The effectiveness of short text messages on nurses' arrhythmia interpretation skills

Nurses' competency on electrocardiography interpretation in adult emergency room: Addis Ababa, Ethiopia, 2021. Multicenter cross-sectional study

AIM

This study aimed to assess the proficiency of nurses in interpreting electrocardiogram within the adult emergency units of Addis Ababa, Ethiopia, during the year 2021.

METHODS

This institutional-based descriptive, cross-sectional study involved 175 nurses from five randomly selected hospitals' adult emergency units. Semi-structured, self-administered questionnaires were used for data collection. Data were entered into Epi-Data and analyzed using SPSS version 26. Fisher's exact test identified statistical significance between dependent and independent variables at a p-value < 0.05.

RESULTS

Out of 203 respondents, 175 participated actively, yielding a response rate of 86.2%. Among these nurses, 159 (90.9%) were deemed not competent (scoring < 65%), with a mean score of 6.82 ± 3.65 SD.

PATIENT OR PUBLIC CONTRIBUTION

No patient or public contribution was included in this study.

CONCLUSION

The overall competency level in electrocardiogram interpretation among nurses is significantly poor. This indicates that most nurses in the emergency units are unable to accurately interpret ECG monitoring, potentially leading to the failure to recognize signs of arrhythmias, electrolyte disturbances, and other cardiac abnormalities. Consequently, this may result in inappropriate patient care and increased mortality rates. Education and training were identified as key factors in enhancing their competency.

Effects of technology-based educational tools on nursing learning outcomes in intensive care units: a systematic review and meta-analysis

BACKGROUND

Nurses working in the Intensive Care Unit (ICU), due to the sensitivity and difficulty of tasks, need continuous and scientific training to be able to offer the best performance in difficult situations and use their knowledge in the best way. Also, nursing students spend internships in ICUs and receive special training in practice in the actual center. Educational tools based on new technologies can potentially improve the educational outcomes of nursing in ICUs.

OBJECTIVES

 The present study aims to review and evaluate the effect of using technology-based educational tools for training critical care nurses and nursing students.

METHODS

 A comprehensive search was conducted to identify peer-reviewed English language articles in Embase, Medline (through PubMed), Scopus, and ISI web of science published from 2010 to Feb 18, 2022. The studies that examined the effectiveness of technology-based educational interventions with control groups were included. The risk of bias in each study was assessed using the Cochrane Collaboration's tool. Also, we used Standard Mean Difference (SMD) to estimate the effect of technology-based educational tools on learning outcomes. All meta-analyses were performed with a random effects model in Stata Ver.16.

RESULTS

 Altogether, ten studies were eligible for the quality assessment and systematic review, while one study that had not reported the pre-intervention analysis was excluded from the meta-analysis. Nine studies were considered to have a low RoB regarding reporting ways, and one of them showed a high risk. Performance and selection bias caused a high risk in six and five of the studies, respectively. In the meta-analysis, improvement in knowledge (SMD = 0.91), skills (SMD = 0.52), and self-confidence (SMD = 0.96) was noticed by applying technology-based educational tools.

CONCLUSION

It can be offered that if the learning method based on the new technologies tested is more effective than conventional teaching methods, they are likely to improve the learning outcome significantly. The new-developed tools also have great potential in improving health care functions among nurses or nursing students as well as enhancing the quality of life and patient satisfaction.

Assessment of electrocardiogram interpretation competency among healthcare professionals and students of Ardabil University of Medical Sciences: a multidisciplinary study

BACKGROUND

Electrocardiogram (ECG) interpretation is a core clinical skill that helps to rapid diagnosis of potentially life-threatening diseases. Misinterpretation of the electrocardiogram can lead to inappropriate clinical decisions with adverse outcomes. The main aim of this survey was to assess the competency of electrocardiogram interpretation and related factors among healthcare professionals and students of Ardabil University of Medical Sciences.

METHODS

This descriptive cross-sectional study included 323 staff and students of Ardabil University of Medical Sciences in northwestern Iran. Data were collected randomly from November to January 1400 using the Badell-Coll ECG Interpretation Competency Questionnaire and analyzed using SPSS V.14. Statistical analysis included descriptive statistics, independent t-test, ANOVA, Pearson correlation coefficient and multiple linear regression.

RESULTS

The results showed that the mean and standard deviation of electrocardiogram interpretation competency of health professional staff and students was 5.13 ± 2.25 (maximum score = 10). The large number of participants wasn't able to identify normal sinus rhythm (n = 251, 77.3%), acute myocardial infarction (n = 206, 63.8%) and pathological Q waves (n = 201, 62.2%). The results of multiple linear regression showed that the variables of education level, self-assessment of electrocardiogram interpretation competence, work experience, and type of hospital were able to predict the competence of ECG interpretation in participants.

CONCLUSIONS

Our findings showed that the participants' level of electrocardiogram interpretation competency was low. Hence, regular, standard training and education are recommended. Also, managers and educators of the health system should consider the role of positive self-assessment and exposure to ECG interpretation in improving the competence of staff and students to interpret ECG.