“We were leery of going”: qualitatively exploring Canadian international retirement migrants’ travel-related decisions during the COVID-19 pandemic
Notice bibliographique
Résumé
BACKGROUND: International retirement migration, which is the seasonal or permanent relocation of older people to another country, has grown in popularity in recent years. These retirees are motivated by the promise of warmer winter climates that are conducive to participating in health-promoting recreational and social activities. Ease of cross-border travel facilitates this transnational practice when undertaken seasonally. However, border closures and other travel-related measures put in place to manage the spread of COVID-19, disrupted travel, including for older Canadians who typically winter in the United States (US). During the 2020-21 winter season, for example, Canadians were advised not to engage in non-essential international travel and the land border between Canada and the US was closed to all but essential travellers. Nonetheless, retirement migration remained a significant draw for many Canadian retirees. Here, we qualitatively explore the factors that Canadian international retirement migrants considered when deciding whether or not to travel to the US for the 2020-21 winter during the COVID-19 pandemic. METHODS: Guided by case study methodology, semi-structured interviews were conducted with 31 Canadian international retirement migrants who had wintered in the US prior to the COVID-19 pandemic and were in the US at the outset of the pandemic in late winter 2020. Interviews were transcribed verbatim and thematically analyzed to decipher what factors were most important to their travel-related decision-making during the pandemic. We structure the thematic results around four factors previously identified to motivate older people to become international retirement migrants and thus inform decision-making: the destination, the people, the cost, and the movement. RESULTS: The previously identified factors that motivate older people to participate in international retirement migration include: the destination (e.g., climate and amenities), the people (e.g., social networks), the cost (e.g., health insurance and living costs), and the movement (e.g., ease of travel). These factors informed how international retirement migrants made decisions to travel abroad or not in the 2020-21 winter season. For example, destination-based factors included a lack of public health measures and high case counts, people-based factors comprised of less opportunities to engage in social activities, cost-based factors involved maintaining property investments and the lack of COVID-19 treatment coverage in available travel health insurance plans, and movement-based factors included challenges in ease of access when travel was viewed as essential or non-essential. These factors disincentivized or motivated international retirement migrants to travel abroad in the 2020-21 winter season during the COVID-19 pandemic. CONCLUSIONS: The results of this study support the need to create tailored decision-support tools for international retirement migrants to make informed travel-related decisions during crisis events so as to protect their health and wellbeing. More research is needed to explore perceptions of risk, especially health risks, among international retirement migrants and how they differently affect their travel-related decisions.
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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 | 0,006 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,018 | 0,011 |
| Communication savante | 0,006 | 0,003 |
| Science ouverte | 0,003 | 0,006 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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 ».