A Trauma-Informed Call to Action: Culturally-Informed,Multidisciplinary Theoretical and Applied Approaches to Prevention and Healing

ABSTRACT

The prevalence of trauma and its negative impact on humankind has created a burgeoning awareness of the need for systems that are trauma-informed across the lifespan. A collaborative project with the National Partnership to End Interpersonal Violence (NPEIV) sought out research as a call-to-action to mitigate the impact of trauma. The following is an introduction to a special double-issue focused on theoretical and applied approaches to using trauma-informed care in multi-disciplinary, mental and physical health, criminal justice, school-based, and community settings. Consideration is given to essential issues such as resilience, self-care, and cultural awareness.     

Capturing non-linear temporally embedded processes in organizations using recurrence quantification analysis

ABSTRACT

Despite the growing consensus that the majority of psychological phenomena at work are temporally embedded and highly dynamic, existing research is often based on simplified theoretical and methodological models, which take limited account of process dynamics and especially non-linear growth trajectories. In this paper, we highlight the potentials of using recurrence quantifications analysis (RQA) and an extension of RQA – cross-recurrence quantification analysis (CRQA) – for researching process dynamics in organizations. (C)RQA is a powerful technique that can be used to both visualize and quantify time-series data such as repeated measurements of psychological states or sequentially coded dyadic and team interactions. To illustrate the manifold opportunities of (C)RQA, we present three application examples focusing on individuals as systems, dyads as systems, and teams as systems. Specifically, we highlight how (C)RQA can be applied to individual diary data, to leader-follower communication dynamics observed during annual appraisal interviews, and to high-density coded team interactions observed during organizational meetings. We discuss the strengths and limitations of (C)RQA and provide recommendations for researchers interested in using the method.     

Adaptive rewiring in weighted networks

Human connectome studies suggest that the brain has a modular small world network structure with rich-club effect. Such structure emerges spontaneously in simple model neural networks, (e.g. coupled maps), through adaptive rewiring according to the dynamic functional connectivity. The utility of adaptive rewiring has so far exclusively been demonstrated for unweighted networks; it is anything but guaranteed to work as well for weighted networks. We investigate adaptive rewiring in weighted networks, comparing various right-skewed, symmetrical, and left-skewed fixed weight distributions. We examine how network clustering, path length, modularity, and rich club coefficients develop for weakly, intermediate and strongly coupled networks. At low coupling strength, the weight distribution, as well as episodes of functional synchrony, have a significant effect on network evolution. With increased coupling strengths, all weighted networks robustly develop architectures similar to the unweighted ones. Adaptive rewiring appears relatively ineffective in networks with (biologically implausibly) extreme right-skewed weight distributions but performed most economically in biologically plausible log-normal distributions.     

Wavelet-frequency analysis for the detection of discontinuities in switched system models of human balance

This paper is concerned with detecting the presence of switching behavior in experimentally obtained posturographic data sets by means of a novel algorithm that is based on a combination of wavelet analysis and Hilbert transform. As a test-bed for the algorithm, we first use a switched model of human balance control during quiet standing with known switching behavior in four distinct configurations. We obtain a time–frequency representation of a signal generated by our model system. We are then able to detect manifestations of discontinuities (switchings) in the signal as spiking behavior. The frequency of switchings, measured by means of our algorithm and detected in our models systems, agrees with the frequency of spiking behavior found in the experimentally obtained posturographic data.     

HUMAN LIFE AND CULTURE: DYNAMIC COMPONENTS OF ECOSYSTEMS

Abstract. Contemporary humanity—especially urban-industrial civilization with its domination of nature—is disturbing complex, integrated, self-regulating systems that have evolved over long periods of time. We are threatening not only biological ecosystems but also human self-regulating capabilities at both the biological and the social-systems levels. This paper presents examples of such disturbance both in the organism—respiratory-cardiovascular problems related to environmental pollution-and at the population level—rates of infant mortality and relations between fertility and mortality in light of economic and emotional factors. Prospects for our future survival and flourishing are thus linked less to technical know-how than to ecological understanding.     

Formal assessment of reliability specifications in embedded cyber-physical systems

Reliability has become an integral component of the design intent of embedded cyber-physical systems. Safety-critical embedded systems are designed with specific reliability targets, and design practices include the appropriate allocation of both spatial and temporal redundancies in the implementation to meet such requirements. With increasing complexity of such systems and considering the large number of components in such systems, redundancy allocation requires a formal scientific basis. In this work, we profess the analysis of the redundancy requirement upfront with the objective of making it an integral part of the specification. The underlying problem is one of synthesizing a formal specification with built-in redundancy artifacts, from the formal properties of the error-free system, the error probabilities of the control components, and the reliability target. We believe that upfront formal analysis of redundancy requirements is important in budgeting the resource requirements from a cost versus reliability perspective. Several case-studies from the automotive domain highlight the efficacy of our proposal.     

The Responses of Health Systems to Marital Sexual Violence – A Perspective from Southern India

ABSTRACT

Marital sexual violence is a serious problem in India. However, marital rape and most other forms of marital sexual violence are not criminalized in the country. This qualitative study with healthcare providers (physicians and nurses), lawyers, members of a non-profit organization that offers domestic violence support services out of a hospital, a journalist and two lawyers suggest that the majority of care providers recognize that marital sexual violence is a serious concern, and agree that health systems can play a vital role in addressing both the immediate biomedical concerns of survivors, and also overall well-being. The study reveals several systemic and internal factors that hinder responsiveness of Indian health institutions. These include, the absence of a protocol or uniform internal guidelines in most hospitals, a lack of screening programs to capture the presence of violence occurring when patients visit hospitals for other reasons, a large patient load, a lack of gender sensitivity in providers’ education, an absence of domestic violence shelters, and poor interlinkages between support services such as counseling and legal services. Notwithstanding these challenges, some exemplar physicians and nurses assist survivors of sexual violence, sometimes risking their own safety. The Indian health system can be made more responsive, provided these factors are addressed, and crucially budgets are allocated for interventions.     

Memory systems and the control of skilled action

ABSTRACT

In keeping with the dominant view that skills are largely automatic, the standard view of memory systems distinguishes between a representational declarative system associated with cognitive processes and a performance-based procedural system. The procedural system is thought to be largely responsible for the performance of well-learned skilled actions. Here we argue that most skills do not fully automate, which entails that the declarative system should make a substantial contribution to skilled performance. To support this view, we review evidence showing that the declarative system does indeed play a number of roles in skilled action.     

Speaker identification using multi-modal i-vector approach for varying length speech in voice interactive systems

The development in the interface of smart devices has lead to voice interactive systems. An additional step in this direction is to enable the devices to recognize the speaker. But this is a challenging task because the interaction involves short duration speech utterances. The traditional Gaussian mixture models (GMM) based systems have achieved satisfactory results for speaker recognition only when the speech lengths are sufficiently long. The current state-of-the-art method utilizes i-vector based approach using a GMM based universal background model (GMM-UBM). It prepares an i-vector speaker model from a speaker’s enrollment data and uses it to recognize any new test speech. In this work, we propose a multi-model i-vector system for short speech lengths. We use an open database THUYG-20 for the analysis and development of short speech speaker verification and identification system. By using an optimum set of mel-frequency cepstrum coefficients (MFCC) based features we are able to achieve an equal error rate (EER) of 3.21% as compared to the previous benchmark score of EER 4.01% on the THUYG-20 database. Experiments are conducted for speech lengths as short as 0.25 s and the results are presented. The proposed method shows improvement as compared to the current i-vector based approach for shorter speech lengths. We are able to achieve improvement of around 28% even for 0.25 s speech samples. We also prepared and tested the proposed approach on our own database with 2500 speech recordings in English language consisting of actual short speech commands used in any voice interactive system.     

Dissociating automatic associations: Comparing two implicit measurements of race bias

Weak correspondence across different implicit bias tasks may arise from the contribution of unique forms of automatic and controlled processes to response behavior. Here, we examined the correspondence between estimates of automatic and controlled processing derived from two sequential priming tasks with identical structure and timing designed to separately measure stereotypic (Weapons Identification Task; WIT) and evaluative (Affective Priming Task; APT) associations. Across two studies using predominantly White samples, three consistent patterns emerged in the data: (a) stereotypic bias was stronger for Black targets, whereas evaluative bias was stronger for White targets; (b) overall response accuracy bias correlated modestly across the two tasks; and (c) multinomial processing tree estimates of controlled processing corresponded much more strongly than estimates of automatic processing. These findings support models positing distinct learning and memory systems for different forms of race bias, and suggest that these differing forms contribute to estimates of automatic associations.