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DIGIPARENT

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DIGIPARENT Implementation personalization and genetics of digitally assisted...

DIGIPARENT Implementation personalization and genetics of digitally assisted parent training intervention to improve child mental health services. Childhood disruptive behavior problems pose huge challenge to societies given the high lifetime burden and costs associated. Mounting evidence shows that parent training is the most effective psychosocial treatment for these probl... ver más

31/10/2026

UNIVERSITY OF TURK...

2M€

Presupuesto del proyecto: 2M€

Líder del proyecto

TURUN YLIOPISTO No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Ver 2 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2021-07-08

ERC-2020-ADG: ERC ADVANCED GRANT

I+D

Cerrada hace 4 años

0% 100% 100%

Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

2 Participantes

UNIVERSITY OF TURKU

2.50M€ | Lider

RIALS FABRICA ARTICULOS DE C...

281.04K€ | Participante

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Duración del proyecto: 63 meses Fecha Inicio: 2021-07-08
Fecha Fin: 2026-10-31

Líder del proyecto

TURUN YLIOPISTO No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 2M€

Descripción del proyecto Childhood disruptive behavior problems pose huge challenge to societies given the high lifetime burden and costs associated. Mounting evidence shows that parent training is the most effective psychosocial treatment for these problems. However, most parents in need of such training do not receive it. DIGIPARENT shift the research focus from specialized care face-to-face parent training to study digitally assisted parent training interventions when implemented in primary health. The proposal is divided into four Work Packages (WP): WP1 is the first population based study about the long-term outcomes and modifiers of digitally assisted parent training. It addresses what works and how it works in real-world practice. WP2 will yield novel knowledge on the genetic and epigenetic variants associated with childhood disruptive behavior and the epigenetic response to childhood psychosocial interventions. WP 3 shifts the research focus from a manualized one-size-fits-all parent training intervention approaches to one that is personalized for families by artificial intelligence and machine learning algorithms. WP 4 adopts a novel approach by comparing community level, well-being indicators when different combinations of digital and face-to-face parent training strategies are implemented in real world. DIGIPARENT combines an evidence-based approach to child mental health with the latest technology and offers the potential for scientific breakthroughs, including the use of artificial technology to produce digital content tailored to the needs of individual families. Detection of genetic factors related to treatment response and possible epigenetic outcomes of treatments opens avenues for new scientific questions on how treatments can affect human biology. DIGIPARENT responds to the urgent need to study digital and remote interventions as child mental health services struggle with the considerable increase in demand for services due to the COVID-19 pandemic

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