Monitoring athletes through self-report: factors influencing implementation

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.

The role of a self-report measure in athlete preparation

Athlete self-report measures (ASRM) are a common and cost-effective method of athlete monitoring. It is purported that ASRM be used to detect athletes at risk of overtraining, injury or illness, allowing intervention through training modification. However it is not known whether ASRM are actually being used for or are achieving these objectives in the applied sport setting. Therefore the aim of this study was to better understand how ASRM are being used in elite sports and their role in athletic preparation. Semi-structured interviews were conducted one-on-one with athletes, coaches and sports science and medicine staff (n=30) at a national sporting institute. Interview recordings were transcribed and analysed for emergent themes. Twelve day-to-day and seven longer-term practices were identified which contributed to a four-step process of ASRM use (record data, review data, contextualize, act). In addition to the purported uses, ASRM facilitated information disclosure and communication amongst athletes and staff and between staff, and improved the understanding and management of athlete preparation. These roles of ASRM are best achieved through engagement of athletes, coaches and support staff in the systematic, cyclic process.

Drug use in Australian nightlife settings: estimation of prevalence and validity of self-report

AIMS: This study aimed to 1) estimate the prevalence of illicit drug use in night-time entertainment districts across five major cities in Australia; and 2) validate self-reported drug use using biochemical marker oral swabs. DESIGN: Street intercept surveys and oral drug swabs conducted over a seven-month period during 2011-2012. SETTING: The night-time entertainment districts of three metropolitan cities (Sydney, Melbourne and Perth) and two regional cities (Wollongong and Geelong) in Australia, between the hours of 10 pm and 5 am. PARTICIPANTS: 7,340 individuals agreed to participate in the survey (a 93% response rate). More than half (62%) of the sample was male, with a median age of 22 years (range 18-73). MEASUREMENTS: Patrons were approached in thoroughfares, and while entering and leaving licensed venues. Data collected included demographics and current session alcohol and other substance use. Drug swabs (n = 401) were performed with a sub-sample of participants. FINDINGS: Approximately 9% (95% CI, 7% to 12%) of participants self-reported consumption of illicit or non-prescribed pharmaceutical drugs prior to interview; of those, 81% identified psychostimulants as the drug used. One in five drug swabs returned a positive result, with psychostimulants the most commonly detected drugs (15%; 95% CI, 12%-19%). Kappa statistics indicate agreement between self-report of any illicit drug and a positive drug swab is in the slight range (κ = 0.12 (95% CI, .05 to .20) p = .000). CONCLUSIONS: Self-report findings suggest drug use in the nightlife in Australia is common, though still very much a minority past-time. Drug swabs indicate a higher prevalence of use (20%) than self-report (9%), which suggests that self-reported drug use may not be reliable in this context. This article is protected by copyright. All rights reserved.

Impact of sport context and support on the use of a self-report measure for athlete monitoring

Athlete self-report measures (ASRM) are a popular method of athlete monitoring in high-performance sports. With increasing recognition and accessibility, ASRM may potentially be utilized by athletes from diverse sport contexts. The purpose of the present study was to improve understanding of ASRM implementation across different sport contexts by observing uptake and compliance of a newly implemented ASRM over 16 weeks, and investigating the perceived roles and factors influencing implementation. Athletes (n=131) completed an electronic survey at baseline and week 16 on their perceptions and experiences with ASRM implementation respectively. Despite initial interest, only 70 athletes attempted to use the ASRM. Of these athletes, team sport athletes who were supported by their coach or sports program to use the ASRM were most compliant (p < 0.001) with a mean compliance of 84 ± 21 %. Compliance for self-directed individual and team sport athletes was 28 ± 40 % and 8 ± 18 % respectively. Self-directed athletes were motivated to monitor themselves, and rated desired content and minimal burden as key factors for initial and ongoing compliance. Supported athletes were primarily motivated to comply for the benefit of their coach or sports program rather than themselves, however rated data output as a key factor for their continued use. Factors of the measure outweighed those of the social environment regardless of sport context, however the influence of social environmental factors should not be discounted. The findings of the present study demonstrate the impact of sport context on the implementation of an ASRM and the need to tailor implementation strategies accordingly. Key pointsAthletes perceive ASRM and the factors influencing implementation differently. Therefore, to encourage compliance, it is important to tailor implementation strategies to the athlete and their sport context to increase appeal and minimize unappealing factors.Athletes using an ASRM on their own accord typically favor a measure which meets their needs and interests, with minimal burden.Athletes using an ASRM under the direction and support of their coach or sports program typically favor feedback and a positive social environment.

Self-report measures in athletic preparation

This thesis provides theoretical and applied support for the use of self-report measures for athlete monitoring. Athlete self-report measures were found to effectively reflect the training response, whilst also providing a means to improve communication, confidence, and regulation of athletic preparation. Context-specific guidelines for implementation were also identified.

Self-report use-of-time tools for the assessment of physical activity and sedentary behaviour in young people: systematic review

UNLABELLED: Regular physical activity and limiting extended periods of sitting are two behaviours critical for the prevention of obesity in young people. The purpose of the systematic review was to synthesize the psychometric evidence for self-report use-of-time tools that assess these behaviours. Articles were retrieved that reported reliability and/or validity for use-of-time tools in participants aged 18 years or under. Outcome variables were physical activity, sedentary behaviour and energy expenditure. Study quality was appraised, and the results summarized narratively. Sixteen studies and six different tools were identified. The tools were the Previous Day Physical Activity Recall, the Three-Day Physical Activity Recall, the Physical Activity Interview, the Computerized Activity Recall, the Activitygram, and the Multimedia Activity Recall for Children and Adolescents. Overall, tools indicated moderate validity compared with objective and criterion comparison methods. Generally, validity correlation coefficients were in the range of 0.30-0.40. Correlation coefficients for test-retest reliability ranged widely from 0.24 to 0.98. CONCLUSION: Use-of-time tools have indicated moderate reliability and validity for the assessment of physical activity and energy expenditure. Future research should focus on using criterion methods and on validating specifically for sedentary behaviour outcomes. Implementation of these tools for population surveillance should be considered.