Year: 2026 | Month: September | Volume: 16 | Issue: 9 | Pages: 260-267
DOI: https://doi.org/10.52403/ijhsr.20260927
Self-Diagnosis and Self-Medication Using Digital Health Information And AI-Assisted Platforms Among Software Employees
Narni Hanumanth1, Kona J S Surya Prabha2, G Rama Krishna3, Ved P Kulkarni4, K Bhuvaneswari5
1Assistant Professor, 2Associate Professor, 3Assistant Professor, 4Professor and HOD, 5Intern,
Department of Community Medicine, GVP Institute of Health Care and Medical Technology, Andhra Pradesh, India
Corresponding Author: Dr Narni Hanumanth
ABSTRACT
Background: The increasing availability of digital health information and artificial intelligence (AI)-assisted platforms has significantly influenced health-seeking behaviour. Individuals increasingly rely on these platforms for symptom interpretation and treatment decisions, which may lead to self-diagnosis and self-medication practices.
Objectives: To estimate the proportion of software employees practicing self-diagnosis and self-treatment using digital health information and AI-assisted platforms, and to determine factors influencing these practices.
Methods: A cross-sectional study was conducted among 75 software employees using a pre-tested semi-structured electronic questionnaire. Participants were selected using a non-random chain-referral sampling method. Data were analysed using SPSS version 25. Descriptive statistics were expressed as frequencies and percentages. Associations were analysed using Chi-square or Fisher’s exact test, and prevalence ratios with 95% confidence intervals were calculated.
Results: The majority of participants were aged 21–25 years (53.3%) and male (68%). Overall, 58.7% practiced self-diagnosis using digital health information and AI-assisted platforms, while 21.3% reported self-treatment practices. Most participants (70.7%) sometimes searched for health information when experiencing symptoms, and 48% searched for drug-related information online. About 20% reported adverse drug reactions. No statistically significant association was observed between socio-demographic variables and self-diagnosis or self-treatment practices (p>0.05).
Conclusion: A considerable proportion of software employees rely on digital health information and AI-assisted platforms for self-diagnosis, with a smaller proportion engaging in self-treatment. While digital platforms are widely used for preliminary health understanding, most individuals continue to prefer professional medical consultation.
Key words: Self-diagnosis, Self-medication, Digital health information, Artificial intelligence, Health-seeking behaviour