Tech-social synergy: nurturing community well-being
Notice bibliographique
Résumé
Dear editors, Strup et al., in a recent article, found that the pandemic has raised awareness of the importance and potential benefits of community-based networks for public health. Community social capital in promoting engagement, resilience and well-being is crucial.1 We complement these findings, that in the pursuit of community well-being, concocting the integration of social capital and technology is a harmonious formula. In a modern era characterized by technological transformation and increasingly complex social dynamics, the combination of technology and social capital is essential in shaping community welfare. Physically and mentally well communities are formed through a combination of factors, such as an effective health system, strong social support and public awareness of the importance of well-being.2 Easy access to physical and mental health services is a key feature.3 These communities are able to create a balance between the demands of work and personal life while providing individuals with support and empowerment. To achieve this, technology integration strategies and social capital that support effectiveness and accessibility are required. Technology and social capital play a central role in optimizing people's physical health. Technology, bringing solutions such as telemedicine4 and wearable devices, facilitates wider access to health services, monitoring of physical conditions and dissemination of health information.5 On the other hand, social capital, such as social support and community engagement, forms the basis for the promotion of healthy lifestyles,6 collaboration in physical activities and acceptance of positive health-related norms. The synergy between technology and social capital creates a favourable environment for concerted efforts to holistically improve people's physical health. The role of technology and social capital in optimizing people's mental health is significant. Technology, through mental health apps such as the use of the metaverse,7 online counselling platforms8 and other digital resources, provides easy9 and anonymous access to psychological support to even the elderly.10 Meanwhile, social capital, such as social support from family and friends, and participation in community activities play a key role in reducing stigma, raising awareness and creating a supportive environment for mental health.11 The synergy between technology and social capital creates an effective channel to support people's mental health in a holistic and inclusive way. The implementation of community welfare through the synergy of technology and social capital requires training and education of communities in technology skills and social capital enhancement. It is necessary to provide an equitable access to technology and build local digital platforms, including digital infrastructure in less developed areas. Online health and education services are also introduced to improve the accessibility. Local governments need to develop policies that support technological development and social capital strengthening. Health and education institutions are responsible for providing accessible services and education through technology. Technology developers play a role in developing and implementing appropriate technological solutions. Local communities are expected to actively participate, identify needs and build social capital. Non-governmental organizations, businesses, universities, media and local civic institutions also have a responsibility to support, disseminate information and ensure the sustainability of community welfare programmes. The involvement of all these stakeholders is key to creating holistic and sustainable solutions. We have no conflicts of interest to disclose. The authors declared that no funding was received for this paper. The authors stated that there is no conflict of interest regarding the subject matter or material discussed and confirmed the data available in this manuscript's article.
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 | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,006 |
| Communication savante | 0,008 | 0,005 |
| Science ouverte | 0,001 | 0,011 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,020 | 0,003 |
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 ».