An Online Survey for Pharmacoepidemiological Investigation (Survey of Non-Medical Use of Prescription Drugs Program): Validation Study

Autor: Nabarun Dasgupta, Colleen M. Haynes, Karilynn Rockhill, Elise Amioka, Richard C. Dart, K Patrick May, Alyssa Forber, Joshua C. Black
Rok vydání: 2019
Předmět:
Male
Prescription Drugs
020205 medical informatics
Computer science
Best practice
Concurrent validity
Psychological intervention
Health Informatics
Sample (statistics)
02 engineering and technology
nonprobability methods
lcsh:Computer applications to medicine. Medical informatics
03 medical and health sciences
0302 clinical medicine
0202 electrical engineering
electronic engineering
information engineering
medicine
Prevalence
Humans
030212 general & internal medicine
Medical prescription
drug abuse
Internet
Original Paper
Actuarial science
calibration weights
Clinical study design
lcsh:Public aspects of medicine
Pharmacoepidemiology
general population survey
Reproducibility of Results
lcsh:RA1-1270
medicine.disease
Health Surveys
Weighting
Substance abuse
Cross-Sectional Studies
lcsh:R858-859.7
Female
Zdroj: Journal of Medical Internet Research
Journal of Medical Internet Research, Vol 21, Iss 10, p e15830 (2019)
ISSN: 1438-8871
Popis: Background In rapidly changing fields such as the study of drug use, the need for accurate and timely data is paramount to properly inform policy and intervention decisions. Trends in drug use can change rapidly by month, and using study designs with flexible modules could present advantages. Timely data from online panels can inform proactive interventions against emerging trends, leading to a faster public response. However, threats to validity from using online panels must be addressed to create accurate estimates. Objective The objective of this study was to demonstrate a comprehensive methodological approach that optimizes a nonprobability, online opt-in sample to provide timely, accurate national estimates on prevalence of drug use. Methods The Survey of Non-Medical Use of Prescription Drugs Program from the Researched Abuse, Diversion and Addiction Related Surveillance (RADARS) System is an online, cross-sectional survey on drug use in the United States, and several best practices were implemented. To optimize final estimates, two best practices were investigated in detail: exclusion of respondents showing careless or improbable responding patterns and calibration of weights. The approach in this work was to cumulatively implement each method, which improved key estimates during the third quarter 2018 survey launch. Cutoffs for five exclusion criteria were tested. Using a series of benchmarks, average relative bias and changes in bias were calculated for 33 different weighting variable combinations. Results There were 148,274 invitations sent to panelists, with 40,021 who initiated the survey (26.99%). After eligibility assessment, 20.23% (29,998/148,274) of the completed questionnaires were available for analysis. A total of 0.52% (157/29,998) of respondents were excluded based on careless or improbable responses; however, these exclusions had larger impacts on lower volume drugs. Number of exclusions applied were negatively correlated to total dispensing volume by drug (Spearman ρ=–.88, P Conclusions Our study illustrates a new approach to using nonprobability online panels to achieve national prevalence estimates for drug abuse. We were able to overcome challenges with using nonprobability internet samples, including misclassification due to improbable responses. Final drug use and health estimates demonstrated concurrent validity to national probability-based drug use and health surveys. Inclusion of multiple best practices cumulatively improved the estimates generated. This method can bridge the information gap when there is a need for prompt, accurate national data.
Databáze: OpenAIRE
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