Detecting Acute Otitis Media Symptom Episodes Using a Mobile App: Cohort Study.

Area of Science:

• Infectious Disease Epidemiology
• Digital Health Technology
• Pediatric Health Monitoring

Background:

• Population cohort studies are vital for tracking infectious diseases outside healthcare settings.
• Traditional methods like paper diaries suffer from poor compliance and recall bias.
• Smart technology offers a promising solution to enhance case finding in such studies.

Purpose of the Study:

• To validate an interactive mobile app for monitoring acute infectious diseases, independent of healthcare seeking.
• To assess participant compliance and app performance in detecting acute otitis media (AOM) symptom episodes in infants.
• To compare the novel app-based tool with traditional methods for disease monitoring.

Main Methods:

• The InfectieApp was tested to detect AOM symptom episodes in children aged 0-3 years.
• A 2013 cohort used paper diaries and questionnaires; a 2015 cohort used a mobile app for AOM symptom recording.
• Both cohorts were followed for 4 months, with data collected on symptom presence and disease questionnaires.

Main Results:

• App-based recording showed higher symptom recording rates per diary day (43.99%) compared to paper (32.50%).
• The incidence of AOM symptom episodes was higher with the app (835/1000 child-years) versus paper (605/1000 child-years).
• Disease questionnaire completion was 100% with the app versus 59% with paper diaries.

Conclusions:

• The smart diary app significantly improved AOM case finding and disease questionnaire completeness.
• This technology enhances the accuracy of disease burden estimates for common infectious diseases.
• Mobile apps represent a valuable tool for improving data quality in epidemiological research.