Abstract
Adapting health professional curriculum and training to evolving requirements and exponential expansion in healthcare awareness and knowledge is vital. As an example of this uniformity, interprofessional education can be found. Teachers’ willingness to participate in interprofessional education is closely linked to their attitude about it. The goal of this research is to investigate teacher attitudes toward interprofessional education (IPE) at Ekiti State College of Health and Technology (EKCHT), Ijero Ekiti, Nigeria. Cross-sectional research involving 85 teachers was used. In order to collect data, a five-point Likert scale with three subscales on IPE was utilized, which was stratified sampling. Positive attitude was defined as having a cut-off percentage of more than seventy-five percent. At a 96% confidence level, SPSS version 21 was used to analyze the Bio-demographic data and teacher attitudes were correlated using logistic regression. There are a greater number of male teachers than females that took part in the survey. Attitudes of teacher's IPE in academic contexts were found to be negative (30.82 < 75%) in the total attitude score (121.45 > 75%). Teacher’s attitudes were not influenced by their age, gender, academic rank, or level of competence. Academics with positive opinions toward interprofessional education were more likely to have used it at the college (P = 0.147). As a result, while teachers have a generally positive view of interprofessional education, they have a negative view of subscale 3-interprofessional education in academic contexts. Training in behavior change and IPE awareness for teachers is suggested to avoid negative attitudes.
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References
World Health Organization. WHO guideline: recommendations on digital interventions for health system strengthening. World Health Organization (2019)
Belasen, A.T.: Resilience in Healthcare Leadership: Practical Strategies and Self-Assessment Tools for Identifying Strengths and Weaknesses. Productivity Press, New York (2021)
Ajibade, S.-S.M., Mejarito, C., Egere, O.M., Adediran, A.O., Gido, N.G., Bassey, M.A.: An analysis of the impact of social media addiction on academic engagement of students. J. Pharm. Negat. Results 13(4), 1390–1398 (2022). https://doi.org/10.47750/pnr.2022.13.S04.166
Sunguya, B.F., Hinthong, W., Jimba, M., Yasuoka, J.: Interprofessional education for whom—challenges and lessons learned from its implementation in developed countries and their application to developing countries: a systematic review. PLoS ONE 9(5), e96724 (2014)
Homeyer, S., Hoffmann, W., Hingst, P., Oppermann, R.F., Dreier-Wolfgramm, A.: Effects of interprofessional education for medical and nursing students: enablers, barriers and expectations for optimizing future interprofessional collaboration–a qualitative study. BMC Nurs. 17(1), 1–10 (2018)
ESPAD Group. ESPAD report 2019: results from the European school survey project on alcohol and other drugs (2020)
Brime, B., et al.: Observatorio Español de las Drogas y las Adicciones. Informe 2021. Alcohol, Tabaco y Drogas Ilegales en España (2021)
Rafael, J., Anupol, J., Cajal, B., Gervilla, E.: Data mining techniques for drug use research. Addict. Behav. Rep. 8, 128–135 (2018)
Smit, K., Voogt, C., Otten, R., Kleinjan, M., Kuntsche, E.: Why adolescents engage in early alcohol use: a study of drinking motives. Exp. Clin. Psychopharmacol. 30(1), 73–81 (2022). https://doi.org/10.1037/pha0000383
Genrich, G., Zeller, C., Znoj, H.J.: Interactions of protective behavioral strategies and cannabis use motives: an online survey among past-month users. PloS ONE 16(3), e0247387 (2021)
Gazibara, T., What differs former, light and heavy smokers? Evidence from a post-conflict setting. Afr. Health Sci. 21(1), 112–22 (2021)
Cody, S.: Data Mining/Data Privacy and the Collection/Misuse of Our Private Data, No. 5823 (2021)
Wahab, L., Jiang, H.: A comparative study on machine learning based algorithms for prediction of motorcycle crash severity. PLoS ONE 14(4), e0214966 (2019)
Parekh, A., Bates, J., Amdur, R.: Response rate and nonresponse bias in oncology survey studies. Am. J. Clin. Oncol. 43(4), 229–230 (2020)
Ajibade, S.S.M., Oyebode, O.J., Mejarito, C.L., Gido, N.G., Dayupay, J., Diaz, R.D.: Feature selection for student prediction accuracy using gravitational search algorithm. J. Optoelectron. Laser 41(8), 2022 (2022)
Bangotra, D.K., Singh, Y., Kumar, N., Singh, P.K., Ojeniyi, A.: Energy-efficient and secure opportunistic routing protocol for WSN: performance analysis with nature-inspired algorithms and its application in biomedical applications. BioMed Res. Int. 2022, 1–13, 1976694 (2022). https://doi.org/10.1155/2022/1976694
Ajibade, S.S.M., Ahmad, N.B., Shamsuddin, S.M.: A data mining approach to predict academic performance of students using ensemble techniques. In: Abraham, A., Cherukuri, A., Melin, P., Gandhi, N. (eds.) ISDA 2018 2018. AISC, vol. 940, pp. 749–760. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-16657-1_70
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Ajibade, SS.M. et al. (2023). Teacher’s Attitudes Towards Improving Inter-professional Education and Innovative Technology at a Higher Institution: A Cross-Sectional Analysis. In: Abraham, A., Bajaj, A., Gandhi, N., Madureira, A.M., Kahraman, C. (eds) Innovations in Bio-Inspired Computing and Applications. IBICA 2022. Lecture Notes in Networks and Systems, vol 649. Springer, Cham. https://doi.org/10.1007/978-3-031-27499-2_66
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