Toward the development of an adolescent gambling problem severity scale

The development and initial psychometric properties of an adolescent gambling problem severity measure are described. The scale, based on a revision of the South Oaks Gambling Screen (Lesieur & Blume, 1987), was administered to 1,101 older (ages 15 to 18) Minnesota adolescents as part of a state-wide gambling survey. Study results indicated that the scale had moderate internal consistency reliability and was significantly related to alternate measures of problem severity for male subjects. Because the rate and severity of gambling among females was very low, the psychometric adequacy of the scale for females is not known at this time. The implications of study findings to the conceptual understanding of adolescent gambling problem severity as well as study limitations and future research needs, are discussed.Support for the study was provided by the Minnesota Department of Human Services and the Center for Addiction Studies, University of Minnesota, Duluth. The authors gratefully acknowledge the assistance from Robert Blum, Linda Harris, Durand Jacobs, J. Laundergan, Alan Mathiason, Brenda Miller, James Schaefer, school officials from the participating high schools, and interviewers who assisted with the telephone survey.     

A Comparison of Partially Adaptive and Reweighted Least Squares Estimation

The small sample performance of least median of squares, reweighted least squares, least squares, least absolute deviations, and three partially adaptive estimators are compared using Monte Carlo simulations. Two data problems are addressed in the paper: (1) data generated from non-normal error distributions and (2) contaminated data. Breakdown plots are used to investigate the sensitivity of partially adaptive estimators to data contamination relative to RLS. One partially adaptive estimator performs especially well when the errors are skewed, while another partially adaptive estimator and RLS perform particularly well when the errors are extremely leptokur-totic. In comparison with RLS, partially adaptive estimators are only moderately effective in resisting data contamination; however, they outperform least squares and least absolute deviation estimators.     

Sources of family violence

This paper suggests a direction for the exploration of the causes of family violence. Explanatory models of family violence were considered in this regard, with the recommendation that a multi-determined model should be considered to ensure the most accurate explanation. We suggest that family violence will be best understood and prevented or alleviated, if a model is used that considers the interaction of structural violence and the personality features of all the family members.     

An exploratory study of gambling cross addictions

A growing body of empirical and theoretical research has concentrated on the overlaps and commonalities among chemical and non-chemical (behavioural) addictions. Pathological gambling has perhaps been the most widely researched behavioural addiction and some of this research has concerned the co-existing links between pathological gambling and alcohol/drug addiction in both the gambling substance abuser and the substance abusing gambler (i.e. cross addiction). This study was of an exploratory nature and attempted to gather information and data regarding gambling cross addictions in the UK. To achieve this, 456 letters were sent to all drug and alcohol helping agencies in England requesting such information. This yielded 210 returns (46% response rate). Results indicated that gambling cross addictions occur in both adults and adolescents and were almost exclusively a male condition. However, it must be noted only just over half of the responding agencies had encountered gambling cross addiction and reasons for this are speculated. Results also indicated the existence of various cross addicted subgroups including an adolescent subgroup who were addicted to fruit machines and abused solvents. Future research ideas are also discussed.A more detailed version of this paper is available from the author on request.     

On the existence and uniqueness of maximizers of two likelihood functions

While applying theclassical maximum likelihood method for a certain statistical inference problem, Smith and Weissman [5] have noted that there are conditions under which the likelihood function may be unbounded above or may not possess local maximizers. Ariyawansà and Templeton [1] have derived inference procedures for this problem using the theory of structural inference [2,3,4]. Based on numerical experience, and without proof, they state that the resulting likelihood functions possess unique, global maximizers, even in instances where the classical maximum likelihood method fails in the above sense. In this paper, we prove that under quite mild conditions, these likelihood functions that result from the application of the theory of structural inference are well-behaved, and possess unique, global maximizers. This research was supported in part by the Applied Mathematical Sciences subprogram of the U.S. Department of Energy under contract W-31-109-Eng-38 while the author was visiting the Mathematics and Computer Science Division of Argonne National Laboratory, Argonne, Illinois.     

Sampling Strategies for Toxic Air Contaminants

Annual concentrations of toxic air contaminants are of primary concern from the perspective of chronic human exposure assessment and risk analysis. Despite recent advances in air quality monitoring technology, resource and technical constraints often impose limitations on the availability of a sufficient number of ambient concentration measurements for performing environmental risk analysis. Therefore, sample size limitations, representativeness of data, and uncertainties in the estimated annual mean concentration must be examined before performing quantitative risk analysis. In this paper, we discuss several factors that need to be considered in designing field-sampling programs for toxic air contaminants and in verifying compliance with environmental regulations. Specifically, we examine the behavior of SO2, TSP, and CO data as surrogates for toxic air contaminants and as examples of point source, area source, and line source-dominated pollutants, respectively, from the standpoint of sampling design. We demonstrate the use of bootstrap resampling method and normal theory in estimating the annual mean concentration and its 95% confidence bounds from limited sampling data, and illustrate the application of operating characteristic (OC) curves to determine optimum sample size and other sampling strategies. We also outline a statistical procedure, based on a one-sided t-test, that utilizes the sampled concentration data for evaluating whether a sampling site is compliance with relevant ambient guideline concentrations for toxic air contaminants.     

The Independence of Aptitudes,Interests, and Career Beliefs

The importance of client beliefs in career counseling depends on their ability to add unique information about the client over and above that contributed by aptitudes and interests. The Career Beliefs Inventory was administered to 200 Australian students in grade 10 together with measures of Holland's RIASEC interest themes and scholastic aptitudes. The correlations between scales from the three domains showed clearly that beliefs made a contribution distinct from that provided by aptitudes and interests. Even though the results may reflect possible sampling or method variance, career beliefs in this sample added unique information to that traditionally used in career counseling.