Use of Digital Health Technologies for Dementia Care: Bibliometric Analysis and Report
Notice bibliographique
Résumé
BACKGROUND: Dementia is a syndrome that compromises neurocognitive functions of the individual and that is affecting 55 million individuals globally, as well as global health care systems, national economic systems, and family members. OBJECTIVE: This study aimed to determine the status quo of scientific production on use of digital health technologies (DHTs) to support (older) people living with dementia, their families, and care partners. In addition, our study aimed to map the current landscape of global research initiatives on DHTs on the prevention, diagnosis, treatment, and support of people living with dementia and their caregivers. METHODS: A bibliometric analysis was performed as part of a systematic review protocol using MEDLINE, Embase, Scopus, Epistemonikos, the Cochrane Database of Systematic Reviews, and Google Scholar for systematic and scoping reviews on DHTs and dementia up to February 21, 2024. Search terms included various forms of dementia and DHTs. Two independent reviewers conducted a 2-stage screening process with disagreements resolved by a third reviewer. Eligible reviews were then subjected to a bibliometric analysis using VOSviewer to evaluate document types, authorship, countries, institutions, journal sources, references, and keywords, creating social network maps to visualize emergent research trends. RESULTS: A total of 704 records met the inclusion criteria for bibliometric analysis. Most reviews were systematic, with a substantial number covering mobile health, telehealth, and computer-based cognitive interventions. Bibliometric analysis revealed that the Journal of Medical Internet Research had the highest number of reviews and citations. Researchers from 66 countries contributed, with the United Kingdom and the United States as the most prolific. Overall, the number of publications covering the intersection of DHTs and dementia has increased steadily over time. However, the diversity of reviews conducted on a single topic has resulted in duplicated scientific efforts. Our assessment of contributions from countries, institutions, and key stakeholders reveals significant trends and knowledge gaps, particularly highlighting the dominance of high-income countries in this research domain. Furthermore, our findings emphasize the critical importance of interdisciplinary, collaborative teams and offer clear directions for future research, especially in underrepresented regions. CONCLUSIONS: Our study shows a steady increase in dementia- and DHT-related publications, particularly in areas such as mobile health, virtual reality, artificial intelligence, and sensor-based technologies interventions. This increase underscores the importance of systematic approaches and interdisciplinary collaborations, while identifying knowledge gaps, especially in lower-income regions. It is crucial that researchers worldwide adhere to evidence-based medicine principles to avoid duplication of efforts. This analysis offers a valuable foundation for policy makers and academics, emphasizing the need for an international collaborative task force to address knowledge gaps and advance dementia care globally. TRIAL REGISTRATION: PROSPERO CRD42024511241; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=511241.
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 | 0,070 | 0,300 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,010 | 0,010 |
| Bibliométrie | 0,296 | 0,329 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,009 | 0,006 |
| Science ouverte | 0,002 | 0,008 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 ».