Summary:

Fetal alcohol spetrum disorder (FASD) describes a group of conditions that are caused by the consumption of alcohol during pregnancy. Prevalence estimates suggest a high occurence in the population, but the overall distribution and prevalance is still an open research question.

The aim of this project in collaboration with the Clinic for Psychiatry, Psychosomatic Medicine, and Psychotherapy at Charité Berlin are:

• Evaluate an expert-based prediction algorithm of FASD,
• develop machine-learning-based algorithms,
• and implement both into a screening app that will be deployed in clinical practice

Team:

• Stefan Konigorski
• Lukas Ehrig

Collaboration partner:

Olga Geisel (Klinik für Psychiatrie, Psychosomatik und Psychotherapie, Charité University Medicine Berlin)

References:

• Ehrig L^#, Wagner A^#, Wolter H, Correll CU, Geisel O*, Konigorski S* (2023). FASDetect as a machine learning-based screening app for FASD in youth with ADHD. npj Digital Medicine6:130. https://doi.org/10.1038/s41746-023-00864-1

Summary:

Alcohol consumption is associated with multiple health risks for the concerned individual and causes immense economic costs worldwide. In order to implement adequate alcohol policies on the population level and provide individuals with targeted counselling or treatment as early as possible, it is essential to monitor consumption patterns and identify persons at risk. However, current assessment tools used for scientific and public health purposes have been shown to vastly underestimate the ‘true’ level of alcohol consumption, both on individual levels as well as in the population.

In a pan-European collaboration project with the Heidelberg Institute of Global Health at Heidelberg University and the Alcohol and Illicit Drugs Programme in the WHO European Office for Prevention and Control of Noncommunicable Diseases, led by Heidelberg University, we are currently developing the Animated Alcohol Assessment tool to be used as a mobile app to access drinking behaviors in individual screening tests and population-level studies. With this new assessment tool, we are hoping to improve the assessment options available.

References:

• Wiemker V, Bunova A, Rastogi A, Neufeld M, Ferreira-Borges C, Konigorski S, Probst C (2022). Digital assessment tools using animation features to quantify alcohol consumption: a systematic review. To appear in JMIR.
• Wiemker V, Bunova A, Neufeld M, Gornyi B, Yurasova E, Konigorski S, Kalinina A, Kontsevaya A, Ferreira-Borges C, Probst C (2022). Pilot study to evaluate usability and acceptability of the ‘Animated Alcohol Assessment Tool’ (AAA-Tool) in Russian primary healthcare. To appear in Digital Health. DOI: 10.1177/20552076221074491

Team:

• Stefan Konigorski
• Tobias Fiedler
• Nico Scordialo

Collaboration partners:

• Charlotte Probst (PI), Veronika Wiemker (Heidelberg Institute of Global Health, Heidelberg University)
• WHO European Office for Prevention and Control of Noncommunicable Diseases (Moscow, Russian Federation)