Clinicians' Attitudes Towards Outcome and Process Monitoring: A Validation of the Outcome Measurement Questionnaire.

Valid and reliable instruments to measure monitoring attitudes of clinicians are scarce. The influence of sociodemographics and professional characteristics on monitoring attitudes is largely unknown. First, we investigated the factor structure and reliability of the Outcome Measurement Questionnaire among a sample of Flemish mental health professionals (n = 170). Next, we examined the relationship between clinicians' sociodemographic and professional characteristics and monitoring attitudes. Construct validity was determined using a confirmatory factor analysis. Internal consistency was ascertained using Cronbach's alpha. Mean level differences in monitoring attitudes related to clinicians' gender, work setting, level of education and psychotherapeutic training, were investigated using ANOVAs. The relationships between clinicians' age, clinical experience and attitudes were calculated using the Pearson correlation coefficient. A model with one general factor and a method factor referring to reverse-worded items best fitted our data. Internal consistency was good. Clinicians with psychotherapeutic training reported more favorable monitoring attitudes than those without such training. Compared to clinicians working in subsidized outpatient services, private practitioners and clinicians from inpatient mental health clinics had more positive attitudes. Results highlight the need for sustained and targeted training, with particular focus on transforming measurement data into meaningful clinical support tools.

The German version of the Material Values Scale.

AIM: The Material Values Scale is an instrument to assess beliefs about the importance to own material things. This instrument originally consists of the three subscales: 'centrality', 'success', and 'happiness'. The present study investigated the psychometric properties of the German version of the MVS (G-MVS). METHOD: A population-based sample of 2,295 adult Germans completed the questionnaire in order to investigate the factorial structure. To test construct validity, additional samples were gathered among patients with compulsive buying (N=52) and medical students (N=347) who also answered the Compulsive Buying Scale (CBS) and the Patient Health Questionnaire depression scale (PHQ-8). RESULTS: In the German population-based sample we could not confirm the 3-factor model but rather suggest a 2-factor solution with a first collapsed factor 'centrality/success', and the second factor 'happiness'. Patients with compulsive buying showed the highest scores on the G-MVS. While G-MVS scores among compulsive buyers and medical students were significantly related to compulsive buying scores, the correlation between the G-MVS and the depression measure appeared substantially lower. We did not find any gender differences regarding materialism, neither in the population-based sample nor in the students' or compulsive buyers' samples. However, age was negatively related to G-MVS scores. CONCLUSION: Confirmatory factor analyses suggest a 2-factor model of the G-MVS. Overall, the results indicate the use of the G-MVS as a brief, psychometrically sound, and potentially valid measure for the assessment of material values.

Mixed model estimation methods for the Rasch model.

Mixed models take the dependency between observations based on the same person into account by introducing one or more random effects. After introducing the mixed model framework, it is explained, by taking the Rasch model as a generic example, how item response models can be conceptualized as generalized linear and nonlinear mixed models. Common estimation methods for generalized linear and nonlinear models are discussed. In a simulation study, the performance of four estimation methods is assessed for the Rasch model under different conditions regarding the number of items and persons, and the degree of interindividual differences. The estimation methods included in the study are: an approximation of the integral over the random effect by means of Gaussian quadrature; direct maximization with a sixth-order Laplace approximation to the integrand; a linearized approximation of the nonlinear model employing PQL2; and finally a Bayesian MCMC method. It is concluded that the estimation methods perform almost equally well, except for a slightly worse recovery of the variance parameter for PQL2 and MCMC.

The appraisal basis of anger: specificity, necessity and sufficiency of components.

The nature of the association between anger and 5 appraisal-action tendency components--goal obstacle, other accountability, unfairness, control, and antagonism--was examined in terms of specificity, necessity, and sufficiency. In 2 studies, participants described recently experienced unpleasant situations in which 1 of the appraisal-action tendency components was present or absent and indicated which emotions they had experienced. The results showed that (a) other accountability and arrogant entitlement, as an instance of unfairness, are specific appraisals ability for anger; and most important, (b) none of the components is necessary or sufficient for anger. The findings suggest that the relation between emotions and appraisal-action tendency components should be conceptualized instead as a contingent association, meaning that they usually co-occur.

Estimation of the MIRID: a program and a SAS-based approach.

The MIRID CML program is a program for the estimation of the parameter values of two different componential IRT models: the Rasch-MIRID and the OPLM-MIRID (Butter, 1994; Butter, De Boeck, & Verhelst, 1998). To estimate the parameters of both models, the program uses a CML approach. The model parameters can also be estimated with a MML approach that can be implemented in PROC NLMIXED of SAS Version 8. Both the MIRID CML program and the MML SAS approach are explained and compared in a simulation study. The results showed that they did about equally well in estimating the values of the item parameters but that there were some differences in the estimation of the person parameters, as could be expected from the differential assumptions regarding the distribution of the persons. The SAS MML approach is much slower than the MIRID CML program, but it is more flexible.