Literature DB >> 25729301

Monitoring athletes through self-report: factors influencing implementation.

Anna E Saw1, Luana C Main2, Paul B Gastin1.   

Abstract

Monitoring athletic preparation facilitates the evaluation and adjustment of practices to optimize performance outcomes. Self-report measures such as questionnaires and diaries are suggested to be a simple and cost-effective approach to monitoring an athlete's response to training, however their efficacy is dependent on how they are implemented and used. This study sought to identify the perceived factors influencing the implementation of athlete self-report measures (ASRM) in elite sport settings. Semi-structured interviews were conducted with athletes, coaches and sports science and medicine staff at a national sporting institute (n = 30). Interviewees represented 20 different sports programs and had varying experience with ASRM. Purported factors influencing the implementation of ASRM related to the measure itself (e.g., accessibility, timing of completion), and the social environment (e.g., buy-in, reinforcement). Social environmental factors included individual, inter-personal and organizational levels which is consistent with a social ecological framework. An adaptation of this framework was combined with the factors associated with the measure to illustrate the inter-relations and influence upon compliance, data accuracy and athletic outcomes. To improve implementation of ASRM and ultimately athletic outcomes, a multi-factorial and multi-level approach is needed. Key pointsEffective implementation of a self-report measure for monitoring athletes requires a multi-factorial and multi-level approach which addresses the particular measure used and the surrounding social environment.A well-designed self-report measure should obtain quality data with minimal burden on athletes and staff.A supportive social environment involves buy-in and coordination of all parties, at both an individual and organization level.

Entities:  

Keywords:  Training diary; athletic injury; overtraining; questionnaire; wellbeing

Year:  2015        PMID: 25729301      PMCID: PMC4306765     

Source DB:  PubMed          Journal:  J Sports Sci Med        ISSN: 1303-2968            Impact factor:   2.988


  40 in total

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Journal:  J Strength Cond Res       Date:  2010-10       Impact factor: 3.775

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9.  Procedures for assessing psychological predictors of injuries in circus artists: a pilot prospective study.

Authors:  Ian Shrier; John S Raglin; Emily B Levitan; Murray A Mittleman; Russell J Steele; Janette Powell
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10.  Implementing injury surveillance systems alongside injury prevention programs: evaluation of an online surveillance system in a community setting.

Authors:  Christina L Ekegren; Alex Donaldson; Belinda J Gabbe; Caroline F Finch
Journal:  Inj Epidemiol       Date:  2014-07-24
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  26 in total

1.  Impact of Sport Context and Support on the Use of a Self-Report Measure for Athlete Monitoring.

Authors:  Anna E Saw; Luana C Main; Paul B Gastin
Journal:  J Sports Sci Med       Date:  2015-11-24       Impact factor: 2.988

2.  Mobile Athlete Self-Report Measures and the Complexities of Implementation.

Authors:  Ciara M Duignan; Patrick J Slevin; Brian M Caulfield; Catherine Blake
Journal:  J Sports Sci Med       Date:  2019-08-01       Impact factor: 2.988

3.  Single-Item Self-Report Measures of Team-Sport Athlete Wellbeing and Their Relationship With Training Load: A Systematic Review.

Authors:  Ciara Duignan; Cailbhe Doherty; Brian Caulfield; Catherine Blake
Journal:  J Athl Train       Date:  2020-09-01       Impact factor: 2.860

4.  Predicting Youth Athlete Sleep Quality and the Development of a Translational Tool to Inform Practitioner Decision Making.

Authors:  Haresh T Suppiah; Richard Swinbourne; Jericho Wee; Qixiang He; Johan Pion; Matthew W Driller; Paul B Gastin; David L Carey
Journal:  Sports Health       Date:  2021-11-09       Impact factor: 3.843

5.  Investigating the Psychophysiological Response to Grade One Muscular Injuries in Professional Australian Football Athletes.

Authors:  Billymo Rist; Alan J Pearce; Anthea C Clarke
Journal:  Int J Exerc Sci       Date:  2022-07-01

Review 6.  Monitoring the athlete training response: subjective self-reported measures trump commonly used objective measures: a systematic review.

Authors:  Anna E Saw; Luana C Main; Paul B Gastin
Journal:  Br J Sports Med       Date:  2015-09-09       Impact factor: 13.800

Review 7.  Comparison of Non-Invasive Individual Monitoring of the Training and Health of Athletes with Commercially Available Wearable Technologies.

Authors:  Peter Düking; Andreas Hotho; Hans-Christer Holmberg; Franz Konstantin Fuss; Billy Sperlich
Journal:  Front Physiol       Date:  2016-03-09       Impact factor: 4.566

Review 8.  Troubleshooting a Nonresponder: Guidance for the Strength and Conditioning Coach.

Authors:  Benjamin H Gleason; William G Hornsby; Dylan G Suarez; Matthew A Nein; Michael H Stone
Journal:  Sports (Basel)       Date:  2021-06-05

9.  The Sports-Related Injuries and Illnesses in Paralympic Sport Study (SRIIPSS): a study protocol for a prospective longitudinal study.

Authors:  Kristina Fagher; Jenny Jacobsson; Toomas Timpka; Örjan Dahlström; Jan Lexell
Journal:  BMC Sports Sci Med Rehabil       Date:  2016-08-30

10.  Association between Match Activity Variables, Measures of Fatigue and Neuromuscular Performance Capacity Following Elite Competitive Soccer Matches.

Authors:  Ian Varley; Ryan Lewin; Robert Needham; Robin T Thorpe; Ross Burbeary
Journal:  J Hum Kinet       Date:  2017-12-28       Impact factor: 2.193

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