Implementing Technology Literacy Programs in Retirement Homes and Residential Care Facilities: Conceptual Framework
Notice bibliographique
Résumé
BACKGROUND: The COVID-19 pandemic caused widespread societal disruption, with governmental stay-at-home orders resulting in people connecting more via technology rather than in person. This shift had major impacts on older adult residents staying in retirement homes and residential care facilities, where they may lack the technology literacy needed to stay connected. The enTECH Computer Club from the University of Waterloo in Ontario, Canada created a knowledge translation toolkit to support organizations interested in starting technology literacy programs (TLPs) by providing guidance and practical tips. OBJECTIVE: This paper aimed to present a framework for implementing TLPs in retirement homes and residential care facilities through expanding on the knowledge translation toolkit and the framework for person-centered care. METHODS: Major concepts relating to the creation of a TLP in retirement homes and residential care facilities were extracted from the enTECH knowledge translation toolkit. The domains from the framework for person-centered care were modified to fit a TLP context. The concepts identified from the toolkit were sorted into the three framework categories: "structure," "process," and "outcome." Information from the knowledge translation toolkit were extracted into the three categories and synthesized to form foundational principles and potential actions. RESULTS: All 13 domains from the framework for person-centered care were redefined to shift the focus on TLP implementation, with 7 domains under "structure," 4 domains under "process," and 2 domains under "outcome." Domains in the "structure" category focus on developing an organizational infrastructure to deliver a successful TLP; 10 foundational principles and 25 potential actions were identified for this category. Domains in the "process" category focus on outlining procedures taken by stakeholders involved to ensure a smooth transition from conceptualization into action; 12 foundational principles and 9 potential actions were identified for this category. Domains in the "outcome" category focus on evaluating the TLP to consider making any improvements to better serve the needs of older adults and staff; 6 foundational principles and 6 potential actions were identified for this category. CONCLUSIONS: Several domains and their foundational principles and potential actions from the TLP framework were found to be consistent with existing literatures that encourage taking active steps to increase technology literacy in older adults. Although there may be some limitations to the components of the framework with the current state of the pandemic, starting TLPs in the community can yield positive outcomes that will be beneficial to both older adult participants and the organization in the long term.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».