Pediatricians’ Knowledge, Attitudes and Clinical Practices Regarding Drug-Drug Interactions: A Survey Study

Pediatricians’ Knowledge, Attitudes and Clinical Practices Regarding Drug-Drug Interactions: A Survey Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Pediatricians’ Knowledge, Attitudes and Clinical Practices Regarding Drug-Drug Interactions: A Survey Study Ercan TUTAK, Yunus Emre AYHAN, Berre MERCÜMEK, Nilay AKSOY This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6673873/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Drug-drug interactions (DDIs) are an important health problem that can cause serious side effects and treatment failures, especially in pediatric patients. Healthcare professionals' knowledge, attitudes and clinical practices about DDI play a critical role in preventing these risks. The aim of this study was to evaluate the knowledge, attitudes and clinical practices of pediatric physicians about DDIs and to examine the relationship of these factors with demographic characteristics. Method Demographic characteristics, DDI education status, knowledge levels and clinical practices of the participants were evaluated with questionnaires and knowledge tests. Statistical analyses included correlation, t-test, ANOVA and multiple regression analyses. Results A total of 290 pediatricians were included in the study. The mean age of the participants was 46.9 years, and 61.4% had received DDI training. The highest correct response rate (94.8%) was observed in the question about nephrotoxicity risk, while the lowest rate (31.4%) was observed in the question about the use of evidence-based resources. 45.2% of the participants evaluated their knowledge level as insufficient. In clinical practice, 47.2% sometimes and 12.4% always perform DDI checks, while 37.2% never do checks. A weak but significant negative correlation was found between age and knowledge level, and the effect of other variables was not significant. Conclusion The DDI knowledge of pediatricians is at a moderate level, and there are some gaps, especially in the use of evidence-based resources. Dissemination of clinical decision support systems and continuous training are necessary to improve drug safety and patient care quality. Pediatricians Drug-Drug Interactions Knowledge Attitudes Clinical Practices Education Survey Background Pediatric patients frequently receive multiple medications during hospitalization, which increases their susceptibility to drug–drug interactions (DDIs). In a retrospective cohort study, Dai et al. reported that hospitalized children were exposed to an average of 10 medications per day and up to 20 different drugs throughout their hospital stay. The magnitude and nature of DDIs in children may differ significantly from adults due to age-related physiological variations and distinct pharmacokinetic and pharmacodynamic profiles ( 1 ). Pharmacokinetic (PK) DDIs are typically evaluated in healthy adult volunteers, and their results are reflected in drug labeling and post-marketing surveillance. However, data on PK interactions in pediatric patients, particularly infants, remain scarce due to ethical and practical constraints such as difficulties in blood sampling and patient recruitment. Extrapolating adult data to children may lead to either overestimation or underestimation of interaction risks. Salerno et al. emphasized that DDIs in pediatric patients can be life-threatening and advocated for the inclusion of systematic interaction assessments in all pediatric drug development programs ( 2 , 3 ) Potential DDIs (pDDIs) are defined as preventable circumstances that may increase drug toxicity or reduce therapeutic efficacy. Various clinical decision support tools and electronic drug interaction databases are now available to predict pDDIs and alert prescribers to take precautionary measures ( 4 , 5 ) Nevertheless, studies continue to show that DDIs are frequently under-recognized and inadequately managed in pediatric clinical settings, where polypharmacy is common ( 6 ) This underscores the importance of assessing healthcare professionals’ knowledge and attitudes towards DDIs. Although limited research exists on pediatricians’ knowledge, attitudes, and clinical practices regarding DDIs, their level of understanding plays a critical role in safe prescribing. Inadequate knowledge can result in unsafe drug combinations and adverse outcomes, whereas improved awareness and training can enhance therapeutic safety and efficacy. Prior studies have shown that educational interventions significantly improve pediatricians’ DDI knowledge and are associated with better patient outcomes ( 7 , 8 ). This study aims to evaluate pediatricians’ knowledge, attitudes, and clinical practices related to DDIs. It also explores the challenges they face in managing DDIs and identifies the sources of information they rely on. The results may inform the development of targeted training programs and the improvement of drug safety protocols in pediatric care. Method Study Design and Participants This cross-sectional online survey was conducted between April 1 and 30, 2025, targeting pediatric specialists working in various healthcare institutions across Istanbul. The questionnaire was developed using Google Forms and distributed via online links shared through phone messaging applications and social media platforms. Ethical approval Ethical approval was obtained from the Altınbaş University Health Sciences Research Ethics Committee (Approval No. 2024/54; Date: February 6, 2025). Participation was voluntary, and informed consent was obtained electronically at the beginning of the survey. Data Collection and Survey Questions The survey instrument was developed through a comprehensive literature review to assess pediatricians’ knowledge, attitudes, and clinical practices regarding DDIs. The structured questions were reviewed by both a clinical pharmacist and a pediatrician to ensure content validity and consistency (3,9–13). A pilot study involving 20 pediatricians (not included in the final sample) was conducted to assess clarity and reliability. Internal consistency was acceptable (Cronbach’s alpha = 0.6). The survey was administered using Google Forms and distributed to pediatricians via a secure online link. Upon accessing the link, participants were presented with a brief description of the study and asked to confirm their willingness to participate. Those who selected “no” were automatically excluded from the survey, thereby ensuring informed consent. The survey link was primarily shared through the WhatsApp platform. The questionnaire began with 12 items collecting sociodemographic and educational information (e.g., age, gender, years of experience, and subspecialty status). It was followed by 15 structured questions divided equally into three sections: knowledge of DDIs, attitudes toward DDIs, and clinical practices related to DDI management. The English version of the survey is provided in the supplementary material. Survey Evaluation and Scoring Participants’ knowledge of DDIs was evaluated objectively, with one point awarded for each correct response and zero points for incorrect answers, resulting in a total score ranging from 0 to 5. The questionnaire included 15 structured questions, categorized into three equal sections: Knowledge of DDIs (5 items): Focused on awareness of specific drug interactions, toxicity types, interaction severity, and the use of clinical decision support systems. Attitudes toward DDIs (5 items): Explored participants’ perspectives on the clinical importance of DDIs, the use of clinical guidelines, and the perceived need for further education on this topic. Clinical practices regarding DDIs (5 items): Assessed how pediatricians incorporate DDI checkers into routine practice, including frequency of use, reliance on decision support tools, prescribing considerations, and collaboration with colleagues. Based on their knowledge scores, participants were classified into the following categories: 0–1 points: Low knowledge level 2–3 points: Intermediate knowledge level 4–5 points: High knowledge level Inclusion and Exclusion Criteria The study included pediatricians who were actively practicing in healthcare institutions across Istanbul at the time of data collection. Participants who submitted incomplete responses were excluded from the final analysis. Sample Calculation The total number of pediatric specialists in Istanbul was estimated to be approximately 3,000. Based on this population, a minimum sample size of 263 participants was calculated to ensure a 95% confidence level with a ±5% margin of error, assuming a 25% response rate. A convenience sampling method was employed, and the survey was distributed directly to pediatricians via online communication channels. Only those who voluntarily consented to participate were included in the study. The potential for selection bias due to the non-random sampling method was acknowledged when interpreting the findings. Statistical analysis Categorical variables were summarized as frequencies and percentages, while continuous variables were expressed as means ± standard deviations. The normality of numerical data was assessed using the Kolmogorov-Smirnov test, confirming a parametric distribution. Accordingly, parametric statistical methods were applied. Associations between binary categorical variables and knowledge scores were analyzed using independent samples t-tests, while comparisons across more than two groups were performed using one-way ANOVA. Correlation analysis was conducted to evaluate linear relationships between continuous variables, and linear regression analysis was used to identify factors influencing the knowledge score. The internal consistency of the knowledge-related items was assessed using Cronbach’s alpha coefficient (α = 0.6). All statistical analyses were conducted using IBM SPSS Statistics for Windows, version 29.0 (Armonk, NY: IBM Corp.), with a significance level set at p < 0.05. Results Of the 500 pediatricians invited to participate, 290 completed the survey, yielding a response rate of 58%. The participants’ demographic and professional characteristics are summarized in Table 1. The mean age was 46.9 ± 8.7 years, and 52.4% were male. Regarding experience, 61.4% of participants had 16 or more years of practice. Additionally, 59.0% reported having a pediatric subspecialty. As shown in Table 1, the most common subspecialty was neonatology (26.9%), followed by pediatric gastroenterology, social pediatrics, and pediatric cardiology. Participants were nearly evenly distributed between public (52.4%) and private hospitals (47.6%), and 39.0% worked in institutions with 31 or more inpatient beds. Table 1: Demographic and drug-interaction education characteristics of participants Characteristic n = 290 Age, mean ± standard deviation 46.9 ± 8.7 Sex, n (%) Male 152 (52.4) Female 138 (47.6) Experience (year), n (%) 0-5 years 24 (8.3) 6-10 years 36 (12.4) 11-15 years 52 (17.9) ≥16 years 178 (61.4) Subspecialty, n (%) Yes 171 (59.0) No 119 (41.0) Specialty area, n (%) Neonatology 78 (26.9) Social Pediatrics 10 (3.4) Pediatric Gastroenterology 11 (3.8) Pediatric Cardiology 5 (1.7) Pediatric Nephrology 10 (3.4) Pediatric Intensive Care 6 (2.1) Pediatric Neurology 10 (3.4) Other 41 (14.1) Institution type, n (%) Public hospital 152 (52.4) Private hospital 138 (47.6) Bed Capacity, n (%) 0-10 beds 80 (27.6) 11-20 beds 57 (19.7) 21-30 beds 40 (13.8) ≥31 beds 113 (39.0) Education status about DDIs, n (%) Yes 178 (61.4) No 112 (38.6) Education format , n (%) During university education 116 (65.0) Online training program 7 (4.0) In-service seminar/course 55 (31.1) Preferred sources of DDI information , n (%) Academic textbooks 14 (4.8) Clinical decision support systems 201 (69.3) Online databases/books 70 (24.1) Other 5 (1.7) Education sufficiency on DDI , n (%) Agree 50 (17.2) Disagree 131 (45.2) Undecided 109 (37.6) Willingness to attend additional DDI education Yes 262 (90.3) No 28 (9.7) DDI: Drug-drug interaction In terms of prior education on drug–drug interactions, 61.4% of pediatricians reported having received DDI training. Of these, the majority (65.0%) received their training during medical school, while others attended in-service training (31.1%) or online courses (4.0%). The most commonly used sources for DDI information were clinical decision support systems (69.3%), followed by online databases/books (24.1%) and academic textbooks (4.8%). All 290 participants responded to the five knowledge-based questions on DDIs, as summarized in Table 2. The highest correct response rate (94.8%) was for the question on nephrotoxicity risk (aminoglycosides and vancomycin), while the lowest rate (31.4%) was for identifying Lexicomp as an evidence-based resource for DDI evaluation. The mean knowledge score was 3.1 ± 1.0, with 7.1% of participants classified as having low knowledge (0–1 correct answers), 57.6% moderate (2–3 correct), and 35.3% high knowledge (4–5 correct). Table 2: Knowledge-based questions on drug-drug interactions and correct response rates Question Correct Answer n = 290 Which of the following drug pairs is most likely to cause a major DDI? Furosemide and Ibuprofen 206 (71.0) Which drug combination may increase the risk of nephrotoxicity? Aminoglycosides and Vancomycin 275 (94.8) Which level of DDI poses the highest clinical risk? Contraindicated 182 (62.8) What is the term for precipitation or discoloration when two IV drugs are mixed in the same solution? Incompatibility 167 (57.6) Which of the following is among the evidence-based source for evaluating DDIs? Lexicomp 91 (31.4) DDI: Drug-drug interaction Participants’ perceptions and attitudes regarding DDI knowledge and education are presented in Table 3. When asked to self-assess their knowledge, 45.2% rated themselves as poor, 43.4% as moderate, and only 11.4% as good. Nearly all participants (97.9%) emphasized the importance of using clinical guidelines and decision support tools to prevent DDIs, and all respondents (100%) agreed that education on DDIs should be increased. Regarding the level of intervention, 64.8% believed that all types of DDIs should be addressed, whereas 33.8% thought only contraindicated or major interactions required intervention. Table 3: Participants’ self-perceptions and attitudes regarding drug-drug interactions Item Response Option n = 290 How do you evaluate your knowledge level on DDIs? Good 33 (11.4) Moderate 126 (43.4) Poor 131 (45.2) How important do you consider the use of clinical guidelines and decision support systems to prevent DDIs? Very important 284 (97.9) Moderately important 6 (2.1) Do you agree that training on DDIs should be increased? Agree 290 (100.0) At what level should DDIs be intervened in clinical practice? Contraindicated and major interactions 98 (33.8) Moderate and minor interactions only 4 (1.4) All levels 188 (64.8) If evaluating DDIs requires additional time in your practice, does this pose a barrier for you? Sometimes a barrier 128 (44.1) Often a barrier 26 (9.0) Not a barrier 133 (45.9) Always a barrier 3 (1.0) DDI: Drug-drug interaction As shown in Table 4, only 12.4% of participants reported always checking for DDIs in clinical practice, while 47.2% did so occasionally, and 37.2% never performed DDI checks. Upon identifying a potential interaction, the majority (87.2%) stated that they intervene immediately, whereas 6.6% monitor without taking action, and 5.2% consulted a pharmacist. Table 4: Clinical practices regarding drug-drug interactions and prevention strategies Question Response Option n = 290 How often do you check for DDIs in clinical practice? Sometimes 137 (47.2) Always 36 (12.4) Never 108 (37.2) How do you generally approach DDIs when identified in a patient's prescription? Consult with pharmacists 15 (5.2) Monitor but do not intervene 19 (6.6) Intervene immediately 253 (87.2) Which decision support systems do you benefit from when checking DDIs? Mobile apps 29 (10.0) Electronic prescribing systems 78 (26.9) Clinical decision support systems 125 (43.1) What is the primary factor you consider when prescribing multiple medications? Drug dose 100 (34.5) Drug availability 96 (33.1) Side effects 85 (29.3) What strategies would you recommend for the prevention of DDIs in clinical practice? Increase training programs 37 (12.8) Utilize decision support systems 20 (6.9) Develop clinical guidelines 25 (8.6) All of the above 208 (71.7) DDI: Drug-drug interaction A Pearson correlation analysis was conducted to examine the relationships between total knowledge score and various independent variables. A weak but statistically significant negative correlation was found between age and total knowledge score (r = -0.184, p = 0.002). However, no statistically significant correlation was found between gender, experience, subspecialty status, institution type, hospital bed capacity, and DDI education status (p > 0.05). Independent samples t-test analysis revealed no statistically significant differences in total knowledge scores by gender, subspecialty status, institution type, or DDI education status (p > 0.05 for all comparisons). Similarly, one-way ANOVA showed no significant differences in knowledge scores based on years of experience, institutional bed capacity, or education format (p > 0.05). Additional subgroup analyses were conducted to assess whether clinical role characteristics were associated with differences in DDI-related knowledge. When participants were compared based on their subspecialty area, no statistically significant difference was found in total knowledge scores across subspecialty groups (p = 0.145). Similarly, when participants were grouped according to whether they worked in a neonatal or pediatric intensive care unit, no significant difference was observed in total knowledge scores (p = 0.928). A multiple linear regression analysis was performed to identify factors associated with the total knowledge score. The independent variables included age, gender, years of experience, subspecialty status, institution type, hospital bed capacity, and DDI education format. The model was statistically significant (F = 2.302, p = 0.029), with an R² value of 0.087, indicating that it explained 8.7% of the variance in knowledge scores. However, none of the individual predictor variables had a statistically significant effect on the outcome (p > 0.05 for all). Discussion This study meticulously assessed the knowledge levels, attitudes, and clinical practices of pediatricians concerning DDIs. The average age of the pediatricians was 46.9 years, more than half were male, and the majority had 16 years or more of experience in the pediatric field. This demographic structure is important as it reflects the perspectives of experienced pediatricians on DDIs. A weak but statistically significant negative correlation between age and knowledge level suggests that older pediatricians may have reduced access to up-to-date information or may be in greater need of knowledge refreshment. This may be partly due to decreased use of technological resources with age, which can limit access to current drug information and reduce awareness of emerging drug interactions. It was observed that 61.4% of pediatricians had received training on DDIs, though most of this training occurred during their university education. In contrast, in-service training and continuous professional development programs were found to be limited. This indicates a critical need for ongoing education throughout healthcare professionals' careers to ensure they stay current on issues such as DDIs. Multiple studies demonstrate that structured educational interventions significantly improve DDI knowledge among healthcare professionals and students, while also promoting safer prescribing practices and reducing the risk of adverse drug events (7,14,15). In addition, the fact that clinical decision support systems (69.3%) were the most preferred information source in our study highlights the critical role of technology in facilitating access to information and supporting clinical decisions in healthcare. Numerous studies have shown that technological tools—including those for managing DDIs and assisting clinical decision-making—improve information accessibility, encourage data-driven and collaborative care, enhance patient safety, and help clinicians make optimized treatment decisions. Nonetheless, issues such as usability, customization, standardization, and assessment of effectiveness remain ongoing challenges (16–19). The pediatricians' average knowledge score was 3.1, with 35.3% demonstrating a high level of understanding. However, 45.2% of pediatricians self-assessed their knowledge of DDIs as inadequate, revealing a notable gap between actual performance and perceived competence. This suggests that healthcare professionals are aware of their limitations and receptive to additional training and resources. Recognizing such knowledge deficits highlights the importance of continuous professional development in clinical practice. Although medical professionals often have insufficient knowledge of DDIs, the literature shows that they acknowledge the importance of these interactions and are willing to seek information, reflecting a mismatch between their actual knowledge and the importance they attribute to the issue (15,20,21). The highest correct response rate (94.8%) was observed for the question regarding drugs that pose a risk of nephrotoxicity, indicating that pediatricians are well aware of nephrotoxic medications. This knowledge is essential, as nephrotoxic drugs are implicated in a significant proportion of acute kidney injuries (AKIs) in pediatric patients, accounting for approximately 16% of all AKIs in older children and adolescents (22,23). Although our study did not examine pediatricians’ prescribing practices of nephrotoxic agents, the literature indicates that such medications are more frequently administered to children with chronic kidney disease (24). The low awareness regarding Lexicomp as an evidence-based resource for checking drug interactions (31.4% correct response) is concerning. Lexicomp Online is widely recognized for providing up-to-date, accurate, and reliable drug information, making it a valuable tool for healthcare professionals. This low level of awareness highlights the need for additional training on available digital drug information platforms. A systematic review reported that information technology-based interventions improve surrogate clinical outcomes and adherence to DDI alerts, although evidence on their direct clinical impact remains limited (25). Studies evaluating electronic drug information resources consistently identify Lexicomp Online as a leading tool, offering concise and current data to ensure safe prescribing practices (26). Other platforms, such as Micromedex, also contribute to updated drug information; however, Lexicomp was selected for our study due to its widespread hospital availability and frequent use in clinical practice. 45.2% of the pediatricians stated that their level of knowledge about DDIs is insufficient. However, 97.9% reported that clinical guidelines and decision support systems play a crucial role in preventing DDIs, and 100% agreed that DDI training should be expanded. This high level of awareness can serve as a driving force for the broader implementation of training programs and digital support tools. Abougalambou and Alenezi (2023) emphasized that while health professionals’ knowledge of DDIs is generally insufficient, there is a strong demand for structured training and technological support systems (8). The broader literature similarly underscores that although appropriate education on DDI management is essential, it remains inadequate in current clinical settings. Targeted educational interventions, integrated pedagogical strategies, and ongoing professional development are key methods for enhancing DDI-related competencies, thereby improving both patient safety and the overall quality of care (7,15,27,28). 37.2% of participants reported that they never check for DDIs, indicating a clear disconnect between knowledge and clinical practice. This is consistent with the literature, which shows that despite recognizing the importance of DDIs, healthcare professionals often face time constraints and heavy workloads that hinder their ability to perform DDI checks. Over half of the pediatricians in our study identified limited time as a major barrier to incorporating DDI evaluations into their routine practice. Likewise, existing research confirms that insufficient time and clinical workload are key obstacles to the effective implementation of DDI control measures (29). Furthermore, 87.2% of pediatricians reported taking prompt action upon detecting DDIs, yet only 5.2% sought consultation from pharmacists. This suggests that while pediatricians are proactive in managing DDIs, they rarely engage in multidisciplinary collaboration by utilizing the expertise of pharmacists. The literature emphasizes the vital role of pharmacists in optimizing patient safety and supporting clinical decision-making in DDI management (5,30–32). It is widely recognized that involving pharmacists enhances the quality of care and reduces medication-related risks. Moreover, consulting pharmacists could help mitigate the time-related barriers that pediatricians often face when assessing DDIs. In the present study, demographic and professional variables—except for age—did not significantly influence the level of DDI knowledge. Although the regression model was valid, none of the independent variables showed a statistically significant association with knowledge scores. While Hardan et al. (2023) reported a link between years of experience and improved awareness of DDIs, our findings suggest that DDI knowledge cannot be explained solely by demographic or professional characteristics. Instead, more complex and nuanced factors—such as the quality of education, personal motivation, and institutional learning culture—should be considered to better understand what truly influences knowledge levels (15). Furthermore, subgroup analysis revealed no significant differences in knowledge scores between pediatricians working in intensive care settings and those who do not (p = 0.9298). Likewise, no statistically significant variation was found across different pediatric subspecialties (p = 0.145). This study has several limitations. First, the findings are based on participants’ self-reports, which may introduce bias and reduce the accuracy and objectivity of the data. The online format of the survey may have contributed to brief or incomplete responses, thereby limiting the depth of the collected information. Additionally, the study sample was geographically restricted to pediatricians working exclusively in Istanbul, which limits the generalizability of the results to other regions or healthcare systems. The cross-sectional design also prevents causal inferences from being made. Finally, the scope of the knowledge assessments was limited and may not fully reflect pediatricians’ actual clinical practices. Future research should consider expanding the sample to include a broader geographic distribution and utilize longitudinal study designs to evaluate the long-term effects of continuous DDI training. It would also be valuable to explore the specific barriers that prevent pediatricians from routinely integrating DDI checks into their clinical workflows. Conclusion This study revealed that pediatricians possess a moderate level of knowledge about DDIs, with a clear need for further training and support. While age showed a slight negative impact, no significant differences were found based on work setting or subspecialty. Despite positive attitudes, DDI checks were not consistently implemented in clinical practice. These findings highlight the importance of expanding structured DDI education, promoting the use of evidence-based digital tools, and integrating DDI control into routine workflows. Strengthening decision support systems and continuous professional development may help improve medication safety and care quality. Abbreviations AKIs: Acute kidney injuries DDIs: Drug-drug interactions PK: Pharmacokinetic pDDIs: Potential drug-drug interactions Declarations Ethics approval and consent to participate Ethical approval was obtained from the Altınbaş University Health Sciences Research Ethics Committee (Approval No. 2024/54; Date: February 6, 2025). Informed consent of participation was obtained electronically at the beginning of the survey. All procedures adhered to the ethical standards of the University of Siena and complied with the 1964 Helsinki declaration and its subsequent amendments. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding The author received no financial support for the research, authorship, and/or publication of this article. Clinical trial number Not applicable. Authors' contributions Author contributions are as follows ET: Conceptualization, Methodology, Data collection, Writing - review and editing, Resources, Supervision. YEA: Conceptualization, Methodology, Formal analysis and investigation, Data collection, Writing – original draft preparation, Writing - review and editing, Resources, Supervision. BM: Methodology, Data collection, Resources, Writing - review and editing, Resources. NA: Conceptualization, Methodology, Writing - review and editing. Resources, Supervision. Acknowledgements None. References Gonzalez D, Sinha J. Pediatric drug‐drug interaction evaluation: drug, patient population, and methodological considerations. The Journal of Clinical Pharmacology. 2021;61:S175–S187. Salem F, Rostami‐Hodjegan A, Johnson TN. Do children have the same vulnerability to metabolic drug–drug interactions as adults? A critical analysis of the literature. 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Drug related problems identified by clinical pharmacist at the Internal Medicine Ward in Turkey. Int J Clin Pharm. 2018;40(2):360–7. Dahri K, Araujo L, Chen S, Bagri H, Walia K, Lau L, et al. Community pharmacist perceptions of drug-drug interactions. Canadian Phamacists Journal. 2022;156(1):42–7. Additional Declarations No competing interests reported. Supplementary Files Survey.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6673873","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":471476387,"identity":"30579804-4157-4bf0-9147-e52b9e6028aa","order_by":0,"name":"Ercan TUTAK","email":"","orcid":"","institution":"Prof. Dr. Cemil Taşcıoğlu City Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ercan","middleName":"","lastName":"TUTAK","suffix":""},{"id":471476388,"identity":"e24f1740-bec1-4ea1-acf6-d5109e5b3cf0","order_by":1,"name":"Yunus Emre AYHAN","email":"","orcid":"","institution":"Prof. Dr. Cemil Taşcıoğlu City Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yunus","middleName":"Emre","lastName":"AYHAN","suffix":""},{"id":471476389,"identity":"de8fbc2a-fd26-4637-811c-4b50d67db8ee","order_by":2,"name":"Berre MERCÜMEK","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBklEQVRIiWNgGAWjYBACA1TuAZsEMJ1QQLyWtAQGNpAWA6yqsWo5DNGCLo4MzNl7n334wLBNzrz9jOmGD2fO5/HLdyd+eGDAIM8vdgCrFsue48YzZzDcNpY5k2N2c8aN28WSbbybJYAOM5w5OwG7w26kMTPzMNxOnCHBY3ab58PtxA3HeDeAtCQY3Mah5f4zZuY/DLfrwVr+fDgH0rL5B14tN9iYmRkYbidIgLQw3DgA0rINry2WPWnMjD0Gtw1n8KSV3ew5k5w4sy13m0WCgQROv5izH2Nm+FFxW16C/fC2Gz+O2SX2M5/dfPNHhY08vzR2LVDnYQpJ4FE+CkbBKBgFo4AQAAD77mBLIZd7hwAAAABJRU5ErkJggg==","orcid":"","institution":"Bezmialem Vakif University","correspondingAuthor":true,"prefix":"","firstName":"Berre","middleName":"","lastName":"MERCÜMEK","suffix":""},{"id":471476390,"identity":"59ddcefb-a144-4e20-bf21-3fabb9429701","order_by":3,"name":"Nilay AKSOY","email":"","orcid":"","institution":"Altınbaş University","correspondingAuthor":false,"prefix":"","firstName":"Nilay","middleName":"","lastName":"AKSOY","suffix":""}],"badges":[],"createdAt":"2025-05-15 15:08:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6673873/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6673873/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":96905241,"identity":"97f285a5-0f18-4e0f-b648-a4957fe6f433","added_by":"auto","created_at":"2025-11-27 12:09:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":814413,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6673873/v1/3eb46455-b9d3-4687-89c3-99bf27987aa8.pdf"},{"id":84787812,"identity":"05fd7b6e-6633-4be7-bebc-7dd8c67acb6a","added_by":"auto","created_at":"2025-06-17 10:48:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":100305,"visible":true,"origin":"","legend":"","description":"","filename":"Survey.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6673873/v1/bf1c4a549da7155f4de9b33b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Pediatricians’ Knowledge, Attitudes and Clinical Practices Regarding Drug-Drug Interactions: A Survey Study","fulltext":[{"header":"Background","content":"\u003cp\u003ePediatric patients frequently receive multiple medications during hospitalization, which increases their susceptibility to drug\u0026ndash;drug interactions (DDIs). In a retrospective cohort study, Dai et al. reported that hospitalized children were exposed to an average of 10 medications per day and up to 20 different drugs throughout their hospital stay. The magnitude and nature of DDIs in children may differ significantly from adults due to age-related physiological variations and distinct pharmacokinetic and pharmacodynamic profiles (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePharmacokinetic (PK) DDIs are typically evaluated in healthy adult volunteers, and their results are reflected in drug labeling and post-marketing surveillance. However, data on PK interactions in pediatric patients, particularly infants, remain scarce due to ethical and practical constraints such as difficulties in blood sampling and patient recruitment. Extrapolating adult data to children may lead to either overestimation or underestimation of interaction risks. Salerno et al. emphasized that DDIs in pediatric patients can be life-threatening and advocated for the inclusion of systematic interaction assessments in all pediatric drug development programs (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003cp\u003ePotential DDIs (pDDIs) are defined as preventable circumstances that may increase drug toxicity or reduce therapeutic efficacy. Various clinical decision support tools and electronic drug interaction databases are now available to predict pDDIs and alert prescribers to take precautionary measures (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) Nevertheless, studies continue to show that DDIs are frequently under-recognized and inadequately managed in pediatric clinical settings, where polypharmacy is common (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) This underscores the importance of assessing healthcare professionals\u0026rsquo; knowledge and attitudes towards DDIs.\u003c/p\u003e \u003cp\u003eAlthough limited research exists on pediatricians\u0026rsquo; knowledge, attitudes, and clinical practices regarding DDIs, their level of understanding plays a critical role in safe prescribing. Inadequate knowledge can result in unsafe drug combinations and adverse outcomes, whereas improved awareness and training can enhance therapeutic safety and efficacy. Prior studies have shown that educational interventions significantly improve pediatricians\u0026rsquo; DDI knowledge and are associated with better patient outcomes (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study aims to evaluate pediatricians\u0026rsquo; knowledge, attitudes, and clinical practices related to DDIs. It also explores the challenges they face in managing DDIs and identifies the sources of information they rely on. The results may inform the development of targeted training programs and the improvement of drug safety protocols in pediatric care.\u003c/p\u003e"},{"header":"Method","content":"\u003cp\u003e\u003cstrong\u003eStudy Design and Participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis cross-sectional online survey was conducted between April 1 and 30, 2025, targeting pediatric specialists working in various healthcare institutions across Istanbul. The questionnaire was developed using Google Forms and distributed via online links shared through phone messaging applications and social media platforms.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from the Altınbaş University Health Sciences Research Ethics Committee (Approval No. 2024/54; Date: February 6, 2025). Participation was voluntary, and informed consent was obtained electronically at the beginning of the survey.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Collection and Survey Questions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe survey instrument was developed through a comprehensive literature review to assess pediatricians’ knowledge, attitudes, and clinical practices regarding DDIs. The structured questions were reviewed by both a clinical pharmacist and a pediatrician to ensure content validity and consistency (3,9–13). A pilot study involving 20 pediatricians (not included in the final sample) was conducted to assess clarity and reliability. Internal consistency was acceptable (Cronbach’s alpha = 0.6).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe survey was administered using Google Forms and distributed to pediatricians via a secure online link. Upon accessing the link, participants were presented with a brief description of the study and asked to confirm their willingness to participate. Those who selected “no” were automatically excluded from the survey, thereby ensuring informed consent. The survey link was primarily shared through the WhatsApp platform.\u003c/p\u003e\n\u003cp\u003eThe questionnaire began with 12 items collecting sociodemographic and educational information (e.g., age, gender, years of experience, and subspecialty status). It was followed by 15 structured questions divided equally into three sections: knowledge of DDIs, attitudes toward DDIs, and clinical practices related to DDI management.\u0026nbsp;The English version of the survey is provided in the supplementary material.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSurvey Evaluation and Scoring\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants’ knowledge of DDIs was evaluated objectively, with one point awarded for each correct response and zero points for incorrect answers, resulting in a total score ranging from 0 to 5.\u003c/p\u003e\n\u003cp\u003eThe questionnaire included 15 structured questions, categorized into three equal sections:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eKnowledge of DDIs (5 items): Focused on awareness of specific drug interactions, toxicity types, interaction severity, and the use of clinical decision support systems.\u003c/li\u003e\n \u003cli\u003eAttitudes toward DDIs (5 items): Explored participants’ perspectives on the clinical importance of DDIs, the use of clinical guidelines, and the perceived need for further education on this topic.\u003c/li\u003e\n \u003cli\u003eClinical practices regarding DDIs (5 items): Assessed how pediatricians incorporate DDI checkers into routine practice, including frequency of use, reliance on decision support tools, prescribing considerations, and collaboration with colleagues.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eBased on their knowledge scores, participants were classified into the following categories:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e0–1 points: Low knowledge level\u003c/li\u003e\n \u003cli\u003e2–3 points: Intermediate knowledge level\u003c/li\u003e\n \u003cli\u003e4–5 points: High knowledge level\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eInclusion and Exclusion Criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study included pediatricians who were actively practicing in healthcare institutions across Istanbul at the time of data collection. Participants who submitted incomplete responses were excluded from the final analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample Calculation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe total number of pediatric specialists in Istanbul was estimated to be approximately 3,000. Based on this population, a minimum sample size of 263 participants was calculated to ensure a 95% confidence level with a ±5% margin of error, assuming a 25% response rate. A convenience sampling method was employed, and the survey was distributed directly to pediatricians via online communication channels. Only those who voluntarily consented to participate were included in the study. The potential for selection bias due to the non-random sampling method was acknowledged when interpreting the findings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCategorical variables were summarized as frequencies and percentages, while continuous variables were expressed as means ± standard deviations. The normality of numerical data was assessed using the Kolmogorov-Smirnov test, confirming a parametric distribution. Accordingly, parametric statistical methods were applied.\u003c/p\u003e\n\u003cp\u003eAssociations between binary categorical variables and knowledge scores were analyzed using independent samples t-tests, while comparisons across more than two groups were performed using one-way ANOVA. Correlation analysis was conducted to evaluate linear relationships between continuous variables, and linear regression analysis was used to identify factors influencing the knowledge score.\u003c/p\u003e\n\u003cp\u003eThe internal consistency of the knowledge-related items was assessed using Cronbach’s alpha coefficient (α = 0.6). All statistical analyses were conducted using IBM SPSS Statistics for Windows, version 29.0 (Armonk, NY: IBM Corp.), with a significance level set at p \u0026lt; 0.05.\u003c/p\u003e"},{"header":"Results ","content":"\u003cp\u003eOf the 500 pediatricians invited to participate, 290 completed the survey, yielding a response rate of 58%. The participants\u0026rsquo; demographic and professional characteristics are summarized in Table 1. The mean age was 46.9 \u0026plusmn; 8.7 years, and 52.4% were male. Regarding experience, 61.4% of participants had 16 or more years of practice. Additionally, 59.0% reported having a pediatric subspecialty.\u003c/p\u003e\n\u003cp\u003eAs shown in Table 1, the most common subspecialty was neonatology (26.9%), followed by pediatric gastroenterology, social pediatrics, and pediatric cardiology. Participants were nearly evenly distributed between public (52.4%) and private hospitals (47.6%), and 39.0% worked in institutions with 31 or more inpatient beds.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1:\u0026nbsp;\u003c/strong\u003eDemographic and drug-interaction education characteristics of participants\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003en = 290\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, mean \u0026plusmn; standard deviation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e46.9 \u0026plusmn; 8.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e152 (52.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e138 (47.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eExperience (year), n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0-5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e24 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6-10 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36 (12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11-15 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e52 (17.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;16 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e178 (61.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSubspecialty, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e171 (59.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e119 (41.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"8\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecialty area, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNeonatology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e78 (26.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSocial Pediatrics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePediatric Gastroenterology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePediatric Cardiology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePediatric Nephrology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePediatric Intensive Care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 (2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePediatric Neurology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e41 (14.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eInstitution type, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePublic hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e152 (52.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePrivate hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e138 (47.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBed Capacity, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0-10 beds\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e80 (27.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11-20 beds\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e57 (19.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21-30 beds\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40 (13.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;31 beds\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e113 (39.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation status about DDIs,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e178 (61.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e112 (38.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation format\u003c/strong\u003e\u003cstrong\u003e, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDuring university education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e116 (65.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOnline training program\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7 (4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIn-service seminar/course\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e55 (31.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePreferred sources of DDI information\u003c/strong\u003e\u003cstrong\u003e, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAcademic textbooks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eClinical decision support systems\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e201 (69.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOnline databases/books\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e70 (24.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation sufficiency on DDI\u003c/strong\u003e\u003cstrong\u003e, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e50 (17.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDisagree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e131 (45.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUndecided\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e109 (37.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWillingness to attend additional DDI education\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e262 (90.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28 (9.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eDDI: Drug-drug interaction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eIn terms of prior education on drug\u0026ndash;drug interactions, 61.4% of pediatricians reported having received DDI training. Of these, the majority (65.0%) received their training during medical school, while others attended in-service training (31.1%) or online courses (4.0%). The most commonly used sources for DDI information were clinical decision support systems (69.3%), followed by online databases/books (24.1%) and academic textbooks (4.8%).\u003c/p\u003e\n\u003cp\u003eAll 290 participants responded to the five knowledge-based questions on DDIs, as summarized in Table 2. The highest correct response rate (94.8%) was for the question on nephrotoxicity risk (aminoglycosides and vancomycin), while the lowest rate (31.4%) was for identifying Lexicomp as an evidence-based resource for DDI evaluation. The mean knowledge score was 3.1 \u0026plusmn; 1.0, with 7.1% of participants classified as having low knowledge (0\u0026ndash;1 correct answers), 57.6% moderate (2\u0026ndash;3 correct), and 35.3% high knowledge (4\u0026ndash;5 correct).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u0026nbsp;\u003c/strong\u003eKnowledge-based questions on drug-drug interactions and correct response rates\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"614\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 359px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuestion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCorrect Answer\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en = 290\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 359px;\"\u003e\n \u003cp\u003eWhich of the following drug pairs is most likely to cause a major DDI?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eFurosemide and Ibuprofen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e206 (71.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 359px;\"\u003e\n \u003cp\u003eWhich drug combination may increase the risk of nephrotoxicity?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eAminoglycosides and Vancomycin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e275 (94.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 359px;\"\u003e\n \u003cp\u003eWhich level of DDI poses the highest clinical risk?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eContraindicated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e182 (62.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 359px;\"\u003e\n \u003cp\u003eWhat is the term for precipitation or discoloration when two IV drugs are mixed in the same solution?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eIncompatibility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e167 (57.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 359px;\"\u003e\n \u003cp\u003eWhich of the following is among the evidence-based source for evaluating DDIs?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 187px;\"\u003e\n \u003cp\u003eLexicomp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e91 (31.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 614px;\"\u003e\n \u003cp\u003eDDI: Drug-drug interaction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eParticipants\u0026rsquo; perceptions and attitudes regarding DDI knowledge and education are presented in Table 3. When asked to self-assess their knowledge, 45.2% rated themselves as poor, 43.4% as moderate, and only 11.4% as good. Nearly all participants (97.9%) emphasized the importance of using clinical guidelines and decision support tools to prevent DDIs, and all respondents (100%) agreed that education on DDIs should be increased. Regarding the level of intervention, 64.8% believed that all types of DDIs should be addressed, whereas 33.8% thought only contraindicated or major interactions required intervention.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3:\u0026nbsp;\u003c/strong\u003eParticipants\u0026rsquo; self-perceptions and attitudes regarding drug-drug interactions\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eItem\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResponse Option\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en = 290\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 53px;\"\u003e\n \u003cp\u003eHow do you evaluate your knowledge level on DDIs?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003eGood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e33 (11.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e126 (43.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003ePoor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e131 (45.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 53px;\"\u003e\n \u003cp\u003eHow important do you consider the use of clinical guidelines and decision support systems to prevent DDIs?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003eVery important\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e284 (97.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003eModerately important\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e6 (2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eDo you agree that training on DDIs should be increased?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003eAgree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e290 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 53px;\"\u003e\n \u003cp\u003eAt what level should DDIs be intervened in clinical practice?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003eContraindicated and major interactions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e98 (33.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003eModerate and minor interactions only\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e4 (1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003eAll levels\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e188 (64.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 53px;\"\u003e\n \u003cp\u003eIf evaluating DDIs requires additional time in your practice, does this pose a barrier for you?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003eSometimes a barrier\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e128 (44.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003eOften a barrier\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e26 (9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003eNot a barrier\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e133 (45.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 32px;\"\u003e\n \u003cp\u003eAlways a barrier\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e3 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 100px;\"\u003e\n \u003cp\u003eDDI: Drug-drug interaction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAs shown in Table 4, only 12.4% of participants reported always checking for DDIs in clinical practice, while 47.2% did so occasionally, and 37.2% never performed DDI checks. Upon identifying a potential interaction, the majority (87.2%) stated that they intervene immediately, whereas 6.6% monitor without taking action, and 5.2% consulted a pharmacist.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4:\u0026nbsp;\u003c/strong\u003eClinical practices regarding drug-drug interactions and prevention strategies\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 340px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuestion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResponse Option\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en = 290\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 340px;\"\u003e\n \u003cp\u003eHow often do you check for DDIs in clinical practice?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eSometimes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e137 (47.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eAlways\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e36 (12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e108 (37.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 340px;\"\u003e\n \u003cp\u003eHow do you generally approach DDIs when identified in a patient\u0026apos;s prescription?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eConsult with pharmacists\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e15 (5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eMonitor but do not intervene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e19 (6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eIntervene immediately\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e253 (87.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 340px;\"\u003e\n \u003cp\u003eWhich decision support systems do you benefit from when checking DDIs?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eMobile apps\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e29 (10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eElectronic prescribing systems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e78 (26.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eClinical decision support systems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e125 (43.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 340px;\"\u003e\n \u003cp\u003eWhat is the primary factor you consider when prescribing multiple medications?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eDrug dose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e100 (34.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eDrug availability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e96 (33.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eSide effects\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e85 (29.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 340px;\"\u003e\n \u003cp\u003eWhat strategies would you recommend for the prevention of DDIs in clinical practice?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eIncrease training programs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e37 (12.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eUtilize decision support systems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e20 (6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eDevelop clinical guidelines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e25 (8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 198px;\"\u003e\n \u003cp\u003eAll of the above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e208 (71.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 604px;\"\u003e\n \u003cp\u003eDDI: Drug-drug interaction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eA Pearson correlation analysis was conducted to examine the relationships between total knowledge score and various independent variables. A weak but statistically significant negative correlation was found between age and total knowledge score (r = -0.184, p = 0.002). However, no statistically significant correlation was found between gender, experience, subspecialty status, institution type, hospital bed capacity, and DDI education status (p \u0026gt; 0.05).\u003c/p\u003e\n\u003cp\u003eIndependent samples t-test analysis revealed no statistically significant differences in total knowledge scores by gender, subspecialty status, institution type, or DDI education status (p \u0026gt; 0.05 for all comparisons).\u003c/p\u003e\n\u003cp\u003eSimilarly, one-way ANOVA showed no significant differences in knowledge scores based on years of experience, institutional bed capacity, or education format (p \u0026gt; 0.05).\u003c/p\u003e\n\u003cp\u003eAdditional subgroup analyses were conducted to assess whether clinical role characteristics were associated with differences in DDI-related knowledge. When participants were compared based on their subspecialty area, no statistically significant difference was found in total knowledge scores across subspecialty groups (p = 0.145). Similarly, when participants were grouped according to whether they worked in a neonatal or pediatric intensive care unit, no significant difference was observed in total knowledge scores (p = 0.928).\u003c/p\u003e\n\u003cp\u003eA multiple linear regression analysis was performed to identify factors associated with the total knowledge score. The independent variables included age, gender, years of experience, subspecialty status, institution type, hospital bed capacity, and DDI education format.\u003c/p\u003e\n\u003cp\u003eThe model was statistically significant (F = 2.302, p = 0.029), with an R\u0026sup2; value of 0.087, indicating that it explained 8.7% of the variance in knowledge scores. However, none of the individual predictor variables had a statistically significant effect on the outcome (p \u0026gt; 0.05 for all).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study meticulously assessed the knowledge levels, attitudes, and clinical practices of pediatricians concerning DDIs. The average age of the pediatricians was 46.9 years, more than half were male, and the majority had 16 years or more of experience in the pediatric field. This demographic structure is important as it reflects the perspectives of experienced pediatricians on DDIs. A weak but statistically significant negative correlation between age and knowledge level suggests that older pediatricians may have reduced access to up-to-date information or may be in greater need of knowledge refreshment. This may be partly due to decreased use of technological resources with age, which can limit access to current drug information and reduce awareness of emerging drug interactions.\u003c/p\u003e\n\u003cp\u003eIt was observed that 61.4% of pediatricians had received training on DDIs, though most of this training occurred during their university education. In contrast, in-service training and continuous professional development programs were found to be limited. This indicates a critical need for ongoing education throughout healthcare professionals\u0026apos; careers to ensure they stay current on issues such as DDIs. Multiple studies demonstrate that structured educational interventions significantly improve DDI knowledge among healthcare professionals and students, while also promoting safer prescribing practices and reducing the risk of adverse drug events (7,14,15).\u003c/p\u003e\n\u003cp\u003eIn addition, the fact that clinical decision support systems (69.3%) were the most preferred information source in our study highlights the critical role of technology in facilitating access to information and supporting clinical decisions in healthcare. Numerous studies have shown that technological tools\u0026mdash;including those for managing DDIs and assisting clinical decision-making\u0026mdash;improve information accessibility, encourage data-driven and collaborative care, enhance patient safety, and help clinicians make optimized treatment decisions. Nonetheless, issues such as usability, customization, standardization, and assessment of effectiveness remain ongoing challenges (16\u0026ndash;19).\u003c/p\u003e\n\u003cp\u003eThe pediatricians\u0026apos; average knowledge score was 3.1, with 35.3% demonstrating a high level of understanding. However, 45.2% of pediatricians self-assessed their knowledge of DDIs as inadequate, revealing a notable gap between actual performance and perceived competence. This suggests that healthcare professionals are aware of their limitations and receptive to additional training and resources. Recognizing such knowledge deficits highlights the importance of continuous professional development in clinical practice. Although medical professionals often have insufficient knowledge of DDIs, the literature shows that they acknowledge the importance of these interactions and are willing to seek information, reflecting a mismatch between their actual knowledge and the importance they attribute to the issue (15,20,21).\u003c/p\u003e\n\u003cp\u003eThe highest correct response rate (94.8%) was observed for the question regarding drugs that pose a risk of nephrotoxicity, indicating that pediatricians are well aware of nephrotoxic medications. This knowledge is essential, as nephrotoxic drugs are implicated in a significant proportion of acute kidney injuries (AKIs) in pediatric patients, accounting for approximately 16% of all AKIs in older children and adolescents (22,23). Although our study did not examine pediatricians\u0026rsquo; prescribing practices of nephrotoxic agents, the literature indicates that such medications are more frequently administered to children with chronic kidney disease (24).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe low awareness regarding Lexicomp as an evidence-based resource for checking drug interactions (31.4% correct response) is concerning. Lexicomp Online is widely recognized for providing up-to-date, accurate, and reliable drug information, making it a valuable tool for healthcare professionals. This low level of awareness highlights the need for additional training on available digital drug information platforms. A systematic review reported that information technology-based interventions improve surrogate clinical outcomes and adherence to DDI alerts, although evidence on their direct clinical impact remains limited (25). Studies evaluating electronic drug information resources consistently identify Lexicomp Online as a leading tool, offering concise and current data to ensure safe prescribing practices (26). Other platforms, such as Micromedex, also contribute to updated drug information; however, Lexicomp was selected for our study due to its widespread hospital availability and frequent use in clinical practice.\u003c/p\u003e\n\u003cp\u003e45.2% of the pediatricians stated that their level of knowledge about DDIs is insufficient. However, 97.9% reported that clinical guidelines and decision support systems play a crucial role in preventing DDIs, and 100% agreed that DDI training should be expanded. This high level of awareness can serve as a driving force for the broader implementation of training programs and digital support tools. Abougalambou and Alenezi (2023) emphasized that while health professionals\u0026rsquo; knowledge of DDIs is generally insufficient, there is a strong demand for structured training and technological support systems (8). \u0026nbsp;The broader literature similarly underscores that although appropriate education on DDI management is essential, it remains inadequate in current clinical settings. Targeted educational interventions, integrated pedagogical strategies, and ongoing professional development are key methods for enhancing DDI-related competencies, thereby improving both patient safety and the overall quality of care (7,15,27,28).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e37.2% of participants reported that they never check for DDIs, indicating a clear disconnect between knowledge and clinical practice. This is consistent with the literature, which shows that despite recognizing the importance of DDIs, healthcare professionals often face time constraints and heavy workloads that hinder their ability to perform DDI checks. Over half of the pediatricians in our study identified limited time as a major barrier to incorporating DDI evaluations into their routine practice. Likewise, existing research confirms that insufficient time and clinical workload are key obstacles to the effective implementation of DDI control measures (29).\u003c/p\u003e\n\u003cp\u003eFurthermore, 87.2% of pediatricians reported taking prompt action upon detecting DDIs, yet only 5.2% sought consultation from pharmacists. This suggests that while pediatricians are proactive in managing DDIs, they rarely engage in multidisciplinary collaboration by utilizing the expertise of pharmacists. The literature emphasizes the vital role of pharmacists in optimizing patient safety and supporting clinical decision-making in DDI management \u0026nbsp;(5,30\u0026ndash;32). It is widely recognized that involving pharmacists enhances the quality of care and reduces medication-related risks. Moreover, consulting pharmacists could help mitigate the time-related barriers that pediatricians often face when assessing DDIs.\u003c/p\u003e\n\u003cp\u003eIn the present study, demographic and professional variables\u0026mdash;except for age\u0026mdash;did not significantly influence the level of DDI knowledge. Although the regression model was valid, none of the independent variables showed a statistically significant association with knowledge scores. While Hardan et al. (2023) reported a link between years of experience and improved awareness of DDIs, our findings suggest that DDI knowledge cannot be explained solely by demographic or professional characteristics. Instead, more complex and nuanced factors\u0026mdash;such as the quality of education, personal motivation, and institutional learning culture\u0026mdash;should be considered to better understand what truly influences knowledge levels (15). Furthermore, subgroup analysis revealed no significant differences in knowledge scores between pediatricians working in intensive care settings and those who do not (p = 0.9298). Likewise, no statistically significant variation was found across different pediatric subspecialties (p = 0.145).\u003c/p\u003e\n\u003cp\u003eThis study has several limitations. First, the findings are based on participants\u0026rsquo; self-reports, which may introduce bias and reduce the accuracy and objectivity of the data. The online format of the survey may have contributed to brief or incomplete responses, thereby limiting the depth of the collected information. Additionally, the study sample was geographically restricted to pediatricians working exclusively in Istanbul, which limits the generalizability of the results to other regions or healthcare systems. The cross-sectional design also prevents causal inferences from being made. Finally, the scope of the knowledge assessments was limited and may not fully reflect pediatricians\u0026rsquo; actual clinical practices. Future research should consider expanding the sample to include a broader geographic distribution and utilize longitudinal study designs to evaluate the long-term effects of continuous DDI training. It would also be valuable to explore the specific barriers that prevent pediatricians from routinely integrating DDI checks into their clinical workflows.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study revealed that pediatricians possess a moderate level of knowledge about DDIs, with a clear need for further training and support. While age showed a slight negative impact, no significant differences were found based on work setting or subspecialty. Despite positive attitudes, DDI checks were not consistently implemented in clinical practice. These findings highlight the importance of expanding structured DDI education, promoting the use of evidence-based digital tools, and integrating DDI control into routine workflows. Strengthening decision support systems and continuous professional development may help improve medication safety and care quality.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAKIs: Acute kidney injuries\u003c/p\u003e\n\u003cp\u003eDDIs: Drug-drug interactions\u003c/p\u003e\n\u003cp\u003ePK: Pharmacokinetic\u003c/p\u003e\n\u003cp\u003epDDIs: Potential drug-drug interactions\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from the Altınbaş University Health Sciences Research Ethics Committee (Approval No. 2024/54; Date: February 6, 2025). Informed consent of participation was obtained electronically at the beginning of the survey. All procedures adhered to the ethical standards of the University of Siena and complied with the 1964 Helsinki declaration and its subsequent amendments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author received no financial support for the research, authorship, and/or publication of this article. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthor contributions are as follows ET: Conceptualization, Methodology, Data collection, Writing - review and editing, Resources, Supervision. YEA: Conceptualization, Methodology, Formal analysis and investigation, Data collection, Writing – original draft preparation, Writing - review and editing, Resources, Supervision. BM: Methodology, Data collection, Resources, Writing - review and editing, Resources. NA: Conceptualization, Methodology, Writing - review and editing. Resources, Supervision.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGonzalez D, Sinha J. Pediatric drug‐drug interaction evaluation: drug, patient population, and methodological considerations. The Journal of Clinical Pharmacology. 2021;61:S175\u0026ndash;S187. \u003c/li\u003e\n\u003cli\u003eSalem F, Rostami‐Hodjegan A, Johnson TN. Do children have the same vulnerability to metabolic drug\u0026ndash;drug interactions as adults? A critical analysis of the literature. The Journal of Clinical Pharmacology. 2013;53(5):559\u0026ndash;66. \u003c/li\u003e\n\u003cli\u003eSalerno S, Burckart G, Huang S, Gonzalez D. Pediatric Drug\u0026ndash;Drug Interaction Studies: Barriers and Opportunities. Clin Pharmacol Ther. 2018;105. \u003c/li\u003e\n\u003cli\u003eMoura CS, Acurcio FA, Belo NO. Drug-drug interactions associated with length of stay and cost of hospitalization. Journal of Pharmacy \u0026amp; Pharmaceutical Sciences. 2009;12(3):266\u0026ndash;72. \u003c/li\u003e\n\u003cli\u003eAksoy N, Ozturk N. A meta‐analysis assessing the prevalence of drug\u0026ndash;drug interactions among hospitalized patients. Pharmacoepidemiol Drug Saf. 2023;32(12):1319\u0026ndash;30. \u003c/li\u003e\n\u003cli\u003eBebitoğlu BT, Oğuz E, Nuhoğlu \u0026Ccedil;, Dalkılı\u0026ccedil; AEK, \u0026Ccedil;irtlik P, Temel F, et al. Evaluation of potential drug-drug interactions in a pediatric population. Turkish Archives of Pediatrics. 2020;55(1):30. \u003c/li\u003e\n\u003cli\u003eHarrington AR, Warholak TL, Hines LE, Taylor AM, Sherrill D, Malone DC. Healthcare professional students\u0026rsquo; knowledge of drug-drug interactions. Am J Pharm Educ. 2011;75(10):199. \u003c/li\u003e\n\u003cli\u003eAbougalambou SSI, Alenezi TN. Knowledge and information sources of potential drug\u0026ndash;drug interactions of healthcare professionals among Buraydah Hospitals. J Pharm Policy Pract. 2023;16(1):131. \u003c/li\u003e\n\u003cli\u003eNeubert A, Dormann H, Weiss J, Egger T, Criegee-Rieck M, Rascher W, et al. The impact of unlicensed and off-label drug use on adverse drug reactions in paediatric patients. Drug Saf. 2010;33(6):427\u0026ndash;35. \u003c/li\u003e\n\u003cli\u003eShaniv S, others. Knowledge, attitudes, and practices of pediatricians regarding drug-drug interactions: A cross-sectional study. Journal of Pediatric Pharmacology and Therapeutics. 2023;28(1):45\u0026ndash;52. \u003c/li\u003e\n\u003cli\u003eChedoe I, Vaessen H, den Oudenrijn LP, van der Starre C, Egberts ACG, van den Anker JN. Drug use and potential drug-drug interactions in pediatric patients admitted to the intensive care unit of a university hospital. Int J Clin Pharm. 2007;29(4):319\u0026ndash;24. \u003c/li\u003e\n\u003cli\u003eCosta L, Silva R, Pereira M, Santos A, Oliveira J. Potential drug\u0026ndash;drug interactions in pediatric intensive care unit patients: A retrospective analysis. Journal of Pediatric Pharmacology and Therapeutics. 2021;26(2):123\u0026ndash;30. \u003c/li\u003e\n\u003cli\u003eHassanzad M, Arenas-Lopez S, Baniasadi S. Potential Drug\u0026ndash;Drug Interactions Among Critically Ill Pediatric Patients in a Tertiary Pulmonary Center. J Clin Pharmacol. 2018;58(2):221\u0026ndash;7. \u003c/li\u003e\n\u003cli\u003eOguz F, Arslan M. 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BMC Med Educ. 2019;19. \u003c/li\u003e\n\u003cli\u003eHammar T, Hamqvist S, Zetterholm M, Jokela P, Ferati M. Current knowledge about providing drug\u0026ndash;drug interaction services for patients\u0026mdash;a scoping review. Pharmacy. 2021;9(2):69. \u003c/li\u003e\n\u003cli\u003eLopez-Martin C, Garrido Siles M, Alcaide-Garcia J, Faus Felipe V. Role of clinical pharmacists to prevent drug interactions in cancer outpatients: a single-centre experience. Int J Clin Pharm. 2014;36:1251\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eAbunahlah N, Elawaisi A, Velibeyoglu FM, Sancar M. Drug related problems identified by clinical pharmacist at the Internal Medicine Ward in Turkey. Int J Clin Pharm. 2018;40(2):360\u0026ndash;7. \u003c/li\u003e\n\u003cli\u003eDahri K, Araujo L, Chen S, Bagri H, Walia K, Lau L, et al. Community pharmacist perceptions of drug-drug interactions. Canadian Phamacists Journal. 2022;156(1):42\u0026ndash;7. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Pediatricians, Drug-Drug Interactions, Knowledge, Attitudes, Clinical Practices, Education, Survey","lastPublishedDoi":"10.21203/rs.3.rs-6673873/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6673873/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eDrug-drug interactions (DDIs) are an important health problem that can cause serious side effects and treatment failures, especially in pediatric patients. Healthcare professionals' knowledge, attitudes and clinical practices about DDI play a critical role in preventing these risks. The aim of this study was to evaluate the knowledge, attitudes and clinical practices of pediatric physicians about DDIs and to examine the relationship of these factors with demographic characteristics.\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e \u003cp\u003eDemographic characteristics, DDI education status, knowledge levels and clinical practices of the participants were evaluated with questionnaires and knowledge tests. Statistical analyses included correlation, t-test, ANOVA and multiple regression analyses.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 290 pediatricians were included in the study. The mean age of the participants was 46.9 years, and 61.4% had received DDI training. The highest correct response rate (94.8%) was observed in the question about nephrotoxicity risk, while the lowest rate (31.4%) was observed in the question about the use of evidence-based resources. 45.2% of the participants evaluated their knowledge level as insufficient. In clinical practice, 47.2% sometimes and 12.4% always perform DDI checks, while 37.2% never do checks. A weak but significant negative correlation was found between age and knowledge level, and the effect of other variables was not significant.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe DDI knowledge of pediatricians is at a moderate level, and there are some gaps, especially in the use of evidence-based resources. Dissemination of clinical decision support systems and continuous training are necessary to improve drug safety and patient care quality.\u003c/p\u003e","manuscriptTitle":"Pediatricians’ Knowledge, Attitudes and Clinical Practices Regarding Drug-Drug Interactions: A Survey Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-17 10:48:41","doi":"10.21203/rs.3.rs-6673873/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d27ae944-300f-418d-a9e0-5ee62d889893","owner":[],"postedDate":"June 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-27T12:08:30+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-17 10:48:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6673873","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6673873","identity":"rs-6673873","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}