Associations Between Social Media Use and Anxiety and Depression Among Older Adults : Cross-Sectional Study
Notice bibliographique
Résumé
Background: Social media engagement among older adults has surged worldwide, with China's older users exceeding 120 million in 2023. However, research remains disproportionately focused on youth. Critically, the dose-response relationship between use intensity and mental health in this population is poorly quantified, especially in rapidly aging societies such as China, where 23% of the population will be aged ≥65 years by 2035. Objective: This study aimed to outline the social media use status among retired older adults and explore the association between social media use, including time spent on social media and social media addiction, and mental health status. Methods: A cross-sectional survey was conducted in Shanghai, China, in 2024. A total of 15,986 retired participants were recruited via universities for older adults and primary health care institutions. Short versions of anxiety (the 2-item Generalized Anxiety Disorder scale) and depression (the 2-item Patient Health Questionnaire) scales were used to minimize the required time to complete the questionnaires for older adults. Logistic regressions were used to examine the associations between social media use and mental health after controlling for covariates. Subgroup analysis was conducted considering sex, age, marital status, urbanicity, and socioeconomic status. Results: The participants had an average age of 68.49 (SD 7.6) years, with most (13,854/15,986, 86.7%) being married and living with their spouse and approximately half (8155/15,986, 51.0%) being male. Our research indicated that over 98% of retired older individuals (15,807/15,986, 98.88%) had used social media, with WeChat, Douyin, and Kuaishou being the most common platforms. Among them, 52.3% (8361/15,986) spent 2 to 3 hours a day on social media, 32.29% (5162/15,986) spent >4 hours a day, and 20.34% (3253/15,986) were addicted to social media. Older adults with ≥6 hours of daily social media use time exhibited higher rates of anxiety (odds ratio [OR] 1.44, 95% CI 1.20-1.72; P<.001) and depression (OR 1.50, 95% CI 1.25-1.79; P<.001) compared with those who used social media for ≤1 hour per day. Older adults addicted to social media had higher odds of anxiety (OR 2.81, 95% CI 2.57-3.08; P<.001) and depression (OR 2.51, 95% CI 2.30-2.75; P<.001). Subgroup analyses revealed stronger associations for women, people aged 49-75 years, those with a lower educational level and income, urban residents, and non-solo dwellers. Conclusions: Retired older adults in Shanghai are an active group of social media users. Using social media for over 6 hours a day and social media addiction were significantly associated with anxiety and depression. Future social media research should pay more attention to older adults and explore these longitudinal relationships.
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 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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».