scholarly journals Differences in Affective Dynamics Among Eating-Disorder Diagnostic Groups

2020 ◽  
Vol 8 (5) ◽  
pp. 857-871
Author(s):  
Gail A. Williams-Kerver ◽  
Stephen A. Wonderlich ◽  
Ross D. Crosby ◽  
Li Cao ◽  
Kathryn E. Smith ◽  
...  
Keyword(s):  
Eating Disorder ◽  
Ecological Momentary Assessment ◽  
Mixed Models ◽  
Emotional Experience ◽  
Affect Intensity ◽  
Emotion Differentiation ◽  
Affective Experiences ◽  
Ecological Momentary ◽  
Ema Data ◽  
Momentary Assessment

Emotion-regulation theories suggest that affect intensity is crucial in the development and maintenance of eating disorders. However, other aspects of emotional experience, such as lability, differentiation, and inertia, are not as well understood. This study is the first to use ecological momentary assessment (EMA) to examine differences in several daily negative affect (NA) indicators among adults diagnosed with anorexia nervosa (AN), bulimia nervosa (BN), or binge-eating disorder (BED). We used EMA data from three large studies to run a series of linear mixed models; the results showed that participants in the AN and BN groups experienced significantly greater NA intensity and better emotion differentiation than participants in the BED group. Alternatively, the BN group demonstrated significantly greater NA lability than the AN group and greater NA inertia than the BED group. These results suggest that several daily affective experiences differ among eating-disorder diagnostic groups and have implications toward distinct conceptualizations and treatments.

scholarly journals Examining convergence of retrospective and ecological momentary assessment measures of negative affect and eating disorder behaviors

2014 ◽  
Vol 48 (3) ◽  
pp. 305-311 ◽  
Author(s):  
Joseph A. Wonderlich ◽  
Jason M. Lavender ◽  
Stephen A. Wonderlich ◽  
Carol B. Peterson ◽  
Scott J. Crow ◽  
...  
Keyword(s):  
Eating Disorder ◽  
Negative Affect ◽  
Ecological Momentary Assessment ◽  
Assessment Measures ◽  
Ecological Momentary ◽  
Momentary Assessment ◽  
Eating Disorder Behaviors

scholarly journals Affect fluctuations examined with ecological momentary assessment in patients with current or remitted depression and anxiety disorders

2020 ◽  
pp. 1-10 ◽  
Author(s):  
R. A. Schoevers ◽  
C. D. van Borkulo ◽  
F. Lamers ◽  
M.N. Servaas ◽  
J. A. Bastiaansen ◽  
...  
Keyword(s):  
Anxiety Disorder ◽  
Anxiety Disorders ◽  
Ecological Momentary Assessment ◽  
Affect Regulation ◽  
Depression And Anxiety ◽  
Remitted Depression ◽  
Ecological Momentary ◽  
Ema Data ◽  
Momentary Assessment ◽  
A Current

Abstract Background There is increasing interest in day-to-day affect fluctuations of patients with depressive and anxiety disorders. Few studies have compared repeated assessments of positive affect (PA) and negative affect (NA) across diagnostic groups, and fluctuation patterns were not uniformly defined. The aim of this study is to compare affect fluctuations in patients with a current episode of depressive or anxiety disorder, in remitted patients and in controls, using affect instability as a core concept but also describing other measures of variability and adjusting for possible confounders. Methods Ecological momentary assessment (EMA) data were obtained from 365 participants of the Netherlands Study of Depression and Anxiety with current (n = 95), remitted (n = 178) or no (n = 92) DSM-IV defined depression/anxiety disorder. For 2 weeks, five times per day, participants filled-out items on PA and NA. Affect instability was calculated as the root mean square of successive differences (RMSSD). Tests on group differences in RMSSD, within-person variance, and autocorrelation were performed, controlling for mean affect levels. Results Current depression/anxiety patients had the highest affect instability in both PA and NA, followed by remitters and then controls. Instability differences between groups remained significant when controlling for mean affect levels, but differences between current and remitted were no longer significant. Conclusions Patients with a current disorder have higher instability of NA and PA than remitted patients and controls. Especially with regard to NA, this could be interpreted as patients with a current disorder being more sensitive to internal and external stressors and having suboptimal affect regulation.

The use of ecological momentary assessment approaches in eating disorder research

2001 ◽  
Vol 30 (1) ◽  
pp. 83-95 ◽  
Author(s):  
Joshua Smyth ◽  
Stephen Wonderlich ◽  
Ross Crosby ◽  
Raymond Miltenberger ◽  
James Mitchell ◽  
...  
Keyword(s):  
Eating Disorder ◽  
Ecological Momentary Assessment ◽  
Ecological Momentary ◽  
Momentary Assessment

scholarly journals Are Retrospective Assessments Means of People’s Experiences? Accounting for Interpersonal and Intrapersonal Variability when Comparing Retrospective Assessment Data to Ecological Momentary Assessment Data

2021 ◽  
Author(s):  
IJsbrand Leertouwer ◽  
Noémi Katalin Schuurman ◽  
Jeroen Vermunt
Keyword(s):  
Ecological Momentary Assessment ◽  
Assessment Data ◽  
Interindividual Differences ◽  
Retrospective Assessment ◽  
The Mean ◽  
The Difference ◽  
Ecological Momentary ◽  
Ema Data ◽  
Momentary Assessment ◽  
Intrapersonal Variability

Retrospective Assessment (RA) scores are often found to be higher than the mean of Ecological Momentary Assessment (EMA) scores about a concurrent period. This difference is generally interpreted as bias towards salient experiences in RA. During RA, participants are often asked to summarize their experiences in unspecific terms, which may indeed facilitate bias. At least in this unspecific form, the summary that participants apply to their remembered experiences can take many different forms. In this study, we reanalyzed an existing dataset (N = 92) using a repeated N = 1 approach. We reported on interindividual differences between EMA data and RA score, and assessed for each participant whether it was likely that their RA score was an approximation of the mean of their experiences as captured by their EMA data. We found considerable interpersonal differences in the difference between EMA scores and RA scores, as well as some extreme cases. Furthermore, for a considerable part of the sample (n = 46 for positive affect, n = 60 for negative affect), we did not reject the null hypothesis that their RA score represented the mean of their experiences as captured by their EMA data. We conclude that in its current unspecific form, RA may facilitate bias, although not for everyone. Future studies may determine whether more specific forms of RA reduce bias, while acknowledging interindividual differences.

Statistical Considerations for Analyzing Ecological Momentary Assessment Data

2021 ◽  
pp. 1-17
Author(s):  
Jacob J. Oleson ◽  
Michelle A. Jones ◽  
Erik J. Jorgensen ◽  
Yu-Hsiang Wu
Keyword(s):  
Ecological Momentary Assessment ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
General Purpose ◽  
Statistical Characteristics ◽  
Statistical Approaches ◽  
Survey Responses ◽  
Ecological Momentary ◽  
Ema Data ◽  
Momentary Assessment

Purpose: The analysis of Ecological Momentary Assessment (EMA) data can be difficult to conceptualize due to the complexity of how the data are collected. The goal of this tutorial is to provide an overview of statistical considerations for analyzing observational data arising from EMA studies. Method: EMA data are collected in a variety of ways, complicating the statistical analysis. We focus on fundamental statistical characteristics of the data and general purpose statistical approaches to analyzing EMA data. We implement those statistical approaches using a recent study involving EMA. Results: The linear or generalized linear mixed-model statistical approach can adequately capture the challenges resulting from EMA collected data if properly set up. Additionally, while sample size depends on both the number of participants and the number of survey responses per participant, having more participants is more important than the number of responses per participant. Conclusion: Using modern statistical methods when analyzing EMA data and adequately considering all of the statistical assumptions being used can lead to interesting and important findings when using EMA. Supplemental Material https://doi.org/10.23641/asha.17155961

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