Correlates of AUDIT Risk Status for Male and Female College Students

Abstract

Objective: The current study identified gender-specific correlates of hazardous drinker status as defined by the AUDIT. Participants: A total of 462 college student volunteers completed the study in 2006. The sample was predominantly Caucasian (75%) and female (55%). Methods: Participants completed a survey assessing demographics, alcohol use patterns, and health indices. Scores of 8 or more on the AUDIT defined the at-risk subsample. Logistic regression models determined which variables predicted AUDIT risk status for men and women. Results: The at-risk participants reported higher alcohol use and related problems, elevated sleep problems and lower health ratings. High typical blood alcohol concentration (BAC), lifetime drug use, and psychosocial problems predicted risk status for males. Binge frequency and psychosocial problems predicted risk status for females. Conclusions: Different behavioral profiles emerged for men and women identified as hazardous drinkers on the AUDIT. The efficacy of brief alcohol interventions could be enhanced by addressing these behavioral correlates.     

The photo‐survey research method: capturing life in the city

Recent promotion of city centre living within UK policy has led to a commensurate interest in city centre conditions and the opinions and experiences of the people who live there. An apposite, straightforward method to capture city centre residents' experiences and views is described in this article. We successfully combined a novel, under‐utilized visual technique (self‐directed photography) with qualitative methods (log‐sheets and interviews) in the form of a ‘photo‐survey’. A background to visual methodologies is presented in this article, alongside a critique of using the photo‐survey with 84 city centre residents to investigate environmental conditions and perceptions within three of the UK's major cities. The method provided a rich, detailed set of data, but also brought a number of noticeable benefits to the data collection process. The photo‐survey not only effectively captured and documented life in the city but also acted as an ‘agent for change’, evoking thoughts and feelings which ultimately encouraged participants to reflect on their existing perceptions and urban experiences. The study also raises some important considerations for future work undertaken with this method and with using photographs as a set of data, and proposes techniques for minimising potential problems.     

Social work through collaborative autoethnography

This paper discusses a research project involving five MA Social Work Students and one member of Social Work Academic Staff. Using narrative and taking a collaborative autoethnographical approach, this project highlights some of the feelings that students articulated following a 70-day placement experience. Findings include anxiety, powerlessness and frustration, together with growing confidence, recognition of their skills and a deeper understanding of the role of ‘self’ in social work. Raising issues of preparedness for practice placement, this paper has implications for both social work practice and social work education. Autoethnography (AE) is both a method of carrying out research and a methodology, specifically a qualitative methodology linked to ethnography and narrative inquiry. AE results in highly personalized narrative accounts of the researcher’s engagement with specific sociocultural contexts in the pursuit of knowing more about a phenomenon. Applying such a methodology to explore collaboratively issues of student lived experience of placement is a new and innovative use of this method.     

Health Behavior Change and the College Personal Health Class: A Multifaceted Approach

Abstract

Both the literature review and the results of a behavioral change project conducted at the University of Oregon indicate that health courses can bring about positive lifestyle changes when behavior is made a focus of the class. A multi-faceted behavioral intervention strategy was developed and used with 433 students enrolled in personal health classes during the fall term, 1983. At the end of the term, 23% of the students reported they were 100% successful in obtaining their desired behavioral changes. Another 40% reported they had just missed their goal. Overall, it appears the intervention was highly successful. More research is needed to validate the approach.     

The personalisation agenda: the case of the Australian National Disability Insurance Scheme

As part of the international trend towards personalisation, in 2013 Australia launched a major disability scheme aiming to give participants greater choice and control over services. The scheme aims to cover a wide diversity of disabilities, services and significant geographical area – resulting in a highly complex system of local overlapping markets. At four years into implementation a range of challenges have emerged. In this paper we firstly describe the Australian National Disability Insurance Scheme, then explore a range of implementation challenges it currently faces as a large-scale personalisation scheme. Based on these experiences we pose a range of questions for similar schemes internationally.     

Conditional Gaussian mixture modelling for dietary pattern analysis

Summary.  Free-living individuals have multifaceted diets and consume foods in numerous combinations. In epidemiological studies it is desirable to characterize individual diets not only in terms of the quantity of individual dietary components but also in terms of dietary patterns. We describe the conditional Gaussian mixture model for dietary pattern analysis and show how it can be adapted to take account of important characteristics of self-reported dietary data. We illustrate this approach with an analysis of the 2000–2001 National Diet and Nutrition Survey of adults. The results strongly favoured a mixture model solution allowing clusters to vary in shape and size, over the standard approach that has been used previously to find dietary patterns.     

A new family of random graphs for testing spatial segregation

The authors discuss a graph‐based approach for testing spatial point patterns. This approach falls under the category of data‐random graphs, which have been introduced and used for statistical pattern recognition in recent years. The authors address specifically the problem of testing complete spatial randomness against spatial patterns of segregation or association between two or more classes of points on the plane. To this end, they use a particular type of parameterized random digraph called a proximity catch digraph (PCD) which is based on relative positions of the data points from various classes. The statistic employed is the relative density of the PCD, which is a U‐statistic when scaled properly. The authors derive the limiting distribution of the relative density, using the standard asymptotic theory of U‐statistics. They evaluate the finite‐sample performance of their test statistic by Monte Carlo simulations and assess its asymptotic performance via Pitman's asymptotic efficiency, thereby yielding the optimal parameters for testing. They further stress that their methodology remains valid for data in higher dimensions.