This study will explore whether integrating a mobile app to track physical activity-recommended by family doctors during routine primary care visits-can help individuals with metabolic syndrome become more active. Participants will be randomly assigned to one of two groups: the intervention group will use the mobile app combined with an activity-tracking wristband; the control group will receive usual care without digital tools.

Family doctors will introduce and support the use of the mobile app during standard consultations. The study will also assess physicians' perceptions of using digital technologies, such as mobile apps and telemedicine, to encourage physical activity.

Researchers will monitor the frequency of app use, step counts and changes in physical activity habits over time.

The primary goal is to determine whether digital health tools can be feasibly implemented in primary care to promote healthier lifestyles and improve chronic disease management in people with metabolic syndrome.

This study examines the impact of a mobile application for tracking physical activity (PA) on the management of metabolic syndrome in a primary care setting. It also explores family physicians' attitudes and behavioral intentions regarding the adoption of telemedicine tools for health promotion.

This is a two-arm, parallel-group, superiority randomized controlled pilot study. Adult patients diagnosed with metabolic syndrome, who own a compatible smartphone, will be recruited from primary care units. Eligible participants will be randomly assigned to one of two groups: an intervention group, receiving a mobile health application (Polis Saúde®) integrated with a wearable PA-tracking device (Fitbit Inspire 3), or to a control group receiving the usual care without digital tools. Follow-up assessments will be conducted at baseline and 6 months.

The mobile application offers personalized motivational messages, health education content, and real-time PA monitoring. Data will be collected on app usage, engagement with motivational content, step counts, and participant feedback. Clinical and anthropometric data, such as lipid profiles, fasting glucose, blood pressure, BMI, and waist circumference, will also be collected.

Primary outcomes include adherence to the intervention (app usage, engagement with motivational content), retention, step count data, and dropout rates. Secondary outcomes include assessment of physical literacy, PA habits (via IPAQ), app usage metrics (frequency, session duration, feedback responses, completion and dismissal rates, etc).

The study will further assess family physicians' attitudes and intentions toward telemedicine (using the PAIT questionnaire).

Data will be analyzed using descriptive and inferential statistics, including regression and survival models.

The study aims to assess the feasibility, adherence, and potential effectiveness of mobile health technologies for promoting PA and managing chronic conditions in primary care. It will also provide insights into the behavioral determinants of physician adoption of digital health tools. The findings will inform future large-scale trials and contribute to clinical strategies and public health policies that integrate digital health solutions into chronic disease care.

Inclusion Criteria:

• Adults aged 18 years or older;

• Diagnosed with metabolic syndrome;

• Presence of at least one of the following ICPC-2 (International Classification of Primary Care - 2nd edition), used in primary health care:codes in the medical record:

  • T83 (Overweight) or T82 (Obesity), with waist circumference ≥ 94 cm (men) or ≥ 80 cm (women)
  • T89 (Non-insulin-dependent diabetes)
  • T93 (Lipid metabolism disorder: HDL < 40 mg/dl for men, < 50 mg/dl for women; or triglycerides ≥ 150 mg/dl)
  • K86 (Hypertension without complications) or K87 (Hypertension with complications);

• Access to a smartphone compatible with the mobile application;

• Does not currently use any physical activity monitoring device (e.g., pedometer, smartwatch, fitness tracker);

• Willing and able to provide informed consent.

Exclusion Criteria:

• No scheduled medical appointments in the past three years;
• Refusal to participate or withdraws consent;
• Change of primary care unit during the study period;
• Pregnant at the time of enrollment or becomes pregnant during the study;
• Diagnosed mental incapacity that prevents answering questionnaires;
• Does not own a smartphone;
• Inability to use a mobile application;
• Inability to use a physical activity tracking wristband.