Loneliness among older adults in the community during COVID-19
Notice bibliographique
Résumé
Abstract Objective Physical distancing and stay-at-home measures implemented to slow transmission of novel coronavirus disease (COVID-19) may intensify feelings of loneliness in older adults, especially those living alone. Our aim was to characterize the extent of loneliness in a sample of older adults living in the community and assess characteristics associated with loneliness. Design Online cross-sectional survey between May 6 and May 19, 2020 Setting Ontario, Canada Participants Convenience sample of the members of a national retired educators’ organization. Primary outcome measures Self-reported loneliness, including differences between women and men. Results 4879 respondents (71.0% women; 67.4% 65-79 years) reported that in the preceding week, 43.1% felt lonely at least some of the time, including 8.3% that felt lonely always or often. Women had increased odds of loneliness compared to men, whether living alone (adjusted Odds Ratio (aOR) 1.52 [95% Confidence Interval (CI) 1.13-2.04]) or with others (2.44 [95% CI 2.04-2.92]). Increasing age group decreased the odds of loneliness (aOR 0.69 [95% CI 0.59-0.81] 65-79 years and 0.50 [95% CI 0.39-0.65] 80+ years compared to <65 years). Living alone was associated with loneliness, with a greater association in men (aOR 4.26 [95% CI 3.15-5.76]) than women (aOR 2.65 [95% CI 2.26-3.11]). Other factors associated with loneliness included: fair or poor health (aOR 1.93 [95% CI 1.54-2.41]), being a caregiver (aOR 1.18 [95% CI 1.02-1.37]), receiving care (aOR 1.47 [95% CI 1.19-1.81]), high concern for the pandemic (aOR 1.55 [95% CI 1.31-1.84]), not experiencing positive effects of pandemic distancing measures (aOR 1.94 [95% CI 1.62-2.32]), and changes to daily routine (aOR 2.81 [95% CI 1.96-4.03]). Conclusions While many older adults reported feeling lonely during COVID-19, several characteristics – such as being female and living alone – increased the odds of loneliness. These characteristics may help identify priorities for targeting interventions to reduce loneliness. Strengths and limitations of this study This survey study leveraged a strong community-based partnership to obtain timely data from a large sample of older Canadians on the impacts of COVID-19. This study identified several characteristics that increased the odds of loneliness, which may help to identify priorities for targeted interventions to reduce loneliness. The data were based on a convenience sample of retired, educational staff, who are not fully representative of the Canadian population. The perspectives of vulnerable groups who may be at greater risk for loneliness (e.g. those with severe mental health illness, low income, no home internet access, etc.) are likely underrepresented in this sample.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».