The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Monitoring the athlete training response: subjective self-reported measures trump commonly used objective measures: a systematic review
Open accessAbstract
Background: Monitoring athlete well-being is essential to guide training and to detect any progression towards negative health outcomes and associated poor performance. Objective (performance, physiological, biochemical) and subjective measures are all options for athlete monitoring. Objective: We systematically reviewed objective and subjective measures of athlete well-being. Objective measures, including those taken at rest (eg, blood markers, heart rate) and during exercise (eg, oxygen consumption, heart rate response), were compared against subjective measures (eg, mood, perceived stress). All measures were also evaluated for their response to acute and chronic training load. Methods: The databases Academic search complete, MEDLINE, PsycINFO, SPORTDiscus and PubMed were searched in May 2014. Fifty-six original studies reported concurrent subjective and objective measures of athlete well-being. The quality and strength of findings of each study were evaluated to determine overall levels of evidence. Results: Subjective and objective measures of athlete well-being generally did not correlate. Subjective measures reflected acute and chronic training loads with superior sensitivity and consistency than objective measures. Subjective well-being was typically impaired with an acute increase in training load, and also with chronic training, while an acute decrease in training load improved subjective well-being. Summary: This review provides further support for practitioners to use subjective measures to monitor changes in athlete well-being in response to training. Subjective measures may stand alone, or be incorporated into a mixed methods approach to athlete monitoring, as is current practice in many sport settings.
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Cites
A Global Measure of Perceived Stress
Cohen, S., Kamarck, T., & Mermelstein, R. (1983) · Journal of Health and Social Behavior · doi:10.2307/2136404 · Cited by 32,807
Updated Method Guidelines for Systematic Reviews in the Cochrane Collaboration Back Review Group
van Tulder, M., Furlan, A., Bombardier, C., & Bouter, L. (2003) · Spine · doi:10.1097/01.brs.0000065484.95996.af · Cited by 2,180
(2013) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e318279a10a · Cited by 1,233
Development and validation of a mood measure for adolescents
Terry, P. C., Lane, A. M., Lane, H. J., & Keohane, L. (1999) · Journal of Sports Sciences · doi:10.1080/026404199365425 · Cited by 548 · cited 6×
“1 3 – 6 8 89 92 93 This may be supplemented with a more comprehensive measure such as the POMS or RESTQ-S on a weekly basis, 1 8 92 and objective measures on a less-frequent basis such as once per training microcycle.”
BackgroundInfluentialHalson, S. L., Bridge, M. W., Meeusen, R., Busschaert, B., Gleeson, M., Jones, D. A., & Jeukendrup, A. E. (2002) · Journal of Applied Physiology · doi:10.1152/japplphysiol.01164.2001 · Cited by 304
Autonomic imbalance hypothesis and overtraining syndrome
LEHMANN, M., FOSTER, C., DICKHUTH, H.-H., & GASTMANN, U. (1998) · Medicine & Science in Sports & Exercise · doi:10.1097/00005768-199807000-00019 · Cited by 221
Cited by
Soligard, T., Schwellnus, M., Alonso, J.-M., Bahr, R., Clarsen, B., Dijkstra, H. P., Gabbett, T., Gleeson, M., Hägglund, M., Hutchinson, M. R., et al. (2016) · British Journal of Sports Medicine · doi:10.1136/bjsports-2016-096581 · Cited by 1,041
Ardern, C. L., Glasgow, P., Schneiders, A., Witvrouw, E., Clarsen, B., Cools, A., Gojanovic, B., Griffin, S., Khan, K. M., Moksnes, H., et al. (2016) · British Journal of Sports Medicine · doi:10.1136/bjsports-2016-096278 · Cited by 985
Schwellnus, M., Soligard, T., Alonso, J.-M., Bahr, R., Clarsen, B., Dijkstra, H. P., Gabbett, T. J., Gleeson, M., Hägglund, M., Hutchinson, M. R., et al. (2016) · British Journal of Sports Medicine · doi:10.1136/bjsports-2016-096572 · Cited by 836
Mountjoy, M., Ackerman, K. E., Bailey, D. M., Burke, L. M., Constantini, N., Hackney, A. C., Heikura, I. A., Melin, A., Pensgaard, A. M., Stellingwerff, T., et al. (2023) · British Journal of Sports Medicine · doi:10.1136/bjsports-2023-106994 · Cited by 974
Purcell, R., Gwyther, K., & Rice, S. M. (2019) · Sports Medicine - Open · doi:10.1186/s40798-019-0220-1 · Cited by 394
Metadata
- Authors
- Saw, A. E., Main, L. C., & Gastin, P. B.
- Venue
- British Journal of Sports Medicine
- Publisher
- BMJ
- Published
- 2015-09-09
- Volume
- 50
- Issue
- 5
- Pages
- 281-291
- ISSN
- 0306-3674 (ISSN-L)
- 1473-0480
- OpenAlex
- W2111075265
- Cited by
- 910
- References
- 6
- FWCI
- 9.67
- Type
- journal article
- Language
- en
- Open access
- hybrid
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