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Selecting items for Big Five questionnaires : At what sample size do factorloadings stabilize?
(2014)
Researchers often use exploratory factor analysis (EFA) to develop and refine questionnaires assessing theBig Five personality traits. We use sequential sampling and bootstrapping to determine the number ofparticipants needed to yield stable loading patterns for the Big Five Inventory (BFI) and the InternationalPersonality Item Pool Big Five measure (IPIP). Overall 21,350 participants (BFI = 10,285; IPIP = 11,065)participated. In two studies primary factor loadings are highly variable in smaller samples (n< 500)and some primary loadings are not stable with 10,000 participants. Most studies will not have adequatesample size to yield stable loading patterns for Big Five measures such as the BFI and IPIP. Researchersshould assess and report the variability of loading patterns.
Multiple-group confirmatory factor analysis (MG-CFA) is among the most productive extensions of.structural equation modeling. Many researchers conducting cross-cultural or longitudinal studies are interested in testing for measurement and structural invariance. The aim of the present paper is to provide a tutorial in MG-CFA using the freely available R-packages lavaan, semTools, and semPlot. The combination of these packages enable a highly efficient analysis of the measurement models both for normally distributed as well as ordinal data. Data from two freely available datasets – the first with continuous the second with ordered indicators - will be used to provide a walk-through the individual steps.
Background:
One of the main problems of Internet-delivered interventions for a range of disorders is the high dropout rate, yet little is known about the factors associated with this. We recently developed and tested a Web-based 6-session program to enhance motivation to change for women with anorexia nervosa, bulimia nervosa, or related subthreshold eating pathology.
Objective:
The aim of the present study was to identify predictors of dropout from this Web program.
Methods:
A total of 179 women took part in the study. We used survival analyses (Cox regression) to investigate the predictive effect of eating disorder pathology (assessed by the Eating Disorders Examination-Questionnaire; EDE-Q), depressive mood (Hopkins Symptom Checklist), motivation to change (University of Rhode Island Change Assessment Scale; URICA), and participants’ age at dropout. To identify predictors, we used the least absolute shrinkage and selection operator (LASSO) method.
Results:
The dropout rate was 50.8% (91/179) and was equally distributed across the 6 treatment sessions. The LASSO analysis revealed that higher scores on the Shape Concerns subscale of the EDE-Q, a higher frequency of binge eating episodes and vomiting, as well as higher depression scores significantly increased the probability of dropout. However, we did not find any effect of the URICA or age on dropout.
Conclusions:
Women with more severe eating disorder pathology and depressive mood had a higher likelihood of dropping out from a Web-based motivational enhancement program. Interventions such as ours need to address the specific needs of women with more severe eating disorder pathology and depressive mood and offer them additional support to prevent them from prematurely discontinuing treatment.
Theoretischer Hintergrund: Bisherige Studien zeigen, dass internetbasierte Interventionen kurzfristig die Veränderungsmotivation bei Essstörungen verbessern können. Zur Stabilität dieser Effekte ist jedoch wenig bekannt. Fragestellung: Wie entwickeln sich die Veränderungsmotivation, die Essstörungspsychopathologie und das Selbstwertgefühl 8 Wochen nach Abschluss eines internetbasierten Motivationsprogramms?
Methode: Neunzig Frauen bearbeiteten den Stages of Change Questionnaire for Eating Disorders, den Eating Disorder Examination-Questionnaire und die Rosenberg Self-Esteem-Scale unmittelbar (Post) sowie 8 Wochen nach Abschluss der Intervention (Katamnese).
Ergebnisse: Es zeigten sich stabile Effekte in der Veränderungsmotivation sowie im Selbstwertgefühl. Zusätzlich zeigten sich in der Essstörungspsychopathologie signifikante Verbesserungen.
Schlussfolgerungen: Die Studie belegt die längerfristige Wirksamkeit eines internetbasierten Motivationsprogramms für Frauen mit Essstörungen.
The Brief Symptom Inventory (BSI)-18 is a widely-used tool to assess changes in general distress in patients despite an ongoing debate about its factorial structure and lack of evidence for longitudinal measurement invariance (LMI). We investigated BSI-18 scores from 1,081 patients from an outpatient clinic collected after the 2nd, 6th, 10th, 18th, and 26th therapy session. Confirmatory factor analysis (CFA) was used to compare models comprising one, three, and four latent dimensions that were proposed in the literature. LMI was investigated using a series of model comparisons, based on chi-square tests, effect sizes, and changes in comparative fit index (CFI). Psychological distress diminished over the course of therapy. A four-factor structure (depression, somatic symptoms, generalized anxiety, and panic) showed the best fit to the data at all measurement occasions. The series of model comparisons showed that constraining parameters to be equal across time resulted in very small decreases in model fit that did not exceed the cutoff for the assumption of measurement in variance. Our results show that the BSI-18 is best conceptualized as a four-dimensional tool that exhibits strict longitudinal measurement invariance. Clinicians and applied researchers do not have to be concerned about the interpretation of mean differences over time.