Scientific References
The monitoring aspects behind Metrifit are based on solid scientific references that show the value of both subjective and objective monitoring. We are delighted that Metrifit has been associated with increased athlete sporting self-confidence in recent research reported by Anna Saw, Deakin University, Australia. Anna has also recently published research showing that subjective self-reported measures trump commonly used objective measures when assessing the athlete training response. We have covered this topic in more detail in our recent blog ‘Study highlights the benefits of subjective self-reporting measures in training’. This review provides further support for practitioners to use subjective measures to monitor changes in athlete well-being in response to training. Metrifit caters for collation of these subjective measures but also supports a mixed methods approach to include collation of objective measures through tests and device input.
The American College Health Association (ACHA) 2014 National College Health Assessment survey reported that nearly one in six college students (14.3 percent) had been diagnosed with, or treated for, anxiety. The same survey found that 21.8 percent of students said that within the last 12 months, anxiety had affected their academic performance. Student athletes face both academic and athletic pressures and its difficult for them to find the correct balance between both. In the words of Richard Deuchrass – Lincoln University Athletic Performance Manager
Metrifit doesn’t just help with optimizing our Sports Scholarship students’ athletic performance. It assists us in helping them get the balance right between their sporting activities and academic studies. We’re trying to build resourcefulness and character in our students for life, not just the sports field.
References
This is by no means an exhaustive list of references and research articles in this area but we have cited some interesting topics and research papers below.
Temporal Robustness of the Session RPE
by Joshua Christen, Carl Foster, John P. Porcari, and Richard P. Mikat 2016
Monitoring the athlete training response: subjective self-reported measures trump commonly used objective measures: a systematic review
by Anna E Saw, Luana C Main, Paul B Gastin 2015
Quantifying Training Load: A Comparison of Subjective and Objective Methods
by Jill Borresen and Michael I. Lambert 20008
Subjective Indicators in Monitoring pt 3
by Mladen Jovanovic 2013
Correlations between injury, training intensity, and physical and mental exhaustion among college athletes
by Vetter RE, Symonds ML 2010
Impact of training patterns on injury incidences in 12 Swiss Army basic military training schools
by Wyss T, Roos L, Hofstetter MC, Frey F, Mäder U 2014
Preventing overtraining in athletes in high-intensity sports and stress/recovery monitoring
by Kellmann M 2010
Relationship between training load and injury in professional rugby league players
by Gabbett TJ, Jenkins DG.
The relationship between workloads, physical performance, injury and illness in adolescent male football players
by Gabbett TJ, Whyte DG, Hartwig TB, Wescombe H, Naughton GA.
Monitoring training status with HR measures: do all roads lead to Rome?
by Martin Buchheit 2014
Monitoring Training Load to Understand Fatigue in Athletes
by Shona L. Halson 2014
Monitoring Athletes Through Self-Report: Factors Influencing Implementation
by Anna E. Saw, Luana C. Main, and Paul B. Gastin, 2015
Managing the health of the elite athlete: a new integrated performance health management and coaching model
by H Paul Dijkstra, N Pollock, R Chakraverty, and J M Alonso1
The Effects of Sleep Extension on the Athletic Performance of Collegiate Basketball Players
by Cheri D. Mah, MS; Kenneth E. Mah, MD, MS; Eric J. Kezirian, MD, MPH; William C. Dement, MD, PhD
Has the athlete trained enough to return to play safely? Acute:Chronic workloads and rehabilitation
by Jo Clubb, March 2016
The training-injury prevention paradox: should athletes be training smarter and harder?
by Tim Gabett 2016
Athlete Monitoring in Sport- Key Principles and Practical Tips
By Jason Laird (@PhysioReel)
The Athlete Sleep Screening Questionnaire: a new tool for assessing and managing sleep in elite athletes
by Charles Samuels, Lois James, Doug Lawson, Willem Meeuwisse 2014
Sleep as a recovery tool for athletes
Time to wake up: individualising the approach to sleep promotion interventions
by Hugh H K Fullagar, Jonathan D Bartlett
Psychological factors as predictors of injuries among senior soccer players. A prospective study.
by Ivarsson A, Johnson U.
Rating of perceived exertion as a predictor of the duration of exercise that remains until exhaustion
by TD Noakes
Validity and reliability of the session RPE method for monitoring exercise training intensity
by L Herman, C Foster, MA Maher, RP Mikat, JP Porcari
Validity and Reliability of the Session-RPE Method for Quantifying Training in Australian Football
by Scott, Tannath J; Black, Cameron R; Quinn, John; Coutts, Aaron J
The validity of the session-RPE method for quantifying training load in water polo.
by Lupo C, Capranica L, Tessitore A. 2014
Use of RPE-based training load in soccer.
by Impellizzeri FM, Rampinini E, Coutts AJ, Sassi A, Marcora SM. 2004
Weekly sport practice and adolescent well-being.
by Merglen A, Flatz A, Bélanger RE, Michaud PA, Suris JC.
Injury risk is different in team and individual youth sport
by Theisen D, Frisch A, Malisoux L, Urhausen A, Croisier JL, Seil R. 2013
Football injuries in children and adolescent players: are there clues for prevention?
by Lupo C, Capranica L, Tessitore A.
Late specialization: the key to success in centimeters, grams, or seconds (cgs) sports
by Moesch K, Elbe AM, Hauge ML, Wikman JM. 2011
Youth sport specialization: how to manage competition and training?
by Capranica L, Millard-Stafford ML.
