Cited by 11Mobile Health and mHealth ApplicationsPhysical Activity and HealthContext-Aware Activity Recognition Systems

A Multimodal mHealth Intervention (FeatForward) to Improve Physical Activity Behavior in Patients with High Cardiometabolic Risk Factors: Rationale and Protocol for a Randomized Controlled Trial

Open access
Agboola, Stephen, Palacholla, Ramya Sita, Centi, Amanda, Kvedar, Joseph, Jethwani, Kamal·2016·JMIR Research Protocols

Abstract

BACKGROUND: Physical inactivity is one of the leading risk factors contributing to the rising rates of chronic diseases and has been associated with deleterious health outcomes in patients with chronic disease conditions. We developed a mobile phone app, FeatForward, to increase the level of physical activity in patients with cardiometabolic risk (CMR) factors. This intervention is expected to result in an overall improvement in patient health outcomes. OBJECTIVE: The objective of this study is to evaluate the effect of a mobile phone-based app, FeatForward, on physical activity levels and other CMR factors in patients with chronic conditions. METHODS: The study will be implemented as a 2-arm randomized controlled trial with 300 adult patients with chronic conditions over a 6-month follow-up period. Participants will be assigned to either the intervention group receiving the FeatForward app and standard care versus a control group who will receive only usual care. The difference in physical activity levels between the control group and intervention group will be measured as the primary outcome. We will also evaluate the effect of this intervention on secondary measures including clinical outcome changes in global CMR factors (glycated hemoglobin, fasting blood glucose, blood pressure, waist circumference, Serum lipids, C-reactive protein), health-related quality of life, health care usage, including attendance of scheduled clinic visits and hospitalizations, usability, and satisfaction, participant engagement with the FeatForward app, physician engagement with physician portal, and willingness to engage in physical activity. Instruments that will be used in evaluating secondary outcomes include the Short-Form (SF)-12, app usability and satisfaction questionnaires, physician satisfaction questionnaire. The intention-to-treat approach will be used to evaluate outcomes. All outcomes will be measured longitudinally at baseline, midpoint (3 months), and 6 months. Our primary outcome, physical activity, will be assessed by mixed-model analysis of variance with intervention assignment as between-group factor and time as within-subject factor. A similar approach will be used to analyze continuous secondary outcomes while categorical outcomes will be analyzed by chi-square test. RESULTS: The study is still in progress and we hope to have the results by the end of 2016. CONCLUSIONS: The mobile phone-based app, FeatForward, could lead to significant improvements in physical activity and other CMR factors in patients.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.2196/resprot.5489

Cites

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

The citation lists haven’t been fetched yet

References 15 · Cited by 11

Authors
Agboola, S., Palacholla, R. S., Centi, A., Kvedar, J., & Jethwani, K.
Affiliations
Brigham and Women's Hospital (US)
Corresponding author
Agboola, Stephen
Venue
JMIR Research Protocols
Published
2016-05-12
Volume
5
Issue
2
Pages
e84
ISSN
1929-0748 (ISSN-L)
OpenAlex
W2370754342
Cited by
11
References
15
Citations by year
2023: 1 · 2022: 1 · 2020: 2 · 2019: 5 · 2018: 1 · 2017: 1
FWCI
4.35
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • JMIR Research Protocols (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
Samsung
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Health Sciences › Medicine › Physiology › Physical Activity and Health
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
Keywords
physical activity, cardiometabolic risk factors, mobile health apps, chronic disease, multimodal intervention, HbA1c, blood pressure, serum lipids, C-reactive protein, health-related quality of life, physician engagement, physical inactivity

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review