Community indicators for mental health in Europe: a scoping review.

community indicators mental health promotion and prevention neighborhood public mental health scoping review

Journal

Frontiers in public health
ISSN: 2296-2565
Titre abrégé: Front Public Health
Pays: Switzerland
ID NLM: 101616579

Informations de publication

Date de publication:
2023
Historique:
received: 17 03 2023
accepted: 19 06 2023
medline: 7 8 2023
pubmed: 4 8 2023
entrez: 4 8 2023
Statut: epublish

Résumé

Community indicators may predict and influence individuals` mental health, and support or impede mental health management. However, there is no consensus on which indicators should be included in predictions, prognostic algorithms, or management strategies for community-based mental health promotion and prevention approaches. Therefore, this scoping review provides an overview of relevant community-level indicators for mental health in the general as well as risk populations in a European context. We conducted a scoping review in the following electronic databases: PubMed, Embase, and PsycInfo. Eligible studies focused on context factors such as either the physical or social environment, reporting at least one mental health outcome and referring to a European population. Publications between 2012 and March 8, 2022 are considered. In total, the search yielded 12,200 identified records. After the removal of duplicates, 10,059 records were screened against the eligibility criteria. In total, 169 studies were included in the final analysis. Out of these included studies, 6% focused on pan-European datasets and 94% on a specific European country. Populations were either general or high-risk populations (56 vs. 44%, respectively) with depressive disorder as the main reported outcome (49%), followed by general mental health (33%) and anxiety (23%). Study designs were cross-sectional studies (59%), longitudinal (27%), and others (14%). The final set of indicators consisted of 53 indicators, which were grouped conceptually into 13 superordinate categories of community indicators. These were divided into the domains of the physical and social environment. The most commonly measured and reported categories of community indicators associated with mental health outcomes were social networks ( This review provides an evidence base of existing and novel community-level indicators that are associated with mental health. Community factors related to the physical and social environment should be routinely recorded and considered as influencing factors or potentially underestimated confounders. The relevance should be analyzed and included in clinical outcomes, data, monitoring and surveillance as they may reveal new trends and targets for public mental health interventions.

Sections du résumé

Background
Community indicators may predict and influence individuals` mental health, and support or impede mental health management. However, there is no consensus on which indicators should be included in predictions, prognostic algorithms, or management strategies for community-based mental health promotion and prevention approaches. Therefore, this scoping review provides an overview of relevant community-level indicators for mental health in the general as well as risk populations in a European context.
Methods
We conducted a scoping review in the following electronic databases: PubMed, Embase, and PsycInfo. Eligible studies focused on context factors such as either the physical or social environment, reporting at least one mental health outcome and referring to a European population. Publications between 2012 and March 8, 2022 are considered.
Results
In total, the search yielded 12,200 identified records. After the removal of duplicates, 10,059 records were screened against the eligibility criteria. In total, 169 studies were included in the final analysis. Out of these included studies, 6% focused on pan-European datasets and 94% on a specific European country. Populations were either general or high-risk populations (56 vs. 44%, respectively) with depressive disorder as the main reported outcome (49%), followed by general mental health (33%) and anxiety (23%). Study designs were cross-sectional studies (59%), longitudinal (27%), and others (14%). The final set of indicators consisted of 53 indicators, which were grouped conceptually into 13 superordinate categories of community indicators. These were divided into the domains of the physical and social environment. The most commonly measured and reported categories of community indicators associated with mental health outcomes were social networks (
Conclusion
This review provides an evidence base of existing and novel community-level indicators that are associated with mental health. Community factors related to the physical and social environment should be routinely recorded and considered as influencing factors or potentially underestimated confounders. The relevance should be analyzed and included in clinical outcomes, data, monitoring and surveillance as they may reveal new trends and targets for public mental health interventions.

Identifiants

pubmed: 37538274
doi: 10.3389/fpubh.2023.1188494
pmc: PMC10396773
doi:

Types de publication

Systematic Review Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1188494

Investigateurs

Jochen Vukas (J)
Puya Younesi (P)
Feyza Gökce (F)
Victoria von Schrottenberg (V)
Petra Schönweger (P)
Hannah Schillock (H)
Jonas Raub (J)
Philipp Reindl-Spanner (P)
Lisa Hattenkofer (L)
Lukas Kaupe (L)
Carolin Haas (C)
Julia Eder (J)
Vita Brisnik (V)
Constantin Brand (C)
Katharina Biersack (K)

Informations de copyright

Copyright © 2023 Schoenweger, Kirschneck, Biersack, Di Meo, Reindl-Spanner, Prommegger, Ditzen-Janotta, Henningsen, Krcmar, Gensichen and Jung-Sievers.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Petra Schoenweger (P)

Institute of Medical Data Processing, Biometrics and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Munich, Germany.
Pettenkofer School of Public Health, Munich, Germany.

Michaela Kirschneck (M)

Institute of Medical Data Processing, Biometrics and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Munich, Germany.
Pettenkofer School of Public Health, Munich, Germany.

Katharina Biersack (K)

Department of Psychosomatic Medicine and Psychotherapy, University Hospital, Technical University of Munich, Munich, Germany.

Anna-Francesca Di Meo (AF)

Institute of Medical Data Processing, Biometrics and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Munich, Germany.
Pettenkofer School of Public Health, Munich, Germany.

Philipp Reindl-Spanner (P)

TUM School of Computation, Information and Technology, Technical University of Munich, Munich, Germany.

Barbara Prommegger (B)

TUM School of Computation, Information and Technology, Technical University of Munich, Munich, Germany.

Claudia Ditzen-Janotta (C)

Institute of Medical Data Processing, Biometrics and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Munich, Germany.
Pettenkofer School of Public Health, Munich, Germany.

Peter Henningsen (P)

Department of Psychosomatic Medicine and Psychotherapy, University Hospital, Technical University of Munich, Munich, Germany.

Helmut Krcmar (H)

TUM School of Computation, Information and Technology, Technical University of Munich, Munich, Germany.

Jochen Gensichen (J)

Institute of General Practice and Family Medicine, University Hospital of Ludwig-Maximilians-University Munich, Munich, Germany.

Caroline Jung-Sievers (C)

Institute of Medical Data Processing, Biometrics and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Munich, Germany.
Pettenkofer School of Public Health, Munich, Germany.

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