Online alcohol interventions : a systematic review

Background: There has been a significant increase in the availability of online programs for alcohol problems. A systematic review of the research evidence underpinning these programs is timely. Objectives: Our objective was to review the efficacy of online interventions for alcohol misuse. Systematic searches of Medline, PsycINFO, Web of Science, and Scopus were conducted for English abstracts (excluding dissertations) published from 1998 onward. Search terms were: (1) Internet, Web*; (2) online, computer*; (3) alcohol*; and (4) E\effect*, trial*, random* (where * denotes a wildcard). Forward and backward searches from identified papers were also conducted. Articles were included if (1) the primary intervention was delivered and accessed via the Internet, (2) the intervention focused on moderating or stopping alcohol consumption, and (3) the study was a randomized controlled trial of an alcohol-related screen, assessment, or intervention. Results: The literature search initially yielded 31 randomized controlled trials (RCTs), 17 of which met inclusion criteria. Of these 17 studies, 12 (70.6%) were conducted with university students, and 11 (64.7%) specifically focused on at-risk, heavy, or binge drinkers. Sample sizes ranged from 40 to 3216 (median 261), with 12 (70.6%) studies predominantly involving brief personalized feedback interventions. Using published data, effect sizes could be extracted from 8 of the 17 studies. In relation to alcohol units per week or month and based on 5 RCTs where a measure of alcohol units per week or month could be extracted, differential effect sizes to post treatment ranged from 0.02 to 0.81 (mean 0.42, median 0.54). Pre-post effect sizes for brief personalized feedback interventions ranged from 0.02 to 0.81, and in 2 multi-session modularized interventions, a pre-post effect size of 0.56 was obtained in both. Pre-post differential effect sizes for peak blood alcohol concentrations (BAC) ranged from 0.22 to 0.88, with a mean effect size of 0.66. Conclusions: The available evidence suggests that users can benefit from online alcohol interventions and that this approach could be particularly useful for groups less likely to access traditional alcohol-related services, such as women, young people, and at-risk users. However, caution should be exercised given the limited number of studies allowing extraction of effect sizes, the heterogeneity of outcome measures and follow-up periods, and the large proportion of student-based studies. More extensive RCTs in community samples are required to better understand the efficacy of specific online alcohol approaches, program dosage, the additive effect of telephone or face-to-face interventions, and effective strategies for their dissemination and marketing.

Online social networks as an emerging opportunity for entrepreneurship : a study of the music industry

The explosion in use of online social networks is an important phenomenon that provides a new set of entrepreneurial opportunities. Emerging musicians have been among the first to exploit this new market opportunity – and indeed, many have used it successfully. A recent study Carter (2009) reveals that artists who earned the most returns had an online presence on multiple social online sites and services such as MySpace and Facebook. These web pages are leveraged to build fan bases and develop different types of revenue streams. Yet, little is currently known about discovery or exploitation of such opportunities.

Approximate Bayesian computation using indirect inference

We present a novel approach for developing summary statistics for use in approximate Bayesian computation (ABC) algorithms by using indirect inference. ABC methods are useful for posterior inference in the presence of an intractable likelihood function. In the indirect inference approach to ABC the parameters of an auxiliary model fitted to the data become the summary statistics. Although applicable to any ABC technique, we embed this approach within a sequential Monte Carlo algorithm that is completely adaptive and requires very little tuning. This methodological development was motivated by an application involving data on macroparasite population evolution modelled by a trivariate stochastic process for which there is no tractable likelihood function. The auxiliary model here is based on a beta–binomial distribution. The main objective of the analysis is to determine which parameters of the stochastic model are estimable from the observed data on mature parasite worms.

Development of an online condition monitoring system for slow speed machinery

One of the main challenges of slow speed machinery condition monitoring is that the energy generated from an incipient defect is too weak to be detected by traditional vibration measurements due to its low impact energy. Acoustic emission (AE) measurement is an alternative for this as it has the ability to detect crack initiations or rubbing between moving surfaces. However, AE measurement requires high sampling frequency and consequently huge amount of data are obtained to be processed. It also requires expensive hardware to capture those data, storage and involves signal processing techniques to retrieve valuable information on the state of the machine. AE signal has been utilised for early detection of defects in bearings and gears. This paper presents an online condition monitoring (CM) system for slow speed machinery, which attempts to overcome those challenges. The system incorporates relevant signal processing techniques for slow speed CM which include noise removal techniques to enhance the signal-to-noise and peak-holding down sampling to reduce the burden of massive data handling. The analysis software works under Labview environment, which enables online remote control of data acquisition, real-time analysis, offline analysis and diagnostic trending. The system has been fully implemented on a site machine and contributing significantly to improve the maintenance efficiency and provide a safer and reliable operation.

Design education online : learning delivery and evaluation

Online learning has been recognised as an effective pedagogical method and tool, and is broadly integrated into various types of teaching and learning strategies in higher education. In practice, the use of Virtual Learning Environment (VLE) in higher education has become an integral strategy for quality education. The field of design education however has not been researched extensively in regard to online learning, delivery and evaluation. This paper discusses design education from an online learning perspective. It proposes an integrated framework with three key components for online learning via VLE including an interactive delivery structure, communication channels, and learning evaluation. Additionally, the paper describes and evaluates how VLE sites for two design units were built based on an integrated framework and student learning experiences. The results indicate that online design education should be integrated with various educational values and functional features in a systematic manner, and requires designing learning evaluation protocols as part of learning activities and communicative forms within online-based learning sites.

Integrated literacies : every online player wins a prize

QUT Library’s model of learning support brings together academic literacy (study skills) and information literacy (research skills). The blended portfolio enables holistic planning and development, seamless services, connected learning resources and more authentic curriculum-embedded education. The model reinforces the Library’s strategic focus on learning service innovation and active engagement in teaching and learning. ----- ----- ----- The online learning strategy is a critical component of the broader literacies framework. This strategy unifies new and existing online resources (e.g.: Pilot, QUT cite|write and IFN001|AIRS Online) to augment learner capability. Across the suite, prudent application of emerging technologies with visual communications and learning design delivers a wide range of adaptive study tools. Separately and together, these resources meet the learning needs and styles of a diverse cohort providing positive and individual learning opportunities. Deliberate articulation with strategic directions regarding First Year Experience, assessment, retention and curriculum alignment assures that the Library’s initiatives move in step with institutional objectives relating to enhancing the student experience and flexible blended learning. ----- ----- ----- The release of Studywell in 2010 emphasises the continuing commitment to blended literacy education. Targeting undergraduate learners (particularly 1st year/transition), this online environment provides 24/7 access to practical study and research tools. Studywell’s design and application of technology creates a “discovery infrastructure” [1] which facilitates greater self-directed learning and interaction with content. ----- ----- ----- This paper presents QUT Library’s online learning strategy within the context of the parent “integrated literacies” framework. Highlighting the key online learning resources, the paper describes the inter-relationships between those resources to develop complementary literacies. The paper details broad aspects of the overarching learning and study support framework as well as the online strategy, including strategic positioning, quality and evaluation processes, maintenance, development, implementation, and client engagement and satisfaction with the learning resources.

The impact of online reviews on hotel booking intentions and trust

A growing reliance on the Internet as an information source when making choices about tourism products raises the need for more research into electronic word of mouth. Within a hotel context, this study explores the role of four key factors that influence perceptions of trust and consumer choice. An experimental design is used to investigate four independent variables: the target of the review (core or interpersonal); overall valence of a set of reviews (positive or negative); framing of reviews (what comes first: negative or positive information); and whether or not a consumer generated numerical rating is provided together with the written text. Consumers seem to be more influenced by early negative information, especially when the overall set of reviews is negative. However, positively framed information together with numerical rating details increases both booking intentions and consumer trust. The results suggest that consumers tend to rely on easy-to-process information, when evaluating a hotel based upon reviews. Higher levels of trust are also evident when a positively framed set of reviews focused on interpersonal service.

A survey on the relationship between trust and interest similarity in online social networks

A remarkable growth in quantity and popularity of online social networks has been observed in recent years. There is a good number of online social networks exists which have over 100 million registered users. Many of these popular social networks offer automated recommendations to their users. This automated recommendations are normally generated using collaborative filtering systems based on the past ratings or opinions of the similar users. Alternatively, trust among the users in the network also can be used to find the neighbors while making recommendations. To obtain the optimum result, there must be a positive correlation exists between trust and interest similarity. Though the positive relations between trust and interest similarity are assumed and adopted by many researchers; no survey work on real life people’s opinion to support this hypothesis is found. In this paper, we have reviewed the state-of-the-art research work on trust in online social networks and have presented the result of the survey on the relationship between trust and interest similarity. Our result supports the assumed hypothesis of positive relationship between the trust and interest similarity of the users.

Managing Trust in Online Social Networks

In recent years, there is a dramatic growth in number and popularity of online social networks. There are many networks available with more than 100 million registered users such as Facebook, MySpace, QZone, Windows Live Spaces etc. People may connect, discover and share by using these online social networks. The exponential growth of online communities in the area of social networks attracts the attention of the researchers about the importance of managing trust in online environment. Users of the online social networks may share their experiences and opinions within the networks about an item which may be a product or service. The user faces the problem of evaluating trust in a service or service provider before making a choice. Recommendations may be received through a chain of friends network, so the problem for the user is to be able to evaluate various types of trust opinions and recommendations. This opinion or recommendation has a great influence to choose to use or enjoy the item by the other user of the community. Collaborative filtering system is the most popular method in recommender system. The task in collaborative filtering is to predict the utility of items to a particular user based on a database of user rates from a sample or population of other users. Because of the different taste of different people, they rate differently according to their subjective taste. If two people rate a set of items similarly, they share similar tastes. In the recommender system, this information is used to recommend items that one participant likes, to other persons in the same cluster. But the collaborative filtering system performs poor when there is insufficient previous common rating available between users; commonly known as cost start problem. To overcome the cold start problem and with the dramatic growth of online social networks, trust based approach to recommendation has emerged. This approach assumes a trust network among users and makes recommendations based on the ratings of the users that are directly or indirectly trusted by the target user.

Team role preference and online role play

Role play approaches have been used in online environments in an effort to create a mix of contested ideas and to promote participant engagement. While it is recognised that there is an aspect of ‘fun’ associated with role play there is a need to understand role assignment more rigorously than simply levels of reported participation and enjoyment. It is the contention of this paper that individuals are unlikely to be able to authentically play a role and, that in fact, there may be little purpose to contrived roles. Additionally, the literature has widely reported that personality factors, such as introversion and extroversion continue to be of significance in the way that individuals contribute in online contexts. The findings in the study reported in this paper confirm that introversion and extroversion do, indeed, play a role in the way individuals contribute in online environments. Thus, this paper argues that an active consideration needs to be given to individuals preferred (or natural) way of working even where use is made of online role play.

Challenges of tracking topical discussion networks online

Attempts to map online networks, representing relationships between people and sites, have covered sites including Facebook, Twitter, and blogs. However, the predominant approach of static network visualization, treating months of data as a single case rather than depicting changes over time or between topics, remains a flawed process. As different events and themes provoke varying interactions and conversations, it is proposed that case-by-case analysis would aid studies of online social networks by further examining the dynamics of links and information flows. This study uses hyperlink analysis of a population of French political blogs to compare connections between sites from January to August 2009. Themes discussed in this period were identified for subsequent analysis of topic-oriented networks. By comparing static blogrolls with topical citations within posts, this research addresses challenges and methods in mapping online networks, providing new information on temporal aspects of linking behaviors and information flows within these systems.

Blackboard as an online learning environment : what do teacher education students and staff think?

Abstract: As online learning environments now have an established presence in higher education we need to ask the question: How effective are these environments for student learning? Online environments can provide a different type of learning experience than traditional face-to-face contexts (for on-campus students) or print-based materials (for distance learners). This article identifies teacher education student and staff perceptions of teaching and learning using the online learning management system, Blackboard. Perceptions of staff and students are compared and implications for teacher education staff interested in providing high quality learning environments within an online space are discussed.

Online environmental information systems

In today’s information society, electronic tools, such as computer networks for the rapid transfer of data and composite databases for information storage and management, are critical in ensuring effective environmental management. In particular environmental policies and programs for federal, state, and local governments need a large volume of up-to-date information on the quality of water, air, and soil in order to conserve and protect natural resources and to carry out meteorology. In line with this, the utilization of information and communication technologies (ICTs) is crucial to preserve and improve the quality of life. In handling tasks in the field of environmental protection a range of environmental and technical information is often required for a complex and mutual decision making in a multidisciplinary team environment. In this regard e-government provides a foundation of the transformative ICT initiative which can lead to better environmental governance, better services, and increased public participation in environmental decision- making process.

Online urban information systems

Countless factors affect the inner workings of a city, so in an attempt to gain an understanding of place and making sound decisions, planners need to utilize decision support systems (DSS) or planning support systems (PSS). PSS were originally developed as DSS in academia for experimental purposes, but like many other technologies, they became one of the most innovative technologies in parallel to rapid developments in software engineering as well as developments and advances in networks and hardware. Particularly, in the last decade, the awareness of PSS have been dramatically heightened with the increasing demand for a better, more reliable and furthermore a transparent decision-making process (Klosterman, Siebert, Hoque, Kim, & Parveen, 2003). Urban planning as an act has quite different perspective from the PSS point of view. The unique nature of planning requires that spatial dimension must be considered within the context of PSS. Additionally, the rapid changes in socio-economic structure cannot be easily monitored or controlled without an effective PSS.