Coping strategies used by ballet dancers: effects of individual differences in competitive trait anxiety

The world of classical ballet exerts considerable physical and psychological stress upon those who participate, and yet the process of coping with such stressors is not well understood. Relationships between coping strategies and competitive trait anxiety were investigated among 104 classical dancers (81 females and 23 males) from three professional ballet companies, two private dance schools, and two full-time, university dance courses in Australia. Coping strategies were assessed using the Modified COPE scale (MCOPE: Crocker & Graham, 1995), a 48-item measure of 12 dimensions of coping. Competitive trait anxiety was assessed using the Sport Anxiety Scale (SAS: Smith, Smoll, & Schutz, 1990), a 21-item measure of three anxiety dimensions. Trait anxiety scores, in particular for Somatic Anxiety and Worry, predicted seven of the 12 coping strategies (Suppression of Competing Activities: R2 = 27.1%; Venting of Emotions: R2 = 23.2%; Active Coping: R2 = 14.3%; Denial: R2 = 17.7%; Self-Blame: R2 = 35.7%; Effort: R2 = 16.6%; Wishful Thinking: R2 = 42.3%). High trait anxious dancers reported more frequent use of all categories of coping strategies, some of which are considered to be maladaptive. No effects of gender or status (professional versus students) were identified. Results emphasize the need for the effectiveness of specific coping strategies to be considered during the process of preparing young classical dancers for a career in professional ballet.

Coping strategies used by ballet dancers : effects of individual differences in competitive trait anxiety

The world of classical ballet exerts considerable physical and psychological stress upon those who participate, and yet the process of coping with such stressors is not well understood. The purpose of the present investigation was to examine relationships between coping strategies and competitive trait anxiety among ballet dancers. Participants were 104 classical dancers (81 females and 23 males) ranging in age from 15 to 35 years (M = 19.4 yr., SD = 3.8 yr.) from three professional ballet companies, two private dance schools, and two full-time, university dance courses in Australia. Participants had a mean of 11.5 years of classical dance training (SD = 5.2 yr.), having started dance training at 6.6 years of age (SD = 3.4 yr.). Coping strategies were assessed using the Modified COPE scale (MCOPE: Crocker & Graham, 1995), a 48-item measure comprising 12 coping subscales (Seeking Social Support for Instrumental Reasons, Seeking Social Support for Emotional Reasons, Behavioral Disengagement, Planning, Suppression of Competing Activities, Venting of Emotions, Humor, Active Coping, Denial, Self-Blame, Effort, and Wishful Thinking). Competitive trait anxiety was assessed using the Sport Anxiety Scale (SAS: Smith, Smoll, & Schutz, 1990), a 21-item measure comprising three anxiety subscales (Somatic Anxiety, Worry, Concentration Disruption). Standard multiple regression analyses showed that trait anxiety scores, in particular for Somatic Anxiety and Worry, were significant predictors of seven of the 12 coping strategies (Suppression of Competing Activities: R2 = 27.1%; Venting of Emotions: R2 = 23.2%; Active Coping: R2 = 14.3%; Denial: R2 = 17.7%; Self-Blame: R2 = 35.7%; Effort: R2 = 16.6%; Wishful Thinking: R2 = 42.3%). High trait anxious dancers reported more frequent use of all categories of coping strategies. A separate two-way MANOVA showed no significant main effect for gender nor status (professional versus students) and no significant interaction effect. The present findings are generally consistent with previous research in the sport psychology domain (Crocker & Graham, 1995; Giacobbi & Weinberg, 2000) which has shown that high trait anxious athletes tend, in particular, to use more maladaptive, emotion-focused coping strategies when compared to low trait anxious athletes; a tendency which has been proposed to lead to negative performance effects. The present results emphasize the need for the effectiveness of specific coping strategies to be considered during the process of preparing young classical dancers for a career in professional ballet. In particular, the results suggest that dancers who are, by nature, anxious about performance may need special attention to help them to learn to cope with performance-related stress. Given the absence of differences in coping strategies between student and professional dancers and between males and females, it appears that such educational efforts should begin at an early career stage for all dancers.

Heat-related morbidity in Brisbane, Australia : spatial variation and area-level predictors

Background: Extreme heat is a leading weather-related cause of illness and death in many locations across the globe, including subtropical Australia. The possibility of increasingly frequent and severe heat waves warrants continued efforts to reduce this health burden, which could be accomplished by targeting intervention measures toward the most vulnerable communities. Objectives: We sought to quantify spatial variability in heat-related morbidity in Brisbane, Australia, to highlight regions of the city with the greatest risk. We also aimed to find area-level social and environmental determinants of high risk within Brisbane. Methods: We used a series of hierarchical Bayesian models to examine city-wide and intracity associations between temperature and morbidity using a 2007–2011 time series of geographically referenced hospital admissions data. The models accounted for long-term time trends, seasonality, and day of week and holiday effects. Results: On average, a 10°C increase in daily maximum temperature during the summer was associated with a 7.2% increase in hospital admissions (95% CI: 4.7, 9.8%) on the following day. Positive statistically significant relationships between admissions and temperature were found for 16 of the city’s 158 areas; negative relationships were found for 5 areas. High-risk areas were associated with a lack of high income earners and higher population density. Conclusions: Geographically targeted public health strategies for extreme heat may be effective in Brisbane, because morbidity risk was found to be spatially variable. Emergency responders, health officials, and city planners could focus on short- and long-term intervention measures that reach communities in the city with lower incomes and higher population densities, including reduction of urban heat island effects.

Assessment of the effects of maternal exposure to heatwave on birth outcomes in Brisbane, Australia

Even though heatwave events have become more frequent and intense in most regions around the world, little is known about the impact of heatwave on birth outcomes. This thesis uses a population-based study design to investigate the relationship between maternal heatwave exposure and adverse birth outcomes in Brisbane, Australia. This study found that heatwave exposure at any stage of pregnancy can be harmful to fetal growth, and further increase the risk of adverse birth outcomes. Both short- and long-term effects of heatwave on adverse birth outcomes were found. The findings in this thesis may have significant public health implications.

Perception of prescription medicine sample packs among Australian professional, government, industry, and consumer organizations, based on automated textual analysis of one-on-one interviews

Background Prescription medicine samples provided by pharmaceutical companies are predominantly newer and more expensive products. The range of samples provided to practices may not represent the drugs that the doctors desire to have available. Few studies have used a qualitative design to explore the reasons behind sample use. Objective The aim of this study was to explore the opinions of a variety of Australian key informants about prescription medicine samples, using a qualitative methodology. Methods Twenty-three organizations involved in quality use of medicines in Australia were identified, based on the authors' previous knowledge. Each organization was invited to nominate 1 or 2 representatives to participate in semistructured interviews utilizing seeding questions. Each interview was recorded and transcribed verbatim. Leximancer v2.25 text analysis software (Leximancer Pty Ltd., Jindalee, Queensland, Australia) was used for textual analysis. The top 10 concepts from each analysis group were interrogated back to the original transcript text to determine the main emergent opinions. Results A total of 18 key interviewees representing 16 organizations participated. Samples, patient, doctor, and medicines were the major concepts among general opinions about samples. The concept drug became more frequent and the concept companies appeared when marketing issues were discussed. The Australian Pharmaceutical Benefits Scheme and cost were more prevalent in discussions about alternative sample distribution models, indicating interviewees were cognizant of budgetary implications. Key interviewee opinions added richness to the single-word concepts extracted by Leximancer. Conclusions Participants recognized that prescription medicine samples have an influence on quality use of medicines and play a role in the marketing of medicines. They also believed that alternative distribution systems for samples could provide benefits. The cost of a noncommercial system for distributing samples or starter packs was a concern. These data will be used to design further research investigating alternative models for distribution of samples.

Characterisation of a cell wall-anchored protein of Staphylococcus saprophyticus associated with linoleic acid resistance

The Gram-positive bacterium Staphylococcus saprophyticus is the second most frequent causative agent of community-acquired urinary tract infections (UTI), accounting for up to 20% of cases. A common feature of staphylococci is colonisation of the human skin. This involves survival against innate immune defenses including antibacterial unsaturated free fatty acids such as linoleic acid which act by disrupting bacterial cell membranes. Indeed, S. saprophyticus UTI is usually preceded by perineal skin colonisation.

UafB is a serine-rich repeat adhesin of Staphylococcus saprophyticus that mediates binding to fibronectin, fibrinogen and human uroepithelial cells

Staphylococcus saprophyticus is an important cause of urinary tract infection (UTI), particularly among young women, and is second only to uropathogenic Escherichia coli as the most frequent cause of UTI. The molecular mechanisms of urinary tract colonization by S. saprophyticus remain poorly understood. We have identified a novel 6.84 kb plasmid-located adhesin-encoding gene in S. saprophyticus strain MS1146 which we have termed uro-adherence factor B (uafB). UafB is a glycosylated serine-rich repeat protein that is expressed on the surface of S. saprophyticus MS1146. UafB also functions as a major cell surface hydrophobicity factor. To characterize the role of UafB we generated an isogenic uafB mutant in S. saprophyticus MS1146 by interruption with a group II intron. The uafB mutant had a significantly reduced ability to bind to fibronectin and fibrinogen. Furthermore, we show that a recombinant protein containing the putative binding domain of UafB binds specifically to fibronectin and fibrinogen. UafB was not involved in adhesion in a mouse model of UTI; however, we observed a striking UafB-mediated adhesion phenotype to human uroepithelial cells. We have also identified genes homologous to uafB in other staphylococci which, like uafB, appear to be located on transposable elements. Thus, our data indicate that UafB is a novel adhesin of S. saprophyticus that contributes to cell surface hydrophobicity, mediates adhesion to fibronectin and fibrinogen, and exhibits tropism for human uroepithelial cells.

Glutathione transferase isozyme genotypes in patients with prostate and bladder carcinoma

Genotype distributions for GSTP1, GSTM1, and GSTT1 were determined in 91 patients with prostatic carcinoma and 135 patients with bladder carcinoma and compared with those in 127 abdominal surgery patients without malignancies. None of the genotypes differed significantly with respect to age or sex among controls or cancer patients. In the group of prostatic carcinoma patients, GSTT1 null allele homozygotes were more prevalent (25% in carcinoma patients vs 13% in controls, Fisher P=0.02, χ2 P = 0.02, OR = 2.31, CI = 1.17-4.59) and the combined M1-/T1-null genotype was also more frequent (9% vs 3%, χ2 P= 0.02, Fisher P = 0.03). Homozygosity for the GSTM1 null allele was more frequent among bladder carcinoma patients (59% in bladder carcinoma patients vs 45% in controls, Fisher P = 0.03, χ2 P = 0.02, OR = 1.76, CI = 1.08-2.88). In contrast to a previous report, no significant increase in the frequency of the GSTP1b allele was found in the tumor patients. Except for the combined GSTM1-/T1-null genotype in prostatic carcinoma, none of the combined genotypes showed a significant association with either of the cancers. These findings suggest that specific single polymorphic GST genes, that is GSTM1 in the case of bladder cancer and GSTT1 in the case of prostatic carcinoma, are most relevant for the development of these urological malignancies among the general population in Central Europe.

Prescribing for nausea in palliative care : A cross-sectional national survey of Australian palliative medicine doctors

Background: Nausea can be a debilitating symptom for patients with a life-limiting illness. While addressing reversible components, nonpharmacological strategies and antiemetics are the main therapeutic option. The choice of medication, dose, and route of administration remain highly variable. Objective: The aim of this study was to codify the current clinical approaches and quantify any variation found nationally. Methods: A cross-sectional study utilizing a survey of palliative medicine clinicians examined prescribing preferences for nausea using a clinical vignette. Respondent characteristics, the use of nonpharmacological interventions, first- and second-line antiemetic choices, commencing and maximal dose, and time to review were collected. Results: Responding clinicians were predominantly working in palliative medicine across a range of settings with a 49% response rate (105/213). The main nonpharmacological recommendation was “small, frequent snacks.” Metoclopramide was the predominant first-line agent (69%), followed by haloperidol (26%), while second-line haloperidol was the predominant agent (47%), with wide variation in other nominated agents. Respondents favoring metoclopramide as first-line tended to use haloperidol second-line (65%), but not vice versa. Maximal doses for an individual antiemetic varied up to tenfold. Conclusion: For nausea, a commonly encountered symptom in palliative care, clinicians' favored metoclopramide and haloperidol; however, after these choices, there was large variation in antiemetic selection. While most clinicians recommended modifying meal size and frequency, use of other nonpharmacological therapies was limited.

Aspect-based opinion extraction from customer reviews

Text is the main method of communicating information in the digital age. Messages, blogs, news articles, reviews, and opinionated information abounds on the Internet. People commonly purchase products online and post their opinions about purchased items. This feedback is displayed publicly to assist others with their purchasing decisions, creating the need for a mechanism with which to extract and summarize useful information for enhancing the decision-making process. Our contribution is to improve the accuracy of extraction by combining different techniques from three major areas, named Data Mining, Natural Language Processing techniques and Ontologies. The proposed framework sequentially mines product’s aspects and users’ opinions, groups representative aspects by similarity, and generates an output summary. This paper focuses on the task of extracting product aspects and users’ opinions by extracting all possible aspects and opinions from reviews using natural language, ontology, and frequent “tag” sets. The proposed framework, when compared with an existing baseline model, yielded promising results.

Serosorting may increase the risk of HIV acquisition among men who have sex with men

Background: Serosorting, the practice of seeking to engage in unprotected anal intercourse with partners of the same HIV status as oneself, has been increasing among men who have sex with men. However, the effectiveness of serosorting as a strategy to reduce HIV risk is unclear, especially since it depends on the frequency of HIV testing. Methods: We estimated the relative risk of HIV acquisition associated with serosorting compared with not serosorting by using a mathematical model, informed by detailed behavioral data from a highly studied cohort of gay men. Results: We demonstrate that serosorting is unlikely to be highly beneficial in many populations of men who have sex with men, especially where the prevalence of undiagnosed HIV infections is relatively high. We find that serosorting is only beneficial in reducing the relative risk of HIV transmission if the prevalence of undiagnosed HIV infections is less than ∼20% and ∼40%, in populations of high (70%) and low (20%) treatment rates, respectively, even though treatment reduces the absolute risk of HIV transmission. Serosorting can be expected to lead to increased risk of HIV acquisition in many settings. In settings with low HIV testing rates serosorting can more than double the risk of HIV acquisition. Conclusions: Therefore caution should be taken before endorsing the practice of serosorting. It is very important to continue promotion of frequent HIV testing and condom use, particularly among people at high risk.

SHM through flexible vibration sensing technologies and robust safety evaluation paradigm

This research has successfully developed a novel synthetic structural health monitoring system model that is cost-effective and flexible in sensing and data acquisition; and robust in the structural safety evaluation aspect for the purpose of long-term and frequent monitoring of large-scale civil infrastructure during their service lives. Not only did it establish a real-world structural monitoring test-bed right at the heart of QUT Gardens Point Campus but it can also facilitate reliable and prompt protection for any built infrastructure system as well as the user community involved.

Injury narrative text classification : a preliminary study

Description of a patient's injuries is recorded in narrative text form by hospital emergency departments. For statistical reporting, this text data needs to be mapped to pre-defined codes. Existing research in this field uses the Naïve Bayes probabilistic method to build classifiers for mapping. In this paper, we focus on providing guidance on the selection of a classification method. We build a number of classifiers belonging to different classification families such as decision tree, probabilistic, neural networks, and instance-based, ensemble-based and kernel-based linear classifiers. An extensive pre-processing is carried out to ensure the quality of data and, in hence, the quality classification outcome. The records with a null entry in injury description are removed. The misspelling correction process is carried out by finding and replacing the misspelt word with a soundlike word. Meaningful phrases have been identified and kept, instead of removing the part of phrase as a stop word. The abbreviations appearing in many forms of entry are manually identified and only one form of abbreviations is used. Clustering is utilised to discriminate between non-frequent and frequent terms. This process reduced the number of text features dramatically from about 28,000 to 5000. The medical narrative text injury dataset, under consideration, is composed of many short documents. The data can be characterized as high-dimensional and sparse, i.e., few features are irrelevant but features are correlated with one another. Therefore, Matrix factorization techniques such as Singular Value Decomposition (SVD) and Non Negative Matrix Factorization (NNMF) have been used to map the processed feature space to a lower-dimensional feature space. Classifiers with these reduced feature space have been built. In experiments, a set of tests are conducted to reflect which classification method is best for the medical text classification. The Non Negative Matrix Factorization with Support Vector Machine method can achieve 93% precision which is higher than all the tested traditional classifiers. We also found that TF/IDF weighting which works well for long text classification is inferior to binary weighting in short document classification. Another finding is that the Top-n terms should be removed in consultation with medical experts, as it affects the classification performance.

Mining discriminative Itemsets in data streams

This paper presents a single pass algorithm for mining discriminative Itemsets in data streams using a novel data structure and the tilted-time window model. Discriminative Itemsets are defined as Itemsets that are frequent in one data stream and their frequency in that stream is much higher than the rest of the streams in the dataset. In order to deal with the data structure size, we propose a pruning process that results in the compact tree structure containing discriminative Itemsets. Empirical analysis shows the sound time and space complexity of the proposed method.

Identifying product families using data mining techniques in manufacturing paradigm

Identifying product families has been considered as an effective way to accommodate the increasing product varieties across the diverse market niches. In this paper, we propose a novel framework to identifying product families by using a similarity measure for a common product design data BOM (Bill of Materials) based on data mining techniques such as frequent mining and clus-tering. For calculating the similarity between BOMs, a novel Extended Augmented Adjacency Matrix (EAAM) representation is introduced that consists of information not only of the content and topology but also of the fre-quent structural dependency among the various parts of a product design. These EAAM representations of BOMs are compared to calculate the similarity between products and used as a clustering input to group the product fami-lies. When applied on a real-life manufacturing data, the proposed framework outperforms a current baseline that uses orthogonal Procrustes for grouping product families.