JMIR Publications

ABSTRACT

Background:

The full spectrum of side-effects of Covid-19 vaccinations and infections, including milder symptoms or other health effects that do not result in contacts with healthcare, remains unknown. Person-centered self-reporting of symptoms may be a solution.

Objective:

We aim to describe how Symptoms, a system for person-centered self-reporting of symptoms, functions and health-related quality of life, was used in the setting of an investigation of Covid-19 vaccine side-effects.

Methods:

Recently vaccinated individuals were identified as the ideal population to query for milder symptoms of Covid-19 vaccinations and infections. For that purpose, we used posters in the observation areas after Covid-19 vaccination at 150 vaccination sites to invite newly vaccinated individuals to use a novel digital system, Symptoms. In the Symptoms system, users can chart their symptoms, functions and quality of life, as often as they like, using evidence-based patient-reported outcome measures and short numeric rating scales for a pre-specified list of symptoms, and for self-defined symptoms if the relevant symptom was not on the pre-specified list.

Results:

731 people created a user account and consented to share data with the study from July 21, 2021 to Sept 27, 2022. A total of 563 individuals (77%) reported having one or more symptoms. The most common symptom was pain at the injection site (86.3%) followed by fatigue (32.1%) and headache (30%). A total of 143 unique symptoms were reported. Of these, 29 symptoms were pre-specified suggestions, and the remaining 80% were self-defined symptoms.

Conclusions:

Self-reported symptoms in the Symptoms system seemed to align with previously observed self-experienced symptoms after Covid-19 vaccination. The system seems to have been fairly easy to use, and was seen to capture relatively broad data in a longitudinal fashion. The person-centered and self-directed nature of the system appeared important for capturing the whole burden of symptoms experienced by the users.