Investigating the Dynamics of Migration and Health in Australia: A Longitudinal Study

There have been few longitudinal studies investigating the immigrant health and changes in their health with longer residency in the host country. Additionally, the pathways and mechanisms by which transition of health over time occurs are poorly understood, limiting the ability to implement policies that will result in improved health for all, including immigrants. We assessed differences in health outcomes among foreign-born people from English speaking countries and non-English speaking countries relative to native-born Australians over a 10-year period using a large representative longitudinal dataset. We also explored English language proficiency, socio-economic factors and health behaviour factors as possible mechanisms through which health outcomes change over time post-migration. Conventional multilevel mixed and hybrid regression models were used to evaluate health outcomes in 9558 native-born and 3067 foreign-born people from the Household, Income and Labour Dynamics in Australia survey. There were clear differences in physical health, mental health and self-assessed health between foreign-born subgroups in comparison with native-born Australians. Foreign-born people from English speaking countries typically had a health advantage relative to native-born people, and foreign-born people from non-English speaking countries had a health disadvantage with respect to native-born people for all health outcomes. There was no evidence that these differences changed by duration of residence except for self-assessed health amongst foreign-born people from non-English speaking countries when duration of residence exceeded 20 years. English language proficiency mediated the relationship between duration of residence and health for foreign-born people from non-English speaking countries.     

Second‐order bias‐corrected AIC in multivariate normal linear models under non‐normality

This paper deals with a bias correction of Akaike's information criterion (AIC) for selecting variables in multivariate normal linear regression models when the true distribution of observation is an unknown non‐normal distribution. It is well known that the bias of AIC is $O(1)$ , and there are a number of the first‐order bias‐corrected AICs which improve the bias to $O(n^{-1})$ , where $n$ is the sample size. A new information criterion is proposed by slightly adjusting the first‐order bias‐corrected AIC. Although the adjustment is achieved by merely using constant coefficients, the bias of the new criterion is reduced to $O(n^{-2})$ . Then, a variance of the new criterion is also improved. Through numerical experiments, we verify that our criterion is superior to others. The Canadian Journal of Statistics 39: 126–146; 2011 © 2011 Statistical Society of Canada     

An Application of Expectancy Theory to Explain a Manager's Intention to Use a Decision Support System

A continuing gap exists between the capabilities of sophisticated computer-based information systems and the extent to which these systems are used by individuals. Studies which have examined the relationship between system utilization and various user, system, implementation, and organizational variables have provided few consistent findings. A new approach to this topic is suggested by a recent study by Davis, Bagozzi, and Warshaw [11], which indicates that individuals' intentions to use a system determine subsequent use. A large body of psychology-based research also supports this relationship between behavioral intentions and subsequent behavior. This study employs expectancy theory, which has often been used to examine behavioral intentions, to explain managers' intentions to use a decision support system (DSS). The results imply that the variables of the expectancy force model are determinants of a manager's behavioral intentions to use a DSS, and the variables of the expectancy valence model are determinants of the attractiveness of using a DSS to a manager.     

Socio-economic inequalities in mortality for Asian people: New Zealand Census-Mortality Study, 1996–2004

Journal of Population Research - This study examines the association of socio-economic factors with mortality for the Asian population, and compares with those of the European/Other group....     

The Extraction of Nonverbal Behaviors: Using Video Images and Speech-Signal Analysis in Dyadic Conversation

This study examined the validity and possible utility of a new procedure for the extraction of nonverbal behaviors from dyadic conversation. Three methods were used to extract nonverbal behaviors (i.e., hand gestures, adaptors, and utterances). A novel automated method employing video images and speech-signal analysis software programs was compared to the more traditional coding and behavioral rating methods. The automated and coding methods provided an objective count of how many times a target behavior occurred, while behavioral ratings were based on more subjective impressions. Although there was no difference between the automated and coding methods for hand gestures, the coding method using an event recorder yielded marginally significantly more instances of adaptors and utterances as compared to the software programs. Measures of each nonverbal behavior were positively correlated across the different methods. In addition, interpersonal impressions of each speaker were rated by both observers and conversational partners. Although R ² was lower than for the coding/behavioral rating methods, nonverbal behaviors extracted using the software programs significantly predicted familiarity and activeness ratings from both observer and partner points of view. These results support the validity and possible utility of the software-based automated extraction procedure.     

An age–period–cohort analysis of cancer incidence among the oldest old,Utah 1973–2002

We used age–period–cohort (APC) analyses to describe the simultaneous effects of age, period, and cohort on cancer incidence rates in an attempt to understand the population dynamics underlying their patterns among those aged 85+. Data from the Utah Cancer Registry (UCR), the US Census, the National Center for Health Statistics (NCHS), and the National Cancer Institute's Surveillance, Epidemiology and End Results (SEER) programme were used to generate age-specific estimates of cancer incidence at ages 65–99 from 1973 to 2002 for Utah. Our results showed increasing cancer incidence rates up to the 85–89 age group followed by declines at ages 90–99 when not confounded by the separate influences of period and cohort effects. We found significant period and cohort effects, suggesting the role of environmental mechanisms in cancer incidence trends between the ages of 85 and 100.     

Collegiate Recovery Communities Programs: What Do We Know and What Do We Need to Know?

As the broad construct of recovery increasingly guides addiction services and policy, federal agencies have called for the expansion of peer-driven recovery support services. The high prevalence of substance use and abuse in colleges and universities in the United States constitutes a significant obstacle to pursuing an education for the unknown number of youths who have attained remission from substance use dependence. Collegiate recovery programs (CRPs) are an innovative and growing model of peer-driven recovery support delivered on college campuses. Although no systematic research has examined CRPs, available site-level records suggest encouraging outcomes: low relapse rates and above-average academic achievement. The number of CRPs nationwide is growing, but there is a noticeable lack of data on the model, its students, and their outcomes. We review the literature supporting the need for the expansion of CRPs, present information on the diversity of CRP services, and outline key areas where research is needed.