Prescription Opioid Medication Survey: A Tool to Collect Deep Phenotypic Data on the Multifactorial Pathways to Opioid Use Disorder in Clinical and Population-Based Cohorts

处方阿片类药物调查:一种用于收集临床和人群队列中阿片类药物使用障碍多因素途径的深度表型数据的工具

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Abstract

INTRODUCTION: We are in the midst of an opioid epidemic. In the USA, more than a third of the country knows someone who has died from an opioid overdose. Prescription opioids (e.g., oxycodone, hydrocodone, and fentanyl) are commonly used and misused, and it has been estimated that approximately 8-12% of individuals who misuse opioids will subsequently develop an opioid use disorder (OUD). While emphasis has been placed on understanding OUD and the associated adverse effects, there remains a critical gap in systematically characterizing the multifactorial pathways (e.g., behavioral, clinical, genetic, and socio-demographic characteristics) that contribute to the transition from initial use to misuse to OUD. METHODS: To address this gap, we introduce the Prescription Opioid Medication Survey (POMS), an online 120-item assessment that compiles multiple validated and standardized instruments. POMS is intended for individuals with any lifetime prescription opioid use. POMS captures various aspects of prescription opioid use including data on opioid use patterns, subjective effects (e.g., euphoria, nausea), problematic use, withdrawal, OUD, overdose, treatment history, and remission. It also addresses comorbid risk factors such as surgical history, chronic pain, other substance use disorders (SUD; e.g., nicotine, alcohol, cannabis, stimulants), other addictive behaviors (i.e., gambling, sexual behaviors, and gaming), and family history of SUD and other addictive behaviors. Mental health assessments, including screening for depression and anxiety, self-reports of eight psychiatric disorders (anxiety, depression, bipolar, schizophrenia, attention-deficit/hyperactivity disorder, post-traumatic stress disorder, obsessive-compulsive disorder, eating disorders), and related mental health conditions (e.g., loneliness, suicide, trauma) are included, along with data on personality traits (e.g., risk-taking, delay discounting, wisdom) and socio-demographic factors. POMS is intended to be administered in clinical settings and large population-based cohorts, facilitating data collection that can enable discoveries to inform better prevention and intervention strategies for OUD. CONCLUSION: POMS offers a comprehensive tool for systematically capturing the multifactorial risk factors associated with opioid misuse and OUD, providing insights that can inform prevention and intervention strategies.

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