Summary
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
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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| Web resources: | https://cordis.europa.eu/project/id/101020767 |
| Start date: | 01-11-2021 |
| End date: | 31-10-2026 |
| Total budget - Public funding: | 2 499 198,00 Euro - 2 499 198,00 Euro |
Cordis data
Original description
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
Status
SIGNEDCall topic
ERC-2020-ADGUpdate Date
27-04-2024
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