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Measuring the complex path to a prescription opioid use disorder

Science Highlight

December 04, 2019

Crowd of pedestrians walking up stairs.Image courtesy of pixabay.com/B_Me

Prescription opioid use disorder (POUD) remains a national crisis, yet only a small percentage of people seek treatment and there are no well-established prevention interventions. Scientists funded by NIDA wanted to learn if an accepted model of the causes of depression would be useful for predicting the development of POUD. The model, which has been adapted for other addictive disorders, suggests that there is no single cause of a mental health disorder, that these disorders are influenced by ongoing psychological development (and do not happen all of a sudden), and that risk factors experienced earlier in life can increase the probability of developing other risk factors that will lead to the disorder.

Prior research has identified several personal characteristics that increase the probability that someone will develop POUD, including a family history of substance use disorders (SUD), antisocial behavior, and other psychiatric disorders. The researchers conducting this study hypothesized that an accurate model to predict POUD would consider how these personal characteristics interact with and are intensified by a patient’s life experiences.

To better understand the complex path that leads to a POUD, data were drawn from profiles of people who participated in the National Epidemiologic Survey on Alcohol and Related Conditions-III (2012–2013). The model examined if factors present earlier in life, such as childhood sexual abuse, increased the probability of developing other characteristics, such as psychiatric conditions, that contribute to the development of POUDs. Following the model on depression, these life experiences were grouped into the following four developmental tiers: childhood/early adolescence, late adolescence, adulthood, past year.

Using statistical models that group data into clusters to assess their influence—hierarchical logistic regression models—scientists examined the independent contribution of each potential risk factor. Separate models were built to predict past year misuse of prescription opioids, and the risk of actually developing opioid use disorder.

The probability of misusing prescription opioids in the past year was increased by history of trauma, social deviance, use of drugs other than opioids in adulthood, and by past-year pain, alcohol use disorder, tobacco use disorder, panic disorder, social anxiety disorder, post-traumatic stress disorder, and number of stressful events.

Scientists concluded that the depressive model provides a useful foundation for predicting the causes of POUD, which could lead to the development of targeted approaches to prevention and treatment.

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