Mapping Physical Activity Participation Barriers and Facilitators in Older East Asian Canadian Immigrants: A Scoping Review Protocol
Notice bibliographique
Résumé
Exercise and physical activity has long been considered within the scientific community as a holistic remedy to upkeep health and wellbeing, with its multifaceted benefits thoroughly documented within the literature. It comes as no shock that within the aging population, there is a significant association between the health status of an individual, and the amount of physical activity they perform and integrate into their lives (Merom et al., 2012). However, despite these findings, within marginalized aged populations, more specifically, East Asian older adult immigrants in Canada, it is reported that a substantial portion of their time is spent devoted to sedentary activities post immigration (Tong, 2019). Understandably, this can be attributed to a multiplex of factors contributing to their lack of participation and sedentary behaviour, including various SES factors, societal barriers, lack of knowledge or education, low intrinsic motivation, current health status, stigma or personally held biases and beliefs, or just overall reduced vitality and diminished initiative, to name a few. This places an avoidable and unjustified negative impact on their healthspan, which could be readily mitigated and effectively addressed if their participation within physical activity could somehow be enhanced. Gaps in the literature currently include what factors inhibit this population from higher participation rates towards existing physical activity programs in Canada, and how to reduce this gap to promote equitable access to the health benefits of physical activity observed among non-marginalized older adults. (Bryan & Walsh, 2012). The question (and objective of scoping literature review) is then posed: What barriers do East Asian older adult immigrants face towards physical activity programming participation in Canada? In addition, what are some facilitating factors that, if amplified, would possibly promote higher engagement and adhesion towards physical activity for this population? For the methodological framework of the scoping review, I will be following Arksey and O’Malley’s proposed framework. The following databases have been selected for preliminary search, Medline OVID, CINAHL, Scopus, Web of Science (WoS), and SPORTDiscus (via EBSCOhost). Inclusion criteria will include sources published in English, sources published between 1990-2025, as the 90s marked a notable increase in East Asian immigrants among new arrivals, and research pertaining to exercise participation. Data will be extracted and thematically analyzed through the generation of a data chart via Excel, and thematic analysis will take place through iterative coding via NVivo. Results will be shared primarily via academic publications, community outreach channels, and will be included in my final thesis project. It is anticipated that the map will be used to inform the target population, exercise program directors, and wider municipal or national policy makers of the current constraints faced by older East Asian immigrants towards participation within existing physical activity programming, and potential future directions to explore to encourage elevated participation rates. Ultimately, the goal is to optimize the health benefits that physical activity can provide to support aging in place for this population. Ethics approval at the current time is inessential as the current scoping review protocol does not call for live subjects.
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 | 0,045 | 0,045 |
| Méta-épidémiologie (sens strict) | 0,004 | 0,005 |
| Méta-épidémiologie (sens large) | 0,011 | 0,012 |
| Bibliométrie | 0,017 | 0,012 |
| Études des sciences et des technologies | 0,007 | 0,004 |
| Communication savante | 0,008 | 0,005 |
| Science ouverte | 0,005 | 0,005 |
| Intégrité de la recherche | 0,006 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,059 | 0,007 |
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 ».