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

J Med Internet Res. 2024 Dec 9:26:e55161. doi: 10.2196/55161.

Abstract

Background: Symptom checker apps (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 SCA and their opinions on these tools.

Objective: This mixed methods study aims to explore the circumstances under which medical laypeople use SCA and to identify which aspects users find noteworthy after using SCA.

Methods: A total of 48 SCA users documented their medical symptoms, provided open-ended responses, and recorded their SCA use along with other variables over 6 weeks in a longitudinal study. Generalized linear mixed models with and those 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 qualitative content analysis.

Results: Significant predictors of SCA use included the initial occurrence of symptoms, day of measurement (odds ratio [OR] 0.97), self-rated health (OR 0.80, P<.001), and the following International Classification in Primary Care-2-classified symptoms, that are general and unspecified (OR 3.33, P<.001), eye (OR 5.56, P=.001), cardiovascular (OR 8.33, P<.001), musculoskeletal (OR 5.26, P<.001), and skin (OR 4.76, P<.001). 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 using SCA, (2) diverse affective responses, (3) a broad spectrum of 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 use. Specific International Classification in Primary Care-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 SCA fit into the concept of health literacy as bricolage, where SCA is leveraged as flexible tools by patients based on individual and situational requirements, functioning alongside other health care resources.

Keywords: GLMM; General Linear Mixed Models; Kuckartz; applications; apps; circumstances; content analysis; eHealth; explorative longitudinal study; mHealth; mixed method; mobile health; participants; patterns; prediction; predicts; qualitative data; self care; self management; self-diagnosis; self-rated; self-triage; survey; symptoms checker; usage; users.

MeSH terms

  • Adult
  • Female
  • Humans
  • Longitudinal Studies
  • Male
  • Middle Aged
  • Mobile Applications*
  • Self Care