SBIR-STTR Award

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-18-010) released in June of 2018, 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 data submission to NIAAADA is expected in 2020. Many obstacles exist for alcohol researchers to comply with this policy, especially for those with limited budget and information technology and data management support. To submit the study data, researchers have to map their data to the right fields in the right format in a given data template, which often requires researchers to manipulate their data by-hand or with complicated scripts, or request a new data structure from NDA, which compromises the goal of data sharing. These data submission processes are error prone, time-consuming, and require 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. We propose to 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 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. Phase I aims include: 1) Collect stakeholder feedback from ten alcohol researchers via focus groups and interviews to understand how they currently collect and manage their human subject questionnaire data and explore how they would submit the data to the NIAAADA with an “ideal” tool; 2) Develop the prototype using a user-centric design process and the latest e-technologies. Also code ten common alcohol measures in the SHARE measure library using the NDA data dictionary standards and integrate the SHARE assessment engine with REDCap, a popular data collection program; 3) Evaluate the prototype by conducting two rounds of usability tests with twenty alcohol researchers to evaluate system usability and perceived usefulness of the SHARE solution. Also use the NDA Validator to validate data exported from SHARE.

Public Health Relevance Statement:
Project Narrative The NIAAA data-sharing policy (NOT-AA-18-010) released in June of 2018, requires that—beginning in 2019— all NIAAA grant applications involving human subjects must include plans for the submission of study data to NIAAADA, a central data archive to store and share de-identified human subject data from NIAAA-funded research studies. The first wave of data submission to NIAAADA is expected in 2020. Many obstacles exist for alcohol researchers to comply with this policy, especially for those with limited budget and information technology and data management support. To submit the study data, researchers have to map their data to the right fields in the right format in a given data template, which often requires researchers to manipulate their data by-hand or with complicated scripts, or request a new data structure from NDA, which compromises the goal of data sharing. These data submission processes are error prone, time-consuming, and require 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.

Project Terms:
Academia; Address; Adoption; alcohol consequences; Alcohol consumption; alcohol research; Alcohols; Applications Grants; Budgets; Code; Communities; Consumption; Data; data access; data archive; Data Collection; data management; Data Set; data sharing; data structure; data submission; data warehouse; Databases; design; Dictionary; epidemiologic data; Family; Feedback; Focus Groups; Funding; Genetic; Goals; Group Interviews; Hand; Health; Human; human subject; Human Subject Research; Image; improved; Information Systems; Information Technology; Knowledge; Language; Libraries; Maps; Measures; Mental Health; Minority-Serving Institution; National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; Online Systems; open data; Phase; Policies; Privatization; Procedures; Process; programs; prototype; psychologic; Publications; Questionnaires; repository; Research; Research Personnel; Research Project Grants; research study; Resources; Rest; social; Standardization; standardize measure; success; Surveys; System; Technical Expertise; Technology; Testing; Time; tool; Translational Research; United States National Institutes of Health; usability; Validation; web services

The National Institute of Mental Health (NIMH) Data Archive (NDA) collects and shares de-identified humansubjects data from hundreds of NIH-funded research projects across many mental health-related scientificdomains with qualified researchers. A new NDA repository is created for the National Institute on AlcoholAbuse and Alcoholism Data Archive (NIAAADA) and will serve as the portal for NIAAA-related data submissionsand 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 thesubmission 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 budgetand information technology support. To submit the study data, researchers have to comb through large andcomplex NDA data definition files, often filled with inconsistencies and inaccuracies, to find the measure itemsthat they need, and then map their data to the right fields in the right format in a given data template. Thisprocess often requires researchers to manipulate their data by-hand or with complicated scripts, and is errorprone, time-consuming, and requires certain technical skills. Our ultimate goal is to provide a nearly-automatedprocess for the submission of alcohol research data into the NIAAADA so that the data submission can beperformed accurately and efficiently by alcohol researchers with minimum IT knowledge and resources.We propose to develop and validate the Share HumAn REsearch (SHARE) platform to address the unmetneed for assisting alcohol researchers with the submission of study data to NIAAADA. SHARE does so byoffering the SHARE Measure Library of pre-defined standard measures that are already mapped to NDA datadictionaries. Alcohol researchers need to only select the measures that they want to use for their studies andlet SHARE do the rest for data submission to NIAAADA.Phase II aims include: 1) Platform and measure development. In Phase II we will continue using a user-centricdesign process and the latest e-technologies to develop SHARE, and we will extend to 200 measures in bothEnglish and Spanish (when available). 2) Pilot evaluation. There will be 4 NIAAADA submission waves duringthe two-year Phase II period. We plan to align both Aim 1 and Aim 2 activities to these 4 submission wavesand recruit five projects in each wave to compare the performance of SHARE vs. NDA. A total of 20 pilotprojects will be recruited and randomized to use either SHARE or NDA for NIAAADA submission. The time andcost for data preparation and submission will be tracked, and the accuracy of submitted data assessed. Wehypothesize that compared to NDA, SHARE will perform significantly better in terms of reduced time and costimproved data accuracy.

Public Health Relevance Statement:
Project Narrative 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, a central data archive to store and share de-identified human subject data from NIAAA-funded research studies. The first wave of data 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 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 utilizing pre-defined standard measures so that the data submission can be performed accurately and efficiently by alcohol researchers with minimum technology knowledge and resources.

Project Terms: