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A new method of calculating attentional bias from the dot-probe task measures fluctuations in bias towards and away from emotional stimuli over time using trial level bias score metrics. We assessed the stability and reliability of traditional attentional bias scores and trial level bias score measures of attentional bias across time in two five-block dot-probe task experiments in nonclinical samples. In experiments 1 and 2, both traditional attentional bias scores and trial level bias score measures of attentional bias did not habituate/decrease across time. In general, trial level bias score metrics (i.e., attention bias variability as well as the mean biases toward and away from threat) were more reliable than the traditional attention bias measure. This pattern was observed across both experiments. The traditional bias score, however, did improve in reliability in the later blocks of the fearful face dot-probe task. Although trial level bias score measures did not habituate and were more reliable across blocks, these measures did not correlate with state or trait anxiety. On the other hand, trial level bias score measures were strongly correlated with general reaction time variability-and after controlling for this effect no longer superior in reliability in comparison to the traditional attention bias measure. We conclude that general response variability should be removed from trial level bias score measures to ensure that they truly reflect attention bias variability.Terms of use and reuse: academic research for non-commercial purposes, see here for full terms. https://www.springer.com/aamterms-v1

Abstract:The development of landslide susceptibility maps is of great importance due to rapid urbanization. The purpose of this study is to present a method to integrate the subjective weight with objective weight for regional landslide susceptibility mapping on the geographical information system (GIS) platform. The analytical hierarchy process (AHP), which is subjective, was employed to weight predictive factors' contribution to landslide occurrence. The frequency ratio (FR) method, which is objective, was used to derive subclasses' frequency ratio with respect to landslides that indicate the relative importance of a subclass within each predictive factor. A case study was carried out at Tsushima Island, Japan, using a historical inventory of 534 landslides and seven predictive factors: elevation, slope, aspect, terrain roughness index (TRI), lithology, land cover and mean annual precipitation (MAP). The landslide susceptibility index (LSI) was calculated using the weighted linear combination of factors' weights and subclasses' weights. The study area was classified into five susceptibility zones according to the LSI. In addition, the produced susceptibility map was compared with maps generated using the conventional FR and AHP method and validated using the relative landslide index (RLI). The validation result showed that the proposed method performed better than the conventional application of the FR method and AHP method. The obtained landslide susceptibility maps could serve as a scientific basis for urban planning and landslide hazard management.