  In the last decade, the United States has lost more than 500,000 people from
an overdose involving prescription and illicit opioids making it a national
public health emergency (USDHHS, 2017). Medical practitioners require robust
and timely tools that can effectively identify at-risk patients.
Community-based social media platforms such as Reddit allow self-disclosure for
users to discuss otherwise sensitive drug-related behaviors. We present a
moderate size corpus of 2500 opioid-related posts from various subreddits
labeled with six different phases of opioid use: Medical Use, Misuse,
Addiction, Recovery, Relapse, Not Using. For every post, we annotate span-level
extractive explanations and crucially study their role both in annotation
quality and model development. We evaluate several state-of-the-art models in a
supervised, few-shot, or zero-shot setting. Experimental results and error
analysis show that identifying the phases of opioid use disorder is highly
contextual and challenging. However, we find that using explanations during
modeling leads to a significant boost in classification accuracy demonstrating
their beneficial role in a high-stakes domain such as studying the opioid use
disorder continuum.
