Understanding Trust in AI Symptom Checker Applications Through Empathy and Privacy
Keywords:
Artificial Intelligence, Symptom Checker Applications, Perceived Empathy, Privacy Concerns, Young AdultsAbstract
The increasing use of artificial intelligence in healthcare has introduced AI symptom checker applications as accessible tools for identifying health conditions and supporting early medical decision making. Despite their growing adoption among young adults, trust remains a critical factor influencing user acceptance of these applications. This study examines the influence of perceived empathy and privacy concerns on trust in AI symptom checker applications among young adults. A quantitative approach was employed using a questionnaire distributed to young adults aged 18 to 35 who had experience using AI-based symptom checker applications or digital healthcare platforms with symptom analysis features. A total of 168 valid responses were collected and analyzed using multiple linear regression through SPSS. The findings indicate that perceived empathy has a positive and significant effect on trust, while privacy concerns have a negative and significant effect on trust. The regression results also show that perceived empathy has a stronger influence than privacy concerns in shaping user trust toward AI symptom checker applications. These findings highlight the importance of integrating empathetic communication features and strengthening data privacy protection in AI healthcare technologies. This study contributes to the development of human-centered healthcare innovation by emphasizing that trust in AI systems is shaped not only by technical functionality but also by emotional interaction and ethical data management.
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Copyright (c) 2026 Sunda Ariana, Linda Unsriana, Dedeh Supriyanti, Shakeel Rahagi, Nur Silawati
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