There is an urgent need for the evaluation of innovative web-based data collection methods that are conven- ient for the general public and yield high-quality scientific information for population researchers. The vast ma- jority of all Americans between the ages of 15 and 49 now use the Internet, even across historically marginal- ized groups such as the poor. Scientific advance has been equally rapid in: 1. Web-based survey data collection tools, giving us tremendous knowledge of the strengths and weak- nesses of using the Internet for scientific data collections. 2. The survey methodology of maximizing response to data collection efforts under fixed constraints and understanding non-response bias across measures within the same survey, including the tools for con- ducting web-based data collection that minimizes non-response bias. These rapid advances in knowledge of how the Internet might be used to conduct large-scale, high-quality sci- entific data collections are especially important to demographers researching population health. The rising costs of data collections are threatening the future of national face-to-face surveys of the general population. This issue is of high significance to all NIH-supported research on the general population, but it is especial- ly high priority for reproductive health research on topics such as contraceptive use and non-use. NIH R01 budget caps have remained exactly the same for more than 25 years, in spite of both inflation and the rapidly rising costs of data collection. As a result, new primary data collections using face-to-face interviewing of na- tional samples are now a rare, large-scale team enterprise in the population sciences, and one that is almost impossible to support using the R01 mechanism. Even the few remaining national studies using face-to-face survey data collection are now threatened, because the continued increases in costs are likely to render them difficult to support within another decade. The development of an alternative, scientifically sound data collec- tion methodology that is both well-aligned with emerging web-based technologies and convenient for the gen- eral public is absolutely essential for the continuation of high-quality population research on evolving high- priority health and well-being issues in the U.S. population. We propose to develop an optimal web-based approach to conducting national survey data collection, and validate the approach against a current gold-standard national survey of reproductive health that relies on in- terviewer-administered data collection (the U.S. National Survey of Family Growth, or NSFG). This work will allow us to determine the ability of a national web-based survey that employs an address-based sample and both sequential mixed-mode and modular survey design techniques (i.e., completing a survey in several short- er sessions rather than a single longer session) to replicate the content in this survey as well as national face- to-face survey estimates across a range of reproductive health topics using a more cost-efficient design.

Public Health Relevance

We propose to develop an optimal web-based approach to conducting national survey data collections on population health. This new methodology would significantly reduce the costs of collecting health-related data from the general population in representative samples of the entire nation or other large groups. The result will be more evidence on population health to guide both research and practice on high-priority public health topics.

Agency
National Institute of Health (NIH)
Institute
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Type
Research Project (R01)
Project #
5R01HD095920-02
Application #
9765360
Study Section
Social Sciences and Population Studies B Study Section (SSPB)
Program Officer
King, Rosalind B
Project Start
2018-09-01
Project End
2023-05-31
Budget Start
2019-06-01
Budget End
2020-05-31
Support Year
2
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Biostatistics & Other Math Sci
Type
Organized Research Units
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109