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Psychometric Properties and Assessment of Knowledge, Attitude, and Practice Towards ChatGPT in Pharmacy Practice and Education: a Study Protocol

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Abstract

ChatGPT represents an advanced conversational artificial intelligence (AI), providing a powerful tool for generating human-like responses that could change pharmacy prospects. This protocol aims to describe the development, validation, and utilization of a tool to assess the knowledge, attitude, and practice towards ChatGPT (KAP-C) in pharmacy practice and education. The development and validation process of the KAP-C tool will include a comprehensive literature search to identify relevant constructs, content validation by a panel of experts for items relevancy using content validity index (CVI) and face validation by sample participants for items clarity using face validity index (FVI), readability and difficulty index using the Flesch-Kincaid Readability Test, Gunning Fog Index, or Simple Measure of Gobbledygook (SMOG), assessment of reliability using internal consistency (Cronbach’s alpha), and exploratory factor analysis (EFA) to determine the underlying factor structures (eigenvalues, scree plot analysis, factor loadings, and varimax). The second phase will utilize the validated KAP-C tool to conduct KAP surveys among pharmacists and pharmacy students in selected low- and middle-income countries (LMICs) (Nigeria, Pakistan, and Yemen). The final data will be analyzed descriptively using frequencies, percentages, mean (standard deviation) or median (interquartile range), and inferential statistics like Chi-square or regression analyses using IBM SPSS version 28. A p<0.05 will be considered statistically significant. ChatGPT holds the potential to revolutionize pharmacy practice and education. This study will highlight the psychometric properties of the KAP-C tool that assesses the knowledge, attitude, and practice towards ChatGPT in pharmacy practice and education. The findings will contribute to the potential ethical integration of ChatGPT into pharmacy practice and education in LMICs, serve as a reference to other economies, and provide valuable evidence for leveraging AI advancements in pharmacy.

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Data Availability

All data generated or analyzed during this study are included in this published article [and its supplementary information files].

References

  1. Haleem A, Javaid M, Khan IH. Current status and applications of artificial intelligence (AI) in medical field: an overview. Curr Med Res Pract. 2019;9(6):231–7. https://doi.org/10.1016/j.cmrp.2019.11.005.

    Article  Google Scholar 

  2. Awad SO, Mohamed Y, Shaheen R. Applications of artificial intelligence in education. Al-Azkiyaa-Jurnal Antarabangsa Bahasa dan Pendidikan. 2022;1(1):71–81.

    Article  Google Scholar 

  3. Arif TB, Munaf U, Ul-Haque I. The future of medical education and research: is ChatGPT a blessing or blight in disguise? Taylor & Francis; 2023. p. 2181052.

    Google Scholar 

  4. Baines D, Nørgaard LS, Rossing C. The Fourth Industrial Revolution: will it change pharmacy practice? Res Soc Adm Pharm. 2020;16(9):1279–81.

    Article  Google Scholar 

  5. Raza MA, Aziz S, Noreen M, et al. Artificial intelligence (AI) in pharmacy: an overview of innovations. Innov Pharm. 2022;13(2). https://doi.org/10.24926/iip.v13i2.4839.

  6. Das S, Dey R, Nayak AK. Artificial intelligence in pharmacy. Indian J Pharm Educ Res. 2021;55(2):304–18. https://doi.org/10.5530/ijper.55.2.68.

    Article  CAS  Google Scholar 

  7. Sallam M, Salim N, Barakat M, Al-Tammemi A. ChatGPT applications in medical, dental, pharmacy, and public health education: a descriptive study highlighting the advantages and limitations. Narra J. 2023;3(1):e103–3.

    Article  Google Scholar 

  8. Sallam M. ChatGPT utility in health care education, research, and practice: systematic review on the promising perspectives and valid concerns. MDPI. 2023:887.

  9. Kung TH, Cheatham M, Medenilla A, et al. Performance of ChatGPT on USMLE: potential for AI-assisted medical education using large language models. PLOS Digit Health. 2023;2(2):e0000198. https://doi.org/10.1371/journal.pdig.0000198.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Korinek A, Stiglitz JE. Artificial intelligence, globalization, and strategies for economic development. 2021;28453. https://doi.org/10.1371/10.3386/w28453.

  11. Tey NP, Lai SL. Correlates of and barriers to the utilization of health services for delivery in South Asia and Sub-Saharan Africa. Sci World J. 2013;2013:423403. https://doi.org/10.1155/2013/423403.

    Article  Google Scholar 

  12. Kumar N, Ahmed F, Raza MS, et al. Monkeypox cross-sectional survey of knowledge, attitudes, practices, and willingness to vaccinate among university students in Pakistan. Vaccines. 2022;11(1):97.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Mustapha M, Lawal BK, Sha’aban A, et al. Factors associated with acceptance of COVID-19 vaccine among university health sciences students in Northwest Nigeria. Plos One. 2021;16(11):e0260672. https://doi.org/10.1371/journal.pone.0260672.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Bala AA, Jatau AI, Yunusa I, et al. Development and validation of antisnake venom knowledge assessment tool (AKAT) for healthcare practitioners. Toxicon X. 2020;8:100064. https://doi.org/10.1016/j.toxcx.2020.100064.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Bala AA, Jatau AI, Yunusa I, et al. Knowledge assessment of snake antivenom among healthcare practitioners involving educational intervention in northern Nigeria: a study protocol. Ther Adv Drug Saf. 2020;11(2):042098620935721. https://doi.org/10.1177/2042098620935721.

    Article  CAS  Google Scholar 

  16. Tsang S, Royse CF, Terkawi AS. Guidelines for develo**, translating, and validating a questionnaire in perioperative and pain medicine. Saudi J Anaesthesia. 2017;11(Suppl 1):S80.

    Article  Google Scholar 

  17. Sousa VD, Rojjanasrirat W. Translation, adaptation and validation of instruments or scales for use in cross-cultural health care research: a clear and user-friendly guideline. J Eval Clin Pract. 2011;17(2):268–74.

    Article  PubMed  Google Scholar 

  18. Polit DF, Beck CT, Owen SV. Is the CVI an acceptable indicator of content validity? Appraisal and recommendations. Res Nurs Health. 2007;30(4):459–67.

    Article  PubMed  Google Scholar 

  19. Yusoff MSB. ABC of content validation and content validity index calculation. Educ Med J. 2019;11(2):49–54.

    Article  Google Scholar 

  20. Nevo B. Face validity revisited. J Educ Measure. 1985;22(4):287–93. https://doi.org/10.1111/j.1745-3984.1985.tb01065.x.

    Article  Google Scholar 

  21. Thomas SD, Hathaway DK, Arheart KL. Face validity. West J Nurs Res. 1992;14(1):109–12. https://doi.org/10.1177/019394599201400111.

    Article  CAS  PubMed  Google Scholar 

  22. Yusoff MSB. ABC of response process validation and face validity index calculation. Educ Med J. 2019;11(10.21315)

  23. Contreras A, Garcia-Alonso R, Echenique M, Daye-Contreras F. The SOL formulas for converting SMOG readability scores between health education materials written in Spanish, English, and French. J Health Commun. 1999;4(1):21–9. https://doi.org/10.1080/108107399127066.

    Article  CAS  PubMed  Google Scholar 

  24. Feldt LS. The relationship between the distribution of item difficulties and test reliability. Appl Measure Educ. 1993;6(1):37–48.

    Article  Google Scholar 

  25. Rattray J, Jones MC. Essential elements of questionnaire design and development. J Clin Nurs. 2007;16(2):234–43. https://doi.org/10.1111/j.1365-2702.2006.01573.x.

    Article  PubMed  Google Scholar 

  26. Guad RM, Mangantig E, Low WY, et al. Development and validation of a structured survey questionnaire on knowledge, attitude, preventive practice, and treatment-seeking behaviour regarding dengue among the resident population of Sabah, Malaysia: an exploratory factor analysis. BMC Infect Dis. 2021;21(1):893. https://doi.org/10.1186/s12879-021-06606-6.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Soleymanian A, Niknami S, Hajizadeh E, Shojaeizadeh D, Montazeri A. Development and validation of a health belief model based instrument for measuring factors influencing exercise behaviors to prevent osteoporosis in pre-menopausal women (HOPE). BMC Musculoskelet Disord. 2014;15(1):61. https://doi.org/10.1186/1471-2474-15-61.

    Article  PubMed  PubMed Central  Google Scholar 

  28. von Elm E, Altman DG, Egger M, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Int J Surg. 2014;12(12):1495–9. https://doi.org/10.1016/j.ijsu.2014.07.013.

    Article  Google Scholar 

  29. Eysenbach G. Correction: improving the quality of web surveys: the checklist for reporting results of internet e-surveys (CHERRIES). J Med Internet Res. 2012;14(1):e2042.

    Article  Google Scholar 

  30. Yasar N. The relationship between energy consumption and economic growth: evidence from different income country groups. Int J Energy Econ Policy. 2017;7(2):86–97.

    Google Scholar 

  31. Abubakar I, Dalglish SL, Angell B, et al. The Lancet Nigeria Commission: investing in health and the future of the nation. Lancet. 2022;399(10330):1155–200. https://doi.org/10.1016/S0140-6736(21)02488-0.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Nonyel N, Ogbonna BO. Capacity-building and collaborative curriculum development: a transition from BPharm to PharmD degree at Nnamdi Azikiwe University in Nigeria. Pharm Educ. 2022;22(4):131–42.

    Article  Google Scholar 

  33. Ekpenyong A, Udoh A, Kpokiri E, Bates I. An analysis of pharmacy workforce capacity in Nigeria. J Pharm Policy Pract. 2018;11(1):9. https://doi.org/10.1186/s40545-018-0147-9.

    Article  Google Scholar 

  34. Daniel-Ebune E, Jatau AI, Burji SL, Mohammed M. Notes from the field: availability of satellite pharmacies and pharmacy service units in Nigerian hospitals—implications for pharmaceutical care. Eval Health Prof. 2021;44(2):177–9. https://doi.org/10.1177/0163278720934174.

    Article  PubMed  Google Scholar 

  35. Obansa S, Orimisan A. Health care financing in Nigeria: prospects and challenges. Mediterr J Soc Sci. 2013;4(1):221–36.

    Google Scholar 

  36. Oleribe OO, Momoh J, Uzochukwu BS, et al. Identifying key challenges facing healthcare systems in Africa and potential solutions. Int J Gen Med. 2019;12:395–403. https://doi.org/10.2147/IJGM.S223882.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Jamal A. Generation Z in Pakistan: individualistic and collectivist in orientation. The new generation Z in asia: Dynamics, differences, digitalisation. Emerald Publishing Limited; 2020. p. 105–17.

    Google Scholar 

  38. Madiha M, Yang C-q. Curriculum and pharmacy practice experience offered for Pharm-D in Pakistan: needs and possibilities. International Current. Pharm J. 2014;3(8):313–7.

    Google Scholar 

  39. Hussain A, Jamshed S. Pharmacy practice in Pakistan. Pharm Practice in Develo** Countries Elsevier. 2016:97–115.

  40. Atif M, Ahmad M, Saleem Q, Curley L, Qamar-uz-Zaman M, Babar ZUD. Pharmaceutical policy in Pakistan. Pharm Policy Countries Dev Healthcare Syst. 2017:25–44.

  41. Atif M, Ahmad M, Saleem Q, Curley L, Qamar-uz-Zaman M, Babar Z-U-D. Pharmaceutical policy in Pakistan. In: Babar Z-U-D, editor. Pharmaceutical Policy in Countries with Develo** Healthcare Systems. Springer International Publishing; 2017. p. 25–44. chap Chapter 3.

    Chapter  Google Scholar 

  42. Gelvin JL. The new Middle East: what everyone needs to know. Oxford University Press; 2018.

    Book  Google Scholar 

  43. Alles L. Missiles and food: Yemen’s man-made food security crisis. Oxfam; 2017.

    Google Scholar 

  44. Garber K, Fox C, Abdalla M, et al. Estimating access to health care in Yemen, a complex humanitarian emergency setting: a descriptive applied geospatial analysis. Lancet Glob Health. 2020;8(11):e1435–43. https://doi.org/10.1016/S2214-109X(20)30359-4.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Al-Worafi YM. Pharmacy practice and its challenges in Yemen. Australas Med J. 2014;7(1):17–23. https://doi.org/10.4066/AMJ.2014.1890.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Al-Worafi YMA. Pharmacy practice in Yemen. Pharmacy practice in develo** countries. Elsevier. 2016:267–87.

  47. Raosoft I. Sample size calculator. 2004. Available from: www.raosoft.com/samplesize. Accessed 01/03/2023.

  48. Saka SA, Adisa R, Isah A, Biambo AA. Pharmacy graduates’ perceptions of competency, integration, and social accountability in the undergraduate curriculum of pharmacy schools in Nigeria. Curr Pharm Teach Learn. 2021;13(11):1414–23.

    Article  PubMed  Google Scholar 

  49. Naqvi AA, Zehra F, Naqvi SBS, et al. Migration trends of pharmacy students of Pakistan: a study investigating the factors behind brain drain of pharmacy professionals from Pakistan. Indian J Pharm Educ Res. 2017;51(2):192–206. https://doi.org/10.5530/ijper.51.2.25.

    Article  Google Scholar 

  50. Al-Ashwal FY, Sulaiman SAS, Sheikh Ghadzi SM, Kubas MA, Halboup A. Physicians and pharmacists’ clinical knowledge of statin therapy and monitoring parameters, and the barriers to guideline implementation in clinical practice. PLoS One. 2023;18(1):e0280432. https://doi.org/10.1371/journal.pone.0280432.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Al-Worafi YM. Pharmacy education in Yemen. Am J Pharm Educ. 2013;77(3):65. https://doi.org/10.5688/ajpe77365.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Haleem A, Javaid M, Singh RP. An era of ChatGPT as a significant futuristic support tool: a study on features, abilities, and challenges. Bench Council Trans Benchmarks Stand Evaluat. 2022;2(4):100089.

    Article  Google Scholar 

  53. Yusoff MSB, Arifin WN, Hadie SNH. ABC of questionnaire development and validation for survey research. Educ Med J. 2021;13(1)

  54. Sallam M. ChatGPT utility in healthcare education, research, and practice: systematic review on the promising perspectives and valid concerns. MDPI. 2023:887.

  55. ElMassah S, Mohieldin M. Digital transformation and localizing the sustainable development goals (SDGs). Ecol Econ. 2020;169:106490.

    Article  Google Scholar 

  56. Tinmaz H, Fanea-Ivanovici M, Baber H. A snapshot of digital literacy. Library Hi Tech News. 2023;40(1):20–3.

    Article  Google Scholar 

  57. Shin D, Chotiyaputta V, Zaid B. The effects of cultural dimensions on algorithmic news: how do cultural value orientations affect how people perceive algorithms? Comp Hum Behav. 2022;126:107007.

    Article  Google Scholar 

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Acknowledgements

The authors would like to thank the experts who provided feedback for improvement to the study tool and the participants for volunteering to complete the survey.

Author information

Authors and Affiliations

  1. Department of Clinical Pharmacy and Pharmacy Practice, Faculty of Pharmaceutical Sciences, Ahmadu Bello University, Zaria, Kaduna, Nigeria

    Mustapha Mohammed

  2. School of Pharmaceutical Sciences, Universiti Sains Malaysia, Gelugor, Pulau Pinang, Malaysia

    Mustapha Mohammed, Mohammed Zawiah, Abdulsalam Halboup & Rabbiya Ahmad

  3. Vice President for Medical and Health Science Office, QU Health, Qatar University, Doha, Qatar

    Mustapha Mohammed

  4. Department of Pharmacy Practice, Faculty of Pharmacy, University of Sindh Jamshoro, Sindh, Pakistan

    Narendar Kumar

  5. Department of Pharmacy Practice, Faculty of Clinical Pharmacy, Hodeidah University, Al Hodeidah, Yemen

    Mohammed Zawiah

  6. Department of Pharmacy, Al-Maarif University College, Anbar, 31001, Iraq

    Fahmi Y. Al-Ashwal

  7. Department of Pharmacology, College of Medicine and Health Sciences, Federal University Dutse, Dutse, Jigawa, Nigeria

    Auwal Adam Bala

  8. Department of Clinical Pharmacy and Pharmacy Management, Kaduna State University, Kaduna, Nigeria

    Basira Kankia Lawal

  9. Department of Pharmacology and Therapeutics, Bayero University, Kano, Nigeria

    Abubakar Sadiq Wada

  10. Department of Clinical Pharmacy and Pharmacy Practice, University of Science and Technology, Sana’a, Yemen

    Abdulsalam Halboup

  11. Faculty of Veterinary Medicine, Ahmadu Bello University, Zaria, Kaduna, Nigeria

    Surajuddeen Muhammad

  12. Division of Population Medicine, School of Medicine, Cardiff University, Heath Park, Cardiff, CF14 4YS, Wales, UK

    Abubakar Sha’aban

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  1. Mustapha Mohammed
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Contributions

Conceptualization: [MM, NK, MZ, FYA]; methodology: [MM, NK, MZ, FYA, AAB]; formal analysis and investigation: [MM, NK, FYA, AAB, SM]; writing — original draft preparation: [MM, NK, MZ, FYA, AAB, BKL, ASW, AH, SM, RA, AH, AS]; writing — review and editing: [MM, NK, MZ, FYA, AAB, BKL, ASW, AH, SM, RA, AH, AS]; resources: [MM, MZ, NK, ASW, AH, SM, RA, AH, AS]; supervision: [BKL, AS]; all authors approved the final draft for publication.

Corresponding author

Correspondence to Mustapha Mohammed.

Ethics declarations

Ethics Approval and Consent to Participate

The present study is a methodological protocol and does not involve human participants. Therefore, it does not require ethical approval and consent. However, the approvals for the main study are currently under processing with the respective institutional review boards in Nigeria, Pakistan, and Yemen, as detailed in the manuscript.

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All authors agreed to the publication of the manuscript as presented.

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The authors declare no competing interests.

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Mohammed, M., Kumar, N., Zawiah, M. et al. Psychometric Properties and Assessment of Knowledge, Attitude, and Practice Towards ChatGPT in Pharmacy Practice and Education: a Study Protocol. J. Racial and Ethnic Health Disparities (2023). https://doi.org/10.1007/s40615-023-01696-1

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