Source comparison
TB-500 Research Apple Health Integration: Protocol Comparison
MyFitnessPal Custom Food Entries Low. Single app entry syncs automatically Exact (meal timestamp) Moderate. Requires calorie-to-dose decoding post-export Moderate. Nutrition data cluttered with non-nutrition entries Best for researchers prioritizing ease over
This comparison does not assign a generated winner or score.
- MyFitnessPal Custom Food Entries
- Low. Single app entry syncs automatically
- Exact (meal timestamp)
- Moderate. Requires calorie-to-dose decoding post-export
- Moderate. Nutrition data cluttered with non-nutrition entries
- Best for researchers prioritizing ease over data purity. Works reliably but requires post-processing
- Apple Shortcuts with Dictation
- Moderate. Voice prompts each entry
- Exact (automation timestamp)
- High. Structured notes field preserves raw protocol details
- Low. Data isolated in custom fields, minimal cross-contamination
- Ideal for researchers comfortable with iOS automation. Most flexible but requires setup expertise
- Spreadsheet Parallel Tracking
- High. Manual dual-entry into Apple Health + spreadsheet
- Manual alignment needed
- Highest. Full control over data structure and correlation analysis
- Very Low. Complete separation prevents data corruption
- Gold standard for formal research protocols. Labor-intensive but produces publication-grade datasets
- LabArchives + Manual Health Export
- Moderate. Peptide data in LabArchives, biomarkers auto-captured by Apple Watch
- Retrospective alignment via export timestamps
- High. Both datasets export to CSV for statistical analysis
- Very Low. Professional-grade separation of research vs wellness data
- Preferred by institutional researchers. Maintains audit trail and regulatory compliance