3 research outputs found
Antidiabetic, Antihypertensive and Statin Medication Use in Metabolic Syndrome
No full textBackground: Metabolic syndrome (MetS) is characterised by a cluster of metabolic risk factors, which eventually increases the risk of diabetes and cardiovascular disease (CVD). The aim of the current study was to investigate medication use in outpatient communities with respect to the occurrence of these metabolic risk factors as defined by ATPIII.Methods: Data for this study was obtained from patients attending a diabetes health screening clinic (DiabHealth) in south-eastern Australia between 2005 and 2011. Participants had a medical history taken and anthropomorphic data collected. Participants with three or more MetS factors were classified as MetS positive as outlined by the National Cholesterol Education Program Adult Treatment Panel III (ATP III).Results: Antidiabetic, antihypertensive and antihyperlipidaemic use varies significantly in uptake by participants and with respect to the number of ATPIII factors present. Blood glucose levels (BGL) and the female waist circumference were significantly better in the MetS compared to the non-MetS group. The most increase in medication use in the MetS group was seen for antidiabetic medication (21.3% versus 2.4%, p < 0.01) compared to the non-MetS group. Antihypertensive use tripled (67.8% vs. 26.03%) and Statin use doubled significantly (p<0.01) in the MetS group (21.8% vs. 8.9%).Conclusion: Medication use increases with an increase in ATPIII factors present in the study. Participants with increased BGL (>6.1mmol/L) were not found to have antihyperglycemic medication prescribed. However both antihypertensive medication and Statins were extensively prescribed in cases where only 1 and 2 ATP factors for MetS were present.</p
The influence of the extracellular matrix on cell behaviour
No full textStem cell research has raised great interest in the scientific community as it has the potential to form multiple cell types and it is believed they hold the key to curing many diseases. However, there is a need for better understanding of how to control these cells and further research investigating methods for controlling and directing these cells is required. Pluripotent stem cells transplanted into immune-deficient mice 'spontaneously’ differentiate and proliferate to form a complex mass of differentiated and undifferentiated cells, teratomas - teratoma assay. Such tumours are generally haphazard in their organisation however; they do contain some structures similar to those observed in the embryo. Teratoma formation is a useful model to explore the developmental potential of stem cells and study aspects of tissue development. Examination of how the anatomical location into which human pluripotent stem cells are grafted influences their growth in situ allows investigation of how these cells are affected by different areas within the body: cells grafted into the liver rapidly produce large tumours containing predominantly immature cells whereas, subcutaneous implants were significantly slower growing and formed tumours composed of differentiated tissues. These different growth patterns indicate how environmental cues within the niche affect stem cell behaviour. One factor which contributes to the maintenance of a niche is the extracellular matrix (ECM). To investigate how endogenous ECM affects teratoma behaviour, co-transplantation is carried out with stem cells and ECM components. The ECM extract Matrigel™ dramatically increased the success rate of teratoma formation and size with no detectable affect on teratoma composition when compared to controls and removal of the growth factors from the co-transplanted ECM extract had no effect on teratoma success rate, growth rate, or composition. To study the effects of the ECM in vitro, components of the ECM are often used topcoat glass or plastic surfaces to enhance cell attachment in vitro. Fragments of ECM molecules can be immobilised on surfaces in order to mimic the effects seen by whole molecules. In this study a novel technology developed by Oria Protein Technologies for the immobilisation of peptide sequences from ECM proteins is evaluated. By examining: the adherence of cultured PC 12; neurite outgrowth from PC 12 cells; and neuronal differentiation of neural stem/progenitor cells (NSPCs) it is shown that peptides from collagen I, collagen IV, fibronectin and laminin can mimic surfaces coated with ECM proteins. Collectively, this data demonstrates that peptides from ECM proteins can be immobilised in functional fashion to control cell behaviour. Surfaces with adsorbed proteins and biomimetic surfaces presenting peptide motifs from ECM proteins are used to investigate and explain observations from in vivo teratoma experiments. In vivo, Matrigel™ increases the gene expression of the pluripotent stem cell marker Oct4, increasing the pluripotent cell percentage and thus increases the likelihood of teratoma formation. In vitro, Matrigel™ also increases the gene expression of the proliferative marker Ki67, indicating that large teratomas from by the co-transplantation of stem cells with Matrigel™ could be due to increased cell proliferation
Visual Gender Stereotypes (Advertisement, Social Media)
No full textThe depiction of gender is the focus of a growing number of content analyses in the fields of both mass media (e.g., Goffman, 1979; Grau & Zotos, 2016; Mitchell & McKinnon, 2019; Sink & Mastro, 2017; Ward & Grower, 2020) and social media (e.g., Baker & Walsh, 2018; Döring, 2019; Döring & Mohseni, 2019; Döring et al., 2016). Typically, the depiction of gender follows traditional gender roles and, hence, does not include at lot of individuality and diversity but sticks to established gender stereotypes (Collins, 2011). Gender steoreotypes are defined as beliefs about how men versus women are (descriptive beliefs) or should be (prescriptive beliefs). Relevant dimensions of gender stereotyping are occupations (e.g., the man as the hero, breadwinner, or executive; the woman as the mother, housewife, or subordinate), sexual and romantic behaviors (e.g., the man seeking sex; the woman seeking love), personality traits (e.g., the man being active, aggressive, rational, and instrumental; the woman being passive, affectionate, emotional, and social), or body types (e.g., the man being tall, muscular and older; the woman being petite, slim, and younger). Gender stereotypes in the media cover different dimensions of traditional masculinity and feminity and are represented textually and/or (audio-)visually. Typically, the occurrence and nature of gender stereotyping in different media is measured and changes over time are of particular interest (e.g., Bhatia & Bhatia, 2020; Maker & Childs, 2003).
Field of application/theoretical foundation:
According to the Social Cognitive Theory (SCT; Bandura 1986, 2009), gender-stereotyped protagonists in the media can influence how media audiences perceive gender roles and to which degree they imitate them as role models. Cultivation theory (Gerbner & Gross, 1976; Kim & Lowry, 2005) predicts, that exposure to distorted media images of reality will shape the audiences’ worldviews. Repeated or constant exposure to gender stereotpyes in the media, according to cultivation theory, will influence the audiences’ perceptions of the roles of women and men in society. Against the background of human rights and gender equality, exaggerated gender stereotypes and the related subordination of women in the media are criticized (e.g. Döring et al., 2016; Goffman, 1979; Grau & Zotos, 2016). Often times, gender-related media content analyses support feminist claims about gender-based inequalities (Collins, 2011; Rudy et al., 2010).
When criticizing gender steoreotypes in the media, it is important to realize, though, that media do not one-directionally influence public perception and opinion (mold theory) but also bi-directionally reflect existing social gender relations and societal attitudes (mirror theory). Last but not least, based on an understanding of stereotypes as cognitive shortcuts and simplifications (Windels, 2016) it needs to be acknowledged that using stereotypes in media representations makes it easier to disseminate clear messages, inform or entertain the audience. Hence, the use of gender-related or other group-related stereotypes is not only an issue of societal relations and equality but also an issue of information processing and message creation.
References/combination with other methods of data collection:
Manual (e.g., Döring et al., 2016) and computational (e.g., Bhatia & Bhatia, 2020) content analyses of gender representations in mass media and social media can be combined. Furthermore, content analyses can be complemented with qualitative interviews and quantitative surveys to investigate both media creators’ and media audiences’ perceptions and evaluations of gender stereotypes in the media. Additionally, experimental studies are helpful to measure directly how different gender stereotypes in the media are perceived and evaluated by recipients and if and how they can affect their gender-related thoughts, feelings, and behaviors (Bast et al., 2021).
Example Studies for Manual Content Analyses:
Acknowledging the multidimensionality and complexity of gender stereotypes in the media, this DOCA entry focuses on the analysis of gender displays in the tradition of Erving Goffman (1979, 1988). Goffman’s approach originally addressed press adversitements and was qualitative in nature. It has been adopted for quantitative content analyses and extended regarding relevant dimensions with a focus on press advertisments (Kang, 1997), magazine titles (Mortensen et al., 2020) as well as social media images such as selfies on Instagram (Döring et al., 2016; Baker & Walsh, 2018). Extending Goffman’s gender display framework to social media contexts and user-generated content does make sense from a theoretical point of view (Butkowski, 2020). Usually, dichotomous or polytomous variables are used to code stereotypical gender displays in the Goffman tradition, however, some content researchers also have developed and used rating scales for coding (Butkowski et al., 2020). So far, published codebooks with example pictures are scarce.
Table 1. Example studies for manual content analyses.
Coding Material
Measure
Operationalization (excerpt)
Reliability
Source
a) Six categories of gender display according to Goffman (1979, 1988)
Relative size (between 2 or more persons)
One person (usually the man) is depicted as larger in height and greater in girth through positioning or perspective of the image compared to the other person(s) (usually the woman). Can only be coded with 2 or more persons in the picture. Binary coding (1: yes; 2: no).
Not available
N=500 selfies on Instagram
Feminine touch
One person (usually the woman) is pictured using their fingers and hands to trace the outlines of an object or to cradle it or to caress its surface or to touch their own body (e.g., their hair). The so-called feminine touch is not goal-oriented or functional. Binary coding (1: yes; 2: no).Example image for femine touch:
Cohen’s Kappa = .79
Döring et al. (2016)
Function ranking (between 2 or more persons)
One person (usually the man) is pictured in the executive or dominant role, the other person in the subordinate or assisting role (usually the woman). Can only be coded with 2 or more persons in the picture. Binary coding (1: yes; 2: no)
Not available
Family(nuclear family of four persons)
The typical nuclear family is depicted with mother, father, daughter, and son. Typically, closer bonds between mother and daughter on the one side, and father and son on the other side are depicted. Can only be coded with a whole family in the picture. Multidimensional qualitative variable that has not been adopted for quantitative coding yet.
Not available
N=500 selfies on Instagram
Ritualization of subordination
One person (usually the woman) is depicted in a posture of subordination that deviates from a stable, upright position and includes lying/sitting postures and imbalance.
Posture of subordination includes lying or sitting versus standing: Polytomous coding (1: lying, 2: sitting, 3: standing)Example image for lying posture:
Imbalance in body posture includes canting positions and knee bending. Binary coding (1: yes; 2: no). Example image for imbalance posture:
Lying, sitting, standing posture Cohen’s Kappa = 1.00
Imbalance posture: Cohen’s Kappa = .90
Döring et al. (2016)
N=500 selfies on Instagram
Licensed withdrawal
One person (usually the woman) is depicted in a situation of licensed withdrawal meaning that she does not fully turn to the camera. This includes withdrawing gaze and loss of control.
Withdrawing gaze means that one person (usually the woman) is depicted gazing away from the camera. Binary coding (1: yes; 2: no).Example image withdrawing gaze:
Loss of control means that one person (usually the woman) is depicted expressing strong emotions implying that she is not fully focusing on the current scene . Binary coding (1: yes; 2: no).Example image loss of control:
Withdrawing gaze: Cohen’s Kappa = 1.00
Loss of control: Cohen’s Kappa = 1.00
Döring et al. (2016)
b) Two additional gender display categories according to Kang (1997)
N=500 selfies on Instagram
Body Display
Body display of persons vary with the type of clothing.
One person (usually the man) is depicted in full clothing. Binary coding (1: yes; 2: no).
One person (usually the woman) is depicted in sparse clothing or nudity. Binary coding (1: yes; 2: no).Example image sparse closing
Full clothing Cohen’s Kappa = .73
Sparse clothing: Cohen’s Kappa = .73
Döring et al. (2016)
Independence and self-assertiveness
One person (usually the man) is depicted in a position of independence and self-assertivenesss. Binary coding (1: yes; 2: no).
Not available
c) Three categories of social media related gender stereotypes (Döring et al., 2016)
N=500 selfies on Instagram
Kissing pout
One person (usually the woman) is depicted showing a kissing pout (“duck face”). Binary coding (1: yes; 2: no).
Example image for kissing pout:
Cohen’s Kappa = 1.00
Döring et al. (2016)
N=500 selfies on Instagram
Muscle presentation
One person (usually the man) is depicted presenting their muscles (e.g., biceps, sixpack). Binary coding (1: yes; 2: no).
Example image for muscle presentation:
Cohen’s Kappa = 1.00
Döring et al. (2016)
N=500 selfies on Instagram
Faceless portrayal
One person (usually the woman) is depicted without the face in the picture. Binary coding (1: yes; 2: no).
Example image for faceless portayal:
Cohen’s Kappa = 1.00
Döring et al. (2016)
Note. In order to ensure anonymity, no original Instagram posts are displayed. All example pictures shown are re-enactments to visually illustrate the categories and all protagonists gave their informed consent for publication of the pictures. The pictures are also used in the original study Döring et al. (2016).
The categories of gender display in the tradition of Erving Goffman (1979, 1988) can be complemented with further categories that go into more detail of physical appearance in terms of body type, attire or sexualization. Furthermore, additional dimensions of gender stereotyping such as occupations or activities can be added.
References
Baker, S. A., & Walsh, M. J. (2018). ‘Good morning fitfam’: Top posts, hashtags and gender display on Instagram. New Media & Society, 20(12), 4553–4570. https://doi.org/10.1177/1461444818777514
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Bandura, A. (2009). Social cognitive theory of mass communication. In J. Bryant & M. B. Oliver (Eds.), Communication series. Media effects: Advances in theory and research (3rd ed., pp. 94–124). Routledge.
Bast, J., Oschatz, C., & Renner, A.‑M. (2021). Successfully overcoming the “bouble bind”? A mixed-method analysis of the self-presentation of female right-wing populists on Instagram and the impact on voter attitudes. Political Communication, 1–25. https://doi.org/10.1080/10584609.2021.2007190
Bhatia, N., & Bhatia, S. (2021). Changes in gender stereotypes over time: A computational analysis. Psychology of Women Quarterly, 45(1), 106–125. https://doi.org/10.1177/0361684320977178
Butkowski, C. P. (2020). Beyond “commercial realism”: Extending Goffman’s gender display framework to networked media contexts. Communication, Culture and Critique, 14(1), 89-108.
Butkowski, C. P., Dixon, T. L., Weeks, K. R., & Smith, M.A. (2020). Quantifying the feminine self(ie): Gender display and social media feedback in young women’s Instagram selfies. New Media & Society, 22(5), 817-837. https://doi.org/10.1177/1461444819871669
Collins, R. L. (2011). Content analysis of gender roles in media: Where are we now and where should we go? Sex Roles, 64(3-4), 290–298. https://doi.org/10.1007/s11199-010-9929-5
Döring, N. (2019). Videoproduktion auf YouTube: Die Bedeutung von Geschlechterbildern [Video production on YouTube: The relevance of gender images]. In J. Dorer, B. Geiger, B. Hipfl, & V. Ratković (Eds.), Handbuch Medien und Geschlecht: Perspektiven und Befunde der feministischen Kommunikations- und Medienforschung (pp. 1–11). Springer Fachmedien. https://doi.org/10.1007/978-3-658-20712-0_53-1
Döring, N., & Mohseni, M. R. (2019). Fail videos and related video comments on YouTube: A case of sexualization of women and gendered hate speech? Communication Research Reports, 36(3), 254–264. https://doi.org/10.1080/08824096.2019.1634533
Döring, N., Reif, A., & Poeschl, S. (2016). How gender-stereotypical are selfies? A content analysis and comparison with magazine adverts. Computers in Human Behavior, 55, 955–962. https://doi.org/10.1016/j.chb.2015.10.001
Gerbner, G., & Gross, L. (1976). Living with television: The violence profile. The Journal of Communication, 26(2), 173–199. https://doi.org/10.1111/j.1460-2466.1976.tb01397.x
Goffman, E. (1979). Gender advertisements. Harper & Row.
Goffman, E. (1988). Gender advertisements (revised edition). Harpercollins College Div.
Grau, S. L., & Zotos, Y. C. (2016). Gender stereotypes in advertising: A review of current research. International Journal of Advertising, 35(5), 761–770. https://doi.org/10.1080/02650487.2016.1203556
Kang, M.‑E. (1997). The portrayal of women’s images in magazine advertisements: Goffman’s gender analysis revisited. Sex Roles, 37(11-12), 979–996. https://doi.org/10.1007/BF02936350
Kim, K., & Lowry, D. T. (2005). Television commercials as a lagging social indicator: Gender role stereotypes in Korean television advertising. Sex Roles, 53(11-12), 901–910. https://doi.org/10.1007/s11199-005-8307-1
Maker, J. K., & Childs, N. M. (2003). A longitudinal content analysis of gender roles in children\u27s television advertisements: A 27 year review. Journal of Current Issues & Research in Advertising, 25(1), 71–81. https://doi.org/10.1080/10641734.2003.10505142
Mitchell, M., & McKinnon, M. (2019). \u27Human\u27 or \u27objective\u27 faces of science? Gender stereotypes and the representation of scientists in the media. Public Understanding of Science (Bristol, England), 28(2), 177–190. https://doi.org/10.1177/0963662518801257
Mortensen, T. M., Ejaz, K., & Pardun, C. J. (2020). Quantifying gender stereotypes? Visually assessing stereotypes of women in People Magazine. Journal of Magazine Media, 21(1), 30–50. https://doi.org/10.1353/jmm.2020.0002
Rudy, R. M., Popova, L., & Linz, D. G. (2010). The context of current content analysis of gender roles: An introduction to a special issue. Sex Roles, 62(11-12), 705–720. https://doi.org/10.1007/s11199-010-9807-1
Sink, A., & Mastro, D. (2017). Depictions of gender on primetime television: A quantitative content analysis. Mass Communication and Society, 20(1), 3–22. https://doi.org/10.1080/15205436.2016.1212243
Ward, L. M., & Grower, P. (2020). Media and the development of gender role stereotypes. Annual Review of Developmental Psychology, 2(1), 177–199. https://doi.org/10.1146/annurev-devpsych-051120-010630
Windels, K. (2016). Stereotypical or just typical: How do US practitioners view the role and function of gender stereotypes in advertisements? International Journal of Advertising, 35(5), 864–887. https://doi.org/10.1080/02650487.2016.116085
