Context-Sensitive Ecological Momentary Assessment: Application of User-Centered Design for Improving User Satisfaction and Engagement During Self-Report.


Journal

JMIR mHealth and uHealth
ISSN: 2291-5222
Titre abrégé: JMIR Mhealth Uhealth
Pays: Canada
ID NLM: 101624439

Informations de publication

Date de publication:
03 04 2019
Historique:
received: 01 05 2018
accepted: 31 12 2018
revised: 30 11 2018
entrez: 4 4 2019
pubmed: 4 4 2019
medline: 4 4 2019
Statut: epublish

Résumé

Ecological momentary assessment (EMA) can be a useful tool for collecting real-time behavioral data in studies of health and health behavior. However, EMA administered through mobile technology can be burdensome, and it tends to suffer from suboptimal user engagement, particularly in low health-literacy populations. This study aimed to report a case study involving the design and evaluation of a mobile EMA tool that supports context-sensitive EMA-reporting of location and social situations accompanying eating and sedentary behavior. An iterative, user-centered design process with obese, middle-aged women seeking care in a safety-net health system was used to identify the preferred format of self-report measures and the look, feel, and interaction of the mobile EMA tool. A single-arm feasibility field trial with 21 participants receiving 12 prompts each day for momentary self-reports over a 4-week period (336 total prompts per participant) was used to determine user satisfaction with interface quality and user engagement, operationalized as response rate. A second trial among 38 different participants randomized to receive or not to receive a feature designed to improve engagement was conducted. The feasibility trial results showed high interface satisfaction and engagement, with an average response rate of 50% over 4 weeks. Qualitative feedback pointed to the need for auditory alerts. We settled on 3 alerts at 10-min intervals to accompany each EMA-reporting prompt. The second trial testing this feature showed a statistically significant increase in the response rate between participants randomized to receive repeat auditory alerts versus those who were not (60% vs 40%). This paper reviews the design research and a set of design constraints that may be considered in the creation of mobile EMA interfaces personalized to users' preferences. Novel aspects of the study include the involvement of low health-literacy adults in design research, the capture of data on time, place, and social context of eating and sedentary behavior, and reporting prompts tailored to an individual's location and schedule. ClinicalTrials.gov NCT03083964; https://clinicaltrials.gov/ct2/show/NCT03083964.

Sections du résumé

BACKGROUND
Ecological momentary assessment (EMA) can be a useful tool for collecting real-time behavioral data in studies of health and health behavior. However, EMA administered through mobile technology can be burdensome, and it tends to suffer from suboptimal user engagement, particularly in low health-literacy populations.
OBJECTIVE
This study aimed to report a case study involving the design and evaluation of a mobile EMA tool that supports context-sensitive EMA-reporting of location and social situations accompanying eating and sedentary behavior.
METHODS
An iterative, user-centered design process with obese, middle-aged women seeking care in a safety-net health system was used to identify the preferred format of self-report measures and the look, feel, and interaction of the mobile EMA tool. A single-arm feasibility field trial with 21 participants receiving 12 prompts each day for momentary self-reports over a 4-week period (336 total prompts per participant) was used to determine user satisfaction with interface quality and user engagement, operationalized as response rate. A second trial among 38 different participants randomized to receive or not to receive a feature designed to improve engagement was conducted.
RESULTS
The feasibility trial results showed high interface satisfaction and engagement, with an average response rate of 50% over 4 weeks. Qualitative feedback pointed to the need for auditory alerts. We settled on 3 alerts at 10-min intervals to accompany each EMA-reporting prompt. The second trial testing this feature showed a statistically significant increase in the response rate between participants randomized to receive repeat auditory alerts versus those who were not (60% vs 40%).
CONCLUSIONS
This paper reviews the design research and a set of design constraints that may be considered in the creation of mobile EMA interfaces personalized to users' preferences. Novel aspects of the study include the involvement of low health-literacy adults in design research, the capture of data on time, place, and social context of eating and sedentary behavior, and reporting prompts tailored to an individual's location and schedule.
TRIAL REGISTRATION
ClinicalTrials.gov NCT03083964; https://clinicaltrials.gov/ct2/show/NCT03083964.

Identifiants

pubmed: 30942698
pii: v7i4e10894
doi: 10.2196/10894
pmc: PMC6468333
doi:

Banques de données

ClinicalTrials.gov
['NCT03083964']

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

e10894

Subventions

Organisme : NHLBI NIH HHS
ID : R01 HL128494
Pays : United States

Informations de copyright

©Preethi Srinivas, Kunal Bodke, Susan Ofner, NiCole R Keith, Wanzhu Tu, Daniel O Clark. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 03.04.2019.

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Auteurs

Preethi Srinivas (P)

Indiana University, Center for Aging Research, Indianapolis, IN, United States.
Regenstrief Institute, Indianapolis, IN, United States.

Kunal Bodke (K)

Indiana University, Center for Aging Research, Indianapolis, IN, United States.
Regenstrief Institute, Indianapolis, IN, United States.

Susan Ofner (S)

Indiana University, School of Medicine, Department of Biostatistics, Indianapolis, IN, United States.

NiCole R Keith (NR)

Indiana University, Center for Aging Research, Indianapolis, IN, United States.
Regenstrief Institute, Indianapolis, IN, United States.
Indiana University, School of Health and Human Sciences, Department of Kinesiology, Indianapolis, IN, United States.

Wanzhu Tu (W)

Indiana University, Center for Aging Research, Indianapolis, IN, United States.
Indiana University, School of Medicine, Department of Biostatistics, Indianapolis, IN, United States.

Daniel O Clark (DO)

Indiana University, Center for Aging Research, Indianapolis, IN, United States.
Regenstrief Institute, Indianapolis, IN, United States.
Indiana University, School of Medicine, Department of Medicine, Indianapolis, IN, United States.

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Classifications MeSH