Physical InactivityNCT06225518
The Effect of a Machine Learning-Based Mobile Application on Physical Activity in Overweight and Obese Women
A study testing Individualized physical activity management system in people with Physical Inactivity, run by Istanbul University - Cerrahpasa at 1 site in Turkey (Türkiye).
Trial 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… Read more about this study
- Who is it for?
- Ages 35 to 60 years, women onlyHealthy volunteers can take part
- Conditions the study is for
- Physical Inactivity
- What is being tested?
- Individualized physical activity management system
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 80 participants
- Where
- 1 siteTurkey (Türkiye)
- Study dates
- 5 Apr 2024to 5 Aug 2024
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 35 to 60 years
- Women only
- Healthy volunteers accepted
- Adult
Who may be able to join
- BMI>25
- Who do not have any obstacle to participating in physical activities
Who cannot join
- Who have previously used a smart band to increase their physical activity levels
Trial locations and contacts
1 site in 1 country.
Turkey (Türkiye)1 site
Istanbul University - Cerrahpasa (IUC)
Istanbul
About this study
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.
Read more
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.
Read the detailed description
According to the World Health Organization (WHO), physical inactivity is one of the significant public health issues of our time. Health problems associated with this issue lead to an overload of healthcare services. According to the report published by WHO in 2022, the prevalence of overweight and obesity in the world constitutes 60% of the total population and causes 1.2 million deaths in the European region. In Turkey, the prevalence of obesity is 66.8 in all genders and 69.3 in women. The increasing epidemic of excessive weight and obesity, which leads to chronic diseases in the long term, poses a significant public health threat both globally and in our country.
Physical activity is an essential lifestyle measure for maintaining a healthy weight and preventing obesity. In women, physical activity levels decrease during pregnancy, and inactivity continues after childbirth. Therefore, determining the physical activity levels of women at risk for obesity and planning public health initiatives to increase their physical activity levels are also important.
Cognitive Behavioral Theory (CBT) is a theory that suggests thoughts, feelings, and behaviors are interconnected and influence each other. CBT is used in many health improvement interventions, such as improving physical activity levels. On the other hand, Social Cognitive Theory (SCT) is an important theory in planning behavior change interventions related to individuals' changing and sustaining health behaviors. SCT provides a strong perspective in understanding health behaviors related to physical activity by identifying the interaction between individuals, the environment, and behavior. Associating the components of CBT and SCT with the level of physical activity will provide a comprehensive approach by simultaneously addressing cognitive, behavioral, environmental, and social factors that affect the physical activity levels of middle-aged women.
Increasing physical activity is an effective intervention in reducing the prevalence of obesity and overweight, which are significant public health problems worldwide and in our country. There is an urgent need for behavior change interventions to determine and increase physical activity levels in the entire society and especially in risk groups to promote healthy lifestyles. This research is designed to evaluate the impact of a machine learning-based mobile application that provides personalized recommendations to increase physical activity, which is an essential health behavior in preventing obesity and many other non-communicable diseases in overweight and obese women.
After obtaining institutional and ethical approvals, data will be collected through face-to-face interviews with women aged 35-60 who apply to Family Health Centers in Istanbul. The height and weight of the women will be measured, and their Body Mass Index (BMI) will be calculated. Women with a BMI value of 25 or higher and no medical condition or health issue that would impede their physical activity status will be included in the study.
The data for the study will be collected using the following tools and measures: Identifying Characteristics Form, Visual Analog Scale (VAS), Anthropometric Measurements, International Physical Activity Questionnaire (Short Form), Women's Physical Activity Self-Efficacy Scale, Physical Activity Barriers Scale, Cognitive Behavioral Physical Activity Scale, Exercise Self-Efficacy Scale, and a smart wristband.
After data collection, the data will be transferred to the Statistical Package for the Social Sciences (SPSS) 25.0 software package for analysis. The data analysis will include percentages, mean values, standard deviations and chi-square test, independent sample t-test, repeated measures ANOVA test, and the corrected Bonferroni test for advanced analyses.
- Conditions
- Physical Inactivity
- Being tested
- Individualized physical activity management system
- Medical subject headings
- Sedentary Behavior
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Individualized physical activity management systemBehavioural
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.
| Study group | Role | What they receive |
|---|---|---|
| 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. Receives: 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. |
What is being measured
The primary outcome is the main question the study is designed to answer.
International Physical Activity Questionnaire (IPAQ) score
Participants' International Physical Activity Questionnaire (IPAQ) score.
Measured: 3 months
Daily step count
Participants' daily step counts measured with their smart bands
Measured: 3 months
BMI
Weight and height will be combined to report BMI in kg/m^2
Measured: 3 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted26 Jan 2024
- Study start5 Apr 2024
- Primary completion5 Jul 2024
- Study completion5 Aug 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (9)Papers the sponsor has linked to this study.
- Other trials for Physical InactivityStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- 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.
- Masking
- Triple blind
- Who is masked
- Participant, Investigator, Outcomes assessor
- Enrolment
- 80 participants (actual)
Sponsor and investigators
- Lead sponsor
- Istanbul University - Cerrahpasa
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Ezgi Hasret Kozan Cikirikci, Istanbul University - Cerrahpasa
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06225518
- Sponsor's protocol ID
- ETKU10/201
- Status last verified
- Oct 2024
- First submitted
- 25 Sep 2023
- Last updated
- 28 Oct 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: The data of this research will be shared with researchers who request it via e-mail.
Publications
World Health Organization. Burden: mortality, morbidity and risk factors. Global status report on non communicable diseases. 2010.
WHO European Regional Obesity Report. Copenhagen: WHO Regional Office for Europe. 2022. Licence: https://creativecommons.org/licenses/by-nc-sa/3.0/igo
Fadhil, A. Towards Automatic and Personalised Mobile Health Interventions: An Interactive Machine Learning Perspective. arXiv preprint arXiv:1803.01842. 2018
Niemiro GM, Rewane A, Algotar AM. Exercise and Fitness Effect on Obesity. 2023 Nov 17. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2026 Jan-. Available from http://www.ncbi.nlm.nih.gov/books/NBK539893/
PubMed 30969715Evenson 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.
PubMed 20044854Pinto 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.
PubMed 18687261Bandura A. Health promotion by social cognitive means. Health Educ Behav. 2004 Apr;31(2):143-64. doi: 10.1177/1090198104263660.
PubMed 15090118Bandura A. Social cognitive theory: an agentic perspective. Annu Rev Psychol. 2001;52:1-26. doi: 10.1146/annurev.psych.52.1.1.
PubMed 11148297Shamizadeh 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.
PubMed 30717779
Study at a glance
From the registry record, last updated by the sponsor on 28 Oct 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- The Effect of a Machine Learning-Based Mobile Application on Physical Activity in Overweight and Obese Women
- ClinicalTrials.gov ID
- NCT06225518
- Acronym / sponsor ID
- ETKU10/201
- Conditions
- Physical Inactivity
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 80 participants (actual)
- Lead sponsor
- Istanbul University - CerrahpasaUniversity, hospital or other
- Study start
- 5 Apr 2024 (actual)
- Primary completion
- 5 Jul 2024 (actual)
- Study completion
- 5 Aug 2024 (actual)
- First posted
- 26 Jan 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
According to the World Health Organization (WHO), physical inactivity is one of the significant public health issues of our time. Health problems associated with this issue lead to an overload of healthcare services. According to the report published by WHO in 2022, the prevalence of overweight and obesity in the world constitutes 60% of the total population and causes 1.2 million deaths in the European region. In Turkey, the prevalence of obesity is 66.8 in all genders and 69.3 in women. The increasing epidemic of excessive weight and obesity, which leads to chronic diseases in the long term, poses a significant public health threat both globally and in our country.
Physical activity is an essential lifestyle measure for maintaining a healthy weight and preventing obesity. In women, physical activity levels decrease during pregnancy, and inactivity continues after childbirth. Therefore, determining the physical activity levels of women at risk for obesity and planning public health initiatives to increase their physical activity levels are also important.
Cognitive Behavioral Theory (CBT) is a theory that suggests thoughts, feelings, and behaviors are interconnected and influence each other. CBT is used in many health improvement interventions, such as improving physical activity levels. On the other hand, Social Cognitive Theory (SCT) is an important theory in planning behavior change interventions related to individuals' changing and sustaining health behaviors. SCT provides a strong perspective in understanding health behaviors related to physical activity by identifying the interaction between individuals, the environment, and behavior. Associating the components of CBT and SCT with the level of physical activity will provide a comprehensive approach by simultaneously addressing cognitive, behavioral, environmental, and social factors that affect the physical activity levels of middle-aged women.
Increasing physical activity is an effective intervention in reducing the prevalence of obesity and overweight, which are significant public health problems worldwide and in our country. There is an urgent need for behavior change interventions to determine and increase physical activity levels in the entire society and especially in risk groups to promote healthy lifestyles. This research is designed to evaluate the impact of a machine learning-based mobile application that provides personalized recommendations to increase physical activity, which is an essential health behavior in preventing obesity and many other non-communicable diseases in overweight and obese women.
After obtaining institutional and ethical approvals, data will be collected through face-to-face interviews with women aged 35-60 who apply to Family Health Centers in Istanbul. The height and weight of the women will be measured, and their Body Mass Index (BMI) will be calculated. Women with a BMI value of 25 or higher and no medical condition or health issue that would impede their physical activity status will be included in the study.
The data for the study will be collected using the following tools and measures: Identifying Characteristics Form, Visual Analog Scale (VAS), Anthropometric Measurements, International Physical Activity Questionnaire (Short Form), Women's Physical Activity Self-Efficacy Scale, Physical Activity Barriers Scale, Cognitive Behavioral Physical Activity Scale, Exercise Self-Efficacy Scale, and a smart wristband.
After data collection, the data will be transferred to the Statistical Package for the Social Sciences (SPSS) 25.0 software package for analysis. The data analysis will include percentages, mean values, standard deviations and chi-square test, independent sample t-test, repeated measures ANOVA test, and the corrected Bonferroni test for advanced analyses.
Study design
- Primary purpose
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Triple blind (participant, investigator, outcomes assessor)
- Number of arms
- 2
- Model description
- 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.
| Arm | Type | Receives |
|---|---|---|
| Individualized physical activity management system | Experimental | Behavioral: Individualized physical activity management systemThe 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. |
| 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. |
Who may qualify
- Ages
- 35 to 60 years
- Sex
- Female only
- Healthy volunteers
- Accepted
- Age groups
- Adult
Key inclusion criteria (2 listed)
- BMI>25
- Who do not have any obstacle to participating in physical activities
Key exclusion criteria (1 listed)
- Who have previously used a smart band to increase their physical activity levels
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Individualized physical activity management systemParticipants 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. | Behavioural | Individualized physical activity management system |
Primary outcome
International Physical Activity Questionnaire (IPAQ) score
Time frame: 3 months
Participants' International Physical Activity Questionnaire (IPAQ) score.
Daily step count
Time frame: 3 months
Participants' daily step counts measured with their smart bands
BMI
Time frame: 3 months
Weight and height will be combined to report BMI in kg/m^2
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 28 Oct 2024.
- BackgroundWorld Health Organization. Burden: mortality, morbidity and risk factors. Global status report on non communicable diseases. 2010.
- BackgroundWHO European Regional Obesity Report. Copenhagen: WHO Regional Office for Europe. 2022. Licence: https://creativecommons.org/licenses/by-nc-sa/3.0/igo
- BackgroundFadhil, A. Towards Automatic and Personalised Mobile Health Interventions: An Interactive Machine Learning Perspective. arXiv preprint arXiv:1803.01842. 2018
- Background: PubMed 30969715Niemiro GM, Rewane A, Algotar AM. Exercise and Fitness Effect on Obesity. 2023 Nov 17. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2026 Jan-. Available from http://www.ncbi.nlm.nih.gov/books/NBK539893/
- Background: PubMed 20044854Evenson 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.
- Background: PubMed 18687261Pinto 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.
- Background: PubMed 15090118Bandura A. Health promotion by social cognitive means. Health Educ Behav. 2004 Apr;31(2):143-64. doi: 10.1177/1090198104263660.
- Background: PubMed 11148297Bandura A. Social cognitive theory: an agentic perspective. Annu Rev Psychol. 2001;52:1-26. doi: 10.1146/annurev.psych.52.1.1.
- Background: PubMed 30717779Shamizadeh 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.
- Individual participant dataSharing planned: Yes. The data of this research will be shared with researchers who request it via e-mail.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Individualized physical activity management system in people with Physical Inactivity, run by Istanbul University - Cerrahpasa at 1 site in Turkey (Türkiye).
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 28 Oct 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Turkey (Türkiye). Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
International Physical Activity Questionnaire (IPAQ) score (time frame: 3 months). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06225518, which also lists 9 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 28 Oct 2024.