Living with s(k)in: An analysis of tattoo removal.

This paper investigates the role of tattoo removal in postmodernity. Specifically, I suggest tattoo removal is a technology of self in which the tattooed person can attain absolution from a "sinful" tattoo. This paper explores the construction of the confessional act in two parts: the construction of the confessing subject and the construction of the medical clinic as the confessor's listener. Using the texts medical offices place on the internet to advertise their services, I investigate the text's interpellation of subjects desiring tattoo removal. I then examine the construction of the clinic's status in the confessional act. Websites and brochures on gang tattoo removal provide a dialogue in which the clinic negotiates and attains its powerful position in the confessional act. The paper concludes by investigating the implications of the tattoo remnant, the material effects of the technology of self, and the benefits of studying the body-skin in rhetoric

fMRI repetition suppression reveals no sensitivity to trait judgments from faces in face perception or theory-of-mind networks

<div><p>The human face cues a wealth of social information, but the neural mechanisms that underpin social attributions from faces are not well known. In the current fMRI experiment, we used repetition suppression to test the hypothesis that populations of neurons in face perception and theory-of-mind neural networks would show sensitivity to faces that cue distinct trait judgments. Although faces were accurately discriminated based on associated traits, our results showed no evidence that face or theory-of-mind networks showed repetition suppression for face traits. Thus, we do not provide evidence for population coding models of face perception that include sensitivity to high and low trait features. Due to aspects of the experimental design, which bolstered statistical power and sensitivity, we have reasonable confidence that we could detect effects of a moderate size, should they exist. The null findings reported here, therefore, add value to models of neural organisation in social perception by showing instances where effects are absent or small. To test the generalisability of our findings, future work should test different types of trait judgment and different types of facial stimuli, in order to further probe the neurobiological bases of impression formation based on facial appearance.</p></div

Trusting the evidence in evidence-based practice: use of fetal fibronectin testing for threatened preterm labour in remote far North Queensland

Background: Threatened preterm labour is a common reason for medical transfer from remote communities, however many transferred women do not deliver preterm. A tool for prediction of preterm birth such as fetal fibronectin may reduce transfers and the related social and economic costs. Aim: To review the use of fetal fibronectin testing in women transferred for threatened preterm labour from Cape York to Cairns Hospital between 2011 and 2015 and determine the role testing could play in reducing transfers and associated costs. Materials/methods: Royal Flying Doctor Service and Cairns Hospital records were accessed with women transferred solely for threatened preterm labour included in the study. Fetal fibronectin testing, hospital admission, outpatient stays and birth outcome data was collated and analysed. The National Hospital Cost Data Collection, round 19 was used to assign costs. Results: Forty-seven women were included in the study however only 20 underwent fetal fibronectin testing. Transfer of 30 women who had either a negative test or were not tested but delivered at term resulted in 41 inpatient nights and 443 excess outpatient nights, costing an estimated A$61,579. Aeromedical transfers were estimated to cost a further$151,500. Conclusion: Adherence to clinical guidelines and greater availability and use of fetal fibronectin testing in Cape York has the potential to reduce aeromedical transfers for threatened preterm labour. Substantial inpatient and excess outpatient stays could be avoided with associated reduction in health system and social costs. Strategies to improve adherence to guidelines and increase access to testing are required

Academic Libraries 2014: Understanding the Diverse Grant-seeking Needs of Our Faculty

With Federal and State governments divestment from higher education research expanding over the last decade and sequestration impacts hitting the funding streams of major Federal funding agencies this year, many faculty across all disciplines are scrambling to find alternative sources of funding. Who are the major stakeholders within our campus landscapes, and how can the Library collaborate with stakeholders to insure faculty have access to the necessary tools and resources to find funding for their research, programmatic efforts and creative endeavors? How can academic libraries facilitate effective access to and use of information around grant funding for faculty use across disciplines? During the summer and fall of 2013, two University of Michigan librarians conducted interviews with faculty from the health sciences, the arts and humanities, social sciences, sciences and engineering to better understand the changing grants landscape, its intersection with research at our university, and how faculty undertake their grant-seeking activities. Wanting to know more about how grant-seeking fits into the overall research life-cycle, what resources and tools faculty utilize, and who they talk with about their grant needs, the librarians found some interesting trends and some disturbing truths.This poster compares traditional and emerging trends in grant-seeking across the disciplines at the University of Michigan. We also present a model containing the funding stakeholders, and potential ways for librarians to more closely collaborate with faculty grant-seekers.http://deepblue.lib.umich.edu/bitstream/2027.42/107043/1/MLA2014PosterHandout.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/107043/2/MLA14_GrantsAssess_Poster v3.pd

Differences in Nonmedical Use of Prescription Stimulants Among Fraternity- and Sorority-Afiliated Students

The current study reviewed data from the 2022 College Prescription Drug Study of 4,967 undergraduate students to examine differences in lifetime and past-year misuse of prescription stimulants, academic motivations and consequences of misuse, and misperceptions of prescription stimulants. Results indicate that fraternity- and sorority-affiliated students are more likely to report misusing a prescription stimulant in their lifetime and within the past year than nonaffiliated students. Fraternity and sorority members are more influenced by academic reasons and social norms than nonaffiliated students, with gender identity further predicting level of risk. Implications for prevention programming for fraternity and sorority members are discussed

Applying novel tree-based frameworks to big data for classification of heart failure patients and prediction of clinical responses

Over 5 million Americans suffer from heart failure, a condition with a 5-year survival that eclipses all cancers apart from that of lung cancer. Conventional understanding of heart failure is simplistic: it is viewed as a single syndrome, despite real heterogeneity. In addition, models predicting outcomes focus on dichotomous results, like 30-day readmission. A novel approach to classification of heart failure may improve our ability to target interventions, improve patient experiences, and predict outcomes. The Healthcare Cost and Utilization Project is a family of administrative claims databases that describes patient demographics, comorbidities, procedures, acute care utilization and outcomes, such as mortality and readmission. Using the California datasets, which allow linkage of hospital admissions to emergency department visits, we sought to (1) develop a new classification tool for heart failure, (2) predict patient response based on previous visits, (3) predict survival time. In this pilot study, we propose novel tree-based frameworks for the classification of heart failure patients that can also be used to predict clinical response, health care utilization and mortality. The pilot sample contains 822 patients with heart failure who are randomly picked from a total sample of 211284 patients. The median number of encounters per patient was 3 (IQR: 5); each are associated with up to 168 variables. By applying random forest approaches to this pilot sample, we have performed classification of patients with heart failure and identified important predictors of outcomes. Going forward, we will refine the model and apply to the entire data set to produce broadly applicable insights

Does Educator Training or Experience Affect the Quality of Multiple-Choice Questions?

Rationale and objectivesPhysicians receive little training on proper multiple-choice question (MCQ) writing methods. Well-constructed MCQs follow rules, which ensure that a question tests what it is intended to test. Questions that break these are described as "flawed." We examined whether the prevalence of flawed questions differed significantly between those with or without prior training in question writing and between those with different levels of educator experience.Materials and methodsWe assessed 200 unedited MCQs from a question bank for our senior medical student radiology elective: an equal number of questions (50) were written by faculty with previous training in MCQ writing, other faculty, residents, and medical students. Questions were scored independently by two readers for the presence of 11 distinct flaws described in the literature.ResultsQuestions written by faculty with MCQ writing training had significantly fewer errors: mean 0.4 errors per question compared to a mean of 1.5-1.7 errors per question for the other groups (P&nbsp;&lt;&nbsp;.001). There were no significant differences in the total number of errors between the untrained faculty, residents, and students (P values .35-.91). Among trained faculty 17/50 questions (34%) were flawed, whereas other faculty wrote 38/50 (76%) flawed questions, residents 37/50 (74%), and students 44/50 (88%). Trained question writers' higher performance was mainly manifest in the reduced frequency of five specific errors.ConclusionsFaculty with training in effective MCQ writing made fewer errors in MCQ construction. Educator experience alone had no effect on the frequency of flaws; faculty without dedicated training, residents, and students performed similarly

Long-Term Citizen-Collected Data Reveal Geographical Patterns and Temporal Trends in Lake Water Clarity

We compiled a lake-water clarity database using publically available, citizen volunteer observations made between 1938 and 2012 across eight states in the Upper Midwest, USA. Our objectives were to determine (1) whether temporal trends in lake-water clarity existed across this large geographic area and (2) whether trends were related to the lake-specific characteristics of latitude, lake size, or time period the lake was monitored. Our database consisted of >140,000 individual Secchi observations from 3,251 lakes that we summarized per lake-year, resulting in 21,020 summer averages. Using Bayesian hierarchical modeling, we found approximately a 1% per year increase in water clarity (quantified as Secchi depth) for the entire population of lakes. On an individual lake basis, 7% of lakes showed increased water clarity and 4% showed decreased clarity. Trend direction and strength were related to latitude and median sample date. Lakes in the southern part of our study-region had lower average annual summer water clarity, more negative long-term trends, and greater interannual variability in water clarity compared to northern lakes. Increasing trends were strongest for lakes with median sample dates earlier in the period of record (1938–2012). Our ability to identify specific mechanisms for these trends is currently hampered by the lack of a large, multi-thematic database of variables that drive water clarity (e.g., climate, land use/cover). Our results demonstrate, however, that citizen science can provide the critical monitoring data needed to address environmental questions at large spatial and long temporal scales. Collaborations among citizens, research scientists, and government agencies may be important for developing the data sources and analytical tools necessary to move toward an understanding of the factors influencing macro-scale patterns such as those shown here for lake water clarity