Funding: NIAAA R44AA027981
ARG Lead: Thomas K. Greenfield; Principal Investigator: Niina Haas, Bright Outcome
The National Institute of Mental Health (NIMH) Data Archive (NDA) collects and shares de-identified human subjects data from hundreds of NIH-funded research projects across many mental health-related scientific domains with qualified researchers. A new NDA repository is created for the National Institute on Alcohol Abuse and Alcoholism Data Archive (NIAAADA) and will serve as the portal for NIAAA-related data submissions and access.
The NIAAA data-sharing policy (NOT-AA-19-020) released in July of 2019, requires that— beginning in 2019—all NIAAA grant applications involving human subjects must include plans for the submission of study data to NIAAADA.
The first wave of submission to NIAAADA is expected in January of 2021. Many obstacles exist for alcohol researchers to comply with this policy, especially for those with limited budget and information technology support. To submit the study data, researchers have to comb through large and complex NDA data definition files, often filled with inconsistencies and inaccuracies, to find the measure items that they need, and then map their data to the right fields in the right format in a given data template. This process often requires researchers to manipulate their data by-hand or with complicated scripts, and is error prone, time-consuming, and requires certain technical skills. Our ultimate goal is to provide a nearly-automated process for the submission of alcohol research data into the NIAAADA so that the data submission can be performed accurately and efficiently by alcohol researchers with minimum IT knowledge and resources.
The project will develop and validate the Share HumAn REsearch (SHARE) platform to address the unmet need for assisting alcohol researchers with the submission of study data to NIAAADA. SHARE does so by offering the SHARE Measure Library of pre-defined standard measures that are already mapped to NDA data dictionaries. Alcohol researchers need to only select the measures that they want to use for their studies and let SHARE do the rest for data submission to NIAAADA.
- Platform and measure development. In Phase II we will continue using a user-centric design process and the latest e-technologies to develop SHARE, and we will extend to 200 measures in both English and Spanish (when available).
- Pilot evaluation. There will be 4 NIAAADA submission waves during the two-year Phase II period. We plan to align both Aim 1 and Aim 2 activities to these 4 submission waves and recruit five projects in each wave to compare the performance of SHARE vs. NDA. A total of 20 pilot projects will be recruited and randomized to use either SHARE or NDA for NIAAADA submission. The time and cost for data preparation and submission will be tracked, and the accuracy of submitted data assessed. We hypothesize that compared to NDA, SHARE will perform significantly better in terms of reduced time and cost improved data accuracy.
