by Margaret Giorgio, Elizabeth Sully, Doris W Chiu
Studies in Family Planning 52(4), Version of Record Online, 11 November 2021 (Open access)
From the Introduction
Accurate estimates of the incidence of induced abortion are essential in order to track trends in fertility and contraception use. They also provide a necessary foundation for understanding the conditions under which abortions occur, risk factors for severe abortion complications, and unintended pregnancy rates. However, abortion is notoriously difficult to measure. In countries with restrictive abortion laws, information on abortion is not routinely gathered. In countries where abortion is legal yet highly stigmatized, the clandestine circumstances under which many abortions are performed make official records incomplete. Further, respondents are often reluctant to directly admit to having had an abortion in a survey (Jones and Forrest; Jones and Kost; Lindberg et al., and efforts to encourage direct reporting through anonymized response methods have failed to consistently generate reliable abortion incidence estimates.
As a result of these challenges, researchers have tended to rely on indirect estimation techniques for producing more robust abortion incidence estimates. One common indirect approach is the abortion incidence complications method (AICM). The AICM uses data on patients hospitalized with induced abortion complications in combination with estimates of the proportion of all abortions that do not lead to a facility-based treatment to calculate an abortion incidence rate. However, recent increases in the use of medication abortion likely limit the AICM’s ability to accurately measure abortion incidence, as self-managed abortions become safer and reduce interactions with the formal healthcare system.
Another promising set of indirect methods for measuring abortion incidence are social network-based methods that use third-party reporting (TPR) to collect information on abortions within a respondent’s social network. TPR methods represent an improvement over the AICM, as they are not reliant on interactions with the health care system. These methods include (1) anonymous third-party reporting (ATPR), which collects information on all close friends; (2) the best friend approach, which collects information on a respondent’s one closest female friend (or relative), and (3) the confidante method, which collects information on two to three women with whom the respondent reciprocally shares personal information. Based on the proliferation of the use of these methods to measure abortion, with the recent increase in the use of the confidante method, in particular, there is a pressing need to evaluate the assumptions underlying these methods, potential violations of those assumptions, and the resulting biases in abortion estimates.
This paper provides the first critical assessment of the confidante method to measure abortion. We outline six key assumptions behind the confidante method and describe how potential violations of these assumptions can introduce bias to both the numerator and the denominator of these estimates. Using data from modules added to the nationally representative performance monitoring for action (PMA) surveys in Uganda and Ethiopia in 2018, we employ the confidante method to compute one-year abortion incidence estimates, which we then compare to incidence estimates derived from self-reported abortions in the same surveys, as well as the most recent AICM abortion incidence estimate in each country….
Our findings highlight the serious challenges of using the confidante method to estimate abortion incidence, which has important implications for the use of this method to measure other sensitive and stigmatized behaviors.