Peer-Informed Learning on Increasing Contraceptive Knowledge Among Women in Rural Haiti

Contraceptive prevalence in Haiti remains low despite extensive foreign aid targeted at improving family planning. [1] Earlier studies have found that peer-informed learning have been successful in promoting sexual and reproductive health. [2-5] This pilot project was implemented as a three-month, community-based, educational intervention to assess the impact of peer education in increasing contraceptive knowledge among women in Fondwa, Haiti. Research investigators conducted contraceptive information trainings to pre-identified female leaders of existing women’s groups in Fondwa, who were recruited as peer educators (n=4). Later, these female leaders shared the knowledge from the training with the test participants in the women’s group (n=23) through an information session. Structured surveys measuring knowledge of contraceptives were conducted with all participants before the intervention began, at the end of the intervention, and four weeks after the intervention. The surveys measured general contraceptive knowledge, knowledge about eight selected types of modern contraceptives and contraceptive preferences and attitudes. Only test participants showed significant improvement in their general contraceptive knowledge score (p<0.001), but both test participants and peer educators showed significant improvement in overall knowledge scores for identifying the types and uses of modern contraceptive methods. Assessment for knowledge retention remained significantly higher four weeks after the intervention than prior to the intervention. Therefore, a one-time, three-hour peer-based educational intervention using existing social structures is effective, and might be valuable in a population with minimal access to education and little to no knowledge about contraceptives.

Experimental measurement of preferences in health care using best-worst scaling (BWS): theoretical and statistical issues.

For optimal solutions in health care, decision makers inevitably must evaluate trade-offs, which call for multi-attribute valuation methods. Researchers have proposed using best-worst scaling (BWS) methods which seek to extract information from respondents by asking them to identify the best and worst items in each choice set. While a companion paper describes the different types of BWS, application and their advantages and downsides, this contribution expounds their relationships with microeconomic theory, which also have implications for statistical inference. This article devotes to the microeconomic foundations of preference measurement, also addressing issues such as scale invariance and scale heterogeneity. Furthermore the paper discusses the basics of preference measurement using rating, ranking and stated choice data in the light of the findings of the preceding section. Moreover the paper gives an introduction to the use of stated choice data and juxtaposes BWS with the microeconomic foundations.