scholarly journals Memorable meals: The memory-experience gap in day-to-day experiences

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0249190
Author(s):  
Karoline Villinger ◽  
Deborah R. Wahl ◽  
Harald T. Schupp ◽  
Britta Renner

Research shows that retrospective memory is often more extreme than in-the-moment experiences. While investigations into this phenomenon have mostly focused on distinct, one-time experiences, we examined it with respect to recurring day-to-day experiences in the eating domain, focusing on variables of the snapshot model—i.e., the most intense and the final experience. We used a smartphone-based Ecological Momentary Assessment to assess the food intake and eating happiness of 103 participants (82.52% female, Mage = 21.97 years) over eight days, and then calculated their best (positive peak), worst (negative peak) and final experiences. Remembered eating happiness was assessed immediately after the study (immediate recall) and after four weeks (delayed recall). A significant memory-experience gap was revealed at immediate recall (d = .53). Remembered eating happiness was predicted by the worst eating experience (β = .41, p < .001), but not by the best or final eating experience. Analyzing changes over time did not show a significant memory-experience gap at delayed recall, but did reveal a similar influence of the worst eating experience (β = .39, p < .001). Findings indicate that, in the domain of eating, retrospective memory is mainly influenced by negative experiences. Overall, the results indicate that the snapshot model is a valid conceptualization to explain recall of both outstanding and day-to-day experiences.

Buildings ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 54 ◽  
Author(s):  
Lina Engelen ◽  
Fabian Held

Studying the workplace often involves using observational, self-report recall, or focus group tools, which all have their established advantages and disadvantages. There is, however, a need for a readily available, low-invasive method that can provide longitudinal, repeated, and concurrent in-the-moment information to understand the workplace well. In this study, ecological momentary assessment (EMA) was used to collect 508 real-time responses about activities, posture, work performance, social interactions, and mood in 64 adult office workers in three Australian workplaces. The response rate was 53%, and the time to fill out the survey was 50 seconds on average. On average, the participants were sitting, standing, and walking in 84%, 9%, and 7% of survey instances, respectively. The participants reported they were working alone at their desks in 55% of all reported instances. Reported mood varied up to nine points within one person over the course of the post-occupancy observations. EMA can be used to paint a rich picture of occupants’ experiences and perceptions and to gain invaluable understanding of temporal patterns of the workplace, how the space is used, and how aspects of the workplace interact. This information can be used to make improvements to the physical and social workspaces and enhance occupants’ work performance and mood.


2017 ◽  
Vol 38 (8) ◽  
pp. 1121-1146 ◽  
Author(s):  
Christina Matz-Costa ◽  
Stephanie Cosner Berzin ◽  
Marcie Pitt-Catsouphes ◽  
Cal J Halvorsen

The ecological momentary assessment (EMA) method was used to examine the antecedents and correlates of older adults’ in-the-moment perceptions of meaning at work. Data were collected six times per day for 7 days from 30 older adults who were mostly social entrepreneurs and who were engaged in purpose work (i.e., work that addresses a social problem or issue). We found concurrent effects of two types of affective states (i.e., relaxed and energetic) and generative work behaviors (i.e., sharing information about one’s work and encouraging/inviting others into one’s work) on three measures of perceptions of meaningful work (i.e., high passion for one’s work, high sense of engagement in one’s work, and high connection to a sense of meaning in life). Feeling energetic had a lagged effect on meaningful work approximately 2.5 and 5 hr later in the day. We consider ways to foster engagement in meaningful work as a path toward healthy aging.


2021 ◽  
Author(s):  
Cheng K. Fred Wen ◽  
Doerte U. Junghaenel ◽  
David B. Newman ◽  
Stefan Schneider ◽  
Marilyn Mendez ◽  
...  

BACKGROUND Ecological Momentary Assessment (EMA) has the potential to minimize recall bias by having people report on their experiences in the moment (momentary model) or over short periods of time (coverage model). This potential hinges on the assumption that participants provide ratings based on the reporting timeframe instructions prescribed in the EMA items. However, it is unclear what timeframes participants are actually using when they answer EMA questions and whether participant training improves participants’ adherence to the reporting instructions. OBJECTIVE The objectives of this study are to investigate the reporting timeframes participants used when answering EMA questions and whether participant training improves participants’ adherence to the EMA reporting timeframe instructions. METHODS This study used telephone-based cognitive interviews to investigate this question. In a 2x2 factorial design, participants (n=100) were assigned to receive either basic or enhanced EMA training and also randomized to rate their experiences using a momentary (at the moment you were called) or coverage (since the last phone call) model. Participants received 5 calls over the course of one day to provide ratings; after each rating, participants were immediately interviewed about the timeframe that they used to answer the EMA questions. Two raters independently coded the momentary interview responses into timeframe categories (Cohen’s kappa = 0.64 (95%CI: 0.55-0.73)). RESULTS Results from the momentary conditions showed that most of the calls referred to the period during the call (28.6%) or just before the call (49.2%) to provide ratings; the remainder were from longer reporting periods. Multinomial logistic regression results indicated a significant training effect (χ2 (1, 199)=16.61, p<0.001), where the enhanced training condition yielded more reports within the intended reporting timeframes for momentary EMA reports. Cognitive interview data from the coverage model did not lend themselves to reliable coding and were not analyzed. CONCLUSIONS These findings provide the first evidence about adherence to EMA instructions to reporting periods, and that enhanced participant training improves adherence to the timeframe specified in momentary EMA studies.


Author(s):  
Heather T. Schatten ◽  
Kenneth J. D. Allen ◽  
Michael F. Armey

As emotion is a dynamic construct, ecological momentary assessment (EMA) methods, which gather data at multiple time points in individuals’ real-world environments, in the moment, are particularly well suited to measure emotion dysregulation and related constructs. EMA methods can identify contextual events that prompt or follow an emotional response. This chapter provides an overview of traditional methods of studying emotion dysregulation and how EMA can be used to capture emotion dysregulation in daily life, both within and independent of psychiatric diagnoses. It reviews the literature on emotion dysregulation and related constructs within specific diagnoses (e.g., depression, bipolar disorder, borderline personality disorder, and eating disorders) and behaviors (e.g., suicide, nonsuicidal self-injury, and alcohol use). Finally, it discusses future directions in EMA research, as well as its implications for psychological treatment.


2018 ◽  
Author(s):  
Aidan G.C. Wright ◽  
Johannes Zimmermann

Ambulatory assessment (also known as ecological momentary assessment) has enjoyed enthusiastic implementation in psychological research. The ability to assess thoughts, feelings, behavior, physiology, and context intensively and repeatedly in the moment in an individual’s natural ecology affords access to data that can answer exciting questions about sequences of events and dynamic processes in daily life. Ambulatory assessment also holds unique promise for developing personalized models of individuals (i.e., precision or person-specific assessment) that might be transformative for applied settings such as clinical practice. However, successfully translating ambulatory assessment from bench to bedside is challenging because of the inherent tension between idiographic and nomothetic principles of measurement. We argue that the value of applied ambulatory assessment will be most fully realized by balancing the ability to develop personalized models with ensuring comparability among individuals.


10.2196/11845 ◽  
2019 ◽  
Vol 6 (5) ◽  
pp. e11845 ◽  
Author(s):  
Aaron M Mofsen ◽  
Thomas L Rodebaugh ◽  
Ginger E Nicol ◽  
Colin A Depp ◽  
J Philip Miller ◽  
...  

A major problem in mental health clinical trials, such as depression, is low assay sensitivity in primary outcome measures. This has contributed to clinical trial failures, resulting in the exodus of the pharmaceutical industry from the Central Nervous System space. This reduced assay sensitivity in psychiatry outcome measures stems from inappropriately broad measures, recall bias, and poor interrater reliability. Limitations in the ability of traditional measures to differentiate between the trait versus state-like nature of individual depressive symptoms also contributes to measurement error in clinical trials. In this viewpoint, we argue that ecological momentary assessment (EMA)—frequent, real time, in-the-moment assessments of outcomes, delivered via smartphone—can both overcome these psychometric challenges and reduce clinical trial failures by increasing assay sensitivity and minimizing recall and rater bias. Used in this manner, EMA has the potential to further our understanding of treatment response by allowing for the assessment of dynamic interactions between treatment and distinct symptom response.


2020 ◽  
Vol 32 (3) ◽  
pp. 257-278
Author(s):  
Kevin Doherty ◽  
Andreas Balaskas ◽  
Gavin Doherty

Abstract Ecological Momentary Assessment (EMA) methods and technologies, designed to support the self-report of experience in the moment of daily life, have long been considered poised to revolutionize human-centred research, the practice of design and mental healthcare. The history of EMA is inextricably linked to technology, and mobile devices embody many of the characteristics required to support these methods. However, significant barriers to the design and adoption of these systems remain, including challenges of user engagement, reporting burden, data validity and honest disclosure. While prior research has examined the feasibility of a variety of EMA systems, few reviews have attended to their design. Through inter-disciplinary narrative literature review (n = 342), this paper presents a characterization of the EMA technology design space, drawing upon a diverse set of literatures, contexts, applications and demographic groups. This paper describes the options and strategies available to the EMA systems designer, with an eye towards supporting the design and deployment of EMA technologies for research and clinical practice.


Author(s):  
Maryam Hussain ◽  
Carmen Kho ◽  
Alexandra Main ◽  
Matthew J. Zawadzki

AbstractSleep problems and poorer well-being may be particularly salient for Latino/a college students as they tend to experience sociocultural adjustments during this transitory time. Social connections, a correlate of health, change moment-to-moment for college students and may be experienced differently for people who more strongly endorse horizontal collectivist cultural values. We used ecological momentary assessment (EMA) to examine how in-the-moment social connections influence in-the-moment health, and how horizontal collectivism moderates the moment-to-moment associations. Self-identified Latino/a college students (n = 221) completed a demographic information and cultural values questionnaire and then responded to EMA measures on their social connections, affective and subjective well-being, and sleep for 14 consecutive days. Better in-the-moment social connections associated with better health. Horizontal collectivism moderated some, but not all associations between social connections and health. Social connections are multidimensional and differently predict in-the-moment health among Latino/a college students who more strongly endorse horizontal collectivistic values. We discuss implications for identifying vulnerable well-being moments among this understudied population.


10.2196/13191 ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. e13191 ◽  
Author(s):  
Deborah Ronja Wahl ◽  
Karoline Villinger ◽  
Michael Blumenschein ◽  
Laura Maria König ◽  
Katrin Ziesemer ◽  
...  

Background Why do we eat? Our motives for eating are diverse, ranging from hunger and liking to social norms and affect regulation. Although eating motives can vary from eating event to eating event, which implies substantial moment-to-moment differences, current ways of measuring eating motives rely on single timepoint questionnaires that assess eating motives as situation-stable dispositions (traits). However, mobile technologies including smartphones allow eating events and motives to be captured in real time and real life, thus capturing experienced eating motives in-the-moment (states). Objective This study aimed to examine differences between why people think they eat (trait motives) and why they eat in the moment of consumption (state motives) by comparing a dispositional (trait) and an in-the-moment (state) assessment of eating motives. Methods A total of 15 basic eating motives included in The Eating Motivation Survey (ie, liking, habit, need and hunger, health, convenience, pleasure, traditional eating, natural concerns, sociability, price, visual appeal, weight control, affect regulation, social norms, and social image) were assessed in 35 participants using 2 methodological approaches: (1) a single timepoint dispositional assessment and (2) a smartphone-based ecological momentary assessment (EMA) across 8 days (N=888 meals) capturing eating motives in the moment of eating. Similarities between dispositional and in-the-moment eating motive profiles were assessed according to 4 different indices of profile similarity, that is, overall fit, shape, scatter, and elevation. Moreover, a visualized person × motive data matrix was created to visualize and analyze between- and within-person differences in trait and state eating motives. Results Similarity analyses yielded a good overall fit between the trait and state eating motive profiles across participants, indicated by a double-entry intraclass correlation of 0.52 (P<.001). However, although trait and state motives revealed a comparable rank order (r=0.65; P<.001), trait motives overestimated 12 of 15 state motives (P<.001; d=1.97). Specifically, the participants assumed that 6 motives (need and hunger, price, habit, sociability, traditional eating, and natural concerns) are more essential for eating than they actually were in the moment (d>0.8). Furthermore, the visualized person × motive data matrix revealed substantial interindividual differences in intraindividual motive profiles. Conclusions For a comprehensive understanding of why we eat what we eat, dispositional assessments need to be extended by in-the-moment assessments of eating motives. Smartphone-based EMAs reveal considerable intra- and interindividual differences in eating motives, which are not captured by single timepoint dispositional assessments. Targeting these differences between why people think they eat what they eat and why they actually eat in the moment may hold great promise for tailored mobile health interventions facilitating behavior changes.


2018 ◽  
Author(s):  
Deborah Ronja Wahl ◽  
Karoline Villinger ◽  
Michael Blumenschein ◽  
Laura Maria König ◽  
Katrin Ziesemer ◽  
...  

BACKGROUND Why do we eat? Our motives for eating are diverse, ranging from hunger and liking to social norms and affect regulation. Although eating motives can vary from eating event to eating event, which implies substantial moment-to-moment differences, current ways of measuring eating motives rely on single timepoint questionnaires that assess eating motives as situation-stable dispositions (traits). However, mobile technologies including smartphones allow eating events and motives to be captured in real time and real life, thus capturing experienced eating motives in-the-moment (states). OBJECTIVE This study aimed to examine differences between why people think they eat (trait motives) and why they eat in the moment of consumption (state motives) by comparing a dispositional (trait) and an in-the-moment (state) assessment of eating motives. METHODS A total of 15 basic eating motives included in The Eating Motivation Survey (ie, liking, habit, need and hunger, health, convenience, pleasure, traditional eating, natural concerns, sociability, price, visual appeal, weight control, affect regulation, social norms, and social image) were assessed in 35 participants using 2 methodological approaches: (1) a single timepoint dispositional assessment and (2) a smartphone-based ecological momentary assessment (EMA) across 8 days (N=888 meals) capturing eating motives in the moment of eating. Similarities between dispositional and in-the-moment eating motive profiles were assessed according to 4 different indices of profile similarity, that is, overall fit, shape, scatter, and elevation. Moreover, a visualized person × motive data matrix was created to visualize and analyze between- and within-person differences in trait and state eating motives. RESULTS Similarity analyses yielded a good overall fit between the trait and state eating motive profiles across participants, indicated by a double-entry intraclass correlation of 0.52 (<italic>P</italic>&lt;.001). However, although trait and state motives revealed a comparable rank order (<italic>r</italic>=0.65; <italic>P</italic>&lt;.001), trait motives overestimated 12 of 15 state motives (<italic>P</italic>&lt;.001; <italic>d</italic>=1.97). Specifically, the participants assumed that 6 motives (need and hunger, price, habit, sociability, traditional eating, and natural concerns) are more essential for eating than they actually were in the moment (<italic>d</italic>&gt;0.8). Furthermore, the visualized person × motive data matrix revealed substantial interindividual differences in intraindividual motive profiles. CONCLUSIONS For a comprehensive understanding of why we eat what we eat, dispositional assessments need to be extended by in-the-moment assessments of eating motives. Smartphone-based EMAs reveal considerable intra- and interindividual differences in eating motives, which are not captured by single timepoint dispositional assessments. Targeting these differences between why people think they eat what they eat and why they actually eat in the moment may hold great promise for tailored mobile health interventions facilitating behavior changes.


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