The Exploration, Ideation, and Design of Athlete Retirement Prototypes for the Canadian High-Performance Sport System
Notice bibliographique
Résumé
High-performance athletes' (HPAs) engagement in proactive retirement preparation has become increasingly important for their well-being and quality of life during and after sport. As researchers continue to highlight the plethora of challenges underprepared HPAs face when retiring from sport, retirement support available to Canadian HPAs through Game Plan continues to be significantly underutilized (Game Plan, 2023). Researchers have identified environmental barriers as an influencing factor determining athletes' ability to access and utilize available forms of retirement support (Brassard et al., 2022). Current literature lacks the use of a holistic lens to identify the organizational factors that act as barriers and facilitators faced by athletes in this regard. An exploration with this lens could enhance our understanding of HPAs' ability to prepare for retirement by providing insights into the organizational interplay sport members have in facilitating a sport environment that enables, restricts, or hinders a HPA's ability to prepare for life after sport. Furthermore, a holistic lens can provide researchers with the necessary information to develop further frameworks and strategies to minimize athlete retirement barriers (Stambulova et al., 2020). The purpose of this doctoral dissertation is to address this gap through the following objectives: (a) examine how active and retired athletes utilized retirement support mechanisms, (b) explore high-performance sport members' perspectives and understanding of retirement support mechanisms, and (c) facilitate co-design sessions to innovate solution-driven prototypes to address sport members' athlete retirement needs. The methodologies of Bronfenbrenner's Ecological Systems theory and Design Thinking were adopted to guide and facilitate this research. This dissertation is composed of three articles, each correlating with the research objectives. With the first research objective, a secondary data analysis was used to examine how athletes in the Canadian sport system were utilizing Game Plan's resources from 2019-2021. This examination provided insight into athletes' Game Plan usage discrepancies when drawing comparisons to the funding each National Sport Organization (NSO) earned, their league of competition (e.g., Para or Non-Para sport), and repeat uses of Game Plan's resources after an initial interaction. As a result of the findings from this examination, considerations are proposed for sport organizations who seek to improve their athlete engagement with Game Plan's retirement resources. The second objective was investigated through empathy interviews (Kelley & Kelley, 2013) conducted with active athletes, retired athletes, support personnel, and performance partners across the sport system. A total of 19 individuals were interviewed. Empathy interviews were used to create personas for each role. Findings from this exploration add to the literature by outlining the following empirical findings: (a) high-performance sport members have limited knowledge and understanding of accessible retirement resources, (b) sport organizations' cultures can present barriers or facilitators through direct and indirect messages to athletes, and (c) HPAs who proactively sought out support or had a good sport-life balance experienced fewer challenges adapting to life after sport. The third and final objective was supported via the Stanford d. school's five-step Design Thinking model: empathize, define, ideate, prototype, and test. This section of research consisted of a co-design session conducted with two groups of participants. In each session, participants were led through brainstorming cluster activities to define, ideate, design, and evaluate athlete retirement solution-driven prototypes. Sport members collaboratively designed the following three evidenced-based prototypes: (a) creating a new funding metrics system, (b) strengthening collaboration between NSOs and Game Plan, and (c) enhancing athlete retirement coach education. The Design Thinking process as well as the insights outlining why and how the adoption of each prototype can advance HPAs' ability to prepare for their lives after sport are discussed. This article is the first to adopt a Design Thinking approach to advance athlete retirement literature and aims to serve as a catalyst for researchers to adopt Design Thinking methods to further the field of sport performance psychology. The results of this doctoral dissertation research add empirical, theoretical, and methodological contributions to both the athlete retirement and Design Thinking literature.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,009 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,006 |
| Communication savante | 0,006 | 0,003 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».