Psychological essentialism, implicit theories, and intergroup relations

Research on implicit person theories shows that beliefs about the malleability of human attributes have important implications for social cognition, interpersonal behavior, and intergroup relations. We argue that these implications can be understood within the framework of psychological essentialism, which extends work on implicit theories in promising directions. We review evidence that immutability beliefs covary with a broader set of essentialist beliefs, and that these essentialist beliefs are associated with stereotyping and prejudice. We then present recent studies indicating that associations between implicit person theories and stereotyping may be explained in terms of essentialist beliefs, implying a significant role for these beliefs in the psychology of group perception. Finally, we propose ways in which research and theory on essentialist beliefs might clarify and advance research on implicit person theories.

The culture of young women's drinking: Implications for developing effective policing strategies. Report to National Drug Strategy Law Enforcement Committee

Alcohol-related mortality and morbidity represents a substantial financial burden on communities across the world. Adolescence and young adulthood is a peak period for heavy episodic alcohol consumption, with over a third of all people aged 14-19 years having been at risk of acute alcoholrelated harm at least once in the previous 12 months (Australian Institute of Health and Welfare [AIHW], 2011). Excessive alcohol consumption has long been seen as a male problem; however, a gradual shift towards a social acceptance of female drunkenness has narrowed the gap in drinking quantity and style between men and women (Grucza, Bucholz, Rice, & Bierut, 2008). The presented data point to the vulnerability of women to the consequences of acute alcohol intoxication and indicate that alcohol-related offending by women is on the rise. Taken together, these findings reveal that alcohol-related harms and aggression for young women are becoming more prevalent and problematic. This report addressed these issues from a policing perspective...

Key beliefs of hospital nurses’ hand-hygiene behaviour: Protecting your peers and needing effective reminders

Issues addressed: Hand hygiene in hospitals is vital to limit the spread of infections. This study aimed to identify key beliefs underlying hospital nurses’ hand-hygiene decisions to consolidate strategies that encourage compliance. Methods: Informed by a theory of planned behaviour belief framework, nurses from 50 Australian hospitals (n = 797) responded to how likely behavioural beliefs (advantages and disadvantages), normative beliefs (important referents) and control beliefs (barriers) impacted on their hand-hygiene decisions following the introduction of a national ‘5 moments for hand hygiene’ initiative. Two weeks after completing the survey, they reported their hand-hygiene adherence. Stepwise regression analyses identified key beliefs that determined nurses’ hand-hygiene behaviour. Results: Reducing the chance of infection for co-workers influenced nurses’ hygiene behaviour, with lack of time and forgetfulness identified as barriers. Conclusions: Future efforts to improve hand hygiene should highlight the potential impact on colleagues and consider strategies to combat time constraints, as well as implementing workplace reminders to prompt greater hand-hygiene compliance. So what? Rather than emphasising the health of self and patients in efforts to encourage hand-hygiene practices, a focus on peer protection should be adopted and more effective workplace reminders should be implemented to combat forgetting.

Achievement unlocked: Investigating the design of effective gamification experiences for mobile applications and devices

This thesis investigates the design of motivating and engaging software experiences. In particular it examines the use of video game elements in non-game contexts, known as gamification, and how to effectively design gamification experiences for smartphone applications. The original contribution of this thesis is a novel framework for designing gamification, derived from an iterative process of evaluating gamified prototypes. The outcomes of this research can help us to better understand the impact of gamification in today's society and how it can be used to design more effective software.

Investigating a model of mentoring for effective teaching

This paper investigates a five-factor model of mentoring for effective teaching. A survey was administered to 218 student teachers after student teaching to provide insights into their mentoring experience. Results indicated the five factors, namely, personal attributes, system requirements, pedagogical knowledge, modeling, and feedback, had Cronbach alpha scores of .93, .81, .95, .91, and .91, respectively with mean scale scores ranging from 4.20 to 4.60 (p< .001). Items associated with each factor were analyzed; the lowest percentage response was reviewing lesson plans (71%) and the highest percentage was modeling effective teaching practices (96%). Triangulated data from the survey results suggested that the practices implemented by the mentor teachers were perceived to have supported the student teachers’ development during student teaching. Implications of this study suggest that actively engaging mentor teachers who apply the principles outlined by the five factor areas will serve to ensure highly effective support for the development of student teachers.

Centroid training to achieve effective text classification

Traditional text classification technology based on machine learning and data mining techniques has made a big progress. However, it is still a big problem on how to draw an exact decision boundary between relevant and irrelevant objects in binary classification due to much uncertainty produced in the process of the traditional algorithms. The proposed model CTTC (Centroid Training for Text Classification) aims to build an uncertainty boundary to absorb as many indeterminate objects as possible so as to elevate the certainty of the relevant and irrelevant groups through the centroid clustering and training process. The clustering starts from the two training subsets labelled as relevant or irrelevant respectively to create two principal centroid vectors by which all the training samples are further separated into three groups: POS, NEG and BND, with all the indeterminate objects absorbed into the uncertain decision boundary BND. Two pairs of centroid vectors are proposed to be trained and optimized through the subsequent iterative multi-learning process, all of which are proposed to collaboratively help predict the polarities of the incoming objects thereafter. For the assessment of the proposed model, F1 and Accuracy have been chosen as the key evaluation measures. We stress the F1 measure because it can display the overall performance improvement of the final classifier better than Accuracy. A large number of experiments have been completed using the proposed model on the Reuters Corpus Volume 1 (RCV1) which is important standard dataset in the field. The experiment results show that the proposed model has significantly improved the binary text classification performance in both F1 and Accuracy compared with three other influential baseline models.

Development of a cost-effective and flexible vibration DAQ system for long-term continuous structural health monitoring

In the structural health monitoring (SHM) field, long-term continuous vibration-based monitoring is becoming increasingly popular as this could keep track of the health status of structures during their service lives. However, implementing such a system is not always feasible due to on-going conflicts between budget constraints and the need of sophisticated systems to monitor real-world structures under their demanding in-service conditions. To address this problem, this paper presents a comprehensive development of a cost-effective and flexible vibration DAQ system for long-term continuous SHM of a newly constructed institutional complex with a special focus on the main building. First, selections of sensor type and sensor positions are scrutinized to overcome adversities such as low-frequency and low-level vibration measurements. In order to economically tackle the sparse measurement problem, a cost-optimized Ethernet-based peripheral DAQ model is first adopted to form the system skeleton. A combination of a high-resolution timing coordination method based on the TCP/IP command communication medium and a periodic system resynchronization strategy is then proposed to synchronize data from multiple distributed DAQ units. The results of both experimental evaluations and experimental–numerical verifications show that the proposed DAQ system in general and the data synchronization solution in particular work well and they can provide a promising cost-effective and flexible alternative for use in real-world SHM projects. Finally, the paper demonstrates simple but effective ways to make use of the developed monitoring system for long-term continuous structural health evaluation as well as to use the instrumented building herein as a multi-purpose benchmark structure for studying not only practical SHM problems but also synchronization related issues.

Effective removal of zinc (II) from aqueous solutions by tricalcium aluminate (C3A)

Recently, studies have identified high zinc levels in various environmental resources, and excessive intake of zinc has long been considered to be harmful to human health. The aim of this research was to investigate the effectiveness of tricalcium aluminate (C3A) as a removal agent of zinc from aqueous solution. Inductively coupled plasma-atomic emission spectrometer (ICP-AES), X-ray diffraction (XRD) and scanning electron microscopy (SEM) have been used to characterize such removal behavior. The effects of various factors such as pH influence, temperature and contact time were investigated. The adsorption capacity of C3A for Zn2+ was computed to be up to 13.73 mmol g−1, and the highest zinc removal capacity was obtained when the initial pH of Zn(NO3)2 solution was between 6.0 and 7.0, with temperature around 308 K. The XRD analysis showed that the resultant products were ZnAl-LDHs. Combined with the analysis of solution component, it was proved the existence of both precipitation and cation exchange in the removal process. From the experimental results, it was clear that C3A could be potentially used as a cost-effective material for the removal of zinc in aqueous environment.

Data driven and practice-based evidence : design and development of efficient and effective clinical decision support system

Decision-making is such an integral aspect in health care routine that the ability to make the right decisions at crucial moments can lead to patient health improvements. Evidence-based practice, the paradigm used to make those informed decisions, relies on the use of current best evidence from systematic research such as randomized controlled trials. Limitations of the outcomes from randomized controlled trials (RCT), such as “quantity” and “quality” of evidence generated, has lowered healthcare professionals’ confidence in using EBP. An alternate paradigm of Practice-Based Evidence has evolved with the key being evidence drawn from practice settings. Through the use of health information technology, electronic health records (EHR) capture relevant clinical practice “evidence”. A data-driven approach is proposed to capitalize on the benefits of EHR. The issues of data privacy, security and integrity are diminished by an information accountability concept. Data warehouse architecture completes the data-driven approach by integrating health data from multi-source systems, unique within the healthcare environment.

Effective communication during disasters: What effects community decision making & action?

Study/Objective This paper describes a program of research examining emergency messaging during the response and early recovery phases of natural disasters. The objective of this suite of studies is to develop message construction frameworks and channels that maximise community compliance with instructional messaging. The research has adopted a multi-hazard approach and considers the impact of formal emergency messages, as well as informal messages (e.g., social media posts), on community compliance. Background In recent years, media reports have consistently demonstrated highly variable community compliance to instructional messaging during natural disasters. Footage of individuals watching a tsunami approaching from the beach or being over-run by floodwaters are disturbing and indicate the need for a clearer understanding of decision making under stress. This project’s multi-hazard approach considers the time lag between knowledge of the event and desired action, as well as how factors such as message fatigue, message ambiguity, and the interplay of messaging from multiple media sources are likely to play a role in an individual’s compliance with an emergency instruction. Methods To examine effective messaging strategy, we conduct a critical analysis of the literature to develop a framework for community consultation and design experiments to test the potential for compliance improvement. Results Preliminary results indicate that there is, as yet, little published evidence on which to base decisions about emergency instructional messages to threatened communities. Conclusion The research described here will contribute improvements in emergency instructional message compliance by generating an evidence-based framework that takes into account behavioural compliance theory, the psychology of decision making under stress, and multiple channels of communication including social media.

Effective communication during disasters

This paper describes a program of research examining emergency messaging during the response and early recovery phases of natural disasters. The objective of this suite of studies is to develop message construction frameworks and channels that maximise community compliance with instructional messaging. The research has adopted a multi-hazard approach and considers the impact of formal emergency messages, as well as informal messages (e.g., social media posts), on community compliance. In recent years, media reports have consistently demonstrated highly variable community compliance to instructional messaging during natural disasters. Footage of individuals watching a tsunami approaching from the beach or being over-run by floodwaters are disturbing and indicate the need for a clearer understanding of decision making under stress. This project’s multi-hazard approach considers the time lag between knowledge of the event and desired action, as well as how factors such as message fatigue, message ambiguity, and the interplay of messaging from multiple media sources are likely to play a role in an individual’s compliance with an emergency instruction. To examine effective messaging strategy, we conduct a critical analysis of the literature to develop a framework for community consultation and design experiments to test the potential for compliance improvement. Preliminary results indicate that there is, as yet, little published evidence on which to base decisions about emergency instructional messages to threatened communities. The research described here will contribute improvements in emergency instructional message compliance by generating an evidence-based framework that takes into account behavioural compliance theory, the psychology of decision making under stress, and multiple channels of communication including social media.

How everyday language can and will boost effective information retrieval

Typing 2 or 3 keywords into a browser has become an easy and efficient way to find information. Yet, typing even short queries becomes tedious on ever shrinking (virtual) keyboards. Meanwhile, speech processing is maturing rapidly, facilitating everyday language input. Also, wearable technology can inform users proactively by listening in on their conversations or processing their social media interactions. Given these developments, everyday language may soon become the new input of choice. We present an information retrieval (IR) algorithm specifically designed to accept everyday language. It integrates two paradigms of information retrieval, previously studied in isolation; one directed mainly at the surface structure of language, the other primarily at the underlying meaning. The integration was achieved by a Markov machine that encodes meaning by its transition graph, and surface structure by the language it generates. A rigorous evaluation of the approach showed, first, that it can compete with the quality of existing language models, second, that it is more effective the more verbose the input, and third, as a consequence, that it is promising for an imminent transition from keyword input, where the onus is on the user to formulate concise queries, to a modality where users can express more freely, more informal, and more natural their need for information in everyday language.

Effective intercalation of sodium dodecylsulfate (SDS) into hydrocalumite: Mechanism discussion via near-infrared and mid-infrared investigations

The intercalation of an anionic surfactant, sodium dodecylsulfate (SDS), into hydrocalumite (CaAl-LDH-Cl) was investigated in this study. To understand the intercalation behavior, X-ray diffraction (XRD), mid-infrared spectroscopy (MIR), near-infrared spectroscopy (NIR) and scanning electron microscopy (SEM) were undertaken. The near-infrared spectra indicated a special spectral range from 6000 to 5600cm-1and prominent bands of CaAl-LDH-Cl intercalated with SDS around 8388cm-1. This band was assigned to the second overtone of the first fundamental of CH stretching vibrations of SDS, and it could be used to determinate the result of CaAl-LDH-Cl modified by SDS. Moreover, the results revealed that different adsorption behaviors were observed at different (high and low) concentrations of SDS. When the SDS concentration was around 0.2molL-1, anion exchange intercalation occurred and the interlayer distance expanded to about 3.25nm. When SDS concentration was 0.005molL-1, the surface adsorption of DS- was the major anion exchange event.

Effective clinical decision-making from practice-based evidence

This is an ongoing research investigating the use of health information technologies (HIT) to improve clinical decision-making processes. Effective and timely clinical decision-making can lead to positive improvements in patient’s health outcome...

Facilitating sustainable professional part-time work: A question of design?

Despite significant socio-demographic and economic shifts in the contours of work over the past 40 years, there has been surprisingly little change in the way work is designed. Current understandings of the content and structure of jobs are predominantly underpinned by early 20th century theories derived from the manufacturing industry where employees worked independently of each other in stand-alone organisations. It is only in the last 10 years that elaborations and extensions to job/work design theory have been posed, which accommodate some of the fundamental shifts in contemporary work settings, yet these extended frameworks have received little empirical attention. Utilising contemporary features of work design and a sample of professional service workers, the purpose of this study is to examine to what extent and how part-time roles are designed relative to equivalent full-time roles. The findings contribute to efforts to design effective part-time roles that balance organisational and individual objectives.