The Effect of a Machine Learning-Based Mobile Application on Physical Activity in Overweight and Obese Women

NCT06225518 | Completed

• 1 other identifier: ETKU10/201
• Study Type: interventional
• Target: 80
• Locations: 1 country
• Sites: 1

Brief Summary

The goal of this clinical trial is to evaluate the effect of an algorithm-driven mobile application that provides personalized recommendations for increasing physical activity, which is an important health behavior, in the prevention of obesity and many other related non-communicable diseases in overweight and obese women. Hypotheses of this study are:

• The physical activity level of overweight and obese adult women in the intervention group increases.
• Body Mass Index decreases in overweight and obese adult women in the intervention group.
• The daily step count of overweight and obese adult women in the intervention group increases. Participants will be asked to use the mobile application they received daily and follow their personalized physical activity program. Researchers will compare the experimental and control groups to see if the mobile application affected the physical activity level.

Conditions

Physical Inactivity

Outcome Measures

Primary Outcomes (3)

• International Physical Activity Questionnaire (IPAQ) score

  Participants' International Physical Activity Questionnaire (IPAQ) score.

  3 months

• Daily step count

  Participants' daily step counts measured with their smart bands

  3 months

• BMI

  Weight and height will be combined to report BMI in kg/m\^2

  3 months

Study Arms (2)

Individualized physical activity management system

EXPERIMENTAL

The mobile application will be downloaded to the smartphones of the participants in the experimental group and the application will be introduced by the nurse at the family health center. Participants will receive daily and weekly goals with personalized physical activity recommendations, using the exercise recommendations determined by the decision system by public health nursing and physiotherapy and rehabilitation experts in the mobile application. With the initial data collected, a personalized physical activity program will be created according to each participant's lifestyle, physical activity level and physical activity barriers. The physical activity program will include a daily step count goals, exercises and stretching movements for each participant, and this program will be offered to the participants via the mobile application. The exercises that the participants are expected to complete will be shown in the application as videos with animated characters.

Behavioral: Individualized physical activity management system

Control

NO INTERVENTION

The mobile application will be downloaded to the smartphones of the participants in the experimental and control groups and the application will be introduced by the nurse at the family health center to which the participants are affiliated. Participants in the control group will use the mobile application only to enter and track daily step counts and other data.

Interventions

Individualized physical activity management system BEHAVIORAL

Participants will be provided with personalized exercise recommendations determined by a decision system by public health nursing and physiotherapy and rehabilitation experts via the mobile application. Targets will be determined for participants based on their completion of physical activity recommendations every day and every week in the mobile application. The initial program will be individually created based on the initial data collected and each participant's lifestyle, physical activity level and barriers to physical activity. Then, depending on the participants' ability to achieve their goals, the duration and intensity of the suggestions given will be individualized to a level that the person can complete.

Individualized physical activity management system

Eligibility Criteria

• Age: 35 Years - 60 Years
• Sex: female
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64)

You may qualify if:

• BMI\>25
• Who do not have any obstacle to participating in physical activities

You may not qualify if:

• Who have previously used a smart band to increase their physical activity levels

Sponsors & Collaborators

• Istanbul University - Cerrahpasa: lead

Study Sites (1)

Istanbul University - Cerrahpasa (IUC)

Istanbul, Turkey (Türkiye)

Location

Related Publications (9)

• World Health Organization. Burden: mortality, morbidity and risk factors. Global status report on non communicable diseases. 2010.

  BACKGROUND

• WHO European Regional Obesity Report. Copenhagen: WHO Regional Office for Europe. 2022. Licence: https://creativecommons.org/licenses/by-nc-sa/3.0/igo

  BACKGROUND

• Fadhil, A. Towards Automatic and Personalised Mobile Health Interventions: An Interactive Machine Learning Perspective. arXiv preprint arXiv:1803.01842. 2018

  BACKGROUND

• Niemiro GM, Rewane A, Algotar AM. Exercise and Fitness Effect on Obesity. 2023 Nov 17. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2025 Jan-. Available from http://www.ncbi.nlm.nih.gov/books/NBK539893/

  PMID: 30969715 BACKGROUND

• Evenson KR, Aytur SA, Borodulin K. Physical activity beliefs, barriers, and enablers among postpartum women. J Womens Health (Larchmt). 2009 Dec;18(12):1925-34. doi: 10.1089/jwh.2008.1309.

  PMID: 20044854 BACKGROUND

• Pinto BM, Floyd A. Theories underlying health promotion interventions among cancer survivors. Semin Oncol Nurs. 2008 Aug;24(3):153-63. doi: 10.1016/j.soncn.2008.05.003.

  PMID: 18687261 BACKGROUND

• Bandura A. Health promotion by social cognitive means. Health Educ Behav. 2004 Apr;31(2):143-64. doi: 10.1177/1090198104263660.

  PMID: 15090118 BACKGROUND

• Bandura A. Social cognitive theory: an agentic perspective. Annu Rev Psychol. 2001;52:1-26. doi: 10.1146/annurev.psych.52.1.1.

  PMID: 11148297 BACKGROUND

• Shamizadeh T, Jahangiry L, Sarbakhsh P, Ponnet K. Social cognitive theory-based intervention to promote physical activity among prediabetic rural people: a cluster randomized controlled trial. Trials. 2019 Feb 4;20(1):98. doi: 10.1186/s13063-019-3220-z.

  PMID: 30717779 BACKGROUND

MeSH Terms

Conditions

Sedentary Behavior

Condition Hierarchy (Ancestors)

Behavior

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: TRIPLE
• Who Masked: PARTICIPANT, INVESTIGATOR, OUTCOMES ASSESSOR
• Purpose: PREVENTION
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Lecturer

Model Details: This research was planned as an experimental type study. Randomization will be achieved by randomly selecting women from the study population and randomly assigning from the sample group women to the experimental and control groups by two people other than the researcher. Supervision in the research will be provided by creating a control group. Management will be provided by evaluating and comparing the effect of the mobile application on the physical activity level of women in experimental and control groups.

Study Record Dates

• First Submitted: September 25, 2023
• First Posted: January 26, 2024
• Study Start: April 5, 2024
• Primary Completion: July 5, 2024
• Study Completion: August 5, 2024
• Last Updated: October 28, 2024

Record last verified: 2024-10

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, ICF, CSR
• Time Frame: The data will be available after the statistical analysis have completed. All the relevant data will be kept without any time restriction
• Access Criteria: The data of this research will be available for the researchers who are planning a systematic review/metanalysis on this issue and have a PROSPERO record.

Locations

TU (1)