Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

RecoverEsupport-A Digital Health Intervention for Recovery After Breast Cancer Surgery: Feasibility and Acceptability Outcomes from a Pilot Randomized Controlled Trial.

JMIR formative research·2026
Same author

The Effectiveness of Parent-Targeted Digital Health Interventions on Breastfeeding Practices: Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Journal of medical Internet research·2026
Same author

Harnessing artificial intelligence for scalable evidence synthesis in reviews: Application in a bibliometric analysis of physical activity technologies.

Digital health·2026
Same author

Applying Sequence Analysis to Explore Real-World Usage Patterns in the 10,000 Steps Digital Physical Activity Program.

Journal of physical activity & health·2026
Same author

mHealth to support resistance training using outdoor gyms: the ecofit hybrid type 3 implementation-effectiveness trial.

Translational behavioral medicine·2026
Same author

Sleep-inducing algorithms: can artificial intelligence help shiftworkers and those working nonstandard hours sleep better?

Sleep advances : a journal of the Sleep Research Society·2026

Related Experiment Video

Updated: Nov 1, 2025

Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity
05:59

Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity

Published on: March 7, 2019

6.9K

The Association Between Logging Steps Using a Website, App, or Fitbit and Engaging With the 10,000 Steps Physical

Anna T Rayward1,2, Corneel Vandelanotte1, Anetta Van Itallie1

  • 1School of Health, Medical and Applied Sciences, Central Queensland University, Rockhampton, Australia.

Journal of Medical Internet Research
|June 18, 2021
PubMed
Summary

Using a Fitbit with a physical activity program significantly boosted user engagement compared to manual data entry. Combining devices like Fitbit with apps or websites enhances participation and long-term adherence.

Keywords:
Fitbitactivity trackerseHealthengagementmobile phonepedometerphysical activity intervention

More Related Videos

A Method for Quantifying Upper Limb Performance in Daily Life Using Accelerometers
07:24

A Method for Quantifying Upper Limb Performance in Daily Life Using Accelerometers

Published on: April 21, 2017

12.7K
An Application for Pairing with Wearable Devices to Monitor Personal Health Status
06:58

An Application for Pairing with Wearable Devices to Monitor Personal Health Status

Published on: February 3, 2022

3.0K

Related Experiment Videos

Last Updated: Nov 1, 2025

Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity
05:59

Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity

Published on: March 7, 2019

6.9K
A Method for Quantifying Upper Limb Performance in Daily Life Using Accelerometers
07:24

A Method for Quantifying Upper Limb Performance in Daily Life Using Accelerometers

Published on: April 21, 2017

12.7K
An Application for Pairing with Wearable Devices to Monitor Personal Health Status
06:58

An Application for Pairing with Wearable Devices to Monitor Personal Health Status

Published on: February 3, 2022

3.0K

Area of Science:

  • Digital Health
  • Behavioral Science
  • Human-Computer Interaction

Background:

  • User engagement is crucial for the effectiveness of digital health interventions.
  • The impact of automatically synchronized tracking devices versus manual data entry on engagement is not well understood.

Purpose of the Study:

  • To compare engagement levels across different step-logging methods in the 10,000 Steps program.
  • To analyze how age and gender influence these engagement differences.
  • To identify which logging methods are associated with higher program engagement.

Main Methods:

  • Analysis of 22,142 users of the 10,000 Steps program, categorized by step-logging method (Website Only, App Only, Fitbit Only, Web and App, Fitbit Combination).
  • Generalized linear regression and binary logistic regression were used to assess engagement and participation parameters.
  • Cox proportional hazards regression analyzed time to nonusage attrition.

Main Results:

  • App Only users were younger; Fitbit users had more women. Fitbit Combination users showed significantly higher engagement (more sessions, more minutes per session, more step entries) compared to Website Only users.
  • App Only and Fitbit Only groups had lower daily step counts and fewer website sessions.
  • Web and App and Fitbit Combination groups demonstrated longer adherence, with higher time to nonusage attrition.

Conclusions:

  • Integrating automatically synchronizing tracking devices, such as Fitbit, enhances engagement in physical activity programs.
  • Combined use of tracking devices with digital platforms (app/website) is a viable strategy to improve user engagement and adherence.