Aged, Artificial Intelligence (AI), Cognition, Exercise, Health Behavior
Conditions
Brief summary
The purpose of this study is to develop an artificial intelligence-based chatbot application to support exercise behavior in individuals aged 60 and over who do not regularly exercise, and to evaluate its effectiveness. In addition, the study aims to examine the effects of changes in exercise habits on the cognitive (mental) functions of older adults. In this study, the impact of a chatbot-supported personalized exercise program on cognitive functions in older individuals will be evaluated. A total of 90 participants is planned for inclusion in this study. If you agree to participate in this study, depending on the group you are assigned to, you may receive: * An artificial intelligence-based chatbot program, along with educational materials about the importance of exercise, or * Only educational materials (brochures) prepared by the researchers about the importance of exercise. At the beginning of the study, you will be asked to complete a data collection form. The same form will also be administered at week 12 and week 24. This form will include: * Basic information such as your age and gender, * Questions about your exercise habits, * A brief test to assess your cognitive (mental) functions, * Questions evaluating your level of physical activity. The study duration is 24 weeks, including 12 weeks of intervention and 12 weeks of follow-up.
Interventions
BEHAVIORALArtificial intelligence-supported chatbot
Participants will receive a combined behavioral intervention of an educational brochure developed by the Ministry of Health and access to an artificial intelligence (AI)-supported chatbot designed to promote physical activity. The brochure will provide standardized written information on the importance of exercise, including general recommendations, health benefits, and basic guidance for an active lifestyle. Participants will also have access to an AI-supported chatbot throughout the intervention period. The chatbot will deliver automated, interactive messages to increase physical activity, including motivational prompts, educational reinforcement, and behavior-change support. The intervention will be delivered digitally via the chatbot platform, with no medication or physical devices required. The total duration and frequency of chatbot interactions will be continuous and on-demand during the study period.
Sponsors
Dokuz Eylul University
Vinnova
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
SUPPORTIVE_CARE
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
65 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
* Aged 65 years and older * Normal or mildly impaired cognitive status * Medical condition that does not prevent participation in physical activity * Ability to use a smartphone or tablet (for chatbot access) * Voluntary participation
Exclusion criteria
* Moderate to severe dementia * Severe depression or serious psychiatric disorders * Acute cardiovascular risk * Communication difficulties due to significant hearing or visual impairment * Regular engagement in structured exercise within the past 6 months (participants in the maintenance phase of exercise behavior)
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Cognitive function | Day 0, 3. Month, 6. Month | Cognitive function will be assessed using the Mini-Mental State Examination (MMSE), a standardized tool evaluating orientation, memory, attention, language, and visuospatial abilities. Higher scores indicate better cognitive performance. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Physical activity level | Day 0, 3. Month, 6. Month | Physical activity level will be measured using the Physical Activity Scale for the Elderly (PASE), which assesses the frequency and duration of physical activity in older adults, including leisure, household, and occupational activities. Higher scores indicate higher physical activity levels. |
Countries
Turkey (Türkiye)
Contacts
CONTACTGizem Limnili, MD
CONTACTMakbule Neslişah Tan, Associate Professor
STUDY_DIRECTORGizem Limnili
Dokuz Eylul University Faculty of Medicine Department of Family Medicine
PRINCIPAL_INVESTIGATORMakbule Neslişah Tan
Dokuz Eylul University Faculty of Medicine Department of Family Medicine
STUDY_CHAIRVildan Mevsim, Prof
Dokuz Eylul University Faculty of Medicine Department of Family Medicine
Outcome results
None listed