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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Dec 7, 2023
Date Accepted: Oct 14, 2024

The final, peer-reviewed published version of this preprint can be found here:

Unveiling Usage Patterns and Explaining Usage of Symptom Checker Apps: Explorative Longitudinal Mixed Methods Study

Wetzel AJ, Preiser C, Müller R, Joos S, Koch R, Henking T, Haumann H

Unveiling Usage Patterns and Explaining Usage of Symptom Checker Apps: Explorative Longitudinal Mixed Methods Study

J Med Internet Res 2024;26:e55161

DOI: 10.2196/55161

PMID: 39652845

PMCID: 11667141

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

“Do I really not need to go to the doctor?” Unveiling usage patterns and predicting usage of Symptom Checker Apps: an explorative longitudinal study

  • Anna-Jasmin Wetzel; 
  • Christine Preiser; 
  • Regina Müller; 
  • Stefanie Joos; 
  • Roland Koch; 
  • Tanja Henking; 
  • Hannah Haumann

ABSTRACT

Background:

Symptom Checker Applications (SCA) aim to enable individuals without medical training to classify perceived symptoms and receive guidance on appropriate actions, such as self-care or seeking professional medical attention. However, there is a lack of detailed understanding regarding the contexts in which individuals use SCAs and their opinions on these tools.

Objective:

This mixed-methods study aims to explore the circumstances under which medical laypeople utilize SCAs and to identify which aspects users find noteworthy after using SCA.

Methods:

A total of n=48 SCA users documented their medical symptoms, provided open-ended responses, and recorded their SCA use along with other variables over six weeks in a longitudinal study. General Linear Mixed Models (GLMM) with and without regularization were applied to consider the hierarchical structure of the data, and the models' outcomes were evaluated for comparison. Qualitative data were analyzed through Kuckartz's qualitative content analysis

Results:

Significant predictors of SCA use included the initial occurrence of symptoms, day of measurement, self-rated health and the following ICPC-2 classified symptom: general and unspecified, eye, cardiovascular, musculoskeletal and skin. The day of measurement and self-rated health showed minor importance due to their small effect sizes. Qualitative analysis highlighted four main themes: (1) reasons for utilizing SCA, diverse (2) affective responses, a broad spectrum of (3) behavioral reactions and (4) unmet needs including a lack of personalization.

Conclusions:

The emergence of new and unfamiliar symptoms was a strong determinant for SCA utilization. Specific ICPC rated symptom clusters, particularly those related to cardiovascular, eye, skin, general, and unspecified symptoms, were also highly predictive of SCA use. The varied applications of SCAs fit into the concept of health literacy as bricolage, where SCAs are leveraged as flexible tools by patients based on individual and situational requirements, functioning alongside other healthcare resources. Clinical Trial: German Clinical Trials Register (DRKS) DRKS00022465


 Citation

Please cite as:

Wetzel AJ, Preiser C, Müller R, Joos S, Koch R, Henking T, Haumann H

Unveiling Usage Patterns and Explaining Usage of Symptom Checker Apps: Explorative Longitudinal Mixed Methods Study

J Med Internet Res 2024;26:e55161

DOI: 10.2196/55161

PMID: 39652845

PMCID: 11667141

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