Addressing Missing Data in Substance Use Research: A Review and Data Justice-based Approach

Area of Science:

• Public Health
• Biostatistics
• Data Science

Background:

• Missing data is a significant challenge in substance use disorder (SUD) research, impacting the reliability of study findings.
• Existing statistical tools for handling missing data are underutilized and may not cover all types of missingness.
• Missing data in SUD research disproportionately affects underserved populations, leading to incomplete narratives and potentially flawed policy decisions.

Purpose of the Study:

• To review the types of missing data encountered in SUD research.
• To highlight the underuse of existing statistical methods for managing missing data.
• To advocate for the increased development and application of statistical tools through a data justice framework.

Main Methods:

• Literature review of missing data types in SUD research.
• Analysis of the implications of missing data from a data justice perspective.
• Examination of current statistical tools and their limitations in SUD contexts.

Main Results:

• Identified various types of missing data prevalent in SUD research.
• Demonstrated how missing data can obscure critical information, particularly for vulnerable groups.
• Highlighted the gap between available statistical methods and their practical application in SUD studies.

Conclusions:

• Emphasizes that missing data in SUD research is not merely a statistical issue but a data justice concern.
• Stresses the urgent need for greater adoption and innovation in statistical methodologies to address missing data.
• Advocates for a more equitable approach to data collection and analysis in SUD research to ensure all voices and stories are represented.