The family attitude scale : reliability and validity of a new scale for measuring the emotional climate of families

Research on outcomes from psychiatric disorders has highlighted the importance of expressed emotion (EE), but its cost-effective measurement remains a challenge. This article describes development of the Family Attitude Scale (FAS), a 30-item instrument that can be completed by any informant. Its psychometric characteristics are reported in parents of undergraduate students and in 70 families with a schizophrenic member. The total FAS had high internal consistency in all samples, and reports of angry behaviour in FAS items showed acceptable inter-rater agreement. The FAS was associated with the reported anger, anger expression and anxiety of respondents. Substantial associations between the parents' FAS and the anger and anger expression of students was also observed. Parents of schizophrenic patients had higher FAS scores than parents of students, and the FAS was higher if disorder duration was longer or patient functioning was poorer. Hostility, high criticism and low warmth on the Camberwell Family Interview (CFI) were associated with a more negative FAS. The highest FAS in the family was a good predictor of a highly critical environment on the CFI. The FAS is a reliable and valid indicator of relationship stress and expressed anger that has wide applicability.

Imagery and strength of craving for eating, drinking and playing sport

The elaborated intrusion (EI) theory of desire (Kavanagh, Andrade, & May, 2005) attributes the motivational force of cravings to cognitive elaboration, including imagery, of apparently spontaneous thoughts that intrude into awareness. We report a questionnaire study in which respondents rated a craving for food or drink. Questionnaire items derived from EI theory formed a single factor alongside factors for anticipated reward/relief, resistance, and opportunity. In a multiple regression predicting strength of craving, the first three factors accounted for 36% of the variance. Opportunity did not enter the model. In a second study, the difference between individuals' strong and weak cravings to take part in a sporting activity was shown to be related to visual, auditory, and general imagery, and to anticipated reward or relief from engaging in the activity. Implications for treatment of craving-related disorders are discussed in the light of these results and of other research indicating that interference with imagery can reduce the strength of craving.

Information enrichment for quality recommender systems

The explosive growth of the World-Wide-Web and the emergence of ecommerce are the major two factors that have led to the development of recommender systems (Resnick and Varian, 1997). The main task of recommender systems is to learn from users and recommend items (e.g. information, products or books) that match the users’ personal preferences. Recommender systems have been an active research area for more than a decade. Many different techniques and systems with distinct strengths have been developed to generate better quality recommendations. One of the main factors that affect recommenders’ recommendation quality is the amount of information resources that are available to the recommenders. The main feature of the recommender systems is their ability to make personalised recommendations for different individuals. However, for many ecommerce sites, it is difficult for them to obtain sufficient knowledge about their users. Hence, the recommendations they provided to their users are often poor and not personalised. This information insufficiency problem is commonly referred to as the cold-start problem. Most existing research on recommender systems focus on developing techniques to better utilise the available information resources to achieve better recommendation quality. However, while the amount of available data and information remains insufficient, these techniques can only provide limited improvements to the overall recommendation quality. In this thesis, a novel and intuitive approach towards improving recommendation quality and alleviating the cold-start problem is attempted. This approach is enriching the information resources. It can be easily observed that when there is sufficient information and knowledge base to support recommendation making, even the simplest recommender systems can outperform the sophisticated ones with limited information resources. Two possible strategies are suggested in this thesis to achieve the proposed information enrichment for recommenders: • The first strategy suggests that information resources can be enriched by considering other information or data facets. Specifically, a taxonomy-based recommender, Hybrid Taxonomy Recommender (HTR), is presented in this thesis. HTR exploits the relationship between users’ taxonomic preferences and item preferences from the combination of the widely available product taxonomic information and the existing user rating data, and it then utilises this taxonomic preference to item preference relation to generate high quality recommendations. • The second strategy suggests that information resources can be enriched simply by obtaining information resources from other parties. In this thesis, a distributed recommender framework, Ecommerce-oriented Distributed Recommender System (EDRS), is proposed. The proposed EDRS allows multiple recommenders from different parties (i.e. organisations or ecommerce sites) to share recommendations and information resources with each other in order to improve their recommendation quality. Based on the results obtained from the experiments conducted in this thesis, the proposed systems and techniques have achieved great improvement in both making quality recommendations and alleviating the cold-start problem.

Analysing preservice teachers' potential for implementing engineering education in the middle school

Engineering is pivotal to any country's development. Yet there are insufficient engineers to take up available positions in many countries, including Australia (Engineers Australia, 2008). Engineering education is limited in Australia at the primary, middle and high school levels. One of the starting points for addressing this shortfall lies in preservice teacher education. This study explores second-year preservice teachers' potential to teach engineering in middle school, following their engagement with engineering concepts in their science curriculum unit and their teaching of engineering activities to Year 7 students. Using a literature-based pretest-posttest survey, items were categorised into four constructs (ie. personal professional attributes, student motivation, pedagogical knowledge and fused curricula). Results indicated that the preservice teachers' responses had not changed for instilling positive attitudes (88%) and accepting advice from colleagues (94%). However, there was statistical significance with 9 of the 25 survey items (p<0.05) after the preservice teachers' involvement in engineering activities. Fusing engineering education with other subjects, such as mathematics and science, is an essential first step in promoting preservice teachers' potential to implement engineering education in the middle school.

Working memory correlates of three symptom clusters in schizophrenia

Examined whether discrete working memory deficits underlie positive, negative and disorganised symptoms of schizophrenia. 52 outpatients (mean age 37.5 yrs) with schizophrenia were studied using items drawn from the Positive and Negative Syndrome Scale (PANSS). Linear regression and correlational analyses were conducted to examine whether symptom dimension scores were related to performance on several tests of working memory function. Severity of negative symptoms correlated with reduced production of words during a verbal fluency task, impaired ability to hold letter and number sequences on-line and manipulate them simultaneously, reduced performance during a dual task, and compromised visuospatial working memory under distraction-free conditions. Severity of disorganisation symptoms correlated with impaired visuospatial working memory under conditions of distraction, failure of inhibition during a verbal fluency task, perseverative responding on a test of set-shifting ability, and impaired ability to judge the veracity of simple declarative statements. The present study provides evidence that the positive, negative and disorganised symptom dimensions of the PANSS constitute independent clusters, associated with unique patterns of working memory impairment.

Validation of the Edinburgh Postnatal Depression Scale for men, and comparison of item endorsement with their partners

BACKGROUND: The Edinburgh Postnatal Depression Scale (EPDS) has been validated and used extensively in screening for depression in new mothers, both in English speaking and non-English speaking communities. While some studies have reported the use of the EPDS with fathers, none have validated it for this group, and thus the appropriate cut-off score for screening for depression or anxiety caseness for this population is not known. METHODS: Couples were recruited antenatally and interviewed at six weeks postpartum. EPDS scores and distress caseness (depression or anxiety disorders) for 208 fathers and 230 mothers were determined using the Diagnostic Interview Schedule. RESULTS: Analyses of the EPDS for fathers using distress caseness (depression or anxiety disorders) as the criterion shows that a cut-off of 5/6 has optimum receiver operating characteristics. Furthermore acceptable reliability (split-half and internal consistency) and validity (concurrent) coefficients were obtained. For mothers the optimum cut-off screening value to detect distress caseness was 7/8. Item analysis revealed that fathers endorsed seven of the ten items at lower rates to mothers, with the most significant being that referring to crying. CONCLUSIONS: The EPDS is a reliable and valid measure of mood in fathers. Screening for depression or anxiety disorders in fathers requires a two point lower cut-off than screening for depression or anxiety in mothers, and we recommend this cut-off to be 5/6

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.

Tip-over injuries in children under 5 years of age in Queensland 1999-2008

Furniture and appliance related injuries in children under 5 years of age accounts for an estimated 180 emergency presentations annually in Queensland. Injuries occur when children push or pull items over, climb and fall off furniture, or climb and tip the item over. Children under 2 years of age tend to injure themselves by pulling items over onto themselves Children over 2 years of age are more likely to be injured after climbing the item and either falling off or tipping the item over onto themselves. Tip over injuries (where the item falls over and injures the child) in children under 5 years of age account for an estimated 115 emergency presentations annually in Queensland. The item most commonly associated with a tip over injury is a television (with or without the cabinet) Prevention requires better design and selection of furniture with inherent stability coupled with mechanisms to install or fix less stable items

Age-related differences in exercise and quality of life among breast cancer survivors

Purpose: Physical activity has become a focus of cancer recovery research as it has the potential to reduce treatment-related burden and optimize health-related quality of life (HRQoL). However, the potential for physical activity to influence recovery may be age-dependent. This paper describes physical activity levels and HRQoL among younger and older women after surgery for breast cancer and explores the correlates of physical inactivity. Methods: A population-based sample of breast cancer patients diagnosed in South-East Queensland, Australia, (n=287) were assessed once every three months, from 6 to 18 months post-surgery. The Functional Assessment of Cancer Therapy-Breast questionnaire (FACTB+4) and items from the Behavioral Risk Factor Surveillance System (BRFSS) questionnaire were used to measure HRQoL and physical activity, respectively. Physical activity was assigned metabolic equivalent task (MET) values, and categorized as < 3, 3 to 17.9 and 18+ MET-hours/weeks. Descriptive statistics, generalized linear models with age stratification (<50 years versus 50+ years), and logistic regression were used for analyses (p=0.05, two-tailed). Results: Younger women who engaged in 3 or more MET-hours/week of physical activity reported a higher HRQoL at 18 months compared to their more sedentary counterparts (p<0.05). Older women reported similar HRQoL irrespective of activity level and consistently reported clinically higher HRQoL than younger women. Increasing age, being overweight or obese, and restricting use of the treated side at six months post-surgery increased the likelihood of sedentary behavior (OR>3, p<0.05). Conclusions: Age influences the potential to observe HRQoL benefits related to physical activity participation. These results also provide relevant information for the design of exercise interventions for breast cancer survivors and highlights that some groups of women are at greater risk of long-term sedentary behavior.

Measuring factors that influence the utilisation of preventive care services provided by general practitioners in Australia

Background: Relatively little research attention has been given to the development of standardised and psychometrically sound scales for measuring influences relevant to the utilisation of health services. This study aims to describe the development, validation and internal reliability of some existing and new scales to measure factors that are likely to influence utilisation of preventive care services provided by general practitioners in Australia.----- Methods: Relevant domains of influence were first identified from a literature review and formative research. Items were then generated by using and adapting previously developed scales and published findings from these. The new items and scales were pre-tested and qualitative feedback was obtained from a convenience sample of citizens from the community and a panel of experts. Principal Components Analyses (PCA) and internal reliability testing (Cronbach's alpha) were then conducted for all of the newly adapted or developed scales utilising data collected from a self-administered mailed survey sent to a randomly selected population-based sample of 381 individuals (response rate 65.6 per cent).----- Results: The PCA identified five scales with acceptable levels of internal consistency were: (1) social support (ten items), alpha 0.86; (2) perceived interpersonal care (five items), alpha 0.87, (3) concerns about availability of health care and accessibility to health care (eight items), alpha 0.80, (4) value of good health (five items), alpha 0.79, and (5) attitudes towards health care (three items), alpha 0.75.----- Conclusion The five scales are suitable for further development and more widespread use in research aimed at understanding the determinants of preventive health services utilisation among adults in the general population.

Tag based collaborative filtering for recommender systems

Collaborative tagging can help users organize, share and retrieve information in an easy and quick way. For the collaborative tagging information implies user’s important personal preference information, it can be used to recommend personalized items to users. This paper proposes a novel tag-based collaborative filtering approach for recommending personalized items to users of online communities that are equipped with tagging facilities. Based on the distinctive three dimensional relationships among users, tags and items, a new similarity measure method is proposed to generate the neighborhood of users with similar tagging behavior instead of similar implicit ratings. The promising experiment result shows that by using the tagging information the proposed approach outperforms the standard user and item based collaborative filtering approaches.

Collaborative Filtering Recommender Systems based on Popular Tags

The social tags in web 2.0 are becoming another important information source to profile users' interests and preferences for making personalized recommendations. However, the uncontrolled vocabulary causes a lot of problems to profile users accurately, such as ambiguity, synonyms, misspelling, low information sharing etc. To solve these problems, this paper proposes to use popular tags to represent the actual topics of tags, the content of items, and also the topic interests of users. A novel user profiling approach is proposed in this paper that first identifies popular tags, then represents users’ original tags using the popular tags, finally generates users’ topic interests based on the popular tags. A collaborative filtering based recommender system has been developed that builds the user profile using the proposed approach. The user profile generated using the proposed approach can represent user interests more accurately and the information sharing among users in the profile is also increased. Consequently the neighborhood of a user, which plays a crucial role in collaborative filtering based recommenders, can be much more accurately determined. The experimental results based on real world data obtained from Amazon.com show that the proposed approach outperforms other approaches.

Personalized recommender systems integrating social tags and item taxonomy

The social tags in web 2.0 are becoming another important information source to profile users' interests and preferences to make personalized recommendations. To solve the problem of low information sharing caused by the free-style vocabulary of tags and the long tails of the distribution of tags and items, this paper proposes an approach to integrate the social tags given by users and the item taxonomy with standard vocabulary and hierarchical structure provided by experts to make personalized recommendations. The experimental results show that the proposed approach can effectively improve the information sharing and recommendation accuracy.

Collaborative filtering recommender systems using tag information

Recommender Systems is one of the effective tools to deal with information overload issue. Similar with the explicit rating and other implicit rating behaviours such as purchase behaviour, click streams, and browsing history etc., the tagging information implies user’s important personal interests and preferences information, which can be used to recommend personalized items to users. This paper is to explore how to utilize tagging information to do personalized recommendations. Based on the distinctive three dimensional relationships among users, tags and items, a new user profiling and similarity measure method is proposed. The experiments suggest that the proposed approach is better than the traditional collaborative filtering recommender systems using only rating data.

Interestingness Measures for Multi-Level Association Rules

Association rule mining is one technique that is widely used when querying databases, especially those that are transactional, in order to obtain useful associations or correlations among sets of items. Much work has been done focusing on efficiency, effectiveness and redundancy. There has also been a focusing on the quality of rules from single level datasets with many interestingness measures proposed. However, with multi-level datasets now being common there is a lack of interestingness measures developed for multi-level and cross-level rules. Single level measures do not take into account the hierarchy found in a multi-level dataset. This leaves the Support-Confidence approach,which does not consider the hierarchy anyway and has other drawbacks, as one of the few measures available. In this paper we propose two approaches which measure multi-level association rules to help evaluate their interestingness. These measures of diversity and peculiarity can be used to help identify those rules from multi-level datasets that are potentially useful.