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This study delves into the factors that influence the practice of female genital mutilation in West Africa, as well as the health implications. An online cross-sectional study was conducted with the use of electronic questionnaire. The study was targeted at adult females who were between the age of 18 and 50 years old. The Uniform Resource Locator (URL) of the electronic questionnaire was administered on social media platforms (Facebook and WhatsApp) only through convenience and snowball sampling techniques. A sample size of 3,119 adult females participated in the study. Spearman rank correlation (r) was employed to test the hypotheses. Responses were gathered from adult females whom originates from nine West African countries which are Nigeria, Ghana, Mali, Liberia, Benin, Cameroon, Chad, Gambia and Guinea. The study found a strong and positive relationship between culture and the practice of female genital mutilation in West Africa, and there was a weak and positive relationship between religion and education, and the practice of female genital mutilation in West Africa. Despite the health risks, it was revealed that female genital mutilation remained uninterrupted in West Africa. The findings of this study imply that the culture of the people, religious belief system and education are critical factors in efforts to be considered when discouraging the practice of female genital mutilation. Therefore, for healthy living, the practice of female genital mutilation should be discouraged in the study area. Based on the study outcome, recommendations were suggested.

The traditional predictor of technical inefficiency proposed by Jondrow, Lovell, Materov, and Schmidt (1982) is a conditional expectation. This chapter explores whether, and by how much, the predictor can be improved by using auxiliary information in the conditioning set. It considers two types of stochastic frontier models. The first type is a panel data model where composed errors from past and future time periods contain information about contemporaneous technical inefficiency. The second type is when the stochastic frontier model is augmented by input ratio equations in which allocative inefficiency is correlated with technical inefficiency. Compared to the standard kernel-smoothing estimator, a newer estimator based on a local linear random forest helps mitigate the curse of dimensionality when the conditioning set is large. Besides numerous simulations, there is an illustrative empirical example.

In an era where health professionals are increasingly demanding, and communicative skills are one of the keys to improve the relationship with the patient. The communicative competencies of assertiveness, clarity in verbal and non-verbal language, and positivity, based on the positive construction of the patient’s health path, improve the therapeutic relationship, as well as the relationship between professionals in the world of health complexity. The ACP Model is validated with extensive application by hundreds of professionals in Portugal who use it daily. Active learning is one of the most effective means of raising awareness and involving the professionals who are learning and implementing the ACP Model.