The moderating role of digital addiction in the effect of digital literacy on life satisfaction in amateur athletes

Abstract

Purpose

This study examines the moderating role of digital addiction in the effect of digital literacy on the life satisfaction of amateur athletes.

Method

A correlational survey was conducted with 320 amateur athletes (151 male, 169 female) aged 15–38 from Osmaniye province, Turkey. Three validated scales measured digital literacy (α = 0.892), digital addiction (α = 0.890), and life satisfaction (α = 0.761). Data were analyzed using descriptive statistics, Pearson correlations, regression, and moderation analyses with PROCESS Macro Model 1.

Results

Digital literacy positively correlated with life satisfaction (r = .25, p < .01), while digital addiction negatively correlated with life satisfaction (r = − .24, p < .01). No significant relationship existed between digital literacy and digital addiction. Moderation analysis revealed that digital addiction partially moderates the relationship between digital literacy and life satisfaction (interaction term: β = 0.12, p = .06). Johnson-Neyman analysis indicated that when digital addiction levels exceed 1.30, the positive effect of digital literacy on life satisfaction becomes statistically significant.

Conclusion

Digital literacy enhances life satisfaction among amateur athletes, whereas digital addiction has detrimental effects. As digital literacy levels increase, life satisfaction improves. Educational institutions should integrate digital literacy programs with wellness strategies. Policymakers should establish guidelines for healthy technology use, while practitioners should create balanced intervention programs.

Introduction

This study is grounded in the Technology Acceptance Model (TAM), Social Cognitive Theory (SCT) and Self-Determination Theory (SDT). TAM posits that technology adoption depends primarily on perceived usefulness and ease of use, with digital literacy representing ease of use and life satisfaction reflecting perceived benefits [1]. SCT emphasizes reciprocal interactions among personal factors, environmental influences, and behaviors, providing a theoretical framework for understanding how digital addiction moderates the relationship between digital competence and life satisfaction [2]. According to SDT, digital literacy satisfies three basic psychological needs—autonomy, competence, and relatedness thereby enhancing life satisfaction [3]. Digital literacy enables autonomous navigation of digital environments, fosters competence through skill mastery, and facilitates relatedness via social connections. Recent empirical evidence supports this theoretical framework in athlete populations: Özsarı and Görücü [4] found that digital literacy positively affected life satisfaction among 139 judo athletes, while a study of 224 university athletes demonstrated a moderate positive correlation between digital literacy and mental well-being. These findings provide the empirical basis for our hypothesis that recreational athletes’ digital literacy levels are positively associated with their life satisfaction. These theoretical perspectives collectively support examining how recreational athletes’ technological competencies influence well-being, particularly when moderated by problematic usage patterns [5, 6].

For recreational athletes specifically, digital literacy represents enhanced technological competence that enables effective utilization of sport-related digital resources [7, 8]. According to TAM, when athletes perceive digital tools as user-friendly, they experience greater perceived benefits from technology use, leading to enhanced satisfaction with their athletic experience and overall quality of life [1, 5]. In the athletic context, this manifests through improved access to evidence-based training methodologies, real-time performance analytics, nutritional guidance, and peer support networks via digital platforms [9, 10].

The integration of these theoretical perspectives provides a comprehensive framework for examining how recreational athletes’ digital competencies influence their well-being when moderated by potentially problematic usage patterns. Previous research supporting this theoretical approach includes studies by Venkatesh and Davis (2000) [5], who extended TAM to include social influence factors, and LaRose et al. (2003) [6], who applied SCT to understand problematic internet use behaviors.

The rapid evolution of technology has arguably made digital tools essential, particularly for young people who encounter both opportunities and challenges in the digital environment [11, 12]. Modern society has become increasingly technology-dependent, requiring citizens to develop digital literacy skills [13, 14]. Digital literacy encompasses cognitive, motor, sociological, and emotional competencies needed to function effectively in digital environments [15]. It is defined as the ability to access accurate information in the digital world, critically evaluate this information, and engage in healthy interactions on digital platforms [7].

Athletes with high levels of digital competence are more likely to engage consciously with social media and other digital platforms, utilize digital resources efficiently, and resist digital addiction [8]. Digital literacy is also characterized as a process that enables individuals to reflect on their agency in life situations and engage in meaningful social actions [16].

For recreational athletes, digital competence serves not only educational or social purposes but also enhances athletic performance. Through digital tools, athletes can monitor their training and physical performance while interacting with professional athletes [9]. Recreational athletes with higher digital literacy demonstrate enhanced capabilities in: (a) accessing professional training protocols and expert knowledge through specialized applications and platforms [7, 9], (b) maintaining motivation through gamified fitness applications and achievement sharing [6], (c) building supportive communities through online athletic networks and forums [17], (d) monitoring progress through wearable technology and performance tracking applications [10], and (e) receiving real-time feedback from coaches and peers through digital communication tools [18]. These digital competencies create pathways for improved athletic experiences, enhanced self-efficacy, and ultimately higher life satisfaction [19].

The growing prevalence of digital addiction among individuals has become increasingly concerning. Excessive exposure to social media platforms or various internet technologies is directly linked to digital addiction, and excessive use can lead to psychological and physical health issues [20]. Among recreational athletes specifically, digital addiction can transform internet use into a source of stress, disrupt training routines, and diminish life values [21]. Digital addiction adversely affects athletes’ social, psychological, and physical health, undermines collaboration, and deteriorates quality of life, leading to significantly decreased life satisfaction [22]. This situation can result in poorer performance and reduced quality of life [23].

Digital addiction among recreational athletes can manifest as excessive time spent on social media comparing performance with others, compulsive checking of fitness applications that disrupts training focus, or problematic gaming behaviors that interfere with sleep and recovery [24, 25]. This excessive digital engagement can create psychological stress, reduce present-moment awareness during training, and lead to unhealthy social comparisons that diminish intrinsic motivation for athletic participation [21, 22].

Understanding these negative impacts of digital addiction becomes particularly important when examining their effects on overall well-being. Life satisfaction is a critical concept that reflects how individuals evaluate their lives and experiences. Life satisfaction pertains not to contentment with specific situations but rather encompasses satisfaction derived from all life experiences as a whole [26]. Research suggests that life satisfaction positively contributes to an individual’s resilience against life’s challenges [27]. Individuals with high life satisfaction generally tend to lead healthier and more balanced lives [24, 28]. Furthermore, quality of life encompasses perceptions of physical and mental health as well as satisfaction derived from life itself.

Given the increasingly prominent role of digital technologies in daily life, understanding their impact on individual life satisfaction is crucial [29]. Athletes with high levels of digital literacy are more likely to engage consciously with the digital world, protect themselves from the negative effects of digital addiction, and consequently achieve higher life satisfaction [30]. Therefore, enhancing digital literacy can help athletes utilize opportunities in the digital world more healthily to improve life satisfaction [10, 19]. Additionally, combating digital addiction and achieving balance in the digital world can also contribute to increasing athletes’ life satisfaction [25].

Research in sports psychology indicates that technology-mediated interventions enhance athlete motivation, performance tracking, and social connectivity [7, 9]. Athletes who effectively utilize digital platforms report higher levels of training adherence, goal achievement, and social support satisfaction [10, 31]. The integration of digital literacy skills with athletic pursuits creates opportunities for enhanced performance feedback, community connection, and personal development that contribute to overall life satisfaction [17, 19].

In this context, digital literacy enables athletes to utilize opportunities in the digital world more healthily, thereby improving their quality of life [17]. Conversely, combating digital addiction and maintaining balance in the digital world can contribute to increasing athletes’ life satisfaction [18]. Digital literacy is defined as the ability to use digital tools effectively and safely, while digital addiction is characterized as the excessive use of digital technology, creating negative psychological, social, and physical health impacts [32].

Recreational athletes, defined as individuals who are not professionals but engage in regular physical activity, experience different dynamics in their relationships with the digital world [33, 34]. Therefore, understanding how recreational athletes interact in the digital world, the impact of their digital literacy levels on life satisfaction, and their skills in combating digital addiction form the core focus of this study. This research aims to examine the relationship between digital literacy, digital addiction, and life satisfaction specifically among recreational athletes.

Hypothesis development

The rapid advancement of the digital age has intensified individuals’ interactions with the digital world, thereby increasing the significance of concepts such as digital literacy and life satisfaction [35, 36].

Digital literacy encompasses individuals’ ability to use digital technologies effectively, including accessing information through these technologies, applying critical thinking, and demonstrating ethical behaviors. The hypothesis that digital literacy positively influences individuals’ life satisfaction represents an important research question [37].

The theoretical foundation for this relationship can be traced to the Technology Acceptance Model, which suggests that when individuals perceive digital tools as useful and easy to use, they experience greater benefits from technology adoption [35]. For recreational athletes specifically, digital literacy creates pathways to improved life satisfaction through better access to training resources, performance monitoring tools, and supportive online communities [36].

Studies conducted by Yılmaz and Yiğit [38], Holm [30], and Audrin and Audrin [39] demonstrate that digital literacy levels are associated with social interaction and personal development, consequently increasing life satisfaction. In the athletic context, digitally literate athletes can more effectively utilize training applications and evidence-based methodologies, contributing to overall well-being [35, 36]. Based on this evidence, the first hypothesis is formulated as follows:

• H₁: Digital literacy (DigLit) positively affects life satisfaction (LifeSat).

The rapid technological advances brought by the digital age have led to radical changes in almost every aspect of our lives. Although these changes offer many advantages, they have also caused individuals to face new problems such as digital addiction. Digital addiction can be defined as excessive and uncontrolled use of the internet and digital devices, which can negatively affect individuals’ social, academic and professional lives.

Many studies have shown that digital addiction negatively affects life satisfaction. In a study conducted at the sports science’s faculty of a university, it was found that the level of digital addiction decreased life satisfaction [40]. Similarly, in a study conducted on 670 sport sciences students from different universities, it was observed that digital addiction negatively affected life satisfaction [41]. In addition, in another study, individuals with internet and smartphone use disorder were found to have lower empathy and life satisfaction [42]. These findings clearly reveal that digital addiction negatively affects life satisfaction and the second hypothesis is as follows.

• H₂: Digital addiction (DigAdd) negatively affects life satisfaction (LifeSat).

While digital literacy refers to individuals’ ability to use digital tools effectively and consciously, life satisfaction reflects individuals’ level of satisfaction with their lives [35]. However, negative effects such as digital addiction (DigAdd) can change individuals’ life satisfaction and the effect of digital literacy on this satisfaction [43]. In the study conducted by Kang et al. [35], it was shown that digital addiction negatively affects life satisfaction. Similarly, Taşkın and Ok [36] found that digital literacy positively affected life satisfaction. In addition, Çiftçi and Yıldız [43] suggested that digital addiction moderates the relationship between digital literacy and life satisfaction. In this context, the third hypothesis was formed as follows.

Digital literacy refers to individuals’ capacity to use technology consciously and effectively, and it has the potential to create positive effects on life satisfaction [15]. However, the strength of this positive effect may vary depending on the degree of individuals’ dependence on using digital platforms. Indeed, research shows that digital addiction has negative effects on psychological well-being and life satisfaction [25].

A study conducted in South Korea showed that the positive effect of digital literacy on life satisfaction weakened in the presence of problematic smartphone use. Furthermore, it was found that while the impact of digital literacy strengthened in the post-pandemic period, the negative effects of addiction became more pronounced [36]. Therefore, digital addiction can be conceptualized as a moderating variable that directs the relationship between digital literacy and life satisfaction.

• H₃:Digital addiction (DigAdd) moderates the relationship between digital literacy (DigLit) and life satisfaction (LifeSat).

Based on the literature review and the purpose of the study, the research model was developed as follows (Fig. 1).

Fig. 1.

Research Model

Method

Sample

Amateur athletes represent a critical population for examining digital wellness due to their independence in technology adoption decisions, unlike professional athletes with structured support systems. This population constitutes the majority of sporting participants globally and experiences unique digital behavior patterns at the intersection of recreational athletics and autonomous technology use. Their susceptibility to both benefits and risks of digital technologies provides an optimal context for examining moderating effects between digital literacy and life satisfaction.

We utilized convenience sampling; a non-probability sampling method commonly used in social science research due to its practicality and ease of access to participants [44]. The sample consists of 320 voluntary participants of various ages and genders engaged in amateur sports in Osmaniye Province.

Participants’ ages ranged from 15 to 38 years (M = 19.84, SD = 5.69, median = 19), with the following age group distribution: 15–18 years (n = 153, 47.8%), 19–25 years (n = 103, 32.2%), 26–30 years (n = 44, 13.8%), and 31–38 years (n = 20, 6.3%). Among them, 151 (47.2%) were male, and 169 (52.8%) were female. Their duration of involvement in amateur sports ranged from 1 to 15 years (M = 4.98, SD = 3.15, median = 4), with sport experience groups distributed as follows: 1–5 years (beginner level) 210 participants (65.6%), 6–10 years (intermediate level) 91 participants (28.4%), and 11–15 years (experienced) 19 participants (5.9%). Among participants, 85.3% (n = 273) engaged in team sports while 14.7% (n = 47) participated in individual sports. Sport branch distribution was: volleyball 106 participants (33.1%), football 100 participants (31.3%), basketball 44 participants (13.9%), wrestling 24 participants (7.5%), hockey 25 participants (7.6%), and swimming 21 participants (6.6%).

Permission for the survey was obtained from the Scientific Research Ethics Committee of Graduate Education Institute, Osmaniye Korkut Ata University (Approval Code: 2024/9, Date: 2024.10.18). For participants under 18 years of age, parental consent and participant assent were obtained.

A priori power analysis using G*Power 3.1.9.4 [45] determined the minimum sample size for moderation analysis in multiple regression. Assuming medium effect size (f² = 0.15), α = 0.05, and power = 0.80 for detecting the interaction effect between digital literacy and digital addiction on life satisfaction, a minimum of 55 participants was required for the tested predictor with 3 total predictors in the model. The final sample (N = 320) substantially exceeded this requirement, ensuring adequate statistical power for hypothesis testing and moderation analysis.

Data collect tools

Digital Literacy:A 17-item, unidimensional scale developed by Avinç and Doğan [46] was used to measure digital literacy. The scale demonstrated high internal consistency (Cronbach’s alpha = 0.87) and construct validity, as confirmed by CFA results (CFI = 0.95, RMSEA = 0.06). These psychometric properties support its reliability and validity in higher education settings The scale employs a 5-point Likert format (1 = Strongly Disagree to 5 = Strongly Agree) and has a Cronbach’s Alpha (α) coefficient of.892. During factor analysis, one item with low factor loading was excluded from the scale.

Digital Addiction: A 10-item, unidimensional scale developed by Seema et al. [24] was used to measure digital addiction. The scale showed strong psychometric properties, with a Cronbach’s alpha of 0.91 and test-retest reliability of 0.87. The scale’s unidimensional construct was validated using both EFA and CFA procedures, demonstrating good model fit (CFI = 0.96, RMSEA = 0.05). This scale also employs a 5-point Likert format (1 = Never to 5 = Always) and has a Cronbach’s Alpha (α) coefficient of .890 for this study.

Life Satisfaction: To evaluate life satisfaction, the scale developed by Lavallee et al. [47] and adapted into Turkish by Akın and Yalnız [48] was used. This is a 5-item, unidimensional scale that measures global life satisfaction through overall evaluation of life circumstances and contentment with current life activities. The scale assesses general life satisfaction rather than domain-specific well-being, focusing on individuals’ comprehensive evaluation of their life quality and fulfillment. Sample items include evaluations of satisfaction with current life activities and overall life contentment. The scale is formatted in a 5-point Likert style (1 = Strongly Disagree to 5 = Strongly Agree). The original scale demonstrated strong psychometric properties with internal consistency (Cronbach’s alpha = 0.87) and construct validity confirmed through factor analysis. In the Turkish adaptation study, the scale showed acceptable reliability (Cronbach’s alpha = 0.73) and construct validity through confirmatory factor analysis. For this study, the scale has a Cronbach’s Alpha (α) coefficient of 0.76.

Statistical analysis

To analyse the data based on the research model and hypotheses, correlation, regression, and moderation analyses were conducted. Moderation analysis was conducted using the PROCESS Macro model 1 for SPSS proposed by Hayes [49]. Assessing the normality of data is crucial in statistical analysis, as many parametric tests assume that variables follow a normal distribution. Skewness and kurtosis values were calculated to assess deviations from normality. Skewness and kurtosis values between − 2 and + 2 were considered acceptable for normality [50]. Since the obtained data were within this range and showed a normal distribution, advanced parametric tests were subsequently conducted.

Result

As shown in Table 1, skewness and kurtosis values were within the ± 2 range, indicating that the variables demonstrated normal distribution.

Table 1.

Descriptive statistics and normality test results for study variables

Variable	Skewness		Kurtosis		Kolmogorov-Smirnov	Shapiro-Wilk
	S	SE	K	SE	D	W
DigLit	−0.70	(0.14)	0.90	(0.27)	0.07***	0.97***
DigAdd	0.56	(0.14)	0.11	(0.27)	0.09***	0.97***
LifSat	−0.33	(0.14)	1.25	(0.27)	0.11***	0.97***

N = 320. S = Skewness; K = Kurtosis; SE = Standard Error; D = Kolmogorov-Smirnov test statistic; W = Shapiro-Wilk test statistic. **p <.001

Table 2 the findings of descriptive statistics and correlation analysis between the scales used in the study are presented. Pearson’s correlation coefficients were computed to explore the relationships among life satisfaction, digital literacy, and digital addiction. Correlations were interpreted using Cohen’s [51] guidelines, categorizing effects as small (r =.10), medium (r =.30), and large (r =.50). Statistical significance was assessed at the conventional threshold of p <.05. The averages of the variables indicate that participants have low digital addiction levels, while their digital literacy and life satisfaction levels are slightly above average. Correlation analysis results show no significant relationship between digital literacy and digital addiction. However, there is a positive relationship between digital literacy and life satisfaction (r =.25; p <.01) and a negative relationship between digital addiction and life satisfaction (r = −.24; p <.01).

Table 2.

Means, standard deviation and correlations between variables

	Means	SD	DigLit	DigAdd	LifSat
DigLit	3,71	0,73	1
DigAdd	2,49	0,95	−0,05	1
LifSat	3,49	0,92	0,25**	−0,24**	1

**. Correlation is significant at the 0.01 level (2-tailed)

In order to verify the moderating effect of digital addiction on the relationship between digital literacy and life satisfaction, it was analyzed according to the procedure of PROCESS Macro model 1 for SPSS proposed by Hayes [49]. Bootstrap was used for verification, the confidence interval was 95%, and the number of samples was 5000. Prior to the analysis, assumptions of linearity and multicollinearity were assessed using Variance Inflation Factors (VIFs). VIF values below 5 are generally considered acceptable, with values above 10 indicating problematic multicollinearity. The VIF values for Digital Literacy (1.039) and Digital Addiction (1.039) were well below the threshold, indicating no multicollinearity concerns. Additionally, the Durbin-Watson statistic (1.951) was within the acceptable range (1.5–2.5), confirming independence of residuals and indicating no autocorrelation issues in the model.

The model summary for the moderation analysis is presented in Table 3. As shown in Table 3, looking at the regression coefficients, the effect of the digital literacy variable on life satisfaction is not significant (b = 0.06, p =.75). This indicates that, without considering any level of digital addiction, the effect of digital literacy on life satisfaction is generally not statistically significant. In contrast, the main effect of the digital addiction variable is statistically significant (b = − 0.69, p =.01). As seen in the table, digital addiction has a moderating effect on the relationship between digital literacy and life satisfaction.

Table 3.

Moderating effect of digital addiction

Model	β	SE	t	p	F	R 2	∆R2
DigLit	0,06	0,18	0,32	0,75
DigAdd	−0,69	0,25	−2,74	0,01
DigLit × DigAdd	0,12	0,06	1,90	0,06	1,32	0,14	1

The most important finding in the study is the interaction term between digital literacy and digital addiction (DigLit x DigAdd). The coefficient of the interaction term (β = 0.12) and its corresponding p-value (p =.06) are marginally significant. This finding shows that the effect of digital literacy on life satisfaction varies according to different values of digital addiction. The F test results (F = 1.32, p =.06) support the statistical significance of the interaction.

The next step was to analyze the conditional effects of on digital literacy according to the level of digital addiction, and the results are shown in Table 4. The digital addiction level was given as three conditions (+ 1 SD, −1 SD), and the effects of digital literacy concern were all significant. In other words, the lower the digital addiction, the higher the effect of digital literacy concern on life satisfaction.

Table 4.

Conditional effects of digital literacy concern at values of digital addiction

Digital Addiction Level	Effect	SE	t	p	LLCI	ULCI
1,55	0,25	0,10	2,53	0,01	0,05	0,44
2,51	0,36	0,07	5,15	< 0.001	0,22	0,50
3,48	0,48	0,09	5,32	< 0.001	0,30	0,66

LLCI = The lower bound within the 95% confidence interval; ULCI = The upper bound within the 95% confidence interval

The Johnson-Neyman technique is used to determine at which values of the moderator variable the effect of the independent variable becomes statistically significant. As shown in Table 5, the threshold value for digital dependency is 1.30. According to this threshold value, when the digital dependency value is greater than 1.30 (90.31% of the sample), the positive effect of digital literacy on life satisfaction is statistically significant (p <.05). This finding indicates that at high levels of digital addiction, an increase in digital literacy leads to a significant increase in life satisfaction.

Table 5.

Digital addiction value defining Johnson-Neyman significance region

Digital Addiction	Digital Literacy	t	p
1,00	0,18	1,44	0,15
1,20	0,20	1,78	0,08
1,30	0,22	1,97	0,05
1,40	0,23	2,19	0,03
1,60	0,25	2,65	0,01
2,00	0,30	3,76	0,00
2,51	0,36	5,15	0,00
3,48	0,48	5,32	0,00
5,00	0,67	3,92	0,00

Finally, the result of visualizing the effect of digital literacy concern on life satisfaction according to digital addiction level is shown in Fig. 2. The graph shows how the relationship between digital literacy and life satisfaction changes at low, medium, and high levels of digital addiction. The graph shows that an increase in digital literacy leads to a steeper increase in life satisfaction at high levels of digital addiction, while at low levels of digital addiction, the slope becomes less steep or insignificant, indicating that the relationship weakens or disappears.

Fig. 2.

Interaction Graph

Discussion

Results support our theoretical framework. The positive digital literacy-life satisfaction relationship aligns with TAM’s premise that ease of use leads to positive outcomes. Social Cognitive Theory explains how digital addiction (personal factor) moderates this relationship through self-regulatory capabilities.

The findings of the research reveal a positive relationship between digital literacy and life satisfaction (r =.25; p <.01), indicating that digital literacy enhances the quality of life among amateur athletes. This can be attributed to amateur athletes’ ability, through digital literacy, to access training techniques, nutrition programs, and health information more easily, thereby improving their performance and overall health, which ultimately increases their life satisfaction. Additionally, using digital tools to connect with sports communities, strengthen social bonds, share achievements in the digital world, boost motivation, and reinforce self-confidence may contribute to their sense of happiness. Many studies in the literature support our findings.

Lee [37] identified a significant positive correlation between digital literacy and life satisfaction in their study on this topic. Fris [52] found that digital competence had a significant positive effect on life satisfaction in their research on the digital age and life satisfaction. Jang and Jee [53] reported a positive relationship between digital media literacy and quality of life in their study on digital literacy and quality of life. Sagong and Yoon [31] observed that participants in their study displayed significant and positive effects of smartphone usage levels on life satisfaction. Bae [54] found a positive relationship between digital literacy and life satisfaction in a study involving older adults. These findings demonstrate that increased digital literacy levels contribute to individuals’ ability to use digital tools more consciously and effectively. Bayrakçı [55] also found that digital literacy skills positively impacted life satisfaction.

Similarly, Ng [17] reported that digital literacy levels had a positive effect on life satisfaction. This study highlighted that digital literacy improves individuals’ access to information and enhances social interactions, thereby increasing life satisfaction. Livingstone and Helsper [56] indicated that higher levels of digital literacy help individuals manage digital risks more effectively, contributing to improved life satisfaction.

Age-Specific considerations

Our 15–38 age demographic represents “digital natives” with unprecedented technology exposure. For amateur athletes in this group, digital technologies serve multiple functions: performance monitoring, social connectivity, training resources, and online community participation. Research indicates young adult athletes show higher digital engagement but increased addiction vulnerability compared to older athletes, making digital literacy a crucial protective factor.

Contribution to amateur athlete research

This study contributes to digital wellness literature by examining amateur athletes, who navigate digital environments independently unlike professional athletes with structured support systems. Our findings reveal that amateur athletes’ dual identity as competitive yet recreational participants create distinct intervention needs. These results directly inform sport-specific digital literacy curricula and targeted addiction prevention programs within recreational sports organizations. Additionally, findings suggest policy implications including mandatory digital wellness components in sports facility regulations and funding priorities for technology-mediated interventions in amateur sports contexts.

Our research identified a negative relationship between digital addiction and life satisfaction (r =-.24; p <.01). Amateur athletes who spend a significant portion of their time online due to digital addiction may lack sufficient time for essential activities such as training, rest, and social interaction. This can adversely affect their performance and physical health, leading to reduced life satisfaction. Digital addiction can also result in social isolation, sleep disturbances, sedentary lifestyles, and mental fatigue, all of which can diminish overall life satisfaction. Moreover, the stress and distractions caused by constant online engagement can hinder focus in sports, block feelings of accomplishment, and lead to greater restlessness, further lowering general life satisfaction. This finding aligns with other studies in the literature highlighting the adverse effects of digital addiction on quality of life.

Gökmen and Batmaz [57] found that as internet addiction increases, life satisfaction decreases, and vice versa. Agaj [58] observed a negative relationship between internet addiction and life satisfaction in a study involving students. İlk and Güler [40] demonstrated the relationship between digital addiction and life satisfaction in their study, confirming the connection. Çiftçi and Yıldız [43] concluded that higher levels of social media addiction result in reduced life satisfaction in their research on social media addiction, happiness, and life satisfaction. Garvanova [59] also identified that increased internet addiction leads to decreased life satisfaction. Hawi and Samaha [60] reported that higher levels of digital addiction in university students negatively impacted their psychological health and life satisfaction. Kuss and Griffiths [25], in a meta-analysis, revealed the detrimental psychological effects of digital addiction, which ultimately reduced life satisfaction.

The study found no significant relationship between digital literacy and digital addiction, suggesting that digital literacy education alone has limited direct effects on digital addiction. This could be because digital literacy enhances individuals’ ability to use technology effectively but does not directly address the fundamental psychological and behavioural causes of addiction. Digital literacy teaches how to use tools but may not strengthen the self-discipline skills needed to prevent excessive and uncontrolled use of these tools. Similar findings exist in the literature supporting these results.

Singh [61] found no significant relationship between digital literacy and internet addiction in their study. Kul [32] concluded that digital literacy courses did not statistically impact internet addiction among students. Canan et al. [62] also reported no significant relationship between digital literacy and internet addiction among university students. These findings underscore the limited direct effects of digital literacy education on preventing digital addiction, emphasizing the need for more comprehensive strategies. Therefore, combating digital addiction may require more than digital literacy education; it may also necessitate psychological support, time management, and the development of social skills.

The regression analysis findings of the study indicate that digital addiction has a partially moderating effect on the relationship between digital literacy and life satisfaction. While there are no studies in the literature directly supporting this finding, there are studies that partially align with it. Yakut et al. [63] found a negative correlation between digital addiction and life satisfaction. According to these findings, as digital addiction increases, life satisfaction decreases. Research by Choi and Song [64] and Yeon and Choi [65] on digital literacy suggests that digital literacy positively affects individuals’ life satisfaction. Based on these results, it can be said that digital addiction partially moderates the relationship between digital literacy and life satisfaction.

From a broader perspective, conducting more holistic studies that explore individuals’ relationships with the digital world and the impact of these factors on their overall mental states is crucial. While the findings indicating the positive effects of digital literacy education on life satisfaction are encouraging, the insufficiency of digital literacy in reducing digital addiction underscores the necessity for developing more complex and multifaceted strategies.

Several alternative explanations merit consideration for our findings. First, cultural context may significantly influence the relationships observed, as Turkey’s collectivistic culture and specific social media usage patterns may differ from Western individualistic contexts where most digital wellness research originates [66]. The strong family-oriented values in Turkish culture might buffer against digital addiction effects or enhance the benefits of digital literacy through social support mechanisms [67].

Second, self-report measurement bias represents another consideration, as participants may underreport addiction symptoms due to stigma or overestimate their digital competencies to appear socially desirable [68]. The social desirability bias could particularly affect amateur athletes who may feel pressure to present themselves as disciplined and controlled [69].

Third, reverse causality cannot be ruled out given our cross-sectional design [70]. Higher life satisfaction might predispose individuals to develop better digital literacy skills through increased motivation and positive engagement with learning technologies. Similarly, individuals with lower life satisfaction might be more prone to develop addictive behaviors as coping mechanisms [71].

Finally, unmeasured third variables such as personality traits (conscientiousness, emotional stability), socioeconomic status, or pre-existing mental health conditions could confound the observed relationships, suggesting the need for more comprehensive models in future research [72].

Practical implications

Sports organizations should prioritize digital wellness through mandatory workshops during registration, peer mentorship programs, and phone-free training zones. Developing sport-specific apps with usage monitoring and installing digital wellness resources in facilities can create supportive environments for healthy technology use.

Coaches and trainers need tools to assess and monitor athletes’ digital habits through quarterly screenings and weekly check-ins. Annual training on recognizing digital addiction warning signs (sleep disruption, performance decline, social withdrawal) enables early intervention. Clear social media policies and boundaries between performance monitoring and recreational use help maintain focus.

Policymakers can mandate digital wellness components in facility licensing, fund technology impact research, and create evidence-based guidelines for amateur sports. Standardized certification programs for sports personnel and digital wellness requirements in physical education curricula ensure systematic implementation.

Healthcare professionals should integrate digital addiction screening into routine assessments using validated instruments. Sport-specific intervention protocols, specialized training programs, and referral networks with digital addiction specialists provide comprehensive support. Educational materials addressing technology’s impact on sleep, performance, and recovery help athletes make informed decisions. These evidence-based interventions can help amateur athletes maximize digital literacy benefits while minimizing addiction risks, ultimately supporting their overall life satisfaction and athletic performance.

Future research directions

Researchers should:

• - Conduct longitudinal studies establishing causal relationships.

• - Investigate cultural variations across sporting contexts.

• - Develop integrated interventions enhancing literacy while preventing addiction.

• - Examine specific platform effects on athlete well-being.

Practitioners should:

• - Design comprehensive digital wellness programs for sports organizations.

• - Create athlete-specific digital literacy curricula.

• - Implement screening tools for at-risk individuals.

• - Establish interdisciplinary partnerships addressing digital wellness.

Limitations

The limitations of this study include convenience sampling constraints, cross-sectional research design, participant bias, cultural factors and technological changes. Firstly, the use of convenience sampling from Osmaniye province limits external validity and generalizability. The sample may not represent amateur athletes from different socioeconomic backgrounds, urban-rural contexts, or varying digital engagement levels across Turkey or internationally. Athletes with higher digital comfort may have been more likely to participate, creating potential selection bias. Regional variations in digital infrastructure and sports participation patterns further restrict generalizability.

Additionally, the demographically limited sample of the study may reduce the generalizability of the results obtained. Cross-sectional studies may make it difficult to monitor changes and cause-effect relationships over time. Participants’ subjectivity and lack of honesty in their responses may affect the accuracy of the results. Different interpretations of the concepts of digital literacy and digital addiction in different cultural contexts may create difficulties in interpreting the findings of the study. In addition, the rapid change of digital technologies may cause the findings of the study to lose validity in a short time.

For future studies, it is recommended to use stratified random sampling across multiple regions and socioeconomic groups, to conduct longitudinal studies and to examine cultural differences. Considering the speed of technological changes, research in this field should be kept up-to-date. In addition, intervention and implementation studies evaluating the effectiveness of strategies to increase digital literacy and reduce digital addiction should be conducted. These recommendations can help us better understand the effects of digital literacy and digital addiction on life satisfaction by making research more comprehensive and effective.

Conclusion

In conclusion, the findings of this study are believed to contribute both theoretically and practically. The primary theoretical contribution of the research is demonstrating that while digital literacy positively influences life satisfaction in today’s rapidly digitalizing world, digital addiction has a negative impact. Additionally, digital addiction plays a moderating role in the relationship between digital literacy and life satisfaction. In other words, digital addiction partially reduces the positive effect of digital literacy on life satisfaction.

The practical contribution of the study is the observation that as digital literacy levels increase, life satisfaction also increases, whereas digital addiction decreases life satisfaction. Therefore, it is recommended that individuals engage in activities to enhance their digital literacy levels and reduce the use of digital tools that could lead to addiction in order to achieve adequate life satisfaction.

Abbreviations

TAM

Technology Acceptance Model

SCT

Social Cognitive Theory

SDT

Self-Determination Theory

DigLit

Digital Literacy

LifeSat

Life Satisfaction

DigAdd

Digital Addiction

VIFs

Variance Inflation Factors

Authors’ contributions

Conceptualization, S.O., B.K., M.E., O.S.U., M.F.C., and A.E.,; methodology, S.O., B.K., M.E., O.S.U M.F.C., and A.E.,; formal analysis, S.O., B.K., M.E., O.S.U., M.F.C., and A.E.,; validation S.O., B.K., M.E., O.S.U M.F.C., and A.E.,; investigation, S.O., B.K., M.E., O.S.U., M.F.C., and A.E.,; resources, M.E., O.S.U., and M.F.C.; writing—original draft preparation, S.O., B.K., M.E., O.S.U., and M.F.C.,; writing—review and editing, S.O., B.K., M.E., O.S.U., M.F.C., and A.E.,; supervision, S.O., and M.F.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data availability

The datasets presented in this article are not readily available in order to protect the privacy and identities of the participants. Requests to access the datasets should be directed to [aerdogan@kmu.edu.tr](mailto: aerdogan@kmu.edu.tr).

Declarations

Ethics approval and consent to participate

This study has been reviewed and approved by the Scientific Research Ethics Committee of the Graduate School of Osmaniye Korkut Ata University (Approval Code: 2024/9, Date: 18 October 2024). All procedures were conducted in accordance with the principles of the Helsinki Declaration for medical research involving human subjects.

The Institutional Review Board determined that written informed consent was required for this study. Written informed consent was obtained from all participants aged 18 and above. For participants under 18 years, parental consent and participant assent were obtained in compliance with Turkish national legislation (Law No. 6698 on Protection of Personal Data). The consent procedures were deemed appropriate for this non-interventional survey research.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.