Athlete monitoring has grown to reflect standard practice in athletic preparation and there remain few facets of performance that cannot or are not being measured in the quest for competitive advantage. Training load monitoring, performance measurement and training load response are some of a suite of factors employed to maximize the positive effects and minimize the negative effects of training, informing workload and recovery (Gabbett et al., 2017). One such suite are athlete self-report measures (ASRM): records of perceived physical, psychological and/or social well-being (Saw et al., 2016). ASRM can offer simplicity, affordability
and practical advantages over other traditional methods of athlete monitoring such as physiological measurement (Main and Grove, 2009; Buchheit et al., 2013; Halson, 2014; Saw et al., 2015b), and validated measures have been shown to accurately reflect training-induced changes in athlete well-being (Saw et al., 2016). Through their accessibility and potential to monitor both sport and non-sport stressors, ASRM are a well-placed and attractive athlete monitoring option for sport at many levels, as they can often be implemented with minimal financial investment and staffing expertise (Saw et al., 2015a). Typically, ASRM in practice are digitized, short, customized or commercially available measures designed for daily completion, which are favored by coaches for their ease of use, sport specificity and automation capacity (Taylor et al., 2012; Gastin et al., 2013; Saw et al., 2015c). These digital ASRM, whether custom or commercial will be referred to here as mobile athlete self-report measures, or M-ASRM.
Gaelic Games are the national sports of Ireland, typically known by the dynamic field sports of football, hurling and camogie. Gaelic Games remain amateur sports but at the elite level have been known to demand a professional attitude to the game in their training and preparation (Cromwell et al., 2000; Kelly et al., 2018). As such, Gaelic Games are well-placed to benefit from such M-ASRM, where an amateur sport with a professional approach exists. However, the individual adoption of M-ASRM can often come without due consideration of their use processes and with a proposed rationale for implementation based on personal experience rather than scientific support.
Because the optimal utilization of athlete monitoring systems requires a significant investment of time, financial and human resources to obtain, analyze and leverage the data effectively (Saw et al., 2015c), the early adoption of M-ASRM without due consideration of these processes will have a profound effect on its success and value. Therefore, the drivers of an M-ASRM implementation strategy in practice should be the anticipated purpose and consideration of practical limitations of the use-context with respect to personal, socio-contextual and system factors (Ekegren et al., 2014; Saw et al., 2015c). As such, published recommendations for successful ASRM implementation include pre-planning with respect to feasibility, analysis and interpretation, in addition to the engagement of stakeholders and development of a supportive culture (Saw et al., 2017a).
Social-environmental considerations for ASRM implementation in applied practice include stakeholder buy-in and reinforcement (Saw et al., 2015c) and team sport athletes in particular have been shown to place a greater perceived importance on ASRM output and the buy-in of their coaches in their use of an ASRM (Saw et al., 2015c). Interestingly, previous research has identified a lack of understanding from athletes regarding the purpose and benefits of their training monitoring system (Neupert et al., 2018). Suggestions for the scope of athlete education have been described (Saw et al., 2015c), however, athlete uncertainty regarding how to access and interpret their results has been evident even where a preceding education session has taken place (Neupert et al., 2018). Effective education can address the expectations, motivation and self-efficacy of users and should be followed by ongoing support to improve skills, aid problem solving and maintain motivation (Durlak and DuPre, 2008). However, research investigating the use of these methods in M-ASRM implementation in applied sport is sparse.
Successful implementation of an M-ASRM presents a significant and complex challenge for elite sport and to date, there is limited research concerning the implementation processes employed for M-ASRM use, particularly in elite Gaelic Games. There is a requirement for context-specific knowledge on the implementation complexities and perceptions of M-ASRM use to inform the development of effective implementation guidelines that are based on the needs and preferences of users. Therefore, the aim of this study was to investigate stakeholder perceptions of the implementation and understanding of a pre-existing M-ASRM in the elite Gaelic Games setting.
Twenty-one M-ASRM users in elite Gaelic Games were recruited for this study (players n=10, coaches and support staff (CSS) n = 11), see Table 1. Participants were recruited via opportunity and snowball sampling, where invitations to partake were sent via email. Participants were required to have used an M-ASRM for a minimum of one month and be aged 18 or over. There were no exclusion criteria. The available population consisted of players and CSS from twelve male and three female elite Gaelic Games teams. Ethical approval for this study was granted by University College Dublin Human Research Ethics Committee and participants were advised of their right to withdraw from the study at any stage.
The qualitative approach of semi-structured interviewing was employed to gain insight into the perceptions of participants using an M-ASRM in their individual contexts, as it can allow disclosure of important and often hidden aspects of human and organizational behavior (Qu and Dumay, 2011). The lead author (CD) conducted all interviews and was previously familiar to five of the participants. Interviews were conducted at locations convenient for the participant (e.g. in a meeting room at their training ground) or via telephone if required. Interviews were navigated with the use of a topic guide utilizing open-ended questions (Table 2). The topic guide allowed participants to be interviewed relatively systematically, while enabling new areas of conversation to be explored (Qu and Dumay, 2011). The lead researcher was an 'insider' who had previous clinical experience in the use of M-ASRM in Gaelic Games. This 'insider' status may have aided the development of an initial rapport with participants and equally will have influenced the interpretation of conversation through both shared and conflicting experience (Cowan and Taylor, 2016). Acknowledging the position of the lead author to bring 'insider' perspectives to the study (Carless and Douglas, 2013) and concurrently recognizing the influence of this potential bias, the topic guide was collaboratively formulated by two authors. Open-ended guide questions were developed to cover the broad areas of introduction, rationale and use of M-ASRM, to gain insight into the perceptions of and relationships between these factors. For the purposes of this investigation, it was less important to consider specific features of the M-ASRM used, focusing instead on how it was implemented and understood. Interviews were reviewed by authors CD and PS after completion, to reflect on the topic guide and knowledge co-construction (Roulston, 2010).
Interviews were transcribed verbatim and analyzed using NVivo 12 software. Transcripts were coded as follows: players were coded with the letter P and a number identifier, while CSS were coded with the letter C and a number identifier, e.g. P001 & C001. Thematic analysis of the transcripts adopted an inductive approach to allow patterns to emerge from the data (Walsh et al., 2015), with the topic guide providing an initial structure for the codebook (Saldana, 2015). Thematic analysis involved careful reading and re-reading of the data to identify patterns, assign codes, and formulate themes and sub-themes (Braun and Clarke, 2006; Fereday and Muir-Cochrane, 2017). A sample of the transcripts were analyzed by 'insider' CD and 'outsider' PS (Carless and Douglas, 2013) and key concepts were discussed and challenged in the development of the higher and lower order themes in the codebook (DeCuir-Gunby et al., 2011; Fereday and Muir-Cochrane, 2017). Data were then coded independently by CD and PS, and subsequently discussed in the development of interpretations (Thomas, 2006). To ensure design and analytical rigor through reflexivity, the interviewing procedure was reviewed, and data were micro-analyzed by CD and PS throughout the data collection process (Roulston, 2010). Critical dialogue between all authors on data analysis and construction of interpretations continued throughout this process and during drafting...