Fast Screening of Firearm Discharge Residues by Laser-based Spectrochemical Methods, Electrochemical Sensors, and Chemometrics, West Virginia, 2019-2021 (ICPSR 38296)
The detection of gunshot residue (GSR) provides valuable information in violent crimes, accidental shootings, and terrorism. Despite the scientific validity of this discipline, there are persistent challenges regarding the speed of analysis, preservation of the evidence, and interpretation of results. Consequently, there is a critical need to improve the discipline's turnaround times and reliability. This study's overall purpose was to develop a comprehensive approach to overcome these significant concerns and enhance the criminal justice system capabilities. This project developed and validated fast and reliable tests, using laser-induced breakdown spectroscopy (LIBS) and electrochemical (EC) sensors for GSR detection. Also, statistical models were applied for the quantitative interpretation of the evidence. The combination of LIBS and EC data permitted the accurate identification of organic and inorganic residues (OGSR and IGSR, accuracy ranging from 92-99% depending on the subpopulation and classification models). This research focused on developing SMARTER (Simpler, Modern, Affordable, Rapid, Transformative, Effective, and Reliable) solutions for GSR examinations.
The main objectives were:
- Application of universal and expanded collection methods
- Development of novel, ultrafast methods for dual detection of IGSR and OGSR
- Development of modern 3D chemical imaging for crime scene reconstruction
- Development of novel micro-particle GSR standards
- Creation of a large population study and probabilistic interpretation framework
Improving Methods for Linking Secondary Data Sources for Comparative Effectiveness Research (CER)/Patient-Centered Outcomes Research (PCOR) [Methods Study], United States, 2008-2019 (ICPSR 39614)
Researchers often combine patient health data from different sources, such as claims and health records. These data contain personal information, such as names and social security numbers.
In this study, the research team wanted to learn patients' views on sharing and combining health data for research. The team surveyed patients about their views on
- Sharing health and personal data, such as social security numbers
- Benefits and risks of data sharing
- Ways to help patients feel comfortable sharing health data