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

Interindividual differences in environmentally relevant positive trait affect impacts sustainable behavior in everyday life

Emotions are powerful drivers of human behavior that may make people aware of the urgency to act to mitigate climate change and provide a motivational basis to engage in sustainable action. However, attempts to leverage emotions via climate communications have yielded unsatisfactory results, with many interventions failing to produce the desired behaviors. It is important to understand the underlying affective mechanisms when designing communications, rather than treating emotions as simple behavioral levers that directly impact behavior. Across two field experiments, we show that individual predispositions to experience positive emotions in an environmental context (trait affect) predict pro-environmental actions and corresponding shifts in affective states (towards personal as well as witnessed pro-environmental actions). Moreover, trait affect predicts the individual behavioral impact of positively valenced emotion-based intervention strategies from environmental messages. These findings have important implications for the targeted design of affect-based interventions aiming to promote sustainable behavior and may be of interest within other domains that utilize similar intervention strategies (e.g., within the health domain).</p

The "Creative Right Brain” Revisited: Individual Creativity and Associative Priming in the Right Hemisphere Relate to Hemispheric Asymmetries in Reward Brain Function

The idea that creativity resides in the right cerebral hemisphere is persistent in popular science, but has been widely frowned upon by the scientific community due to little empirical support. Yet, creativity is believed to rely on the ability to combine remote concepts into novel and useful ideas, an ability which would depend on associative processing in the right hemisphere. Moreover, associative processing is modulated by dopamine, and asymmetries in dopamine functionality between hemispheres may imbalance the expression of their implemented cognitive functions. Here, by uniting these largely disconnected concepts, we hypothesize that relatively less dopamine function in the right hemisphere boosts creativity by releasing constraining effects of dopamine on remote associations. Indeed, participants with reduced neural responses in the dopaminergic system of the right hemisphere (estimated by functional MRI in a reward task with positive and negative feedback), displayed higher creativity (estimated by convergent and divergent tasks), and increased associative processing in the right hemisphere (estimated by a lateralized lexical decision task). Our findings offer unprecedented empirical support for a crucial and specific contribution of the right hemisphere to creativity. More importantly our study provides a comprehensive view on potential determinants of human creativity, namely dopamine-related activity and associative processing

Correction: Linking Individual Learning Styles to Approach-Avoidance Motivational Traits and Computational Aspects of Reinforcement Learning.

[This corrects the article DOI: 10.1371/journal.pone.0166675.]

Linking Individual Learning Styles to Approach-Avoidance Motivational Traits and Computational Aspects of Reinforcement Learning.

Learning how to gain rewards (approach learning) and avoid punishments (avoidance learning) is fundamental for everyday life. While individual differences in approach and avoidance learning styles have been related to genetics and aging, the contribution of personality factors, such as traits, remains undetermined. Moreover, little is known about the computational mechanisms mediating differences in learning styles. Here, we used a probabilistic selection task with positive and negative feedbacks, in combination with computational modelling, to show that individuals displaying better approach (vs. avoidance) learning scored higher on measures of approach (vs. avoidance) trait motivation, but, paradoxically, also displayed reduced learning speed following positive (vs. negative) outcomes. These data suggest that learning different types of information depend on associated reward values and internal motivational drives, possibly determined by personality traits

Fitted model parameters separately for approach and avoidance learners.

<p>Mean ± SEM.</p

Behavioural data (Mean ± SEM).

<p>A. Performance as a function of training. Performance improved equally for participants in the different groups as training progressed. B. Approach and avoidance performance during testing. Approach learners were relatively better at selecting the A symbol, as compared to rejecting the B symbol, while avoidance learners displayed the reverse trend. Importantly, this interaction simply reflects the assignment of participants to different groups based on their relative performance on selecting the A-rejecting the B symbol. However, approach learners were also better at selecting the A symbol as compared to avoidance learners, while the B symbol was more frequently rejected by avoidance learners. C. Approach and avoidance learners did not differ in BAS nor BIS scores. D. Approach and avoidance learners scored higher on reward sensitivity (SR) and punishment sensitivity (SP), respectively. BAS = behavioural activation system, BIS = behavioural inhibition system, SP = sensitivity to punishment, SR = sensitivity to reward, SPSRQ = Sensitivity to Punishment and Sensitivity to Reward Questionnaire. • p< 0.10, * p < 0.05, ** p < 0.01,*** p < 0.001, ns. = not significant (p>0.05).</p