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      “Bed bugs live in dirty places”—How Using Live Animals in Teaching Contributes to Reducing Stigma, Disgust, Psychological Stigma, and Misinformation in Students

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          Abstract

          Bed bugs are on the rise and are increasingly perceived as harmful parasites. Because individuals affected by bed bugs often feel disgust and shame and are stigmatized, bed bugs are an important public health and environmental justice concern and therefore a health education issue as well. In this quasi-experimental study, we examine how different constructs, namely, forms of stigma, disgust, psychological distance, and myths about bed bugs (dependent variables), change over time (pre/posttest) in response to two forms of teaching intervention (independent variables) in upper secondary-level high school. The content of the interventions was the same, but in class, we showed live bed bugs to one group of students, assuming this would lead to a more realistic, less imaginative response to bed bugs than in the group presented with only pictures of bed bugs. Together with previous studies, we assumed that live bed bugs would be perceived as less disgusting and with a lower degree of stigmatization. Our results show that stigma, psychological distance, and myths can be reduced through intervention (regardless of live animal or picture). Disgust was more strongly reduced by live animals than by pictures. We present implications for biology education and contemporary health education.

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          lmerTest Package: Tests in Linear Mixed Effects Models

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            Fitting Linear Mixed-Effects Models Using lme4

            Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in an lmer call by a formula, in this case including both fixed- and random-effects terms. The formula and data together determine a numerical representation of the model from which the profiled deviance or the profiled REML criterion can be evaluated as a function of some of the model parameters. The appropriate criterion is optimized, using one of the constrained optimization functions in R, to provide the parameter estimates. We describe the structure of the model, the steps in evaluating the profiled deviance or REML criterion, and the structure of classes or types that represents such a model. Sufficient detail is included to allow specialization of these structures by users who wish to write functions to fit specialized linear mixed models, such as models incorporating pedigrees or smoothing splines, that are not easily expressible in the formula language used by lmer. Journal of Statistical Software, 67 (1) ISSN:1548-7660
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              Conceptualizing Stigma

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                Author and article information

                Contributors
                Role: Monitoring Editor
                Journal
                CBE Life Sci Educ
                CBE Life Sci Educ
                CBE-LSE
                lse
                CBE Life Sciences Education
                American Society for Cell Biology
                1931-7913
                Winter 2022
                : 21
                : 4
                : ar73
                Affiliations
                []Centre for Biology Education, Westfälische Wilhelms-Universität, Schlossplatz 34, 48143 Münster, Germany
                [§ ]Institute for Science Education, Leibniz Universität Hannover, Am Kleinen Felde 30, 30167 Hannover, Germany
                []Faculty of Biology, Applied Zoology, TU Dresden, Zellescher Weg 20b, 01217 Dresden, Germany
                Author notes

                These authors contributed equally to this work.

                *Address correspondence to: Roman Asshoff ( roman.asshoff@ 123456uni-muenster.de ).
                Article
                CBE.22-03-0056
                10.1187/cbe.22-03-0056
                9727609
                36194505
                3a4bfc9d-36eb-4e6f-8a95-6c04cdb548f9
                © 2022 R. Asshoff, B. Heuckmann, et al. CBE—Life Sciences Education © 2022 The American Society for Cell Biology. “ASCB®” and “The American Society for Cell Biology®” are registered trademarks of The American Society for Cell Biology.

                This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 4.0 Unported Creative Commons License.

                History
                : 21 March 2022
                : 23 August 2022
                : 01 September 2022
                Categories
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                Education
                Education

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