Development of a text message-based headache diary in adolescents and children
Abstract
BACKGROUND: International guidelines recommend diaries in migraine trials for prospective collection of headache symptoms. Studies in other patient populations suggest higher adherence with electronic diaries instead of pen-and-paper. This study examines the feasibility of a text message-based (texting) diary for children and adolescents with headache.
METHODS: This is a secondary analysis of data from a study validating a pediatric scale of treatment expectancy. We developed a Health Insurance Portability and Accountability Act-compliant texting diary collecting headache characteristics, medication use, and disability with 3-5 core daily questions for 4 or 12 weeks depending on headache treatment. Adherence was incentivized.
RESULTS: 93 participants consented to the expectancy study. Five participants opted for a paper diary for follow-up. 88 participants chose the texting diary with 28 4-week and 60 12-week participants. Five participants did not complete the enrollment visit. Of those remaining 83, 89% of 4-week and 93% of 12-week participants responded on at least 80% of days. On average, participants fully completed 88% (4-week cohort) and 90% (12-week) of diary entries.
CONCLUSIONS: Text messages are a promising method for collecting patient-reported data. Adherence was similar to that reported for paper diaries in other pediatric migraine trials, but time-stamped entries ensure real-time data collection.
How strong is the evidence?
Evidence Hub reads this as a cohort study, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence. Reported size: 93 participants or records.
Read the paper
Related studies
- Calcium Ions in the Physiology and Pathology of the Central Nervous System
- AI-powered in silico twins: redefining precision medicine through simulation, personalization, and predictive healthcare
- In silico functional, structural and pathogenicity analysis of missense single nucleotide polymorphisms in human MCM6 gene
- In Silico drug repurposing pipeline using deep learning and structure based approaches in epilepsy
- Targeting serotonin receptors with phytochemicals – an in-silico study
- In silico exploration of anti-prostate cancer compounds from differential expressed genes
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.