The Effects of Drowsiness Detection Technology and Education on Nurses’ Beliefs and Attitudes toward Drowsy Driving

References

• Aidman, E., Chadunow, C., Johnson, K., & Reece, J. (2015). Real-time driver drowsiness feedback improves driver alertness and self-reported driving performance. Accident; Analysis and Prevention, 81, 8–13. https://doi.org/10.1016/j.aap.2015.03.041
   PubMed Web of Science ®Google Scholar
• Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl & J. Beckmann (Eds.), Action control (pp. 11–39). Springer. https://doi.org/10.1007/978-3-642-69746-3_2
   Google Scholar
• Ajzen, I. (2013). Theory of planned behaviour questionnaire. Measurement Instrument Database for the Social Science. https://www.midss.org/sites/default/files/tpb.questionnaire_sample.pdf
   Google Scholar
• Cho, J. (2016). The impact of post-adoption beliefs on the continued use of health apps. International Journal of Medical Informatics, 87, 75–83. https://doi.org/10.1016/j.ijmedinf.2015.12.016
   PubMed Web of Science ®Google Scholar
• Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334. https://doi.org/10.1007/BF02310555
   Web of Science ®Google Scholar
• Deng, Z., Hong, Z., Ren, C., Zhang, W., & Xiang, F. (2018). What predicts patients’ adoption intention toward mhealth services in China: Empirical study. JMIR mHealth and uHealth, 6(8), e172. https://doi.org/10.2196/mhealth.9316
   PubMed Web of Science ®Google Scholar
• Dikmen, M., & Burns, C. M. (2016). Autonomous driving in the real world: Experiences with Tesla Autopilot and Summon. In Proceedings of the 8th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (pp. 225––228). Association for Computing Machinery. https://doi.org/10.1145/3003715.3005465
   Google Scholar
• Dorrian, J., Baulk, S. D., & Dawson, D. (2011). Work hours, workload, sleep and fatigue in Australian Rail Industry employees. Applied Ergonomics, 42(2), 202–209. https://doi.org/10.1016/j.apergo.2010.06.009
   PubMed Web of Science ®Google Scholar
• Dorrian, J., Tolley, C., Lamond, N., van den Heuvel, C., Pincombe, J., Rogers, A. E., & Drew, D. (2008). Sleep and errors in a group of Australian hospital nurses at work and during the commute. Applied Ergonomics, 39(5), 605–613. https://doi.org/10.1016/j.apergo.2008.01.012
   PubMed Web of Science ®Google Scholar
• Dou, K., Yu, P., Deng, N., Liu, F., Guan, Y., Li, Z., Ji, Y., Du, N., Lu, X., & Duan, H. (2017). Patients’ Acceptance of smartphone health technology for chronic disease management: A theoretical model and empirical test. JMIR mHealth and uHealth, 5(12), e177. https://doi.org/10.2196/mhealth.7886
   PubMed Web of Science ®Google Scholar
• Edwards, M. P., McMillan, D. E., & Fallis, W. M. (2013). Napping during breaks on night shift: Critical care nurse managers’ perceptions. Dynamics (Pembroke, Ont.), 24(4), 30–35.
   PubMedGoogle Scholar
• Factor, R., Williams, D. R., & Kawachi, I. (2013). Social resistance framework for understanding high-risk behavior among nondominant minorities: Preliminary evidence. American Journal of Public Health, 103(12), 2245–2251. https://doi.org/10.2105/AJPH.2013.301212
   PubMed Web of Science ®Google Scholar
• Fallis, W. M., McMillan, D. E., & Edwards, M. P. (2011). Napping during night shift: Practices, preferences, and perceptions of critical care and emergency department nurses. Critical Care Nurse, 31(2), e1–e11. https://doi.org/10.4037/ccn2011710
   Web of Science ®Google Scholar
• Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Addison-Wesley.
   Google Scholar
• Fogg, B. J. (2003). Persuasive technology: Using computers to change what we think and do. Morgan Kaufmann Publishers. https://doi.org/10.1145/764008.763957
   Google Scholar
• French, D. J., West, R. J., Elander, J., & Wilding, J. M. (1993). Decision-making style, driving style, and self-reported involvement in road traffic accidents. Ergonomics, 36(6), 627–644. https://doi.org/10.1080/00140139308967925
   PubMed Web of Science ®Google Scholar
• Ftouni, S., Sletten, T. L., Howard, M., Anderson, C., Lenné, M. G., Lockley, S. W., & Rajaratnam, S. M. W. (2013). Objective and subjective measures of sleepiness, and their associations with on-road driving events in shift workers. Journal of Sleep Research, 22(1), 58–69. https://doi.org/10.1111/j.1365-2869.2012.01038.x
   PubMed Web of Science ®Google Scholar
• Geiger-Brown, J. G., Sagherian, K., Zhu, S., Wieroniey, M., Blair, L., Warren, J., Hinds, P., & Szeles, R. (2016). Napping on the night shift: A two-hospital implementation project. The American Journal of Nursing, 116(5), 26–33. https://doi.org/10.1097/01.NAJ.0000482953.88608.80
   Web of Science ®Google Scholar
• Geiger-Brown, J., Rogers, V. E., Trinkoff, A. M., Kane, R. L., Bausell, R. B., & Scharf, S. M. (2012). Sleep, sleepiness, fatigue, and performance of 12-hour-shift nurses. Chronobiology International, 29(2), 211–219. https://doi.org/10.3109/07420528.2011.645752
   PubMed Web of Science ®Google Scholar
• Gregor, K., Zvolensky, M., McLeish, A., Bernstein, A., & Morissette, S. (2008). Anxiety sensitivity and perceived control over anxiety-related events: Associations with smoking outcome expectancies and perceived cessation barriers among daily smokers. Nicotine & Tobacco Research: Official Journal of the Society for Research on Nicotine and Tobacco, 10(4), 627–635. https://doi.org/10.1080/14622200801978706
   PubMed Web of Science ®Google Scholar
• Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a Silver Bullet. Journal of Marketing Theory and Practice, 19(2), 139–152. https://doi.org/10.2753/MTP1069-6679190202
   Google Scholar
• Hajian, S., Vakilian, K., Najabadi, K. M., Hosseini, J., & Mirzaei, H. R. (2011). Effects of education based on the health belief model on screening behavior in high risk women for breast cancer, Tehran, Iran. Asian Pacific Journal of Cancer Prevention: APJCP, 12(1), 49–54.
   Google Scholar
• Harst, L., Lantzsch, H., & Scheibe, M. (2019). Theories predicting end-user acceptance of telemedicine use: Systematic review. Journal of Medical Internet Research, 21(5), e13117.
   PubMed Web of Science ®Google Scholar
• Horne, J., & Reyner, L. (1996). Counteracting driver sleepiness: Effects of napping, caffeine, and placebo. Psychophysiology, 33(3), 306–309. https://doi.org/10.1111/j.1469-8986.1996.tb00428.x
   PubMed Web of Science ®Google Scholar
• Janz, N. K., & Becker, M. H. (1984). The health belief model: A decade later. Health Education Quarterly, 11(1), 1–47.
   PubMedGoogle Scholar
• Kidwell, B., & Jewell, R. D. (2007). The moderating effects of past experience on behavioral intentions. In G. Fitzsimons & V. Morwitz (Eds.), NA - Advances in Consumer Research (Vol. 34, pp. 555–556). Association for Consumer Research. https:///www.acrwebsite.org/volumes/12878/volumes/v34/NA-34
   Google Scholar
• Kruskal, W. H., & Wallis, W. A. (1952). Use of ranks in one-criterion variance analysis. Journal of the American Statistical Association, 47(260), 583–621. https://doi.org/10.1080/01621459.1952.10483441
   Web of Science ®Google Scholar
• Lee, C. J., Geiger-Brown, J., & Beck, K. H. (2016). Intentions and willingness to drive while drowsy among university students: An application of an extended theory of planned behavior model. Accident; Analysis and Prevention, 93, 113–123. https://doi.org/10.1016/j.aap.2016.05.002
   PubMed Web of Science ®Google Scholar
• Mulhall, M. D., Sletten, T. L., Magee, M., Stone, J. E., Ganesan, S., Collins, A., Anderson, C., Lockley, S. W., Howard, M. E., & Rajaratnam, S. M. W. (2019). Sleepiness and driving events in shift workers: The impact of circadian and homeostatic factors. Sleep, 42(6), zsz074. https://doi.org/10.1093/sleep/zsz074
   Web of Science ®Google Scholar
• Nazari, S. S. H., Moradi, A., & Rahmani, K. (2017). A systematic review of the effect of various interventions on reducing fatigue and sleepiness while driving. Chinese Journal of Traumatology = Zhonghua Chuang Shang za Zhi, 20(5), 249–258.
   PubMed Web of Science ®Google Scholar
• Ng, T. W. Y., Cowling, B. J., So, H. C., Ip, D. K. M., & Liao, Q. (2020). Testing an integrative theory of health behavioural change for predicting seasonal influenza vaccination uptake among healthcare workers. Vaccine, 38(3), 690–698. https://doi.org/10.1016/j.vaccine.2019.10.041
   PubMed Web of Science ®Google Scholar
• Nguyen-Feng, V. N., Frazier, P. A., Roy, N., Cohen, S., & Misono, S. (2021). Perceived control, voice handicap, and barriers to voice therapy. Journal of Voice, 35(2), 326.e13–326.E19. https://doi.org/10.1016/j.jvoice.2019.09.002
   Web of Science ®Google Scholar
• National Institute for Occupational Safety & Health. (2015). NIOSH training for nurses on shift work and long work hours. U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health. https://doi.org/10.26616/NIOSHPUB2015115revised102019
   Google Scholar
• Novak, R. D., & Auvil-Novak, S. E. (1996). Focus group evaluation of night nurse shiftwork difficulties and coping strategies. Chronobiology International, 13(6), 457–463. https://doi.org/10.3109/07420529609020916
   PubMed Web of Science ®Google Scholar
• Parasuraman, R., & Miller, C. A. (2004). Trust and etiquette in high-criticality automated systems. Communications of the ACM, 47(4), 51–55. https://doi.org/10.1145/975817.975844
   Web of Science ®Google Scholar
• Pender, N. J., & Pender, A. R. (1986). Attitudes, subjective norms, and intentions to engage in health behaviors. Nursing Research, 35(1), 15–18.
   Web of Science ®Google Scholar
• Reyner, L. A., & Horne, J. A. (1997). Suppression of sleepiness in drivers: Combination of caffeine with a short nap. Psychophysiology, 34(6), 721–725. https://doi.org/10.1111/j.1469-8986.1997.tb02148.x
   PubMed Web of Science ®Google Scholar
• Scott, L. D., Hofmeister, N., Rogness, N., & Rogers, A. E. (2010). Implementing a fatigue countermeasures program for nurses. The Journal of Nursing Administration, 40(5), 233–240. https://doi.org/10.1097/NNA.0b013e3181da4078
   PubMed Web of Science ®Google Scholar
• Scott, L. D., Hwang, W.-T., Rogers, A. E., Nysse, T., Dean, G. E., & Dinges, D. F. (2007). The relationship between nurse work schedules, sleep duration, and drowsy driving. Sleep, 30(12), 1801–1807. https://doi.org/10.1093/sleep/30.12.1801
   PubMed Web of Science ®Google Scholar
• Sideridis, G., Simos, P., Papanicolaou, A., & Fletcher, J. (2014). Using structural equation modeling to assess functional connectivity in the brain: Power and sample size considerations. Educational and Psychological Measurement, 74(5), 733–758. https://doi.org/10.1177/0013164414525397
   PubMed Web of Science ®Google Scholar
• Sletten, T. L., Ftouni, S., Nicholas, C. L., Magee, M., Grunstein, R. R., Ferguson, S., Kennaway, D. J., O’Brien, D., Lockley, S. W., & Rajaratnam, S. M. W. (2017). Randomised controlled trial of the efficacy of a blue-enriched light intervention to improve alertness and performance in night shift workers. Occupational and Environmental Medicine, 74(11), 792–801. https://doi.org/10.1136/oemed-2016-103818
   PubMed Web of Science ®Google Scholar
• Smit, E. S., de Vries, H., & Hoving, C. (2013). Determinants of practice nurses’ intention to implement a new smoking cessation intervention: The importance of attitude and innovation characteristics. Journal of Advanced Nursing, 69(12), 2665–2674. https://doi.org/10.1111/jan.12153
   Web of Science ®Google Scholar
• Smith, A., McDonald, A. D., & Sasangohar, F. (2020). Night-shift nurses and drowsy driving: A qualitative study. International Journal of Nursing Studies, 112, 103600. https://doi.org/10.1016/j.ijnurstu.2020.103600
   PubMed Web of Science ®Google Scholar
• Smith, A., McDonald, A. D., & Sasangohar, F. (2021). The impact of commutes, work schedules, and sleep on near-crashes during nurses’ post shift-work commutes: A naturalistic driving study. IISE Transactions on Occupational Ergonomics and Human Factors, 9(1), 13–22. https://doi.org/10.1080/24725838.2021.1945708
   PubMedGoogle Scholar
• Smith, A., McDonald, A., Sasangohar, F., Sosa, L., Lazaro, L., & Ouko, C. (2020). Preventing drowsy driving crashes among night shift nurses: An evaluation of educational and technological interventions. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 64(1), 1592–1593. https://doi.org/10.1177/1071181320641380
   Google Scholar
• Smith, A., Sasangohar, F., McDonald, A. D., Bonuel, N., Shui, H., Ouko, C., & Lazaro, L. (2019). Drowsy driving among shift work nurses: A qualitative data analysis. Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care, 8(1), 167–171. https://doi.org/10.1177/2327857919081041
   Google Scholar
• Steege, L. M., Pinekenstein, B. J., Rainbow, J. G., & Arsenault Knudsen, É. (2017). Addressing occupational fatigue in nurses: Current state of fatigue risk management in hospitals, part 1. The Journal of Nursing Administration, 47(9), 426–433. https://doi.org/10.1097/NNA.0000000000000509
   Web of Science ®Google Scholar
• Trinkoff, A. M., Baldwin, C. M., Chasens, E. R., Dunbar-Jacob, J., Geiger-Brown, J., Imes, C. C., Landis, C. A., Patrician, P. A., Redeker, N. S., Rogers, A. E., Scott, L. D., Todero, C. M., Tucker, S. J., & Weinstein, S. M. (2021). CE: Nurses are more exhausted than ever: What should we do about it? The American Journal of Nursing, 121(12), 18–28. https://doi.org/10.1097/01.NAJ.0000802688.16426.8d
   Web of Science ®Google Scholar
• Williamson, T. M., Rouleau, C. R., Aggarwal, S. G., Arena, R., & Campbell, T. S. (2020). Bridging the intention-behavior gap for cardiac rehabilitation participation: The role of perceived barriers. Disability and Rehabilitation, 42(9), 1284–1291. https://doi.org/10.1080/09638288.2018.1524519
   PubMed Web of Science ®Google Scholar
• Wolf, E. J., Harrington, K. M., Clark, S. L., & Miller, M. W. (2013). Sample size requirements for structural equation models: An evaluation of power, bias, and solution propriety. Educational and Psychological Measurement, 73(6), 913–934. https://doi.org/10.1177/0013164413495237
   Web of Science ®Google Scholar
• Yoon, H. J., & Kim, Y. J. (2016). Understanding green advertising attitude and behavioral intention: An application of the health belief model. Journal of Promotion Management, 22(1), 49–70. https://doi.org/10.1080/10496491.2015.1107006
   Google Scholar
• Zhang, Y., Liu, C., Luo, S., Xie, Y., Liu, F., Li, X., & Zhou, Z. (2019). Factors influencing patients’ intentions to use diabetes management apps based on an extended unified theory of acceptance and use of technology model: Web-based survey. Journal of Medical Internet Research, 21(8), e15023. https://doi.org/10.2196/15023
   PubMed Web of Science ®Google Scholar