The mediating role of nomophobia in the effect of executive function on problem-solving skills in gifted students

Abstract

This study investigated the mediating role of nomophobia in the impact of executive function on problem-solving skills among a sample of Turkish gifted middle school students. This study employed a quantitative, non-experimental design using a relational screening model. For this study, data were collected in August 2024 at Science and Art Centers using a random sampling method. 284 gifted students were surveyed using the Executive Function Scale, the Reflective Problem-Solving Scale, and the Nomophobia Scale. A mediation analysis was employed using SPSS. The results revealed a significant relationship between executive function and nomophobia, with specific components of executive function (stimulus control, impulse regulation, working memory storage) showing a positive association with nomophobia, while others (retrieval, cognitive flexibility, behavior regulation) were negatively related. A negative correlation between nomophobia and problem-solving skills was also found, indicating that nomophobia impairs cognitive processes essential for problem solving. The study further revealed a positive link between executive function and problem-solving abilities, emphasizing its importance in cognitive tasks. Importantly, nomophobia was identified as a mediator in the relationship between executive function and problem solving, indicating that anxiety related to nomophobia diminishes both executive function and problem-solving performance. In total, 74% of the variance in problem solving is explained by executive functions and nomophobia. The findings underscore the need for interventions aimed at enhancing executive function and mitigating nomophobia, which could lead to improved problem-solving skills in gifted students. The study concludes by discussing its limitations and offers suggestions for future research, including the necessity for longitudinal studies.

Introduction

Giftedness is a complex construct encompassing exceptional academic potential and advanced cognitive abilities [1]. These children often demonstrate advanced abilities from an early age, including superior verbal and mathematical reasoning, precise perception of time, strong memory, and sustained attention [2]. Such cognitive strengths extend to distinctive problem-solving abilities and executive functions [3]. Understanding these characteristics is essential for designing educational interventions that support gifted learners’ unique developmental needs.

Gifted students frequently leverage digital technologies for personal and academic growth [4]. They use online courses, virtual collaboration tools, and adaptive learning systems to explore complex ideas and creative challenges [5]. This technology integration supports autonomous learning, personalized pacing, and collaborative problem solving, fostering critical thinking and inquiry skills [6, 7]. However, high digital engagement can introduce risks. Gifted students’ extensive use of technology for both education and recreation may make them more susceptible to Internet and gaming addictions, which can affect social, emotional, and academic well-being. Excessive screen time on social media or games can interfere with face-to-face social interactions and emotional regulation [8, 9]. Among these challenges, one emerging concern is nomophobia – anxiety or stress when separated from a mobile phone. Nomophobia arises from excessive smartphone use and is sometimes viewed as a modern “digital-age phobia” [10]. It is associated with increased anxiety, attachment issues, and loneliness, and it can disrupt cognitive function: nomophobic anxiety (or even the mere presence of a smartphone) can reduce attention span, slow processing speed, and diminish working memory and reasoning [11, 12].

As mentioned above, a growing body of research highlights the cognitive implications of nomophobia, particularly its negative impact on attention and memory. Gifted students typically exhibit both advanced cognitive abilities [3, 13] and strong executive functions [14, 15], which underlie their superior problem-solving skills [16]. However, nomophobia’s cognitive costs could undermine this advantage. To our knowledge, few studies have examined nomophobia’s mediating role between executive function and problem solving in gifted learners [17]. Understanding this mediation is crucial for several reasons. For example, it could reveal how digital dependencies influence gifted students’ cognitive processes, inform interventions to bolster their executive functioning, and problem solving. This research also highlights how excessive mobile technology use can disrupt attentional control, self-regulation, and cognitive flexibility—factors critical to academic performance and lifelong learning. Integrating nomophobia with established cognitive theories enriches educational psychology, fostering better approaches to digital literacy and mental health in schools. Finally, the findings have broader implications for educational policy and practice, particularly in designing environments that balance technological integration with cognitive development.

Executive function

Executive functions (EFs) are self-regulatory cognitive processes associated with the prefrontal cortex (PFC) that govern thoughts, actions, and emotions. Miyake et al. [18] categorize EFs into three core functions: inhibition (suppressing habitual responses), switching (shifting attention between tasks), and updating (integrating new information while discarding outdated content). Rather than a single process, EFs comprise multiple interrelated cognitive skills, including working memory, cognitive flexibility, inhibitory control, and attention. Working memory was defined as the ability to hold and manipulate information over short periods, essential for daily tasks like remembering instructions [19]. Cognitive flexibility enables adapting to changing demands and viewing situations from different perspectives. Attention, crucial for regulating thoughts and emotions, develops in childhood and is influenced by genetic and environmental factors.

Research consistently shows strong relationships between executive function and intelligence, particularly fluid intelligence [20, 21]. Some theorists argue that fluid intelligence relies on executive processes like working memory and cognitive control [20, 21]. Empirical studies report moderate to strong correlations between core EF tasks and IQ [22]. In gifted children, superior EF performance tends to align with higher IQ (13,14), and genetic studies suggest overlapping influences between EF and intelligence [22].

Problem-solving

Polya [23] defines problem solving as the effort to attain a clearly defined goal that is not immediately reachable. His well-regarded four-stage process involves understanding the problem, devising a strategy (making a plan), implementing the strategy (implementing the plan), and evaluating the results. Problem solving is characterized as a heuristic process centered on the development and representation of problem-solving strategies. It entails answering questions, acquiring new concepts, and achieving goals through the use of various resources and tools. Effective problem solving starts with identifying a problem, planning and executing a solution, and continuously monitoring and evaluating progress [24]. It involves organizing previously acquired knowledge and concepts to navigate obstacles and achieve desired outcomes through a series of behavioral and cognitive steps. The speed of problem solving is a key indicator of higher performance in gifted children, who consistently solve simple problems faster than their non-gifted peers, reflecting a greater overall problem-solving capacity.

Nomophobia

Nomophobia, derived from “no mobile phone phobia,” is a contemporary psychological issue characterized by anxiety or discomfort when individuals are without their mobile phones or unable to use them. This phenomenon has become increasingly prevalent with the widespread adoption of smartphones, particularly among younger populations who rely heavily on these devices for communication, information, and social interaction. Nomophobia, often labeled as a “disorder of the modern world,” is characterized by feelings of discomfort, anxiety, nervousness, or distress when a smartphone is unavailable [25]. This condition stems from a reliance on smartphones and the extensive use of social media and other digital functions. Those affected by nomophobia fear missing out on social media messages, events, and experiences, and they become anxious when their phones are inaccessible due to a dead battery or lack of network coverage. Nomophobia is thus considered a disorder of contemporary digital society, reflecting a pathological fear of being out of touch with technology [26].

Theoretical framework

Baddeley’s multicomponent working memory model provides a natural lens for linking executive functions and problem solving. It posits subsystems including the phonological loop, visuospatial sketchpad, episodic buffer, and central executive [27]. The central executive allocates attention and coordinates these components, while the episodic buffer integrates multimodal information from the other subsystems and long-term memory. In sum, higher-order tasks like problem solving draw on this integrated WM architecture [27].

Executive functions (EFs) are crucial for problem solving. Working memory serves to coordinate inhibition and selective attention [16]. For example, cognitive flexibility and WM capacity predict analogy-based problem solving [13], and verbal and spatial WM together with flexibility predict mathematical problem solving. These findings underscore the importance of WM and cognitive flexibility in goal-directed cognition. Among EF components, working memory is one of the strongest predictors of learning problem-solving strategies [16].

EFs support problem solving in all phases (representation, planning, execution, evaluation) and enhance cognitive flexibility, decision-making, and emotional regulation [27]. Working memory capacity is foundational to complex cognition [28]. The episodic buffer contributes by integrating information during reasoning. Effective problem solving thus involves the following processes: Maintaining task rules and subgoals in WM, integrating new and prior information via the episodic buffer, and inhibiting irrelevant content through the central executive. Consequently, high cognitive load or disruption of WM components can significantly impair problem-solving performance [28].

High levels of social media use and problematic internet use (PIU) strongly predict greater nomophobia [29, 30]. PIU is characterized by poor impulse control and attentional deficits [31]; social-media addiction (SMA) correlates with inhibitory-control deficits [32]; and problematic smartphone use reflects broad EF difficulties [29]. Collectively, these findings implicate EF dysfunction as an independent vulnerability factor for nomophobia. Nomophobia introduces cognitive interference in WM. Nomophobic anxiety (and even mere phone presence) impairs executive functions and attention [31]. The anxiety consumes central-executive resources and increases distractibility [33], limiting one’s ability to maintain and manipulate information in WM [31]. Moreover, habitual reliance on smartphones externalizes memory; separation from the device disrupts normal encoding and retrieval [33]. Thus, nomophobia adds extra load to the central executive and fragments the subsidiary WM stores, undermining the WM mechanisms essential for complex problem solving.

Smartphones can support learning and data collection, but excessive use provokes distraction, anxiety, and cognitive impairment. High nomophobia is linked to greater anxiety and poorer academic outcomes [10]. Chronic smartphone engagement undermines attention, WM, and cognitive control; the device’s constant presence imposes additional cognitive load and reduces WM resources for complex tasks [34]. Anxiety from smartphone dependency further degrades the executive functions needed for systematic problem solving. Overall, nomophobia disrupts the cognitive mechanisms vital to effective problem solving.

Gifted students often exhibit advanced cognitive abilities and strong EF skills, which contribute directly to their problem-solving ability. However, many gifted individuals show uneven executive functioning: they may have superior working memory but weaker inhibitory control, and they may not consistently excel on EF tasks [35]. This asynchronous profile (superior cognition paired with planning or inhibitory gaps) renders gifted learners particularly vulnerable to nomophobia. For example, when a gifted student’s WM is heavily engaged, nomophobia-induced anxiety can disproportionately deplete central-executive resources. Relying on a smartphone as an external memory aid exacerbates this effect by occupying executive attention and removing an external support mechanism. The combined impact of heightened anxiety and loss of mnemonic cues undermines the WM processes needed for advanced problem solving.

In sum, Baddeley’s WM model provides a coherent framework for understanding how EF and problem solving rely on interconnected subsystems. Nomophobia’s interference with attention and memory suggests that the WM substrate of problem solving is compromised. Empirical studies have observed that smartphone-related anxiety impairs executive control and reduces available WM capacity. These insights suggest nomophobia may mediate the link between EF and problem-solving skills, especially in gifted students. Hence, this study explores the mediating role of nomophobia in the impact of executive function on problem-solving skills among gifted students. By clarifying this pathway, educators and psychologists can target interventions to mitigate nomophobia’s effects and bolster gifted learners’ cognitive resources (Fig. 1). (Fig. 1 appears here.)

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The primary hypotheses are:

1. 1.

Executive function has a positive effect on problem-solving skills in gifted students. (H1).

2. 2.

Executive function has a negative effect on nomophobia in gifted students. (H2).

3. 3.

Nomophobia has a negative effect on problem-solving skills in gifted students. (H3).

4. 4.

Nomophobia mediates the relationship between executive function and problem-solving skills in gifted students. (H4).

Research design

This study employs a quantitative, non-experimental design using a relational screening model to examine naturally occurring associations between variables. This method is suitable when experimental manipulation is impractical, allowing for the analysis of co-variation in real-world contexts [36]. By focusing on correlational dynamics, it enables the investigation of direct and indirect effects without imposing artificial conditions. The relational screening model assumes that meaningful insights emerge from observed variable relationships, offering a nuanced understanding of complex phenomena. Hence, this study employed the relational screening model as its research method, which is designed to determine if there is co-variation between two or more variables. This method explores whether and how variables change together or remain unchanged. While experimental studies are ideal for identifying the specific effects of a variable on an outcome, non-experimental approaches, like the one used in this study, can yield similar insights. The aim of this research is to explore the relational connections and interactions between variables deeply. The primary reason for selecting this approach is its capacity to provide a deeper understanding of the direct and indirect effects between variables. Inferential statistical methods were utilized in the relational analyses, thereby ensuring the research results are grounded on a solid foundation.

Human ethics and consent to participate

The study was approved by the Ethics Committee of Harran University Social Sciences and Humanities (protocol code E-76244175-050.04.04-346650). Participants were recruited on a voluntary basis and declared this. A declaration of voluntariness was obtained from each participant before the scales were administered. Informed consent was also obtained from the parents of the participants. All procedures were in accordance with the ethical standards of the institutional and national research committees and with the 1964 Helsinki Declaration and its later amendments.

Participants

G*Power software was used to assess the adequacy of the questionnaire sample. The analysis indicated that 146 participants were sufficient for a statistical power of 0.99. The actual sample size exceeded this threshold, confirming its adequacy [37, 38]. Out of 305 collected questionnaires, 284 were considered valid after excluding those with over 5% missing values. Table 1 outlines the demographic details of these 284 respondents. Participants were aged between 11 and 15, with an average age of 13.10. Among them, 22.9% were 5th-grade students (N = 65), 25.0% were 6th-grade students (N = 71), 38.4% were 7th-grade students (N = 109), and 13.7% were 8th-grade students (N = 39). (Table 1 appears here.)

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The study focused on gifted students participating in differentiated education programs at the Science and Art Centers (SACs). Data collection occurred in August 2024 using three Likert-type scales. SACs are public pull-out schools that offer after-school enrichment programs for gifted students at the primary, middle, and high school levels. These programs emphasize advanced learning opportunities and ability-based grouping [39]. Student admission is based on a multi-stage process, including teacher nominations, group and individual intelligence assessments, and committee evaluations in specific talent areas such as intellectual ability, visual arts, and music. The SAC curriculum is structured into five phases: orientation, support, talent discovery, talent development, and project engagement, with a strong emphasis on project- and problem-based learning. Giftedness identification at SACs is conducted using the Anatolian-Sak Intelligence Scale (ASIS), an individually administered intelligence test designed for Turkish-speaking children aged 4 to 12 [40]. ASIS, normed in Turkey in 2016, is based on the Cattell–Horn–Carroll intelligence model and consists of 256 items across seven subtests and three cognitive factors. Its reliability and validity have been confirmed through exploratory and confirmatory factor analyses.

Instruments

The executive function scale was developed by Genç [41] to measure the executive function skills of students. The inventory is a five-point Likert-type scale (1: never, 2: rarely…, 5: always) including 28 items in six domains (stimulus, impulse, storage, retrieval, act, social). Some exemplary items are as follows: When s/he’s doing something, s/he get distracted by other things (S), If it’s fun, s/he’ll do it, even if s/he know it’s wrong (I), S/he has difficulty when s/he is asked to repeat a given sequence of numbers (S), S/he remember an incident from the past as it happened (R), If his/her plan does not work, S/he makes alternative plans to achieve my goal (A), S/he can easily make new friends (SO). An analysis of the six factors in the scale shows that they can be grouped into three broader factors, each made up of two related components. Specifically, inhibitory control includes the impulse and stimulus components, working memory includes storage and retrieval, and cognitive flexibility includes act and social components. When reverse items are transformed in the scoring of the scale, high scores indicate high inhibitory control, high working memory, and high cognitive flexibility.

The original Executive Function Scale demonstrated subscale reliability coefficients ranging from 0.59 to 0.73, with six factors explaining 50.34% of the variance. Subsequent validation studies confirmed a similar six-factor structure, accounting for 50.49% of the variance. In the present study, Cronbach’s alpha values ranged from 0.55 to 0.73, and McDonald’s Omega was 0.71, indicating acceptable internal consistency [42]. Discriminant validity was supported by the Fornell-Larcker criterion, as the square root of the AVE for each construct exceeded its inter-construct correlations. The composite reliability (CR) was 0.96, indicating strong reliability, and the AVE was 0.51, exceeding the 0.50 threshold for convergent validity [42] (See Table 2).

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The reflective problem solving scale was developed by Kızılkaya and Askar [43] to measure the reflective problem-solving skills of students. The inventory is a five-point Likert-type scale (1: never, 2: rarely…, 5: always) including 14 items in three domains (questioning, evaluation, reasoning). Some exemplary items are as follows: When I cannot solve a problem, I ask myself questions to understand why I cannot solve it (Q), I re-evaluate my solutions and try to solve the next problem better (E), When solving problems, I think about why I am doing what I am doing (R).

The original Reflective Problem Solving Scale showed subscale reliability coefficients between 0.69 and 0.73, with three factors explaining 49.12% of the total variance and an overall reliability of 0.83. In the present study, the scale demonstrated a reliability of 0.81, with factor analysis confirming a three-factor structure explaining 53.34% of the variance. McDonald’s Omega was Ω = 0.82, indicating good internal consistency. Discriminant validity was supported by the Fornell-Larcker criterion, as each construct’s AVE exceeded its correlations with other constructs. The CR was 0.93, and the AVE was 0.52, exceeding the 0.50 threshold, thereby supporting convergent validity (See Table 2).

The Nomophobia scale was developed by Özdemir and Bektaş [44] to measure nomophobic attitudes of children. The inventory is a seven-point Likert-type scale (1: disagree strongly, …, 5: agree strongly) including 20 items in four domains (inability to access information − 1, losing online connection-2, loss of comfort-3, inability to communicate − 4). Some exemplary items are as follows: I feel uncomfortable when I am not able to access information on my smartphone at all times (1), I’d feel weird because I wouldn’t know what to do (2), If I haven’t looked at my smartphone for a while, I feel a strong desire to look at it (3), I’d feel uneasy about being disconnected (4).

The original Nomophobia Scale reported subscale reliabilities ranging from 0.74 to 0.87, with four factors accounting for 57.8% of the total variance and an overall reliability of 0.90. In the current study, reliability was 0.87, and factor analysis confirmed a four-factor structure explaining 60.2% of the variance. McDonald’s Omega was Ω = 0.83, indicating good internal consistency. Discriminant validity was supported by the Fornell-Larcker criterion, with each construct’s AVE exceeding its correlations with other constructs. Composite reliability was 0.96, and AVE was 0.57, both confirming strong internal consistency and adequate convergent validity (See Table 2). (Table 2 appears here.)

Data analysis

Prior to performing the statistical analysis to achieve the study’s objectives, the data required organization, and several assumptions needed to be evaluated. These included missing value analysis, extreme value analysis, and assessments of normal distribution and linearity. The initial step involved analyzing missing values, revealing 21 missing data points, which were subsequently excluded. In the extreme value analysis, variable scores were converted to standard z-scores to assess their deviation from the mean [45]. Z-scores falling outside the range of − 3 to + 3 were to be excluded, but no outliers were identified. Skewness (range: −1.00 to 0.17, Standard Error [SE] = 0.18) and kurtosis values (range: − 0.66 to 1.00, SE = 0.36) were examined to evaluate normal distribution, with values within the − 1.5 to + 1.5 range, as recommended in the literature, indicating no significant deviation from normal distribution. Descriptive statistics for the study measures are presented in Table 3. (Table 3 appears here.)

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SPSS (version 22) was used to perform preliminary statistical analyses such as factorability, normality, descriptive statistics, and correlation analysis. The adequacy of the sample for factor analysis was assessed using the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy, which yielded an overall value of 0.81, confirming the appropriateness of the dataset for exploratory factor analysis and indicating sufficient intercorrelations among items without excessive multicollinearity or singularity. Bartlett’s sphericity test was significant (p <.001), indicating the dataset was eligible for factor analysis. The overall variation described by the scales varied from 50.49% to 60.20%, indicating that they adequately captured response variability. Table 4 presents the correlations among the constructs.

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Confirmatory factor analysis was conducted to evaluate the validity of the structural and measurement models. Based on the fit thresholds recommended, the results shown in Table 5 indicated an acceptable model fit, thereby confirming the construct validity of both models. (Table 5 appears here.)

Following the completion of missing value analysis, extreme value analysis, normality distribution assessments, and linearity analysis, the data analysis process was initiated. Baron and Kenny [46] provided foundational guidelines for testing mediation. In their model, however, the effect of the mediator variable on the dependent variable, denoted as c-cı or ab, is not directly evaluated. To address this, Baron and Kenny [46] recommend the Sobel test, which is contingent upon the assumptions of normal distribution and requires large sample sizes to accurately calculate the indirect effect of the mediator variable (ab). At this stage, it is recommended to examine confidence intervals through bootstrapping methods [47]. In this study, we incorporated bootstrapping-based confidence intervals (N = 5000) and additionally examined the κ2 and PM values as advocated by Preacher and Kelley [48].

Maxwell et al. [49] have reported that mediation analysis using cross-sectional data tends to yield biased estimates of mediator effects. They further identified several inherent issues within cross-sectional designs that impede the accurate representation of true mediational processes. Additionally, a mediator variable identified in a cross-sectional design may not fully mediate in a longitudinal perspective. To mitigate this problem, this study adopted Hayes and Preacher [50] suggestion of establishing a counter-argument to rule out alternative mediation pathways. Accordingly, alternative models with reversed pathways among variables were tested. Data analysis was conducted using SPSS 22.0 software, employing the process macro developed by Hayes and Preacher [50] to test mediation based on bootstrapping.

Effect sizes (R²) were interpreted using the context-specific benchmarks proposed by Wei and Hu [51], which emphasize that effect size thresholds are inherently relative and depend on the research context rather than being absolute [52]. In this system, R² thresholds are lowered to 0.005 (small), 0.01 (medium/typical), 0.02 (large), and 0.09 (very large) to account for the typically modest effect sizes observed in such research contexts. Cohen’s benchmarks (R² = 0.02 small, 0.13 medium, 0.26 large) were not adopted because they s were developed for general application across the social sciences, often drawing from experimental designs (R² = 0.02 small, 0.13 medium, 0.26 large), and thus may set unrealistically high expectations for survey-based research where effects are typically more modest due to real-world variability in self-reported data. As Wei and Hu [51] emphasize, effect size benchmarks are inherently relative and context-dependent rather than absolute, making their scale more appropriate for the current study’s survey-based design focused on tolerance of ambiguity. Therefore, all R² values in our analyses are classified using Wei and Hu’s scale.

Findings

Correlation analysis

To clarify the associations among executive function skills, nomophobia, and reflective problem solving, zero-order correlations were examined. Correlation analysis revealed that reflective problem solving was significantly associated with stimulus (r = −.65, p <.01), impulse (r = −.48, p <.01), storage (r = −.28, p <.01), retrieval (r =.32, p <.01]), act (r =.32, p <.01), social (r =.21, p <.01), and nomophobia (r = −.70, p <.01). Additionally, there was significant association between nomopobia and stimulus (r =.40, p <.01), impulse (r =.34, p <.01), storage (r =.28, p <.01), retrieval (r = −.23, p <.01), behaviour (r = −.20, p <.01), and social (r =-.20, p <.01). The associations among study variables were presented in Table 4. (Table 5 appears here.)

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Mediation analysis

We performed mediation analysis for each executive function skill by means of Process Macro (Model 4). Accordingly, we reported five different indirect effects on problem solving. The process of mediation analysis for executive function skills was revealed as follows (Table 6): (Table 6 appears here.)

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Stimulus

(Inhibitory Control-IC) The analysis of non-standardized regression coefficients indicated that the stimulus had a significant effect on nomophobia (ß = 0.24, p <.001, 95% CI [0.18, 0.31] path a) and that nomophobia significantly influenced reflective problem solving (ß = − 0.27, p <.001, 95% CI [−0.34, − 0.19], path b). As both paths a and b were significant, the bootstrap method was employed to construct confidence intervals for the mediation analysis. In this study, nomophobia acted as a mediator in the relationship between stimulus and reflective problem solving (ß = − 0.07, SE = 0.03, 95% CI [0.11, 0.25], path ab). The significant association between stimulus and reflective problem solving (ß = − 0.16, p <.01, 95% CI [0.10, 0.53], path cı) when nomophobia was included in the analysis suggests that nomophobia plays a mediating role. The mediated path accounted for 26% of the variance in reflective problem solving (R²med = 0.26). In practical terms, this suggests that over a quarter of differences in problem-solving scores can be attributed to the pathway from inhibitory control → nomophobia → problem solving. This indicates a large effect size, and a meaningful portion of problem-solving ability is explained by EF’s indirect effect through nomophobia [52].

Impulse

(IC) The examination of non-standardized regression coefficients revealed that impulse had a significant effect on nomophobia (ß = 0.16, p <.001, 95% CI [0.11, 0.21] path a), and that nomophobia significantly influenced reflective problem solving (ß = − 0.34, p <.001, 95% CI [−0.41, − 0.26], path b). Given the significance of both paths a and b, confidence intervals derived from the bootstrap method were employed in the mediation analysis. In this study, nomophobia functioned as a mediator in the relationship between impulse and reflective problem solving (ß = − 0.05, SE = 0.03, 95% CI [−0.08, − 0.03], path ab). The significant relationship between impulse and reflective problem solving (ß = − 0.09, p <.01, 95% CI [−0.12, − 0.06], path cı) when nomophobia is accounted for further supports the role of nomophobia as a mediator. Importantly, the mediated pathway accounted for 30% of the variance in reflective problem solving (R²med = 0.30). In practical terms, nomophobia explains nearly one-third of the variability in students’ problem‐solving performance linked to impulsivity. This substantial proportion suggests that interventions aimed at reducing nomophobia (or improving impulse control) could yield meaningful improvements in reflective problem solving, underscoring nomophobia’s key role in the cognitive pathways linking impulsivity to academic outcomes [52].

Storage

(Working memory-WM) The analysis of non-standardized regression coefficients revealed that storage had a significant impact on nomophobia (ß = 0.17, p <.001, 95% CI [0.09, 0.25] path a), and that nomophobia had a significant effect on reflective problem solving (ß = − 0.38, p <.001, 95% CI [−0.45, − 0.30], path b). Given the significance of both paths a and b, confidence intervals based on the bootstrap method were utilized for the mediation analysis. In this study, nomophobia was found to mediate the relationship between storage and reflective problem solving (ß = − 0.06, SE = 0.02, 95% CI [−0.10, − 0.03], path ab). The significant association between storage and reflective problem solving (ß = − 0.08, p <.01, 95% CI [−0.12, − 0.03], path cı) when nomophobia is included in the analysis supports the conclusion that nomophobia plays a mediating role. Crucially, the mediated pathway accounted for 37% of the variance in reflective problem solving (R²med = 0.37). In practical terms, the storage-nomophobia pathway explains over one-third of the differences in students’ reflective problem solving, underscoring nomophobia’s substantial role [52].

Retrieval

(WM) The examination of non-standardized regression coefficients demonstrated that retrieval significantly affected nomophobia (ß = 0.15, p <.001, 95% CI [0.06, 0.24] path a), and nomophobia significantly influenced reflective problem solving (ß = − 0.37, p <.001, 95% CI [−0.44, − 0.30], path b). Given the significance of both paths a and b, confidence intervals based on the bootstrap method were employed for the mediation analysis. The findings of this study indicate that nomophobia served as a mediator in the relationship between retrieval and reflective problem solving (ß = − 0.06, SE = 0.02, 95% CI [−0.09, − 0.02], path ab). The significant association between retrieval and reflective problem solving (ß = − 0.10, p <.01, 95% CI [−0.15, − 0.05], path cı) when nomophobia is included in the analysis supports the conclusion that nomophobia plays a mediating role. Importantly, the mediated pathway accounted for 42% of the variance in reflective problem solving (R²med = 0.42). Practically, this means that over two-fifths of the variability in students’ reflective problem-solving performance can be attributed to the sequence from retrieval behaviors through nomophobia to problem solving. Such a substantial mediated effect highlights nomophobia as a critical mechanism: interventions aiming to reduce nomophobia may yield meaningful improvements in students’ cognitive performance [52].

Behavior

(Cognitive Flexibility-CF) The analysis of non-standardized regression coefficients indicated that the act had a significant effect on nomophobia (ß = 0.19, p <.001, 95% CI [0.10, 0.28] path a), and that nomophobia significantly affected reflective problem solving (ß = − 0.37, p <.001, 95% CI [−0.44, − 0.30], path b). Given the significance of both paths a and b, the bootstrap method was employed to generate confidence intervals for the mediation analysis. The findings demonstrate that nomophobia served as a mediator in the relationship between the behavior and reflective problem solving (ß = − 0.07, SE = 0.02, 95% CI [−0.11, − 0.03], path ab). This result supports the conclusion that nomophobia plays a mediating role, as indicated by the significant relationship between the behavior and reflective problem solving (ß = − 0.10, p <.01, 95% CI [−0.15, − 0.05], path cı) when nomophobia is accounted for in the analysis. Importantly, the mediated pathway accounted for 37% of the variance in reflective problem solving (R²med = 0.37). In practical terms, over one-third of the variability in students’ problem-solving performance can be attributed to the sequence from this behavior through nomophobia to problem solving. This indicates a large effect size [52].

Social

(CF) The examination of non-standardized regression coefficients revealed that social factors had a significant impact on nomophobia (ß = 0.14, p <.001, 95% CI [0.04, 0.25] path a), and that nomophobia significantly affected reflective problem solving (ß = − 0.39, p <.001, 95% CI [−0.46, − 0.31], path b). Given the statistical significance of paths a and b, the bootstrap method was utilized to derive confidence intervals for the mediation analysis. The results demonstrate that nomophobia served as a mediator in the relationship between social factors and reflective problem solving (ß = − 0.06, SE = 0.02, 95% CI [−0.10, − 0.01], path ab). This finding supports the conclusion that nomophobia plays a mediating role, as indicated by the significant relationship between social factors and reflective problem solving (ß = − 0.06, p <.01, 95% CI [−0.12, 0.00], path cı) when nomophobia is included in the analysis. Importantly, the mediated pathway accounted for 44% of the variance in reflective problem solving (R²ₘed = 0.44). Practically, this means that a large effect size and nearly half of the variability in students’ reflective problem-solving performance is explained by the pathway from social factors through nomophobia to problem solving [52].

Discussion

In this study, we investigated the relationships among executive function, problem-solving skills, and nomophobia in a sample of Turkish gifted middle school students. Further, we specifically investigated the mediating role of nomophobia in the relationship between executive function skills and problem-solving skills. To achieve these aims, four hypotheses were tested.

Consistent with the first hypothesis, our results show a significant positive relationship between executive function (EF) and problem-solving skills. Prior research indicates that various components of EF—namely inhibitory control, working memory, and cognitive flexibility—contribute to effective problem solving across diverse contexts. In particular, EF appears to support key cognitive processes that underlie problem resolution, thereby influencing academic performance and reasoning across multiple domains [53]. For example, components such as working memory and inhibitory control have been identified as robust predictors of problem-solving abilities [16].

Some studies even suggest a bidirectional relationship between EF and problem solving, indicating that stronger EF can enhance cognitive flexibility and emotional regulation—both of which are important for decision-making [54]. Within educational settings, longitudinal research further supports this EF-problem solving link. For instance, Swanson [55] reported that working memory and attention significantly contribute to elementary students’ mathematical problem-solving skills, highlighting the role of these executive components in academic achievement. Together, these findings underscore the importance of executive functions in both cognitive assessments and real-world problem-solving situations.

In gifted students, this relationship highlights their cognitive strengths. EF skills such as working memory, cognitive flexibility, and inhibitory control are crucial for effective problem solving. Studies find a strong positive correlation between these EF components and gifted students’ problem-solving abilities. Gifted learners often demonstrate superior EF compared to their peers, especially in tasks involving inductive and mathematical reasoning; this advantage has been linked to aspects of fluid intelligence [56]. Moreover, cognitive control—a key component of EF—supports both intelligence and creativity, potentially facilitating creative problem solving [57]. Overall, advanced EF appears to enhance gifted students’ problem-solving capacity in complex and mathematical contexts, emphasizing the importance of nurturing these skills to help them reach their full potential.

The results support the second hypothesis by showing a significant association between EF skills and nomophobia. Specifically, higher scores on aspects of inhibitory control and working memory storage were positively related to nomophobia, whereas stronger memory retrieval, behavioral regulation, and social skills were related to lower nomophobia. These findings align with prior research. For example, higher impulsivity has been linked to problematic smartphone use and increased nomophobia [58]. Strong social skills have been associated with greater face-to-face interaction, which may mitigate loneliness and anxiety related to nomophobia, and appropriate social behaviors may reduce dependence on smartphones for social validation [59].

Among gifted students, higher nomophobia correlated with EF components such as stimulus control, impulse regulation, and memory storage. This aligns with research suggesting that gifted individuals often have distinct cognitive profiles, which include both advanced abilities and challenges in impulse control and emotional regulation. Gifted students may also be especially susceptible to distraction by external stimuli, which could increase their reliance on digital devices [60]. Conversely, stronger retrieval, action, and social skills were associated with lower nomophobia in this group, reflecting gifted students’ greater ability to access information independently and engage in face-to-face interactions [61]. Emotional intelligence and self-control have also been linked to lower smartphone dependence, as they help individuals manage anxiety and external pressures more effectively.

The observed associations highlight the complexity of the relationship between EF and nomophobia: some EF components may elevate nomophobia risk, while others may serve as protective factors. Further research is needed to clarify these relationships and determine how targeted interventions that strengthen EF skills could help gifted students manage their smartphone use. Enhancing executive functions in gifted students may protect against nomophobia by equipping them with strong cognitive and emotional regulation skills. Developing these abilities could support students’ academic success and overall mental well-being in an increasingly digital world.

With respect to the third hypothesis, our analysis revealed a significant negative relationship between nomophobia and problem-solving skills, indicating that higher nomophobia is associated with lower problem-solving ability. This finding is consistent with previous research linking nomophobia to declines in cognitive performance. In particular, studies suggest that nomophobia is associated with impairments in cognitive functions such as attention and memory, which are essential for effective problem solving. For example, King et al. [62] reported that nomophobia is associated with increased anxiety and distraction, factors that can adversely affect focus and problem-solving abilities.

Additionally, research indicates that excessive smartphone use is linked to increased distractions and emotional disturbances, which may contribute to declines in problem-solving performance [63]. Even among gifted students with strong cognitive skills, over-reliance on technology may present challenges: for instance, it may undermine their independent problem-solving abilities [64]. Social pressures in gifted education may also compound these issues; for example, pressures within gifted programs can hinder the development of face-to-face problem solving and collaborative skills [56]. Therefore, targeted interventions are essential to promote independent problem solving and emotional regulation, reducing reliance on technology and supporting cognitive development in gifted students.

Finally, our study provides evidence that nomophobia mediates the relationship between executive function and problem-solving skills. Nomophobia, an emerging focus in research on student populations, appears to influence both emotional well-being and cognitive functioning. Prior studies have linked deficits in executive functions to poorer academic performance and challenges in complex problem solving [65]. In line with this literature, students with stronger executive functions tend to perform better academically, potentially due to more effective management of learning tasks and improved emotional regulation. Our results also suggest that higher nomophobia is associated with increased anxiety and stress, which in turn may impair aspects of executive functioning such as concentration and attention [66]. This impaired executive control could create a form of cognitive overload, thereby reducing students’ problem-solving capacity. Furthermore, relying on mobile phones as a coping strategy might further exacerbate executive function deficits. These effects can be understood through cognitive load theory, which proposes that excessive cognitive demands interfere with learning and problem-solving processes [58].

While our findings indicate that nomophobia may mediate the EF-problem solving relationship, further research is needed to confirm these effects. Future studies might examine whether interventions—such as mindfulness training, self-regulation strategies, or increased physical activity— can reduce nomophobia-related anxiety and support cognitive performance. In summary, these findings suggest that nomophobia may partly explain how variations in executive function relate to differences in problem-solving skills among students. A more comprehensive understanding of this mediating relationship could help educators and mental health professionals develop interventions aimed at reducing the potential cognitive impacts of nomophobia.

Conclusion and implications

This study explored the interrelationships among executive function (EF), problem-solving skills, and nomophobia in gifted Turkish middle school students, with a specific focus on the mediating role of nomophobia. The findings confirm that strong executive function skills are positively associated with enhanced problem-solving abilities. However, higher levels of nomophobia are linked to poorer problem-solving performance and can mediate the negative effects of EF deficits. These results highlight the dual role of executive functions—as both a cognitive strength and a protective factor against nomophobia. They also underscore the potential cognitive and emotional risks associated with excessive smartphone dependence. Enhancing EF skills and addressing nomophobia through targeted educational and psychological interventions may significantly improve both academic performance and emotional well-being among gifted learners.

This study identified a significant relationship between executive function, nomophobia, and problem-solving skills, highlighting executive function’s critical role in both domains. Cognitive processes such as working memory, cognitive flexibility, inhibitory control, and attention are essential for academic success and regulating technology-related behaviors. Therefore, educational and intervention programs should target these skills through activities like memory sequencing and task-switching. Additionally, as nomophobic attitudes negatively affect problem-solving abilities, addressing this issue requires a multifaceted approach, including education, awareness, and behavioral interventions to promote healthier technology use and cognitive development.

Educational programs should incorporate memory sequencing and task-switching exercises to enhance executive functioning. Research indicates that students informed about nomophobia risks develop healthier technology habits, while integrating discussions on nomophobia into health and psychology curricula fosters understanding and self-reflection [33]. Mindfulness practices, such as meditation, can mitigate nomophobic tendencies by reducing anxiety and improving emotional regulation [67]. Encouraging structured phone use, alternative activities, and social connections can further help manage smartphone reliance [68]. Additionally, integrating social-emotional learning programs promotes resilience against nomophobia [69]. Institutional policies regulating smartphone use can also curb nomophobic behaviors. In conclusion, diminishing nomophobic attitudes among students requires a multifaceted approach that includes educational interventions, mindfulness practices, social support, and institutional policies. By addressing the psychological and behavioural aspects of nomophobia, educational institutions can foster a healthier academic environment that supports students’ mental well-being and academic success.

Limitations

This study has several limitations that warrant consideration. First, its cross-sectional design limits the ability to infer causal relationships among the variables. Future research employing longitudinal or experimental designs is needed to enhance generalizability and establish causality. Second, the focus on primarily gifted students may restrict the applicability of the findings to other populations. Subsequent studies should incorporate more diverse samples—comparing gifted, non-gifted, and other special education groups—to further investigate the role of nomophobia in the relationship between executive function and problem-solving skills. Additionally, future research should assess the effectiveness of educational interventions aimed at improving executive function and their subsequent impact on both nomophobia and problem-solving abilities. Furthermore, future research could examine the mediating role of problematic internet use, social media use, and game addiction in relation to digital dependency. Future studies may analyze how the cognitive load of technology dependence affects problem solving efficiency in gifted students. In addition, future studies can compare gifted and non-gifted students in terms of digital dependency constructs. Cross-cultural studies may be conducted to determine whether the effects of nomophobia differ across different cultures and educational systems. Longitudinal studies would be particularly valuable from early childhood to adolescence in understanding the long-term effects of executive function-focused interventions on nomophobia and problem-solving skills.

Data availability

The data supporting the findings of this study are available from the corresponding author upon reasonable request.

Abbreviations

EF:

Executive function

PFC:

Prefrontal cortex

IQ:

Intelligence quotation

S:

Stimulus

I:

Impulse

S:

Storage

R:

Retrieval

A:

Act

SO:

Social

Q:

Questioning

E:

Evaluation

R:

Reasoning

IC:

Inhibitory Control

WM:

Working memory

CF:

Cognitive Flexibility

SAC:

Science and Art Centers

ASIS:

Anatolian-Sak Intelligence Scale

AVE:

Average variance extracted

CR:

Composite reliability

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