30 research outputs found
Cue‐induced effects on decision‐making distinguish subjects with gambling disorder from healthy controls
While an increased impact of cues on decision‐making has been associated with substance dependence, it is yet unclear whether this is also a phenotype of non‐substance‐related addictive disorders, such as gambling disorder (GD). To better understand the basic mechanisms of impaired decision‐making in addiction, we investigated whether cue‐induced changes in decision‐making could distinguish GD from healthy control (HC) subjects. We expected that cue‐induced changes in gamble acceptance and specifically in loss aversion would distinguish GD from HC subjects.
Thirty GD subjects and 30 matched HC subjects completed a mixed gambles task where gambling and other emotional cues were shown in the background. We used machine learning to carve out the importance of cue dependency of decision‐making and of loss aversion for distinguishing GD from HC subjects.
Cross‐validated classification yielded an area under the receiver operating curve (AUC‐ROC) of 68.9% (p = .002). Applying the classifier to an independent sample yielded an AUC‐ROC of 65.0% (p = .047). As expected, the classifier used cue‐induced changes in gamble acceptance to distinguish GD from HC. Especially, increased gambling during the presentation of gambling cues characterized GD subjects. However, cue‐induced changes in loss aversion were irrelevant for distinguishing GD from HC subjects. To our knowledge, this is the first study to investigate the classificatory power of addiction‐relevant behavioral task parameters when distinguishing GD from HC subjects. The results indicate that cue‐induced changes in decision‐making are a characteristic feature of addictive disorders, independent of a substance of abuseDFG, 103586207, GRK 1589: Sensory Computation in Neural System
Addressing climate change with behavioral science:A global intervention tournament in 63 countries
Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions' effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior-several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people's initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors.</p
Addressing climate change with behavioral science:A global intervention tournament in 63 countries
Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions' effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior-several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people's initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors.</p
Addressing climate change with behavioral science: a global intervention tournament in 63 countries
Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions’ effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior—several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people’s initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors
The DFPase from Loligo Vulgaris in sugar surfactant based bicontinuous microemulsions
Wellert S, Tiersch B, Koetz J, et al. The DFPase from Loligo Vulgaris in sugar surfactant based bicontinuous microemulsions. Euro. Biophysics J. 2011;40(6):761-774
The Link Between the Local Bubble and Radioisotopic Signatures on Earth
Traces of 2-3 Myr old 60Fe were recently discovered in a manganese crust and in lunar samples. We have found that this signal is extended in time and is present in globally distributed deep-sea archives. A second 6.5-8.7 Myr old signature was revealed in a manganese crust. The existence of the Local Bubble hints to a recent nearby supernova-activity starting 13 Myr ago. With analytical and numerical models generating the Local Bubble, we explain the younger 60Fe-signature and thus link the evolution of the solar neighborhood to terrestrial anomalies