Cent Eur J Nurs Midw 2022, 13(1):595-602 | DOI: 10.15452/cejnm.2021.12.0034

Complexity and intention to use an innovative device for post-infarction patients: rehabilitation nurses’ perspectives

Rafael Alves Bernardes1, Pedro Parreira1, Luís Sousa2, Arménio Cruz1
1 The Health Sciences Research Unit: Nursing (UICISA:E), Nursing School of Coimbra (ESEnfC), Portugal
2 Comprehensive Health Research Centre (CHRC), Department of Nursing, University of Évora, Portugal

Aim:  This study aims to describe rehabilitation nurses’ perspectives on the complexity of and intention to use an innovative device for post-infarction patients. Design: The research employed a qualitative method, with a video demonstration, and analysis provided by the participants. To guide the study, the Technology Acceptance Model was used in order to measure perceived usefulness and perceived ease of use. Methods: Focus Groups were used to collect nurses’ perspectives on the developed device. Recruitment followed a snowball sampling method. Eligible participants received an email with an informed consent form. Privacy and confidentiality were maintained throughout. Content analysis was performed using ATLAS.ti v7, with Bardin’s technique, i.e., an a posteriori categorical organization. Results: Three categories were identified as relevant to the study objectives: “Therapeutic adherence and motivation”; “Home and autonomy of the patient and caregiver”; and “Factors that facilitate the practice of the rehabilitation nurse”. Participants felt that the innovation and technological complexity of the device might help to increase patient motivation and adherence, which would be of great use to rehabilitation nurses, allowing better intervention development. Conclusion: Participants perceived the device as useful to practice, and beneficial to post-infarction patients. Interestingly, the complexity inherent to the device is regarded as a factor that may increase motivation and adherence.

Keywords: cardiac rehabilitation, myocardial infarction, nurses, rehabilitation nursing, self-help devices

Received: May 4, 2021; Revised: November 4, 2021; Accepted: November 23, 2021; Prepublished online: December 27, 2021; Published: March 5, 2022  Show citation

ACS AIP APA ASA Harvard Chicago Chicago Notes IEEE ISO690 MLA NLM Turabian Vancouver
Alves Bernardes R, Parreira P, Sousa L, Cruz A. Complexity and intention to use an innovative device for post-infarction patients: rehabilitation nurses’ perspectives. Central European Journal of Nursing and Midwifery. 2022;13(1):595-602. doi: 10.15452/cejnm.2021.12.0034.
Share...
Download citation
  • BibTeX (.bib)
  • Bookends (.ris)
  • EasyBib (.ris)
  • EndNote (.enw)
  • EndNote 8 (.xml)
  • ISI WoS (.isi)
  • Medlars (.medlars)
  • Mendeley (.ris)
  • MODS (.xml)
  • Papers (.ris)
  • RefWorks (.txt)
  • RefManager (.ris)
  • RIS (.ris)
  • MS Word (.xml)
  • Zotero (.ris)
    • Open full article

    References

    1. Bardin, L. (2016). Análise de Conteúdo [Content analysis]. Edições 70.
    2. Bitterman, N. (2011). Design of medical devices - a home perspective. European Journal of Internal Medicine, 22(1), 39-42. https://doi.org/10.1016/j.ejim.2010.09.017 Go to original source... Go to PubMed...
    3. Bodilsen, A. C., Klausen, H. H., Petersen, J., Beyer, N., Andersen, O., Jørgensen, L. M., Juul-Larsen, H. G., & Bandholm, T. (2016). Prediction of mobility limitations after hospitalization in older medical patients by simple measures of physical performance obtained at admission to the emergency department. PLoS ONE, 11(5), e0154350. https:/doi.org/10.1371/journal.pone.0154350 Go to original source... Go to PubMed...
    4. Brysiewicz, P., Hughes, T. L., & McCreary, L. L. (2015). Promoting innovation in global nursing practice. Rwanda Journal Series F: Medicine and Health Sciences, 2(2), 41-45. https://doi.org/10.4314/rj.v2i2.7F Go to original source...
    5. Burns, D., Westra, H., Trockel, M., & Fisher, A. (2013). Motivation and changes in depression. Cognitive Therapy and Research, 37(2), 368-379. https://doi.org/10.1007/s10608-012-9458-3 Go to original source...
    6. Casas, J. A., Céspedes, N., Cifuentes, C. A., Gutierrez, L. F., Rincón-Roncancio, M., & Múnera, M. (2019). Expectation vs reality: attitudes towards a socially assistive robot in cardiac rehabilitation. Applied Sciences, 9(21), 4651. https://doi.org/10.3390/APP9214651 Go to original source...
    7. Castner, J., Sullivan, S. S., Titus, A. H., & Klingman, K. J. (2016). Strengthening the role of nurses in medical device development. Journal of Professional Nursing, 32(4), 300-305. Go to original source... Go to PubMed...
    8. 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 Uhealth, 6(8), e172. https://doi.org/10.2196/mhealth.9316 Go to original source... Go to PubMed...
    9. Garcia, R. P., Budó, M. L. D., Simon, B. S., Wusch, S., Oliveira, S. G., & Barbosa, M. S. (2013). Vivências da família após infarto agudo do miocárdio [Family experiences after acute myocardial infarction]. Revista Gaúcha de Enfermagem, 34(3). https://doi.org/10.1590/S1983-14472013000300022 Go to original source... Go to PubMed...
    10. Hajduk, A. M., Dodson, J. A., Murphy, T. E., Tsang, S., Geda, M., Ouellet, G. M., Gill, T. M., Brush, J. E., & Chaudhry, S. I. (2020). Risk model for decline in Activities of Daily Living among older adults hospitalized with acute myocardial infarction: The SILVER-AMI study. Journal of the American Heart Association, 9, e015555. https://doi.org/10.1161/JAHA.119.015555 Go to original source... Go to PubMed...
    11. Halpin, A. P. & Hodge, F. S. (2019). Transition theory applications - "wishes". American Journal of Education and Information Technology, 3(1), 12-16.
    12. He, Y., Chen, Q., & Kitkuakul, S. (2018). Regulatory focus and technology acceptance: perceived ease of use and usefulness as efficacy. Cogent Business & Management, 5(1), Article ID 1459006. https://doi.org/10.1080/23311975.2018.1459006 Go to original source...
    13. Huang, T. C. K., Liu, C. C., Chang, D. C. (2012). An empirical investigation of factors influencing the adoption of data mining tools. International Journal of Information Management, 32(3), 257-270. https://doi.org/10.1016/j.ijinfomgt.2011.11.006 Go to original source...
    14. Jenèa, D., Melenovský, V., Stehlik, J., Stanìk, V., Kettner, J., Kautzner, J., Adámkova, V., & Wohlfahrt, P. (2021). Heart failure after myocardial infarction: incidence and predictors. ESC Heart Failure, 8(1), 222-237. https://doi.org/10.1002/ehf2.13144 Go to original source... Go to PubMed...
    15. Koh, K. W. L., Wang, W., Richards, A. M., Chan, M. Y., & Cheng, K. K. F. (2016). Effectiveness of advanced practice nurse-led telehealth on readmissions and health-related outcomes among patients with post-acute myocardial infarction: ALTRA Study Protocol. Journal of Advanced Nursing, 72(6), 1357-1367. https://doi.org/10.1111/jan.12933 Go to original source... Go to PubMed...
    16. Kweon, S., Sohn, M. K., Jeong, J. O., Kim, S., Jeon, H., Lee, H., Ahn, S-C., Park, S. H., & Jee, S. (2017). Quality of life and awareness of cardiac rehabilitation in people with cardiovascular diseases. Annals of Rehabilitation Medicine, 41(2), 248-256. https://doi.org/10.5535/arm.2017.41.2.248 Go to original source... Go to PubMed...
    17. Lai, P. C. (2017). The literature review of technology adoption models and theories for the novelty technology. Journal of Information Systems and Technology Management, 14(1), 21-38. httsp://doi.org/10.4301/S1807-17752017000100002 Go to original source...
    18. Lara, J. S., Casas, J., Aguirre, A., Munera, M., Rincon Roncancio, M., Irfan, B., Senft, E., Belpaeme, T., & Cifuentes, C. A. (2017). Human-robot sensor interface for cardiac rehabilitation. In F. Amirabdollahian, E. Burdet, & M. Lorenzo, Medical and Health-Care Robotics (Eds., pp. 1013-1018). IEEE Xplore. https://doi.org/10.1109/ICORR40122.2017 Go to original source...
    19. Lee, H., Chung, H., Ko, H., Jeong, C., Noh, S., Kim, C., & Lee, J. (2017). Dedicated cardiac rehabilitation wearable sensor and its clinical potential. PLoS One, 12(10), e0187108. https://doi.org/10.1371/journal.pone.0187108 Go to original source... Go to PubMed...
    20. Lopes, M. F. S. (2011). The person with acute myocardial infarction - male impact [Master's dissertation, ICBAS - School of Medicine and Biomedical Sciences]. Open Repository of the University of Porto. https://repositorio-aberto.up.pt/bitstream/10216/71918/2/30451.pdf
    21. Myskja, B. K., & Steinsbekk, K. S. (2020). Personalized medicine, digital technology and trust: a Kantian account. Medicine, Health Care and Philosophy, 23, 577-587. https://doi.org/10.1007/s11019-020-09974-z Go to original source... Go to PubMed...
    22. Nakajima, H., Yoshioka, J., Totsuka, N., Miyazawa, I., Usui, T., Urasawa, N., Kobayashi, T., & Mochidome, T. (2016). Activities of daily living as an additional predictor of complications and outcomes in elderly patients with acute myocardial infarction. Clinical Interventions in Aging, 11, 1141-1147. https://dx.doi.org/10.2147/CIA.S107136 Go to original source... Go to PubMed...
    23. O'Brien, B. C., Harris, I. B., Beckman, T. J., Reed, D. A., & Cook, D. A. (2014). Standards for reporting qualitative research: a synthesis of recommendations. Academic Medicine, 89(9), 1245-1251. https://doi.org/10.1097/ACM.0000000000000388 Go to original source... Go to PubMed...
    24. Okamura, A. M., Mataric, M. J., & Cristensen, H. I. (2010). Medical and health-care robotics. IEEE Robot, 17(3), 26-37. https://doi.org/10.1109/MRA.2010.937861 Go to original source...
    25. Paiva, S., & Ferreira, P. (2018). Transição Saúde-Doença na Pessoa com Enfarte Agudo do Miocárdio: Estudo Qualitativo [Health-disease transition in persons with acute myocardial infarction: qualitative study]. Revista de Investigação & Inovação em Saúde, 1(1), 57-66. Go to original source...
    26. Potter, P. A., & Perry, A. G. (2018). Nursing fundamentals. 9th edition. Elsevier.
    27. Qian, Z., & Bi, Z. (2014). Recent development of rehabilitation robots. Advances in Mechanical Engineering, 2014, Article ID 563062. Go to original source...
    28. Rahimi, B., Nadri, H., Afshar, H. L., & Timpka, T. (2018). A systematic review of the technology acceptance model in health informatics. Applied Clinical Informatics, 9(3), 604-634. https://doi.org/10.1055/s-0038-1668091 Go to original source... Go to PubMed...
    29. Seewoodharry, M. S., Maconachie, G. D. E., Gillies, C. L., Gottlob, I., & McLean, R. J. (2017). The effects of feedback on adherence to treatment: a systematic review and meta-analysis of RCTs. American Journal of Preventive Medicine, 53(2), 232-240. https://doi.org/10.1016/j.amepre.2017.03.005 Go to original source... Go to PubMed...
    30. Silva, J. P. A. (2012). Quality of life of individuals after acute myocardial infarction [Master's dissertation. Viseu Higher School of Health]. Open Repository of Viseu Higher School of Health. https://repositorio.ipv.pt/bitstream/10400.19/1694/1/SILVA%20Jose%20Paulo%20Almeida%20-%20QUALIDADE%20VIDA%20INDIV%C3%8DDUOS%20AP%C3%93S%20%20ENFARTE%20AGUDO%20MIOCRADIO.pdf
    31. Strudwick, G. (2015). Predicting nurses' use of healthcare technology using the technology acceptance model. CIN: Computers, Informatics, Nursing, 33(5), 189-198. https://doi.org/10.1097/CIN.0000000000000142 Go to original source... Go to PubMed...
    32. Thomas, R. J., Beatty, A. L., Beckei, T. M., Brewer, L. C., Brown, T. M., Forman, D. E., Franklin, B. A., Keteyian, S. J., Kitzman, D. W., Regensteiner, J. G., Sanderson, B. K., & Whooley, M. A. (2019). Home-based cardiac rehabilitation. Circulation, 140(1), e69-e89. https://doi.org/10.1161/CIR.0000000000000663 Go to original source... Go to PubMed...
    33. Virani, S. S., Alonso, A., Benjamin, E. J., Bittencourt, M. S., Callaway, C. W., Carson, A. P., Chamberlain, A. M., Chang, A. R., Cheng, S., Delling, F. N., Djousse, L., Elkind, M. S. V., Ferguson, J. F., Fornage, M., Khan, S. S., Kissela, B. M., Knutson, K. L., Kwan, T. W., Lackland, D. T., …, & Tsao, C. W. (2021). Heart disease and stroke statistics - 2021 update. Circulation, 143(8), e254-e743. https://doi.org/10.1161/CIR.0000000000000950 Go to original source... Go to PubMed...

    This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0), which permits non-comercial use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.


    Return to the content