Laura M. Koehly

Validation of the modified Fagerstrom Tolerance Questionnaire with salivary cotinine among adolescents

This study was conducted to gain evidence of validity for a nicotine dependence measure for adolescent smokers. We hypothesized that the individual item responses and the total Fagerström Tolerance Questionnaire (FTQ) score would be positively correlated with cotinine values. We examined the relationship between a seven-item modified FTQ and saliva continine among 131 adolescent volunteers in a smoking cessation program. As anticipated, the total FTQ score was related to saliva cotinine (r = .40, p < .01), as were six of the seven individual FTQ items (p < .05). Our findings provide preliminary evidence that the modified FTQ scale is valid and applicable to adolescent smokers.

How families communicate about HNPCC genetic testing: Findings from a qualitative study

Little is known about how hereditary nonpolyposis colon cancer (HNPCC) genetic counseling and testing information is communicated within at‐risk families. This article describes findings from a qualitative study of 39 adult members from five families with known HNPCC‐predisposing mutations. We evaluated how information from HNPCC genetic counseling and testing was disseminated in these families and how family members reacted to and acted on this information. We included family members who had been diagnosed with an HNPCC syndrome cancer, unaffected individuals who were at 50% risk of carrying a mutation, and their spouses. Participants included those who had undergone testing and those who had not. In general, all families had shared the news about an HNPCC mutation with at‐risk relatives. Communication about HNPCC genetic counseling and testing followed the norms used for conveying other nonurgent family news. Mutation noncarriers, nontesters, and those who were not biological relatives were less involved in discussing genetic counseling and testing and perceived these processes as less relevant to them. Although all family members were generally willing to share information about HNPCC, probands and mutation carriers informed extended family members and actively persuaded others to seek counseling or testing. Family members who were persuaded to seek those services by the proband were more likely to have counseling and testing and were more likely to seek those services sooner. Genetic counseling should attempt to identify the existing communication norms within families and ways that family members can take an active role in encouraging others to learn about their cancer risk and options for testing. Interventions may also need to emphasize the relevance of hereditary cancer information beyond the immediate family and to unaffected family members who may be central to the communication process (e.g., spouses of mutation carriers).

Gender differences in chronic disease risk behaviors through the transition out of high school.

BACKGROUNDnMajor life transitions (e.g., graduation from high school) are times when many changes occur in a persons social and physical environment. Men and women likely experience aspects of these changes differently. As a result, health-related behaviors likely change at these times with possible differences in these changes by gender.nnnMETHODSnGender differences in the performance of chronic disease risk-related behaviors (fruit, juice, and vegetable intake; physical activity; tobacco and alcohol use; and sexual practices) through the transition out of high school (HS) were assessed in a secondary analysis of a nationally representative sample from the 1992 National Health Interview Survey-Youth Risk Behavior Survey. The survey was completed by 5881 young people aged 14 to 21 years. Regression discontinuity analysis with piecewise regression was performed.nnnRESULTSnStatistically significant gender by transition effects were obtained for exercise/physical activity (decreases at the transition point for males), snuff use (decrease for females in HS), binge drinking and number of days drinking alcohol (increases for males at the transition point), and use of alcohol or drugs before sexual intercourse (decrease for females post HS). Fruit intake decreased for males and females and daily and heavy cigarette smoking increased during the HS years. Effect sizes were small but promising, given that the data set was not designed to test this hypothesis.nnnCONCLUSIONnThese data offer evidence of differences by gender in chronic disease risk behaviors through the HS transition. Longitudinal studies are needed to assess the true nature of these differences, the tracking of these risk behaviors and their personal, social, and environmental determinants, including gender-specific determinants, that may explain these changes and inform future intervention development.

Smoking withdrawal and relapse in head and neck cancer patients.

Smoking withdrawal and relapse were characterized among newly diagnosed head and neck cancer patients participating in a physician‐delivered smoking cessation intervention.

Linear Discriminant Analysis versus Logistic Regression: A Comparison of Classification Errors in the Two-Group Case.

Abstract Classification studies are important for practitioners who need to identify individuals for specialized treatment or intervention. When interventions are irreversible or misclassifications are costly, information about the proficiency of different classification procedures becomes invaluable. This study furnishes information about the relative accuracy of two widely used classification procedures, linear discriminant analysis and logistic regression, under various commonly encountered and interacting conditions. Monte Carlo simulation was used to manipulate four factors under multivariate normality: equality of covariance matrices, degree of group separation, sample size, and prior probabilities. Three criterion measures were employed: total, small-group, and large-group classification error. Interactions of these between factors with two within factors, cut-score and method of classification, were of primary interest.

Social Network Analysis: A New Methodology for Counseling Research.

Social network analysis (SNA) is a set of procedures that use indices of relatedness among individuals to produce representations of social structures and positions inherent in dyads or groups. This approach differs from traditional research strategies in that the focus is on developing an understanding of the ongoing transactions and the implications of transactional patterns between individuals, groups, or other social units. Although the primary emphasis in SNA is on the social context, network analysts also include traditional individual-differences variables as potential explanatory factors. SNA methods provide the means to derive a more complete view of a given social environment. A group-psychotherapy example is used to provide an overview of SNA, introducing the concepts, notation, and statistical methods used by the current generation of network researchers. Methodological issues are discussed, applications are reviewed, and resources are recommended for those wishing to learn more about SNA.

Exponential Family Models for sampled and census Network data

Much progress has been made on the development of statistical methods for network analysis in the past ten years, building on the general class of exponential family random graph (ERG) network models first introduced by Holland and Leinhardt (1981). Recent examples include models for Markov graphs, “p*” models, and actor-oriented models. For empirical application, these ERG models take a logistic form, and require the equivalent of a network census: data on all dyads within the network. In a largely separate stream of research, conditional log-linear (CLL) models have been adapted for analyzing locally sampled (“egocentric”) network data. While the general relation between log-linear and logistic models is well known and has been exploited in the case of a priori blockmodels for networks, the relation for the CLL models is different due to the treatment of absent ties. For fully saturated tie independence models, CLL and ERG are equivalent and related via Bayes rule. For other tie independence models, the two do not yield equivalent predicted values, but we show that in practice the differences are unlikely to be large. The alternate conditioning in the two models sheds light on the relationship between local and complete network data, and the role that models can play in bridging the gap between them.

Other Multivariate Techniques

I would like to hear comments from more experienced experimental researchers about standard practices for recruiting and compensating participants in consumer and marketing experiments. What are the pros and cons of using student participants? (I know there was a debate about this in the literature a few years ago, but what is the current prevailing opinion?) Is there a difference between using undergraduate students (business majors or nonbusiness majors) and graduate students? When using student participants, is it better to compensate them with extra course credit or to pay them? And, is one time of the semester or quarter (i.e., beginning, middle, or end) preferable for using student participants? I am especially interested to know if anyone has conducted a systematic study of these last two issues. I have recently run experiments using student samples from the same population, but paying one sample and giving extra credit to the other, which definitely affected the rate at which students showed up for their assigned sessions. It may also have affected the variance in the quality of students that chose to participate. Also, in an experiment that I recently ran at the end of a semester (during the last week and a half of class meetings before the final exam week), I collected informal statements from participants in debriefing sessions that indicated that they were no busier or more distracted than they would have been in the middle of the semester. Also, what are the standard practices for recruiting and compensating nonstudent participants (e.g., ordinary folks off the street)? And, for experimental marketing and organizational research (on which I am presently embarking), what are the equivalent standards for industry-based samples (i.e., executives, managers, executive MBA students)? (This information is critical for budgeting grant proposals. I recently called the National Science Foundation and they could not offer much help on this point.) Also, does anyone have any great suggestions for increasing our success rate for getting such populations to participate in experimental research? I was discouraged by a recent conversation with George Day and David Montgomery, who said that even they are finding it increasingly difficult to recruit managerial research participants in the executive courses at the Wharton School and Stanford University. (So, where does that leave the rest of us?) Professor Prashant Malaviya University of Illinois at ChicagoIn the spring of 1990, the Hubble Space Telescope was put into orbit, the culmination of work by a multitude of astronomers, engineers, technicians, and researchers over a period of many years. Its proponents hail it as a key tool to understanding the universe, while its critics write it off as a monumental waste of resources that will never fulfill the expectations of those who designed it. Almost immediately after it went on-line, concern arose about the robustness of its inner workings, yet the demand for access to this device is immense.This special issue poses anonymous questions, then provides the answers and a discussion of the issues by the expert who responded. The answers are not anonymous--partly to give credit to the experts and partly to encourage future communication and debate on whatever lingering controversies may arise. After a number of questions, the special issue concludes with a discussion by the guest editor that summarizes the answers and provides straightforward answers to questions that were not addressed by the experts.