Background Rates of trauma exposure and posttraumatic stress disorder (PTSD) are high among refugee youth. Although there is a vast evidence base on effective trauma-focused interventions for children and adolescents, there is only limited understanding of how to adapt these interventions for oftentimes severely traumatized young refugees. This study aims to investigate adaptations undertaken during trauma-focused cognitive behavioral therapy (TF-CBT) in a pilot study with unaccompanied refugee minors (URMs). Method Written answers on five questions given by N = 9 therapists on N = 16 TF-CBT cases were analysed qualitatively using Mayring’s content analysis. The questions were on (1) additional techniques used in the sessions, (2) obstacles to TF-CBT treatment, (3) cultural factors considered and most helpful components for (4) patient and (5) therapist. The categories were built inductively and analysed descriptively. Results In addition to the regular TF-CBT components, added content mostly concerned the so-called “crisis of the week”, meaning a more lengthy discussion of struggles and concerns in their daily lives. Few obstacles in treatment were reported, and little cultural factors had to be considered. The implementation of a trauma narrative and the agenda provided by the manual were frequently reported as helpful. Conclusion The results of this study indicate that the manualized evidence-based treatment TF-CBT can be used in the culturally heterogeneous population of URMs with minor adaptations. These findings can contribute to future research as well as clinical practice with URMs.

Objective Alzheimer’s disease (AD) is a growing challenge worldwide, which is why the search for early‐onset predictors must be focused as soon as possible. Longitudinal studies that investigate courses of neuropsychological and other variables screen for such predictors correlated to mild cognitive impairment (MCI). However, one often neglected issue in analyses of such studies is measurement invariance (MI), which is often assumed but not tested for. This study uses the absence of MI (non‐MI) and latent factor scores instead of composite variables to assess properties of cognitive domains, compensation mechanisms, and their predictability to establish a method for a more comprehensive understanding of pathological cognitive decline. Methods An exploratory factor analysis (EFA) and a set of increasingly restricted confirmatory factor analyses (CFAs) were conducted to find latent factors, compared them with the composite approach, and to test for longitudinal (partial‐)MI in a neuropsychiatric test battery, consisting of 14 test variables. A total of 330 elderly (mean age: 73.78 ± 1.52 years at baseline) were analyzed two times (3 years apart). Results EFA revealed a four‐factor model representing declarative memory, attention, working memory, and visual–spatial processing. Based on CFA, an accurate model was estimated across both measurement timepoints. Partial non‐MI was found for parameters such as loadings, test‐ and latent factor intercepts as well as latent factor variances. The latent factor approach was preferable to the composite approach. Conclusion The overall assessment of non‐MI latent factors may pose a possible target for this field of research. Hence, the non‐MI of variances indicated variables that are especially suited for the prediction of pathological cognitive decline, while non‐MI of intercepts indicated general aging‐related decline. As a result, the sole assessment of MI may help distinguish pathological from normative aging processes and additionally may reveal compensatory neuropsychological mechanisms.

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Dementia, including Alzheimer's disease, is a growing problem worldwide.Prevention or early detection of the disease or a prodromal cognitive decline is necessary. By means of our long-term follow-up 'Vogel study', we aim to predict the pathological cognitive decline of a German cohort (mean age was 73.9 AE 1.55 years at first visit) with three measurement time points within 6 years per participant. Especially in samples of the elderly and subjects with chronic or co-morbid diseases, dropouts are one of the biggest problems of long-term studies. In contrast to the large number of research articles conducted on the course of dementia, little research has been done on the completion of treatment. To ensure unbiased and reliable predictors of cognitive decline from study completers, our objective was to determine predictors of dropout. We conducted multivariate analyses of covariance and multinomial logistic regression analyses to compare and predict the subject's dropout behaviour at the second visit 3 years after baseline (full participation, partial participation and no participation/dropout) with neuropsychiatric, cognitive, blood and lifestyle variables. Lower performance in declarative memory, attention and visual-spatial processing predicted dropout rather than full participation. Lower performance in visual-spatial processing predicted partial participation as opposed to full participation. Furthermore, lower performance in mini-mental status examination predicted whether subjects dropped out or participated partially instead of full participation. Baseline cognitive parameters are associated with dropouts at follow-up with a loss of impaired participants. We expect a bias into a healthier sample over time.