dc.contributor.author
Löchner, Johanna
dc.contributor.author
Bolivar, Mariana
dc.contributor.author
Booth, Lesley
dc.contributor.author
Canella, Sara
dc.contributor.author
Calobro, Michele
dc.contributor.author
Firth, Joseph
dc.contributor.author
Garcia-Palacios, Azucena
dc.contributor.author
Kyritsaka, Aleksandra
dc.contributor.author
Sander, Lasse B.
dc.contributor.author
Seiferth, Caroline
dc.contributor.author
Seizer, Lennart
dc.contributor.author
Teesson, Maree
dc.contributor.author
Tyrowicz, Joanna
dc.contributor.author
Vogel, Lea
dc.contributor.author
Wheeler, Emily
dc.contributor.author
Wolstein, Jörg
dc.contributor.author
Schuller, Björn W.
dc.date.accessioned
2025-10-30T06:26:05Z
dc.date.available
2025-10-30T06:26:05Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/50074
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-49799
dc.description.abstract
The pervasive impact of mental illnesses extends beyond individual suffering, affecting families, communities, and societies at large. Prevention efforts are imperative to mitigate this burden, promoting well-being and resilience across diverse populations. A particularly vulnerable period is adolescence, which is associated with numerous mental health issues that are exacerbated by declining healthy behaviours as well as socioeconomic inequalities. But adolescence also presents an opportune moment for early intervention. However, recognising warning signs and providing timely support involves considerable hurdles, so innovative prevention measures are needed. Advancements in AI, particularly in emotion recognition, offer promise for early mental health intervention. Yet, current AI achievements fall short in addressing the mental healthcare gap. This vision paper seeks to outline future directions and recommendations for effective preventive approaches by integrating experts of the necessary multidisciplinary field to develop, evaluate and implement novel and promising prevention approaches. Therefore, representatives based in Europe from diverse fields such as clinical psychology, computer science, physical activity, nutrition, economics, entrepreneurship, politics, and digital innovation propose potential avenues to integrate efficient treatment, AI methodology, and comprehensive implementation strategies that align with user needs. Based on a literature review and expert consensus, key ingredients suggested for effective preventive measures for mental health include holistic, individualised, AI-based mHealth interventions, leveraging smart and passive data from digital biomarkers for monitoring and feedback, evaluating cost-effectiveness, conducting participatory research to ensure user acceptance, and identifying barriers and facilitators for integration into regular healthcare systems. By utilising AI-driven interventions for adolescents, we can address the urgent need for preventive mental healthcare, ultimately enhancing the well-being of future generations.
en
dc.format.extent
14 Seiten
dc.rights
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
dc.subject
mental health
en
dc.subject
artificial intelligence
en
dc.subject
implementation
en
dc.subject.ddc
100 Philosophie und Psychologie::150 Psychologie::150 Psychologie
dc.title
Multidisciplinary perspectives on personalised prevention in youth mental health
dc.type
Wissenschaftlicher Artikel
dc.date.updated
2025-10-29T22:59:44Z
dcterms.bibliographicCitation.articlenumber
1568472
dcterms.bibliographicCitation.doi
10.3389/fdgth.2025.1568472
dcterms.bibliographicCitation.journaltitle
Frontiers in Digital Health
dcterms.bibliographicCitation.volume
7
dcterms.bibliographicCitation.url
https://doi.org/10.3389/fdgth.2025.1568472
refubium.affiliation
Erziehungswissenschaft und Psychologie
refubium.affiliation.other
Arbeitsbereich Klinische Psychologie und Psychotherapie

refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.isPartOf.eissn
2673-253X
refubium.resourceType.provider
DeepGreen