Reflective thinking : turning a critical incident into a topic for research

Clinical nurses encounter critical incidents every day.  While these may be a source of frustration they also have the potential to be turned into research projects so that problems can be examined and others can learn from them.  This paper describes the reflective process used to generate a research project from a critical incident encountered in the clinical area.

Modeling response rates in surveys of female sexual difficulty and dysfunction

INTRODUCTION: Studies that address sensitive topics, such as female sexual difficulty and dysfunction, often achieve poor response rates that can bias  results. Factors that affect response rates to studies in this area are not well characterized.
AIM: To model the response rate in studies investigating the prevalence of female sexual difficulty and dysfunction.
METHODS: Databases were searched for English-language, prevalence studies using the search terms: sexual difficulties/dysfunction, woman/women/female, prevalence, and cross-sectional. Studies that did not report response rates or were clinic-based were excluded. A multiple linear regression model was constructed.
MAIN OUTCOME MEASURES: Published response rates.
RESULTS: A total of 1,380 publications were identified, and 54 of these met our inclusion criteria. Our model explained 58% of the variance in response rates of studies investigating the prevalence of difficulty with desire, arousal, orgasm, or sexual pain (R(2) = 0.581, P = 0.027). This model was based on study design variables, study year, location, and the reported prevalence of each type of sexual difficulty. More recent studies (beta = -1.05, P = 0.037) and studies that only included women over 50 years of age (beta = -31.11, P = 0.007) had lower response rates. The use of face-to-face interviews was associated with a higher response rate (beta = 20.51, P = 0.036). Studies that did not include questions regarding desire difficulties achieved higher response rates than those that did include questions on desire difficulty (beta = 23.70, P = 0.034).
CONCLUSION: Response rates in prevalence studies addressing female sexual difficulty and dysfunction are frequently low and have decreased by an average of just over 1% per anum since the late 60s. Participation may improve by conducting interviews in person. Studies that investigate a broad range of ages may be less representative of older women, due to a poorer response in older age groups. Lower response rates in studies that investigate desire difficulty suggest that sexual desire is a particularly sensitive topic.

Topic 12 : drugs in society

Available from Deakin University Archives

Knowledge discovery in multi-databases by analyzing local instances

Multi-databases mining is an urgent task. This thesis solves 4 key problems in multi-databases mining: Application-independent database classification - Local instance analysis model - Useful pattern discovery - Pattern synthesis.

Computer databases and the Jewish Museum of Australia : investigating the future to access the past

This thesis aims to analyse the needs of museums in terms of computer databases, examine the ways in which these databases can assist with cataloguing and museum operations in general, and survey current database programs available. The Jewish Museum of Australia is used as a pilot study to practically apply the issues discussed.

Mining frequent itemsets in distorted databases with granula computing

Data perturbation is a popular method to achieve privacy-preserving data mining. However, distorted databases bring enormous overheads to mining algorithms as compared to original databases. In this paper, we present the GrC-FIM algorithm to address the efficiency problem in mining frequent itemsets from distorted databases. Two measures are introduced to overcome the weakness in existing work: firstly, the concept of independent granule is introduced, and granule inference is used to distinguish between non-independent itemsets and independent itemsets. We further prove that the support counts of non-independent itemsets can be directly derived from subitemsets, so that the error-prone reconstruction process can be avoided. This could improve the efficiency of the algorithm, and bring more accurate results; secondly, through the granular-bitmap representation, the support counts can be calculated in an efficient way. The empirical results on representative synthetic and real-world databases indicate that the proposed GrC-FIM algorithm outperforms the popular EMASK algorithm in both the efficiency and the support count reconstruction accuracy.

An overview of previous studies in stakeholder management and its implications for construction industry

Purpose – The purpose of this paper is to provide an overview of previous studies in the field of stakeholder management, and propose implications for the construction industry.

Design/methodology/approach – Three major databases are searched: ABI, EI CompendexWeb, and ISI web of knowledge. Papers are searched on topic by using the keywords of “stakeholder management”, “management of stakeholders” and “management of stakeholder”. A brief review of the abstracts and conclusions of these papers is conducted to filter out the irrelevant and/or duplicate papers. After filtering, 159 articles with content relevant to stakeholder management are selected for analysis.

Findings – An overview of previous studies reveals that research interest in stakeholder management has turned to the descriptive approach. Through a critical review of stakeholder management process, three main problems of previous studies are identified: very few methods and tools are available to identify all stakeholders and their interests; limited studies involve the change management about the stakeholders' influence and relationship; and few studies are capable of reflecting the influence of the entire relationship network in practice.

Research limitations/implications – Two implications for the construction industry are suggested: establish a practical framework for managing stakeholders; and apply social network theory (SNT) in developing a stakeholder relationship model.

Originality/value – The overview and implications lead to new knowledge and an improved understanding of the management of multiple stakeholders in construction projects. The perspective of SNT avoids the deficiency of Freeman's dyadic ties model, and the project managers can make decisions in response to the stakeholder behaviours according to the entire relationship.

General mutation databases : analysis and review

Databases of mutations causing Mendelian disease play a crucial role in research, diagnostic and genetic health care and can play a role in life and death decisions. These databases are thus heavily used, but only gene or locus specific databases have been previously reviewed for completeness, accuracy, currency and utility. We have performed a review of the various general mutation databases that derive their data from the published literature and locus specific databases. Only two—the Human Gene Mutation Database (HGMD) and Online Mendelian Inheritance in Man (OMIM)—had useful numbers of mutations. Comparison of a number of characteristics of these databases indicated substantial inconsistencies between the two databases that included absent genes and missing mutations. This situation strengthens the case for gene specific curation of mutations and the need for an overall plan for collection, curation, storage and release of mutation data.

Topic transition detection using hierarchical hidden Markov and semi-Markov models

In this paper we introduce a probabilistic framework to exploit hierarchy, structure sharing and duration information for topic transition detection in videos. Our probabilistic detection framework is a combination of a shot classification step and a detection phase using hierarchical probabilistic models. We consider two models in this paper: the extended Hierarchical Hidden Markov Model (HHMM) and the Coxian Switching Hidden semi-Markov Model (S-HSMM) because they allow the natural decomposition of semantics in videos, including shared structures, to be modeled directly, and thus enabling efficient inference and reducing the sample complexity in learning. Additionally, the S-HSMM allows the duration information to be incorporated, consequently the modeling of long-term dependencies in videos is enriched through both hierarchical and duration modeling. Furthermore, the use of the Coxian distribution in the S-HSMM makes it tractable to deal with long sequences in video. Our experimentation of the proposed framework on twelve educational and training videos shows that both models outperform the baseline cases (flat HMM and HSMM) and performances reported in earlier work in topic detection. The superior performance of the S-HSMM over the HHMM verifies our belief that duration information is an important factor in video content modeling.