The identification of critical fluctuations and phase transitions in short term and coarse-grained time series—a method for the real-time monitoring of human change processes

Schiepek, Günter; Strunk, Guido

doi:10.1007/s00422-009-0362-1

Cited by 120 publications

(124 citation statements)

References 27 publications

(20 reference statements)

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“…Importantly, as a dynamical system approaches a phase transition, the constraints among the system's components begin to break down. A number of methods have been proposed as a means of detecting these phase transitions, such as changes in variability and autocorrelation (Dakos, Van Nes, D'Odorico, & Scheffer, 2012), examining shifts in the values to which the system is attracted (Butler, 2011), changes in entropy and power law scaling (Stephen, Boncoddo, Magnuson, & Dixon, 2009;Stephen, Dixon, & Isenhower, 2009), measures of fluctuation (Schiepek & Strunk, 2010), and, more qualitatively, cognitive event analysis (Steffensen, Vall ee-Tourangeau, & Vall ee-Tourangeau, 2016).…”

Section: Dynamical Systems and Phase Transitionsmentioning

confidence: 99%

Problem‐Solving Phase Transitions During Team Collaboration

2017

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Multiple theories of problem-solving hypothesize that there are distinct qualitative phases exhibited during effective problem-solving. However, limited research has attempted to identify when transitions between phases occur. We integrate theory on collaborative problem-solving (CPS) with dynamical systems theory suggesting that when a system is undergoing a phase transition it should exhibit a peak in entropy and that entropy levels should also relate to team performance. Communications from 40 teams that collaborated on a complex problem were coded for occurrence of problem-solving processes. We applied a sliding window entropy technique to each team's communications and specified criteria for (a) identifying data points that qualify as peaks and (b) determining which peaks were robust. We used multilevel modeling, and provide a qualitative example, to evaluate whether phases exhibit distinct distributions of communication processes. We also tested whether there was a relationship between entropy values at transition points and CPS performance. We found that a proportion of entropy peaks was robust and that the relative occurrence of communication codes varied significantly across phases. Peaks in entropy thus corresponded to qualitative shifts in teams' CPS communications, providing empirical evidence that teams exhibit phase transitions during CPS. Also, lower average levels of entropy at the phase transition points predicted better CPS performance. We specify future directions to improve understanding of phase transitions during CPS, and collaborative cognition, more broadly.

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Section: Dynamical Systems and Phase Transitionsmentioning

confidence: 99%

Problem‐Solving Phase Transitions During Team Collaboration

2017

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“…Concerning technology for high-frequency process monitoring, an important contribution has been made with the introduction of the "Synergetic Navigation System" by Schiepek & Strunk (2010). This software package is able to send out daily questionnaires that have been developed specifically for process monitoring, like the therapy process questionnaire (TPB, Schiepek, Aichhorn, & Strunk, 2012), but also outcome-related measures and other instruments.…”

Section: Introductionmentioning

confidence: 99%

Attitudes of Austrian psychotherapists towards process and outcome monitoring

Kaiser¹,

Schmutzhart²,

Laireiter³

2017

Preprint

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While monitoring systems in psychotherapy have become more common, little is known about the attitudes that mental health practitioners have towards these systems. In an online survey among 111 Austrian psychotherapists and trainees, attitudes towards therapy monitoring were measured. A well-validated questionnaire measuring attitudes towards outcome monitoring, the outcome measurement questionnaire (OMQ), was used. Clinicians' theoretical orientations as well as previous knowledge and experience with monitoring systems were associated with positive attitudes towards monitoring. Possible factors that may have led to these findings, like the views of different theoretical orientations or obstacles in Austrian public health care, are discussed.

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“…For situations where timeseries measurement is principally possible, but not at the order of several hundred data points, other complexity properties than fractal scaling can be investigated, which are indicative of IDD and suitable for shorter timeseries (e.g., Schiepek and Strunk 2010;Webber and Zbilut 1994), but whose relationship to fractal scaling has yet to be clarified.…”

Section: Interaction-dominant Dynamicsmentioning

confidence: 99%

Interaction-Dominant Causation in Mind and Brain, and Its Implication for Questions of Generalization and Replication

Wallot

Kelty-Stephen

2017

Minds & Machines

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The dominant assumption about the causal architecture of the mind is, that it is composed of a stable set of components that contribute independently to relevant observables that are employed to measure cognitive activity. This view has been called component-dominant dynamics. An alternative has been proposed, according to which the different components are not independent, but fundamentally interdependent, and are not stable basic properties of the mind, but rather an emergent feature of the mind given a particular task context. This view has been called interaction-dominant dynamics. In this paper, we review evidence for interaction-dominant dynamics as the causal architecture of the mind. We point out, that such an architecture is consistent with problems of convergence in research on the level of results and theorizing. Moreover, we point out that if interactiondominant dynamics as the causal architecture of the mind were to be true, this would naturally lead to (some degree of) problems with generalization and replicability in sciences of the mind and brain, and would probably warrant changes in the scientific practice with regard to study-design and data analysis.

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The identification of critical fluctuations and phase transitions in short term and coarse-grained time series—a method for the real-time monitoring of human change processes

Cited by 120 publications

References 27 publications

Problem‐Solving Phase Transitions During Team Collaboration

Problem‐Solving Phase Transitions During Team Collaboration

Attitudes of Austrian psychotherapists towards process and outcome monitoring

Interaction-Dominant Causation in Mind and Brain, and Its Implication for Questions of Generalization and Replication

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