Corrigendum on Data Science Approaches in Criminal Justice and Public Health Research: Lessons Learned From Opioid Projects

2021 ◽  
pp. 104398622110521
Keyword(s):  
Public Health ◽  
Criminal Justice ◽  
Health Research ◽  
Data Science ◽  
Public Health Research ◽  
Lessons Learned

Data Science Approaches in Criminal Justice and Public Health Research: Lessons Learned From Opioid Projects

2021 ◽  
pp. 104398622199985
Author(s):  
Tammy L. Anderson ◽  
Ellen A. Donnelly ◽  
Chris Delcher ◽  
Yanning Wang
Keyword(s):  
Public Health ◽  
Criminal Justice ◽  
Best Practices ◽  
Data Science ◽  
Health And Safety ◽  
Public Health Research ◽  
Lessons Learned ◽  
Future Research ◽  
Science And Policy ◽  
Public Health Agencies

The persistence of the nation’s opioid epidemic has called on criminal justice and public health agencies to collaborate more than ever. This epidemiological criminology framework highlights the surveillance of public health and safety, often using data science approaches, to inform best practices. The purpose of our article is to delineate the main benefits and challenges of adopting data science approaches for epidemiological criminology partnerships, research, and policy. We offer “lessons learned” from our opioid research in Delaware and Florida to advise future researchers, especially those working closely with policymakers and practitioners in translating science into impactful best practices. We begin with a description of our projects, pivot to the challenges we have faced in contributing to science and policy, and close with recommendations for future research, public advocacy, and practice.

scholarly journals Avatar Web-Based Self-Report Survey System Technology for Public Health Research: Technical Outcome Results and Lessons Learned

2016 ◽  
Vol 8 (2) ◽  
Author(s):  
Craig Savel ◽  
Stan Mierzwa ◽  
Pamina M Gorbach ◽  
Samir Souidi ◽  
Michelle Lally ◽  
...  
Keyword(s):  
Public Health ◽  
Health Research ◽  
The United States ◽  
Public Health Research ◽  
Lessons Learned ◽  
Self Report ◽  
Web Based ◽  
Survey System ◽  
Report Data ◽  
Self Report Data

This paper reports on a specific Web-based self-report data collection system that was developed for a public health research study in the United States. Our focus is on technical outcome results and lessons learned that may be useful to other projects requiring such a solution. The system was accessible from any device that had a browser that can support HTML5. Report findings include: which hardware devices, Web browsers, and operating systems were used, the rate of survey completion, and key considerations for employing Web-based surveys in a clinical trial setting. 

scholarly journals The Emergence and Future of Public Health Data Science

2021 ◽  
Vol 42 ◽  
Author(s):  
Jeff Goldsmith ◽  
Yifei Sun ◽  
Linda P. Fried ◽  
Jeannette Wing ◽  
Gary W. Miller ◽  
...  
Keyword(s):  
Public Health ◽  
Health Research ◽  
Data Science ◽  
Public Health Research ◽  
Health Data ◽  
Science Methods ◽  
Critical Component ◽  
Public Health Perspective ◽  
Public Health Data ◽  
Term Data

Data science is a newly‐formed and, as yet, loosely‐defined discipline that has nonetheless emerged as a critical component of successful scientific research. We seek to provide an understanding of the term “data science,” particularly as it relates to public health; to identify ways that data science methods can strengthen public health research; to propose ways to strengthen education for public health data science; and to discuss issues in data science that may benefit from a public health perspective.

scholarly journals Utilizing asynchronous email interviews for health research: overview of benefits and drawbacks

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Michelle Amri ◽  
Christina Angelakis ◽  
Dilani Logan
Keyword(s):  
Public Health ◽  
Data Collection ◽  
Data Quality ◽  
Health Research ◽  
Geographic Location ◽  
Public Health Research ◽  
Data Accuracy ◽  
Global Public Health ◽  
Snowball Sampling ◽  
Face To Face

Abstract Objective Through collating observations from various studies and complementing these findings with one author’s study, a detailed overview of the benefits and drawbacks of asynchronous email interviewing is provided. Through this overview, it is evident there is great potential for asynchronous email interviews in the broad field of health, particularly for studies drawing on expertise from participants in academia or professional settings, those across varied geographical settings (i.e. potential for global public health research), and/or in circumstances when face-to-face interactions are not possible (e.g. COVID-19). Results Benefits of asynchronous email interviewing and additional considerations for researchers are discussed around: (i) access transcending geographic location and during restricted face-to-face communications; (ii) feasibility and cost; (iii) sampling and inclusion of diverse participants; (iv) facilitating snowball sampling and increased transparency; (v) data collection with working professionals; (vi) anonymity; (vii) verification of participants; (viii) data quality and enhanced data accuracy; and (ix) overcoming language barriers. Similarly, potential drawbacks of asynchronous email interviews are also discussed with suggested remedies, which centre around: (i) time; (ii) participant verification and confidentiality; (iii) technology and sampling concerns; (iv) data quality and availability; and (v) need for enhanced clarity and precision.

scholarly journals Reporting the methods used in public health research and practice

2017 ◽  
Vol 1 ◽  
pp. 89-89 ◽  
Author(s):  
Donna F. Stroup ◽  
C. Kay Smith ◽  
Benedict I. Truman
Keyword(s):  
Public Health ◽  
Health Research ◽  
Public Health Research ◽  
Research And Practice
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