Guidelines to Classify Subject Groups in Sport-Science Research

术语 主题(文档) 工作量 数学 自行车 统计 计算机科学 语言学 地理 哲学 图书馆学 操作系统 考古
作者
Kevin De Pauw,Bart Roelands,Stephen S. Cheung,Bas de Geus,Gerard Rietjens,Romain Meeusen
出处
期刊:International Journal of Sports Physiology and Performance [Human Kinetics]
卷期号:8 (2): 111-122 被引量:560
标识
DOI:10.1123/ijspp.8.2.111
摘要

The aim of this systematic literature review was to outline the various preexperimental maximal cycle-test protocols, terminology, and performance indicators currently used to classify subject groups in sport-science research and to construct a classification system for cycling-related research.A database of 130 subject-group descriptions contains information on preexperimental maximal cycle-protocol designs, terminology of the subject groups, biometrical and physiological data, cycling experience, and parameters. Kolmogorov-Smirnov test, 1-way ANOVA, post hoc Bonferroni (P < .05), and trend lines were calculated on height, body mass, relative and absolute maximal oxygen consumption (VO(2max)), and peak power output (PPO).During preexperimental testing, an initial workload of 100 W and a workload increase of 25 W are most frequently used. Three-minute stages provide the most reliable and valid measures of endurance performance. After obtaining data on a subject group, researchers apply various terms to define the group. To solve this complexity, the authors introduced the neutral term performance levels 1 to 5, representing untrained, recreationally trained, trained, well-trained, and professional subject groups, respectively. The most cited parameter in literature to define subject groups is relative VO(2max), and therefore no overlap between different performance levels may occur for this principal parameter. Another significant cycling parameter is the absolute PPO. The description of additional physiological information and current and past cycling data is advised.This review clearly shows the need to standardize the procedure for classifying subject groups. Recommendations are formulated concerning preexperimental testing, terminology, and performance indicators.

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
Zx_1993应助杨怂怂采纳,获得50
1秒前
yiyi完成签到,获得积分10
1秒前
1秒前
科研通AI6应助strawberry采纳,获得10
1秒前
丰盛的煎饼发布了新的文献求助100
1秒前
Square发布了新的文献求助10
2秒前
2秒前
大力超大力完成签到 ,获得积分10
3秒前
李爱国应助紫麒麟采纳,获得10
3秒前
3秒前
聪明水之发布了新的文献求助10
4秒前
4秒前
海拉鲁电焊大师完成签到,获得积分10
4秒前
量子星尘发布了新的文献求助10
5秒前
ZhouZhou发布了新的文献求助10
5秒前
赘婿应助bjjtdx1997采纳,获得10
5秒前
5秒前
上官若男应助zxc采纳,获得10
5秒前
6秒前
kkk发布了新的文献求助10
6秒前
强小强完成签到,获得积分10
7秒前
一口发布了新的文献求助10
7秒前
7秒前
7秒前
研友_VZG7GZ应助呼叫554采纳,获得10
8秒前
廖紊发布了新的文献求助10
8秒前
小二郎应助100采纳,获得10
9秒前
汪丽娜发布了新的文献求助10
9秒前
俏皮道之发布了新的文献求助10
9秒前
9秒前
邓文博完成签到 ,获得积分20
10秒前
木子完成签到,获得积分10
10秒前
10秒前
cxt发布了新的文献求助10
10秒前
十三发布了新的文献求助10
11秒前
12秒前
Ccc发布了新的文献求助10
12秒前
12秒前
12秒前
12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
Predation in the Hymenoptera: An Evolutionary Perspective 1800
List of 1,091 Public Pension Profiles by Region 1561
Binary Alloy Phase Diagrams, 2nd Edition 1400
Specialist Periodical Reports - Organometallic Chemistry Organometallic Chemistry: Volume 46 1000
Holistic Discourse Analysis 600
Beyond the sentence: discourse and sentential form / edited by Jessica R. Wirth 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5513178
求助须知:如何正确求助?哪些是违规求助? 4607547
关于积分的说明 14505663
捐赠科研通 4543090
什么是DOI,文献DOI怎么找? 2489360
邀请新用户注册赠送积分活动 1471340
关于科研通互助平台的介绍 1443362