Search research articles

Related Concept Videos

Obesity

Obesity

The Body Mass Index (BMI) is a numerical value derived from a person's weight and height, used to categorize individuals into weight ranges. It is calculated using the formula: weight in kilograms divided by height in meters squared. Obesity is a health condition characterized by excessive accumulation of adipose tissue that poses health risks, often diagnosed with a BMI ≥ 30. This excess fat storage occurs when surplus dietary calories are converted into triglycerides and stored in...

You might also read

Related Articles

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

Sort by

Same author

Verification of historical sketches via one-class learning on compact feature representations.

PloS one·2026

Same author

Subject-Wise Depression Screening from Eight-Channel Resting-State EEG Using Asymmetry-Aware Spectral Features and Connectivity Ablation.

Sensors (Basel, Switzerland)·2026

Same author

Development and validation of the EDIT weight stigma reduction checklist.

International journal of obesity (2005)·2026

Same author

A Scoping Review of the Photographic Assessment of Donor Liver Steatosis in Transplantation Using Artificial Intelligence.

Clinical transplantation·2026

Same author

Components of Adolescent Behavioural Interventions With Eating Disorder Outcomes: Systematic Review With Intervention Mapping.

Pediatric obesity·2025

Same author

How Do the Psychological Functions of Eating Disorder Behaviours Compare with Self-Harm? A Systematic Qualitative Evidence Synthesis.

Healthcare (Basel, Switzerland)·2025

Same journal

Technology-Enhanced Peer Support for Depression in Older Adults: Single-Arm Mixed Methods Feasibility Study.

JMIR formative research·2026

Same journal

AI-Assisted Clinical Data Abstraction From Electronic Health Records: Retrospective Concordance Study.

JMIR formative research·2026

Same journal

Structured Large Language Model Workflows for Motivational Interviewing in Health Behavior Change: Proof-of-Concept Study.

JMIR formative research·2026

Same journal

Mining Association Rules From a Multimodal Dataset of a Digital Therapeutics Application for Sleep Improvement Through a Healthy Lifestyle: Quantitative Study.

JMIR formative research·2026

Same journal

Construct Validation of a Remote Brain Health Assessment Battery to Evaluate Vocational Aptitude and Factors Associated With Cognitive Resilience in the Military: Observational Trial.

JMIR formative research·2026

Same journal

Identifying Behavior Change Techniques for Digital Interventions Addressing Alcohol and Tobacco Co-Use: Findings From a Delphi Consensus Study.

JMIR formative research·2026

See all related articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Video

Updated: Aug 26, 2025

Author Spotlight: Advancements in 3D Optical Imaging for Comprehensive Body Composition Assessment in Modern Research

Author Spotlight: Advancements in 3D Optical Imaging for Comprehensive Body Composition Assessment in Modern Research

Published on: June 7, 2024

Using Personalized Avatars as an Adjunct to an Adult Weight Loss Management Program: Randomized Controlled

Maria Horne¹, Maryann Hardy², Trevor Murrells³

¹Faculty of Medicine and Health, School of Healthcare, University of Leeds, Leeds, United Kingdom.

JMIR Formative Research

|October 5, 2022

Summary

This summary is machine-generated.

Personalized avatars in weight loss programs enhance motivation and engagement, leading to greater weight loss and improved self-efficacy. This avatar-based technology shows promise for sustained behavioral change in obesity interventions.

Keywords:

avatar feasibility obesity weight loss weight management

More Related Videos

Control of Eating Behavior Using a Novel Feedback System

Control of Eating Behavior Using a Novel Feedback System

Published on: May 8, 2018

Validation of a Psychosocial Intervention on Body Image in Older People: An Experimental Design

Validation of a Psychosocial Intervention on Body Image in Older People: An Experimental Design

Published on: May 31, 2021

Related Experiment Videos

Last Updated: Aug 26, 2025

Author Spotlight: Advancements in 3D Optical Imaging for Comprehensive Body Composition Assessment in Modern Research

Author Spotlight: Advancements in 3D Optical Imaging for Comprehensive Body Composition Assessment in Modern Research

Published on: June 7, 2024

Control of Eating Behavior Using a Novel Feedback System

Control of Eating Behavior Using a Novel Feedback System

Published on: May 8, 2018

Validation of a Psychosocial Intervention on Body Image in Older People: An Experimental Design

Validation of a Psychosocial Intervention on Body Image in Older People: An Experimental Design

Published on: May 31, 2021

Area of Science:

Behavioral Science
Digital Health
Obesity Research

Background:

Obesity is a global health issue with poor adherence to traditional interventions.
Lack of motivation and self-efficacy are key barriers to sustained weight loss.
Avatar-based interventions can improve patient engagement and outcomes in chronic conditions.

Purpose of the Study:

To evaluate if a personalized avatar enhances motivation, engagement, and health outcomes in a weight loss program.
To assess the feasibility and acceptability of avatar-based technology for weight management.

Main Methods:

Feasibility randomized design comparing avatar intervention with routine care in a 12-week program.
Primary outcome: weight loss. Secondary outcomes: quality-of-life and self-efficacy.
Qualitative interviews assessed feasibility and acceptability; quantitative data analyzed using descriptive statistics.

Main Results:

Avatar group showed accelerated weight loss in later stages and greater improvements in quality-of-life and self-efficacy.
Mean weight loss was 5.3 kg in the avatar arm versus 4.5 kg in the routine care arm.
Participants found the avatar acceptable, reporting increased motivation to change behavior.

Conclusions:

Avatar-based technology is a feasible and acceptable adjunct to weight loss programs.
Personalized avatars can enhance participant motivation, engagement, and self-confidence.
This approach shows potential for improving weight loss outcomes and promoting sustained behavioral change.