Obesity & Overweight
Conditions
Keywords
Digital health, Artificial intelligence, Nutritional tracking, Food recognition, Mobile health, Eating behavior, Usability
Brief summary
NutriTrack is a digital health application designed to support nutritional and behavioral tracking in patients with obesity followed in an outpatient obesity clinic. The application allows patients to record food intake using food photographs, barcode scanning, or manual search, and to register behavioral variables related to eating episodes. This prospective, single-center, observational pilot study will evaluate the feasibility and usability of NutriTrack in 20 to 50 adult patients with obesity or overweight with comorbidities followed at the Obesity Clinic of Hospital Clínico San Carlos. Participants will use the application for 4 weeks as a complementary tool. The information generated by NutriTrack will be available to healthcare professionals as supportive information and will not replace clinical judgment or modify usual care decisions. The main outcome is usability measured using the System Usability Scale. Secondary and exploratory outcomes include agreement between artificial intelligence-based nutritional estimates and standard dietitian assessment, adherence to daily food logging, professional perceived clinical utility, changes in eating behavior and emotional regulation scales, and technical feasibility of data export.
Detailed description
NutriTrack is a digital health application developed within Hospital Clínico San Carlos and Universidad Complutense de Madrid to support nutritional and behavioral tracking in patients with obesity. The application integrates artificial intelligence-based food image recognition, the Spanish BEDCA nutritional database, and a rule-based engine for the detection of clinically relevant eating patterns. This is a prospective, single-center, observational pilot study with complementary clinical use. The application will be used by adult patients followed at the Obesity Clinic for 4 weeks. Participants will record daily food intake and behavioral variables related to eating episodes, including hunger, satiety, emotional state, eating context, eating speed, perceived control, and cravings. Healthcare professionals may review the NutriTrack clinical panel as supportive information. The application output will not replace clinical judgment, will not trigger automated clinical decisions, will not modify usual care, and will not be integrated into the hospital electronic health record during the pilot phase. The study will assess usability, nutritional estimation accuracy, adherence to food logging, professional perceived clinical utility, exploratory changes in emotional regulation and eating behavior, and technical feasibility of data export. The study is intended to generate preliminary evidence to support future larger-scale validation.
Interventions
OTHERNutriTrack digital health application
NutriTrack is a digital health application used for nutritional and behavioral tracking. Patients record food intake using food photographs, barcode scanning, or manual search, and report behavioral variables such as hunger, satiety, emotional state, eating context, eating speed, perceived control, and cravings. The application output is informational, requires healthcare professional supervision, and does not replace clinical judgment or modify usual care.
Sponsors
Francisco José García González
Hospital San Carlos, Madrid
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Age 18 years or older. * Diagnosis of obesity, defined as body mass index 30 kg/m2 or higher, or overweight with comorbidities, defined as body mass index 27 kg/m2 or higher. * Active follow-up at the Obesity Clinic of Hospital Clínico San Carlos. * Regular possession and use of a smartphone with iOS or Android operating system. * Ability to read and understand Spanish. * Signed informed consent.
Exclusion criteria
* Active diagnosed eating disorder, including anorexia nervosa, bulimia nervosa, or binge eating disorder. * Cognitive impairment preventing autonomous use of the application. * Simultaneous participation in another nutritional intervention study. * Inability or refusal to use mobile technology. * Current pregnancy or breastfeeding. * Acute medical condition requiring hospitalization during the study period.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| System Usability Scale score | Week 4 | Usability of the NutriTrack application measured using the System Usability Scale. The score ranges from 0 to 100, with higher scores indicating better usability. A score of 70 or higher will be considered acceptable. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Correlation between AI-based caloric estimation and dietitian assessment | Week 4 | Correlation between caloric estimation obtained using NutriTrack artificial intelligence-based food image recognition and standard dietitian-nutritionist assessment. |
| Adherence to daily food logging | From baseline to Week 4 | Percentage of days with complete food intake records during the 4-week follow-up period. |
| Healthcare professional perceived clinical utility score | Week 4 | Perceived clinical utility of NutriTrack assessed by the healthcare professional using an ad hoc questionnaire. |
Countries
Spain
Contacts
CONTACTFrancisco José García González, PhD, RN
PRINCIPAL_INVESTIGATORFrancisco José García González, PhD, RN
Hospital Clínico San Carlos / Universidad Complutense de Madrid
Outcome results
None listed