Journal: Nonlinear dynamics, psychology, and life sciences
A mathematical model is proposed for interpreting the love story between Elizabeth and Darcy portrayed by Jane Austen in the popular novel Pride and Prejudice. The analysis shows that the story is characterized by a sudden explosion of sentimental involvements, revealed by the existence of a saddle-node bifurcation in the model. The paper is interesting not only because it deals for the first time with catastrophic bifurcations in romantic relation-ships, but also because it enriches the list of examples in which love stories are described through ordinary differential equations.
Much has been written about the differences between single- and double-loop learning, or more general between lower level and higher level learning. Especially in times of a fundamental crisis, a transition between lower and higher level learning would be an appropriate reaction to a challenge coming entirely out of the dark. However, so far there is no quantitative method to monitor such a transition. Therefore we introduce theory and methods of synergetics and present results from an experimental study based on the simulation of a crisis within a business simulation game. Hypothesized critical fluctuations - as a marker for so-called phase transitions - have been assessed with permutation entropy. Results show evidence for a phase transition during the crisis, which can be interpreted as a transition between lower and higher level learning.
This study aimed (a) to address the evidence for situational specificity in the connection between safety climate to occupational accidents, (b) to resolve similar issues between anxiety and accidents, © to expand and develop the concept of safety climate to include a wider range of organizational con-structs, (d) to assess a cusp catastrophe model for occupational accidents where safety climate and anxiety are treated as bifurcation variables, and environ-mental hazards are asymmetry variables. Bifurcation, or trigger variables can have a positive or negative effect on outcomes, depending on the levels of asymmetry, or background variables. The participants were 1262 production employees of two steel manufacturing facilities who completed a survey that measured safety management, anxiety, subjective danger, dysregulation, stressors and hazards. Nonlinear regression analyses showed, for this industry, that the accident process was explained by a cusp catastrophe model in which safety management and anxiety were bifurcation variables, and hazards, age and experience were asymmetry variables. The accuracy of the cusp model (R2 = .72) exceeded that of the next best log-linear model (R2 = .08) composed from the same survey variables. The results are thought to generalize to any industry where serious injuries could occur, although situationally specific effects should be anticipated as well.
This article improves our understanding of the causal processes driving the dynamic behavior of education systems using a System Dynamics approach. The model presented here has three state variables: Population, Population in Primary School, and Primary School Graduates whose values are calibrated for the case of Nicaragua. It also includes nonlinear complex interactions between critical factors, e.g., the state of the economy, the state of the education system, and population literacy that affect the system’s transition rates -intake, repetition, dropout, and promotion- which therefore influence the dynamics of schooling outcomes. These schooling outcomes in turn affect population literacy and economic progress in the country thus generating aggregate patterns that continuously change (and are changed by) the inputs that endogenously determine them, which could potentially explain why educational systems exhibit persistently good or bad outcomes. Simulation runs show a strong correspondence with observed data and additionally the model provides meaningful insights to guide policy making in educational reform, such as the ability to reveal the presence of ‘ghost students’. This paper concludes that complex dynamic systems modeling and simulation can facilitate forecasting of school system behavior and the detection of policy inconsistencies, something conventional modeling cannot do.
How does primary care psychology deal with organized complexity? Has it escaped Newtonian science? Has it, as Weaver (1991) suggests, found a way to ‘manage problems with many interrelated factors that cannot be dealt by statistical techniques’? Computer simulations and mathematical models in psychology are ongoing positive developments in the study of complex systems. However, the theoretical development of complex systems in psychology lags behind these advances. In this article we use complexity science to develop a theory on experienced complexity in the daily practice of primary care psychologists. We briefly answer the ontological question of what we see (from the perspective of primary care psychology) as reality, the epistemological question of what we can know, the methodological question of how to act, and the ethical question of what is good care. Following our empirical study, we conclude that complexity science can describe the experienced complexity of the psychologist and offer room for personalized client-centered care. Complexity science is slowly filling the gap between the dominant reductionist theory and complex daily practice.
We show that a path not yet considered exists in the parameter space of the cusp catastrophe that constitutes a ‘target-trajectory,’ along which psychological change may be achieved in a variety of situations by taking advantage of the protagonists' resistance. The parameters Pathogen - the pathogenic agent - and Therapy, or Dissent and Remedy, are used depending on whether the theory is applied to psychotherapy or conflict, respectively. This proposed target-trajectory offers: (a) conditions optimised in therapy with regard to the intrinsic limitations for the reduction of a patient’s pathogenic agent, and in conflict with regard to the ‘red-lines’ of the protagonists, and (b) the benefit of a step of rapid decrease in the potential barrier to change. Questions raised concern the benefit that a patient may obtain from performing his cognitive task in psychotherapy with minimal requirement for the reduction of his pathogen, and the role that a step of rapid decrease in a potential barrier may play in decision-making, in particular when it comes to end a conflict. The argument is developed in detail for psychoanalytic resistance, relying on principles and procedures described in numerous texts of psychoanalysis. The theory deals with scaling laws - power laws - rather than strict equalities.
Consistent links exist between male and female alcohol intake and intimate partner violence (IPV). However, the nature of the relationship remains unclear. This study explores the temporal relationships between violence and heavy alcohol intake, looking for multi-day patterns. 200 women with a recent history of husband-to-wife abuse from six primary care clinics were asked to complete daily assessments using Interactive Verbal Response (IVR) via telephone for 12 weeks. To identify recurrent strings of activities, we used orbital decomposition. Multi-day patterns were found at the 5-, 7- and 9-day levels, but most represented extensions of 4-day patterns. Overall, consecutive days of male-perpetrated, moderate-severe violence were common. In addition, heavy alcohol intake by the husband was underrepresented on days involving verbal abuse only but overrepresented in consecutive days of such abuse; husband’s alcohol intake preceded his verbal abuse and a sequence of husbandperpetrated verbal abuse followed by mutual abuse followed by wife-perpetrated verbal abuse was noted. No patterns involved heavy alcohol intake by the wife. In conclusion, few patterns involved heavy alcohol intake by men and none by women. Although husband’s heavy alcohol intake may contribute to onset and maintenance of verbal abuse, it plays little role in recurrent patterns of physical violence.
Service research tends to operationalize word of mouth (WOM) behavior as one of the many responses to service satisfaction. In this sense, little is known about its antecedents or moderators. The objective of this study was to investigate the role of customers' emotions during service experiences on WOM, applying nonlinear techniques and exploring the moderating role of customers' propensity for emotional contagion. Using the critical incidents technique, 122 customers recalled significant service experiences and the emotions they aroused, and reported if they shared said experiences with other individuals. We found that, whereas linear methods presented non-significant results in the emotions-WOM relationship, nonlinear ones (artificial neural networks) explained 46% of variance. Negative emotions were stronger predictors of WOM and the importance of emotions for WOM was significantly higher for individuals with high propensity for emotional contagion (R^2 = .79) than for those with lower levels (R^2 = .48). Theoretical and practical implications are discussed.
This paper introduces a new measure to evaluate heart output from a dynamical systems approach. The measure is based on the time delay technique for two-dimensional state space reconstruction from time series of interbeat intervals. The system’s trajectories within this space are depicted and the mean distance, as well as the total and maximum distances travelled by the system, are calculated in pixels. Preliminary data from adolescents with highly positive emotional regulation (HPER) style (n=10) and adolescents with highly negative (HNER) style (n=10) who underwent a protocol of stress induction show the usefulness of the new metrics to distinguish the dynamical behavior of the heart systems from these groups. Repeated measures ANOVAs revealed that changes in all three distances across conditions (baseline, anticipation of stress, exposure to stress, and recovery) were significant in the HPER group but not in the HNER group. As to the physiological meaning of the new measure a correlational analysis revealed that associations with time-domain HRV measures were stronger than associations with frequency-domain HRV measures in both groups. Because of the small sample size, bootstrap resampling was used to obtain confidence intervals. Distances calculated with the new measure are sensitive to the ER-related cardiac flexibility under acute stress conditions. However, the physiological meaning of the new indices remains unclear.
This article overviews several contemporary models that assume power law scaling is a plausible description of the skewed right tails that are typical of response time distributions. The properties and markers of these distribution functions have implications for cognitive and neurophysiological dynamics. The power law hypothesis suggests studies should collect larger samples, and that analyses may combine individual subjects' data into a single set for a distribution-function contrasts. Techniques for contrasting response time measurements are illustrated on data from a previously published study comparing the performance of children diagnosed with dyslexia and a group of age-matched controls in flanker, color naming, word naming, and arithmetic performance.