Evaluating depression severity and remission with a modified Beck Depression Inventory

In an attempt to improve assessment of recovery from depression, a modified Beck Depression Inventory (mBDI) was created that permits endorsement of positive feelings in addition to depressive symptoms. In both normal and clinical samples, the mBDI showed evidence of reliability for measuring varying degrees of depression. In comparison to the original BDI, the mBDI did not significantly improve differentiation in depression severity among depressed individuals and assessment of remission of depressive symptoms. However, the mBDI was significantly better than the original BDI in detecting differences in depression level when overall depression severity was low. Clinical implications for evaluating remission of depression are discussed.     

To Use or Not to Use: The Prenatal Genetic Technology/Worry Conundrum

We conducted an exploratory, qualitative study investigating the factors influencing the use of genetic counseling and prenatal genetic testing for two groups: pregnant women 35 years of age and over (AMA) at the time of delivery and pregnant women with an abnormal maternal serum triple screen (MSAFP3). The convenience sample consisted of 25 semistructured interviews of women/couples and 50 observations of genetic counseling sessions. Worry turned out to be the most important variable influencing decision making about prenatal genetic testing and was greater in the MSAFP3 group than in the AMA group. The women in the AMA group appeared to assign the risk of having a child with Down syndrome to their age category rather than to themselves individually, whereas, the risk perception for women with an abnormal MSAFP3 appeared to have shifted from a general population risk for pregnant women to an individual, personal risk. There was a general lack of understanding and also more misinformation about the MSAFP3 screen compared to amniocentesis. Women in both groups were torn between fear of an invasive test and worry about the health of their fetus for the rest of their pregnancy if they did not undergo amniocentesis.     

The study of early emotion processing in the frontal area using a two-dipole source model

The present study explored early emotion processing in the frontal area using the two-dipole source model. The 21-channel recordings of event-related potentials (ERPs) produced by a pure tone were analyzed in order to assess information processing. In the test conditions, the pure tone followed the presentation of one of two unpleasant sounds to enhance anxiety. In the control condition, only the pure tone was presented. There were two groups of eight subjects, one with low scores for trait anxiety and one with high scores. The ERPs were separately averaged for the groups, as well as for the high- and low-anxiety sound and control session. A negative peak around 120 ms (C2) and a positive peak around 280 ms (C5) after stimulus onset were identified in all the sessions. The two-dipole source model was applied to these two components. In the C2 component, dipole sources were located in the left frontal area in the control sessions, and in the right frontal area in the high-anxiety sessions. This activation pattern was clearer in the group with low trait anxiety. In contrast, with the C5 component, lateralization of the dipole source in the frontal area was not seen. These findings suggest that the frontal area is involved in early emotion processing. A dual-stage model of emotion processing is therefore proposed.     

Initial excitatory conditioning with the truly random control procedure in rats: The effects of density of the conditioned stimulus

The present experiments were designed to test whether initial excitatory conditioning to a stimulus was obtained, using a within-subject design of the truly random control (TRC) procedure, and to examine the effects of the density of the conditioned stimulus on it. In Experiment 1, the effect of the three levels of CS density (50%, 25%, 20%) was assessed at six different stages of training, using the conditioned suppression of licking in rats. Although all of the groups given the TRC procedure showed evidence of initial excitatory conditioning, it was more marked in the group with the highest CS density than in the other groups. Experiment 2 confirmed the results of Experiment 1, using a between-subject design. The findings are in line with predictions from the Rescorla-Wagner model, and are discussed with reference to other contemporary theories of associative learning.     

Stepwise variable selection in factor analysis

It is very important to choose appropriate variables to be analyzed in multivariate analysis when there are many observed variables such as those in a questionnaire. What is actually done in scale construction with factor analysis is nothing but variable selection.In this paper, we take several goodness-of-fit statistics as measures of variable selection and develop backward elimination and forward selection procedures in exploratory factor analysis. Once factor analysis is done for a certain numberp of observed variables (thep-variable model is labeled the current model), simple formulas for predicted fit measures such as chi-square, GFI, CFI, IFI and RMSEA, developed in the field of the structural equation modeling, are provided for all models obtained by adding an external variable (so that the number of variables isp + 1) and for those by deleting an internal variable (so that the number isp – 1), provided that the number of factors is held constant.A programSEFA (Stepwise variable selection in Exploratory Factor Analysis) is developed to actually obtain a list of the fit measures for all such models. The list is very useful in determining which variable should be dropped from the current model to improve the fit of the current model. It is also useful in finding a suitable variable that may be added to the current model. A model with more appropriate variables makes more stable inference in general.The criteria traditionally often used for variable selection is magnitude of communalities. This criteria gives a different choice of variables and does not improve fit of the model in most cases.The URL of the programSEFA is http://koko15.hus.osaka-u.ac.jp/~harada/factor/stepwise/.     

The weighted oblimin rotation

Cureton & Mulaik (1975) proposed the Weighted Varimax rotation so that Varimax (Kaiser, 1958) could reach simple solutions when the complexities of the variables in the solution are larger than one. In the present paper the weighting procedure proposed by Cureton & Mulaik (1975) is applied to Direct Oblimin (Clarkson & Jennrich, 1988), and the rotation method obtained is called Weighted Oblimin. It has been tested on artificial complex data and real data, and the results seem to indicate that, even though Direct Oblimin rotation fails when applied to complex data, Weighted Oblimin gives good results if a variable with complexity one can be found for each factor in the pattern. Although the weighting procedure proposed by Cureton & Mulaik is based on Landahl's (1938) expression for orthogonal factors, Weighted Oblimin seems to be adequate even with highly oblique factors. The new rotation method was compared to other rotation methods based on the same weighting procedure and, whenever a variable with complexity one could be found for each factor in the pattern, Weighted Oblimin gave the best results. When rotating a simple empirical loading matrix, Weighted Oblimin seemed to slightly increase the performance of Direct Oblimin.The author is obliged to Henk A. L. Kiers and three anonymous reviewers for helpful comments on an earlier version of this paper.     

Optimal scaling by alternating length-constrained nonnegative least squares, with application to distance-based analysis

An important feature of distance-based principal components analysis, is that the variables can be optimally transformed. For monotone spline transformation, a nonnegative least-squares problem with a length constraint has to be solved in each iteration. As an alternative algorithm to Lawson and Hanson (1974), we propose the Alternating Length-Constrained Non-Negative Least-Squares (ALC-NNLS) algorithm, which minimizes the nonnegative least-squares loss function over the parameters under a length constraint, by alternatingly minimizing over one parameter while keeping the others fixed. Several properties of the new algorithm are discussed. A Monte Carlo study is presented which shows that for most cases in distance-based principal components analysis, ALC-NNLS performs as good as the method of Lawson and Hanson or sometimes even better in terms of the quality of the solution. Supported by The Netherlands Organization for Scientific Research (NWO) by grant nr. 030-56403 for the “PIONEER” project “Subject Oriented Multivariate Analysis” to the third author. We would like to thank the anonymous referees for their valuable remarks that have improved the quality of this paper.     

The typical rank of tall three-way arrays

The rank of a three-way array refers to the smallest number of rank-one arrays (outer products of three vectors) that generate the array as their sum. It is also the number of components required for a full decomposition of a three-way array by CANDECOMP/PARAFAC. The typical rank of a three-way array refers to the rank a three-way array has almost surely. The present paper deals with typical rank, and generalizes existing results on the typical rank ofI × J × K arrays withK = 2 to a particular class of arrays withK ≥ 2. It is shown that the typical rank isI when the array is tall in the sense thatJK − J < I < JK. In addition, typical rank results are given for the case whereI equalsJK − J. The author is obliged to Henk Kiers, Tom Snijders, and Philip Thijsse for helpful comments.     

Single Session Treatment of Test Anxiety with Eye Movement Desensitization and Reprocessing (EMDR)

One session of Eye Movement Desensitization and Reprocessing (EMDR) appeared to be an effective treatment for test anxiety, reducing reported physiological distress, worry, and fears of negative evaluation. The research design included two components: a comparison study, comparing Immediate Treatment and Wait List groups, and a replication study, comparing the treatment response of Immediate and Delayed (Treated Wait List) groups. Seventeen test anxious university students were randomly assigned to one session of EMDR or Wait List. At post-test, the Immediate group demonstrated significant improvement, compared to the Wait List group, on the Test Anxiety Inventory (TAI) and Fear of Negative Evaluation Scale. Treatment effects were maintained at follow-up. The Wait List group received treatment after post-measures were taken. Treatment of the Delayed group replicated effects. Improvement was reflected by large treatment effect sizes and a decrease in percentile ranking on the TAI from the 90th to the 50th percentile.