# Advancing Innovative Measurement of Pregnancy Preferences with Longitudinal Data

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2023 · $268,970

## Abstract

PROJECT SUMMARY
Research into effective strategies to reduce unintended pregnancy and short interval births, and to mitigate
associated adverse maternal and neonatal health outcomes, has been hampered by poor conceptualization
and measurement of pregnancy intentions. Until recently, no validated psychometric measures had been
available to prospectively capture the range and complexity of feelings many women have about pregnancy,
including ambivalence and uncertainty. Reliance on simplistic measures and retrospective data have left
serious scientific gaps in our understanding of the causes, and health consequences, of unintended pregnancy
and short interpregnancy intervals (IPIs). Scholars have expressed an urgent need for improved measures and
longitudinal study designs, citing their importance to rigorous investigations of the role of pregnancy intentions
on the causal pathway to unintended pregnancy, short IPIs, and adverse health outcomes. This proposal
addresses these critical scientific and measurement gaps using longitudinal data from population-based
surveys, fielded to over 12,000 women, aged 18-44, across nine US states. These surveys include the Desire
to Avoid Pregnancy (DAP) scale, a novel instrument developed by our team using cutting-edge, rigorous
psychometric methods. The instrument reconceptualizes “intentions” as “preferences” and captures the
diversity of considerations and feelings women have about a potential future pregnancy. Using three years of
data, we will examine the predictive relationships between DAP scores, contraceptive use, incident pregnancy,
and birth outcomes. We will use structural equation models to investigate the extent to which DAP scores
mediate relationships between the personal and social contexts of women’s lives and pregnancy and birth
outcomes, addressing confounding that has hindered prior investigations. Critically, analyses will for the first
time apply prospective pregnancy preference data to investigate whether the elevated risk of negative maternal
and birth outcomes from short IPIs results from physiologic mechanisms, or the contexts in which these
frequently unintended pregnancies occur. We will then capitalize on the DAP’s strengths to develop novel
measurement tools that expand its utility. First, we will use item response theory (IRT) to develop a shorter
DAP version that maintains construct validity, facilitating the integration of rigorous, person-centered measures
into future research, surveillance, and clinical care. Then, we will use IRT to establish evidence-based
thresholds on the scale, defining standardized groupings of pre-pregnancy preferences (e.g., “undesired” or
“less preferred”), and addressing the urgent need for alternative measures to “unintended pregnancy” that
capture if women attain their reproductive preferences. A better understanding of how pregnancy preferences
are formed, and how unintended pregnancy contributes to adverse maternal and neonatal outcomes – as well
...

## Key facts

- **NIH application ID:** 10709484
- **Project number:** 5R01HD105764-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Corinne H. Rocca
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $268,970
- **Award type:** 5
- **Project period:** 2022-09-30 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10709484

## Citation

> US National Institutes of Health, RePORTER application 10709484, Advancing Innovative Measurement of Pregnancy Preferences with Longitudinal Data (5R01HD105764-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10709484. Licensed CC0.

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