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Cited by 179Mental Health Research TopicsDigital Mental Health InterventionsMobile Health and mHealth Applications

The DOI matches its Crossref record; 44 of the 45 references it cites were found in a registry or an index.

A Smartphone Ecological Momentary Assessment/Intervention “App” for Collecting Real-Time Data and Promoting Self-Awareness

Open access
Runyan, Jason D., Steenbergh, Timothy A., Bainbridge, Charles, Daugherty, Douglas A., Oke, Lorne, Fry, Brian N.·2013·PLoS ONE
DOI 10.1371/journal.pone.0071325PMC PMC3743745
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Abstract

We have designed a flexible ecological momentary assessment/intervention smartphone (EMA/EMI) "app". We examine the utility of this app for collecting real-time data, and assessing intra-subject variability, by using it to assess how freshman undergraduates spend their time. We also explore whether its use can promote greater self-awareness. Participants were randomly divided into an experimental group, who used the app, and a control group, who did not. We used the app to collect both randomized in-the-moment data as well as end-of-day data to assess time use. Using a posttest survey we asked participants questions about how they spent time throughout the school semester. We also asked the experimental group about their experience with the app. Among other findings, 80.49% participants indicated that they became more aware of how they spent their time using the app. Corroborating this report, among the experimental group, end-of-semester self-assessment of time spent wasted, and time spent using electronics recreationally, predicted semester GPA at a strength comparable to high school GPA and ACT score (two of the best single predictors for first semester college GPA), but had no correlation among controls. We discuss the advantages and limitations of using apps, such as ours, for EMA and/or EMI.

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Crossref · 10.1371/journal.pone.0071325

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Figure 1 Screen captures of (A) iHabit’s visual check-in notification, (B) a representative check-in question, and (C) a representative end-of-day question.
Figure 1 Screen captures of (A) iHabit’s visual check-in notification, (B) a representative check-in question, and (C) a representative end-of-day question.CC BY · PubMed Central
Figure 2 Intra-subject change in estimated time spent on academics at check-in across test weeks. Average estimated time spent on academics over the 20 minutes prior to check-in was significantly greater in weeks 8 and 14 than in week 3 (p = 0.05). Each participant’s average estimate during each week is represented by a colored line.
Figure 2 Intra-subject change in estimated time spent on academics at check-in across test weeks. Average estimated time spent on academics over the 20 minutes prior to check-in was significantly greater in weeks 8 and 14 than in week 3 (p = 0.05). Each participant’s average estimate during each week is represented by a colored line.CC BY · PubMed Central
Figure 3 Means and standard deviations for posttest estimations of percentage of time (A) spent recreationally using electronics and (B) wasted throughout the semester. The app group estimated spending more time using electronics recreationally and wasting more time than controls (p<.05; statistical significance denoted by an asterisk).
Figure 3 Means and standard deviations for posttest estimations of percentage of time (A) spent recreationally using electronics and (B) wasted throughout the semester. The app group estimated spending more time using electronics recreationally and wasting more time than controls (p<.05; statistical significance denoted by an asterisk).CC BY · PubMed Central
Figure 4 Means and standard deviations for end-of-day estimates of time spent studying during the three testing weeks for participants who reported changing their behavior as a result of app use (“Change”) and who reported no change (“No Change”) in the posttest questionnaire. Average end-of-day estimates of time spent studying over week 8–but not weeks 3 or 14 (p’s>,05)–was significantly higher for the group that reported changing their behavior as a result of using the app than for the group that reported no change (p<.01; statistical significance denoted by an asterisk).
Figure 4 Means and standard deviations for end-of-day estimates of time spent studying during the three testing weeks for participants who reported changing their behavior as a result of app use (“Change”) and who reported no change (“No Change”) in the posttest questionnaire. Average end-of-day estimates of time spent studying over week 8–but not weeks 3 or 14 (p’s>,05)–was significantly higher for the group that reported changing their behavior as a result of using the app than for the group that reported no change (p<.01; statistical significance denoted by an asterisk).CC BY · PubMed Central

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Metadata

Authors
Runyan, J. D., Steenbergh, T. A., Bainbridge, C., Daugherty, D. A., Oke, L., & Fry, B. N.
Affiliations
Indiana Wesleyan University (US)
Corresponding author
Runyan, Jason D.
ORCID
Venue
PLoS ONE
Publisher
Public Library of Science (PLoS)
Published
2013-08-14
Volume
8
Issue
8
Pages
e71325
ISSN
1932-6203 (ISSN-L)
DOI
10.1371/journal.pone.0071325
PMC
PMC3743745
OpenAlex
W2133044419
Cited by
179
References
45
Citations by year
2026: 6 · 2025: 14 · 2024: 9 · 2023: 12 · 2022: 12 · 2021: 19 · 2020: 13 · 2019: 15 · 2018: 25 · 2017: 12 · 2016: 15 · 2015: 21 · 2014: 5 · 2013: 1
FWCI
18.92
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Eli Lilly and Company
Topics
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
Keywords
ecological momentary assessment, ecological momentary intervention, mobile application, self-awareness, time use, within-person variability, GPA prediction, time waste, mobile health
MeSH terms
Adolescent, Awareness, Data Collection, Female, Humans, Male, Surveys and Questionnaires, Self-Assessment, Space Perception, Task Performance and Analysis, Time Perception, Time Management, Cell Phone, Young Adult, Mobile Applications

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