N of 1: Optimizing Methodology for the Detection of Individual Response Variation in Resistance Training.
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 individua...
| Publicado en: | Sports Medicine Vol. 54; no. 8; pp. 1979 - 1991 |
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| Autores principales: | , , , , , , |
| Formato: | review tables/charts Journal Article |
| Publicado: |
Springer Nature
Aug2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=179067912&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 179067912 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01121642 C5H jtl: Sports Medicine issn: 01121642 maglogo: N pubinfo: dt: Aug2024 vid: 54 iid: 8 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 179067912 177838424 179067912 179067912 10.1007/s40279-024-02050-z 179067912 ppf: 1979 ppct: 12 formats: tig: atl: N of 1: Optimizing Methodology for the Detection of Individual Response Variation in Resistance Training. aug: au: Robinson, Zac P. Helms, Eric R. Trexler, Eric T. Steele, James Hall, Michael E. Huang, Chun-Jung Zourdos, Michael C. affil: https://ror.org/05p8w6387 Department of Exercise Science and Health Promotion, Muscle Physiology Laboratory, Florida Atlantic University, 777 Glades Road, 33431, Boca Raton, FL, USA sug: subj: Resistance Training Training Effect (Physiology) Evaluation Research Methodology Variable Random Sample Measurement Error Observer Bias Epistemology Crossover Design Data Analysis, Statistical ab: 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., n 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. pubtype: Academic Journal doctype: review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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