A Review of Digital Surveillance Methods and Approaches to Combat Prescription Drug Abuse

Abstract

Purpose of Review: The use of social media to conduct digital surveillance to address different health challenges is growing. This multidisciplinary review assesses the current state of methods and applied research used to conduct digital surveillance for prescription drug abuse. Recent Findings: Fifteen studies met our inclusion criteria from the databases reviewed (PubMed, IEEE Xplore, and ACM Digital Library). The articles were characterized based on their overarching goals and aims, data collection and dataset attributes, and analysis approaches. Overall, reviewed studies grouped into two overarching categories as either being method-focused (advancing novel methodologies using social media data), applied-focused (generating new information on prescription drug abuse behavior), or having both elements. The social media platform most predominantly used was Twitter, with wide variation in sample size and duration of data collection. Several data analysis strategies were employed, including machine learning, temporal analysis, rule-based approaches, and statistical analysis. Summary: Our review indicates that the field of prescription drug abuse digital surveillance is still maturing. Though many studies captured large volumes of data, the majority did not analyze data to characterize user behavior, a critical step needed in order to better explain the underlying risk environment for prescription drug abuse. Future studies need to better translate method-based approaches into applied research, use data generated from social media platforms other than Twitter, and take advantage of emerging data analysis strategies, including deep learning and multimodal approaches.