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Despite the central role of posttraumatic stress disorder (PTSD) in international humanitarian aid work, there has been little examination of the measurement invariance of PTSD measures across culturally defined refugee subgroups. This leaves mental health workers in disaster settings with little to support inferences made using the results of standard clinical assessment tools, such as the severity of symptoms and prevalence rates. We examined measurement invariance in scores from the most widely used PTSD measure in refugee populations, the Harvard Trauma Questionnaire (HTQ; Mollica et al., 1992), in a multinational and multilingual sample of asylum seekers from 81 countries of origin in 11 global regions. Clustering HTQ responses to justify grouping regional groups by response patterns resulted in three groups for testing measurement invariance: West Africans, Himalayans, and all others. Comparing log-likelihood ratios showed that while configural invariance seemed to hold, metric and scalar invariance did not. These findings call into question the common practice of using standard cut-off scores on PTSD measures across culturally dissimilar refugee populations. In addition, high correlation between factors suggests that the construct validity of scores from North American and European measures of PTSD may not hold globally.

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Climate researchers use carbon dioxide emission scenarios to explore alternative climate futures and potential impacts, as well as implications of mitigation and adaptation policies. Often, these scenarios are published without formal probabilistic interpretations, given the deep uncertainty related to future development. However, users often seek such information, a likely range or relative probabilities. Without further specifications, users sometimes pick a small subset of emission scenarios and/or assume that all scenarios are equally likely. Here, we present probabilistic judgments of experts assessing the distribution of 2100 emissions under a business-as-usual and a policy scenario. We obtain the judgments through a method that relies only on pairwise comparisons of various ranges of emissions. There is wide variability between individual experts, but they clearly do not assign equal probabilities for the total range of future emissions. We contrast these judgments with the emission projection ranges derived from the shared socioeconomic pathways (SSPs) and a recent multi-model comparison producing probabilistic emission scenarios. Differences on long-term emission probabilities between expert estimates and model-based calculations may result from various factors including model restrictions, a coverage of a wider set of factors by experts, but also group think and inability to appreciate long-term processes.