Cigarette smoking and Ecuadorian adolescents: A cross-sectional survey and policy review

This study investigates the relationship between cigarette smoking and adolescents in Ecuador, South America. Using the Social Learning Theory as a basis, the cross-sectional survey focuses attention on such social influences as the smoking habits of family members and peers as well as, the role of cigarette advertisements. Actual use prevalence, access to cigarettes and knowledge and attitudes about smoking are also obtained.^ The survey was conducted in both urban and rural areas, with 50 schools in 40 different communities participating. Two thousand four hundred and fifty-seven adolescents aged 9 to 15 years completed a self-administered questionnaire. This part of the study was conducted in collaboration with the international health organization Amigos de las Americas (AMIGOS). Staff assigned to the AMIGOS Ecuador projects worked with local health and education officials to implement the cross-sectional survey in the field.^ The key informant survey and subsequent policy review were designed to illuminate the social, cultural and institutional environment for anti-smoking activities and interventions in Ecuador. Key individuals involved with this issue on both national and local levels were interviewed. A review of past legislative efforts and present anti-smoking laws was also conducted.^ The current smoking prevalence among the study population was 8.6 percent. Findings from the cross-sectional survey revealed significant positive associations between the smoking habits of siblings and peers and the smoking behavior of the adolescents surveyed. Significant age and gender differences were also found in association with several different variables.^ The policy review found an unfavorable environment for anti-smoking efforts. Several factors contribute to this including, most importantly, lack of funding and lack of public support. The present anti-smoking law is often vague and lacks important provisions, such as a prohibition on selling tobacco products to minors.^ Together, the two surveys provide comprehensive information for the purpose of designing smoking prevention interventions. Using the results from the two surveys, recommendations for intervention are proposed. ^

Folklore, fad, and fashion: The concept of misconduct in science redefined

This study is an analytical investigation of the nature and implications of the current conceptions of scientific misconduct, arguing that the question of what constitutes misconduct in science is significantly more complex than what conventionally has been believed. Complicating the definitions of misconduct are the differences between professional science and non-scientific professions, in their respective norms of what constitutes valid knowledge, and what counts as appropriate and inappropriate practice. While institutionalized science claims that there is clear differentiation between its standards of validity and those of the non-scientific professions, this paper argues that, when it comes to misconduct, the perceived boundaries between the scientific and non-scientific professions are breached; the practice standards that science currently employs in self-policing misconduct have come to resemble the minimal juridical standards of practice that other professions employ. This study attempts, despite erosion of these traditional boundaries, to move from legalistic standards of scientific practice to intramural standards of practice, and in so doing, to hold scientific practice to a higher standard than ordinary public conduct. The result is a clearer understanding of scientific misconduct to aid those individual scientists who are required to make onerous determinations about the appropriateness of specific practices by their peers. ^

Texas Health & Safety Code, Section 165.002 - Right to Breastfeed in Texas

The language used in Section 165.002 of the Texas Health and Safety Code renders breastfeeding women vulnerable and susceptible to harassment, discrimination, and persecution via the Texas Penal Code, Sec. 30.05 (Criminal Trespassing), Sec. 21.08 (Indecent Exposure), and Sec. 21.22 (Indecency with a Child). ^ The overall goal of this paper is to develop a solution to this problem via a proposed law or legislative action that offers protection and support for breastfeeding women who choose to nurse in public. Data to inform these recommendations were collected through a literature review and structured interviews with several breastfeeding stakeholders. A literature review of state and federal breastfeeding legislation was conducted to compare and contrast differences between existing legislation in the United States. Interviews were conducted with breastfeeding legislation stakeholders, which included state legislators who have been active in breastfeeding legislation, breastfeeding mothers, and representatives from the Central Texas Healthy Mothers Healthy Babies Coalition (Centex HMHB Coalition), Texas Breastfeeding Coalition (TXBF coalition), La Leche League International, and the Texas Business Association. Data from the literature and legislation reviews and interviews were transcribed and examined for common themes using qualitative data techniques. ^ Overall, most of the stakeholders came to a general consensus on three points, (1) breastfeeding women are supported by stakeholders within the community, (2) other legislation or penal codes should not override the right to breastfeed, and (3) the current breastfeeding legislation needs to be improved to adequately support breastfeeding women. The interviews with breastfeeding legislation stakeholders yielded two major recommendations for the improvement of Section 165.002 of the Texas Health and Safety Code: advocacy efforts to change the wording of the legislation and education to inform people about the legislation. ^ The right to breastfeed is an important public health issue in that it provides a host of health benefits for mothers and children, and is more economical and environmentally superior to alternative feeding methods. While breastfeeding in public is not illegal nor ever has been, adequate legislation is important to affirm this right for women so that they can confidently feed their children without embarrassment or harassment.^

Comparison of machine learning approaches and statistical methods for estimation of airborne chemical exposures

Accurate quantitative estimation of exposure using retrospective data has been one of the most challenging tasks in the exposure assessment field. To improve these estimates, some models have been developed using published exposure databases with their corresponding exposure determinants. These models are designed to be applied to reported exposure determinants obtained from study subjects or exposure levels assigned by an industrial hygienist, so quantitative exposure estimates can be obtained. ^ In an effort to improve the prediction accuracy and generalizability of these models, and taking into account that the limitations encountered in previous studies might be due to limitations in the applicability of traditional statistical methods and concepts, the use of computer science- derived data analysis methods, predominantly machine learning approaches, were proposed and explored in this study. ^ The goal of this study was to develop a set of models using decision trees/ensemble and neural networks methods to predict occupational outcomes based on literature-derived databases, and compare, using cross-validation and data splitting techniques, the resulting prediction capacity to that of traditional regression models. Two cases were addressed: the categorical case, where the exposure level was measured as an exposure rating following the American Industrial Hygiene Association guidelines and the continuous case, where the result of the exposure is expressed as a concentration value. Previously developed literature-based exposure databases for 1,1,1 trichloroethane, methylene dichloride and, trichloroethylene were used. ^ When compared to regression estimations, results showed better accuracy of decision trees/ensemble techniques for the categorical case while neural networks were better for estimation of continuous exposure values. Overrepresentation of classes and overfitting were the main causes for poor neural network performance and accuracy. Estimations based on literature-based databases using machine learning techniques might provide an advantage when they are applied to other methodologies that combine `expert inputs' with current exposure measurements, like the Bayesian Decision Analysis tool. The use of machine learning techniques to more accurately estimate exposures from literature-based exposure databases might represent the starting point for the independence from the expert judgment.^