scholarly journals Technological Ecological Momentary Assessment Tools to Study Type 1 Diabetes in Youth: Viewpoint of Methodologies

JMIR Diabetes ◽  
10.2196/27027 ◽  
2021 ◽  
Vol 6 (2) ◽  
pp. e27027
Author(s):  
Mary Katherine Ray ◽  
Alana McMichael ◽  
Maria Rivera-Santana ◽  
Jacob Noel ◽  
Tamara Hershey
Keyword(s):  
Type 1 Diabetes ◽  
Ecological Momentary Assessment ◽  
Diabetes Care ◽  
Daily Life ◽  
Blood Pressure Monitoring ◽  
Assessment Tools ◽  
Personal Digital Assistants ◽  
Ecological Momentary ◽  
Momentary Assessment

Type 1 diabetes (T1D) is one of the most common chronic childhood diseases, and its prevalence is rapidly increasing. The management of glucose in T1D is challenging, as youth must consider a myriad of factors when making diabetes care decisions. This task often leads to significant hyperglycemia, hypoglycemia, and glucose variability throughout the day, which have been associated with short- and long-term medical complications. At present, most of what is known about each of these complications and the health behaviors that may lead to them have been uncovered in the clinical setting or in laboratory-based research. However, the tools often used in these settings are limited in their ability to capture the dynamic behaviors, feelings, and physiological changes associated with T1D that fluctuate from moment to moment throughout the day. A better understanding of T1D in daily life could potentially aid in the development of interventions to improve diabetes care and mitigate the negative medical consequences associated with it. Therefore, there is a need to measure repeated, real-time, and real-world features of this disease in youth. This approach is known as ecological momentary assessment (EMA), and it has considerable advantages to in-lab research. Thus, this viewpoint aims to describe EMA tools that have been used to collect data in the daily lives of youth with T1D and discuss studies that explored the nuances of T1D in daily life using these methods. This viewpoint focuses on the following EMA methods: continuous glucose monitoring, actigraphy, ambulatory blood pressure monitoring, personal digital assistants, smartphones, and phone-based systems. The viewpoint also discusses the benefits of using EMA methods to collect important data that might not otherwise be collected in the laboratory and the limitations of each tool, future directions of the field, and possible clinical implications for their use.

scholarly journals Technological Ecological Momentary Assessment Tools to Study Type 1 Diabetes in Youth: Viewpoint of Methodologies (Preprint)

2021 ◽  
Author(s):  
Mary Katherine Ray ◽  
Alana McMichael ◽  
Maria Rivera-Santana ◽  
Jacob Noel ◽  
Tamara Hershey
Keyword(s):  
Type 1 Diabetes ◽  
Ecological Momentary Assessment ◽  
Diabetes Care ◽  
Daily Life ◽  
Blood Pressure Monitoring ◽  
Assessment Tools ◽  
Personal Digital Assistants ◽  
Ecological Momentary ◽  
Momentary Assessment

UNSTRUCTURED Type 1 diabetes (T1D) is one of the most common chronic childhood diseases, and its prevalence is rapidly increasing. The management of glucose in T1D is challenging, as youth must consider a myriad of factors when making diabetes care decisions. This task often leads to significant hyperglycemia, hypoglycemia, and glucose variability throughout the day, which have been associated with short- and long-term medical complications. At present, most of what is known about each of these complications and the health behaviors that may lead to them have been uncovered in the clinical setting or in laboratory-based research. However, the tools often used in these settings are limited in their ability to capture the dynamic behaviors, feelings, and physiological changes associated with T1D that fluctuate from moment to moment throughout the day. A better understanding of T1D in daily life could potentially aid in the development of interventions to improve diabetes care and mitigate the negative medical consequences associated with it. Therefore, there is a need to measure repeated, real-time, and real-world features of this disease in youth. This approach is known as ecological momentary assessment (EMA), and it has considerable advantages to in-lab research. Thus, this viewpoint aims to describe EMA tools that have been used to collect data in the daily lives of youth with T1D and discuss studies that explored the nuances of T1D in daily life using these methods. This viewpoint focuses on the following EMA methods: continuous glucose monitoring, actigraphy, ambulatory blood pressure monitoring, personal digital assistants, smartphones, and phone-based systems. The viewpoint also discusses the benefits of using EMA methods to collect important data that might not otherwise be collected in the laboratory and the limitations of each tool, future directions of the field, and possible clinical implications for their use.

scholarly journals Use of Ecological Momentary Assessment to Measure Self-Monitoring of Blood Glucose Adherence in Youth With Type 1 Diabetes

2020 ◽  
Vol 33 (3) ◽  
pp. 280-289 ◽  
Author(s):  
Jennifer L. Warnick ◽  
Sarah C. Westen ◽  
Anastasia Albanese-O’Neill ◽  
Stephanie L. Filipp ◽  
Desmond Schatz ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Ecological Momentary Assessment ◽  
Self Monitoring ◽  
Ecological Momentary ◽  
Momentary Assessment

scholarly journals A mobile app identifies momentary psychosocial and contextual factors related to mealtime self-management in adolescents with type 1 diabetes

2019 ◽  
Vol 26 (12) ◽  
pp. 1627-1631 ◽  
Author(s):  
Shelagh A Mulvaney ◽  
Sarah E Vaala ◽  
Rachel B Carroll ◽  
Laura K Williams ◽  
Cindy K Lybarger ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Problem Solving ◽  
Ecological Momentary Assessment ◽  
Mobile App ◽  
Self Management ◽  
Within Subjects ◽  
Ecological Momentary ◽  
Momentary Assessment

Abstract Effective diabetes problem solving requires identification of risk factors for inadequate mealtime self-management. Ecological momentary assessment was used to enhance identification of factors hypothesized to impact self-management. Adolescents with type 1 diabetes participated in a feasibility trial for a mobile app called MyDay. Meals, mealtime insulin, self-monitored blood glucose, and psychosocial and contextual data were obtained for 30 days. Using 1472 assessments, mixed-effects between-subjects analyses showed that social context, location, and mealtime were associated with missed self-monitored blood glucose. Stress, energy, mood, and fatigue were associated with missed insulin. Within-subjects analyses indicated that all factors were associated with both self-management tasks. Intraclass correlations showed within-subjects accounted for the majority of variance. The ecological momentary assessment method provided specific targets for improving self-management problem solving, phenotyping, or integration within just-in-time adaptive interventions.

Using Personal Cell Phones for Ecological Momentary Assessment

2013 ◽  
Vol 18 (1) ◽  
pp. 3-11 ◽  
Author(s):  
Emmanuel Kuntsche ◽  
Florian Labhart
Keyword(s):  
Data Collection ◽  
Ecological Momentary Assessment ◽  
Communication Systems ◽  
Cell Phones ◽  
Personal Digital Assistants ◽  
Natural Environments ◽  
Mobility Patterns ◽  
Standard Data ◽  
Ecological Momentary ◽  
Momentary Assessment

Ecological Momentary Assessment (EMA) is a way of collecting data in people’s natural environments in real time and has become very popular in social and health sciences. The emergence of personal digital assistants has led to more complex and sophisticated EMA protocols but has also highlighted some important drawbacks. Modern cell phones combine the functionalities of advanced communication systems with those of a handheld computer and offer various additional features to capture and record sound, pictures, locations, and movements. Moreover, most people own a cell phone, are familiar with the different functions, and always carry it with them. This paper describes ways in which cell phones have been used for data collection purposes in the field of social sciences. This includes automated data capture techniques, for example, geolocation for the study of mobility patterns and the use of external sensors for remote health-monitoring research. The paper also describes cell phones as efficient and user-friendly tools for prompt manual data collection, that is, by asking participants to produce or to provide data. This can either be done by means of dedicated applications or by simply using the web browser. We conclude that cell phones offer a variety of advantages and have a great deal of potential for innovative research designs, suggesting they will be among the standard data collection devices for EMA in the coming years.

Temporal Dynamics of PERMA Building Blocks and Well-being in Daily Life: An Ecological Momentary Assessment

2021 ◽  
Author(s):  
Saeideh Heshmati ◽  
Zita Oravecz
Keyword(s):  
Ecological Momentary Assessment ◽  
Temporal Dynamics ◽  
Daily Life ◽  
Well Being ◽  
Building Blocks ◽  
Individual Variability ◽  
Future Research ◽  
Dynamical Features ◽  
Ecological Momentary ◽  
Momentary Assessment

Most assessments of well-being have relied on retrospective accounts, measured by global evaluative well-being scales. Following the recent debates focused on the assessment of hedonic and eudaimonic well-being based on the elements of the PERMA theory, the current study aimed to shed further light onto the measurement of PERMA elements in daily life and their temporal dynamics. Through an Ecological Momentary Assessment (EMA) design (N=160), we examined the dynamics of change (e.g., baselines and intra-individual variability) in the PERMA elements using the mPERMA measure, which is an EMA-adapted version of the PERMA Profiler. Findings revealed that momentary experiences of well-being, quantified via PERMA elements, map onto their corresponding hedonic or eudaimonic well-being components, and its dynamical features provide novel insights into predicting global well-being. This work offers avenues for future research to assess well-being in real-time and real-world contexts in ecologically valid ways, while eliminating recall bias.

scholarly journals A Coordinated Analysis of Variance in Affect in Daily Life

Assessment ◽  
2018 ◽  
Vol 27 (8) ◽  
pp. 1683-1698 ◽  
Author(s):  
Stacey B. Scott ◽  
Martin J. Sliwinski ◽  
Matthew Zawadzki ◽  
Robert S. Stawski ◽  
Jinhyuk Kim ◽  
...  
Keyword(s):  
Negative Affect ◽  
Positive Affect ◽  
Ecological Momentary Assessment ◽  
Daily Life ◽  
Daily Diary ◽  
Levels Of Analysis ◽  
Total N ◽  
Ecological Momentary ◽  
Momentary Assessment ◽  
Widespread Interest

Despite widespread interest in variance in affect, basic questions remain pertaining to the relative proportions of between-person and within-person variance, the contribution of days and moments, and the reliability of these estimates. We addressed these questions by decomposing negative affect and positive affect variance across three levels (person, day, moment), and calculating reliability using a coordinated analysis of seven daily diary, ecological momentary assessment (EMA), and diary-EMA hybrid studies (across studies age = 18-84 years, total Npersons = 2,103, total Nobservations = 45,065). Across studies, within-person variance was sizeable (negative affect: 45% to 66%, positive affect: 25% to 74%); in EMA more within-person variance was attributable to momentary rather than daily level. Reliability was adequate to high at all levels of analysis (within-person: .73-.91; between-person: .96-1.00) despite different items and designs. We discuss the implications of these results for the design of future intensive studies of affect variance.

scholarly journals Food craving in daily life: comparison of overweight and normal‐weight participants with ecological momentary assessment

2019 ◽  
Vol 32 (6) ◽  
pp. 765-774 ◽  
Author(s):  
A. Roefs ◽  
B. Boh ◽  
G. Spanakis ◽  
C. Nederkoorn ◽  
L. H. J. M. Lemmens ◽  
...  
Keyword(s):  
Ecological Momentary Assessment ◽  
Daily Life ◽  
Normal Weight ◽  
Food Craving ◽  
Ecological Momentary ◽  
Momentary Assessment
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