ASSESSMENT OF KNOWLEDGE, ATTITUDE AND PRACTICE OF CHRONOPHARMACOLOGY AMONG DOCTORS
Main Article Content
Keywords
: Knowledge, Attitude, Practice, Chronopharmacology
Abstract
Background: Chronopharmacology is a field of science focusing on studying the effect of biological rhythms on pharmacotherapy, i.e., a branch of pharmacology deals with scheduling of drug regimen in alignment with biological rhythms.. Chronopharmacology is frequently overlooked and poorly studied aspect of therapy rationalization. This study was planned to assess the knowledge, attitude and practice (KAP) of chronopharmacology among doctors. Materials & Methods: It was a questionnaire based cross sectional, descriptive study. Total 60 participants were enrolled after taking consent and subjected to a structured KAP questionnaire & data was expressed in percentage. Questionnaire consisted of 22 questions. Results: 55% of participants have answered that they have heard the term chronopharmacology. 67% of participants have chosen yes for the question that chronopharmacology is concerned with the effects of drugs on timing of biological events & rhythms like circadian rhythm. 81% of participants have answered yes for the question that correct timing of drug administration is always mentioned in your prescription. Conclusion: Most of the participants have not heard the term chronopharmacology but they have knowledge that biological clock is related to diseases& they believe counselling of patients regarding chronopharmacology should be done. Doctors should be educated more about chronopharmacology
Downloads
References
[1] Anandabaskar N. Chronopharmacology. InIntroduction to Basics of Pharmacology and Toxicology 2019 (pp. 261-270). Springer, Singapore. [2] Dallmann R, Brown SA, Gachon F. Chronopharmacology: new insights and therapeutic implications. Annual review of pharmacology and toxicology. 2014 Jan 6;54:339-61. [3] Tamilanban T, Mohamedmajeed A, Chitra V. Overview of chronopharmacology. Research Journal of Pharmacy and Technology. 2020 Sep 1;13(9):4457-63. [4] Gupta PD. Chronopharmacology: A new approach for drug delivery schedules. Clinical Research and Clinical Trials. 2021;3(1). [5] Patil AA, Kengar MD, Mane SA, Wagmare SA, Nirmale DM. Chronopharmacology: A Great Future for the Medicines. [6] Bairy LK. Chronotherapeutics: A hype or future of chronopharmacology?. Indian Journal of Pharmacology. 2013 Nov;45(6):545. [7] Dobrek L. Chronopharmacology in therapeutic drug monitoring—dependencies between the rhythmics of pharmacokinetic processes and drug concentration in blood. Pharmaceutics. 2021 Nov 12;13(11):1915. [8] R. Ramesh, M. Kannan and M. Seenivasan, “Achievement Estimations of Priority Queue System in Fuzzy Environment”, Advances in Mathematical Modelling and Scientific Computing, Trends in Mathematics, Springer Link (Book Chapter),2024, pp. 637-658. [9] R. Ramesh and M. Seenivasan, “Analysis of Attainment Estimates of Loss System Queue”, Advances in Mathematical Modelling and Scientific Computing, Trends in Mathematics, Springer Link (Book Chapter),2024, pp. 519 – 531. [10] K. Sakthivel, N. Paramaguru, R. Ramesh and P. Syamala., “ Accomplishment Expedients of Batch Arrival Queuing Model by Fuzzy Ordering Approach ”, Advances in Mathematical Modelling and Scientific Computing, Trends in Mathematics, Springer Link (Book Chapter),2024, pp. 487 – 496. [11] A. Hari Ganesh, N. Jaimurthi, R. Ramesh and M. Seenivasan, “On testing of Fuzzy Hypothesis for mean and variance using centroid-based new distance functions under symmetric fuzzy environment”, Contemporary Mathematics, Vol. 5. Issue 1, December 26, 2023, pp. 60-92, https://doi.org/10.37256/cm.5120243317. [12] M. Seenivasan, S. Chandiraleka, H. Manikandan and R. Ramesh, “Single Server Queueing Model with Multiple Working Vacation, Feedback and Catastrophe”, 4th International Conference on Material Science and Applications, AIP Conference Proceedings 2822, November 14, 2023,pp.020245-1 – 020245-9,ISBN NO: 978-0-7354-4724-0. [13] M. Seenivasan, F. Patricia and R. Ramesh, “Analysis of Single Server Queue with single working vacation subject to Catastrophe”, 4th International Conference on Material Science and Applications, AIP Conference Proceedings 2822, November 14, 2023,Pp.020246-1to 020246-6,ISBN NO: 978-0-7354-4724-0. [14] R. Ramesh and M. Seenivasan, “Cost Appraises of a Phosphorescent Bulk Arrival Queueing system by Wingspans Fuzzy Ranking Approach”, Stochastic Processes and Their Applications in Artificial UIntelligence chapter 5, Pp. 50-64 ACIR Book Series: ISSN NO: 2327-0411 (Scopus). [15] P. Syamala, R. Ramesh, M. Seenivasan and R. Singaravel, “3D Based CT Scan Retrial Queuing Models by Fuzzy [16] Ordering Approach”, 2023 Second International Conference on Electrical, Electronics, Information and [17] Communication Technologies (ICEEICT), Trichirappalli, India, 2023, Pp. 01-05,(Scopus). [18] P. Gnaanachandra, A.M. Kumar, M. Seenivasan and R. Ramesh, “On Generalization of Fuzzy Topological Groups and Modelling Robotic Crash*”,IEEE Xplore, 2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT), Trichirappalli, India 2023, Pp.1-8, DOI: 10.1109/ICEEICT56924.2023.10157226 (Scopus). [19] R. Ramesh and M. Seenivasan, “Discouraged Arrivals Queuing System in Inter valued type-2 Fuzzy Environment, Recent trends on Type-2 Fuzzy Logic systems: Theory, methodology and Application”, Studies in Fuzziness and Soft Computating, Pp. 235-247, 2023, Volume 425, (Springer): ISSN: 1434 – 9922. [20] R. Ramesh and M. Seenivasan, Performance Analysis of Single Server Low Priority Queue Based on Electronic Transmitter, Lecture Notes in Electrical Engineering, Springer Book Series, (ICAECT 2021), Vol.881,Pp.347-359,June 26th, 2022, ISBN: 978-981-19-1110-1&ISBN 978-981-19-1111-8. [21] R. Ramesh and M. Seenivasan, “Achievement expedients of fuzzy queuing models with an unreliable electrical transformer”, IEEE Xplore (ICEEICT 2022) Vol. 22, February 2022(Scopus), ISBN:978-1-6654-3647-2. [22] R. Ramesh and M. Seenivasan, “Performance Calibrations of A single server Glycolic Acid Based Beauty Parlor by Fuzzy Retrial Queuing Models”, Materials Today: Proceedings, Vol.51, Pp.2422–2426, December2022, (Science Direct), (Scopus) https://doi.org/10.1016/j.matpr.2021.11.603: ISSN: 2214-785 [23] Bhaskaran, S. S. (2024). Discovery of contextual factors using clustering. Multimedia Tools and Applications, 1-30. [24] Bhaskaran, S. S. (2021). Investigation of student performance with contextual factors using association rules in higher educational institutions (HEIs). In Data Engineering and Intelligent Computing: Proceedings of ICICC 2020 (pp. 431-442). Springer Singapore. [25] Bhaskaran, S. S., Al Aali, M., & Lu, K. Contextual Data Mining for Higher Educational Institutions. [26] Bhaskaran, S. S. (2017). An Investigation into the Knowledge Discovery and Data Mining (KDDM) process to generate course taking pattern characterised by contextual factors of students in Higher Education Institution (HEI) (Doctoral dissertation, Brunel University London). [27] Bhaskaran, S. S. (2021). Investigation of factors affecting adoption of FinTech in financial institutions. In Innovative strategies for implementing FinTech in banking (pp. 222-241). IGI Global. [28] Sailesh, S. B. (2022). Adapting IT governance policies and technology to cope with COVID-19 at Ahlia University. In COVID-19 Challenges to University Information Technology Governance (pp. 359-372). Cham: Springer International Publishing. [29] Intelligent context driven data mining to analyse student performance in higher educational institutions (HEIs) Bhaskaran, S.S [30] International Journal of Recent Technology and Engineering, 2019, 8(2), pp. 856–861 [31] Khalaf, F., & Baskaran, S. S. (2023, March). Predicting Acute Respiratory Failure Using Fuzzy Classifier. In 2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD) (pp. 1-4). IEEE. [32] Hasan, Z., & Baskaran, S. S. (2023, March). Propose a Recommender System to Dynamically Align Higher Education Curriculums With 4IR Market Needs. In 2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD) (pp. 1-7). IEEE. [33] Bhaskaran, S. S., & Al Aali, M. (2021). Investigation on the Influence of English Expertise on Non-native English-Speaking Students’ Scholastic Performance Using Data Mining. In Smart Computing Techniques and Applications: Proceedings of the Fourth International Conference on Smart Computing and Informatics, Volume 2 (pp. 9-14). Springer Singapore. [34] Bhaskaran, S. S., & Aali, M. A. (2021). Data mining model for better admissions in higher educational institutions (heis)—a case study of bahrain. In Advanced Machine Learning Technologies and Applications: Proceedings of AMLTA 2020 (pp. 141-150). Springer Singapore. [35] Sailesh, S. B., Lu, K. J., & Al Aali, M. (2016, August). Profiling students on their course-taking patterns in higher educational institutions (HEIs). In 2016 international conference on information science (icis) (pp. 160-167). IEEE. [36] Sailesh, S. B., Lu, K. J., & Al Aali, M. (2016, August). Context driven data mining to classify students of higher educational institutions. In 2016 International Conference on Inventive Computation Technologies (ICICT) (Vol. 2, pp. 1-7). IEEE. [37] Bhaskaran, S. S., Lu, K., & Aali, M. A. (2017). Student performance and time-to-degree analysis by the study of course-taking patterns using J48 decision tree algorithm. International Journal of Modelling in Operations Management, 6(3), 194-213. [38] Bhaskaran, S. S. (2018). Facilitate decision making in higher educational institutions by linking course-taking pattern and student performance characterised by contextual knowledge. International Journal of Society Systems Science, 10(3), 182-200.
Article Sidebar
Article Details
Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Transfer of Copyright and Permission to Reproduce Parts of Published Papers.
Authors retain the copyright for their published work. No formal permission will be required to reproduce parts (tables or illustrations) of published papers, provided the source is quoted appropriately and reproduction has no commercial intent. Reproductions with commercial intent will require written permission and payment of royalties.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.