A team of researchers has developed a new framework that they believe will help identify people previously overlooked for alcohol use disorder (AUD).
The study has been published in the 'Psychological Bulletin Journal'.
This framework focuses on 13 risk factors, such as impulsive behaviour, reward sensitivity, and punishment sensitivity that could lead to someone developing an AUD.
"We know from decades of research that there are a lot of different pathways to alcohol use disorder," said Cassie Boness, a former graduate student at MU in the Department of Psychological Sciences.
"So, we want to make sure that we are targeting people's specific pathways as accurately as possible in order to be most effective in identifying and treating AUD," she added.
Throughout her career, Boness has been interested in the causes, diagnosis and assessment of substance use disorders, including AUD, a chronic medical condition characterized by ongoing alcohol use despite adverse consequences.
For Boness, it's personal -- after seeing her loved ones stigmatized for their addiction to alcohol, and then watching them struggle to get connected with treatment, she wanted to help reduce the amount of suffering people may experience with AUD.
While today's assessment tools, such as the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) can help health care professionals diagnose someone with AUD, Boness believes the current methods are too narrowly focused on the consequences of someone's actions, rather than incorporating a broad list of potential risk factors that may lead to an AUD diagnosis.
Boness, who is now a research assistant professor at the University of New Mexico, hopes their framework can be a step forward toward a comprehensive diagnosis of AUD throughout the health care community. However, she stressed that this tool is not meant to be the only solution, but rather a way for other researchers like her to build upon and enhance the existing research on the subject.
"Eventually, we'd like to see assessment tools that more comprehensively capture the factors articulated in our framework so that we can identify individual profiles of risk and potentially intervene during earlier stages of addiction," Boness said.
Other authors on the study included Ashley Watts, Kimberly Moeller and Ken Sher at MU. (ANI)