affect dynamics
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2021 ◽  
Vol 12 ◽  
Author(s):  
Robert R. McCrae

Some accounts of the evolution of music suggest that it emerged from emotionally expressive vocalizations and serves as a necessary counterweight to the cognitive elaboration of language. Thus, emotional expression appears to be intrinsic to the creation and perception of music, and music ought to serve as a model for affect itself. Because music exists as patterns of changes in sound over time, affect should also be seen in patterns of changing feelings. Psychologists have given relatively little attention to these patterns. Results from statistical approaches to the analysis of affect dynamics have so far been modest. Two of the most significant treatments of temporal patterns in affect—sentics and vitality affects have remained outside mainstream emotion research. Analysis of musical structure suggests three phenomena relevant to the temporal form of emotion: affect contours, volitional affects, and affect transitions. I discuss some implications for research on affect and for exploring the evolutionary origins of music and emotions.


2021 ◽  
Author(s):  
Levente Rónai ◽  
Bertalan Polner

Background: Temporal patterns of affective functioning such as emotional inertia and instability may indicate changes in emotion regulation that predict depression. However, affect dynamics’ incremental validity over affect intensity and exposure to stressors in predicting depression has been questioned.Methods: We collected longitudinal data regarding momentary affective states (measured multiple times a day), perceived stressors and depressive symptoms (measured every three days) from a general population sample during the COVID-19 pandemic’s first wave in Hungary. The final dataset included 7165 affective states surveys from 125 participants, which were aggregated in 464 three-day measurement windows. Using multilevel models, we explored the unique effects of within-person changes in mean level, inertia, and instability of negative affective states (NA), and stressor-exposure on two domains of depression (anhedonia and negative mood and thoughts) within the three-day windows.Results: Within-person increases in NA inertia and NA instability showed significant positive associations with negative mood and thoughts. These effects did not remain significant after adjusting for mean levels of NA. Multilevel mediation analysis revealed that within individuals, NA inertia and instability indirectly predicted negative mood and thoughts through elevated NA mean.Limitations: The application of self-report questionnaires might bias the results, and the overrepresentation of female participants could limit the generalizability of the findings.Conclusions: Specific patterns of temporal affective functioning are indirect predictors of depressive symptoms at the within-individual level. Our findings may facilitate automated depression risk assessment on the basis of simple affective time series.


2021 ◽  
Author(s):  
Lilian Yanqing Li ◽  
Jason Schiffman ◽  
Elizabeth A Martin

There is a critical need for identifying time-sensitive and cost-effective markers of psychosis riskearly in the illness course. One solution may lie in affect dynamics, or the fluctuations of affect across time, which have been demonstrated to predict transitions in psychopathology. Across three studies, the current research is the first to comprehensively investigate affect dynamics in relation to subthreshold positive symptoms (perceptual aberration and magical ideation) and negative symptoms (social anhedonia) of the psychosis spectrum. Across multiple timescales and contexts, affect dynamics were modeled from inexpensive laboratory paradigms and social media text. Findings provided strong evidence for positive symptoms linked to heightened magnitude and frequency of affective fluctuations in response to emotional materials. Alternatively, negative symptoms showed modest association with heightened persistence of baseline states. These affect dynamic signatures of psychosis risk provide insight on the distinct developmental pathways to psychosis and could facilitate current risk detection approaches.


Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1409
Author(s):  
Alexei D. Kiselev ◽  
Ranim Ali ◽  
Andrei V. Rybin

In this paper, we consider the thermal bath Lindblad master equation to describe the quantum nonunitary dynamics of quantum states in a multi-mode bosonic system. For the two-mode bosonic system interacting with an environment, we analyse how both the coupling between the modes and the coupling with the environment characterised by the frequency and the relaxation rate vectors affect dynamics of the entanglement. We discuss how the revivals of entanglement can be induced by the dynamic coupling between the different modes. For the system, initially prepared in a two-mode squeezed state, we find the logarithmic negativity as defined by the magnitude and orientation of the frequency and the relaxation rate vectors. We show that, in the regime of finite-time disentanglement, reorientation of the relaxation rate vector may significantly increase the time of disentanglement.


2021 ◽  
Author(s):  
Zahra Mousavi ◽  
Jocelyn Lai ◽  
Katharine Simon ◽  
Alexander P. Rivera ◽  
Asal Yunusova ◽  
...  

BACKGROUND Sleep disturbance is a transdiagnostic risk factor so prevalent among young adults it is considered a public health epidemic, exacerbated by the COVID-19 pandemic. Sleep may contribute to mental health via affect dynamics. Prior literature on contribution of sleep to affect is largely based on correlational studies or experiments that do not generalize to the daily lives of young adults. Furthermore, the literature examining the associations between sleep variability and affect dynamics remains scant. OBJECTIVE In an ecologically valid context, using an intensive longitudinal design, we aimed to assess the daily and long-term associations between sleep patterns and affect dynamics among young adults during the COVID-19 pandemic. METHODS College student participants (N=20, 65% female) wore an Oura ring continuously for 3-months to measure sleep patterns, such as average and variability in total sleep time (TST), wake after sleep onset (WASO), sleep efficiency (SE), and sleep onset latency (SOL), resulting in 1173 unique observations. We administered a daily ecological momentary assessment (EMA) using a mobile health app to evaluate positive (PA) and negative affect (NA), and COVID-worry once per day. RESULTS Participants with higher SOL and TST on the prior day had lower PA the next day. Further, higher average TST across the 3-month period predicted lower average PA. TST variability predicted higher affect variability across all affect domains. CONCLUSIONS Fluctuating sleep patterns are associated with affect dynamics at daily and long-term scales. Low PA and affect variability may be potential pathways through which sleep has implications for mental health.


2021 ◽  
Author(s):  
Sergio Pirla ◽  
Maxime Taquet ◽  
Jordi Quoidbach

A fast-growing body of evidence from experience sampling studies suggests that affect dynamics are associated with well-being and psychological health. But heterogeneity in experience sampling approaches impedes reproducibility and scientific progress. Leveraging a large dataset of 7016 individuals, each providing over 50 affect reports, we introduce an empirically-derived framework to help researchers design well-powered and efficient experience sampling studies. Our research reveals three general principles. First, a sample of 200 participants and 20 observations per person yields sufficient power to detect medium size associations for most affect dynamic measures. Second, for trait and time-independent variability measures of affect (e.g., S.D.), distant sampling study designs (i.e., a few daily measurements spread out over several weeks) leads to more accurate estimates than close sampling study designs (i.e., several daily measurements concentrated over a few days), whereas differences in accuracy across sampling methods were inconsistent and of little practical significance for temporally dependent affect dynamic measures (i.e., RMSSD, autocorrelation coefficient, TKEO, and PAC). Third, across all affect dynamics measures, sampling exclusively on specific days or time windows leads to little to no improvement over sampling at random times. Because the ideal sampling approach varies for each affect dynamics measure, we provide a companion R-package, an online calculator, and a series of benchmark effect sizes to help researchers address three fundamental how’s of experience-sampling: How many participants to recruit? How often to solicit them? And for how long?


SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A78-A78
Author(s):  
Zahra Mousavi ◽  
Jocelyn Lai ◽  
Asal Yunusova ◽  
Alexander Rivera ◽  
Sirui Hu ◽  
...  

Abstract Introduction Sleep disturbance is a transdiagnostic risk factor that is so prevalent among emerging adults it is considered to be a public health epidemic. For emerging adults, who are already at greater risk for psychopathology, the COVID-19 pandemic has disrupted daily routines, potentially changing sleep patterns and heightening risk factors for the emergence of affective dysregulation, and consequently mood-related disturbances. This study aimed to determine whether variability in sleep patterns across a 3-month period was associated with next-day positive and negative affect, and affective dynamics, proximal affective predictors of depressive symptoms among young adults during the pandemic. Methods College student participants (N=20, 65% female, Mage=19.80, SDage=1.0) wore non-invasive wearable devices (the Oura ring https://ouraring.com/) continuously for a period of 3-months, measuring sleep onset latency, sleep efficiency, total sleep, and time spent in different stages of sleep (light, deep and rapid eye movement). Participants reported daily PA and NA using the Positive and Negative Affect Schedule on a 0-100 scale to report on their affective state. Results Multilevel models specifying a within-subject process of the relation between sleep and affect revealed that participants with higher sleep onset latency (b= -2.98, p<.01) and sleep duration on the prior day (b= -.35, p=.01) had lower PA the next day. Participants with longer light sleep duration had lower PA (b= -.28, p=.02), whereas participants with longer deep sleep duration had higher PA (b= .36, p=.02) the next day. On days with higher total sleep, participants experienced lower NA compared to their own average (b= -.01, p=.04). Follow-up exploratory bivariate correlations revealed significant associations between light sleep duration instability and higher instability in both PA and NA, whereas higher deep sleep duration was linked with lower instability in both PA and NA (all ps< .05). In the full-length paper these analyses will be probed using linear regressions controlling for relevant covariates (main effects of sleep, sex/age/ethnicity). Conclusion Sleep, an important transdiagnostic health outcome, may contribute to next-day PA and NA. Sleep patterns predict affect dynamics, which may be proximal predictors of mood disturbances. Affect dynamics may be one potential pathway through which sleep has implications for health disparities. Support (if any):


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