Psychological Rhythmicities

Hessler, Eric E.; Finan, Patrick H.; Amazeen, Polemnia G.

doi:10.1007/978-1-4614-4998-0_8

Cited by 4 publications

(5 citation statements)

References 59 publications

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“…For example, a couple may start off in a co-escalation state, then move into a co-dysregulated state, and then end in a co-regulatory state. In the standard CLO model, such as we present here, the oscillations are treated as having uniform dampening or amplification effects on all data points (Hessler et al, 2013). A regime switching model, however, could more accurately represent the complexity of reality by allowing for sequences of different dynamic patterns to emerge across the duration of one interaction.…”

Section: Discussionmentioning

confidence: 99%

“…With too few observations it is impossible to model faster frequency oscillations, but with too many observations it is easy to mistake random noise for systematic fast oscillations. Second, if emotional oscillations are relevant to the research question, then classic approaches, such as repeated measures regression, temporal multilevel models, growth modeling, or sequential analyses are inadequate (Boker & Nesselroade, 2002; Butner et al, 2005; Hessler, Finan, & Amazeen, 2013). These methods can assess the general emotional tone of an interaction, trajectories of change across time, or within- and between-person concurrent associations (synchrony) and time-lagged associations (transmission), as well as moderators of these associations (Butler, 2011; Randall, Post, Reed, & Butler, 2013; Reed, Randall, Post, & Butler, 2013).…”

Section: Modeling Interpersonal Emotional Dynamics With Coupled Lineamentioning

confidence: 99%

“…In the present study, coupling is defined as the between-partner difference score, (i.e., partner emotion rating – own emotion rating). A coupling parameter of zero (κ = 0) indicates that the partners behave independently; when κ is nonzero, there is coupling between the partners (Hessler et al, 2013). Partners will be pulled into phase (as pictured in Figure 1) if the signs of their coupling terms are opposite (i.e., the man has a negative coupling parameter and the woman has a positive one, or vice versa).…”

Section: Modeling Interpersonal Emotional Dynamics With Coupled Lineamentioning

confidence: 99%

See 2 more Smart Citations

Distinguishing emotional coregulation from codysregulation: An investigation of emotional dynamics and body weight in romantic couples.

Reed¹,

Barnard²,

Butler³

2015

Emotion

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Well-regulated emotions, both within people and between relationship partners, play a key role in facilitating health and well-being. The present study examined 39 heterosexual couples’ joint weight status (both partners are healthy-weight, both overweight, one healthy-weight and one overweight) as a predictor of two interpersonal emotional patterns during a discussion of their shared lifestyle choices. The first pattern, co-regulation, is one in which partners’ coupled emotions show a dampening pattern over time and ultimately return to homeostatic levels. The second, co-dysregulation, is one in which partners’ coupled emotions are amplified away from homeostatic balance. We demonstrate how a coupled linear oscillator (CLO) model (Butner, Amazeen, & Mulvey, 2005) can be used to distinguish co-regulation from co-dysregulation. As predicted, healthy-weight couples and mixed-weight couples in which the man was heavier than the woman displayed co-regulation, but overweight couples and mixed-weight couples in which the woman was heavier showed co-dysregulation. These results suggest that heterosexual couples in which the woman is overweight may face formidable co-regulatory challenges that could undermine both partners’ well-being. The results also demonstrate the importance of distinguishing between various interpersonal emotional dynamics for understanding connections between interpersonal emotions and health.

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Section: Discussionmentioning

confidence: 99%

Section: Modeling Interpersonal Emotional Dynamics With Coupled Lineamentioning

confidence: 99%

Section: Modeling Interpersonal Emotional Dynamics With Coupled Lineamentioning

confidence: 99%

See 1 more Smart Citation

Distinguishing emotional coregulation from codysregulation: An investigation of emotional dynamics and body weight in romantic couples.

Reed¹,

Barnard²,

Butler³

2015

Emotion

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“…For researchers with a particular interest in estimating the within ‐person relation between cycles in X and cycles in Y (i.e., whether there is a lead–lag relation between cycles in X and cycles in Y ), the within ‐person relation between cycles in X and cycles in Y can be estimated separately for each individual using coupled oscillation models under the dynamical systems framework. The coupled oscillation model can be combined with the multilevel model to investigate the between‐person variability in the within ‐person relation between cycles in X and cycles in Y ; moderators of the within‐person relation can be examined (for a detailed explanation, see Hessler, Finan, & Amazeen, ).…”

Section: Discussionmentioning

confidence: 99%

Weekly Cycles in Daily Report Data: An Overlooked Issue

Liu

West

2015

Journal of Personality

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Daily diaries and other everyday experience methods are increasingly used to study relationships between two time-varying variables X and Y. Although daily data potentially often have weekly cyclical patterns (e.g., stress may be higher on weekdays and lower on weekends), the majority of daily diary studies have ignored this possibility. In this study, we investigated the effect of ignoring existing weekly cycles. We reanalyzed an empirical dataset (stress and alcohol consumption) and performed Monte Carlo simulations to investigate the impact of omitting weekly cycles. In the empirical dataset, ignoring cycles led to the inference of a significant within-person X-Y relation whereas modeling cycles suggested that this relationship did not exist. Simulation results indicated that ignoring cycles that existed in both X and Y led to bias in the estimated within-person X-Y relationship. The amount and direction of bias depended on the magnitude of the cycles, magnitude of the true within-person X-Y relation, and synchronization of the cycles. We encourage researchers conducting daily diary studies to address potential weekly cycles in their data. We provide guidelines for detecting and modeling cycles to remove their influence and discuss challenges of causal inference in daily experience studies.

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“…Im Rahmen der vorliegenden Arbeit umfasst der Begriff der Kopplung, dass Oszillationen in einem Prozess (beispielsweise Änderungen in der Amplitude und/oder der Geschwindigkeit der Oszillation) in parallelen oder entgegengesetzten Änderungen in einer anderen Variable resultieren (Hessler, Finan, & Amazeen, 2013). Weiterhin ist es -wenn Zeitreihen zweier Variablen betrachtet werdenmöglich, dass Co-Variationen zwischen den Variablen unmittelbar oder aber erst mit einem zeitlichen Versatz (lag) auftreten ("Time-Lag Covariation").…”

Section: Formen Der Kopplungunclassified

Ist der Schlaf der Hüter des protektiven Schmerzes?

Strömel-Scheder

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Die vorliegende Dissertation beschäftigte sich mit der Frage, ob Schlaf als „Hüter“ des protektiven Schmerzes betrachtet werden kann. Ein Ziel war es, zu prüfen, ob Erholungsschlaf das Schmerzsystem – nach einer Hyperalgesie durch Schlafentzug – wieder auf einen Normalzustand zurücksetzen kann. Die Befunde eines systematischen Literaturreviews sowie einer empirischen Studie, die sich den Effekten von Schlafentzug und Erholungsschlaf auf Schmerz widmeten, konnten dies untermauern und wiesen auf eine unmittelbare Re-Normalisierung der Schmerzsensitivität nach Erholungsschlaf hin. Im Hinblick auf Parameter der endogenen Schmerzmodulation (temporale Schmerzsummation, Conditioned Pain Modulation) ergaben sich keine systematischen Effekte der Schlafmanipulationen. Als weiteres Ziel wurde – unter Nutzung der Erkenntnisse zu Erholungsschlafeffekten auf Schmerz – die Schlaf-Schmerz-Kopplung näher untersucht, vor allem im Hinblick darauf, ab welchem Variabilitätsausmaß und in welcher Form eine Kopplung zwischen Schlaf und Schmerz auftritt. Im Rahmen zweier empirischer Studien zeigten sich in einem milden/moderaten Variabilitätsbereich erste Zusammenhänge zwischen Schlaf und der Schmerzsensitivität und in einem hohen Variabilitätsbereich schließlich eine Kopplung beider, was für eine schwellenabhängige Kopplung spricht. Zusammenfassend weist die vorliegende Dissertation darauf hin, dass Schlaf als „Hüter“ der Schmerzsensitivität betrachtet werden kann und dass Schlaf einen wesentlichen Beitrag zur Aufrechterhaltung und Wiederherstellung einer normalen Funktionsfähigkeit protektiven Schmerzes leistet.

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Psychological Rhythmicities

Cited by 4 publications

References 59 publications

Distinguishing emotional coregulation from codysregulation: An investigation of emotional dynamics and body weight in romantic couples.

Distinguishing emotional coregulation from codysregulation: An investigation of emotional dynamics and body weight in romantic couples.

Weekly Cycles in Daily Report Data: An Overlooked Issue

Ist der Schlaf der Hüter des protektiven Schmerzes?

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