Parallel mediation of psychological flexibility and vulnerability between multiple-screen addiction and mental health outcomes in adolescents

Abstract

This study examines the mediating role of psychological flexibility and vulnerability variables in the relationships between multiple-screen addiction and depression, anxiety, and stress. Data were collected from 309 high school students (M age = 16.13, SD = 1.40; 57% girls, 43% boys). Analyses were conducted using SPSS 25 and Hayes Model 4. Data were collected using the Multi-Screen Addiction Scale (MSA), the Depression, Anxiety, and Stress Scale (DASS-21), the Psychological Vulnerability Scale, and the Acceptance and Action Questionnaire-II (AAQ-II). Findings show that students with MSA and high levels of depression, anxiety, and stress have low levels of psychological flexibility and high levels of psychological vulnerability. More importantly, psychological flexibility and vulnerability were found to play a fully mediating role in this relationship. As a result, it seems that strengthening psychological flexibility and reducing vulnerability have a significant effect in reducing the adverse effects of depression, anxiety, and stress caused by MSA in students. These findings can provide necessary guidance in developing intervention programs and school policies.

Impact Statement

The unique contribution of this study lies in examining a parallel model in which psychological flexibility and psychological vulnerability simultaneously play mediating roles. This approach offers a more comprehensive framework, both theoretically and empirically, for explaining the effects of MSA on mental health in adolescents. The findings advance current theoretical understanding in the field of digital addiction and contribute significantly to the design of intervention programs specifically aimed at increasing psychological flexibility and reducing psychological vulnerability. Thus, the study provides a concrete, applicable, and innovative roadmap for school-based and clinical practices aimed at strengthening adolescents' digital well-being.

Introduction

As the role and function of technology in our lives have increased, internet use has become more challenging to manage. This process has raised severe concerns due to excessive internet use among young people and adults [1]. The internet is used through digital devices. This usage leads to the concept of multiple-screen addiction. Screen addiction can be classified as digital game addiction (offline, online, single-player, multiplayer), internet addiction (sex, gambling, shopping), technological device addiction (smartphone, VR, tablet, and computer, etc.), and media addiction (traditional and social media) [2]. Indeed, Gupta et al. [3] stated that internet addiction is a serious problem. They found that the most frequently used smart devices are phones, laptops, desktops, and tablets. These findings demonstrate that the screen is the "window" of our lives, opening to the virtual world.

Life in the Digital Age and Multiple-Screen Addiction (MSA)

Digital games are becoming increasingly common in the lives of children and adolescents [4–6]. Children and adolescents are particularly vulnerable to the effects of digital devices due to their incomplete development of impulse control and cognitive flexibility [7]. Additionally, multiple screens increase depressive symptoms and harm sleep quality [8]. Adolescents who are addicted to the Internet are at risk of unhealthy diets, smoking and alcohol use, violence, cyberbullying, and exposure to pornography [9, 10].

Most people have constant access to technological devices. They engage in continuous activities such as sending emails, watching and sharing videos, listening to music, playing games, making voice calls, sending messages, and using social media via smartphones [11–14]. This access process can turn into excessive, obsessive, and repetitive behaviors over time and may reveal disorders such as MSA [15]. However, it becomes inevitable for individuals, especially those who strive to have free time, to be exposed to MSA [16]. MSA, which is a severe risk factor for mental health, can be considered a behavioral addiction, such as internet addiction and smartphone addiction [15].

"Human," the actor of the digital world, has begun to change their life habits in response to the screen. Of individuals between the ages of 16 and 64 who use digital devices, 96.2% use a mobile phone, 95.6% use a smartphone, 58% use a laptop or desktop computer, 33.7% use a tablet, 20.3% use a game console, and 29.9% use smartwatches and wristbands. The number of internet users worldwide has reached 5.16 billion. These individuals spend an average of 6 h and 37 min daily online [17, 18]. In Turkey, the usage rate of portable computers, including laptops and tablets, has increased to 46.6%, while the usage rate of smartphones/mobile phones has increased to 99.2% [19]. Additionally, the rate of internet access among households has exceeded 95%. The internet usage rate among individuals aged 19–74 has reached 87% [20]. The widespread use of digital devices and increased internet access reveal the indispensable place of technology in our daily lives. On the other hand, adolescents can be accurately informed about substance use, sexual health, bullying, and body image through the media [21]. This suggests that the effect of digital devices may be related to their intended purpose.

Multiple-Screen Addiction and Depression Anxiety Stress (DAS)

Technological innovations in the digital age have brought new problems, such as MSA. Multiple screens refer to digital devices, including smartphones, computers, tablets, and TVs. The most common activities of these devices include internet use, communication, gaming, and movie watching [8]. MSA causes symptoms such as tolerance, withdrawal, and apathy. This type of addiction is associated with depression, anxiety, stress, and suicidality [22]. Additionally, individuals who are frequently exposed to screens and engage in online experiences are at risk of self-harm [23]. Internet use is one of the most critical factors in the emergence of MSA. Internet addiction has a triggering role in psychopathological features and dysfunctional attitudes [24]. Problematic internet use and internet addiction can cause depression [25], [26], anxiety [27], stress [3], suicide [28, 29], low self-esteem, semantic verbal fluency [1], social anxiety [30], phubbing [31], low academic achievement [32], low psychosocial well-being [33], social phobia [34], ADHD, lack of excitement seeking and assertiveness [35], and pornography and harassment [36] are situations that trigger various psychological and social problems.

Mental disorders and internet addiction interact with each other. Adverse life events and depressive experiences may be effective in the emergence, severity, and recurrence of addiction [24]. Individuals experiencing psychological distress have a higher level of internet addiction. Internet addiction also increases psychological distress [37]. Individuals with depressive symptoms also have a high tendency to become internet addicted, and the prevalence of internet addiction in depressed individuals is 36%. In addition, depressed individuals have significantly higher levels of television, computer games, and internet addiction than other individuals [38]. Individuals with personalities characterized by shyness, dependence, and low self-esteem have a higher risk of internet addiction [36]. Individuals may increase their Internet use time because they believe online communication is low-level harmful [39]. This explains the complex relationship between online communication and screen addiction.

Easier access to the internet via mobile phones has increased mobile phone usage [40]. Smartphone addiction can be considered a more serious risk factor than internet addiction [27]. This can be explained by smartphones being functional devices with computer and phone features [41]. Mobile phone use also causes technology addiction over time. Mobile phone addiction and problematic use are associated with depression, anxiety [42, 43], low self-esteem [41], chronic and excessive stress [44], anger and impulsivity [45], low academic achievement and low life satisfaction [11], physical fatigue, insomnia (Boumosleh & Jaalouk, 2017), behavioral problems [12], ADHD, smoking and alcohol use [7]. On the other hand, depression and anxiety are also predictors of smartphone addiction (Boumosleh & Jaalouk, 2017). Users sometimes turn to their mobile phones to eliminate their negative emotions. Thus, they can feel that they are free from stress and anxiety. This cycle can become more complex over time.

In the digital world, social media usage is increasing daily for most individuals. Addiction caused by excessive social media use can lead to individuals experiencing mental health problems. However, these individuals have a higher risk of experiencing somatic symptoms, social dysfunction, depression, and anxiety [46–48]. It can be said that one of the components of multi-screen addiction is game addiction. Gaming applications, which are a severe and growing social problem for young generations [49], cause depression, anxiety, and poor sleep quality [50]. Additionally, the majority of individuals with digital gaming disorder have high levels of daily and chronic stress [51]. While game addiction increases stress, stress can also trigger game addiction [49]. In conclusion, the interrelationship of MSA with mental health problems suggests that the variables underlying these complex relationships need to be understood in depth.

The mediating role of psychological flexibility and vulnerability

Psychological flexibility involves maintaining and changing conscious behavior in accordance with selected values [52]. Individuals who lack this flexibility may struggle to integrate their sense of self with their thoughts, actions, and feelings. Thus, the individual cannot distinguish between the self and private feelings, thoughts, and memories. As a result, the individual may evaluate themself as worthless and useless [53]. Psychological flexibility is a crucial skill not only for individuals but also for social interactions. Cognitive and behavioral flexibility is necessary in addressing problems such as economic crises, epidemics, and health issues that concern society as a whole [54]. Therefore, psychological flexibility is vital at the individual and social levels.

The fundamental mechanism of change in the The Acceptance and Commitment Therapy (ACT) model is psychological flexibility [55]. If researchers utilize flexibility in theoretical models and clinical techniques based on the ACT model, it is possible to reduce the suffering of individuals with chronic conditions [56]. ACT approach utilizes six essential components to enhance psychological flexibility: acceptance, present-moment awareness, self-as-context, defusion, values, and committed action. Each of these components is associated with distress, anxiety, and depression [57]. Bramwell and Richardson [58] found that ACT was an important mechanism of reduced dissociation and increased values-based action in people with depression and mental health problems.

ACT practices are effective in increasing psychological flexibility [59] to cope with depression [60], stress [61], and anxiety [62]. Theoretically, these approaches play a crucial role in enhancing psychological flexibility. Additionally, ACT has been determined to be effective in reducing technological addiction [63]. On the other hand, as the duration of smartphone use in adolescents increases, psychological flexibility decreases [64]. Furthermore, psychological flexibility has been found to be affected by social media addiction [65]. The intensity of social media use is associated with multi-screen addiction [66]. Similarly, psychological flexibility has an impact on short video addiction [67]. Therefore, it can be argued that there is an interaction between psychological flexibility and multi-screen addiction, which includes the components of smartphone use, social media addiction, and short video addiction. Furthermore, psychological flexibility, a multidimensional concept, is associated with psychopathology [68, 69]. Flexibility and decisive action, two key components of psychological flexibility, effectively reduce sleep problems, depression, and anxiety [70, 71]. ACT has been found to increase psychological flexibility and reduce pathologies such as stress [72]. Similarly, ACT is effective in reducing depression and increasing psychological flexibility [73].

Interventions based on the ACT model are effective on cognitive structures associated with psychological vulnerability to anxiety and depression [74]. Furthermore, psychological vulnerability is associated with internet and screen addiction [75]. Similarly, social media addiction predicts psychological vulnerability [76]. Digital literacy, which is associated with multiple-screen addiction [77], can negatively affect vulnerable children psychologically [78]. Psychological vulnerability has been found to negatively impact mental health [79]. Conversely, depression, anxiety, and stress have also been found to influence psychological vulnerability [80]. In this context, according to the ACT model, the interaction between psychological vulnerability, psychological resilience, and pathologies such as multiple-screen addiction, depression, anxiety, and stress can be critical.

Vulnerability is another variable associated with internet and screen addiction [75]. Vulnerability, which is more common and often hidden than diagnosable diseases, is influenced by psychological, social, and biological factors. Six factors are indicative of psychological vulnerability: delinquency, early socialization, mental illness, perceived discrimination, social capital, and traumatic experiences [81]. Psychological vulnerability, which plays a crucial role in mental health [82], is linked to individuals' well-being, hope, and psychological resilience [83]. It has been observed that vulnerable individuals experience higher levels of self-alienation and possess lower authentic living skills [84]. In human life, parents, peers, difficult family conditions, poverty, and low socioeconomic level can contribute to pathology, causing individuals to be more vulnerable to stress [85, 86]. The triple vulnerability model argues that psychological vulnerability contributes to the etiology of emotional disorders such as anxiety and stress [87]. Additionally, the cognitive dimension of vulnerability can be evaluated in relation to the hopelessness theory. According to this theory, vulnerability is the tendency to infer the causes and consequences of adverse events. Individuals with high levels of vulnerability associate negative experiences with a fixed cause, feel worthless, and believe that there will be other negative experiences [88].

In the current study, which aims to examine the effect of MSA on individuals' DAS levels, it is thought that psychological flexibility will have a positive impact. However, psychological vulnerability will harm mental health. Therefore, this study aims to examine the mediating effect of psychological flexibility and vulnerability in the relationship between MSA and DAS.

Research findings on psychological flexibility and inflexibility are crucial for supporting ACT-based mental health studies [89]. Because the literature lacks a strong predictive relationship between psychological flexibility and psychological vulnerability, the mediators were modeled in parallel rather than sequentially. Only a few studies have been found in the literature in which flexibility/inflexibility and vulnerability predict each other [90, 91]. It can be argued that psychological resilience, which has a negative relationship with psychological vulnerability [92], has a stronger relationship with flexibility. There are studies finding that flexibility directly predicts psychological resilience [93, 94]. If the psychological resilience variable had been included in the current study, the mediators could have been modeled sequentially.

Present study

Nowadays, individuals are at risk of screen addiction because they are constantly accessing digital devices [13, 95]. This type of addiction is associated with depression, anxiety, and stress [22]. Therefore, it is essential to investigate factors that may affect the relationship between screen addiction and psychopathology. Individuals with high psychological vulnerability [76] and low flexibility [65] have a high risk of becoming addicted to social media, which causes multi-screen addiction. In this context, multi-screen addiction can be expected to increase addiction and decrease flexibility. In addition, relationships have been found between psychological flexibility and depression [96], anxiety [97], and suicide coginitions [98]. Additionally, psychological vulnerability is associated with depression [99, 100] and state anxiety [101].

When the literature is examined, it is seen that there are studies examining the relationships between technology addiction and mental health, psychological flexibility, and vulnerability. However, it is striking that these studies do not specifically address "multi-screen addiction." MSA is a comprehensive and current study topic related to concepts of technology addiction. It covers many factors, including phone, computer, social media, and internet addiction. In addition, the level of depression, anxiety, and stress (DAS) is fundamental in determining mental health. This study examined three psychopathologies. It is thought that the concepts of psychological flexibility and vulnerability may have a critical role in the relationship between multi-screen and DAS. Because flexibility and vulnerability are predicted to affect mental health and psychopathology. In addition, no study has been found that examines these four concepts together. In this context, the current study is considered original and has the potential to play an explanatory role in MSA and mental health.

This study examined the mediating role of psychological flexibility and vulnerability in the relationship between MSA and DAS. Considering the research in the literature, the following hypotheses were tested.

• H1: MSA has a significant direct effect on DAS.

• H2: MSA has a significant direct effect on psychological vulnerability.

• H3: Psychological vulnerability has a significant direct effect on DAS.

• H4: MSA has a significant direct effect on psychological flexibility.

• H5: Psychological flexibility has a significant direct effect on DAS.

• H6: Psychological vulnerability and psychological flexibility have mediated effects between MSA and DAS.

• H7: MSA has an insignificant indirect effect on DAS.

Method

This study examines the mediating roles of cognitive psychological vulnerability and flexibility in the relationship between MSA and DAS. The study was conducted using a correlational design, and quantitative methods were applied. In the data collection process, due to time, budget, and labor limitations, the convenience sampling method was preferred, in which the easiest-to-reach participants were selected.

Procedure

An online questionnaire was prepared for data collection. On the first page of the online survey, participants were informed about the duration and purpose of the study. Google Forms sent the research link to the participants through social media platforms and messaging programs such as WhatsApp, Twitter, and Instagram. The inclusion criteria were being a university student aged 14 years and above. Consent was obtained from the parents of the students based on ethics committee approval. Students with no high school students were not included in the study. Individuals who met these criteria and volunteered to participate were included in the study. In addition, participants were advised not to provide information about their personal information to protect confidentiality and anonymity. The response time was 10 min at the beginning of the questionnaire. The study data were collected while the education process was in progress. The data collection process continued for about two months to avoid coinciding with the exam periods of the students. The data were analyzed using SPSS 28 and AMOS 24 package programs.

Participants

This study was conducted with 309 participants continuing their high school education. The mean age of the participants was 16.13 years (SD = 1.40), and their ages ranged from 14 to 19 years. There were 57% (n: 176) girls and 43% (n:133) boys. In terms of grades, 96 (31.1%) of the participants were high school 3rd-grade students, followed by high school 2nd-grade (29.8%), high school 1st-grade (20.4%) and high school 4th grade (18.8%). In addition, 24 of the participants indicated a low level, 249 showed a medium level, and 36 indicated a high level according to the country's economic status. In addition, the average daily TV watching was 2.34 h (SD: 1.13), daily tablet-computer use was 2.24 h (SD: 1.38), and daily phone use was 4.29 h (SD: 1.32).

Measures

The Multi-Screen Addiction Scale (MSA)

The scale developed by Sarıtepeci [102] is a 5 Likert-type and has 15 items consisting of 3 sub-dimensions. There are four items in “Excessive Screen Time (EST),” 8 items in “Compulsive Behavior (CB),” and three items in “Loss of Control (LoC).” The Cronbach Alpha, internal consistency coefficient, was reported for the MSAS scale, and its sub-dimensions range between 0.71–0.92. Accordingly, it was found that there was an acceptable fit between the factor structure of the MSAS scale and the data (CMIN/DF = 4.232, GFI = 0.95, CFI = 0.95, RMSEA = 0.091). The internal reliability coefficient values of MSAS and its subscales ranged from 0.70 to 0.93. The measurement model for the current study showed an acceptable fit (CFI = 0.95, TLI = 0.94, RMSEA = 0.060, SRMR = 0.045, χ²/df = 2.212, p < 0.01), supporting the factorial validity of the construct. The internal reliability estimate of the MSA in the present sample is shown in Table 1.

Table 1.

Descriptive Statistic. Linearity. Normality. and Multicollinearity

Variables	N	Min	Max	Means	SD	Skew	Kurt	VIF	Tolerance
DAS	309	21.00	78.00	41.65	11.45	.704	.099
MSA	309	15.00	73.00	40.92	13.27	.278	-.562	1.236	.809
Psychological vulnerability	309	6.00	28.00	17.72	4.87	.038	-.774	1.887	.533
Psychological flexibility	309	7.00	49.00	30.24	10.19	-.186	.226	1.828	.547

Depression Anxiety Stress (DAS-21)

DASS-21 was developed by Lovinond and Lovibond [103] by selecting the items of DASS-42 to shorten the duration. DASS-21 contains seven items for each scale, multiplying the evaluation result by two. Henry and Crawford [104] showed that the Cronbach alpha internal consistency reliability coefficient value was 0.88 for the depression subscale, 0.90 for the stress subscale, and 0.93 for the entire scale. According to the same study, the fit index values ​​of the DASS-21 model are S-Bχ2 = 628.0, χ2 = 1092.1, df = 180, CFI = 0.93, SRMR = 0.03, and RMSEA = 0.05. DAS-21 was adapted to Turkish culture by Sarıçam [105]. In the clinical sample, Cronbach's alpha internal consistency reliability coefficient was found to be α = 0.87 for the depression subscale, α = 0.85 for the anxiety subscale, and α = 0.81 for the stress subscale. Within the validity scope, the scale's factor loadings range from 0.42 to 0.72. Three factors explain 49.72% of the total variance. Confirmatory factor analysis (CFA) scale results were calculated as GFI = 0.90, CFI = 0.90, TLI = 0.89, RMSEA = 0.065, and SRMR = 0.067. According to the psychometric properties obtained, it was concluded that DAS-21 is a valid and reliable measurement tool for Turkish culture. The measurement model for the current study showed an acceptable fit (CFI = 0.91, TLI = 0.89, RMSEA = 0.063, SRMR = 0.055, χ²/df = 2.209, p < 0.01), supporting the factorial validity of the construct. The internal reliability estimate of the DAS-21 in the present sample is shown in Table 1.

Psychological Vulnerability Scale

The scale was developed by Sinclair and Wallston [106] and adapted into Turkish by Akın and Eker [107]. This scale is intended to determine the psychological vulnerability levels of adults. The scale includes six questions on a 5-point Likert-type scale (1—Not suitable for me, 2–3–4- 5- Completely suitable for me). The highest possible score on the scale is 30, and the lowest is 5. It is stated that as the score increases, the psychological vulnerability of adults increases, and as the score decreases, psychological vulnerability decreases. The internal consistency coefficient calculated while adopting the psychological vulnerability scale for Turkish was 0.75. The highest score that can be obtained from the scale is 30, and the lowest score is 5. It is stated that as the score increases, the psychological vulnerability of adult individuals decreases, while psychological vulnerability increases. The internal reliability estimate of the psychological vulnerability scale in the present sample is shown in Table 1.

To address concerns regarding the limited reliability of the Psychological Vulnerability Scale, a confirmatory factor analysis (CFA) was conducted using AMOS. The measurement model demonstrated acceptable-to-good fit (CFI = 0.94, TLI = 0.90, RMSEA = 0.065, SRMR = 0.044, χ²/df = 2.28, p < 0.05), supporting the factorial validity of the construct.

Acceptance and Action Questionnaire-II (AAQ-II)

AAQ-II was used to measure psychological flexibility. The scale was developed by Bond et al. [108]. The scale consists of 7 items. It is on a 7-point Likert scale (1: never true, 7: always true). High scores on the scale indicate that psychological flexibility is low and experiential avoidance is high. The internal consistency coefficient of the original scale is 0.84. CFA values ​​(N = 290), CFI = 0.99, SRMR = 0.03, RMSEA = 0.04, CMIN/df = 1.49. Yavuz et al. [109] adapted the scale to Turkish culture. Cronbach's α coefficient of the scale is 0.84. As for construct validity, the Kaiser–Meyer–Olkin index (r = 0.83) was compatible with factor analysis (Bartlett chi-square = 1151.20,p < 0.0001). The single-factor solution (with an Eigenvalue of 3.62) explains 51.76% of the total variance. CFA results indicate that the revised scale model fits the 7-item and single-factor structure well (RMSEA = 0.079, SRMR = 0.021, CFI = 0.97, GFI = 0.97, NFI = 0.96). The measurement model for the current study showed an acceptable fit (CFI = 0.97, TLI = 0.95, RMSEA = 0.085, SRMR = 0.041, χ²/df = 3.228, p < 0.01), supporting the factorial validity of the construct. The internal reliability estimate of the AAQ-II scale in the present sample is shown in Table 1.

Data analysis

In this study, a mediation model was used to examine the mediating roles of psychological vulnerability and psychological flexibility. From a theoretical standpoint, psychological vulnerability and psychological flexibility represent distinct and independent internal processes that are activated by multiple-screen addiction; therefore, they are not conceptualized as influencing one another in a causal sequence. Each mediator is expected to exert its own unique pathway on depression–anxiety–stress outcomes, which conceptually justifies the use of a parallel mediation framework (PROCESS Model 4). The data were analyzed with SPSS PROCESS 25 (Model 4). Prior to the analysis, linear relationship, normality, and multicollinearity were examined. Five outliers that violated the normal distribution were removed from the initially collected 309 data points, and the analysis was then carried out using the remaining 304 data points. Data were collected through Google Forms and delivered to the target audience through various channels [such as e-mail, social media, or academic forums].

To address potential confounding effects, demographic variables (sex, grade level, daily device use, and socioeconomic status) were included as covariates in the PROCESS Model 4 analysis. None of these variables significantly predicted the mediators or the outcome (all p > 0.05), and their inclusion did not alter the magnitude or significance of the mediation effects. Thus, covariates were statistically controlled, but they did not have a meaningful influence on the model.

Multicollinearity was assessed by the Variance Inflation Factor (VIF) values, and all values were below 10. For the normality test, the Shapiro–Wilk (p > 0.05) and skewness (−1 to + 1) and kurtosis (−2 to + 2) values were examined. Q-Q graphs were analyzed, and it was determined that the data were approximately normally distributed. The significance level was set at p < 0.05 for the analyses performed using Pearson correlation. The F statistic was calculated in the regression analysis, and R and R² values were reported. Additionally, the model's validity was assessed by verifying the normality of the residuals. No multicollinearity was found in the analysis results, and it was confirmed that the data were normally distributed. Detailed results are presented in Table 1.

Results

The relationships between variables were examined with the Pearson correlation coefficient, and the results are presented in Table 2. Additionally, the reliability of the scales was assessed using Cronbach's alpha, and the values are reported in Table 2.

Table 2.

The relationships between variables

	α	ω	1	2	3	4
1 = DAS	.90	.91	1
2 = MSA	.91	.91	.38*	1
3 = Psychological vulnerability	.65	.65	.60*	.41*	1
4 = Psychological flexibility	.85	.86	-.72*	-.38*	-.66*	1

^* p < 0.01

As seen in Table 2, the DAS variable exhibited a positive and significant relationship with multiple-screen addiction (MSA) (r = 0.38, p < 0.001). Similarly, a moderate to high positive correlation was found between DAS and psychological vulnerability (r = 0.60, p < 0.001). In contrast, a high negative correlation was found between DAS and psychological flexibility (r = –0.72, p < 0.001). These findings indicate that DAS levels increased as MSA and psychological vulnerability increased, but decreased as psychological flexibility increased.

Mediation analysis

As demonstrated in Table 3, prior to mediation analysis, the simple linear regression results showed that an MSA significantly predicted DAS (β = 0.09, 95% CI: 0.05–0.15; p < 0.05).

Table 3.

The result of the regression analysis

Predictor	β	SE	p	F	R	R2
Constant	48.858	3.79	<.001	124.266	.74	.55
MSA	.08	.04	<.05
Psychological vulnerability	.47	.12	<.001
Psychological flexibility	-.62	.06	<.001

The mediating roles of psychological vulnerability and psychological flexibility were tested using the mediation model, and the results are presented in Table 4.

Table 4.

Mediational model coefficients

Predictors		Psychological vulnerability			Psychological flexibility			DAS
		β	p		β	p		β	p
MSA		.15	.001		-.29	.001		.08	>.05
							Ind1	.07	.001
							Ind2	.18	.001
Psychological vulnerability		–––	–––		–––	–––		.47	.001
Psychological flexibility		–––	–––		–––	–––		-.62	.001
Constant	i1	11.54	.001	i2	42.29	.001	i3	48.85	.001
		R = .41, R2 =.17			R = .38, R2 =.15			R = .74; R2 =.55
		F(1,307) = 62.54, p <.001			F(1,307) = 52.83, p <.001			F(3, 305) = 124.26 p <.001

Initially, the effect of MSA on DAS was significant (β = 0.38, LLCI = 0.32, ULCI = 0.56, p < 0.01). After the mediator variables (Psychological Flexibility and Vulnerability) were included in the model, the mediation analysis revealed that the effect of MSA on DAS was not statistically significant (β = 0.08, 95% LLCI = 0.05, ULCI = 0.15; p > 0.05), which is expressed as "full mediation." Psychological vulnerability (β = 0.47, 95% LLCI = 0.22 ULCI = 0.71; p < 0.01) and psychological flexibility (β = −0.61, 95% LLCI = −0.73 ULCI = −0.50). The magnitude of the indirect effect indicates that approximately 55% of the total effect occurs through the mediation pathway (PM = a.b/c, PM = 0.55). This finding indicates that the mediation mechanism is significant and effective in the model. Finally, mediation analysis revealed that psychological vulnerability and psychological flexibility played a parallel mediating role in the relationship between an MSA and DAS (Fig. 1).

Fig. 1.

Serial Mediation Role of psychological vulnerability and psychological flexibility

The mediation analysis examined and presented the indirect, total, and direct effects of psychological vulnerability and psychological flexibility on DAS, as shown in Table 5. As seen in Table 5, the indirect effect of Ind1 (bβ = 0.07, 95%, LLCI = 0.03 ULCI = 0.12, p < 0.01) and Ind2 (β = 0.18, 95%, LLCI = 0.12 ULCI = 0.25, p < 0.01) on the DAS is significant. These results confirm that the parallel mediating role of psychological vulnerability and psychological flexibility is significant in the relationship between an MSA and DAS (Full mediation). In addition, the findings obtained from the bootstrap analysis with 5000 resamplings are presented in Table 6.

Table 5.

Effects of the psychological vulnerability and psychological flexibility on the DAS

Effects	Estimates of Point β	%95 Confidence Interval
		The lowest	The highest
Total effect	.33	.24	42
Direct effect	.08	.005	.15
Total Indirect Effect	.25	.18	.32
Ind1	.07	.03	.12
Ind2	.18	.12	.25

Ind1= MSA à Psychological Vulnerability à DAS

Ind2= MSA à Psychological Flexibility à DAS 

Table 6.

Results of Bootstrapping Analyses for the Parallel Mediation Model

Model pathways	Coefficient	Confidence Interval (%95)
		Lower	Upper
a à b	0.08	-0.018**	0.16**
a à c	0.15	0.12*	0.19*
a à d	-0.29	-0.37*	-0.21*
c à b	0.47	0.20*	0.73*
d à b	-0.62	-0.73*	-0.49*

 a: MSA, b: DAS, c: psychological vulnerability, d: psychological flexibility

*p<0.01, **p>0.05

Discussion

The fact that digital tools and screens surround the individual from all sides has made behavioral addictions inevitable. MSA, consisting of loss of control, compulsive behavior, and excessive screen time, has become one of the most critical behavioral addiction phenomena of recent years [102]. There seems to be insufficient scientific research to understand the effects of this phenomenon on individuals and to carry out preventive studies. There is a need to examine this more, especially during a period such as adolescence, when identity construction and self-presentation are done through digital screens. In this context, the mediating role of psychological flexibility and psychological vulnerability in the relationship between MSA and DAS in adolescents was examined in the study. The study's first finding showed that MSA in adolescents has a significant positive effect on DAS (confirmed H1). This finding indicates that adolescents addicted to multiple screens are likely to experience depression, anxiety, and stress. In other words, excessive use of any digital screen causes adolescents to lose control and exhibit compulsive behavior, leading to increased depression, anxiety, and stress levels. It is known that behavioral addictions such as internet addiction, smartphone addiction social media addiction and short video addiction have significant positive relationships with DAS [110–114]. These studies support previous findings and reveal that MSA creates similar effects. This finding is consistent with behavioral theories of addiction. In particular, compulsive digital media use can negatively affect an individual's daily functionality, leading to increased levels of stress, anxiety, and depression. This theoretical framework can help us understand the mechanisms underlying the finding. Adolescents' subjective experiences and perceptions of digital screens may also determine the effects of DAS. For example, adolescents who believe that screen use increases social connections may experience different psychological consequences.

According to another study, MSA predicts psychological vulnerability (confirmed H2). This finding shows that as the individual's screen addiction increases, his psychological vulnerability also increases. It is known that adolescents who use multiple screens are exposed to cyber victimization [115, 116] and experience traumatic experiences [117, 118]. Previous studies have proved that the psychological vulnerability of adolescents who experience these negative experiences also decreases [119–121]. Considering that individuals with high levels of vulnerability attribute negative experiences to a fixed cause, feel worthless, and believe that there will be other negative experiences [88], previous studies have revealed that this is similar to the pathologies that occur in adolescents exposed to multiple screens. A study found that adolescents who used smartphones for more than four hours a day worsened indicators related to stress perception, sleep satisfaction, depressive symptoms, and suicide [122]. A different study concluded that more smartphone screen time may be associated with common underlying symptoms of multiple mental illnesses [123].

Considering that high psychological vulnerability predicts DAS (confirmed H3), the expected result was that MSA predicts DAS through psychological vulnerability. It has been proven that psychologically vulnerable adolescents, that is, weak resilience, are more likely to show mental health problems such as depression, anxiety, and stress [82, 124]. Indeed, psychological resilience, defined as the opposite of psychological vulnerability, is known to protect the mental health of individuals in challenging times [46, 125–128]. The findings of this study show that MSA increases psychological vulnerability and increases DAS levels in adolescents. In particular, screen addiction has been found to predict DAS by increasing psychological vulnerability. Adolescents' exposure to cyber victimization and traumatic experiences further increases their psychological vulnerability, which leads to mental health problems. These findings highlight the need to carefully manage digital media use and develop strategies to protect young people's digital health.

According to the study findings, MSA reduces psychological flexibility, while psychological flexibility also reduces DAS (confirmed H4, H5). As a matter of fact, the literature has found that behavioural addictions cause decrease of psychological flexibility [64]. Furthermore, it demonstrates that psychological flexibility plays a vital role in reducing DAS levels during adolescence. It has been found that high psychological flexibility reduces DAS symptoms by increasing adolescents' ability to cope with difficulties and maintain their psychological resilience. A study on this subject concluded that psychological flexibility predicts DAS [129]. Additionally, low psychological flexibility is a significant risk factor for depression, anxiety, and stress symptoms [130]. These findings confirm the mental health-improving effect of psychological flexibility and highlight that low psychological flexibility is a significant risk factor for DAS. Therefore, interventions to improve psychological flexibility in adolescents are of critical importance in the prevention and management of mental health problems. Based on the research results, it can be said that there are different ways to reduce adolescents' depression, anxiety, and stress levels, including lowering their screen addiction and psychological vulnerability and increasing psychological flexibility.

The study's main finding was that psychological vulnerability and flexibility fully mediated the relationship between MSA and DAS (confirmed H6, H7). According to these results, it appears that adolescents' addiction to the screen triggers mental health problems. The negative impact of psychological vulnerability can be mentioned in increasing these problems. However, it has been revealed that psychological flexibility positively affects reducing these problems. It follows that psychological flexibility, which positively affects the mental health of adolescents, should be increased, and psychological vulnerability should be reduced. MSA may affect DAS by increasing psychological vulnerability and reducing psychological flexibility. MSA may increase adolescents' psychological vulnerability. Increased psychological vulnerability may weaken adolescents' ability to cope with stress, which may increase DAS levels. Thus, psychological vulnerability is part of the relationship between MSA and DAS. Likewise, MSA may reduce adolescents' psychological flexibility. Decreased psychological flexibility may weaken adolescents' ability to cope and recover from difficulties, which may increase DAS levels. In this case, psychological flexibility also influences the relationship between MSA and DAS. When considering the full mediation effect, it indicates that the entire impact of MSA on DAS is not explained through psychological vulnerability and flexibility. Still, these two variables play an essential role. In conclusion, part of the impact of MSA on DAS occurs through psychological vulnerability and flexibility.

Limitations and strengths

As in every research, this scientific study also has some limitations. First, being a cross-sectional study can be considered the main limitation. When the valuable results of this study are considered to contribute to the literature, the negative effect of the existing limitations can be reduced. The study sample was based on a specific demographic group or geographical region, so the results may need to be more generalizable to the general population. Different age groups, cultural backgrounds, or socioeconomic situations may influence the study's findings. In addition, abstract concepts such as psychological vulnerability, flexibility, and DAS may be challenging to measure, and the way these concepts are operationalized may affect the study's results. Since screen addiction and technological devices are constantly changing, the study's findings may need to be updated quickly. New technologies and social media platforms may affect the behaviors of the participants. The study may ignore other variables other than screen addiction that may have an impact on DAS. For example, factors such as family dynamics, school or work stress, and physical health may also affect DAS.

Despite these limitations, the originality of the study should be addressed. It brings a new perspective to the literature by examining the relationship between screen addiction and DAS. In particular, evaluating the effects of mediating variables such as psychological vulnerability and flexibility deepens the knowledge in this field. Testing a large number of hypotheses in the study provides a comprehensive picture of the effects of screen addiction on DAS and how psychological variables mediate these effects. The findings provide important insights for practical applications. For example, for educators, parents, and mental health professionals, understanding the relationships between multiple-screen addiction and DAS can help them develop intervention strategies. The study offers a multidisciplinary perspective at the intersection of various disciplines, such as psychology, communication, education, and health. This increases the applicability of the findings across a broader spectrum.

Conclusion

This study confirmed that MSA and DAS have a negative relationship with psychological flexibility and a positive relationship with psychological vulnerability. As the participants' MSA increased, their DAS levels also increased. However, as psychological flexibility levels increased, multiple-screen addiction and DAS levels decreased. It also revealed significant findings by examining the direct and indirect effects of MSA on depression, anxiety, and stress (DAS). Our research shows that MSA has a direct effect on DAS and that this effect is also mediated indirectly through psychological vulnerability and flexibility. This suggests that intensive screen use may have direct adverse effects on mental health. MSA was also found to have essential effects on psychological vulnerability and flexibility. In particular, psychological vulnerability had a direct effect on DAS, while psychological flexibility was found to reduce the adverse effects of DAS. Psychological vulnerability and flexibility mediate the relationship between MSA and DAS, revealing the complexity of this relationship. These psychological factors shape the indirect effects of MSA on DAS.

In terms of theoretical and practical contribution, it helps us better understand the relationships between screen addiction and mental health. The study makes significant contributions to the literature in this field by expanding the theoretical frameworks regarding screen addiction. It can also offer practical guidance for educators, parents, and mental health professionals, helping them develop strategies to reduce the adverse effects of screen addiction among youth. The findings of this study open several avenues for future research. First, it is essential to test the generalizability of the findings by conducting similar studies on different demographic groups. Additionally, examining changes over time and long-term effects by conducting longitudinal studies will help us understand the lasting effects of screen addiction on mental health. Finally, experimental studies are needed to evaluate the effectiveness of intervention and prevention programs.

Authors’ contributions

NT contributed to the conception and design of the study. HB performed data collection and analysis. OY wrote the first draft of the manuscript, and all authors commented on previous versions. All authors read and approved the final manuscript.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Data availability

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

Declarations

Ethics approval and consent to participate

This study adhered to the ethical principles outlined in the Declaration of Helsinki. Ethical approval for this research was obtained from the Siirt University Ethics Committee. (Approval Number: 599, Date: 03.05.2023). Informed consent was obtained from all individual participants included in the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.