Cancer-related Behavioral Research through Integrating Existing Data (R21) | Apply Online

Frequently Asked Questions (FAQs): Cancer-related Behavioral Research through Integrating Existing Data (R21) (PAR-16-255)

What is the PAR-16-255 funding opportunity?

PAR-16-255 is a National Institutes of Health (NIH) funding announcement for the R21 mechanism titled "Cancer-related Behavioral Research through Integrating Existing Data." It supports research that answers new and meaningful questions in cancer control and cancer prevention by combining information from two or more independent, already-existing data sets.

What is the main goal of this FOA?

The main goal is to generate new cancer prevention and cancer control insights by integrating multiple existing data sources, rather than paying for new data collection. The idea is that combining independent data sets can reveal relationships that are not visible in a single study and can strengthen confidence in findings through cross-study comparisons and replication.

What kind of research questions is this grant meant to support?

This program is intended to support genuinely novel cancer control and cancer prevention questions that can be answered by integrating existing data. The expectation is that the integrated analysis produces new and meaningful scientific knowledge, not just a re-analysis of a single dataset.

Does the research have to be behavioral?

Yes. The behavioral component is essential. At least one of the integrated data sources must include behavioral data, even if other data sources contribute information at other levels such as genetic, biological, clinical, environmental, policy, healthcare system, or community-level factors.

What behavioral topics are specifically highlighted?

Examples specifically highlighted include tobacco use, sedentary behavior, poor weight management, and low adherence to recommended medical actions such as cancer screening and vaccine uptake. These examples reflect the FOA's emphasis on behavioral risk factors and behaviors that influence cancer prevention and early detection.

What does "integrating existing data" mean in this announcement?

In this FOA, integrating existing data means combining information from two or more independent data sets that already exist and were gathered separately. The integrated dataset is then analyzed to answer new questions that cannot be addressed as effectively using any single dataset alone.

How many data sets must be included?

The FOA is designed around combining two or more independent, already-existing data sets.

Do the data sets need to come from different sources?

Yes. A core idea in the announcement is that the datasets being integrated should be independent and originate from different sources and types, such as different studies, different populations, or different measurement systems.

What methods are expected for combining the data?

Projects are expected to use Integrative Data Analysis (IDA) methods. Applicants should describe a clear plan for scientifically valid integration, including how differences in measures across studies will be handled and how the integrated dataset will be analyzed to answer novel questions.

What is IDA (Integrative Data Analysis) in the context of this FOA?

IDA refers to methods for combining data across multiple independent studies or sources in a way that supports valid, interpretable analysis. In this opportunity, it includes planning for harmonized measures across studies, addressing differences in how constructs were measured, and conducting analyses that take advantage of the integrated dataset to produce new insights.

Is new data collection supported?

The program is aimed at getting more scientific value out of data that have already been gathered rather than paying for new data collection. The emphasis is on using existing resources and integrating them thoughtfully.

Can the integrated sources include non-behavioral data?

Yes. While at least one source must include behavioral data, other sources may contribute data at different levels (for example, genetic, biological, clinical, environmental, policy, or community-level factors). The FOA encourages integrating across levels of influence on cancer risk and prevention.

Can quantitative and qualitative data be combined?

Yes. The FOA indicates that integration can include combining quantitative data with qualitative data, integrating information collected in different formats or settings, and bringing together diverse data types.

Why does the FOA emphasize integration across different populations or contexts?

Integrating diverse data sources can improve generalizability and support cross-study comparisons. The FOA implies a priority on testing whether relationships hold across different demographic, cultural, and contextual settings rather than relying on a single sample.

What is meant by "harmonized measures"?

Harmonized measures refer to creating comparable variables across studies that may have measured the same concept in different ways. The announcement encourages work that creates harmonized measures and supports careful cross-study comparisons.

Does the FOA mention cultural sensitivity or equity considerations?

Yes. The announcement explicitly encourages developing culturally sensitive measures that perform appropriately across diverse groups. It also implies a priority on improving generalizability and equity by enabling comparisons across different demographic and contextual settings.

What NIH activity mechanism is used for this opportunity?

This is an NIH R21 mechanism, which generally supports exploratory and developmental research.

What is the award ceiling listed in the information provided?

The listed award ceiling is $200,000.

Who is the sponsoring agency?

The sponsoring agency is HHS-NIH (U.S. Department of Health and Human Services, National Institutes of Health).

What activity categories are associated with this opportunity?

The activity categories listed include education and health.

What CFDA number(s) are associated with this opportunity?

The information provided lists CFDA 93.393 (and notes that another code is also listed).

What organizations are eligible to apply?

The information provided indicates a wide range of eligible applicants, including: federally recognized tribal governments and tribal organizations; state and local governments; public and private institutions of higher education; nonprofit organizations with or without 501(c)(3) status; public housing authorities/Indian housing authorities; for-profit organizations (other than small businesses); and small businesses. An additional eligibility clarification is referenced in the full announcement text.

Are tribal entities included in eligibility?

Yes. Federally recognized tribal governments and tribal organizations are explicitly listed as eligible.

Are for-profit organizations eligible?

Yes. For-profit organizations (other than small businesses) are listed as eligible, and small businesses are also listed as eligible.

What dates are shown for the posting and closing of this FOA?

The posting record indicates the FOA was created and posted on May 11, 2016, and the closing date is listed as June 14, 2019 (based on the provided snapshot).

What would a competitive application generally be expected to describe?

Based on the description provided, competitive projects would typically be expected to explain: which independent datasets will be used; why integrating them is necessary to answer the research question; how measures will be harmonized (including attention to cultural validity); how differences across studies will be handled methodologically; and how the integrated analysis improves confidence in findings through replication, cross-validation, or robust comparisons across populations and settings.