RTI uses cookies to offer you the best experience online. By clicking “accept” on this website, you opt in and you agree to the use of cookies. If you would like to know more about how RTI uses cookies and how to manage them please view our Privacy Policy here. You can “opt out” or change your mind by visiting: http://optout.aboutads.info/. Click “accept” to agree.
Methodological strategies for prospective harmonization of studies
Application to 10 distinct outcomes studies of preventive interventions targeting opioid misuse
Ridenour, T. A., Cruden, G., Yang, Y., Bonar, E. E., Rodriguez, A., Saavedra, L. M., Hussong, A. M., Walton, M. A., Deeds, B., Ford, J. L., Knight, D. K., Haggerty, K. P., Stormshak, E., Kominsky, T. K., Ahrens, K. R., Woodward, D., Feng, X., Fiellin, L. E., Wilens, T. E., ... Fernandes, C.-S. (2023). Methodological strategies for prospective harmonization of studies: Application to 10 distinct outcomes studies of preventive interventions targeting opioid misuse. Prevention Science, 24(SUPPL 1), 16-29. https://doi.org/10.1007/s11121-022-01412-1
The Helping to End Addiction Long-Term (HEAL) Prevention Cooperative (HPC) is rapidly developing 10 distinct evidence-based interventions for implementation in a variety of settings to prevent opioid misuse and opioid use disorder. One HPC objective is to compare intervention impacts on opioid misuse initiation, escalation, severity, and disorder and identify whether any HPC interventions are more effective than others for types of individuals. It provides a rare opportunity to prospectively harmonize measures across distinct outcomes studies. This paper describes the needs, opportunities, strategies, and processes that were used to harmonize HPC data. They are illustrated with a strategy to measure opioid use that spans the spectrum of opioid use experiences (termed involvement) and is composed of common "anchor items" ranging from initiation to symptoms of opioid use disorder. The limitations and opportunities anticipated from this approach to data harmonization are reviewed. Lastly, implications for future research cooperatives and the broader HEAL data ecosystem are discussed.