Evaluating Consumer m-Health Services for User Engagement and Health Promotion: An Organizational Field Experiment
1 other identifier
interventional
425
1 country
1
Brief Summary
Introduction Chronic disease is prevalent and costly in the U.S. (Tu \& Cohen, 2009). Poor eating habit is one factor that account for risk of chronic disease (Arsand, Varmedal, \& Hartvigsen, 2007). Smartphone technology has been promising to improve preventive health outcomes. However, its great potential has not been widely applied to people's eating behaviors and its impact is unknown. Professional and peer supports can improve health status (Elkjaer et al., 2010; Lorig et al., 1999; Perri, Sears, \& Clark, 1993). However, the former is usually delivered didactically or passively with limited use of smartphones. There is also little evidence of the effect of peer support delivered by smartphones in the domain of healthy eating. This research aims to study what smartphone technology can do to upgrade professional and peer supports, and to evaluate the impact of these mobile-app enabled supports on people's behavior of healthy eating and user engagement. Hypotheses According to Social Cognitive Theory, we hypothesize the following:
- 1.Mobile-enabled self-monitoring approach improves users' healthy eating behaviors through improved self-efficacy
- 2.Professional support improves users' healthy eating behaviors through improved self-efficacy
- 3.Peer support improves users' healthy eating behaviors through improved self-efficacy
- 4.The amount of support is positively correlated with the change in behaviors and their determinants
- 5.All subjects receive the following interventions: an education package includes the importance of healthy eating, concept of MyPlate, personalized daily food plans; reminders throughout the study; goal setting capabilities;
- 6.Self-monitoring provided by an Android App: a heuristic approach inspired by MyPlate to record their food consumption which allows users to record their meals by images and doesn't require estimations in cups and ounces; daily reports and trend reports
- 7.Self-monitoring provided by the web App: a traditional approach to record their food consumption which requires estimations in cups and ounces, and no images are allowed; no daily reports and trend reports are provided
- 8.Professional support provided by a registered dietitian via the Android App: the supports include the following:
- 9.Reply to users' messages regarding healthy eating
- 10.Provide meal-specific comments on subjects' meal consumptions: one meal per week
- 11.Provide feedback on the subjects' consumption patterns: once per week
- 12.Peer support provided by other subjects via the Android App: the App provides platforms for subjects who have the same interest to communicate to each other. The actions the subjects can do in the platforms include:
- 13.Post images or texts related to healthy eating
- 14.Share meals with their ratings
- 15.Like/dislike others' posts
- 16.Comment on others' posts e Create groups which allow subjects who have the same interest to join
- 17.Dependent Variables
- 18.Eating behavior: a score of healthiness of a meal will be assigned by a dietitian. The scores obtained by the same subject along the experiment compose the subject's eating behavior
- 19.Engaging behavior: this is measured by the number of meals recorded by the subject in a week. The numbers for the same subject along the experiment compose the subject's engaging behavior
- 20.Independent Variables
- 21.Level of peer support: this will be measured by a score representing the number of posts, likes, and comments received and given by a subject in a week
- 22.Level of professional support: this will be measured by a score representing the number of messages or comments exchanged with the dietitian in a week
- 23.Mediator Variables: self-efficacy, outcome expectation, and impediments will be measured by survey instruments
- 24.User Survey: characteristics and perceptions
- 25.Mobile App: time, location, and contents of goal setting, meal entries, communications with professionals and peers
- 26.Web App: contents of goal setting and meal entries
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started Mar 2014
Shorter than P25 for not_applicable
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
March 1, 2014
CompletedFirst Submitted
Initial submission to the registry
July 31, 2014
CompletedFirst Posted
Study publicly available on registry
August 1, 2014
CompletedPrimary Completion
Last participant's last visit for primary outcome
October 1, 2014
CompletedStudy Completion
Last participant's last visit for all outcomes
October 1, 2014
CompletedJuly 28, 2015
July 1, 2015
7 months
July 31, 2014
July 27, 2015
Conditions
Outcome Measures
Primary Outcomes (2)
Healthy Eating Behavior
This will be measured by a score representing the healthiness of each selected meal, evaluated by dietitians. Specifically, the score is composed of three sub-scores: 1) portion of fruits and vegetables (7-point Likert scale); 2) portion of the entire meal (7-point Likert scale); 3) evaluators confidence level (4-point Likert scale). One subject will get one score per week, and hence 16 scores in 4-months.
4 months after signed up
Engaging Behavior
This will be measured by the number of records submitted by the subject via the assigned tool in a week. One subject will get one score per week, and hence 16 scores in 4-months.
4 months after signed up
Study Arms (5)
Mobile: Professional and peer support
EXPERIMENTALA mobile app that provides both professional support and peer support
Mobile: Peer support
EXPERIMENTALA mobile app that provides peer support, but not professional support
Mobile: Professional Support
EXPERIMENTALA mobile app that provides professional support, but no peer support
Mobile: No Support
ACTIVE COMPARATORA mobile app that provides neither peer support nor professional support
Web: No Support
ACTIVE COMPARATORA web app that provides neither peer support, nor professional support
Interventions
Eligibility Criteria
You may qualify if:
- age at least 18 years
- Android smartphone users
- having internet accessibility on the smartphone during the study period
You may not qualify if:
- currently participating in other similar programs
- having specific medical conditions that require specialized diets
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Carnegie Mellon University
Pittsburgh, Pennsylvania, 15213, United States
Related Publications (1)
Kato-Lin YC, Padman R, Downs J, Abhishek V. Evaluating Consumer m-Health Services for Promoting Healthy Eating: A Randomized Field Experiment. AMIA Annu Symp Proc. 2015 Nov 5;2015:1947-56. eCollection 2015.
PMID: 26958294DERIVED
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Yi-Chin Lin, MS
Carnegie Mellon University
- STUDY CHAIR
Rema Padman, PhD
Carnegie Mellon University
- STUDY DIRECTOR
Julie Downs, PhD
Carnegie Mellon University
- STUDY DIRECTOR
Vibhanshu Abhishek, PhD
Carnegie Mellon University
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- NONE
- Purpose
- SUPPORTIVE CARE
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- PhD Candidate
Study Record Dates
First Submitted
July 31, 2014
First Posted
August 1, 2014
Study Start
March 1, 2014
Primary Completion
October 1, 2014
Study Completion
October 1, 2014
Last Updated
July 28, 2015
Record last verified: 2015-07