https://orcid.org/0000-0003-4458-3634
Figures
Abstract
Background
Artificial intelligence (AI) is rapidly advancing in healthcare and has the potential to transform patient care. This study aimed to assess the knowledge, attitudes, and practices (KAP) regarding AI among pediatricians in India.
Methods
A cross-sectional, web-based nationwide survey was conducted, with participants recruited via pediatric WhatsApp groups between 23 March, 2024 to 1 April 2024. A validated 25-item questionnaire, comprising multiple-choice, open-ended, yes/no, and five-point Likert scale questions, was administered using Google Forms. Descriptive statistics were used to summarize responses.
Results
A total of 116 pediatricians participated in the survey. The calculated sample size for the study was 114. As we had 116 responses on day 10, the survey was withdrawn accounting to a response rate of 6.7%. Most participants (91.4%) understood the concept of AI; however, only 33.6% were familiar with AI applications in pediatric practice. The majority (83.6%) anticipated the integration of AI in pediatrics within the next decade, and 90.5% expressed interest in learning more about AI applications. Notably, 25.9% reported concerns regarding AI use, and 48.3% perceived their workplaces as currently not adequately equipped to implement AI tools. Commonly used AI tools included ChatGPT, Canva AI, Neonatal AI, Google AI, Trusted Computing Base (TCB), and Voicera.
Citation: Tyagi M, Ravi R, Rao SS, Kamath N, Soans ST (2025) Knowledge, attitudes and practices toward artificial intelligence among pediatricians in India: A cross-sectional web-based nationwide survey. PLoS One 20(12): e0338314. https://doi.org/10.1371/journal.pone.0338314
Editor: Sampath Kumar Amaravadi, University of Birmingham, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
Received: September 9, 2025; Accepted: November 20, 2025; Published: December 12, 2025
Copyright: © 2025 Tyagi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Background
Artificial intelligence (AI) is increasingly transforming healthcare, with applications in diagnostic decision support, medical imaging, drug discovery, surgical assistance, virtual health assistants, and remote patient monitoring [1–3]. AI systems have demonstrated strong performance in tasks such as medical image interpretation, natural language processing for clinical data, speech recognition, semantic reasoning, and predictive analytics, sometimes achieving accuracy comparable to or exceeding that of human clinicians [4–6]. The integration of AI into healthcare has the potential to improve diagnostic accuracy, optimize treatment pathways, and enhance patient outcomes, although concerns regarding training, ethics, and adoption remain among healthcare professionals [7].
Several international surveys have explored physicians’ knowledge, attitudes, and practices (KAP) regarding AI in medicine. These studies, conducted across specialties such as dermatology [8], psychiatry [9], radiology [10,11], pediatrics [12], surgery [13], and among medical students and residents [14–16], generally report limited knowledge and training but a high level of interest in AI’s potential applications. For example, radiologists and psychiatrists have shown optimism toward AI tools but also uncertainty about integration into clinical workflows. Similar trends have been reported among medical students and residents, who express enthusiasm but lack structured educational opportunities.
In India, research on physicians’ perspectives toward AI remains limited, with few studies addressing pediatricians specifically. Pediatric care presents unique challenges such as child-specific diagnostics, developmental monitoring, and the need for family-centered approaches that may shape how pediatricians view and adopt AI. Understanding these perspectives is critical to guide the development of appropriate training programs, policy initiatives, and the inclusion of AI-related content in medical curricula.
Nasscom has predicted that AI and AI data is expected to generate about 30 billion US dollars to the GDP of India. [17] AI based health innovations have significantly impacted Ayushman Bharat Digital Mission. With the industry academia collaboration, AI with algorithms in machine learning and deep learning is contributing to prediction of disease, analysis of medical images, personalized plans for treatment, platforms for telemedicine, AI backed diagnostics and wearable devices in the ecosystem of Indian healthcare. [18].
The primary objective of this study was to evaluate the knowledge, attitudes, and practices of pediatricians in India regarding the use of AI in Pediatric practice. A secondary objective was to explore their interest in education and training in AI and their willingness to integrate AI tools into pediatric practice.
Materials and methods
The present study received ethical approval from the Institutional Ethical Committee of KMC Mangalore (IEC KMC MLR 03/2024/178). A cross-sectional, web-based survey was carried out to evaluate the knowledge, attitudes, and practices (KAP) regarding AI among pediatricians practicing in India. The online consent was obtained from the participants before participation in the study.
The questionnaire developed by Pecqueux et al. [13] served as the basis for the survey, with modifications to incorporate multiple-choice, open-ended, dichotomous (yes/no), and five-point Likert scale questions. The instrument was subjected to content validation by five pediatricians with over ten years of professional experience, using a four-point relevance scale. Items rated as “relevant” or “quite relevant” were retained following the calculation of the scale content validity index (S-CVI) [19]. The resulting S-CVI of 0.88 indicated excellent content validity.
The finalized questionnaire consisted of 25 items: 6 demographic questions, 9 assessing knowledge, 6 evaluating attitudes, and 4 addressing practices related to AI. This version was converted into an online format using Google Forms, with all questions made mandatory to ensure completeness of responses. Data collection was conducted between 23 March 2024 and 1 April 2024. The survey link was disseminated via WhatsApp to 1,725 pediatricians across India to ensure pan India representation of practicing Pediatricians with minimum two years’ experience in the field. Retired Pediatricians and academic residents were excluded from participation in the study. Distribution channels included the Indian Academy of Pediatrics Dakshina Kannada branch (185 members), the Pediatric Rheumatology Group (129 members), Kasturba Medical College Pediatric Alumni Group (325 members), the Mahatma Gandhi Institute of Medical Sciences Pediatric Alumni Group (114 members), the National Women’s Pediatricians Forum (947 members), and the authors’ personal contacts (25 members). The survey remained open till we achieved the calculated sample size (10 days) A brief introduction outlining study objectives and confidentiality assurances was provided, and informed consent was obtained prior to participation. The estimated completion time was 8–10 minutes. All responses were reviewed by the principal investigator.
The sample size was calculated for estimation of population proportion based on the previous study using the formula: n = x2pq/e2. At 95% confidence level and with 5% level of significance, z-score (z) is 1.96. Margin of error (e) = 4%, Population proportion p = 0.95 and q = 0.15 [20] Substituting values to the above formula, the sample size (n)= 114.
The study adhered to the Checklist for Reporting Results of Internet E-Surveys (CHERRIES) guidelines [21]. Descriptive statistics were computed using SPSS Version 29 (IBM Corporation, Armonk, NY, USA), with means, standard deviations, and ranges calculated for continuous variables, and frequencies and percentages reported for categorical variables.
Results
A total of 116 pediatricians completed the survey as per our sample size calculation, yielding a response rate of 6.7%. Among the respondents, 45 (38.8%) were female and 71 (61.2%) were male. Participant ages ranged from 27 to 82 years, with a mean of 46 years (±13.04). The demographic characteristics of the participants are summarized in Table 1.
The responses to the Yes, No and Not sure questions exploring knowledge, attitude and practice towards AI tool are tabulated in Table 2a, 2b and 2c.
The responses to various multiple-choice questions with different options for exploring knowledge, attitudes and practices are tabulated in Table 3a, 3b and 3c.
A total of 90.5% of the participants responded that they were very interested/interested in learning more about AI. Overall, there was poor knowledge about AI among the participants, and the participants exhibited positive attitudes towards learning more about AI and its application. However, 73% were concerned about possible ethical and legal problems, which could arise from the use of AI. As depicted in Figure 1, respondents identified several key potential advantages of AI in pediatric practice.
Sixty-nine percent of the participants reported improved diagnostic certainty, 56.9% greater consistency in diagnostic and management decisions, and 55.2% reported less time spent by specialists on monotonous tasks as a potential advantage of AI in pediatric practice. For the open-ended question, which explored the tool used by pediatricians, 99 (85.3%) participants did not use AI tools. ChatGPT was the most preferred tool, and the other AI tools reported were Canva AI, Neonatal AI, Google AI, Trusted compute base (TCB), and Voicera. Overall, the results suggest acceptance of the use of AI among pediatricians, but at the same time, they expressed a need for additional information and training.
Discussion
This study provides insight into the knowledge, attitudes, and practices (KAP) regarding AI among pediatricians in India, highlighting both opportunities and challenges in adopting AI in pediatric care. Overall, while most respondents (91.4%) understood the term AI, a majority (59.5%) were unaware of AI subtypes, and only one respondent had prior formal training. Despite this limited formal knowledge, most pediatricians (76%) were willing to use AI alongside their clinical expertise, and nearly all (99%) believed that AI applications could positively impact pediatric healthcare. These findings suggest a high degree of optimism and readiness to learn, consistent with international studies showing similar enthusiasm among physicians and pediatricians in Europe, Russia, and Pakistan [8,10,12,14,15,22,23].
Interestingly, while respondents recognized the theoretical potential of AI in improving diagnostic accuracy, streamlining workflows, and enhancing patient care, the tools they most commonly used were general-purpose applications, such as ChatGPT and Canva AI, rather than pediatric-specific AI solutions. This gap between theoretical knowledge and practical usage emphasizes the need for targeted educational programs that provide pediatricians with training in specialty-specific AI tools and applications. The Indian Association of Pediatrics should take initiatives for CME programs to bridge this gap.
Concerns regarding ethical, legal, and practical aspects of AI were also reported. Approximately three-quarters of respondents worried about potential complications, and over 60% expressed concerns about AI’s inability to empathize or consider the emotional wellbeing of children and caregivers. Other concerns included lack of flexibility, difficulties with controversial cases, and reliability of AI applications developed without sufficient clinical expertise. These findings align with previous studies among Russian and English physicians, highlighting shared apprehensions regarding the integration of AI in clinical practice [15,23].
The study also suggests differences in attitudes based on experience and self-reported knowledge, with younger and more digitally literate pediatricians appearing more open to adopting AI. Although subgroup analyses were limited by sample size, these trends underscore the importance of stratified educational strategies to address knowledge gaps across career stages.
Several limitations must be acknowledged. First, the survey had a low response rate (6.7%), which may limit the generalizability of the findings. Second, distribution via WhatsApp may have introduced selection bias toward pediatricians with higher digital literacy. Third, knowledge and attitudes were self-reported, which may not accurately reflect objective understanding or competence in AI usage. Despite these limitations, the study provides valuable preliminary insights into pediatricians’ perceptions of AI in India.
Implications and future directions.
The findings highlight the need for structured training and continuing medical education programs on AI in pediatrics. Professional associations and academic institutions can develop workshops, online modules, and curricula that focus on the ethical, clinical, and practical aspects of AI use in pediatric care. Additionally, future research should aim for larger, nationally representative samples, objectively assess AI competence, and evaluate the impact of AI integration on clinical outcomes in pediatric practice.
Conclusion
Most pediatricians in India are aware of AI and its potential impact on healthcare. However, formal knowledge and training in AI remain limited, and only a small proportion currently use AI tools in clinical practice. While respondents expressed optimism about AI’s ability to support diagnosis, management, and data analysis, many also raised concerns regarding ethical, legal, and practical implications.
These findings highlight an urgent need for structured educational initiatives to improve awareness, knowledge, and responsible adoption of AI in pediatric practice. National professional bodies, such as the Indian Academy of Pediatrics, should lead efforts to provide continuing medical education programs and workshops for practicing pediatricians. Furthermore, integrating AI principles and applications into undergraduate and postgraduate medical curricula is essential to ensure ethically informed and clinically competent use of AI in pediatric healthcare. By addressing these gaps, pediatricians can be better prepared to leverage AI effectively, ultimately improving patient care and outcomes.
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