Nurses’ thoughts on the metaverse and future time perspectives: a cross-sectional study

doi:10.21203/rs.3.rs-3573001/v1

Download PDF

Research Article

Nurses’ thoughts on the metaverse and future time perspectives: a cross-sectional study

https://doi.org/10.21203/rs.3.rs-3573001/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

Background

The metaverse is a new and developing technology in the field of healthcare. The future perception explains time as a physical phenomenon rather than a physical one. This study aims to determine nurses' thoughts and future perceptions of the metaverse.

Methods

A cross-sectional descriptive design was used in a hospital in Turkey with working nurses from September to November 2023. Face-to-face interviews were conducted with 357 nurses who were chosen using the convenience sampling method. The Personal Identification Form, Metaverse Scale (MS) and Future Time Perspective Scale (FTPS) were used to collect data. The Statistical Package for Social Sciences (SPSS) for Windows 25.0 programme was used to analyse the data.

Results

The findings revealed that 81.6% of nurses believed that they could provide patient education using the metaverse in the future, whereas 46% believed that they could do virtual nursing. The nurses received an average FTPS and MS score of 3.45 (SD = 0.37) and 3.74 (SD = 0.56), respectively. Future time perception and metaverse knowledge, attitude and awareness were found to have a weak, positive relationship (r = 0.157, p = 0.002). A weak, positive relationship was also found between internet use duration and MS (r = 0.169, p = 0.001).

Conclusions

Our research emphasises the significance of the metaverse and future time perception. Our findings can help in the development new metaverse platforms for nurses, as well as nursing academics, hospital administrators and technology companies.

The term ‘metaverse’ first appeared in Stephenson’s science fiction novel ‘Snow Crash’, which was released in 1992. In the novel, the metaverse is a parallel universe made up of computer graphics that users can access via glasses and headphones. Users interact with the metaverse via avatars that are linked to customisable digital bodies [1]. The metaverse is defined as a decentralised, three-dimensional virtual reality environment that serves as the internet's next generation [2]. However, there is a lack of agreement among authors in the literature regarding the definition of the metaverse, but recent publications have reported that the metaverse differs from augmented reality and virtual reality (VR) [3].

The perspective of future time (FTP) is concerned with the perception of time rather than the actual physical time recorded by a calendar or clock. The time frame that individuals consider when making decisions is defined by the temporal context (i.e. how much people plan for the future), the clarity of people's perceptions of their future needs and the extent to which the present time is connected to the past and future [4]. A strong future time perspective can include a focus on long-term goals, professional development plans and a desire for continuous growth and learning.

Intentions influence attitude towards behaviour, and intentions cause differences in behaviour, according to the theory of planned behaviour [5]. According to Zimbardo and Boyd[6], the time perspective (TP) theory has a widespread and powerful influence on many human behaviours. However, the time factor influences people's interpretation of various actions to create continuity [7]. With the advent of a new technology, such as the metaverse, in the field of nursing, there may be a relationship between the metaverse knowledge, attitude and awareness of nurses regarding their future use of this technology; thus, the need for this research arises.

The emergence of the concept of metaverse is expected to increase research and implementation of VR technology in nursing, as well as the connections between different disciplines in this field [8]. Patients, for example, can access 12-lead electrocardiograms, blood pressure and pulse monitors and pulse oximetry results in the metaverse by integrating with existing telehealth services [9]. Improved virtual care models for chronic conditions, such as hypertension, adult diabetes, and morbid obesity that are ineffective and costly to manage with traditional care delivery models, may offer advanced interactive options in a future medical metaverse [10].

There have been few studies on the use of FTP in nursing field. It has been reported in studies with nursing students that there is a relationship between the students' perspective of future time and their career maturity [11] and professional values [12]. However, there are studies in the literature that show a link between FTP and technological behaviours. Miceli et al [13] found that students' TP was a strong predictor of Facebook addiction in a study with undergraduate students. Excessive use of social media was found to be related to future time perspective in a study of adolescents [14]. According to Przepiorka and Blachnio [14], future orientation is a negative predictor of internet and Facebook addiction. According to Lukavska [15], more game time was associated with a lower level of future time perspective.

Nurses are expected to use future-world technological advancements (e.g. artificial intelligence and robotics) in their nursing practices and determine the stage at which these advancements should be applied in their practices [16]. However, there is a scarcity of studies in literature that include nurses' perpectives on metaverse technology. Similarly, a recent scoping review [2] discovered that many countries do not explicitly examine metaverse technology and that research in this area is required in various countries. There are also few studies in literature that explains the relationship between nurses' perspective of the future and their knowledge, attitude and awareness of the metaverse.

The goal of this study is to determine the relationship between nurses' perspectives of future time and their knowledge, attitude and awareness of the metaverse, as well as the factors influencing this relationship. The research questions are as follows:

Research Question 1

Are nurses' future time perspectives and Metaverse Scale scores influenced by their demographic characteristics?

Research Question 2

Is there a link between nurses' perspective of the future and their knowledge, attitude and awareness of the metaverse?

This study was descriptive and cross-sectional in nature. This study was reported using the STROBE checklist [17].

Participants

The study's universe included 750 nurses who worked in the surgical and internal clinics of a Medical Faculty Hospital in western Turkey. The OpenEpi Info Statcalc™ software was used to calculate the minimum sample size required for inclusion in the study, which was 255 based on a 95% confidence interval and a 5% error rate. Because they filled out the data incorrectly, 17 nurses were excluded from the study. The convenience sampling method was used to select the study's sample. The study enlisted the participation of 374 nurses who met the inclusion criteria.

The following were the inclusion criteria: (a) voluntarily agreeing to participate in the study, (b) holding a nursing title and (c) being present in the hospital during data collection. Nurses working in outpatient clinics, administrative unit and operating rooms were excluded as were nurses who were unable to answer questions or complete the survey due to health issues.

Data collection

After obtaining ethical approval, the researcher collected data for the study using face-to-face and pencil-and-paper techniques from September to November 2023. The researcher paid visits to the clinics at regular intervals. Before taking part in the study, the nurses were reminded that their participation was entirely voluntary and that the confidentiality of their data was stressed. The nurses were given the surveys after explaining the purpose of the study and obtaining informed consent. The surveys take approximately 15–20 min to complete.

Data collection tools

The Personal Information Form, Metaverse Scale (MS) and Future Time Perspective Scale (FTPS) were used to collect data for this study.

The Personal Information Form

The researcher's Personal Information Form was used to collect data for this study, which included 11 questions. The form's content validity index (CVI) was assessed by five nursing faculty members who were experts in the field. The scope validity was assessed using a 4-point Likert scale questionnaire, with responses ranging from 4 = very valid to 1 = very illogical for each question. The CVI was calculated to be 0.91, indicating that a value of 0.90 or higher indicates good content validity [18].

Metaverse Scale

The goal of this study was to use the MS to determine nurses' knowledge, attitude and awareness of the metaverse. MS is intended for individuals, and Süleymanoğulları et al [19] investigated its validity and reliability. The scale has 15 items and four subdimensions in total. The subdimensions of the scale are technology (items 1-2-3-4-5-10-13), digitalisation (items 9-11-12), social (items 14–15) and lifestyle (6-7-8). The Cronbach's α value of the scale was 0.813 in this study of Süleymanoğulları et al [19], but it was 0.723 in this study, which is acceptable and shows validity [20]. The items in the scale are in a 5-point Likert scale, with participation levels ranging from 1 = definitely disagree to 5 = definitely agree. Sub-scale scores are calculated by dividing the relevant scores' scores by the number of scores. The excess of scores obtained from the scale' sub-scales indicates that the participant's ownership of the feature measured by the sub-scale has increased. The level of knowledge, attitude and awareness of participants related to the metaverse increases as the scale scores increase [19].

Future Time Perspective Scale

The Future Time Perspective Scale (FTPS) was used to assess nurses' future time perspective. Husman and Shell [21] developed the scale, which was adapted into Turkish, and Avcı and Erden (2009) conducted a validity and reliability study. The Cronbach's α value of the scale in Avcı and Erden's [22] study was 0.78, and it was 0.898 in this study, which is acceptable and demonstrates validity [20]. There are 27 items on the scale and four subdimensions. Connectedness (items 1, 5, 7, 8, 12, 13, 17, 19, 21, 23, 25 and 27), value (2, 6, 9, 14, 15, 18 and 22), speed (11, 16 and 26) and extension are the subdimensions (3, 4, 10, 20 and 24). Additionally, 12 of the scale's items are scored by reversing them. These are the following numbers: 1, 7, 8, 11, 13, 15, 16, 17, 23, 25, 26 and 27. The items in the scale are 5-point Likert type, and the degree of participation is rated from 1 = definitely disagree to 5 = definitely agree. All subdimensions yielded scores ranging from 1 to 5. The sub-scales scores are calculated by dividing the degree of the relevant scores by the number of scores. An excess in the possession of the attribute measured by the subdimension is indicated by an excess of scores obtained from the scale's subdimensions [21, 22].

Data analysis

The data collected in the study were analysed using the Statistical Package for Social Sciences (SPSS) for Windows 25.0 software. Descriptive statistical methods were used to evaluated the data (number, percentage, minimum–maximum values, mean and standard deviation). The data's normality was examined. A Q–Q plot can be used to assesss normality [23]. Furthermore, data with a normal distribution must have skewness and kurtosis values within ± 3 [24].

An independent t test was used to compare numerical data in normally distributed data when comparing two independent groups, and one-way analysis of variance was used when comparing more than two independent groups. To test the relationship between numerical variables, Pearson correlation was used. The correlation coefficient's was calculated as follows: 0.00–0.10 (negligible correlation), 0.10–0.39 (weak correlation), 0.40–0.69 (moderate correlation), 0.70–0.89 (strong correlation) and 0.90–1.00 (very strong correlation) [25].

Demographic characteristics

The average age of the nurses was 29.54 ± 6.53 year, their average professional experience was 7.09 ± 6.70 year, and their average daily internet usage was 4.98 ± 3.60 h.

It was discovered that 82.6% of the nurses in the study were female, 54.3% held a bachelor's degree, and 38% held a graduate degree. It was discovered that nurses use Instagram the most (92.5%) and Facebook the least (38.8%). Of the nurses who took part in the study, 77.8% had heard the term ‘metaverse’ before, 71.4% understood what it meant, 81.6% believe that patient education can be given in metaverse in the future, and 46% believe that virtual nursing can be done in metaverse in the future. It was determined that he believed (Table 1).

Table 1

Comparison of FTPS and Metaverse Scale scores' mean values according to the sociodemographic characteristics of nurses (N = 374)
		MS		FTPS
Variables	n (%)	Mean ± SD	Test and p	Mean ± SD	Test and p
Gender
Female	309 (82.6)	26.51 ± 3.71	t = − 0.772 p = 0.440	3.45 ± 0.38	t = 0.339 p = 0.735
Male	65 (17.4)	3.73 ± 0.8	t = − 0.772 p = 0.440	3.44 ± 0.39	t = 0.339 p = 0.735
Educational level
High school	29 (7.8)	3.61 ± 0.78	t = 1.927 p = 0.382	3.46 ± 0.34	F = 1.002 p = 0.368
Bachelor's degree	203 (54.3)	3.74 ± 0.57		3.43 ± 0.37
Master's degree	142 (38.0)	3.78 ± 0.51		3.48 ± 0.4
Usage of Facebook
Yes	145 (38.8)	3.73 ± 0.61	t = − 0.113 p = 0.910	3.43 ± 0.34	t = − 0.988 p = 0.324
No	229 (61.2)	3.75 ± 0.54	t = − 0.113 p = 0.910	3.47 ± 0.4	t = − 0.988 p = 0.324
Usage of Instagram
Yes	346 (92.5)	3.74 ± 0.57	t = − 0.322 p = 0.747	3.44 ± 0.37	t = − 1.781 p = 0.076
No	28 (7.5)	3.78 ± 0.46	t = − 0.322 p = 0.747	3.57 ± 0.41	t = − 1.781 p = 0.076
Usage of Twitter
Yes	218 (58.3)	3.77 ± 0.58	t = − 1.511 p = 0.131	3.49 ± 0.38	t = 2.424
No	156 (41.7)	3.71 ± 0.54	t = − 1.511 p = 0.131	3.39 ± 0 .38	p = 0.016
Usage of LinkedIn
Yes	156 (41.7)	3.82 ± 0.46	t = − 2.092 p = 0.036	3.55 ± 0.37	t = 4.441 p = 0.000
No	218 (58.3)	3.69 ± 0.63	t = − 2.092 p = 0.036	3.38 ± 0.37	t = 4.441 p = 0.000
Have you heard the term ‘metaverse’ before?
Yes	291 (77.8)	3.80 ± 0.52	t = − 3.598 p = 0.000	3.47 ± 0.35	t = 1.957 p = 0.051
No	83 (22.2)	3.55 ± 0.68	t = − 3.598 p = 0.000	3.38 ± 0.45	t = 1.957 p = 0.051
Do you know what the metaverse is?
Yes	267 (71.4)	3.82 ± 0.52	t = − 4.111 p = 0.000	3.47 ± 0.35	t = 1.728 p = 0.085
No	107 (28.6)	3.56 ± 0.64	t = − 4.111 p = 0.000	3.4 ± 0.44	t = 1.728 p = 0.085
In the future, could patient education be provided through the Metaverse?
Yes	305 (81.6)	3.82 ± 0.52	t = − 5.397 p = 0.000	3.48 ± 0.38	t = 3.545 p = 0.000
No	69 (18.4)	3.4 ± 0.63	t = − 5.397 p = 0.000	3.31 ± 0.34	t = 3.545 p = 0.000
In the future, is it possible to perform virtual nursing using Metaverse?
Yes	172 (46.0)	3.85 ± 0.6	t = − 3.817 p = 0.000	3.48 ± 0.40	t = 1.630 p = 0.104
No	202 (54.0)	3.65 ± 0.52	t = − 3.817 p = 0.000	3.42 ± 0.36	t = 1.630 p = 0.104
Note. FTPS, Future Time Perspective Scale; MS, Metaverse Scale; SD, standard deviation. Statistical significance is highlighted in bold.

FTPS and MS total and subdimension scale mean scores

The average FTPS score for nurses was found to be 3.45 ± 0.37. The nurses received the highest score in the value subdimension (3.91 ± 0.64) and the lowest score in the speed subdimension (2.94 ± 0.67). Meanwhile, the average MS nurses score was 3.74 ± 0.56. The nurses scored highest in the lifestyle (3.96 ± 0.70) subdimension and lowest score in the digitalisation (3.49 ± 0.81) subdimension (Table 2).

Table 2

Average scores of FTPS and MS total and subdimension scales (N = 374)
Scales and subdimensions	Min	Max	\(\stackrel{-}{\varvec{X}}\) ± SD
FTPS total score	1.00	5.00	3.45 ± 0.37
Connectedness	1.00	5.00	3.91 ± 0.64
Value	1.00	5.00	2.94 ± 0.67
Speed	1.00	5.00	3.44 ± 0.96
Extension	1.00	5.00	3.04 ± 0.61
MS total score	1.00	5.00	3.74 ± 0.56
Technology	1.00	5.00	3.77 ± 0.58
Digitalisation	1.00	5.00	3.49 ± 0.81
Social	1.00	5.00	3.69 ± 0.93
Lifestyle	1.00	5.00	3.96 ± 0.70
Note. \(\stackrel{-}{X}\), mean; SD, standard deviation.

Comparison of FTPS and Metaverse Scale Scores' averages according to sociodemographic characteristics of nurses

In our study, we discovered that nurses who use Twitter scored higher on the FTPS scale. Nurses who used LinkedIn had higher scores on both the MS and FTPS scales (p < 0.05, Table 1).

The study discovered that nurses who had previously heard of the metaverse and knew what it was and who believed that patient education and virtual nursing could be performed in the metaverse scored higher on the MS. Furthermore, it was found that nurses who believe that virtual nursing can be performed in the future have higher FTPS scores (p < 0.05, Table 1).

Correlation analysis

There was a weak negative correlation found between the value subdimension scores and the nurses' age and professional experience (r = − 0.167, p < 0.01; r = − 0.165, p < 0.01, respectively). The daily internet usage of nurses was found to have a weak positive correlation with the value subdimension scores (r = 0.104, p < 0.05), the breadth subdimension scores (r = 0.101, p < 0.05), the Metaverse Scale scores (r = 0.169, p < 0.01), the technology subdimension scores (r = 0.151, p < 0.01), the digitalisation subdimension scores (r = 0.166, p < 0.01) and the lifestyle subdimension scores (r = 0.114, p < 0.05; Table 3).

Table 3

Correlation between the scales and subdimensions with continuous variables (N = 374)
Scales and subdimensions	Age	Years of professional experience	Daily internet usage time
	r
FTPS total score	−0.089	−0.088	−0.005
Connectedness	−0.034	−0.044	−0.033
Value	−0.167^**	−0.165^**	0.104^*
Speed	0.073	0.091	−0.062
Extension	−0.019	−0.015	0.101^*
MS total score	−0.074	−0.087	0.169^**
Technology	−0.082	−0.094	0.151^**
Digitalisation	−0.085	−0.093	0.166^**
Social	0.026	0.019	0.076
Lifestyle	−0.060	−0.074	0.114^*
Note. Pearson correlation coefficient (r).
^*p < 0.05.
^**p < 0.01.

A positive, weak significant correlation was discovered between nurses' FTPS scores and MS scores (r = 0.157, p < 0.01). A positive, weak significant correlation was found between FTPS total scores and the MS subdimensions of lifestyle (r = 0.180), technology (r = 0.143) and digitalisation (r = 0.110, p < 0.05). Positive, weak significant correlations were found between MS total scores and the FTPS subdimensions of inclusiveness (r = 0.183) and value (r = 0.181), and a negative, weak significant correlation was found between MS total scores and the FTPS subdimension of speed (r = 0.104, p < 0.05).

Table 4

Results of correlation analysis between scales and subdimensions (N = 374)
Scales and subdimensions	1	2	3	4	5	6	7	8	9	10
	R
1. FTPS total score	1
2. Connectedness	0.794^**	1
3. Value	0.507^**	−0.027	1
4. Speed	0.470^**	0.531^**	0.177^**	1
5. Extension	0.117^*	0.316^**	0.378^**	0.433^**	1
6. MS total score	0.157^**	0.063	0.181^**	−0.104^*	0.183^**	1
7. Technology	0.143^**	0.074	0.148^**	−0.054	0.113^*	0.932^**	1
8. Digitalisation	0.110^*	−0.010	0.231^**	0.165^**	0.188^**	0.789^**	0.673^**	1
9. Social	0.049	−0.015	0.044	−0.052	0.179^**	0.480^**	0.281^**	0.148^**	1
10. Lifestyle	0.180^**	0.131^*	0.129^*	−0.072	0.139^**	0.852^**	0.757^**	0.562^**	0.321^**	1
^*p < 0.05.
^**p < 0.01.

Demographic characteristics

The purpose of this study was to determine nurse' future time perspective and metaverse-related views. According to statistical research, 31% of adults in the United States have heard of the metaverse but do not know much about it [26], and 52% of individuals in 29 different countries have knowledge of the metaverse [27]. Although the metaverse is a relatively new concept in the healthcare sector [28], the findings of this study show that the majority of nurses (77.8%) have heard of it and know what it is (71.4%). As a result, it can be said that unlike the general public, nurses are more familiar with the term ‘metaverse’.

Our research found that nearly half of the nurses responded positively to the question of whether virtual nursing can be done using the metaverse. A study conducted with future nurses' nursing students revealed that the metaverse can help the students' clinical nursing practices [29]. There are studies in the literature that show virtual nursing benefits nurses [30–32]. Furthermore, more than half of the nurses in our study said yes to the question of whether the metaverse can be used for patient education. When the literature is reviewed, it is reported that the metaverse can be used in nursing education [33], medical students monitoring of patients' health status at home [34], lung cancer surgery training for doctors[35] and education of various university students [36]. As a result, the metaverse can be used for patient education as well. In future studies, we plan to investigate the necessity of virtual nursing being involved in nursing care at what points in the metaverse.

5.2. Factors influencing the knowledge, attitude, awareness and future-oriented perspectives of nurses in the metaverse

In 2021, Facebook changed its name to ‘Meta’ and had a large impact [37], but in our study, we discovered that the average MS scores of nurses who used the LinkedIn social network were higher. This result can be explained by the fact that health-related information is shared more frequently on LinkedIn than on other social networks. Furthermore, it was discovered that nurses who had previously heard of or known about the metaverse had higher average MS scores. Studies that examined the metaverse knowledge levels of physical education and sports teacher candidates found that students who knew the term ‘metaverse’ had higher Metaverse Scale scores [38]. As a result, we believe that by organising metaverse training for nurses on what metaverse is and how to use it before using the metaverse platforms prepared for them, nurses' knowledge, attitude and awareness of the metaverse can be increased.

The metaverse should be viewed as an environment for long-term education, free of time and space contraints, with the potential to turn imagination into reality through the convergence of artificial intelligence-supported advanced technologies [3]. In this configuration, it is also believed that patient education can be transferred to a virtual environment. Our findings also revealed that the MS scores obtained by nurses who believe that patient education and virtual nursing can be performed in the metaverse are an expected outcome.

The FTPS scores obtained by nurses using Twitter and LinkedIn were found to be higher. Furthermore, those who believe that patient education can be provided in the future using the metaverse recieved higher FTPS scores.

Correlation analyses

The FTPS value concept can be defined as making efforts for future goals now.[4] According to Weikamp and Göritz [39] as perceived duration increased in terms of age and profession, so did the perspective of the future in a professional context. According to the literature, the value subdimension of FTPS was negatively weakly related to nurses' age and professional experience duration. Futhermore, the value subdimension of FTPS had a negative, weak relationship with MS, suggesting that pilot applications be carried out on younger and less experienced nurses in metaverse platforms that are under consideration for improvement. In a study that examined university students' metaverse-oriented thoughts, Özdemir et al [40] reported that there was a weak, positive relationship between average daily social media usage time and technology subdimension scores.This findings indicates that as nurses' internet usage increases, so will thier knowledge, attitude and awareness of the metaverse.

The study's findings revealed a weak, positive correlation between FTPS and MS, implying. that as nurses' perspectives of future time improve, they may become more open to the idea of using metaverse in nursing care, viewing it as a valuable technology for improving future patient care. The strongest correlation was found between the FTPS dimension of ‘extension’ and MS, which is defined as the perspective of existing goals being more visible and important to the individual [4]. Nurses with higher extension scores are more likely to be involved in the metaverse. Finally, the study discovered the strongest link between the ‘lifestyle’ dimension of MS and FTPS. This finding may imply that as nurses' perspectives of future time improve, so will their lifestyle scores, which include activities, such as participating in metaverse-based activities, positively impacting their health and virtual communication.

Limitations

There are several limitations to this study. First, it was conducted in a Turkey hospital, so the results may be limited in their applicability to other regions of Turkey and other countries. Second, the study's cross-sectional design allows for the examination of relationships between variables but not of cause-and-effect relationships. More complex longitudinal designs may be used in future research.

According to our findings, there is a weak positive relationship between nurses' future TPs and their attitude towards the metaverse. In general, the positive correlation between future TP and attitude towards new technologies, such as the metaverse, suggests that a person's future outlook shapes their attitude and beliefs towards, such technologies. More than half of the nurses had heard of or were familiar with the metaverse, and they believe that it could be used for future patient education and virtual nursing care. As a result, we believe that metaverse platforms could be used in clinical settings in the future for issues, such as nursing care and patient education.

Ethics approval and consent to participate

The study was approved by the Non-Interventional Clinical Research Ethics Committee of XXXXXX University (decision no: 639; research no: 619; approval no: E-93802310-050.01.04). In the research, ethical principles were applied in accordance with the Helsinki Declaration and the Belmont Report. Furthermore, in accordance with Türkiye's ‘Personal Data Protection Law’, the personal data of the nurses who participated in the study were kept confidential. Before participating in the study, the nurses signed an Informed Consent Form that included information about the study's purpose, data use, confidentiality and the fact that they could leave the study at any time. Permission to use the scales in the study was obtained via e-mail from the authors of the scales.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

The authors received no financial support from any funding agency in the public, commercial or not-for-profit sectors.

Authors' contributions

Eda Ergin was responsible for the conceptualization, formal Analysis, methodology, resources, writing – original draft preparation, writing – review & editing; Turgay Yalcinkaya was responsible for the conceptualization, formal analysis, investigation, methodology, resources, writing – original draft preparation, writing – review & editing; Sebnem Cinar Yucel was responsible for the conceptualization, data curation, methodology, resources, writing – original draft preparation, writing – review & editing, supervision.

All authors approved the final version for submission. We confirm that all authors meet the authorship criteria and that all authors are in agreement with the content of the article.

Acknowledgements

We thank all the nurses who participated in the study. We are grateful to Ege University Planning and Monitoring Coordination of Organizational Development and Directorate of Library and Documentation for their support in editing and proofreading service of this study.

Orcid

Eda Ergin https://orcid.org/0000-0002-3732-5402

Turgay Yalcinkaya https://orcid.org/0000-0002-0115-295X

Sebnem Cinar Yucel https://orcid.org/0000-0002-8904-7395

Mystakidis S. Metaverse. Encyclopedia. 2022;2:486–97.
Garavand A, Aslani N. Metaverse phenomenon and its impact on health: A scoping review. Informatics Med Unlocked. 2022;32 July:101029.
Park SM, Kim YG. A Metaverse: Taxonomy, Components, Applications, and Open Challenges. IEEE Access. 2022;10:4209–51.
Husman J, Shell DF. Beliefs and perceptions about the future: A measurement of future time perspective. Learn Individ Differ. 2008;18:166–75.
Ajzen I. The theory of planned behavior. Organ Behav Hum Decis Process. 1991;50:179–211.
Zimbardo PG, Boyd JN. Putting time in perspective: A valid, reliable individual-differences metric. Time Perspect Theory; Rev Res Appl Essays Honor Philip G Zimbardo. 1999;77:17–55.
Van Beek W, Berghuis H, Kerkhof ad, Beekman A. Time perspective, personality and psychopathology: Zimbardo’s time perspective inventory in psychiatry. Time Soc. 2011;20:364–74.
Zhao J, Lu Y, Zhou F, Mao R, Fei F. Systematic Bibliometric Analysis of Research Hotspots and Trends on the Application of Virtual Reality in Nursing. Front Public Heal. 2022;10 May:1–11.
Skalidis I, Muller O, Fournier S. The Metaverse in Cardiovascular Medicine: Applications, Challenges and the role of Non-Fungible Tokens. Can J Cardiol. 2022;:1–2.
Chapman JR, Wang JC, Wiechert K. Into the Spine Metaverse: Reflections on a future Metaspine (Uni-)verse. Glob Spine J. 2022;12:545–7.
Cheng C, Yang L, Chen Y, Zou H, Su Y, Fan X. Attributions, future time perspective and career maturity in nursing undergraduates: Correlational study design. BMC Med Educ. 2016;16:1–8.
Dil S, Öztürk PÇ, Yıldırım T. How nursing students ’ futurism perceptions are affected by their individual values ? 2022;9:11–8.
Miceli S, Cardaci M, Scrima F, Caci B. Time perspective and Facebook addiction: The moderating role of neuroticism. Curr Psychol. 2022;41:8811–20.
Przepiorka A, Blachnio A. Time perspective in Internet and Facebook addiction. Comput Human Behav. 2016;60:13–8.
Lukavska K. Time perspective as a predictor of massive multiplayer online role-playing game playing. Cyberpsychology, Behav Soc Netw. 2012;15:50–4.
Pepito JA, Locsin R. Can nurses remain relevant in a technologically advanced future? Int J Nurs Sci. 2019;6:106–10.
von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The strengthening the reporting of observational studies in epidemiology (STROBE) statement: Guidelines for reporting observational studies. Int J Surg. 2014;12:1495–9.
Polit DF, Beck CT. Essentials of Nursing Research. 9th editio. Wolters Kluwer; 2018.
Süleymanoğulları M, Özdemir A, Bayraktar G, Vural M. Metaverse Ölçeği Geliştirme Çalışması. Anatolia Sport Res. 2022;1:47–58.
George D, Mallery P. IBM SPSS Statistics 26 Step by Step. 2019.
Husman J, Shell DF. Beliefs and perceptions about the future: A conceptualization and measurement of future time perspective. In: The XXVI International Congress of Psychology. Montreal, Canad; 1996.
Avcı S, Erden M. Gelecek Zaman Algısı Ölçeği’nin Türkçe Formunun Geçerlik ve Güvenirlik Çalışması. Çukurova Üniversitesi Eğitim Fakültesi Derg. 2009;3:1–12.
Chan YH. 101 - Data presenation. Singapore Med J. 2003;44:280–5.
Shao AT. Marketing Research: An Aidto Decision Making. Cincinnati - Ohio: South-Western/Thomson Learning; 2002.
Schober P, Schwarte LA. Correlation coefficients: Appropriate use and interpretation. Anesth Analg. 2018;126:1763–8.
Statista. Familiarity with the metaverse according to adults in the United States as of January 2022. 2022.
Ipsos. How the world sees the metaverse and extended reality, A 29-country Global Advisor survey. Global Version, Public. 2022; May:1–12.
Yang Y, Siau K, Xie W, Sun Y. Smart Health: Intelligent Healthcare Systems in the Metaverse, Artificial Intelligence, and Data Science Era. J Organ End User Comput. 2022;34:1–14.
Yang SY, Kang MK. Efficacy Testing of a Multi-Access Metaverse-Based Early Onset Schizophrenia Nursing Simulation Program: A Quasi-Experimental Study. Int J Environ Res Public Health. 2022;20.
Cloyd B, Thompson J. Virtual Care Nursing:: The Wave of the Future. Nurse Lead. 2020;18:147–50.
Bickmore TW, Pfeifer LM, Jack BW. Taking the time to care: Empowering low health literacy hospital patients with virtual nurse agents. Conf Hum Factors Comput Syst - Proc. 2009;:1265–74.
Hughes L, Petrella A, Phillips N, Taylor RM. Virtual care and the impact of COVID-19 on nursing: A single centre evaluation. J Adv Nurs. 2022;78:498–509.
Sezer H, Ergin E. Sanal Gerçeklikten Metaverse; Hemşirelik Eğitiminin Geleceğine Yönelik Öğrenci Deneyimleri. In: 2nd International & 8th National Nursing Education Congress. Aydın, Turkey; 2022.
Petrigna L, Musumeci G. The Metaverse: A New Challenge for the Healthcare System: A Scoping Review. J Funct Morphol Kinesiol. 2022;7.
Koo H. Training in lung cancer surgery through the metaverse, including extended reality, in the smart operating room of Seoul National University Bundang Hospital, Korea. J Educ Eval Health Prof. 2021;18:1–4.
Jovanovic A, Milosavljevic A. VoRtex Metaverse Platform for Gamified Collaborative Learning. Electronics. 2022;11:317.
Zeng Y, Zeng L, Zhang C, Cheng AS. The metaverse in cancer care: Applications and challenges. Asia-Pacific J Oncol Nurs. 2022;:100111.
Savaş BÇ, Karababa B, Turan M. Metaverse Bilgi Düzeyi: Beden Eğitimi ve Spor Öğretmeni Adayları Üzerine Bir İncelenme Metaverse. Uluslararası Egzersiz Psikolojisi Derg. 2022. https://doi.org/10.51538/intjourexerpsyc.1140511.
Weikamp JG, Göritz AS. How stable is occupational future time perspective over time? A six-wave study across 4 years. Work Aging Retire. 2015;1:369–81.
Özdemir A, Vural M, Süleymanoğulları M, Bayraktar G. What Do University Students Think About The Metaverse? J Educ Technol Online Learn. 2022;5:952–62.

No competing interests reported.

Download PDF

Editorial decision: Revision requested
08 Nov, 2023
Editor assigned by journal
08 Nov, 2023
Submission checks completed at journal
07 Nov, 2023
First submitted to journal
07 Nov, 2023

You are reading this latest preprint version

Nurses’ thoughts on the metaverse and future time perspectives: a cross-sectional study

Status:

Version 1

Abstract

Background

Methods

Results

Conclusions

Introduction

Background

Methods

Participants

Data collection

Data collection tools

The Personal Information Form

Metaverse Scale

Future Time Perspective Scale

Data analysis

Results

Demographic characteristics

FTPS and MS total and subdimension scale mean scores

Comparison of FTPS and Metaverse Scale Scores' averages according to sociodemographic characteristics of nurses

Correlation analysis

Discussion

Demographic characteristics

Correlation analyses

Limitations

Conclusion

Declarations

References

Additional Declarations

Status:

Version 1