The role of illness uncertainty on coping with fibromyalgia symptoms.

This study examined the role of illness uncertainty in pain coping among women with fibromyalgia (FM), a chronic pain condition of unknown origin. Fifty-one FM participants completed initial demographic and illness uncertainty questionnaires and underwent 10-12 weekly interviews regarding pain, coping difficulty, and coping efficacy. Main outcome measures included weekly levels of difficulty coping with FM symptoms and coping efficacy. Multilevel analyses indicated that pain elevations for those high in illness uncertainty predicted increases in coping difficulty. Furthermore, when participants had more difficulty coping, they reported lower levels of coping efficacy. Results were consistent with hypothesized effects. Illness uncertainty accompanied by episodic pain negatively influenced coping efficacy, an important resource in adaptation to FM.     

A measurement model of women's behavioral risk taking.

The current study was designed to gain a better understanding of the nature of the relationship between substance use and sexual risk taking within a community sample of women (N = 1,004). Using confirmatory factor analysis, the authors examined the factor structure of sexual risk behaviors and substance use to determine whether they are best conceptualized as domains underlying a single, higher order, risk-taking propensity. A 2 higher order factor model (sexual risk behavior and substance use) provided the best fit to the data, suggesting that these 2 general risk domains are correlated but independent factors. Sensation seeking had large general direct effects on the 2 risk domains and large indirect effects on the 4 first-order factors and the individual indicators. Negative affect had smaller, yet still significant, effects. Impulsivity and anxiety were unrelated to sexual health risk domains.     

The Utility of Problem-solving Training that Emphasises Selfmanagement Principles

This study examined the usefulness of an 8-week applied problem-solving training program. Specifically, the study examined (a) whether problem-solving training that emphasised self-management principles would be useful, (b) if the effects of training would persist over time, (c) whether an individual difference variable (problem-solving appraisal) would affect training outcomes, and (d) whether the cognitive responses of the subjects during the course of training were related to their problem-solving appraisal or the change process. Results indicated that problem solving training was effective at enhancing students’ problem-solving appraisal, and that the self-report changes were maintained at a 1 year follow-up. In particular, training seemed most useful for students who initially appraised their problem solving very negatively. Finally, the results suggested that the process-oriented cognitive responses were related to students' initial problem-solving self-appraisal as well as the impact of training. Implications of the results are discussed in terms of counselling interventions, problem solving training, the interpersonal influence process, and future research.     

Genetics and adoption: Forming a partnership

Genetic issues are demanding more attention in the area of public health. Adoption agencies and policymakers are beginning to address these issues where they relate to the adoption process and to the many families involved in adoption in this country. Genetic counselors need to play an active role as both educators of and consultants for adoption professionals and the families with whom they work. To facilitate a partnership between genetics and adoption we have developed a workshop intended to educate adoption professionals about the lifelong implications of genetic conditions on the adoption triad.     

Statistical consistency and hypothesis testing for nonmetric multidimensional scaling

The properties of nonmetric multidimensional scaling (NMDS) are explored by specifying statistical models, proving statistical consistency, and developing hypothesis testing procedures. Statistical models with errors in the dependent and independent variables are described for quantitative and qualitative data. For these models, statistical consistency often depends crucially upon how error enters the model and how data are collected and summarized (e.g., by means, medians, or rank statistics). A maximum likelihood estimator for NMDS is developed, and its relationship to the standard Shepard-Kruskal estimation method is described. This maximum likelihood framework is used to develop a method for testing the overall fit of the model.