Don't forget asking the others! - The added value of significant other's reports on patient interpersonal style for the prediction of therapy process and outcome

Theory: Interpersonal factors play a major role in causing and maintaining depression. It is unclear, however, to what degree significant others of the patient need to be involved for characterizing the patient's interpersonal style. Therefore, our study sought to investigate how impact messages as perceived by the patients' significant others add to the prediction of psychotherapy process and outcome above and beyond routine assessments, and therapist factors. Method: 143 outpatients with major depressive disorder were treated by 24 therapists with CBT or Exposure-Based Cognitive Therapy. Interpersonal style was measured pre and post therapy with the informant‐based Impact Message Inventory (IMI), in addition to the self‐report Inventory of Interpersonal Problems (IIP‐32). Indicators for the patients' dominance and affiliation as well as interpersonal distress were calculated from these measures. Depressive and general symptomatology was assessed at pre, post, and at three months follow‐up, and by process measures after every session. Results: Whereas significant other's reports did not add significantly to the prediction of the early therapeutic alliance, central mechanisms of change, or post‐therapy outcome including therapist factors, the best predictor of outcome 3 months post therapy was an increase in dominance as perceived by significant others. Conclusions: The patients' significant others seem to provide important additional information about the patients' interpersonal style and therefore should be included in the diagnostic process. Moreover, practitioners should specifically target interpersonal change as a potential mechanism of change in psychotherapy for depression.

Controlling for culture-specific response bias using ipsatization and response style indicators: Family orientation in seventeen cultures and two generations

Within-subject standardization (ipsatization) has been advocated as a possible means to control for culture-specific responding (e.g., Fisher, 2004). However, the consequences of different kinds of ipsatization procedures for the interpretation of mean differences remain unclear. The current study compared several ipsatization procedures with ANCOVA-style procedures using response style indicators for the construct of family orientation with data from 14 cultures and two generations from the Value-of-Children-(VOC)-Study (4135 dyads). Results showed that within-subject centering/standardizing across all Likert-scale items of the comprehensive VOC-questionnaire removed most of the original cross-cultural variation in family orientation and lead to a non-interpretable pattern of means in both generations. Within-subject centering/standardizing using a subset of 19 unrelated items lead to a decrease to about half of the original effect size and produced a theoretically meaningful pattern of means. A similar effect size and similar mean differences were obtained when using a measure of acquiescent responding based on the same set of items in an ANCOVA-style analysis. Additional models controlling for extremity and modesty performed worse, and combinations did not differ from the acquiescence-only model. The usefulness of different approaches to control for uniform response styles (scalar equivalence not given) in cross- cultural comparisons is discussed.

Promoting a low-noise driving style: An eco-driving intervention study

Road-traffic noise impairs the well-being and health of many people. Motivating car drivers to voluntarily adopt a low-noise driving style (i.e., eco-driving) contributes to the reduction of road-traffic noise, complementary to requirements, bans, and laws. In a field study with employees of a municipality (N = 88), we investigated the effects of an intervention on car drivers’ motivation to prevent road-traffic noise, motivation to practice eco-driving, and driving behavior. The intervention consisted of a leaflet intended to enhance participants’ motivation, a practical eco-driving course, and weekly driving-performance feedbacks. We used a switching-replications design with two intervention groups. In both groups, eco-driving behavior was significantly strengthened by the intervention. The effects on the motivational variables were significant in only one of the groups (however, it should be noted that the average motivation was already relatively high before the intervention). For one of the groups, the study design allowed testing for the effects at an additional follow-up assessment (4 months after the intervention). The results showed that the intervention effect on driving behavior held across this period. The findings of the present research suggest that it is possible to improve car driver’s behavior with regard to a low-noise driving style.

Index Tracking Using Data-Mining Techniques and Mixed-Binary Linear Programming

Index tracking has become one of the most common strategies in asset management. The index-tracking problem consists of constructing a portfolio that replicates the future performance of an index by including only a subset of the index constituents in the portfolio. Finding the most representative subset is challenging when the number of stocks in the index is large. We introduce a new three-stage approach that at first identifies promising subsets by employing data-mining techniques, then determines the stock weights in the subsets using mixed-binary linear programming, and finally evaluates the subsets based on cross validation. The best subset is returned as the tracking portfolio. Our approach outperforms state-of-the-art methods in terms of out-of-sample performance and running times.