Disclosing donation decisions : the role of organ donor prototypes in an extended theory of planned behaviour

This study explored the role of donor prototype evaluations (perceptions of the typical organ donor) in organ donation communication decisions using an extended theory of planned behaviour (TPB) model. The model incorporated attitude, subjective norm, perceived behavioural control, moral norm, self-identity, and donor prototype evaluations to predict intentions to record consent on an organ donor register and discuss the organ donation decision with significant others. Participants completed surveys assessing the extended TPB constructs related to registering (n = 359) and discussing (n = 282). Results supported a role for donor prototype evaluations in predicting discussing intentions only. Both extended TPB structural equation models were a good fit to the data, accounting for 74 and 76% of the variance in registering and discussing intentions, respectively. Participants’ self-reported discussing behaviour (but not registering behaviour given low numbers of behavioural performers) was assessed 4 weeks later, with discussing intention as the only significant predictor of behaviour (Nagelkerke R2 = 0.11). These findings highlight the impact of people's perceptions of a typical donor on their decisions to discuss their organ donation preference, assisting our understanding of the factors influencing individuals' communication processes in efforts to bridge the gap between organ supply and demand.

State-of-the-Art Review on Opinion Mining from Online Customers’ Feedback

Dealing with the ever-growing information overload in the Internet, Recommender Systems are widely used online to suggest potential customers item they may like or find useful. Collaborative Filtering is the most popular techniques for Recommender Systems which collects opinions from customers in the form of ratings on items, services or service providers. In addition to the customer rating about a service provider, there is also a good number of online customer feedback information available over the Internet as customer reviews, comments, newsgroups post, discussion forums or blogs which is collectively called user generated contents. This information can be used to generate the public reputation of the service providers’. To do this, data mining techniques, specially recently emerged opinion mining could be a useful tool. In this paper we present a state of the art review of Opinion Mining from online customer feedback. We critically evaluate the existing work and expose cutting edge area of interest in opinion mining. We also classify the approaches taken by different researchers into several categories and sub-categories. Each of those steps is analyzed with their strength and limitations in this paper.

Psychopathology during childhood and adolescence predicts delusional-like experiences in adults : a 21-year birth cohort study

Objective: Community surveys have shown that many otherwise well individuals report delusional-like experiences. The authors examined psychopathology during childhood and adolescence as a predictor of delusional-like experiences in young adulthood. ---------- Method: The authors analyzed prospective data from the Mater-University of Queensland Study of Pregnancy, a birth cohort of 3,617 young adults born between 1981 and 1983. Psychopathology was measured at ages 5 and 14 using the Child Behavior Checklist (CBCL) and at age 14 using the Youth Self-Report (YSR). Delusional-like experiences were measured at age 21 using the Peters Delusional Inventory. The association between childhood and adolescent symptoms and later delusional-like experiences was examined using logistic regression. ---------- Results: High CBCL scores at ages 5 and 14 predicted high levels of delusional-like experiences at age 21 (odds ratios for the highest versus the other quartiles combined were 1.25 and 1.85, respectively). Those with YSR scores in the highest quartile at age 14 were nearly four times as likely to have high levels of delusional-like experiences at age 21 (odds ratio=3.71). Adolescent-onset psychopathology and continuous psychopathology through both childhood and adolescence strongly predicted delusional-like experiences at age 21. Hallucinations at age 14 were significantly associated with delusional-like experiences at age 21. The general pattern of associations persisted when adjusted for previous drug use or the presence of nonaffective psychoses at age 21. ---------- Conclusion: Psychopathology during childhood and adolescence predicts adult delusional-like experiences. Understanding the biological and psychosocial factors that influence this developmental trajectory may provide clues to the pathogenesis of psychotic-like experiences.

Applying data mining to assess crash risk on curves

The wide range of contributing factors and circumstances surrounding crashes on road curves suggest that no single intervention can prevent these crashes. This paper presents a novel methodology, based on data mining techniques, to identify contributing factors and the relationship between them. It identifies contributing factors that influence the risk of a crash. Incident records, described using free text, from a large insurance company were analysed with rough set theory. Rough set theory was used to discover dependencies among data, and reasons using the vague, uncertain and imprecise information that characterised the insurance dataset. The results show that male drivers, who are between 50 and 59 years old, driving during evening peak hours are involved with a collision, had a lowest crash risk. Drivers between 25 and 29 years old, driving from around midnight to 6 am and in a new car has the highest risk. The analysis of the most significant contributing factors on curves suggests that drivers with driving experience of 25 to 42 years, who are driving a new vehicle have the highest crash cost risk, characterised by the vehicle running off the road and hitting a tree. This research complements existing statistically based tools approach to analyse road crashes. Our data mining approach is supported with proven theory and will allow road safety practitioners to effectively understand the dependencies between contributing factors and the crash type with the view to designing tailored countermeasures.

Data-driven impostor selection for T-norm score normalisation and the background dataset in SVM-based speaker verification

A data-driven background dataset refinement technique was recently proposed for SVM based speaker verification. This method selects a refined SVM background dataset from a set of candidate impostor examples after individually ranking examples by their relevance. This paper extends this technique to the refinement of the T-norm dataset for SVM-based speaker verification. The independent refinement of the background and T-norm datasets provides a means of investigating the sensitivity of SVM-based speaker verification performance to the selection of each of these datasets. Using refined datasets provided improvements of 13% in min. DCF and 9% in EER over the full set of impostor examples on the 2006 SRE corpus with the majority of these gains due to refinement of the T-norm dataset. Similar trends were observed for the unseen data of the NIST 2008 SRE.

Using information criteria to select the correct variance–covariance structure for longitudinal data in ecology

1. Ecological data sets often use clustered measurements or use repeated sampling in a longitudinal design. Choosing the correct covariance structure is an important step in the analysis of such data, as the covariance describes the degree of similarity among the repeated observations. 2. Three methods for choosing the covariance are: the Akaike information criterion (AIC), the quasi-information criterion (QIC), and the deviance information criterion (DIC). We compared the methods using a simulation study and using a data set that explored effects of forest fragmentation on avian species richness over 15 years. 3. The overall success was 80.6% for the AIC, 29.4% for the QIC and 81.6% for the DIC. For the forest fragmentation study the AIC and DIC selected the unstructured covariance, whereas the QIC selected the simpler autoregressive covariance. Graphical diagnostics suggested that the unstructured covariance was probably correct. 4. We recommend using DIC for selecting the correct covariance structure.

Safeguarding Rural Australia : Introduction, Framework and Background to Secondary Data Analysis

This report provides an introduction to our analyses of secondary data with respect to violent acts and incidents relating to males living in rural settings in Australia. It clarifies important aspects of our overall approach primarily by concentrating on three elements that required early scoping and resolution. Firstly, a wide and inclusive view of violence which encompasses measures of violent acts and incidents and also data identifying risk taking behaviour and the consequences of violence is outlined and justified. Secondly, the classification used to make comparisons between the city and the bush together with associated caveats is outlined. The third element discussed is in relation to national injury data. Additional commentary resulting from exploration, examination and analyses of secondary data is published online in five subsequent reports in this series.

Data Report No. 1 : Self-harm Including Suicide

This report focuses on our examination of extant data which have been sourced with respect to self-harm and suicide in Australia. Moreover, specific areas of concern regarding elevated rates of suicide for rural males and data anomalies which emerged during our examination of these data are discussed. Additional commentary resulting from exploration, examination and analyses of secondary data is published online in complementary reports in this series.

Safeguarding Rural Australia : Data Report No. 2 - Intentional Violence

This report focuses on our examination of extant data which have been sourced with respect to intentional violence perpetrated or experienced by males in regional and remote Australia. The nature of intentional violent acts can be physical, sexual or psychological or involve deprivation or neglect. We have presented under the headings of: self-harm including suicide; homicide; assault, sexual assault and the threat of assault; child abuse; other family and intimate partner violence; harassment, stalking and bullying; alcohol related social violence; and animal abuse. State variations in interpersonal violence are also presented. Additional commentary resulting from exploration, examination and analyses of secondary data is published online in complementary reports in this series.

Safeguarding Rural Australia: Data Report No. 3 - Unintentional Violence

This report focuses on our examination of extant data which have been sourced with respect to unintentional serious and violent injuries to males living in regional and remote Australia. Such injuries typically might be caused by, for example, transport accidents, occupational exposures and hazards, burns and so on. Thus unintentional violent incidents cause physical trauma the consequences of which can sometimes lead to chronic conditions including psychological harm or substance abuse. Additional commentary resulting from exploration, examination and analyses of secondary data is published online in complementary reports in this series.

Safeguarding rural Australia : addressing masculinity and violence in rural settings. Data report No. 4 - Risky behaviour - misuse of alcohol, illicit drugs, firearms use and abuse, other risky behaviour

This report focuses on our examination of extant data which have been sourced with respect to personally and socially risky behaviour associated with males living in regional and remote Australia . The AIHW (2008: PHE 97:89) defines personally risky behaviour, on the one hand, as working, swimming, boating, driving or operating hazardous machinery while intoxicated with alcohol or an illicit drug. Socially risky behaviour, on the other hand, is defined as creating a public disturbance, damaging property, stealing or verbally or physically abusing someone while intoxicated with alcohol or an illicit drug. Additional commentary resulting from exploration, examination and analyses of secondary data is published online in complementary reports in this series.

Safeguarding rural Australia : addressing masculinity and violence in rural settings. Data report no. 5. Consequences of violence - juvenile offenders, long-term health consequences, anxiety and repression, other chronic disabilities

This report considers extant data which have been sourced with respect to some of the consequences of violent acts and incidents and risky behaviour for males living in regional and remote Australia . This has been collated and presented under the headings: juvenile offenders; long-term health consequences; anxiety and repression; and other chronic disabilities. Additional commentary resulting from exploration, examination and analyses of secondary data is published online in complementary reports in this series.

Ecological perspectives and wellness

Since the industrial revolution, the development of a lifestyle lived predominantly indoors has resulted in less contact with nature. Research over the last twenty years has gradually been identifying the human health benefits attributed to re-connecting with the natural environment. The significance of feeling connected to natural environments, families and friends are described as a foundational requirement for human health and wellbeing (Maller et al., 2008). Also, the early findings of Schultz‟s (2002) work indicated that by feeling connected to the natural world a person is more likely to be committed to positively interact with and protect the natural world. Research on young people has indicated that young people are even more disconnected from the natural world. Leading some writers to call this disconnection a crisis termed “Nature Deficit Disorder.” Participants (n = 131) from 1st year university Physical Education and Human Movement Studies were asked to complete two questionnaires the Connectedness to Nature scale (CNS) (Mayer & Frantz, 2004) and the New Ecological Paradigm Scale (NEP) (Dunlap, Van Liere, Mertig, & Jones, 2000). The NEP and CNS are two scales most commonly used to explore beliefs and feelings of connectedness to the natural world (Schultz, 2002). The NEP was developed over thirty years ago by Dunlap and Van Liere (1978) and originally termed the New Environmental Paradigm. The NEP is now the foremost International tool for measuring beliefs about the natural world (Dunlap, 2008). The CNS measures an individual‟s trait levels of emotional connection to the natural world. It is a relatively new tool for understanding ecological behaviour based on ecopsychology theory and employed to predict behaviour (Mayer and Frantz, 2004). Both questionnaires are based on a 1-5 scale (Strongly disagree to Strongly agree). By combing both scales the researchers aim to develop a snap shot of beliefs and emotional feelings towards the natural world and therefore an idea of intended behaviour. The two questionnaires were combined as one online survey with additional material asking for demographics and self assessments of type of leader included before the surveys. An email inviting outdoor leaders to participate was sent out to networks and interest groups. A basic descriptive statistical analysis was used to interpret data.

The effects of sensing and seizing of market opportunities and reconfiguring activities on the organisational resource base

This study has important implications for marketing theory and practice. In an era of turbulent market environments, the organisational ability to sense and seize market opportunities and to reconfigure the resource base accordingly, has significant effects on performance. This paper uses a dynamic capability framework to explain more explicitly the intricacies of the relationship between sensing and seizing of market opportunities and reconfiguring the resource base (i.e. dynamic capabilities) and the resource base. We investigate how the attributes of dynamic capability deployment, timing, frequency and speed, influence the resource base. We test the proposed framework using survey data from 228 large organisations. Findings show that the timing and frequency of dynamic capability deployment have significant effects on the resource base.