INTRODUCTION

The issue of coronavirus disease has received significant criticism since January 2020¹. It is an additional threat to public health worldwide. It is reported that the pandemic led to unprecedented measures and one of their consequences was distance education. As a result, many countries, including Greece, were obligated to apply exclusively distance education in their educational system, in order to minimize the spread of COVID-19.

Due to the COVID-19 pandemic, a new digital educational reality emerged, and, as a result, the academic community is facing a number of challenges. In particular, the digital divide presented in world literature needs to be bridged². Despite the difficulties, distance education offers students the opportunity to become acquainted with new technology as an urgent need. It is worth noting that distance education offers the students the opportunity to have employment at the same time as their studies or to be able to attend a second study program, if they wish^3,4. Similarly, another positive aspect is the prospect of flexibility not only in space and time but also in many interdisciplinary fields based on their interests^5,6.

In particular, international literature reveals that nursing students have largely adapted to restrictive measures of self-protection to limit the spread of the COVID-19 pandemic⁷. However, students seem to face some difficulties, particularly in clinical practice and this fact raises many concerns about their future progress⁸. In addition, there is evidence that shows a strong positive correlation between the stress of nursing students and their willingness to participate in the educational process⁹. Furthermore, a recent study in Uganda on a sample of nursing and medical students highlighted a lack of skills in using e-learning platforms¹⁰. Similarly, in a study conducted in India, a high percentage of nursing students do not believe that e-learning could replace face-to-face education¹¹. In contrast, researchers in Croatia showed that the majority of nursing students preferred a mixed model based on a combination of face-to-face and distance learning^12,13.

A questionnaire already developed through theoretical research by experts in the Philippines was used. The questionnaire included 111 Filipino nursing students at selected public and private universities. Varimax rotation and internal consistency reliability were used using Cronbach α and element total correlation. The scale was loaded into a component with loading rates ranging from -0.907 to 0.893, explaining 61.92% of the total variance. The KMO test revealed a value of 0.900, while the Bartlett test gave a value of 644.380 (df=55, p=0.000), the Cronbach alpha coefficient of the 9-item scale was 0.917. The tool was considered valid and reliable. The present study reports the translation, cultural adaptation and validation of the measurement of the attitude of nursing students regarding the sudden implementation of distance education in Greece during the pandemic. The translation strategy for intercultural research was used to translate the questionnaire into Greek. The aim of the study was the translation into Greek language, cultural adaptation and validation of the Attitude Scale towards e-learning during the period of the COVID-19 pandemic.

Even though there are studies that recognize the gaps and difficulties of the abrupt implementation of distance education¹⁴, there is a lack of knowledge concerning measuring the attitude of nursing students regarding the sudden implementation of distance education in Greece.

METHODS

RESULTS

From a total of 399 records in the online LimeSurvey^®, 58 (14.5%) were excluded due to incomplete data.

Demographic characteristics of the participants are presented in Table 1. There were 294 (86.2%) women, and the mean age of the participants was 24.4±8.1 years. Most (303; 88.9%) of the students were single, 224 (65.7%) were living with their family, while 25 (7.3%) students had a roommate and 110 (32.3%) were living with high-risk people (e.g. old, chronic diseases). Regarding e-learning process, only 43 (12.6%) students had previous experience, and 39 (11.4%) reported a learning deficit issue (Table 1). Figure 1S (Supplementary file) summarizes the total number of filled in questionnaire items, while Table 1S (Supplementary file) shows that there is no selection bias between filled in and excluded questionnaires in terms of sex, university, and study period.

Initial CFA results are given in Table 2S (Supplementary file). One of the 11 items (‘E-learning environment needs advanced technical knowledge on computer use’) does not converge with the one factor solution as proposed from the questionnaire development (p=0.450). When this item was excluded from the questionnaire, the path diagram showing the converge is shown in Figure 1. Beta coefficient ranged 0.575–1.108. Goodness-of-fit seems moderate, since RMSEA value is 0.131 (best fit when RMSEA is <0.09) and CFI is 0.877 (fit limit >0.90). In addition, EFA was applied in 11-items questionnaire and the same deleted item showed an almost zero loading (-0.007) (Supplementary file Table 3S).

Figure 1

Unstandardized (standardized) beta estimates of 10 questionnaire items in the one factor

Validity and reliability indices

In Table 2 and Figure 2, PCA was presented in the 10-item questionnaire. Analysis resulted in one explanatory factor. Presented eigenvalues were for the 5.446%, while the cumulative explained variance was 54.462%. KMO (KaiserMeier-Olkin) value was 0.910 and the Barlett’s test of sphericity gave χ²=1031.74, df=45 and p<0.0001, supporting the use of PCA on the ATel 10-items questionnaire.

Table 2

Exploratory factor analysis of the total variance explained by factor eigenvalues

	Initial (non-rotated)
1-factor solution	Total	Variance %	Cumulative %
1	5.446	54.462	54.462

Figure 2

Elbow-Scree plot technique

The ATel does not follow a normal distribution as shown from the K-S test (p<0.001). The 10 items of the Greek version of the ATel (ATel-GR) showed a high level of internal consistency with a Cronbach α equal to 0.905 (Table 3). Supplementary file Table 4S presents the values for Cronbach’s α and their values if item was deleted.

Table 3

Statistical indicators of the attitude towards e-learning scale

	Items	Cronbach’s α	Mean±SD	Kurtosis	Skewness	p*
Attitude	10	0.905	2.80±0.94	-0.307	0.424	0.001

* Kolmogorov-Smirnov normality test.

Table 4 shows the factor loadings of ATel-GR. The 1-factor solution shows non-rotated loadings of each item. All items showed high loading >0.500.

Table 4

Factor loadings of ATel-GR

Item		Loading
Q1	I am interested in studying courses that utilize e-learning	0.654
Q2	I think that e-learning promotes my learning experiences	0.769
Q3	Presenting courses on the internet makes learning more efficient	0.815
Q4	I intend to use e-learning tools during the semester if available	0.564
Q5	I am positive about e-learning	0.770
Q6	I would prefer to have courses on the internet rather than in the classroom or face-to-face	0.845
Q7	Online learning is more comfortable and enjoyable to me	0.753
Q8	E-learning is a favorable alternative to the pen-paper based system	0.756
Q9	E-learning is not an efficient learning method (-)	0.617
Q11	Overall, I prefer e-learning and I believe that it is better than the traditional method of learning	0.788

Age as a continuous variable showed a weak correlation with ATel (rs=0.254, p<0.001). When age was treated as an ordinal category variable (age group: 20–23, 23–29, >29 years), a positive linear trend was observed with Attitude Scale. Mean age values were 2.65±0.91 for <23 years, 3.06±0.95 for 23–29, and 3.15±0.96 for >29 years. Gender does not affect any of the scales (p=0.921), while those who were married had a statistically significant higher mean (3.24±0.80) than those who were single (2.74±0.95) in Attitude Scale (p=0.000). Living in a student residence or living with a roommate showed the minimum (2.32±0.75) and the maximum (3.25±0.89) Attitude Scale score, respectively (p=0.007).

In Attitude scale scores, the findings revealed a positive correlation between attitude and previous experience in e-learning. Mean score in participants with experience was 3.09±1.16 showing significant differences (p=0.32) from participants without experience (2.76±0.91) (Table 5).

Table 5

Differences between sociodemographics characteristics with attitude towards e-learning scale

Characteristics	ATel*
	Mean±SD	p
Age (years), rho	0.174	<0.001
Age groups (years)		0.000
20–23	2.65±0.91
23–29	3.06±0.95
>29	3.15±0.96
Sex		0.893
Male	2.78±1.06
Female	3.00±0.93
Marital status		0.000
Single	2.74±0.95
Married	3.24±0.80
Habitation		0.007
Family	2.84±0.97
Alone	2.60±0.86
Roommate	3.25±0.89
Student residence	2.32±0.75
Living with people at high risk		0.465
Yes	2.87±1.03
No	2.76±0.90
Learning deficit		0.104
Yes	3.09±1.16
No	2.76±0.91
Previous experience in e-learning		0.022
Yes	3.13±1.05
No	2.74±0.92

* Statistically significant correlations at significance level α=0.05, according to the nonparametric test of two independent Mann-Whitney U samples, Kruskal-Wallis H test for more than two independent samples and Spearman’s rho correlation coefficient.

DISCUSSION

The Greek version, ATel-GR, of the questionnaire ATel, which consists of 10 items, is user- friendly and easy to complete. The questionnaire focuses on measuring students’ attitudes towards the sudden and exclusive use of distance education due to the COVID-19 pandemic.

In this study, not only were the results formulated according to the Greek culture but also ensured the quality of the translation of the questionnaire from the original version¹⁵. Moreover, Guillasper et al.¹⁵ found that EFA revealed 9 items leading to one single factor. In our analysis, one factor was found with the difference that EFA appointed 10 items out of the 11 used (EBP attitude). According to the literature, changes can be present on a questionnaire because of the different culture of the country where it is applied^16,17.

Standardized Cronbach’s alpha coefficients for the Greek questionnaire were found to be similar to those reported by Guillasper et al.¹⁵ in the first validation study. The Greek version of the questionnaire showed as strong internal reliability (Cronbach’s alpha 0.901) as the original version of the tool.

In the present study, an important finding was that the age seems to be a determining factor for the attitude of nursing students towards distance education. Specifically, the students of the age group 23–29 years (3.09±0.95) and >29 years (3.15±0.96) maintained a positive attitude towards the implementation of distance education as they considered that the flexibility could be a great advantage for them. Recent studies gave prominence to flexibility as a major advantage for working students of all ages that is offered by distance learning compared to face-to-face learning^18-20. On the other hand, a recent study showed that the flexible nature of distance education compared to face-toface education burdens the mental health of nursing students as they felt anxious about their future progress²¹. Similarly, a study revealed the negative impact of the absence of social interaction among students and teachers because of distance learning as it was one of the restrictive measures that were established during the COVID-19 pandemic^22,23.

In addition, the present study highlighted that the marital status of the participants influences the attitude of nursing students towards distance education. Specifically, married participants (3.243±0.80) held a more positive attitude towards distance education than unmarried ones (2.74±0.95). This important finding was supported by a recent study that showed the flexibility that distance education offers to students’ family responsibilities. It was an advantage for the students to utilize the distance education in the space and time they wanted. However, the same study brought to light some difficulties that were generated due to the sudden and exclusive application of distance education in the wider field of the family²⁴. Furthermore, a recent study in Albania found that restrictive measures had a significant impact on depression levels of both students and their families during the period of COVID-19 pandemic^25,26.

Further, the present study stresses the importance of prior experience in distance education for students’ attitudes. In particular, participants with previous experience (3.09±1.16) in comparison to participants with no previous experience (2.76±0.91) in distance education had a more positive attitude. According to a recent study, students with no previous experience (31%) had to face preferences in the sudden transition of distance education from face-to-face education due to the COVID-19 pandemic¹⁸. Similarly, a multicenter study conducted in three European countries revealed that 59.1% of participating nursing students’ mental health deteriorated due to the implementation of restrictive measures imposed during the COVID-19 pandemic, including the sudden implementation of distance education²⁶.

As observed in the present study and in some other recent studies, nursing students held a positive attitude towards distance education^7,15,27. It is noteworthy, that this questionnaire examined the attitude of nursing students towards the sudden implementation of distance education during the COVID-19 pandemic. This tool could be helpful in nursing education research in order to avoid the negative consequences of sudden future changes as that of the COVID-19 pandemic. On the other hand, this questionnaire would be useful for the science of Psychology as it can measure the negative emotions of students due to distance education as a result to abandon their daily habits. Finally, future research could study the remedy to weakness from the exclusive use of distance education during the pandemic.

CONCLUSIONS

The Greek version of the questionnaire appears to be a reliable and valid tool, being quick and easy to complete. This instrument may become a useful tool in future research investigating the attitude of nursing students towards e-learning and assessing their specific needs. It is evident that this study provides a modern handy tool bridging this knowledge gap and supplying an important resource for researchers who might use it with the aim of exploring this field in the future.