Adaptation of the Smartphone Addiction Scale in an Azerbaijani sample and its psychometric associations with distress, academic satisfaction, and subjective well-being

Context and relevance. In the modern world, smartphones have become an integral part of adolescents’ lives; however, their excessive use may negatively affect psychological well-being, social adaptation, and academic performance. At the same time, adequate assessment of this phenomenon is impossible without psychometrically sound instruments adapted to a specific cultural context, and it is precisely in this area that a noticeable gap is observed in most post-Soviet studies. Objective. To adapt and evaluate the psychometric properties of the English-language Smartphone Addiction Scale (SAS) for adolescents in Azerbaijan, as well as to examine its relationship with psychological distress, academic satisfaction, and subjective well-being. Rationale for variable selection. Previous studies have shown that the severity of smartphone addiction is associated with higher levels of psychological distress, lower academic satisfaction, and poorer subjective well-being among adolescents (Elhai et al., 2017; Kwon et al., 2013; Lachmann et al., 2018). These indicators reflect emotional and motivational aspects of functioning that are most sensitive to manifestations of addictive behavior in everyday life. Hypothesis. It was hypothesized that the Azerbaijani adaptation of the Smartphone Addiction Scale (SAS) would demonstrate strong psychometric properties and correspond to a one-factor structure. Smartphone addiction was expected to correlate positively with psychological distress and negatively with subjective well-being and academic satisfaction. Methods and materials. The study involved 470 adolescents aged 10 to 18 years (M = 13,51; SD = 2,15) residing in Azerbaijan. Results. The Azerbaijani version of the Smartphone Addiction Scale demonstrated satisfactory psychometric properties, confirming its applicability for assessing smartphone addiction among adolescents in this cultural context. Conclusions. The Smartphone Addiction Scale (SAS) can be considered a reliable instrument for assessing smartphone addiction in the adolescent population of Azerbaijan. Further research should examine in greater detail the impact of smartphone use on adolescents’ psychological well-being and social behavior.

Introduction

Adolescence is a sensitive developmental period during which social and digital environments exert an increasingly significant influence on psychological functioning. In recent years, smartphones have become an integral part of adolescents’ everyday lives, providing opportunities for communication, learning, and social integration. However, excessive smartphone use has been associated with an increased risk of behavioral addiction and impaired psychological well-being (Belfort, Miller, 2018; Elhai et al., 2017).

Contemporary research indicates that higher levels of smartphone addiction are associated with increased psychological distress, lower life satisfaction, and poorer academic functioning (Lachmann et al., 2018; Samaha, Hawi, 2016). These associations are particularly evident in contexts characterized by high levels of digital engagement, making this issue especially relevant for adolescents.

Studies conducted with Azerbaijani adolescent samples have also identified significant associations between indicators of psychological functioning and various emotional characteristics (Rustamov et al., 2023a).

Psychometric instruments developed within one cultural context require additional validation before being applied in different linguistic and cultural settings (Borsa et al., 2012). Among the available measures of smartphone addiction, the Smartphone Addiction Scale (SAS; Kwon et al., 2013) is one of the most widely used instruments and has demonstrated satisfactory psychometric properties across diverse cultural contexts.

Despite the growing interest in digital behavior among adolescents, research focused on the adaptation and validation of smartphone addiction measures in Azerbaijan remains limited. The absence of validated assessment tools restricts both scientific investigation and practical psychological assessment in this area.

Therefore, the primary aim of the present study was to adapt the Smartphone Addiction Scale (SAS) for use with Azerbaijani adolescents and to evaluate its psychometric properties. In addition, the study examined the relationships between smartphone addiction, psychological distress, academic satisfaction, and subjective well-being.

The study tested the following hypotheses:

1. The Azerbaijani version of the SAS will demonstrate satisfactory psychometric properties and support a unidimensional factor structure.
2. Smartphone addiction will be positively associated with psychological distress and negatively associated with subjective well-being and academic satisfaction.

Participants

The study included 470 adolescents aged 10 to 18 years (M = 13,51, SD = 2,15) residing in Azerbaijan. Participants were recruited using a convenience sampling method through an online survey. Of the respondents, 56,8% were female and 43,2% were male. Detailed demographic characteristics of the sample are presented in Table 1.

Measures

Smartphone Addiction Scale (SAS)

The Smartphone Addiction Scale (SAS; Kwon et al., 2013) is a 10-item self-report questionnaire rated on a 6-point Likert scale ranging from 1 (strongly disagree) to 6 (strongly agree). Higher total scores indicate greater levels of smartphone addiction. In the original study, the scale demonstrated excellent internal consistency (α = 0,91). For the present study, an Azerbaijani-language version was developed using a forward–backward translation procedure.

High-School Satisfaction Scale (H-Sat)

The High-School Satisfaction Scale (H-Sat; Lodi et al., 2019) consists of 20 items rated on a 5-point Likert scale and assesses several dimensions of satisfaction with the school environment, including quality of instruction, peer relationships, and the perceived importance of education for future goals. Internal consistency coefficients for the original subscales ranged from α = 0,85 to α = 0,91. The Azerbaijani adaptation of the scale, which demonstrated satisfactory validity and reliability, was used in the present study (Rustamov et al., 2023).

Children and Adolescents Psychological Distress Scale (CAPDS)

The Children and Adolescents Psychological Distress Scale (CAPDS; De Stefano et al., 2020) is a 10-item instrument rated on a 4-point Likert scale. It assesses psychological distress across four domains: depressive symptoms, anxiety, somatic complaints, and behavioral problems. The original version demonstrated good internal consistency (α = 0,86). In the present study, the Azerbaijani version validated among adolescents and showing satisfactory psychometric properties was employed (Aliyev et al., 2025).

Adolescent Subjective Well-Being Scale

The Adolescent Subjective Well-Being Scale (Eryılmaz, 2009) assesses adolescents’ subjective well-being through indicators of life satisfaction, interpersonal relationships, and positive affect. The original version demonstrated good internal consistency (α = 0,86). The Azerbaijani adaptation of the scale was used in the current study.

Adaptation procedure

All instruments were translated into Azerbaijani using a standardized forward–backward translation procedure. First, the original versions of the scales were translated into Azerbaijani by bilingual experts. Subsequently, an independent translator performed a back-translation into the source language. The translated versions were then reviewed by a panel of experts to evaluate the accuracy of the translation and the equivalence of item content with the original instruments.

A pilot study involving 30 adolescents (N = 30) was conducted to assess the clarity, comprehensibility, and cultural appropriateness of the translated items. Based on participants’ feedback and expert recommendations, minor linguistic revisions were made to improve item wording and ensure cultural relevance. The finalized Azerbaijani versions were subsequently used in the main study.

Data analysis

The primary objective of the study was to evaluate the psychometric properties of the Smartphone Addiction Scale (SAS).

Confirmatory factor analysis (CFA) was conducted using the maximum likelihood estimation method in SPSS Statistics 29. Model fit was assessed using several commonly reported fit indices, including the chi-square to degrees of freedom ratio (χ²/df), the Comparative Fit Index (CFI), the Tucker–Lewis Index (TLI), the Normed Fit Index (NFI), the Relative Fit Index (RFI), the Incremental Fit Index (IFI), and the Root Mean Square Error of Approximation (RMSEA).

Internal consistency reliability was evaluated using Cronbach’s alpha (α), McDonald’s omega (ω), and Guttman’s lambda-6 (λ₆) coefficients.

Item Response Theory (IRT) analyses were performed using the Graded Response Model (GRM) to examine item characteristics and the measurement precision of the scale across different levels of the latent trait.

To investigate associations among the study variables, Spearman’s rank-order correlation analysis was conducted. In addition, network analysis was performed using JASP version 0.18.01 to explore the structural relationships among smartphone addiction, psychological distress, academic satisfaction, and subjective well-being.

Results

Descriptive statistics

Descriptive statistics for all study variables are presented in Table 1. The results of the normality tests, including the Kolmogorov–Smirnov and Shapiro–Wilk tests, indicated statistically significant deviations from a normal distribution for most variables (p < 0.001). Consequently, nonparametric statistical methods were employed in subsequent analyses.

Table 1. Descriptive statistics for the study measures.

Factor structure

The results of the confirmatory factor analysis (CFA) supported the unidimensional structure of the Smartphone Addiction Scale (SAS). The proposed one-factor model demonstrated an acceptable fit to the empirical data, with the following fit indices: χ²(35) = 168,90, p < 0,001; χ²/df = 4,82; CFI = 0,925; TLI = 0,904; IFI = 0,926; NFI = 0,908; RMSEA = 0,090; and SRMR = 0,0489.

Despite the statistical significance of the χ² criterion, which is expected in large samples, the alternative fit indices indicate satisfactory model fit. Factor loadings ranged from 0,39 to 0,80 (Figure), indicating sufficient representativeness of the scale items with respect to the latent construct.

IRT analysis

The results of the Item Response Theory (IRT) analysis using the Graded Response Model (GRM) showed that the item discrimination parameters ranged from 1.01 to 3.02, which, according to the criteria proposed by Baker (2001), indicates high discriminative ability (Table 2).

Table 2. IRT parameter estimates for the Smartphone Addiction Scale (SAS)

Reliability

The analysis of internal consistency demonstrated high reliability of the Smartphone Addiction Scale (SAS) across all reliability indices examined: Cronbach’s α = 0,869 (95% CI: 0.851–0.896), McDonald’s ω = 0,873 (95% CI: 0,856–0,890), and Guttman’s λ₆ = 0,873 (95% CI: 0,857–0,892) (Table 3).

Table 3. Reliability of the Smartphone Addiction Scale (SAS)

Similar values of Cronbach’s α, McDonald’s ω, and Guttman’s λ₆ indicate consistency across the reliability estimates (Nunnally, Bernstein, 1994).

Correlation analysis

The results of Spearman’s correlation analysis revealed statistically significant associations between smartphone addiction and all study variables (Table 4).

Table 4. Correlation coefficients among the study variables

Note. SA – smartphone addiction; SW – subjective well-being; PD – psychological distress; CHO – choice harmony; SER – school services; REL – relationships with classmates; STU – study habits; CAR – career utility. ** – p < 0,01.

In particular, smartphone addiction demonstrated a statistically significant negative association with subjective well-being (r = –0,415, p < 0,01) and a positive association with psychological distress (r = 0,427, p < 0,01).

In addition, significant negative correlations were found between smartphone addiction and indicators related to the school environment, including school satisfaction, quality of school services, and effectiveness of study habits (r values ranging from –0,324 to –0,426, p < 0,01).

Smartphone addiction was negatively correlated with subjective well-being and satisfaction with the educational environment. Psychological distress levels were higher among adolescents who scored higher on the Smartphone Addiction Scale (SAS).

Discussion

The results of the study confirm the satisfactory psychometric properties of the Azerbaijani version of the SAS and its applicability for assessing smartphone addiction among adolescents.

Confirmatory factor analysis supported the unidimensional structure of the scale, consistent with the original version (Kwon et al., 2013) and several cross-cultural adaptations (Kuss, Griffiths, 2017; Lopez-Fernandez et al., 2017; Rumpf et al., 2017; Altundağ, Alperen, 2019).

The IRT analysis demonstrated high discriminative ability for all scale items (α > 1,0; Baker, 2001), with several items exhibiting discrimination parameters exceeding α > 2,0.

Similar values of α, ω, and λ₆ (all > 0,85) indicate consistency across reliability estimates (Nunnally, Bernstein, 1994).

The observed negative association with psychological well-being and positive association with psychological distress are consistent with findings from previous studies (Adams, Kisler, 2013; Bian, Leung, 2015; Elhai et al., 2017; Darcin et al., 2016), as well as with evidence demonstrating relationships between digital forms of addiction and indicators of psychological maladjustment among adolescents (Rustamov et al., 2023c).

Smartphone addiction demonstrated negative correlations with several dimensions of academic satisfaction, which is consistent with the findings of Baert et al. (2020), Kim et al. (2019), Deng (2021), and Samaha and Hawi (2016) regarding the negative impact of smartphone addiction on academic engagement and the quality of the educational experience. The SAS demonstrated its applicability for assessing smartphone addiction among adolescents in Azerbaijan.

Conclusion

The Azerbaijani version of the SAS demonstrated satisfactory psychometric properties and can be used to assess smartphone addiction among adolescents.

The correlations with psychological distress, well-being, and the educational environment are consistent with the findings of Elhai et al. (2017), Samaha and Hawi (2016), and Lachmann et al. (2018).

The study has several limitations. The use of an online survey may be associated with self-selection effects, and the sample consisted predominantly of school students from Baku, which limits the generalizability of the findings. In addition, the absence of a test–retest assessment does not allow for the evaluation of the temporal stability of the scale.

Future research should extend the sample beyond Baku, examine the test–retest reliability of the scale, and employ longitudinal study designs.

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