Adoption of quick response codes as a digital microlearning tool among clinical nurses: a quasi-experimental study

• Published in: BMC medical education Vol. 24; no. 1; pp. 1 - 8
• Main Authors: Mollaei, Amirabbas, Tabari-Khomeiran, Rasoul, Maroufizadeh, Saman, SedghiSabet, Mitra
• Format: Journal Article
• Language: English
• Published: London BioMed Central Ltd 05.11.2024; BioMed Central; BMC
• Subjects: Codes; Educational Development; Educational Resources; Environment; Global positioning systems; GPS; Health care industry; Hospitals; Individual Differences; Influence of Technology; Information sharing; Instructional Materials; Learning Modules; Lifelong Learning; Medical equipment; Medical Evaluation; Medical technology; Microlearning; Nurses; Nursing; Nursing Education; Physiological apparatus; Predictor Variables; Quasi-experimental methods; Quick response code; Regression (Statistics); Regression analysis; Researchers; Sample size; Sampling; Science Equipment; Smartphones; Technology Acceptance Model; Time; Training Methods; Workplace Learning
• ISSN: 1472-6920; 1472-6920
• DOI: 10.1186/s12909-024-06278-1

Background The rapid growth of technology forced enormous changes in the provision of healthcare services. Different strategies are used to keep nurses up to date with rapid changes in health systems. Microlearning is one of the new methods of teaching professional skills to health workers. This method is effective in care settings that have many limitations in terms of time and place. However, it is very important to test the acceptability of this method among nurses before practical measures are taken for its widespread use. This study aimed to determine nurses' acceptance rate of quick response code as a microlearning tool in workplace. Method This is a cross-sectional study was conducted in medical and surgical wards in hospitals affiliated to Guilan University of Medical Sciences. 185 nurses participated in the study. A number of selected medical devices were labeled with quick response codes containing educational content. The eligible nurses were instructed how to use the QR codes. After two months, they were asked to complete a questionnaire adapted from the technology acceptance model 3. SPSS 21 software was used to analyze the data. Results 166 nurses and 19 head nurses with mean age of 34.26 [+ or -] 8.17 years and mean work experience of 10.46 [+ or -] 7.64 years completed the questionnaires. Most participants were female, married, with a bachelor's degree, worked on rotating shifts, in medical wards. The findings showed that the acceptance of the quick response code as a learning tool was at a moderate level (M = 66.1, SD = 16.6). Statistically, there was no significant relationship between nurses' demographic characteristics and the total acceptance rate (P > 0.05). However, the analyses at the multivariate level, using multiple linear regression, showed a significant superiority of the total acceptance score in head nurses compared to nurses (b = 7.97, P = 0.047) and in nurses who had previous experience of using quick response codes, compared to colleagues without such experience (b = 5.18, P = 0.036). Based on the coefficient of determination, only 6.1% of the changes in the total acceptance score of quick response codes of nurses are explained by their personal-occupational characteristics (R.sup.2 = 0.061). Conclusions The provision of QR code requirements such as necessary infrastructure and training by the health authorities could increase the acceptance of this tool as a microlearning measure. Keywords: Microlearning, Quick response code, Medical equipment, Technology acceptance model, Nurses