Evidence map›Paper›PMID 25200666›Full record

ReviewSports medicine (Auckland, N.Z.)2014

Monitoring training load to understand fatigue in athletes.

Shona L Halson

Registry-linked trialAbstract readReview
In one paragraph

Review in Sports medicine (Auckland, N.Z.), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07411339 (Gingko Active App-based Personalized Exercise Training for Middle-Aged and Older Adults), which is not on this map. Cited by 635 papers, 12 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
635citing papers in PubMed, 12 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT07411339 nawithdrawnnot on this mapstarted 2026, after this paper: background citation

Gingko Active App-based Personalized Exercise Training for Middle-Aged and Older Adults

TypeinterventionalSponsorUniversity of Maryland, BaltimoreRan2026 to 2027Enrolled0ConditionsHealthy Adult Participants, Controlled Hypertension, Controlled DiabetesArmsGinkgo App-based Exercise Training, NIA Booklet Exercise
3 · Its place in the literature

Who cites it

635 citing papers in PubMed, 12 syntheses or guidelines pooled it.

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575 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Shona L HalsonAIS Physiology, Australian Institute of Sport, PO Box 176, Belconnen, ACT, 2616, Australia, Shona.halson@ausport.gov.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many athletes, coaches, and support staff are taking an increasingly scientific approach to both designing and monitoring training programs. Appropriate load monitoring can aid in determining whether an athlete is adapting to a training program and in minimizing the risk of developing non-functional overreaching, illness, and/or injury. In order to gain an understanding of the training load and its effect on the athlete, a number of potential markers are available for use. However, very few of these markers have strong scientific evidence supporting their use, and there is yet to be a single, definitive marker described in the literature. Research has investigated a number of external load quantifying and monitoring tools, such as power output measuring devices, time-motion analysis, as well as internal load unit measures, including perception of effort, heart rate, blood lactate, and training impulse. Dissociation between external and internal load units may reveal the state of fatigue of an athlete. Other monitoring tools used by high-performance programs include heart rate recovery, neuromuscular function, biochemical/hormonal/immunological assessments, questionnaires and diaries, psychomotor speed, and sleep quality and quantity. The monitoring approach taken with athletes may depend on whether the athlete is engaging in individual or team sport activity; however, the importance of individualization of load monitoring cannot be over emphasized. Detecting meaningful changes with scientific and statistical approaches can provide confidence and certainty when implementing change. Appropriate monitoring of training load can provide important information to athletes and coaches; however, monitoring systems should be intuitive, provide efficient data analysis and interpretation, and enable efficient reporting of simple, yet scientifically valid, feedback.

Indexed as

Task Performance and AnalysisHumansMuscle FatiguePhysical Education and TrainingSports

Identifiers

PMID25200666
PMCPMC4213373

What OpenQuestion holds

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.