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Erschienen in:

Open Access 01.12.2024 | Research

Investigation of nursing students' addiction to digital game play and associated factors

verfasst von: Hasan Sağlam, Nuray Turan

Erschienen in: BMC Nursing | Ausgabe 1/2024

Abstract

Aims

It was conducted to investigate digital gaming addiction among nursing students and the associated factors of such addiction.

Methods

The descriptive and relationship-seeking study's universe included 1665 nursing students in three universities' nursing faculties and departments. The sample size was determined to be 774 based on a power analysis with a type I error rate of 0.05, a power of the test of 0.80 (α = 0.05, 1-β = 0.80), and an effect size of d = 0.10. Student Information Form, The Digital Game Addiction Scale (DGAS-7), and the Digital Game Playing Motivation Scale (DGPMS) were used to collect student information. Data analysis was performed using the Mann–Whitney U test, Kruskal–Wallis H test, Spearman correlation, and Binary Logistic Regression Model.

Results

It was found that 83.7% of the students were female, and the mean age and BMI were 20.03 ± 1.72 years and 21.98 ± 2.90 kg/m2, respectively. A statistically significant positive correlation was found between the students' Digital Game Addiction Scale and Digital Game Playing Motivation Scale Achievement and Energizing (r = 0.717), Curiosity and Social Acceptance (r = 0.612), and Uncertainty in Game Desire (r = -0.110) sub-dimensions mean scores (p < 0.001).

Conclusions

The relationship between nursing students' digital game addiction, game playing motivation, and several individual characteristics affecting digital games was found. The study's results call for further research to focus on developing and testing interventions that could effectively reduce gaming addiction while enhancing positive aspects of digital engagement among nursing students.
Hinweise

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Introduction

Due to technological advancements, urbanization, and decreased physical play areas, the current generation increasingly turns to indoor activities and digital gaming, utilizing computers, game consoles, and online games. The phenomenon of digital gaming addiction has evolved significantly across different generations. The Silent Generation and Baby Boomers experienced the early days of gaming with arcade games and rudimentary home consoles, where addiction was rare due to limited access. Gen X witnessed the advent of more advanced gaming systems like Atari and Nintendo, leading to increased engagement, though gaming addiction was still not widely recognized. Millennials grew up with the rapid expansion of digital technology and the internet, facing the first wave of widespread gaming addiction as games became more immersive and socially connected. Gen Z has been immersed in a digital world from birth, with higher instances of gaming addiction due to the rise of eSports, streaming platforms, and mobile gaming. Gen Alpha is growing up in an era of ubiquitous digital technology, with gaming integrated into early childhood experiences, making the long-term effects of early exposure to digital gaming and potential addiction an ongoing concern. Over time, digital gaming addiction has progressed from a rare phenomenon to a widespread issue, particularly affecting Millennials and Gen Z, with implications for future generations like Gen Alpha [1]. This shift towards virtual environments is prevalent and expanding among children and adolescents, with a significant daily increase in digital game players. The popularity of these games continues to grow even among younger children [14]. The uncontrolled urge to engage in digital gaming can lead to significant changes in social life, emotions, and thoughts, potentially culminating in gaming addiction [57]. International studies have shown that the incidence of gaming addiction varies between 2 and 15% [3, 8], and according to the American Medical Association, 90% of adolescents engage in digital gaming, with 15% demonstrating addictive behaviors [9].
Digital games offer a virtual realm where users can fulfill their fantasies, creating a world that doesn’t exist in reality [3, 6, 10]. Within university settings, where interpersonal interactions and communication are emphasized, young adults frequently engage in digital gaming to connect with friends [8, 10, 11]. Research by Shuvo and Biswas has indicated a significant association between the time spent on screen-based devices and playing digital games with overweight and obesity among university students [12]. Moreover, findings by Polat and Topal suggest that digital game addiction is significantly predicted by factors such as gender, academic achievement, and hours spent gaming on computers and smartphones each week rather than by body mass index or types of players [13].
The research on digital gaming addiction among nursing students is essential due to its impact on the cognitive and emotional skills critical for patient care, such as attention, decision-making, and stress management. This focus is crucial in nursing education to prepare students for the demanding healthcare environment. These consequences are not exclusive to nursing students; however, they are particularly significant for this group due to their direct implications on patient care and safety. While other university students might experience reduced academic performance and social interaction from gaming addiction, these issues do not typically present immediate life-or-death consequences. In contrast, in nursing, digital addiction directly impacts public health and safety. This study underscores the need for proactive measures in nursing education to equip students with the skills to tackle digital addiction effectively, enhancing patient safety and overall care quality. This approach benefits the nursing professionals and the broader healthcare system, establishing the study's relevance and necessity in training nurses to handle complex health challenges, including addictions, in their careers. The central research questions were as follows:
1)
What are the levels of digital game addiction and digital game playing motivation among nursing students?
 
2)
What factors affect nursing students' digital game addiction and digital game playing motivation?
 

Materials and methods

Study design and participants

The study was designed to be descriptive and correlational, aiming to investigate the addiction of nursing students to digital gaming and associated factors. The research was conducted on a population of 1665 nursing students studying at nursing faculties and departments at two state universities and one foundation university in Istanbul during the 2020–2021 academic year. Using the G*Power 3.0.10 program, the sample size was determined to be 774 based on a power analysis with a type I error rate of 0.05, a power of the test of 0.80 (α = 0.05, 1-β = 0.80), and an effect size of d = 0.10 [9]. In this study, the sample comprised 774 nursing students. The criteria for sample selection were being a nursing student who was enrolled and actively attending classes at the time of the study, having no communication problems, playing computer or video games, and volunteering to participate in the study.

Measurements

The data were collected using the Nursing student information form, the Digital Game Addiction Scale (DGAS-7), and the Digital Game Playing Motivation Scale (DGPMS).

Nursing student information form

The questionnaire developed by the researchers on the relevant literature was based on factors such as the student's sex, age, age groups, marital status, class, body mass index (BMI), BMI classification, class, and digital gaming tool (smartphone, tablets, consoles) [3, 5, 8, 14].

The digital game addiction scale (DGAS-7)

Yalçın Irmak and Erdoğan [5] adapted the scale Lemmens et al. [15] created to identify problematic digital game playing behaviors in Turkish. The DGAS-7 is the short form of the DGAS-21 and consists of 7 subdimensions and 21 items. The DGAS-7 consists of 7 items in total. The scale consists of five-point Likert-type questions, ranging from 1 to 5, with overall scores between 7 and 35. Two formats, monothetic and polythetic, were preferred to determine whether an adolescent was addicted to gaming according to the DOBÖ. In the monothetic format, if the individual scores 3 (sometimes) and above 3 on all 7 items in the scale, he/she is considered risky, and according to another format, polythetic, if he/she scores 3 (sometimes) and above 3 on at least 4 of all items, he/she is considered a high-risk game addict [5]. An increase in score on the scale means that it reflects more severe levels of addiction to digital games and suggests worsening conditions in terms of gaming behavior. Higher scores on this scale indicate a higher likelihood of digital game addiction [5]. The Cronbach's alpha coefficient of the original scale was 0.920, while in the Turkish version and this study, the values were 0.730 and 0.823, respectively.

The digital game playing motivation scale (DGPMS)

The scale devised by Tekkurşun Demir and Hazar [16] to ascertain the motives for playing digital games consists of 19 items and 3 subdimensions. It comprises 3 subdimensions: Success and revival, curiosity and social acceptance, and uncertainty in willingness to play. On the five-point Likert-type scale, in the scoring of this scale, this part, including the 1st to 14th items, is scored directly, while the part between the 15th and 19th items is scored reversely. The lowest score that can be obtained from the DGPMS is 19, and the highest score is 95. The higher the score obtained from this scale, the greater an individual's motivation to play digital games, indicating that participants with high scores exhibit positive motivation. The Cronbach alpha coefficients are 0.96 for the Digital Gaming Play Motivation Scale, 0.70 for achievement and revitalization, 0.87 for curiosity and social acceptance, and 0.72 for uncertainty in-game requests [16]. In this study, Cronbach's alpha coefficient was 0.825 for achievement and revival, 0.926 for curiosity and social acceptance, and 0.909 for uncertainty in willingness to play.

Data collection

After providing institutional approval and ethical clearance, study data was collected using Google Forms. The Student Affairs departments at the participating nursing faculties were initially contacted via their institutional email addresses to facilitate the study distribution. Once the necessary permissions were obtained, the data collection forms link was provided to these offices.
Subsequently, the Student affairs offices emailed the data collection forms to nursing students in all academic years (first through fourth) using the student's official university email addresses. Throughout this process, care was taken to ensure that no identifying information such as names, student numbers, or any other personal identifiers was collected, maintaining the confidentiality and anonymity of all participants. The process was designed to emphasize the voluntary nature of participation, allowing students to opt-out at any time without repercussions.
Data collection forms were delivered online through three universities' nursing faculties and departments. The study details were presented on the first page of each form. Before commencing, students were required to click the “I approve” button if they agreed to participate. Completing the data collection forms took approximately 15 min.

Ethical approval

The study was approved by the Ethics Committee of Istanbul University-Cerrahpaşa, Social Sciences, and Humanities Research Ethics Committee (Date: 13.10.2020 Number: 70800) and conducted in accordance with the ethical standards laid down by the Declaration of Helsinki (1964) and all subsequent revisions.

Data analysis

The statistical analyses were performed using SPSS (IBM SPSS Statistics 24) software. Tables containing frequency distributions and descriptive statistics were used to interpret and explain the data obtained in the study. As a result of the Shapiro–Wilk test applied, p was found to be < 0.05, and it was determined that the data did not comply with normal distribution. Non-parametric methods were used for measurement values ​​that did not comply with normal distribution. The Mann‒Whitney U test was used to analyze two independent groups, while the Kruskal‒Wallis H test was used for three or more independent groups. When a significant difference was identified for three or more independent groups, the Bonferroni correction was applied to examine the variable values by comparing them in pairs. The Spearman correlation coefficient was utilized to investigate the relationship between the abnormally distributed data. We used a binary logistic regression model to determine the factors influencing the risk of digital game addiction. We assessed the outcomes at a 95% confidence interval using a significance level of p < 0.05.

Results

Characteristics of nursing students

Examining the students' characteristics, 83.7% (n = 648) were female, with a mean age of 20.03 ± 1.72 years. Additionally, 32.3% were 21 years or older, 99.2% (n = 768) were single, and their average BMI was 21.98 ± 2.90 kg/m2. Furthermore, 76.4% (n = 591) of the students were classified as having an average weight according to their BMI. A total of 34.1% (n = 264) of the nursing students were 1 year of study; all (n = 774) lived at home, and 94.8% (n = 734) preferred smartphones as a tool (Table 1).
Table 1
Distribution of findings associated with characteristics of nursing students (N = 774)
Variables
 
n
%
Sex
Female
648
83.7
Male
126
16.3
Average age
x̄ ± S.D. = 20.03 ± 1.72
Age groups
18 years and below
116
15.0
19 years
214
27.6
20 years old
194
25.1
21 years and older
250
32.3
Marital status
Married
6
0.8
Single
768
99.2
BMI average
x̄ ± SD = 21.98 ± 2.90 (kg/m2)
 
BMI classification
Underweight
68
8.8
Normal
591
76.4
Overweight
104
13.4
Obese
11
1.4
Class
1 year of study
264
34.1
2 year of study
204
26.4
3 year of study
172
22.2
4 year of study
134
17.3
Digital gaming tool
Tablet
35
4.5
Smartphone
734
94.8
Game console
5
0.7
SD Standart deviation

Levels of digital game addiction and digital game playing motivation among nursing students

The nursing students' mean total score on DGAS-7 was 12.65 ± 4.29 (min.-max: 7.0–35.0), and the mean total scores on the DGPMS subdimensions were 12.60 ± 4.51 (min.-max: 5.0–25.0) in achievement and revival, 23.63 ± 9.34 (min.-max: 9.0–45.0), and 15.25 ± 6.08 (min.-max: 5.0–25.0) uncertainty in-game requests (Table 2).
Table 2
Distribution of nursing students' scores on Digital Game Addiction and Digital Game Play Motivation Scale (N = 774)
Scales
 
Mean ± S.D
Median
Min.- Max
Digital Game Addiction
 
12.65 ± 4.29
12.0
7.0–35.0
 
Success and Revival
12.60 ± 4.51
12.0
5.0–25.0
Digital Game Play Motivation
Curiosity and Social Acceptance
23.63 ± 9.34
23.0
9.0–45.0
 
Uncertainty in Willingness to Play
15.25 ± 6.08
15.0
5.0–25.0
SD Standart Deviation, Min. Minimum, Max. Maksimum
The DGAS-7 has a possible score range from 7 to 35, with higher scores indicating greater levels of game addiction. A mean score of 12.65 suggests a relatively low level of game addiction among nursing students.
Table 3 shows a positive and significant relationship between the DGAS-7 score and the subdimensions of the DGPMS score and between the scores and the mean scores for success and revival (r = 717; p < 0.001), curiosity, and social acceptance (r = 0.612; p < 0.05). There was no correlation between the DGAS-7 score and the uncertainty in the willingness to play (r = -0.110; p = 0.002) of the DGPMS (p > 0.05).
Table 3
Distribution of the relationship between Digital Game Addiction and Digital Game Playing Motivation Scale scores of nursing students (N = 774)
Correlation
Digital Game Addiction
 
r
p
Digital Game Playing Motivation
 Success and Revival
0.717
0.000*
 Curiosity and Social Acceptance
0.612
0.000*
 Uncertainty in Willingness to Play
-0.110
0.002*
*Spearman's correlation coefficient was used to examine the relationship between two quantitative data that do not have a normal distribution. r: Pearson Correlation Analysis. *p < 0.05

Associated factors of nursing students' digital game addiction and digital game playing motivation

As shown in Table 4, the mean DGAS-7 scores of the male nursing students were significantly greater than those of the female nurses (Z = -7.188; p < 0.001).
Table 4
Comparison of Digital Game Addiction and Digital Game Playing Motivation Scale according to characteristics of students (N = 774)
Variable
n
Digital Game Addiction
Digital Game Playing Motivation
Success and Revival
Curiosity and Social Acceptance
Uncertainty in Willingness to Play
Mean ± S.D
Median
Mean ± S.D
Median
Mean ± S.D
Median
Mean ± S.D
Median
Sex
 Female
648
12.14 ± 4.05
11.0
12.17 ± 4.36
12.0
22.73 ± 9.07
22.0
15.15 ± 6.24
15.0
 Male
126
15.25 ± 4.55
15.0
14.83 ± 4.65
15.0
28.24 ± 9.38
29.0
15.73 ± 5.23
16.0
Statistical analysisa
Z = -7.188
Z = -5.785
Z = -5.852
Z = -0.925
Probability
p < 0.001
p < 0.001
p < 0.001
p = 0.355
Age groups
 18 years and below (1)
116
11.60 ± 3.80
11.0
11.28 ± 3.90
11.0
20.93 ± 8.62
19.5
14.59 ± 5.74
14.0
 19 years (2)
214
12.84 ± 4.44
12.0
12.58 ± 4.54
12.0
23.47 ± 9.39
22.0
14.47 ± 6.14
14.0
 20 years old (3)
194
12.36 ± 4.38
11.0
12.23 ± 4.51
11.0
23.29 ± 9.10
22.0
16.09 ± 6.07
16.0
 21 years and older (4)
250
13.22 ± 4.21
13.0
13.52 ± 4.59
14.0
25.28 ± 9.54
26.0
15.58 ± 6.12
15.0
Statistical analysis
χ2 = 15.374
χ2 = 20.663
χ2 = 17.183
χ2 = 9.778
Probability, Difference
p = 0.002 [1.3–4]
p < 0.001 [1.3–4]
p = 0.001 [1-4]
p = 0.021 [1.2–3]
Marital status
 Married
6
9.00 ± 1.55
9.0
11.00 ± 5.97
10.0
22.83 ± 12.40
24.5
13.50 ± 7.69
14.5
 Single
768
12.69 ± 4.29
12.0
12.61 ± 4.50
12.0
23.63 ± 9.32
23.0
15.26 ± 6.07
15.0
Statistical analysis
Z = -2.325
Z = -1.062
Z = -0.338
Z = -0.651
Probability
p = 0.020
p = 0.288
p = 0.735
p = 0.515
BMI classification
 Underweight (1)
68
12.26 ± 4.42
10.5
11.84 ± 4.06
11.5
21.75 ± 8.52
20.5
15.69 ± 6.66
15.5
 Normal (2)
591
12.50 ± 4.17
11.0
12.50 ± 4.39
12.0
23.47 ± 9.14
23.0
15.17 ± 6.03
15.0
 Overweight (3)
104
13.92 ± 4.67
13.0
13.98 ± 5.19
14.0
26.27 ± 10.47
25.5
15.21 ± 6.01
16.0
 Obese (4)
11
11.54 ± 4.37
11.0
9.91 ± 4.42
10.0
19.00 ± 8.99
23.0
17.18 ± 6.31
17.0
Statistical analysis
χ2 = 10.671
χ2 = 11.474
χ2 = 11.608
χ2 = 1.613
Probability, Difference
p = 0.014 [1.2–3]
p = 0.009 [3–1.2.4]
p = 0.009 [1-3]
p = 0.656
Class
 1 year of study(1)
264
11.87 ± 4.14
11.0
11.53 ± 4.04
11.0
21.84 ± 8.89
20.0
14.69 ± 5.99
14.0
 2 year of study (2)
204
12.90 ± 4.54
12.0
12.64 ± 4.69
12.0
23.74 ± 9.58
23.0
15.31 ± 6.22
15.0
 3 year of study(3)
172
12.99 ± 4.06
12.0
13.41 ± 4.61
14.0
25.31 ± 9.72
26.0
16.33 ± 5.95
17.0
 4 year of study(4)
134
13.38 ± 4.27
12.0
13.61 ± 4.60
14.0
24.83 ± 8.84
25.5
14.87 ± 6.12
15.0
Statistical analysis
χ2 = 18.764
χ2 = 25.808
χ2 = 16.967
χ2 = 8.138
Probability, Difference
p < 0.001 [1–2.3.4]
p < 0.001 [1–3.4]
p = 0.001 [1–3.4]
p = 0.043 [1-3]
Digital gaming tool
 Tablet
35
14.34 ± 4.79
13.0
14.14 ± 4.54
14.0
28.28 ± 9.91
29.0
15.20 ± 6.08
15.0
 Smartphone
734
12.54 ± 4.23
12.0
12.49 ± 4.49
12.0
23.33 ± 9.24
22.0
15.26 ± 6.08
15.0
Statistical analysis
Z = -2.277
Z = -2.240
Z = -2.913
Z = -0.066
Probability
p = 0.023
p = 0.025
p = 0.004
p = 0.947
aFor non-normally distributed data, "Mann–Whitney U" test (Z-table value) was used to compare the measurement values of two independent groups, and "Kruskall-Wallis H" test (χ2-table value) statistics were used to compare three or more independent groups
The mean DGAS-7 score was significantly greater for students aged 21 years and older (χ2 = 15.374; p = 0.002). At the same time, it was determined that the mean scores of the DGPMS success and revival (Z = -5.785; p < 0.001), curiosity, and social acceptance (Z = -5.852; p < 0.001) sub-dimensions of male students were statistically significantly higher than female students (p < 0.05). Students aged 21 years and over had statistically significantly higher mean scores in the DGPMS success and revival (χ2 = 20.663; p < 0.001), curiosity, and social acceptance (χ2 = 17.183; p = 0.001) sub-dimensions compared to other age groups. The mean score of 20-year-old students in the DGPMS uncertainty in willingness to play (χ2 = 9.778; p = 0.021) subscale was statistically significant compared to different age groups (Table 4).
Concerning marital status, the mean DGAS-7 score was significantly greater for single students (Z = -2.325; p = 0.020). The overweight students' mean DGAS-7 scores (χ2 = 10.671; p = 0.014) according to their BMI were greater than those of the other groups (Table 4).
Considering BMI, it was determined that the mean scores of the DGPMS success and revival (χ2 = 11.474; p = 0.009) sub-dimension scores of overweight students were significantly higher than the others (p < 0.05) (Table 4).
According to the class variable, the mean DGAS-7 scores of students in years 2, 3, and 4 were significantly greater than those in 1 year of study (χ2 = 18.764; p < 0.001) (Table 4). Regarding the game tool, the mean DGAS-7 score of the nursing students who played with a tablet was significantly greater than that of those who played with a smartphone (Z = -2.277; p = 0.023). According to the digital gaming tool, the mean scores of the DGPMS success and revival (Z = -2.240; p = 0.025), curiosity, and social acceptance (Z = -2.913; p = 0.004) sub-dimension scores of the students who preferred to play digital games with tablets were statistically significantly higher than those who played with smartphones (p < 0.05) (Table 4).
According to Table 5, according to the logistic regression (LR) analysis performed by considering the risk status of nursing students' Digital Game Addiction Scale, it was determined that the Success and Revival subscale of the Digital Game Playing Motivation Scale was a significant variable on the risk of digital game addiction (p < 0.05). When the Success and Revival Score increases by 1 unit, the risk of digital game addiction increases by 47.2% (OR = 1.472).
Table 5
The logistic regression model addressed based on digital game change risk status
Variable
Β
S.H
Wald
SD
p
OR
OR 95% Confidence Interval (OR)
lower
top
Success and Revival
0.387
0.047
68.849
1
0.000
1.472
1.344
1.613
Curiosity and Social Acceptance
0.008
0.019
0.162
1
0.687
1.008
0.970
1.047
Uncertainty in Willingness to Play
-0.003
0.022
0.021
1
0.885
0.997
0.955
1.040
Fixed
-7.430
0.685
65.522
1
0.000
0.001
  
CCR = 86.7% χ2(8) = 9.754; p = 0.283
OR Odds Ratio

Discussion

Students may engage with digital games for various reasons during their university education, potentially leading to digital game addiction if not properly managed [16, 17]. This study found that digital game addiction among nursing students, as measured by DGAS-7, was generally low. This observation aligns with previous research by Aktan [18] and Aktaş with Bostancı-Daştan [3], which also noted low levels of game addiction among nursing students. Despite the challenges posed by the pandemic, nursing students appear to be aware of potential digital gaming issues and manage their gaming habits accordingly.
Regarding motivation for playing digital games, DGPMS revealed that curiosity and social acceptance were significant factors. These external motivations drive gaming behavior, which include the desire for rewards such as trophies and status and the sensory appeal of game sounds and effects [19]. Further studies have confirmed that curiosity and social acceptance are predominant, followed by motives like uncertainty, success, and survival in gaming scenarios [20]. This indicates that external factors are strong determinants of gaming behavior among nursing students, primarily motivated by curiosity, as is common among their peers in different fields.
The subdimension of uncertainty in gaming desire, which ranks second for motivational factors in digital gaming, suggests that students engage in gaming without fully considering the consequences or causes of their gaming habits [21]. This aspect is crucial as it contrasts with the critical thinking and evidence-based practices emphasized in nursing education, grounded in real-world experiences.
Interestingly, the study also highlights that intrinsic motivations such as achievement and revitalization, which include elements like ambition and happiness, are less influential among nursing students [22, 23]. This finding, corroborated by Güler and Çakır [21], suggests a lesser inclination towards gaming driven by these intrinsic factors, challenging some prior studies [1, 2].
Correlations were observed between various motivational subdimensions—achievement, revival, curiosity, and social acceptance—and digital game addiction [24, 25]. These correlations suggest that while motivations can vary, they significantly influence the likelihood of addiction, particularly through social motivations [7].
Examining demographic factors, we found that male nursing students scored higher on the DGAS-7 than their female counterparts, potentially due to cultural and social dynamics that encourage men more towards gaming [3, 10, 11, 25]. The influence of gender on game addiction is also seen in different responses to the motivational factors within the DGPMS, where success, revival, curiosity, and social acceptance scores were notably higher among males [20, 21].
Age also plays a critical role; older students (21 years and above) reported higher addiction scores, possibly exacerbated by the remote learning conditions imposed during the pandemic [6, 25]. This was a deviation from the trends observed in younger age groups, where the pandemic seemed to reduce the interactive aspects of their education, leading to increased gaming.
Marital status and physical health also influenced gaming behavior. Single students and those classified as overweight according to BMI had higher scores on the DGAS-7 [26, 27]. This could be attributed to more free time and less engagement in physical activities, respectively.
Lastly, the type of device used for gaming was a significant factor, with students using tablets showing higher addiction scores than those using smartphones [4, 28]. The ease of use and the immersive experience provided by tablets might contribute to higher levels of engagement and, consequently, higher motivation and addiction scores.
This analysis demonstrates that digital game addiction and motivation among nursing students are influenced by a complex interplay of demographic, psychological, and environmental factors. Understanding these factors can help in developing targeted interventions to manage potential addiction issues effectively [29].

Limitations

This study had some limitations. A self-report scale was used to gather information about all the variables that might have the potential for bias. Another limitation was that causality could be explained to a limited extent due to the descriptive and correlational design of the study. The study's non-experimental design was limited to nursing students from three specific universities: two state universities and one foundation university. Consequently, the findings are applicable only to these institutions.

Conclusion

This study investigated the levels of digital game addiction and digital game playing motivation among nursing students and the factors influencing these aspects. The findings indicate that digital game addiction is generally low among nursing students, yet certain factors such as gender, age, BMI, and the type of device used for gaming (particularly tablets) significantly affect both addiction levels and motivational subdimensions.
Male students, those aged 21 and older, overweight students, and those who prefer tablets for gaming are more likely to have higher digital game addiction scores. These demographic and device preference factors also enhance motivational aspects related to digital gaming, particularly in Success and Revival, Curiosity, and Social Acceptance. While overall addiction levels are low, they are influenced by specific demographic and behavioral factors, which are crucial for developing interventions aimed at reducing game addiction risks and promoting healthier gaming habits among nursing students.
This study shows that evaluating nursing students in terms of digital addictions is critical in preventing future health problems. In line with these results, it can be suggested that digital games can be transferred to the nursing curriculum to be used in cognitive and psychomotor areas and that more comprehensive studies on the effects and management of these games on individuals should be suggested.

Acknowledgements

The authors would like to extend to all nursing students who participated in this study.

Conflict of interest

The authors declare that there are no conflicts of interest regarding the publication of this article.

Declarations

All participants gave informed consent for inclusion before participating in the study. The Declaration of Helsinki conducted the study, and the protocol was approved by the Ethics Committee of Istanbul University-Cerrahpasa Project identification code 2020/70800, dated 13.10.2020. Before starting to collect data, written permission was obtained from the institutions where the research was conducted [Istanbul University-Cerrahpaşa Florence Nightingale Faculty of Nursing (14.09.2020/119213), Istanbul Medeniyet University Faculty of Health Sciences Department of Nursing (16.https://​doi.​org/​10.​2020/​70734980-100-E.​3701), Bezmialem. Retrieved from Foundation University, Faculty of Health Sciences, Department of Nursing (09.11.2020/5403). The authors confirm that all methods were conducted in accordance with the ethical principles.
Not applicable.

Competing interests

The authors declare no competing interests.
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Metadaten
Titel
Investigation of nursing students' addiction to digital game play and associated factors
verfasst von
Hasan Sağlam
Nuray Turan
Publikationsdatum
01.12.2024
Verlag
BioMed Central
Erschienen in
BMC Nursing / Ausgabe 1/2024
Elektronische ISSN: 1472-6955
DOI
https://doi.org/10.1186/s12912-024-02244-w