Modern Technology in the Nursing Labor

Table of Contents

As nursing labor is becoming increasingly intertwined with modern technology, new possibilities for more effective delivery of care open up. As such, telenursing, which might not be associated with cutting-edge technology, is still regarded by some scholars as a prominent mode of caregiving (Balenton & Chiappelli, 2017). In this paper, a literature review of the topic will be conducted, and the methodology for a project that explores telemedicine will be identified.

Literature Review

The newest study by Shahrokhi, Azimian, Amouzegar, and Oveisi (2018) reveals that telenursing has no positive or negative effect on readmission rates of patients. None of the patients with head trauma in the study group were reinstated in the hospital, which seems to be a positive outcome, yet, only two patients from the control group were readmitted. Such results do not provide conclusive data on whether or not telenursing is effective without a bigger sample.

Another study conducted by Harrison, Auerbach, Quinn, Kynoch, and Mourad (2014) suggests that the reliability of telenursing is ambiguous due to the fact of its dependency on the patient answering the phone. On the other hand, in patients who successfully received a call and participated in the dialogue with a nurse, readmission rates decreased slightly. Given the large sample size, the study’s uncovered data could be considered reliable.

In terms of positive features of telenursing, Balenton and Chiappelli (2017) find the economy and ease of data collection on patients are among its core strengths as a method of follow-up care delivery. In addition, this mode allows for better access to health care. Conflicting data emerges in relation to physiological outcomes of telenursing. As such, a randomized controlled trial (RCT) conducted by Goudarzian, Fallahi-Khoshknab, Dalvandi, Delbari, and Biglarian (2018) showed that while mean anxiety in post-intervention patients with stroke decreased significantly, depression levels did not show any meaningful change. Thus, one can conclude that further studies need to be conducted in order to examine the psychological effects of telenursing.

Ramelet et al. (2017) reported that in children suffering from inflammatory rheumatic diseases, telephone follow-ups managed to significantly increase care satisfaction levels and decrease the levels of pain and stiffness. This RCT clearly demonstrates the positive outcome of telemedicine as being able to provide better control of symptoms and stimulate a necessary response from parents. Thus, despite the prevalence of conflicting data in the field that is majorly due to methodological errors, one may conclude that there are certainly positive outcomes of telenursing for a patient’s health and psychological condition.

Data Collection and Sampling

Data collection should reflect the goals of the study and be designed in a manner that provides answers to research questions (LoBiondo-Wood & Haber, 2017). Given that, there is a need to collect primary data from patients. The higher the number of patients from which one could retrieve data, the more representative the study results will be. Realistically, the study will include patients from a single hospital due to the natural resource limitations imposed on this study. The sampling will be based on the non-probability model, as the study does not target any particular group of patients to test any hypotheses (LoBiondo-Wood & Haber, 2017). Thus, no age, gender, ethnicity, or other restrictions will be applied. All patients will be notified beforehand, and their voluntary participation consent will be obtained.


The tools required for this research are primarily can be divided into two categories: software and hardware. Hardware refers to the phone or smartphone that a researcher will use to contact patients. Also, the study would require a computer or a laptop to document the preliminary results, store phone records, and analyze the results. The software will include a voice recorder application and SPSS statistics tool to quantitatively analyze results.

Data Analysis and Algorithm

The study will employ quantitative methodology because it suits the nature of the research questions and provides an objective measurement of results (LoBiondo-Wood & Haber, 2017). The data analysis will follow the following algorithm:

  1. each patient who agreed to participate will leave their contact phone
  2. at regular weekly intervals, the researcher will give follow-up calls to participants gathering information on health, and mental status
  3. after four successive weeks of intervention, patients will be asked over the phone to assess their level of stress or anxiety.
  4. The readmission rates, psychological and economic effects from the intervention will be calculated through SPSS
  5. Results will be assessed, discussed, and formatted into the final paper.


All in all, the literature on the topic of telemedicine demonstrates conflicting results with certain notions of positive outcomes. Such a situation provides ground for the current research and warrants the search for new evidence. The present study adopts quantitative methodology and non-probability sampling to answer the research questions. The main tools selected for this research include a mobile phone, computer, recording, and analytic software. The research algorithm constitutes five steps, namely: enlisting participants, data collection, assessment, analysis, interpretation, and reporting.


Balenton, N., & Chiappelli, F. (2017). Telenursing: Bio information cornerstone in healthcare for the 21st century. Bioinformation, 13(12), 412-414.

Goudarzian, M., Fallahi-Khoshknab, M., Dalvandi, A., Delbari, A., & Biglarian, A. (2018). Effect of telenursing on levels of depression and anxiety in caregivers of patients with stroke: A randomized clinical trial. Iranian Journal of Nursing and Midwifery Research, 23(4), 248-252.

Harrison, J. D., Auerbach, A. D., Quinn, K., Kynoch, E., & Mourad, M. (2014). Assessing the impact of nurse post-discharge telephone calls on 30-day hospital readmission rates. Journal of General Internal Medicine, 29(11), 1519-1525.

LoBiondo-Wood, G., & Haber, J. (2017). Nursing research: Methods and critical appraisal for evidence-based practice (9th ed.). New York, NY: Elsevier Health Sciences.

Ramelet, A., S., Fonjallaz, B., Rio, L., Zoni, S., Ballabeni, P., Rapin, J., … Hofer, M. (2017). Impact of a nurse-led telephone intervention on satisfaction and health outcomes of children with inflammatory rheumatic diseases and their families: A crossover randomized clinical trial. BMC Pediatrics, 17(1), 1-10.

Shahrokhi, A., Azimian, J., Amouzegar, A., & Oveisi, S. (2018). Effect of telenursing on outcomes of provided care by caregivers of patients with head trauma after discharge. Journal of Trauma Nursing, 25(1), 21-25.

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