Scientific Publication Patterns of Systematic Reviews on Psychosocial Interventions Improving Well-being: Bibliometric Analysis
Notice bibliographique
Résumé
BACKGROUND: Despite numerous empirical studies and systematic reviews conducted on the effectiveness of interventions improving psychological well-being, there is no holistic overview of published systematic reviews in this field. OBJECTIVE: This bibliometric study explored the scientific patterns of the effectiveness of different psychosocial interventions improving well-being among various categories of individuals with mental and physical diseases, to synthesize well-being intervention studies, and to suggest gaps and further studies in this emerging field. METHODS: The bibliometric analysis included identifying the most productive authors, institutions, and countries; most explored fields and subjects of study; most active journals and publishers; and performing citation analysis and analyzing publication trends between 2014 and 2022. We focused on data retrieved from known databases, and the study was conducted with a proven bibliometric approach. RESULTS: In total, 156 studies were found concerning the research domains and retrieved using LENS software from high-ranking databases (Crossref, Microsoft Academic, PubMed, and Core). These papers were written in English by 100 authors from 24 countries, among which, the leading country was the United Kingdom. Descriptive characteristics of the publications involved an increased number of publications in 2017 (n=35) and 2019 (n=34) and a decreased number in 2021 (n=4). The top 2 leading authors by citation score are James Thomas (3 papers and 260 citations) and Chris Dickens (3 papers and 182 citations). However, the most cited study had 592 citations. BMJ Open (n=6 articles) is the leading journal in the field of medicine; Clinical Psychology Review (n=5), in psychology; and Frontiers in Psychology, in psychological intervention (n=5) and psychology (n=5). The top 2 publishers were Wiley (n=28) and Elsevier (n=25). CONCLUSIONS: This study indicates an overall interest in the declared domains within the last decade. Our findings primarily indicate that psychosocial interventions (PIs) were evaluated as being effective in managing mental and physical problems and enhancing well-being. Cognitive behavioral therapy was assessed as being effective in treating anxiety, psychoeducation in relapse prevention, and gratitude interventions in improving overall health, and the mindfulness approach had a positive impact on decreasing distress and depression. Moreover, all these intervention types resulted in an overall increase in an individuals' well-being and resilience. Integrating social and cultural factors while considering individual differences increases the efficiency of PIs. Furthermore, PIs were evaluated as being effective in managing symptoms of eating disorders, dementia, and cancer. Our findings could help provide researchers an overview of the publication trends on research domains of focus for further studies, since it shows current findings and potential research needs in these fields, and would also benefit practitioners working on increasing their own and their patients' well-being.
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 | 0,097 | 0,417 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,008 | 0,009 |
| Bibliométrie | 0,245 | 0,307 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,009 | 0,006 |
| Science ouverte | 0,002 | 0,006 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».