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.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
SUPPORTIVE_CARE
Masking
NONE
Enrollment
100
This intervention consists of a mobile health application (Polis Saúde®) integrated with a wearable activity tracker (Fitbit Inspire 3) designed to support physical activity monitoring and behavior change in adults with metabolic syndrome. The mobile application delivers personalized motivational messages and educational content twice weekly and records user engagement, including app usage and interaction with content. The wearable device continuously tracks step count and synchronizes data with the app. Participants are encouraged to use the app and device daily over a 6-month period. Data on adherence, physical activity, and health metrics will be collected to evaluate the impact on lifestyle and clinical outcomes.
USF Cruz de Celas
Coimbra, Portugal, Portugal
Physical Literacy
Physical literacy will be assessed using the Perceived Physical Literacy Instrument (PPLI-PT), a validated questionnaire evaluating motivation, confidence, knowledge, and participation in physical activity (5-point Likert scale, 1=Strongly disagree to 5=Strongly agree). The questionnaire was composed by nine items distributed across three dimensions: * Knowledge and understanding: Items PPLI-PT4, PPLI-PT5, PPLI-PT17; * Self-perception and self-confidence: Items PPLI-PT2, PPLI-PT7, PPLI-PT8; * Self-expression and communication with others: Items PPLI-PT11, PPLI-PT12, PPLI-PT13. Scoring and Interpretation: For each dimension, add the responses to the corresponding items, divide the total by the number of items in the dimension (3) to obtain the average and record the scores for each dimension separately. Higher scores in each dimension reflect a greater perceived physical literacy in the respective specific area.
Time frame: Baseline, 6 months.
EQ5D-5L
An instrument to describe and value health across a wide range of disease areas. 5-level EQ-5D (EuroQol instrument with 5 dimensions and 5 levels) version with five dimensions (five levels, categorical options): mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. Score ranges: 1. I have no problems ...walking/dressing, etc (better outcome); 2. I have some problems ...walking/dressing, etc; 3. I have moderate problems ...walking/dressing, etc; 4. I have severe problems ...walking/dressing, etc; 5. I have extreme problems ...walking/dressing, etc (worse outcome).
Time frame: Baseline, 6 months
Physical Activity Levels
Physical activity will be measured using the International Physical Activity Questionnaire (IPAQ - Short Version, 4 topics with 2 questions each one - question 1a, question 1b, question 2a, question 2b, etc). Score based on the formula: MET-min/week = MET × minutes per day × days per week (values for minutes and days per week are answered through questions 1a, 1b, 2a, 2b, 3a, 3b, 4a, 4b) Standard MET values for each activity type: * Walking: 3.3 METs * Moderate activity: 4.0 METs * Vigorous activity: 8.0 METs
Time frame: Baseline, 6 months
Clinical and Metabolic Health Parameters - Total cholesterol
Total cholesterol (mg/dl)
Time frame: Baseline, 6 months
Clinical and Metabolic Health Parameters - HDL cholesterol
HDL cholesterol (mg/dl - milligrams per deciliter)
Time frame: Baseline, 6 months.
Clinical and Metabolic Health Parameters - LDL cholesterol
HDL cholesterol (mg/dl - milligrams per deciliter) -- calculated field: LDL Cholesterol = Total Cholesterol - HDL Cholesterol - (Triglycerides / 5)
Time frame: Baseline, 6 months
Clinical and Metabolic Health Parameters - nHDL cholesterol
non-HDL cholesterol (mg/dl - milligrams per deciliter) -- calculated field: nHDL = Colesterol Total - Colesterol HDL
Time frame: Baseline, 6 months.
Clinical and Metabolic Health Parameters - Triglycerides
Triglycerides (mg/dl - milligrams per deciliter)
Time frame: Baseline, 6 months.
Clinical and Metabolic Health Parameters - Fasting Glucose
Fasting Glucose (mg/dl - milligrams per deciliter)
Time frame: Baseline, 6 months.
Clinical and Metabolic Health Parameters - Glycated Hemoglobin
Glycated Hemoglobin (%)
Time frame: Baseline, 6 months.
Clinical and Metabolic Health Parameters - Aspartate Aminotransferase
Aspartate Aminotransferase (U/L - units per liter)
Time frame: Baseline, 6 months.
Clinical and Metabolic Health Parameters - Alanine Aminotransferase
Alanine Aminotransferase (U/L - units per liter)
Time frame: Baseline, 6 months.
Anthropometric Data - Body Mass Index (BMI)
BMI-Body Mass Index (kg/m² - kilograms per square meter)
Time frame: Baseline, 6 months.
Anthropometric Data - Abdominal circumference
Abdominal circumference (cm)
Time frame: Baseline, 6 months.
Anthropometric Data - Waist-to-height ratio
Waist-to-height ratio (WHtR, cm-centimeter) WHtR = Waist Circumference (cm-centimeter) ÷ Height (cm-centimeter)
Time frame: Baseline, 6 months.
Anthropometric Data - Blood pressure
Blood pressure (mm Hg-millimeters of mercury)
Time frame: Baseline, 6 months.
Anthropometric Data - Heart rate
Heart rate (beat per minute)
Time frame: Baseline, 6 months.
App Usage Metrics - Daily Active Users
Number of users engaging with the app daily (integer).
Time frame: 6 months.
App Usage Metrics - Monthly Active Users
Number of users engaging with the app at least once per month (integer).
Time frame: 6 months.
App Usage Metrics - Session Frequency
How often users open the app per day or week (number/day or /week).
Time frame: 6 months.
App Usage Metrics - Session Duration
Average time spent in the app per session (minutes).
Time frame: 6 months.
Push Notification Engagement - Open Rate (%)
Percentage of push notifications opened.
Time frame: 6 months.
Push Notification Engagement - Dismissal Rate (%)
Percentage of notifications ignored or dismissed.
Time frame: 6 months.
Wearable activity tracker - measure 1
Data from the wearable activity tracker (e.g., step count and app usage patterns) - DESCREVER EXATAMENTE QUAIS SÃO AS MEDIÇÕES ANALISADAS
Time frame: 6 months
Motivational Content Interaction - Message Open Rate (%)
Percentage of users who open motivational messages.
Time frame: 6 months.
Motivational Content Interaction - Completion Rate (%)
Percentage of users who fully read the messages.
Time frame: 6 months
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.
Motivational Content Interaction - Feedback Responses
Number of "thumbs up" or "thumbs down" clicks on messages, reflecting their perceived usefulness
Time frame: 6 months
Physical Activity Metrics - Step Count Increase (%)
Change in the average daily step count over time.
Time frame: 6 months.
Retention Rate by Users (%)
Percentage of users returning to the app after 1 week, 1 month, etc.
Time frame: 6 months.
Streak Tracking
Number of consecutive days comprising interaction with the app.
Time frame: 6 months
Dropout rate (%)
Participants will be classified as dropouts if they have not used the mobile application and wearable device for a continuous period of 60 days.
Time frame: 6 months