Bringing together humanistic and intergroup perspectives to build a model of internalisation of normative social harmdoing

This article introduces a model of the internalisation of normative social harmdoing: the MINSOH. This model seeks to explain how group members internalise harmful social norms such that they personally endorse their groups' normative actions. To this aim, the MINSOH integrates two divergent yet complementary theoretical perspectives: self-determination theory and the social identity approach. These perspectives differ in their basic assumptions about the possibility for harm to become internalised, yet when integrated, they provide a powerful account of how harmdoing can become internalised. The MINSOH proposes specific conditions under which harmful normative actions become accepted by group members. This article outlines multiple self-determined motivations for harmdoing and discrete group processes that enable harmdoing to be internalised and autonomously enacted, and reviews factors that facilitate (i.e., strong/unique/comparative social identification; endorsement of ideological justifications) and block the internalisation process (presence of multiple identities/diverging norms; inclusive superordinate identity). Directions for future research are then discussed.     

Trajectories of public psycho-behavioural responses relating to influenza A(H7N9) over the winter of 2014-15 in Hong Kong

Objective: To explore trajectories of public psycho-behavioural responses over one influenza A(H7N9) epidemic wave, and examine the interplays among social norm influence, disease worry and protective behaviours.

Methods: Participants were 464 adults who completed the baseline and at least two follow-up assessments on their H7N9-related Perceived Susceptibility, Perceived Severity, Perceived Efficacy, Worry, Social Norms influence and Protective Behaviours in a five-phase longitudinal survey over one H7N9 epidemic wave. Latent growth modelling (LGM) identified trajectories of these psycho-behavioural responses while multi-process LGM examined the inter-relationships among trajectories of Social Norms influence, Worry and Protective Behaviours.

Results: Trajectories of Perceived Susceptibility, Worry, Social Norms and Protective Behaviours increased initially but declined as the epidemic decayed, while Perceived Severity increased linearly and Perceived Efficacy remained stable across the epidemic. Change in Social Norms influence was significantly associated with change in Worry (β?=?0.65) which was significantly associated with change in Protective Behaviours (β?=?0.62).

Conclusion: The public’s threat appraisal but not efficacy appraisal may have been well-informed by epidemic-related information. Social Norms may be important contributors of public emotional response to an epidemic. Communication via social networks during an epidemic could be important for regulating public emotional response and guiding their behavioural change.     

Neuroimaging the sleeping brain: Insight on memory functioning in infants and toddlers

Episodic memory, or the ability to remember past events with specific detail, is central to the human experience and is related to learning and adaptive functioning in a variety of domains. In typically developing children, episodic memory emerges during infancy and improves during early childhood and beyond. Developmental processes within the hippocampus are hypothesized to be primarily responsible for both the early emergence and persistence of episodic memory in late infancy and early childhood. However, these hypotheses are based on non-human models. In-vivo investigations in early human development of hippocampal processes have been significantly limited by methodological challenges in acquiring neuroimaging data, particularly task-related functional neuroimaging data, from infants and toddlers. Recent studies in adults have shown neural activity in the brain regions supporting episodic memory during slow-wave sleep using functional magnetic resonance imaging (fMRI), and fMRI has been increasingly utilized in infancy and early childhood to address other research questions. We review initial evidence and present preliminary data showing the promise of this approach for examining hippocampal contribution to how infants and toddlers remember individual events, and their association with information about the context in which the event occurred. Overall, our review, integrated with the presentation of some preliminary data provides insight on leveraging sleep to gain new perspectives on early memory functioning.     

Empirical Bayes Derivative Estimates

Abstract

A dynamic system is a set of interacting elements characterized by changes occurring over time. The estimation of derivatives is a mainstay for exploring dynamics of constructs, particularly when the dynamics are complicated or unknown. The presence of measurement error in many social science constructs frequently results in poor estimates of derivatives, as even modest proportions of measurement error can compound when estimating derivatives. Given the overlap in the specification of latent differential equation models and latent growth curve models, and the equivalence of latent growth curve models and mixed models under some conditions, derivatives could be estimated from estimates of random effects. This article proposes a new method for estimating derivatives based on calculating the Empirical Bayes estimates of derivatives from a mixed model. Two simulations compare four derivative estimation methods: Generalized Local Linear Approximation, Generalized Orthogonal Derivative Estimates, Functional Data Analysis, and the proposed Empirical Bayes Derivative Estimates. The simulations consider two data collection scenarios: short time series (≤10 observations) from many individuals or occasions, and long individual time series (25–500 observations). A substantive example visualizing the dynamics of intraindividual positive affect time series is also presented.     

Political Consequences of Partisan Prejudice

Political conflict sometimes spills over into unrelated areas of our lives. A growing literature documents examples of partisan considerations influencing judgments and behaviors in ostensibly nonpolitical contexts such as the workplace, academia, and dating, among others. To date, the focus has been on demonstrating these phenomena, with scant consideration of their downstream effects. When politics spills over into nonpolitical settings—that is, when political considerations influence nonpolitical judgments or behaviors—what are the consequences? I address this question with a novel theory and a nationally representative survey experiment. I find that norms exist regarding the spillover of political considerations into nonpolitical matters—and that spillover can have its own political consequences. When one's copartisans discriminate against members of the other party, it can lead to decreased partisan identification and depolarization. Partisan discrimination in nonpolitical settings can—in some sense ironically—reduce affective polarization. That said, partisans also appear to hold a double standard: They expect copartisans to give an edge to fellow copartisans.     

Towards modern post-coma care based on neuroscientific evidence

BackgroundUnderstanding the mechanisms underlying human consciousness is pivotal to improve the prognostication and treatment of severely brain-injured patients. Consciousness remains an elusive concept and the identification of its neural correlates is an active subject of research, however recent neuroscientific advances have allowed scientists to better characterize disorders of consciousness. These breakthroughs question the historical nomenclature and our current management of post-comatose patients.MethodThis review examines the contribution of consciousness neurosciences to the current clinical management of severe brain injury. It investigates the major impact of consciousness disorders on healthcare systems, the scientific frameworks employed to identify their neural correlates and how evidence-based data from neuroimaging research have reshaped the landscape of post-coma care in recent years.ResultsOur increased ability to detect behavioral and neurophysiological signatures of consciousness has led to significant changes in taxonomy and clinical practice. We advocate for a multimodal framework for the management of severely brain-injured patients based on precision medicine and evidence-based decisions, integrating epidemiology, health economics and neuroethics.ConclusionsMajor progress in brain imaging and clinical assessment have opened the door to a new era of post-coma care based on standardized neuroscientific evidence. We highlight its implications in clinical applications and call for improved collaborations between researchers and clinicians to better translate findings to the bedside.