管理) 认知心理学 计算机科学 医学 风险分析(工程) 物理疗法 人工智能 物理 气象学 操作系统
作者
Franco M. Impellizzeri,Paolo Menaspà,Aaron J. Coutts,Judd T. Kalkhoven,Miranda Menaspa
出处
期刊:Journal of Athletic Training [National Athletic Trainers' Association]
卷期号:55 (9): 885-892 被引量:104
标识
DOI:10.4085/1062-6050-500-19
摘要

The purpose of this 2-part commentary series is† to explain why we believe our ability to control injury risk by manipulating training load (TL) in its current state is an illusion and why the foundations of this illusion are weak and unreliable. In part 1, we introduce the training process framework and contextualize the role of TL monitoring in the injury-prevention paradigm. In part 2, we describe the conceptual and methodologic pitfalls of previous authors who associated TL and injury in ways that limited their suitability for the derivation of practical recommendations. The first important step in the training process is developing the training program: the practitioner develops a strategy based on available evidence, professional knowledge, and experience. For decades, exercise strategies have been based on the fundamental training principles of overload and progression. Training-load monitoring allows the practitioner to determine whether athletes have completed training as planned and how they have coped with the physical stress. Training load and its associated metrics cannot provide a quantitative indication of whether particular load progressions will increase or decrease the injury risk, given the nature of previous studies (descriptive and at best predictive) and their methodologic weaknesses. The overreliance on TL has moved the attention away from the multifactorial nature of injury and the roles of other important contextual factors. We argue that no evidence supports the quantitative use of TL data to manipulate future training with the purpose of preventing injury. Therefore, determining “how much is too much” and how to properly manipulate and progress TL are currently subjective decisions based on generic training principles and our experience of adjusting training according to an individual athlete's response. Our message to practitioners is to stop seeking overly simplistic solutions to complex problems and instead embrace the risks and uncertainty inherent in the training process and injury prevention.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
程程发布了新的文献求助10
1秒前
1秒前
深情安青应助小清采纳,获得10
1秒前
小帅发布了新的文献求助10
1秒前
Zzz完成签到 ,获得积分10
2秒前
2秒前
doou应助蛮骨斯汀采纳,获得30
3秒前
3秒前
传奇3应助lessormoto采纳,获得10
4秒前
默笙发布了新的文献求助10
4秒前
4秒前
18204693903发布了新的文献求助10
4秒前
haha完成签到,获得积分10
4秒前
5秒前
打打应助大美女采纳,获得10
5秒前
冲冲冲完成签到 ,获得积分10
5秒前
5秒前
xiaxia发布了新的文献求助10
5秒前
6秒前
LvCR完成签到 ,获得积分10
6秒前
mltyyds完成签到,获得积分10
6秒前
拓扑异构酶应助文件撤销了驳回
7秒前
黄晃晃完成签到 ,获得积分10
8秒前
8秒前
JamesPei应助wx采纳,获得10
8秒前
诚心靳完成签到,获得积分10
8秒前
自由的纲发布了新的文献求助10
9秒前
晶晶发布了新的文献求助10
9秒前
9秒前
nixay621发布了新的文献求助10
9秒前
zz发布了新的文献求助10
10秒前
mumumuzzz完成签到,获得积分10
10秒前
12秒前
大模型应助Silole采纳,获得10
12秒前
12秒前
13秒前
HuangXaun完成签到,获得积分10
13秒前
充电宝应助超级的海豚采纳,获得10
13秒前
14秒前
默笙完成签到,获得积分10
14秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Principles of town planning: translating concepts to applications 1000
1 Peter and Christ's Descent to the Dead in Its Early Christian Reception 700
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Photothermal Science and Techniques 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7725078
求助须知:如何正确求助?哪些是违规求助? 9277548
关于积分的说明 20122518
捐赠科研通 7301484
什么是DOI,文献DOI怎么找? 3301624
关于科研通互助平台的介绍 2454970
邀请新用户注册赠送积分活动 2309348