Digital Entanglement: The Influence of Internet Addiction and Negative Affect on Memory Functions—A Structural Approach

Abstract

This study examines how Internet Addiction (IA) and negative affect relate to everyday memory lapses in Portuguese students and teachers. A cross-sectional sample of 254 participants (167 youth aged < 25 years and 87 adults aged ≥ 25 years) completed validated instruments measuring IA, emotional states, and everyday memory lapses. Memory lapses were assessed with the Memory Lapses Questionnaire (QLM), which evaluates five factors: verbal distraction, failed actions, local/geographical orientation, memory for names and faces, and recovery of misplaced objects. Structural equation modeling showed a strong direct effect of IA on memory lapses among adults (β = 0.94, p = 0.002) and a small indirect effect via negative affect among youth (indirect β = 0.08, p = 0.002), whereas the mediation was not significant in adults. IA correlated moderately (0.32 ≤ r ≤ 0.45) with QLM subscales such as verbal distraction and spatial orientation, and youth reported more verbal distractions and orientation errors than adults. These findings suggest that excessive digital engagement impairs everyday memory, particularly attentional and spatial aspects, and that emotional disturbances contribute only modestly among younger users. This study highlights the need for age-tailored interventions addressing both maladaptive internet use and emotional regulation.

1. Introduction

The ubiquity of digital devices has stimulated debate about how pervasive internet use influences cognition. Research on the so-called “online brain” indicates that heavy digital engagement can alter structural and functional connectivity in the prefrontal and orbitofrontal cortices, impairing executive control [1]. In a society where technology dominates a large part of daily routines—whether in a school environment or during leisure time—it becomes relevant to understand in depth how excessive use or digital addiction can influence brain maturation. Moreover, reliance on search engines for information encourages digital off-loading—outsourcing memory to external devices—which reduces activation in memory-related neural networks and leads to poorer recall of learned information [1]. This interest takes on special significance if we consider that younger brains go through a period of high plasticity, which can enhance negative and lasting effects [2]. Experimental studies further show that the mere presence or availability of a smartphone drains cognitive resources and diminishes working-memory performance and recall accuracy [3]. Such findings raise concerns that intensive internet use may contribute to everyday memory failures.

It was in this context that the study “The Effects of Digital Addiction on Brain Function and Structure of Children and Adolescents: A Scoping Review” carried out a thorough analysis of 28 investigations published between 2013 and 2023. These included neuroimaging methods (MRI, fMRI, rsfMRI, EEG, and fNIRS) to map functional and structural changes associated to patterns of compulsive engagement with video gaming activities, internet and smartphones in individuals aged 0 to 18 years [2]. Surprisingly, the data pointed to adverse consequences both in terms of brain architecture—such as decreased volume in certain regions and reduced cortical thickness—and in terms of functional communication, especially in prefrontal areas linked to decision-making, inhibitory executive control mechanisms, and neural pathways involved in reward valuation [2].

These findings are consistent with previous research outcomes reported by Ioannidis and colleagues [4], who also suggested that problematic internet use was linked to marked impairments in cognitive domains such as attentional inhibition, motor inhibition (including prepotent motor inhibition), decision-making processes, and working memory. These findings are consistent with the aforementioned study and lend support to recent theoretical frameworks suggesting a core role of cognitive dysfunction [4,5,6].

The accessibility and convenience of the internet have fostered an environment of self-indulgence and excessive use, leading to dependency and negatively affecting multiple aspects of personal life. This phenomenon has given rise to the concept of IA, suggesting that problematic and abusive online engagement significantly impacts depression, anxiety, and stress states in students and, to a somewhat lesser extent, diminishes their capacity for self-control [7]. A meta-analysis by Pan and colleagues [8], encompassing 53,184 participants, estimated the prevalence of IA at 7.02% (95% CI: 6.09–8.08%), with evidence indicating a rising trend over time. Furthermore, approximately 11.3% of active users aged 15 to 24 are at high risk of compulsive internet use, with this percentage potentially increasing to 33% among younger adolescents. The reported prevalence of this phenomenon within the studied population of Generalized Internet Addiction (GIA) was found to be higher compared to that of Internet Gaming Disorder (IGD). Additionally, the prevalence of GIA showed a sustained temporal escalation and varied depending on the assessment tools applied. These findings suggest that GIA may represent an emerging pattern of intensified interaction between individuals and digital technology [8].

Developmental factors may modulate susceptibility to IA-related cognitive deficits. The prefrontal cortex, which supports working memory and inhibitory control, continues to mature into the mid-twenties [9]. Younger generations (“digital natives”) are immersed in online environments from childhood; more than 95% of U.S. adolescents own a smartphone and nearly half are online “almost constantly” [1]. While adolescents’ brains retain greater plasticity, this sustained exposure may still disrupt attentional processes. Conversely, adults (“digital migrants”) may accumulate the neurobehavioral consequences of dysfunctional internet use over a longer period. These developmental differences motivated the present investigation into how IA and negative affect influence everyday memory lapses across age groups.

IA is defined by a diminished capacity to regulate and limit online behaviors, reflecting a breakdown in self-control mechanisms; it is often accompanied by impulsive online behavior and ostracism, demonstrating that this association is mediated by increased solitude-seeking behavior and decreased self-control [10]. Individuals with IA may neglect fundamental needs, such as proper nutrition, sleep, and social interactions. Additionally, they frequently experience emotional distress—such as anxiety, irritability, or sadness—when unable to access digital devices. Other consequences include social isolation and decreased academic or occupational performance. The findings suggest that excessive engagement with the internet and digital devices represents a growing public health concern, marked by a rising prevalence of sleep disturbances and robust associations with psychopathological indicators such as depression, anxiety, stress, and symptoms consistent with attention-deficit/hyperactivity disorder (ADHD) [11,12].

The literature widely reports that internet use can lead to memory impairments [13]; for example, higher daily frequency of smartphone-based Facebook checking was significantly linked to a decrease in grey matter volume within the nucleus accumbens (NAcc) [14]. The NAcc has an essential role in the mnemonic aspects of reward that influence memory recall [15]; for example, memory retrieval is modulated by factors such as perceived reward, underscoring how motivational states can enhance or inhibit cognitive functions linked to the NAcc [16]. The NAcc is significantly engaged by personal rewards, highlighting its involvement in memory processes associated with personal experiences [17].

Other studies link problematic internet use to deficits in working memory, decision-making, and inhibitory control [4], and daily diary studies reveal that negative affect mediates the relationship between social media use and memory failures [18]. However, most studies rely on global measures of cognitive failure and seldom differentiate specific memory processes. Moreover, research on mediation often reports modest effects [18] and rarely tests age-related differences. The current study addresses these gaps by employing the QLM to assess distinct everyday memory lapses and by comparing youth and adults.

Memory refers to the cognitive process that enables the storage, encoding, and retrieval of information, encompassing knowledge and experiences that prove useful across various life contexts [19]. According to Moreno-Osuna [20], memory—along with attention and perception—is one of the fundamental cognitive processes involved in the acquisition and consolidation of knowledge. Consequently, it plays a crucial role in academic and professional activities, such as exams, presentations, and problem-solving tasks, being highly affected by depression [21]. Memory performance is influenced by multiple biological and psychological factors, including brain health, sleep quality, emotional state, and stress levels [22].

A comprehensive meta-analysis conducted by Ioannidis and colleagues [4], encompassing a sample of 2922 individuals across 40 independent studies, revealed that problematic internet use is significantly associated with deficits in inhibitory control, decision-making, and working memory. The findings indicated that individuals exhibiting problematic internet use display objectively measurable impairments in cognitive performance when compared to control groups. These impairments may carry functional consequences in everyday life, even though part of the variance might be attributable to unmeasured comorbid psychopathologies [4].

In a similar manner to the cognitive impairments observed in IA, certain psychiatric conditions—namely depression and anxiety—can also exert detrimental effects on memory function. These disorders have been shown to compromise attentional processes and hinder the retention of information in the short term, thereby affecting overall cognitive efficiency [21]. Excessive use of the internet has been shown to aggravate pre-existing mental health conditions, with several studies highlighting a strong comorbidity between IA and a range of psychiatric disorders. Notably, a meta-analysis conducted by Ho and colleagues [23] established consistent associations between IA and psychopathological symptoms, including ADHD, alcohol abuse, depression, and anxiety. More recently, Miao and co-authors [24] identified anxiety as a significant predictive factor for IA among adolescents. These findings are further supported by Mamun and his research team [11], who reported that stress, anxiety, and depressive symptoms play a central role in the etiology and maintenance of IA, especially in vulnerable populations.

Furthermore, Romero-Rodriguez and colleagues [7] emphasize that the core symptoms of IA—notably loss of control and dependency—can precipitate additional adverse outcomes such as fatigue, psychological distress, and heightened tension. These effects are often accompanied by depressive, anxious, and stress-related symptomatology. In parallel, growing evidence has linked problematic internet use to measurable cognitive impairments. For example, Fu and collaborators [25] reported deficits in the orienting component of attentional networks among individuals with IA, suggesting altered attentional allocation processes. Complementing these findings, Montag and co-authors [26] identified structural alterations in the brain, specifically a reduction in grey matter volume within the subgenual anterior cingulate cortex—an area associated with emotional regulation and self-referential processing. These findings are further corroborated by recent neuroimaging data presented by Ding and colleagues [2].

Sha and Dong [27], who explicitly investigated TikTok use disorder and its repercussions on memory, suggested that the increasing prevalence of social media platforms, particularly TikTok, and the associated psychological ramifications may impact cognitive health. These authors utilized the digit span test, a widely accepted cognitive assessment tool, to measure memory capabilities among participants. Their findings suggested a significant correlation between TikTok use, pronounced memory deficits, and increased levels of depression, anxiety, and stress, indicating that these negative emotional states may serve as mediators in the relationship between IA and cognitive outcomes. These references provide a framework for further exploration into the relationship between IA, negative affect, and memory lapses mediated by IA [27].

Within this framework, the present study seeks to investigate the impact of IA and negative affect on memory impairments, with particular emphasis on the potential mediating role of negative affect in the relationship between IA and cognitive dysfunction. Grounded in the existing empirical literature, we propose the following hypotheses: (1) both IA and elevated levels of negative affect are significantly associated with increased memory-related difficulties; and (2) negative affect mediates the association between IA and memory impairment, thereby intensifying the cognitive deficits observed.

2. Methodology

2.1. Procedure and Participants

This study involved the participation of 254 students and teachers from among higher education, secondary, and vocational education students and higher education, secondary, and vocational education teachers in Portugal. The sample consisted of 107 (42.1%) men, 145 (57.1%) women, and 2 (0.8%) who preferred not to answer, aged between 14 and 75 years (M = 28.72, SD = 15.53). Participants were selected based on specific inclusion criteria, namely students or teachers of high (vocational or secondary) or superior schools.

All participants gave their informed consent prior to participation, in full compliance with the ethical principles outlined in the Declaration of Helsinki (1964) and its subsequent amendments. The study was also conducted in accordance with the ethical code and professional deontology established by the Portuguese Order of Psychologists [28].

Participants completed a battery of standardized scales administered through Google Forms [29], which included an informed consent section at the beginning, were are required to specify their category and answer individually. This categorization enabled an analysis of potential significant differences among clusters. The questionnaires were distributed to multiple schools (higher, secondary, and vocational) across several regions of Portugal, and any responses not originating from the intended Portuguese population were excluded.

2.2. Measures

Semi-structured questionnaires were employed to collect demographic information and subjective responses. Data were obtained through a 15-item instrument incorporating nine scales previously validated for the Portuguese population. The following scales/questionnaires were used in this study:

—PFS—Pichot Fatigue Scale [30,31]—The Pichot Fatigue Scale is a valuable tool in various research studies on fatigue, mental health, and well-being. With eight questions, it has four categorization types: absent, mild, moderate, and severe.

—EADS-21—Anxiety, Depression, and Stress Scales (EADS) [32,33]—A 21-item scale validated for the Portuguese population to assess levels of anxiety, depression, and stress among individuals, students and teachers in this case. The EADS-21 has demonstrated adequate reliability, with Cronbach’s alpha coefficients ranging from 0.74 to 0.85 (α = 0.85 for depression, 0.81 for stress, and 0.74 for anxiety) [33].

—QLM—Memory Lapses Questionnaire [34]—A 36-item scale that assesses five factors: verbal distractions, failed actions, local and geographical orientation, memory for names and faces, and recall of where certain objects were left. This instrument has demonstrated adequate test–retest reliability, with a reported coefficient of 0.61 [34].

—IAT—Internet Addiction Scale [35,36,37]—This 20-item scale assesses six dimensions: protrusion, overuse, neglect at work, anticipation, lack of control, and withdrawal from social life. The IAT demonstrated high reliability in the Portuguese version (α = 0.91) [36].

All scales were completed using Google Forms [29], with no mandatory email address collection for results submission.

2.3. Data Analysis

First, we examined the correlations between the variables using Pearson’s correlation test and compared the scores between youth and adults over 25 years old using the independent samples t-test with Welch’s correction. Subsequently, an SEM with mediation effects was constructed to examine whether negative affect mediates the relationship between Internet Anxiety and memory impairments. The Robust Maximum Likelihood (RML) estimation method was used to ensure that effect estimates remained reliable despite minor violations of multivariate normality. All analyses were performed using the lavaan package in R (v. 4.4.3) [38].

3. Results

Initially, correlations were examined between memory difficulties and the dimensions of IA, as well as scores for anxiety, depression, stress, and fatigue. Pearson’s correlation analysis revealed that memory scale scores were positively and moderately associated with the dimensions of IA, both in the functional impairment scale (0.32 < r < 0.44, ps < 0.001) and in the reactive salience scale (0.30 < r < 0.44; ps < 0.001) (see

Table 1. Correlations between IA, memory performance, and negative emotions.

	1	2	3	4	5	6	7	8	9	10	11
(1) Reactive Salience	-
(2) Functional Impairment	0.67	-
(3) Verbal Distractions	0.32	0.38	-
(4) Failed Acts	0.44	0.45	0.79	-
(5) Local Geographic Orientation	0.40	0.32	0.73	0.8	-
(6) Names and Faces Memory	0.32	0.34	0.65	0.73	0.68	-
(7) Recovery	0.34	0.43	0.87	0.8	0.72	0.68	-
(8) Depression	0.35	0.28	0.35	0.33	0.36	0.24	0.36	-
(9) Anxiety	0.34	0.24	0.35	0.39	0.41	0.24	0.35	0.8	-
(10) Stress	0.32	0.28	0.36	0.38	0.35	0.24	0.36	0.8	0.86	-
(11) Fatigue	0.37	0.39	0.46	0.48	0.43	0.41	0.45	0.68	0.62	0.63	-

Note: p < 0.001 for all correlations.

).

Next, we examined whether there were differences between youth (under 25 years old) and adults. Comparisons of means using the independent samples t-test revealed that youth scored higher on reactive salience (p < 0.001, d = 0.55), verbal distractions (p < 0.001, d = 0.53), local geographical orientation errors (p = 0.001, d = 0.52), depression (p < 0.001, d = 0.60), anxiety (p = 0.001, d = 0.48), stress (p = 0.019, d = 0.32), and fatigue (p = 0.018, d = 0.32; see

Table 2. Means and standard deviations for adult and young samples.

	Overall	Adult	Young
Measure	M (SD)	M (SD)	M (SD)	t	p	d
Reactive Salience	1.29 (0.88)	1 (0.75)	1.45 (0.91)	−3.94	<0.001	0.55
Functional Impairment	1.92 (0.88)	1.77 (0.92)	2 (0.85)	−1.86	0.064	0.249
Verbal Distractions	3.21 (1.31)	2.8 (1.06)	3.45 (1.39)	−3.74	<0.001	0.531
Failed Acts	2.60 (1.06)	2.42 (0.92)	2.69 (1.12)	−1.91	0.058	0.266
Local Geographic Orientation	2.31 (1.02)	2.01 (0.69)	2.48 (1.13)	−3.53	0.001	0.523
Names and Faces Memory	2.87 (1.26)	2.94 (1.21)	2.83 (1.29)	0.61	0.541	0.084
Recovery	3.17 (1.29)	2.98 (1.1)	3.27 (1.38)	−1.71	0.089	0.24
Depression	7.46 (5.73)	5.36 (5.21)	8.63 (5.7)	−4.36	<0.001	0.599
Anxiety	7.57 (5.54)	5.95 (4.96)	8.48 (5.66)	−3.44	0.001	0.476
Stress	9.15 (5.30)	8.07 (5.23)	9.75 (5.26)	−2.36	0.019	0.32
Fatigue	14.11 (7.56)	12.55 (7.86)	14.97 (7.26)	−2.39	0.018	0.32

Note: n adult = 85, n young = 152. df = 235.

).

Next, the relationships between variables were examined using SEMs separately for youth and adults over 25 years old. Specifically, the analysis investigated whether IA explains memory difficulties in the present sample and whether this relationship is mediated by emotional factors such as anxiety, depression, stress, and fatigue. The SEM included a latent factor for negative affect, comprising anxiety, depression, stress, and fatigue; a latent factor representing memory subscales; and a latent factor integrating scores from the IA scale. In young people the statistical results suggest that IA has a direct positive effect on memory difficulties (β = 0.53, p = 0.01) and negative affect (β = 2.04, p = 0.003). However, the negative effect on memory is relatively weak (β = 0.08, p = 0.002) compared to IA. Additionally, the indirect effect of IA on memory difficulties is low (β = 0.17, p = 0.02), indicating that negative affect accounts for 24.1% of the total effect in the model (see Figure 1). In the case of adult participants, the SEM suggests that IA has a direct positive effect on memory difficulties (β = 0.94, p = 0.002) and on negative affect (β = 3.83, p < 0.001), demonstrating that the relationships between IA, negative affect, and memory problems are stronger in adults. In contrast, among the youth group, the relationship between negative affect and memory difficulties is weak, and for adults, this relationship is nonexistent (β = 0.01, p = 0.78), as is the mediation effect (β = 0.02, p = 0.78; see Figure 1).

4. Discussion

In the present study, we investigated two primary hypotheses, (H1) that IA and elevated levels of negative affect are positively associated with increased memory impairments and (H2) that negative affect acts as a mediating variable in the relationship between IA and memory-related difficulties, thereby contributing to a deeper understanding of the mechanisms through which IA may impact cognitive functioning. The SEM results suggest that memory difficulties are indeed associated with both IA and negative affect. The current data corroborate the results documented by Sha and Dong [27], who found that TikTok use disorder (TTUD) is linked to memory impairment and elevated levels of depression, anxiety, and stress. Considering the obtained results, it can be asserted that IA is significantly associated with memory difficulties across age groups, reinforcing the growing concern in the literature regarding the deleterious effects of excessive digital exposure on cognitive functioning [2,4].

The results suggest that, particularly among adults, the direct impact of IA on memory difficulties is more robust than that among younger participants, suggesting that the cumulative effect of dysfunctional digital behaviors may become more pronounced over time. This observation complements the evidence presented by Brand and co-authors [5] and Chamberlain and colleagues [6], indicating that prolonged internet exposure can lead to structural and functional cognitive alterations.

Regarding the second hypothesis, we tested for a mediation effect to assess the presence of an indirect influence. The results indicated a small mediating effect of negative affect among the youth, while no such effect was observed in adults. This suggests that both IA and negative affect independently contribute to memory problems, indicating that each factor alone may be sufficient to explain cognitive impairments.

These findings underscore the necessity of acknowledging IA as a potentially significant clinical concern, with ramifications that extend beyond mental health to encompass impairments in cognitive functioning [4]. Evidence suggests that interventions targeting both a reduction in internet usage and the regulation of negative emotional states may be effective strategies in alleviating memory-related impairments [39,40]. This is further substantiated by the meta-analysis conducted by Zhang and colleagues [40], which demonstrated that a range of intervention modalities—including cognitive behavioral therapy (CBT), group counseling, physical activity programs, and even structured internet-based interventions—were particularly efficacious in significantly reducing IA symptomatology.

Regarding the mediating role of negative affect, the results point to weak mediation among youth and no significant mediation among adults. As suggested by Sha and Dong [27], symptoms such as depression, anxiety, and stress may exacerbate memory loss in adolescents; however, in the present study, these emotional factors appeared to be less determinant compared to direct digital exposure. These findings highlight the necessity of viewing IA as an autonomous factor impacting cognitive health, rather than merely a consequence of emotional disorders.

In terms of practical implications, these results call for a multifaceted intervention approach, combining digital time management strategies, emotional regulation programs, and the development of self-control skills. Interventions such as CBT, mindfulness programs, and increased physical activity have proven effective in reducing problematic internet behaviors [39,40] and are therefore recommended, as well as rigid protection from parents and governments in terms of digital use among young people.

A key strength of this study lies in its comprehensive assessment of negative affect, which includes multiple dimensions that are not typically evaluated together in a single study. This allowed for a broader understanding of the participants’ emotional states. However, a limitation is the age range of the sample, which consisted primarily of adolescents and young adults. Future research should consider expanding the sample to include other age groups, such as early childhood populations, who are increasingly exposed to internet content [41].

5. Conclusions

The outcomes of this research underscore a significant interaction between IA, negative affect, and memory problems, confirming the interdependence among these factors suggested by previous studies [2,4] with implications for both theoretical understanding and practical intervention. This triangulation suggests interdependence where excessive internet use can exacerbate negative emotional states, which in turn negatively impact memory, creating a feedback loop. Regardless of age, excessive exposure to digital technologies directly compromises memory abilities, with this impact being more pronounced among adults, suggesting a progressive accumulation of cognitive impairments over time.

Moreover, it was observed that while negative affect plays a modest mediating role among youth, it is not a significant factor among adults. These findings emphasize the urgency of considering IA not merely as a consequence of emotional disturbances but as an autonomous phenomenon capable of altering brain architecture and functionality.

This interdependent relationship suggests that interventions should be multifaceted, addressing both a reduction in problematic internet use and emotional support. Future research should explore specific interventions, such as mindfulness programs or cognitive behavioral therapy, to mitigate these impacts. Additionally, it would be beneficial to diversify the sample to include different age groups (for example before 15 years), ensuring a more comprehensive understanding of the phenomenon.

In light of these results, we propose that future research should focus on the development of intervention programs that simultaneously promote digital literacy, strengthen emotional regulation, and prevent addictive behaviors. Such a multifactorial approach could mitigate the vicious cycle between problematic internet use, negative emotional states, and cognitive decline. Several limitations temper the conclusions. This study was cross-sectional; therefore, causal relationships could not be established. Although we modeled directional paths, reciprocal influences (e.g., memory lapses leading to increased reliance on digital devices) are plausible [1]. The reliance on self-report measures may have introduced recall bias; self-reported memory problems often correlate poorly with objective tests and are influenced by mood [42]. Our sample, drawn from universities and vocational and secondary schools, comprised mostly students and teachers and contained no clinical cases of Internet Addiction; the results may not generalize to other populations. We did not differentiate types of internet activity, despite evidence that gaming, social media, and streaming exert distinct neural effects [1]. Future research should employ longitudinal or experimental designs, incorporate objective cognitive assessments, track digital behavior through logs, examine specific online activities, and recruit diverse age groups, including clinical populations.

Based on these conclusions, it becomes evident that digital health should be a priority in public health and educational strategies. Our society now stands at a critical crossroads: either we shape technology to foster human development, or we allow technology to shape us, compromising our most essential cognitive abilities. Science must be the beacon that illuminates this path towards responsible digital citizenship and the preservation of human memory.