original abstract†Abstracts here may not perfectly match originals, for a variety of technical and practical reasons. Some abstacts are truncated for my purposes here, if they are particularly long-winded and unhelpful. I occasionally add clarifying notes. And I make some minor corrections.
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.
One article on PainScience.com cites Saw 2016 as a source:
- Anxiety & Chronic Pain — A self-help guide for people who worry and hurt
This page is part of the PainScience BIBLIOGRAPHY, which contains plain language summaries of thousands of scientific papers & others sources. It’s like a highly specialized blog. A few highlights:
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- A Bayesian model-averaged meta-analysis of the power pose effect with informed and default priors: the case of felt power. Gronau 2017 Comprehensive Results in Social Psychology.
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