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Original Research

Role of a Self-report Measure in Athlete Preparation

Saw, Anna E.1; Main, Luana C.2; Gastin, Paul B.1

Author Information
The Journal of Strength & Conditioning Research: March 2015 - Volume 29 - Issue 3 - p 685-691
doi: 10.1519/JSC.0000000000000698
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Athlete monitoring involves systematically recording and evaluating athletic preparation. A recent survey identified that 91% of high performance sports used some form of athlete monitoring, with athlete self-report measures (ASRM) used most commonly and frequently (24). Self-report measures assess an athlete's subjective well-being and are favored for their relatively low cost and practical advantages over more traditional physiological and performance measures. However, to date, there is a lack of research to characterize, or guide, how ASRM are actually used in the applied sports setting.

In research settings, ASRM are typically used to evaluate the impact of an acute training phase or intervention on athlete well-being. As a result, ASRM have been demonstrated to be sensitive, reliable, and practical measures of the athlete state (for reviews see Refs. 17,25). Given the difference between top placings at elite competitions have been estimated to be 0.3–3% in various sports (12,20,23), and the negative consequences to performance associated with interrupted training in the event of an injury or illness (19), the ability to closely monitor the athlete state is appealing.

It is often purported in the literature that ASRM be implemented in the applied setting to enable the early detection of athletes at risk of nonfunctional overreaching, overtraining, or staleness (5,7,15,18). There is also empirical support for ASRM to identify athletes at risk of injury (1,9) and illness (26). For early detection and intervention, ASRM must be completed by athletes on a routine and ongoing basis, and data must be promptly interpreted and used to guide adjustments to practices. There are limited examples of such use of ASRM in the literature.

Research conducted in the applied setting has alluded to ASRM being used to adjust training during an acute overload period (21), competition period (16), or over the course of a season (3,10). However, only one of these studies has detailed how this actually occurred (3). This study established individual baselines on ASRM during the off-season, then implemented weekly monitoring during the season to identify elite canoeists who were at risk of becoming stale (more than 50% increase in mood disturbance with fatigue greater than vigor) and those who were insufficiently stressed (less than 10% increase in mood disturbance), and adjusted training load accordingly.

Beyond these examples, the purpose for or the process of ASRM use in the applied sport setting is unknown. Therefore, the aim of this study was to better understand how ASRM are being used in elite sports and their role in athletic preparation.


Experimental Approach to the Problem

As there is little prior knowledge in this area, a qualitative interview-based design was used. To ensure scientific rigor, techniques and guidelines for developing grounded theory were followed (6). Unlike other forms of enquiry, which seek to test a hypothesis, a grounded theory approach allows novel and unexpected themes to emerge from the perspectives of insiders (6). A national sporting institute was selected for data collection because of the elite level of athletes, diversity in sports, athlete experience, and access to experienced coaches and multidisciplinary support staff. A stratified purposeful sample of athletes, coaches, and sports science and medicine staff (SSMS) was sought, with recruitment continuing throughout the data collection period until no new information arose from further interviews.


Ethics approval was granted by both the university and national sporting institute human research ethics committees. Written informed consent was obtained from subjects after full-written and verbal explanation of the study and the opportunity to clarify any concerns. Subjects were 8 athletes, 7 coaches, and 15 SSMS at a national sporting institute. The subjects represented 20 different sports programs including 10 international-level individual sports (rowing, swimming, track and field, tennis, sailing, road cycling, track cycling, mountain biking, winter sports, and boxing), 4 international-level team sports (women's water polo, women's football, rugby union, and rugby league), and 6 elite youth team sports (men's football, men's and women's basketball, hockey, netball, and Australian football).

Athletes (aged 23.8 ± 3.9 years) had been at the national sporting institute for between 3 months and 10 years (4.9 ± 3.7 years). Staff had been at the national sporting institute for between 6 months and 24 years (6.4 ± 6.4 years) and had been working with athletes for 4 to 27 years (12.2 ± 6.9 years). Fourteen staff had additional experience in amateur sports, 9 had experience in professional sports, and 10 had experience in international sports settings. Thirteen staff also had experience as an athlete at a subelite or elite level. Further subject characteristics are outlined in Table 1.

Table 1
Table 1:
Subject characteristics.*†

Subjects had a range of experience with ASRM of both duration (3 months–15 years; 4.8 ± 3.4 years) and measures used. Subjects were currently using various in-house or customized commercial measures. These measures took a multidisciplinary approach, briefly assessing an athlete's subjective well-being alongside behaviors such as training, recovery, and nutrition. For the purposes of this research, the particular characteristics of the ASRM used (e.g., questions, format) were less relevant, rather the purpose and nature of their use in athlete preparation was important.


A semistructured interview schedule was developed with open-ended questions to allow novel insights to emerge. Interviews were conducted one-on-one by the first author at the national sporting institute and lasted approximately 20 minutes. The interview commenced with simple questions regarding the interviewee to both make them feel comfortable and also provide background information on what experiences may influence their responses. Subjects were then interviewed on their views and current practices related to ASRM use (Table 2). The same questions were used for all participants, with some interchanges of wording such as “you” for athletes and “the athletes you work with” for coaches and staff as necessary. Interviewees were prompted for further information or asked to explain or elaborate on points raised where appropriate. The interviews were audio recorded and supplemented with brief hand-written notes.

Table 2
Table 2:
Interview schedule.*

Statistical Analyses

Audio recordings and notes were labeled with a subject code with names recorded separately. Subject codes consisted of a letter representing the interviewee's role (A = athlete, C = coach, and S = SSMS) and numeric identifier. The first author transcribed all interviews verbatim from the audio recordings and rechecked them for accuracy. Complete text files of transcripts were imported into NVivo qualitative data analysis software (Version 10.0, 2012; QSR International Pty Ltd., Doncaster, Australia) for coding and data management.

The techniques of grounded theory were used to systematically develop an overarching theory while minimizing the potential for researcher bias (6). The approach involved identifying informative sections of text (meaning units), which were then coded to nodes, with nodes continually evolving as analysis progressed. Nodes were then grouped into lower and higher-order themes. This process was triangulated among all authors, with several revisions of the thematic structure made until all authors were in agreement.


Analysis of the transcripts revealed 695 meaning units, which related to the role of ASRM. The grouping of meaning units revealed 12 day-to-day and 7 longer-term practices (Table 3), each contributing to a 4-step process of ASRM use (record data, review data, contextualize, and act) (Figure 1).

Table 3
Table 3:
Thematic structure of the practices involved in athlete self-report measure use.*†
Figure 1
Figure 1:
The 4-step process of using a self-report measure in athlete preparation.

Record Data

Record Practices

Athletes recorded details of their training and related practices such as sleep, nutrition, and recovery. Training details included duration and a rating of perceived exertion, which enabled training across different modalities to be combined to calculate an overall training load. Such information enabled staff to identify whether or not athletes were achieving the desired training stress and preparing as intended.

Athlete Provision of Additional Information

Athletes used a free comments area to explain any unusual responses and alert staff to work or life events which may be affecting their preparation. Staff described such comments as “enlightening” and, in some cases, “a cry for help,” with athletes raising personal issues, which they may not have been comfortable raising in-person.

Indication of an Athlete's Current State

To supplement the information deemed on training and non-training loads experienced by an athlete, subjective well-being measures were used to indicate how well an athlete was “coping” with the load. This indication was used to determine whether an appropriate training stimulus and adaptive response was occurring.

Record Keeping

Longer-term record keeping was a fundamental use of ASRM, yet was only mentioned by 4 SSMS. Two key rationales for ASRM being used for record keeping were mentioned. First, record keeping was said to be an obligation, particularly in regards to being accountable for funding. Second, records provide superior accuracy over memories which are prone to bias, enabling the past to be reviewed.

Review Data

Review of Data

Coaches described how initially they would oversee the incoming ASRM data on a daily basis however this drifted to every few days or weekly. Reasons given were the time burden and reliance on SSMS to notify them of any concern which may arise. For SSMS, the frequency of overseeing the data ranged from daily to infrequently, depending on the relevance to their role and athlete compliance. Situations such as training camps, competition, or athletes of particular concern would prompt a higher frequency of reviewing the data by both the coach and SSMS.

Red Flag Identification

It was intended that ASRM would act as an “early alert system,” identifying potential issues and enabling a more “proactive rather than reactive” approach. Monitoring software enabled automated alerts to be programmed and sent to staff; however, the criteria for what constituted a red flag was arbitrary and varied.

Athlete Response Patterns

Consistent, longitudinal data collection over a full training phase or more was intended to reveal athlete response patterns or “trends.” From these patterns, staff could “get a feel for acute and chronic responses of athletes” (S02) and review circumstances associated with an undesired outcome, with the ultimate goal of determining what loads an athlete could and could not handle. A couple of examples were provided where staff had noted patterns in data, such as an acute peak in training load preceding injury; however, they acknowledged the flaws and lack of scientific rigor in this approach.

Athlete Education and Awareness

Through use of an ASRM, athletes were more aware of the many factors outside of training which influence their performance and allowed them to be “more in tune with themselves.” There were also instances of injured athletes gaining a better understanding of their capacities and limitations. Some drawbacks observed included the tendency to “over-swing or under-swing” with a heightened awareness or downplaying of potential issues, respectively, or athletes responding out of habit rather than reflecting on their true current state.


Context of Knowing Athlete

There remained an element of “art” to interpreting an athlete's data based on what staff knew about an athlete. For instance, knowledge of personal circumstances and personality traits would be taken into account when determining the accuracy and significance of unusual responses.

Initiate Communication Between Staff and Athlete

As one of the most commonly cited practices of ASRM use, communication between the staff and athlete took several forms. Staff viewed unusual responses or comments as “an invitation to start a conversation” with an athlete to find out more information. Advantages of this approach were that athletes were made aware that someone was looking at and cared about the data they were entering in their ASRM and that staff could approach conversations in a more targeted and efficient manner. Targeted conversations were particularly useful for staff with large squads, or who had less contact with the athletes, where regular individual conversations were impractical. By comparison, staff who would spend prolonged time with athletes, such as at recovery or physical therapy sessions, mentioned looking at the athlete's ASRM before their attendance and using the information as a conversation starter. In addition to face-to-face communication, conversations were also initiated by phone calls, e-mail, and mobile text messages.

Initiate Communication Between Staff

The initiation of communication and coordination among coaches and SSMS was the most commonly cited practice of ASRM use. The multidisciplinary ASRM were said to keep all staff “on the same page” in regards to the different aspects of athletic preparation. It was suggested that this “should increase the amount of coordinated communication between different therapists, coaches, athletes, and service providers as they have got a commonality or something to talk about, a reason to be communicative” (C06). However the level of communication was said to be “very individual with the support staff… and who is willing to be forthcoming and open and collaborative across disciplines” (C01). Nevertheless, both informal and formal communications were facilitated among staff to draw on different areas of expertise, other data and observations, and ultimately agree on “an action plan.” A key staff member or coach was generally needed to control inputs and convey a unified message to the athlete.

Build Knowledge

Identification of possible relationships between ASRM variables, other variables (e.g., training), and outcomes (e.g., performance, injury) improved understanding of athletic preparation. However, attempts to use such data in applied research were unsuccessful due to a lack of data integrity.


Feedback to the Athlete

Without feedback, ASRM were described as “faceless” or a “black hole” where athletes would see no return for their effort. Often, athletes would only receive feedback if their data were concerning, leaving other athletes responding well to lose interest in the measure. It was commented that feedback needs to be in real time, not lagging by a few weeks, and provide added value of interpretation rather than just re-presenting the data. Yet for staff, “it takes a lot of time and effort to give (athletes) meaningful feedback” (S03). Hence instead of written reports, the simplest and most effective form of feedback was through conversations.

Feedback to the Coach

As for athletes, feedback to coaches was said to be essential for them to see value in ASRM. Feedback was required in a timely manner and easy to interpret format. As 1 coach commented, “I don't feel that I'm quite qualified enough to read (the raw data)” (C07), and so interpretation by SSMS was necessary.

Training Prescription and Modification

Training prescription was said to be fine-tuned in response to ASRM data with “day-to-day manipulation of their training loads based on how they are doing… stressing them as much as we can without putting them over the edge” (S15). Similarly, it was intended to avert undesired outcomes as “hopefully there are early indicators… [so] we can lighten back on the load and freshen them up a bit and hopefully keep the athletes injury free and get as many training days out of them as possible” (C05). However, 1 caveat of this approach was the potential for athletes to manipulate the process through inaccurate responses in their ASRM.


Another common approach for managing the athlete state was targeted referral to the appropriate support staff. Common examples for referral were the detection of poor habits such as sleep and nutrition, unfavorable psychological states, and soreness, which may compromise both athletes' well-being and performance if not addressed. Referral would either occur through suggestion to the athlete to seek assistance or through direct contact from the relevant staff.

Training and Program Planning

Subsequent to an improved understanding of athletic preparation, informed modifications were said to be made to training loads, periodization plans and event scheduling. Specific examples given included revising the program schedule to reduce the stress experienced by athletes and identifying an optimal training load for performance and reduced risk of injury.

Athlete Self-management

An increased sense of accountability and consequently improved self-management behaviors were suggested to result from ASRM use. However, 6 athletes denied this was the case, and 1 SSMS thought such a process was “too linear” as it relies on the athlete knowing what and how to respond. Nevertheless, 6 staff provided specific examples of 1 or more of their athletes improving their self-management in response to their ASRM such as taking the initiative to seek further information and assistance from staff; forming better habits; and being “less likely to sit on pain and injury.” Another example was an athlete who was using their ASRM to help them “leave no stone unturned” toward their Olympic goal.

Prevent Undesired Outcomes

An ultimate objective of ASRM use was to prevent undesired outcomes such as injury, illness, overtraining, and poor performance. One SSMS was confident that ASRM was achieving this objective in their sport, whereas another gave an example of how an ASRM had helped to get an athlete “back on track pretty quickly.” Other interviewees saw such potential, however, accompanied their comments with words such as “hoping,” “ideal,” and “ultimately.” One coach and 1 SSMS expressed opposing views, emphasizing that preventing undesired outcomes was a common misconception but was not the reason for ASRM use. Instead, they felt that an ASRM was like “an insurance package” to improve understanding and management when undesired outcomes inevitably occur.


The findings of this study affirm the purported role of ASRM in the applied setting, namely identifying undesired athlete responses and intervening as necessary. In addition to these, further day-to-day and longer-term practices were identified including the facilitation of communication, athlete self-management, and better understanding of athletic preparation. Collectively, each practice contributed to a 4-step cyclical process of recording, reviewing, contextualizing, and acting on data (Figure 1).

If athletes and sports programs are to invest in ASRM, each of the 4 steps must be well implemented to ensure the purported benefits are achieved. The steps of recording and reviewing data are susceptible to the inherent limitations of self-report such as measurement error and conscious bias (2). Consequently, ASRM data were used as an indicator of the athlete state, directing staff to seek further contextual information. As a result, the overwhelming role of an ASRM in athletic preparation was the facilitation of communication between all parties.

The nature of self-report removes personal and locational barriers to communication, encouraging greater disclosure of potentially relevant information to staff. Such disclosure has been quantified among professional athletes who reported 96% of illness to an online measure compared with only 19% reported to staff in-person (8). Disclosure through additional comments on an ASRM was particularly valued by all parties, a finding previously identified among coaches (22). The initiation of targeted conversations in response to ASRM data provided an efficient and purposeful approach to address a particular concern. Increased conversations between the athlete and coach may improve the athlete-coach relationship, which has been shown to have psychological (13) and performance (11) benefits for the athlete. Among staff, the ASRM facilitated discussions to broaden the insight and expertise used to determine the best approach for the management of athletes.

Athlete management may be improved as a result of ASRM increasing understanding of athlete preparation and in turn, guiding future practices. This is not only the case for staff, but athletes as well. Use of an ASRM encourages athletes to reflect on their preparation, and through a sense of accountability, act to improve their self-management practices in a manner similar to the self-regulation theory (14). However such self-awareness and education takes considerable time and effort (4), which may explain the mixed views of interviewees in this study. The variable engagement of athletes with their ASRM is another factor limiting the strength of this finding.

Engagement of all parties is essential to drive the cyclic process of ASRM use. The final step of action is dependent on the previous steps yet is also an important stimulus for ongoing data input. Therefore, it is important that athletes, coaches, and SSMS have a shared understanding of the role of ASRM and the systematic process required to benefit athlete preparation. The 4-step process identified in this study may be used as a framework for an educational strategy to achieve such understanding.

It must be acknowledged that this study did not attempt to reveal an exhaustive list of ASRM practices or represent all users and sports settings; hence, the transferability of the findings may be limited to the present context. The identified roles of ASRM in athlete preparation, in particular the facilitation of communication and improved athlete management, warrant further investigation through a prospective research design. As it is important that all parties understand the role and process of ASRM use, educational interventions should also be developed and evaluated.

Practical Applications

Athlete preparation is complex, involving the inputs of the athlete, coach, and various support staff. By recording an athlete's preparation and how they are responding, ASRM are a vehicle to facilitate communication between the athlete and staff, and also among staff. As a result, more informed and coordinated decisions can be made to improve practices of both the athlete and staff. However, the efficacy of ASRM use is dependent on all parties being actively engaged in the process day-to-day and in the longer-term. Hence, educational strategies may need to be implemented to ensure a shared understanding of the roles and process of ASRM use among athletes, coaches, and support staff.


This study is part of a doctoral program funded by the Australian Institute of Sport. The authors have no conflicts of interest to declare.


1. Andersen MB, Williams JM. Athletic injury, psychosocial factors and perceptual changes during stress. J Sports Sci 17: 735–741, 1999.
2. Baldwin W. Information no one else knows: The value of self-report. In: The Science of Self-report: Implications for Research and Practice. Stone AA, Turkkan JS, Bachrach CA, Jobe JB, Kurtzman HS, Cain VS, eds. Mahwah, NJ: Lawrence Erlbaum Associates, 2000. pp. 3–7.
3. Berglund B, Safstrom H. Psychological monitoring and modulation of training load of world-class canoeists. Med Sci Sports Exerc 26: 1036–1040, 1994.
4. Botterill C, Wilson C. Overtraining: Emotional and interdisciplinary dimensions. In: Enhancing Recovery: Preventing Underperformance in Athletes. Kellman M, ed. Champaign, IL: Human Kinetics, 2002. pp. 143–159.
5. Brink MS, Visscher C, Coutts AJ, Lemmink KA. Changes in perceived stress and recovery in overreached young elite soccer players. Scand J Med Sci Sports 22: 285–292, 2012.
6. Corbin J, Strauss A. Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory (3rd ed.). Thousand Oaks, CA: SAGE Publications, Inc., 2008.
7. Coutts AJ, Slattery KM, Wallace LK. Practical tests for monitoring performance, fatigue and recovery in triathletes. J Sci Med Sport 10: 372–381, 2007.
8. Cunniffe B, Griffiths H, Proctor W, Jones KP, Baker JS, Davies B. Illness monitoring in team sports using a web-based training diary. Clin J Sport Med 19: 476, 2009.
9. Galambos S, Terry PC, Moyle G, Locke S. Psychological predictors of injury among elite athletes. Br J Sports Med 39: 351–354, 2005.
10. Gastin PB, Meyer D, Robinson D. Perceptions of wellness to monitor adaptive responses to training and competition in elite Australian football. J Strength Cond Res 27: 2518–2526, 2013.
11. Gould D, Guinan D, Greenleaf C, Medberty R, Peterson K. Factors affecting olympic performance: Perceptions of athletes and coaches from more and less successful teams. Sport Psychol 13: 371–394, 1999.
12. Jeukendrup AE, Martin J. Improving cycling performance. Sports Med 31: 559–569, 2001.
13. Jowett S, Cockerill I. Olympic medallists' perspective of the athlete–coach relationship. Psychol Sport Exerc 4: 313–331, 2003.
14. Kanfer FH, Karoly P. Self-control: A behavioristic excursion into the lion's den. Behav Ther 3: 398–416, 1972.
15. Kellmann M. Preventing overtraining in athletes in high-intensity sports and stress/recovery monitoring. Scand J Med Sci Sports 20(Suppl 2): 95–102, 2010.
16. King D, Clark T, Kellmann M. Changes in stress and recovery as a result of participating in a Premier Rugby League Representative competition. Int J Sports Sci Coach 5: 223–237, 2010.
17. Meeusen R, Duclos M, Foster C, Fry A, Gleeson M, Nieman D, Raglin J, Rietjens G, Steinacker J, Urhausen A. Prevention, diagnosis and treatment of the overtraining syndrome: Joint consensus statement of the European College of Sport Science (ECSS) and the American College of Sports Medicine (ACSM). Eur J Sport Sci 13: 1–24, 2013.
18. Morgan WP, Costill DL, Flynn MG, Raglin JS, O'Connor PJ. Mood disturbance following increased training in swimmers. Med Sci Sports Exerc 20: 408–414, 1988.
19. Mujika I, Padilla S. Detraining: Loss of training-induced physiological and performance adaptations. Part I: Short term insufficient training stimulus. Sports Med 30: 79–87, 2000.
20. Pyne DB, Trewin CB, Hopkins WG. Progression and variability of competitive performance of Olympic swimmers. J Sports Sci 22: 613–620, 2004.
21. Raglin JS. Overtraining and staleness: Psychometric monitoring of endurance athletes. In: Handbook of Research on Sport Psychology. Singer RN, Murphey M, Tennant LK, eds. New York, NY: Macmillan, 1993. pp. 840–850.
22. Roos L, Taube W, Brandt M, Heyer L, Wyss T. Monitoring of daily training load and training load responses in endurance sports: What do coaches want? Schweiz Z Sportmed Sporttraumatol 61: 30–36, 2013.
23. Smith TB, Hopkins WG. Variability and predictability of finals times of elite rowers. Med Sci Sports Exerc 43: 2155–2160, 2011.
24. Taylor K, Chapman D, Cronin J, Newton M, Gill N. Fatigue monitoring in high performance sport: A survey of current trends. J Aust Strength Cond 20: 12–23, 2012.
25. Urhausen A, Kindermann W. Diagnosis of overtraining: What tools do we have? Sports Med 32: 95–102, 2002.
26. Zorrilla EP, Luborsky L, McKay JR, Rosenthal R, Houldin A, Tax A, McCorkle R, Seligman DA, Schmidt K. The relationship of depression and stressors to immunological assays: A meta-analytic review. Brain Behav Immun 15: 199–226, 2001.

training diary; questionnaire; athlete monitoring; well-being; overtraining; injury prevention

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