Cultural adaptation and validation of the desire to avoid pregnancy scale in Brazil - Carolina Cavalcante da Silva Ale; Jennifer Hall; Geraldine Barrett; Corinne H. Rocca; Ana Luiza Vilela Borges (PLoS ONE, 2025)
The development of valid measures of pregnancy intentions has been an important priority in the reproductive health field. A validated measure, the Desire to Avoid Pregnancy (DAP) scale, was developed in the USA to assess preferences regarding future pregnancy and childbearing, but it has not yet been validated in Brazil. This psychometric study aimed to adapt and evaluate the DAP scale in Brazilian Portuguese using both Item Response Theory and Classical Test Theory methods. Reproductive-aged women who had ever reported sexual activity, had not had a hysterectomy, were not sterilized, and had no partner with a vasectomy (n = 1,596) responded to an online survey with the 14 DAP scale items in March and April 2021. The items were comprehensible, even among women with lower education levels. Internal consistency (Cronbach’s α = 0.958) and test-retest reliability (ICC = 0.95) were both excellent. Exploratory factor analysis confirmed a one-factor model. Based on confirmatory factor analysis and the Item Response Model, items 3 (Thinking about becoming pregnant in the next 3 months makes me feel unhappy) and 5 (Becoming pregnant in the next 3 months would bring me closer to my main partner) did not perform well. However, testing a version without these items did not show substantial improvement in the psychometric parameters. The analysis showed significant differences in DAP scores according to age, educational status, and relationship status. As hypothesized, women with higher DAP scores were more likely to use contraception than those with lower scores [OR=2.12; 95%CI = 1.90–2.35]. The DAP scale, validated in Brazil, should be used in its full 14-item version until future studies are available. The scale has the potential to generate more accurate estimates of prospective pregnancy intention in Brazil and can be used to assess the outcomes of unintended pregnancies in maternal and infant health, providing an improvement over previous approaches.