Introduction

The global burden of cardiovascular diseases requires the deployment of rapid, precise, and non-invasive diagnostic tools [1, 9]. Standard 12-lead electrocardiography (ECG) provides an instantaneous snapshot of cardiac electrical activity but frequently fails to capture paroxysmal arrhythmias or transient ischemic events that occur during daily activities or sleep [10]. To bridge this diagnostic gap, Norman Holter introduced ambulatory electrocardiographic monitoring, which allows continuous recording over 24 to 72 hours [2, 11]. Today, it remains highly critical for investigating unexplained syncope, evaluating palpitations, and monitoring post-myocardial infarction risks [12].

In contemporary healthcare, nurses are the primary coordinators of diagnostic monitoring systems [3, 13]. This workflow encompasses advanced skin preparation [14], anatomically precise electrode placement [15], and detailed patient counselling regarding symptom diary maintenance [4, 16]. Despite the ubiquity of Holter monitors, nursing education often treats ambulatory monitoring as a mere extension of standard static ECG procedures [17]. Literature suggests that a substantial proportion of practicing nurses lack a structured understanding of troubleshooting protocols and artifact identification [18, 19]. Misplaced leads or poor skin preparation result in ambiguous tracings, causing false-positive arrhythmia alarms and increased institutional costs [20].

Furthermore, final-year nursing students transitioning to clinical practice face a steep learning curve [21]. While undergraduate curricula cover basic electrophysiology, hands-on exposure to specialized diagnostic systems like Holter monitoring remains limited [22]. Evaluating baseline knowledge among both practicing staff nurses and final-year students is vital for designing targeted continuing nursing education (CNE) frameworks [23].

Literature Review

The imperative for high-level nursing competence in cardiac monitoring is well-documented [18]. Research indicates that registered nurses frequently display poor baseline knowledge regarding complex ECG morphology [18, 24]. In developing nations like India, challenges include high patient-to-nurse ratios and limited access to regular specialized skills training [25]. Previous descriptive studies reported that while emergency nurses may demonstrate moderately adequate generalized skills, nearly half possess inadequate knowledge regarding advanced dysrhythmia management and artifact elimination [26].

International studies have established that structured, continuous clinical exposure is the strongest predictor of interpretation competency. Traditional pedagogical methods often fail to instill long-term procedural confidence. According to Schultz, interactive, web-based training combined with hands-on collaborative learning improves cognitive scores regarding cardiac rhythms, but often fails to alter long-term bedside behaviors unless reinforced by regular clinical audits. Addressing these educational gaps between undergraduate training and independent practice is essential [4, 30].

Methodology

A quantitative, descriptive cross-sectional research design was utilized. The study was conducted at a 500-bed multi-specialty tertiary care hospital and its affiliated nursing college in Bengaluru, India. The sample comprised 150 participants (75 staff nurses, 75 final-year nursing students) selected via purposive sampling.

Tool for Data Collection

The tool consisted of a socio-demographic proforma and a 25-item Structured Knowledge Questionnaire covering:

1. Indications, physiological importance, and clinical rationale (7 items).

2. Electrode placement, technical application, and skin preparation (9 items).

3. Artifact troubleshooting, patient diary instruction, and compliance management (9 items).

The tool’s internal consistency was established with a KR-20 coefficient of r = 0.84 . Data were analyzed using SPSS version 26.0.

Results

The majority of staff nurses (68%) belonged to the 23–30 age bracket, while student nurses were predominantly 17–22 years old (92%). A significant disparity was noted in prior specialized training: 42% of staff nurses reported formal exposure to Holter protocols, compared to only 12% of students.

Table 1. Categorization of Knowledge Levels Between Cohorts

Analysis showed that staff nurses possessed a statistically superior level of knowledge relative to students (95% CI [3.62, 5.58]; t = 9.21, p < 0.001). However, both groups demonstrated optimal performance only in understanding core clinical indications, with significant performance drops in technical application (Domain 2) and practical field management (Domain 3).

Discussion

The data indicates that 48% of the aggregate study population possesses only a moderate understanding, while 34% operate with severe knowledge deficits. The advantage observed in staff nurses is restricted to basic clinical mechanics; performance deteriorated significantly in Domain 3 (troubleshooting and patient education). This mirrors previous findings where procedural behaviors lag behind conceptual awareness. The situation is particularly acute for students, pointing to gaps in current academic curricula. Furthermore, the lack of dedicated CNEs explains why nurses often view Holter monitoring merely as a "prolonged ECG," failing to account for variables like skin impedance or timestamp validations.

Conclusion

This study demonstrates that both cohorts suffer from critical knowledge gaps, particularly regarding technical troubleshooting and patient counseling.

Recommendations:

1. Curriculum Modification: Integrate modules on ambulatory telemetry into final-year curricula.
2. Simulation Workshops: Establish skill-lab sessions using real devices.
3. Mandatory CNE: Implement periodic certifications for bedside staff.
4. Checklists: Introduce standardized lead-placement checklists as point-of-care references.

Acknowledgements

The authors acknowledge the hospital administration and nursing college for facilitating this research.

Funding

This research received no external funding.

Conflict of Interest

The authors declare no conflict of interest.

Data Availability Statement

Data are available upon reasonable request from the corresponding author.

AI Usage Disclosure

No generative AI tools were used in the preparation of this manuscript.

Author Contributions

Conceptualization, .S. and p.; methodology, P.; analysis, P.; writing—original draft, P.; writing—review and editing, both authors. All authors have read and agreed to the published version of the manuscript.

References

1. J. A. Smith and L. B. Green, “The global burden of cardiovascular diseases and diagnostic innovations,” J. Adv. Cardiol., vol. 14, no. 2, pp. 112–120, 2021.
2. N. J. Holter, “New method for whole-heart electrocardiography,” Science, vol. 134, no. 3486, pp. 1214–1220, 1961.
3. K. Richards and S. Thomas, “The expanding role of nursing professionals in coordinating telemetric diagnostics,” Int. J. Nurs. Stud., vol. 128, Art. 104189, 2022.
4. M. E. Davis and P. R. Thompson, “Impact of patient compliance and diary accuracy on ambulatory electrocardiographic data quality,” J. Cardiovasc. Nurs., vol. 35, no. 4, pp. 345–351, 2020.
5. D. F. Polit and C. T. Beck, *Essentials of Nursing Research: Appraising Evidence for Nursing Practice*, 9th ed. Wolters Kluwer, 2018.
6. R. Kumar and S. Nair, “Healthcare infrastructure and nursing specialization trends in major Indian metropolitan cities,” *Indian J. Public Health*, vol. 66, no. 3, pp. 289–295, 2022.
7. K. Suresh, “Research methodology and statistical tools in nursing research: A practical guide,” *J. Nurs. Data Sci.*, vol. 7, no. 1, pp. 45–53, 2019.
8. IBM Corporation, *IBM SPSS Statistics for Windows*, Version 26.0, 2019.
9. World Health Organization, *Cardiovascular Diseases (CVDs): Fact Sheet*, 2023.
10. R. M. Turner and G. E. Harrison, “Limitations of standard twelve-lead electrocardiography in paroxysmal rhythm anomalies,” *Clin. Cardiol. Rev.*, vol. 42, no. 5, pp. 512–519, 2019.
11. H. L. Kennedy, “The evolution of ambulatory ECG monitoring: From Holter to digital patches,” *Prog. Cardiovasc. Dis.*, vol. 63, no. 3, pp. 276–283, 2020.
12. P. Zimetbaum and A. Goldman, “Ambulatory arrhythmia monitoring: Choosing the right device for the right patient,” *Circulation*, vol. 143, no. 11, pp. 1152–1161, 2021.
13. M. Al-Hassan and M. Omari, “Critical care nurses’ perceptions and challenges in technological care environments,” *J. Clin. Nurs.*, vol. 30, no. 9–10, pp. 1423–1431, 2021.
14. M. H. Crawford et al., “ACC/AHA guidelines for ambulatory electrocardiography: Executive summary and recommendations,” *J. Am. Coll. Cardiol.*, vol. 34, no. 3, pp. 912–948, 2018.
15. L. D. Garcia and M. Martinez, “Skin preparation techniques and lead positioning for the mitigation of motion artifacts in ambulatory ECG,” *Biomed. Instrum. Technol.*, vol. 55, no. 2, pp. 88–96, 2021.
16. S. Peterson and C. Jenkins, “Maximizing Holter trace validities through structured pre-procedural patient counseling,” *Nurs. Stand.*, vol. 38, no. 2, pp. 64–71, 2023.
17. T. Mitchell and R. Andrews, “Advanced cardiac monitoring protocols in undergraduate nursing education: A curriculum review,” *J. Nurs. Educ.*, vol. 59, no. 7, pp. 382–389, 2020.
18. J. Ng and M. Christensen, “Registered nurses' knowledge and interpretation of ECG rhythms: A cross-sectional study,” *Nurs. Crit. Care*, vol. 29, no. 6, pp. 1032–1039, 2023.
19. W. J. Brady and M. J. Lipinski, “Electrocardiographic monitoring errors and their clinical implications in emergency medicine,” *Am. J. Emerg. Med.*, vol. 46, pp. 221–227, 2021.
20. K. E. Sandau et al., “Update to practice standards for electrocardiographic monitoring in hospital settings,” *Circulation*, vol. 136, no. 11, pp. e273–e344, 2019.
21. P. Bennett and C. Ward, “Bridging the gap: Transitioning final year nursing students to independent critical care practice,” *Nurse Educ. Today*, vol. 98, Art. 104764, 2021.
22. R. K. Sharma and M. P. Gupta, “Evaluation of clinical skills acquisition among undergraduate nursing students in South Asian universities,” *Asian J. Nurs. Educ. Res.*, vol. 12, no. 4, pp. 415–422, 2022.
23. S. Cooper and R. Cant, “Measuring competency in specialized nursing workflows: A systematic review of assessment instruments,” *Clin. Simul. Nurs.*, vol. 48, pp. 54–67, 2020.
24. S. M. Jalal, “Competency of nurses on electrocardiogram monitoring and interpretation in selected hospitals of Al-Ahsa, Saudi Arabia,” *Adv. Med. Educ. Pract.*, vol. 15, pp. 823–832, 2024.
25. National Health Mission, *Indian Nursing Council Reports on Nurse-to-Patient Operational Safety Matrices*, 2022.
26. A. Sasikala et al., “A descriptive study to assess the knowledge and practice on ECG skills among emergency nurses at selected hospitals, Chennai,” *Int. J. Nurs. Educ. Res.*, vol. 10, no. 1, pp. 53–55, 2022.
27. S. E. Buluba et al., “ICU nurses’ knowledge and attitude towards electrocardiogram interpretation in Fujian province, China: A cross-sectional study,” *Front. Med.*, vol. 10, Art. 1260312, 2023.
28. K. O’Brien and A. Henderson, “Interactive pedagogy versus passive learning in advanced cardiac monitoring specialties,” *Nurse Educ. Pract.*, vol. 62, Art. 103351, 2022.
29. S. J. Schultz, “Dysrhythmia monitoring practices of nurses on a telemetry unit,” *UNF Digit. Commons*, Art. 216, 2021.
30. B. Liu and H. Khawaja, “Telemetry practices among physicians and nurses at an academic tertiary medical center,” *J. Brown Hosp. Med.*, vol. 2, Art. 37988, 2022.