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In far too many cases the initiatives to change schools by introducing new programs, processes and reforms has not resulted in obtainment of the desired outcomes. A major reason for limited outcomes suggested in this paper is that there has been a failure to learn from and apply constructs and measures related to understanding, facilitating and measuring dimensions of change processes. The aim of this paper is to introduce the three diagnostic dimensions of the Concerns Based Adoption Model (CBAM) along with illustrations of how each can be used to assess extent of implementation. Highlights from the four decades of development and use of each of these constructs are presented. Each of the constructs, Stages of Concern, Levels of Use and Innovation Configurations, is described along with review of the four decade story of its measurement development. Reference is made to selected studies. Implications of each construct for research, program evaluation and facilitating change processes are highlighted. The final section of the paper explores relationships between each construct. The conceptual explorations end with suggested implications for research, evaluation and practice. Throughout the author inserts short more personal anecdotes about the reasoning and experiences related to development and applications of each construct. The paper concludes with acknowledgement that other factors, especially leadership, are key to achieving implementation success.

Introduction of three research‐based constructs, Stages of Concern, Levels of Use and Innovation Configurations, their measures. Findings from selected studies are reviewed.

The three diagnostic dimensions of the Concerns Based Adoption Model have been applied with a wide range of education innovations, different contexts, and across nations and cultures.

Implementation needs to be determined through direct measurement.

Extent of implementation needs to be determined directly in all treatment and comparison/control groups.

Without direct assessment of the extent of implementation the outputs and outcomes of new programs and innovations may not be determined.

The three Diagnostic Dimensions of the Concerns Based Adoption Model have been applied widely. The conceptual implications, especially when the three constructs are interconnected two at a time, offer important suggestions for future research and in program evaluations.

Heritability studies attempt to estimate the contribution of genes (vs. environments) to variation in phenotypes (or outcomes of interest) in a given population at a given time. This chapter scrutinizes heritability studies of adverse health phenotypes, emphasizing flaws that have become more glaring in light of recent advances in the life sciences and manifest most visibly in epigenetics.

Drawing on a diverse body of research and critical scholarship, this chapter examines the veracity of methodological and conceptual assumptions of heritability studies.

The chapter argues that heritability studies are futile for two reasons: (1) heritability studies suffer from serious methodological flaws with the overall effect of making estimates inaccurate and likely biased toward inflated heritability, and, more importantly (2) the conceptual (biological) model on which heritability studies depend – that of identifiably separate effects of genes versus the environment on phenotype variance – is unsound. As discussed, contemporary bioscientific work indicates that genes and environments are enmeshed in a complex (bidirectional, interactional), dynamic relationship that defies any attempt to demarcate separate contributions to phenotype variance. Thus, heritability studies attempt the biologically impossible. The emerging research on the importance of microbiota is also discussed, including how the commensal relationship between microbial and human cells further stymies heritability studies.

Understandably, few sociologists have the time or interest to be informed about the methodological and theoretical underpinnings of heritability studies or to keep pace with the incredible advances in genetics and epigenetics over the last several years. The present chapter aims to provide interested scholars with information about heritability and heritability estimates of adverse health outcomes in light of recent advances in the biosciences.

This chapter introduces readers to a complex adaptive systems approach for integrating research on genes, behavior, and social structures/institutions. Until recently, scientists have resorted to reductionism as a decoding and epistemological strategy for understanding human health. The complex bonds among health’s biological, behavioral, and social dimensions, however, cannot be fully grasped with reductionist schemas. Moreover, because reducing and simplifying can lead to incomplete understanding of phenomena, the resulting deficient knowledge has the potential to be harmful.

To achieve its purpose, this primer will: (1) introduce fundamental notions from complexity science, useful for inquiry and practice integrating research on genes, behavior, and social structures; (2) outline selected methodological strategies employed in studying complex adaptive/dynamic systems; (3) address the question, “Specifically, how can a dynamic systems approach be helpful for integrating research on genes, behavior, and social structures/institutions, to improve the public’s health?”; and (4) provide examples of studies currently deploying a complexity perspective.

The originality/value of this primer rests in its critique of the research status quo and the proposition of an alternative lens for integrating genomic, biomedical, and sociological research to improve the public’s health. The topic of complex adaptive/dynamic systems has begun to flourish within sociology, medicine, and public health, but many researchers lack exposure to the topic’s basic notions and applications.

Broad-spectrum cephalosporin resistance is rapidly increasing in Escherichia coli, representing a food safety problem. The purpose of this paper is to characterize eight extended-spectrum-ß-lactamase (ESBL) and acquired AmpC ß-lactamase-producing E. coli isolates and virotypes associated, obtained from chicken and pork food samples in Puebla, Mexico.

Samples (36 from chicken and 10 from pork) were cultured on Levine agar plates supplemented with cefotaxime (2 mg/L) for isolation of cefotaxime-resistant (CTXR) E. coli. CTXR-E. coli isolates were detected in 33 of 46 samples (72 percent), and one isolate/sample was characterized (28 from chicken and 5 from pork), for ESBL production, phylogenetic group, sequence typing, resistance and virulence genes by PCR and sequencing.

Results showed 16 ESBL-E. coli (35 percent) (12/16 belonging to phylogroup B1) and 8 CMY-2-E. coli (17 percent). ESBL detected were as follows (number of isolates): CTX-M-2 (8); CTX-M-1 (2); CTX-M-15 (1); SHV-2a (4) and TEM-52c (1). In total, 20 different sequence types (STs) were identified among the ESBL- or CMY-2-producing E. coli strains, which included four new ones. The CTX-M-15 β-lactamase was detected in one E. coli ST617-ST10 Cplx-B1 strain that also carried ibeA gene. One CMY-2-positive strain of lineage ST224-B2 was detected and it carried the qnrA1 gene.

In this study, a ST131-based virotyping scheme for strains from food of animal origin was established since this kind of strains constitutes an important vehicle of virulent ESBL- and CMY-2-producing E. coli isolates, which could be transmitted to humans by direct contact or through the food chain.

This chapter compares interdisciplinary research that engages genomic science from economics, political science, and sociology. It describes, compares, and evaluates concepts and research findings from new and rapidly developing research fields, and develops a conceptual taxonomy of the social environment.

A selection of programmatic and empirical articles, published mostly since 2008 in leading economics, political science, and sociology journals, were analyzed according to (a) the relationship they pose between their discipline and genomic science, (b) the specific empirical contributions they make to disciplinary research questions, and (c) their conceptualization of the “social environment” as it informs the central problematique of current inquiry: gene-environment interaction.

While all three of the social science disciplines reviewed engage genomic science, economics and political science tend to engage genomics on its own terms, and develop genomic explanations of economic and political behavior. In contrast, sociologists develop arguments that for genomic science to advance, the “environment” in gene-environment interaction needs better theorization and measurement. We develop an approach to the environment that treats it as a set of measurable institutional (rule-like) arrangements, which take the forms of neighborhoods, families, schools, nations, states, and cultures.

Interdisciplinary research that combines insights from the social sciences and genomic science should develop and apply a richer array of concepts and measures if gene-environment research – including epigenetics – is to advance.

This chapter provides a critical review and redirection of three rapidly developing areas of interdisciplinary research on gene-environment interaction and epigenetics.

Our primary aim is to discuss the variability that exists in the operationalization of race/ethnicity in research on genetic and biological markers. We employ Stuart Hall’s “floating signifiers” of race approach to explain the ambiguous manner in which researchers discuss the links between race and genetics.

We examine articles that use race/ethnicity and genetic or biological markers between 2000 and 2013 within three prominent genetic journals. We focused on original, empirical articles only. We utilize various race/ethnic-related search terms to obtain our sample and to categorize how terms were used.

A total of 336 articles fit our search criteria. The number of articles mentioning race/ethnicity and genetic or biological information increased over the time. A significant percentage of publications base their research on whites only. When discussions of race are included in studies, scientists often use multiple categories of race/ethnicity without much explanation.

We omit non-research articles and commentary for each journal, which could contain important discussions regarding race and genetics. This work highlights how race/ethnicity can vary in application and interpretation.

Our discussion of race/ethnicity as “floating signifiers” adds a layer of complexity to the longstanding debate regarding the importance of race/ethnicity in genetic research. The “floating” nature of race/ethnicity underlines how subjective the characterizations of samples are and how possible interpretations of results for groups can impact health disparities research. Given the increased use of genetic data by social scientists, there is a need for more cross-disciplinary discussions on the race–gene relationship.

This study analyzes the rise of genome instability in the life sciences and traces the problematic of instability as it relates to the sociology of health. Genome instability is the study of how genomes change and become variable between generations and within organisms over the life span. Genome instability reflects a significant departure from the Platonic genome imagined during the Human Genome Project. The aim of this chapter is to explain and analyze research on copy number variation and somatic mosaicism to consider the implications of these sciences for sociologists interested in genomics.

This chapter draws on two multi-sited ethnographies of contemporary biomedical science and literature in the sociology of health, science, and biomedicine to document a shift in thinking about the genome from fixed and universal to highly variable and influenced by time and context.

Genomic instability has become a framework for addressing how genomes change and become variable between generations and within organisms over the life span. Instability is a useful framework for analyzing changes in the life sciences in the post-genomic era.

Genome instability requires life scientists to address how differences both within and between individuals articulate with shifting disease categories and classifications. For sociologists, these findings have implications for studies of identity, sociality, and clinical experience.

This is the first sociological analysis of genomic instability. It identifies practical and conceptual implications of genomic instability for life scientists and helps sociologists delineate new approaches to the study of genomics in the post-genomic era.