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<p>Artificial intelligence (AI) is increasingly transforming healthcare research by improving data analysis, efficiency, and evidence-based decision-making. However, its practical utilization among healthcare professionals remains inconsistent, particularly in low- and middle-income settings. To assess healthcare professionals’ perception and utilization of AI in healthcare research and examine their relationship and associated factors. A quantitative descriptive cross-sectional study was conducted among 160 healthcare professionals from nursing, medicine, dentistry, and pharmacy institutes in Bhubaneswar, India. Participants were selected using purposive sampling. Data were collected using structured and validated questionnaires assessing perception and utilization of AI in research. Data were analyzed using descriptive and inferential statistics, including correlation and regression analyses. Most participants demonstrated a neutral perception toward AI (73.8%), while 26.3% reported a positive perception (mean: 59.62 ± 8.82). Utilization was predominantly moderate (50%), followed by low (44.4%) and high (5.6%) levels (mean: 41.03 ± 14.38). AI tools were mainly used for writing, grammar correction, and literature search, whereas advanced analytical applications were less frequently utilized. Significant differences in perception and utilization were observed across professional groups. A moderate positive correlation was identified between perception and utilization (<i>r</i> = 0.463, <i>p</i> = 0.001). Regression analysis showed that perception significantly predicted utilization (R² = 0.220, <i>p</i> = 0.001), while designation (<i>p</i> = 0.021), research experience (<i>p</i> = 0.007), and area of specialization (<i>p</i> = 0.006) significantly influenced utilization. Relative Importance Index analysis indicated higher use of AI for automation tasks and lower use in methodology design and data interpretation. Healthcare professionals demonstrated moderate perception but limited utilization of AI in research. Strengthening AI-focused training, improving access to advanced AI tools, and enhancing institutional support may facilitate effective AI integration into healthcare research and improve evidence-based practice.</p>

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Perception and utilization of artificial intelligence in healthcare research among professionals in India: a cross-sectional study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月22日

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  • Sneha Ganguly,
  • Sasmita Das,
  • N. Siva,
  • Nageshwar Venkatesh Reddy

摘要

Artificial intelligence (AI) is increasingly transforming healthcare research by improving data analysis, efficiency, and evidence-based decision-making. However, its practical utilization among healthcare professionals remains inconsistent, particularly in low- and middle-income settings. To assess healthcare professionals’ perception and utilization of AI in healthcare research and examine their relationship and associated factors. A quantitative descriptive cross-sectional study was conducted among 160 healthcare professionals from nursing, medicine, dentistry, and pharmacy institutes in Bhubaneswar, India. Participants were selected using purposive sampling. Data were collected using structured and validated questionnaires assessing perception and utilization of AI in research. Data were analyzed using descriptive and inferential statistics, including correlation and regression analyses. Most participants demonstrated a neutral perception toward AI (73.8%), while 26.3% reported a positive perception (mean: 59.62 ± 8.82). Utilization was predominantly moderate (50%), followed by low (44.4%) and high (5.6%) levels (mean: 41.03 ± 14.38). AI tools were mainly used for writing, grammar correction, and literature search, whereas advanced analytical applications were less frequently utilized. Significant differences in perception and utilization were observed across professional groups. A moderate positive correlation was identified between perception and utilization (r = 0.463, p = 0.001). Regression analysis showed that perception significantly predicted utilization (R² = 0.220, p = 0.001), while designation (p = 0.021), research experience (p = 0.007), and area of specialization (p = 0.006) significantly influenced utilization. Relative Importance Index analysis indicated higher use of AI for automation tasks and lower use in methodology design and data interpretation. Healthcare professionals demonstrated moderate perception but limited utilization of AI in research. Strengthening AI-focused training, improving access to advanced AI tools, and enhancing institutional support may facilitate effective AI integration into healthcare research and improve evidence-based practice.