# Systematic review of cultural influences on ADHD and social media addiction among adults

Almoayad Tayeb, Lucia Romo, Oulmann Zerhouni

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Almoayad Tayeb, Lucia Romo, Oulmann Zerhouni. Systematic review of cultural influences on ADHD and social media addiction among adults. Middle East Current Psychiatry, 2025, 32 (1), pp.69. 10.1186/s43045-025-00565-3. hal-05355498

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SYSTEMATIC REVIEW

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Systematic review of cultural influences
on ADHD and social media addiction
among adults

Almoayad Tayeb¹*, Lucia Romo¹ and Oulmann Zerhouni¹

**Abstract**

This systematic review explored cultural influences on attention-deficit/hyperactivity disorder (ADHD) and social media addiction among adults. With increased digital engagement among young people, concerns about ADHD and its interaction with social media use have become more apparent. This review examined how cultural backgrounds influence the prevalence, manifestations, and management of ADHD and social media addiction. Following a systematic search, ten studies met the inclusion criteria and were analyzed. The research provided a comprehensive overview highlighting significant cultural differences in how these conditions are perceived and addressed. Results indicated that cultural and social dynamics significantly influenced both ADHD presentation and susceptibility to social media addiction. Our findings highlighted the need for culturally sensitive diagnostic and intervention strategies tailored to different sociocultural environments.

**Keywords** ADHD, Social media addiction, Cultural influences, Adult, Mental health

**Introduction**

Attention-deficit hyperactivity disorder (ADHD) is a prevalent neurodevelopmental condition, often diagnosed in childhood. It is characterized by symptoms such as inattention, hyperactivity, and impulsivity, which can greatly disrupt daily functioning [30]. Attention-deficit/hyperactivity disorder (ADHD) is consistently linked to various social challenges, including difficulties in forming and maintaining close relationships, as well as a heightened risk of social rejection and victimization. While these struggles are well documented in offline interactions, emerging research indicates that they also extend to the digital sphere, particularly in the context of social media use. Individuals with ADHD often exhibit impulsivity, difficulty regulating attention, and a strong need

for immediate social reinforcement factors—that may
contribute to problematic social media engagement [21].

Problematic social media use (PSMU) refers to an intense preoccupation with social media, marked by a strong urge to engage with it and excessive time and effort spent that negatively affects social life, academics or work, relationships, and mental health [43].

Particularly under the expansive umbrella of PSMU, while not yet officially recognized in diagnostic frameworks, the term captures a range of behaviors linked to psychological distress, including anxiety and depression, often exacerbated by factors like poor self-control and excessive online engagement [53]. Meanwhile, certain conditions related to this type of behavior have been recognized, such as gaming disorder. Defined in the International Classification of Diseases (ICD-11), gaming disorder involves a pattern of gaming behavior, either digital or video gaming, that is characterized by an inability to control gaming, prioritizing gaming over other life activities to the extent that it becomes more important than other interests and daily activities, and persisting

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<footnote>*Correspondence:
Almoayad Tayeb
Almoayat@gmail.com
¹ Department of Clinical Psychology, Paris Nanterre University, Nanterre, France</footnote>
or increasing gaming despite experiencing negative consequences [57]. In 2013, the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) included Internet gaming disorder (IGD) as a condition for further study [11]. The diagnoses “Internet Gaming Disorder” and “Gaming Disorder” both refer to a problematic use of computer games during the last year. The DSM-5 lists nine criteria for IGD: (1) excessive preoccupation with playing computer games, (2) withdrawal symptoms, (3) development of tolerance, (4) unsuccessful attempts to control playing, (5) loss of interest in (other) previous hobbies and leisure activities, (6) continuation of excessive playing, despite insight into the psychosocial consequences, (7) deceiving others regarding the scope of playing, (8) use of computer games to escape or compensate for negative mood, and (9) risking or losing important relationships, jobs, or career prospects because of gaming behavior. If five or more of these nine criteria are met, a diagnosis of IGD can be given [56].

Furthermore, social media addiction, which involves interaction with digital platforms that support social interaction, is characterized by frequent and intense online activities across different platforms and is increasingly associated with a range of psychological disorders such as anxiety, depression, and insomnia [61]. In addition, research suggests a complex relationship between ADHD and social media use, and ADHD symptoms may increase the risk of social media addiction, influenced by factors such as low self-esteem and impulsive behavior patterns. These issues require tailored intervention strategies that take into account the distinct psychosocial dynamics involved [2, 54, 55]. Cultural differences significantly influence the perception and management of ADHD and social media addiction. Strong community and family ties may buffer against the negative impacts of these disorders, suggesting that cultural factors play a crucial role in both the manifestation and management of these conditions [5, 24]. This review explored cultural variations in the recognition and reporting of ADHD symptoms like inattention and hyperactivity and social media addiction symptoms like excessive use. The goal was to understand how cultural differences influence the diagnosis and management of these conditions, emphasizing the role of cultural norms and social expectations.

## Objectives

The primary aim of this review was to investigate how cultural factors impact the prevalence, manifestation, and management of ADHD and social media addiction among adults. This study sought to explore how different cultures influence the way ADHD and social media addiction are recognized, reported, and treated, helping us better understand these issues.

## Methods

A systematic literature review (SLR) was carried out, following the principles and phases of the PRISMA model. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement is an authoritative and updated guideline that enhances transparency in the reporting of systematic reviews. It addresses the rationale, methods, and outcomes of reviews [31]. The choice of the PRISMA framework was driven by its standardization, which ensures consistency and reliability in the systematic review process, and its comprehensiveness [28], which is critical to addressing the multifaceted issues of ADHD and social media addiction among adults. We followed the four standard PRISMA phases: Identification, Screening, Eligibility, and Inclusion. The search was conducted in January 2024, ensuring that the most recent literature was included. The entire selection process was independently reviewed by two researchers to minimize bias and enhance reliability. Any disagreements during article selection were resolved through discussion until a consensus was reached.

The flow chart with all the detailed information/statistics is shown in Fig. 1. Below, we explain the four stages in detail.

### Identification phase

#### Selection of databases

During the initial phase, we selected various scholarly databases to ensure broad coverage of relevant literature. The selected databases included PubMed, PsycINFO, Scopus, and Web of Science. These platforms were specifically chosen for their ability to provide access to the diverse, high-quality academic resources needed to investigate contemporary research on ADHD and social media addiction.

#### Selection of keywords

We carefully selected keywords for this systematic literature review (SLR) to address specific research questions, including:

- “ADHD,” “social media addiction,” “digital addiction,” “internet use disorder,” “internet gaming disorder, cultural influences,” “cultural factors,” “adults,” “mental health,” “behavioral influence,” and “psychological influence.”

These keywords were strategically combined using the logical operators “AND” and “OR” to improve the precision and scope of the search, as suggested by Eoghan Ryan (2022). Searches were conducted using these keywords to create effective queries such as
<figure><img src="image_4.png" /><figcaption>**Fig. 1** PRISMA flow chart</figcaption></figure>

("ADHD" OR "Attention-Deficit/Hyperactivity Disorder") AND ("social media addiction" OR "digital addiction" OR "internet use disorder") AND ("cultural influences" OR "cultural factors") AND "adult" AND ("mental health" OR "behavioral influence" OR "psychological influence").

**Initial search**

Utilizing the PRISMA framework, we conducted a comprehensive search across the selected databases using the specified keywords.

**Eligibility criteria**

Our inclusion criteria targeted studies published in the past decade (2014 to 2024) that were peer-reviewed, available in English, and with a specific focus on ADHD or social media addiction. Conversely, our exclusion criteria excluded non-peer-reviewed articles, studies not written in English, e.g., [32], those outside our specified time frame, e.g., [13, 19], and research not directly related

to ADHD or social media addiction (e.g., Subu et al., [52], case studies (e.g., Rahm, [38], Ricci et al., [39], and literature review (e.g., Popat & Tarrant [34]).

**Duplicates removal**

We excluded all duplicate entries, reducing the number of remaining articles after the identification phase.

**Screening phase**

We reviewed the title and abstract of each article during the screening phase before moving on to the subsequent eligibility phase. Screening was performed using strict inclusion and exclusion criteria for this phase.

**Inclusion and exclusion criteria**

The criteria during this stage focused on selecting articles that specifically addressed ADHD and social media addiction among adults and excluding those that did not focus on adults (defined as individuals older than 18 years of age [58]).
## Eligibility stage

A total of 302 articles that successfully passed the second screening stage were selected for in-depth full-text review. All articles were accessed, and the established filtering criteria were applied to evaluate each article at this stage.

## Inclusion and exclusion criteria

The eligibility phase applied strict criteria to refine the selection of articles, including studies that focused on the impact of cultural aspects of ADHD and social media addiction among adults specifically. Articles for which we could not access the full text were excluded, as were articles that deviated from this focus or lacked a detailed cultural analysis, resulting in a significant reduction in eligible articles. Several articles were excluded, such as Aydin et al., [9], Griffiths, [23], and Hussain and Wegmann, [25]. This careful selection ensures that the final set of articles strongly represents the most relevant and up-to-date research, providing a solid foundation for identifying effective strategies and understanding the impact of cultural factors on these conditions.

## Results

### A. Research and study selection

The initial search yielded 1114 articles from four major databases: PubMed (N=420), PsycINFO (N=244), Scopus (N=150), and Google Scholar (N=300). After removing 200 duplicate entries, 914 records remained for screening. Articles were evaluated based on predefined inclusion and exclusion criteria, which required studies to be peer-reviewed, published between 2014 and 2024, written in English, and focused on ADHD or social media addiction among adults. During the screening phase, 612 articles were excluded for not focusing on ADHD and social media use among adults. Following this, 302 full-text articles were assessed for eligibility. At this stage, 54 articles were excluded due to inaccessible full texts, and 238 articles were excluded for deviating from the study's focus on cultural aspects or lacking detailed cultural analysis. After applying the final eligibility criteria, 10 studies were selected for inclusion in this systematic review. This rigorous selection process ensured that the review focused on the most relevant and high-quality studies examining cultural influences on ADHD and social media addiction among adults.

Table 1 lists studies found that have explored cultural influences on ADHD and social media addiction, detailing some key points from each (authors, the nature of the sample, the aim of the study, and the most important results.

## B. Selected studies characteristics

### a) Studies type

The systematic review includes 10 studies employing various research designs. Seven studies were cross-sectional surveys, providing a snapshot of ADHD symptoms and social media addiction prevalence across different cultural settings [40, 45], Al [3, 4, 42, 50]. One study was a longitudinal cohort study [17], tracking ADHD diagnosis trends over a decade. Additionally, one meta-analysis [16] examined ADHD and social media addiction prevalence across 32 nations, and one cross-cultural validation study [8] tested the reliability of the Bergen Facebook Addiction Scale across different cultural groups.

### b) Sample characteristics

The studies analyzed a diverse range of populations across multiple countries, including the United States, France, Saudi Arabia, India, Spain, UAE, Algeria, Bangladesh, Pakistan, and Poland. Sample sizes varied widely, with the smallest study including 150 participants [42, 50] and the largest study analyzing over 5.2 million adults [17]. Most studies focused on university students or young adults [3, 22, 40], while others included general adult populations [45], Al [4, 16]. The age range across studies was 18 to 68 years, with varying gender distributions. Some studies highlighted gender-specific differences, with higher ADHD symptoms reported in females [3] and higher internet addiction rates in males [50].

### c) Instrument characteristics

A variety of standardized instruments were used to measure ADHD symptoms, social media addiction, and behavioral influences. ADHD was commonly assessed using the Adult ADHD Self-Report Scale (ASRS) (Al [3, 4]), Wender Utah Rating Scale [40], and Caterino's Adult ADHD Scale (CAADS) [22]. Social media and digital addiction were measured using tools such as the Bergen Social Media Addiction Scale (BSMAS) [16, 42], Internet Addiction Test (IAT) [50], and Bergen Facebook Addiction Scale (BFAS) [8]. Other studies utilized additional behavioral measures, including the Young Internet Addiction Test, Depression Anxiety Stress Scales (DASS-21), and problematic mobile phone use scales to assess addiction severity and psychological distress.
<table><caption>**Table 1** Studies selected within the systematic review</caption><thead><tr><th>Authors and year</th><th>Type of study</th><th>Samples</th><th>Location</th><th>Assessment instruments</th><th>Findings</th></tr></thead><tbody><tr><td>Seo et al. [45]</td><td>Cross-sectional survey</td><td>432 adults in the USA, 51.2% male, 48.8% female; age range 18–68 years (mean = 32.01, SD = 10.10)</td><td>USA</td><td>ADHD Self-Report Scale, measures of social assurance and connectedness, measures of problematic mobile phone use</td><td>ADHD symptoms were linked to problematic mobile phone use, particularly among individuals with a strong need or social connectivity. Women exhibited higher levels of multitasking behaviors due to cultural expectations</td></tr><tr><td>Romo et al. [40]</td><td>Cross-sectional study</td><td>1517 students (472 from Paris, Nanterre and 1042 from Rouen). Male to female ratio: 0.46. Mean age: 20.6 years (SD = 3.6)</td><td>France</td><td>Wender Utah Rating Scale, Adult ADHD Self-Report Scale, various addiction assessment tools (SCOFF, IAT, Yale Food Addiction Scale, Echeburua's, Canadian Problem Gambling Index), Godin's Leisure Time Exercise Questionnaire</td><td>ADHD prevalence was 5.6% and linked to higher risks of substance use (alcohol, cannabis, tobacco) and behavioral addictions (gambling, compulsive buying, internet addiction)</td></tr><tr><td>Gómez-Benito et al. [22]</td><td>Cross-cultural study</td><td>Total of 902 participants; high school (23%), junior college (24%), university (53%), Ethnic groups: African American (n = 210), Hispanic American (n = 148), European American (n = 306), Spanish (n = 238). Mean age: 20.39 years (SD = 4.90)</td><td>USA, Spain</td><td>Caterino's Adult ADHD Scale (CAADS)</td><td>ADHD symptoms varied across cultures, with Hispanic Americans displaying the highest levels. Parenting styles influenced symptom reporting</td></tr><tr><td>Chung et al., [17]</td><td>Longitudinal cohort (2007–2016)</td><td>5,282,877 adults (2,667,562 women [50.5%]; 2,615,315 men [49.5%]); ages and specific racial/ethnic composition SD = not defined</td><td>Kaiser Permanente Northern California</td><td>Licensed mental health clinician–diagnosed ADHD</td><td>ADHD prevalence increased from 0.43% (2007) to 0.96% (2016). White adults had the highest diagnosis rates, while Asian Americans and Pacific Islanders had the lowest</td></tr><tr><td>Al Hadi, Ahmad N. et al. [28]</td><td>Cross-sectional</td><td>Total: 2076 adults, Males: 707 Females: 1369 Mean (SD) = 33.66 (10.88%)</td><td>Saudi Arabia</td><td>Adult ADHD Self-Report Scale (ASRS), IGD-20 scale</td><td>ADHD prevalence was 28.6% in the general population and 30.8% among gamers. Cultural factors such as socioeconomic status and marital stability influenced ADHD and gaming addiction rates</td></tr><tr><td>Sagar and Kumar [42]</td><td>Cross-sectional study</td><td>(150 male, 150 female); mean age 22.45 (SD = 4.67)</td><td>India</td><td>Adult ADHD Self-Report Scale, Bergen Social Media Addiction Scale</td><td>Social media addiction was significantly linked to ADHD symptoms, especially in younger individuals and those with lower education levels</td></tr></tbody></table>
<table><caption>**Table 1 (continued)**</caption><thead><tr><th>Authors and year</th><th>Type of study</th><th>Samples</th><th>Location</th><th>Assessment instruments</th><th>Findings</th></tr></thead><tbody><tr><td>Cheng et al. [16]</td><td>Meta-analysis</td><td>63 independent samples with a total of 34,798 respondents, including adolescents, university students, and community adults, mean ages 24 years. The gender distribution across the samples was 56% female and 44% male<br>SD= not defined</td><td>Global, 32 nations across seven world regions</td><td>BSMAS used for measuring social media addiction</td><td>Collectivist cultures had a higher social media addiction prevalence (31%) than individualist cultures (14%), due to stronger social ties</td></tr><tr><td>Atroszko et al. [8]</td><td>Cross-cultural validation study</td><td>5470 university and high school students<br>- Algerian university students:<br>SD= 4.66<br>- Algerian high school students:<br>SD= 5.28<br>- Bangladeshi university students:<br>SD= 6.00<br>- Pakistani university students:<br>SD= 6.62<br>- Polish university students<br>(2019): SD= 5.36<br>- Polish university students<br>(2016): SD= 5.10<br>- Polish high school students:<br>SD= 4.65<br>- UAE university students:<br>SD= 5.96</td><td>Algeria, Bangladesh, Pakistan, Poland, United Arab Emirates</td><td>Bergen Facebook Addiction Scale (BFAS), Depression Anxiety Stress Scales (DASS-21)</td><td>The Facebook Addiction Scale performed inconsistently across different cultures, questioning its cross-cultural validity</td></tr><tr><td>Singh et al. [50]</td><td>Cross-sectional</td><td>150 students (94 males, 56 females); Mean age: 21.56±3 years<br>For IAT positive:<br>SD= 13.35<br>For IAT negative:<br>SD= 14.36</td><td>Bangalore, India</td><td>Young Internet Addiction Test, Bergen's Facebook Reporting Scale, ADHD Self-Reporting Scale, Wender Utah Brief Rating Scale, Cohen Perceived Stress Scale</td><td>Internet addiction was found in 23.3% of students, with strong correlations to ADHD symptoms (47%) and perceived stress (46%)</td></tr><tr><td>Al-Yateem et al. [3]</td><td>Cross-sectional</td><td>406 young adults; 141 males, 265 females; aged 18–20 years<br>SD= 0.5</td><td>United Arab Emirates</td><td>Adult ADHD Self-Report Scale (ASRS)</td><td>ADHD prevalence was 34.7% among UAE university students. Female students reported higher ADHD symptoms, possibly due to cultural stigma in symptom recognition</td></tr></tbody></table>
## C. Results of selected studies

### A) *Cultural differences in ADHD diagnosis and reporting*

ADHD diagnosis and symptom recognition vary significantly across cultures due to differences in parenting styles, healthcare access, and societal attitudes toward mental health. Some cultures may normalize ADHD-related behaviors, leading to lower diagnosis rates, while others may pathologize certain behaviors, resulting in higher ADHD prevalence. Chung et al. [17] found that White adults in the USA had the highest ADHD diagnosis rates, while Asian Americans and Pacific Islanders had the lowest. This disparity may be due to cultural differences in healthcare-seeking behavior and varying levels of awareness about ADHD. Similarly, Gómez-Benito et al. [22] found that Hispanic Americans exhibited higher ADHD symptoms than European Americans, which may be linked to more permissive parenting styles or differing cultural expectations for impulsivity and hyperactivity. Furthermore, Atroszko et al. [8] raised concerns about the validity of diagnostic tools across cultures, highlighting that standardized ADHD assessments do not always capture cultural nuances, leading to potential misdiagnosis or underdiagnosis in some populations. These findings suggest a strong need for culturally adapted ADHD diagnostic frameworks to ensure more equitable mental health assessments worldwide.

### B) *Influence of cultural norms on social media use*

Social media addiction is strongly shaped by cultural values and societal expectations regarding social engagement and digital communication. In cultures that emphasize collectivism and social harmony, individuals may feel greater pressure to stay connected online, increasing their risk of problematic social media use. Cheng et al. [16] conducted a global meta-analysis and found that social media addiction was significantly higher in collectivist cultures (31%) compared to individualist cultures (14%). The result suggests that group conformity norms and social bonding pressures contribute to excessive digital engagement. Seo et al. [45] explored the relationship between ADHD symptoms and mobile phone dependency in the USA, finding that individuals with ADHD often use social media excessively to fulfill social assurance needs, particularly among women. Singh et al. [50] further highlighted how academic stress in India drives internet addiction among students who turn to digital platforms as a coping mechanism for academic pressures. (“Internet addiction” refers to excessive Internet use across multiple domains, including gaming, browsing, and social networking that causes significant psychological and social disturbance along with functional impairment). These studies collectively indicate that social media addiction is not solely an individual

issue but is influenced by broader cultural expectations regarding connectivity, social validation, and stress management.

### D) *Gender and socioeconomic factors*

Gender and socioeconomic status play a critical role in both ADHD diagnosis and social media addiction. In many cultures, women face greater barriers to ADHD diagnosis due to stigma and societal expectations that discourage hyperactivity or impulsivity in females. Al-Yateem et al. [3] found that female students in the UAE reported significantly higher ADHD symptoms than their male peers, possibly due to cultural norms that discourage open discussion of mental health among women. Similarly, Romo et al. [40] in France observed that women tend to underreport ADHD symptoms, leading to potential underdiagnosis or misdiagnosis. On the other hand, socioeconomic factors also shape ADHD and digital addiction prevalence. Al Hadi et al. [4] found that in Saudi Arabia, ADHD prevalence was highest among unmarried and lower-income individuals, suggesting that economic stability and structured lifestyles act as protective factors against ADHD-related challenges. Moreover, Pellegrino et al. [33] and Wright et al. [59] found that lower-income individuals engage in social media addiction at higher rates, as online platforms provide an accessible escape from financial and social stressors. These findings point out the need for gender-sensitive and economically inclusive approaches to ADHD treatment and social media addiction interventions.

## Discussion

In this systematic review, we delve deeply into the myriad ways that cultural contexts shape the perception and management of attention-deficit/hyperactivity disorder (ADHD) and social media addiction. Our findings demonstrated that ADHD and social media addiction were significantly influenced by cultural, gender, and socioeconomic factors. Individuals with ADHD were more susceptible to excessive social media use, often as a coping mechanism to fulfill unmet social or emotional needs. Additionally, individuals with lower incomes were more likely to show both ADHD symptoms and problematic social media use, probably as a way to escape from daily stressors.

Our findings aligned with the scholarly assertion made by Ryu and Fan [41], who argued that economic stability acts as a crucial buffer against psychiatric disorders, underscoring the integral relationship between economic security and the prevalence and management of mental health issues. Furthermore, this observation resonated with the insights of Quinn and Madhoo [36] and Ahad et al. [1], who highlight that cultural stigmas and
societal pressures often inhibit women from seeking
mental health services, leading potentially to a significant
underdiagnosis or misdiagnosis in this demographic. In
addition, Gómez-Benito et al. [22] uncover striking dif-
ferences in ADHD symptom prevalence between the
USA and Spain, variations that are likely influenced by
divergent cultural parenting practices. This variance
suggests that Hispanic Americans might exhibit higher
symptom levels due to specific cultural expectations, a
notion that Chan et al. [15] corroborate by showing how
different cultural approaches to parenting can affect lev-
els of parental distress and alter ADHD classification
thresholds.

Furthermore, Shen et al. [46] identified a direct link
between academic stress and internet addiction, high-
lighting that educational stressors significantly contrib-
ute to adverse emotional states and addictive behaviors
online, thus emphasizing the need for interventions that
address both educational pressures and individual coping
mechanisms. Also, Shi et al. [47] advocated for culturally
sensitive diagnostic and treatment approaches to mental
health, thereby addressing broader issues of healthcare
equity and the imperative for diagnostic processes that
are cognizant of cultural and racial diversities. In addi-
tion, Atroszko et al. [8] questioned the cross-cultural
validity of diagnostic tools like the Bergen Facebook
Addiction Scale, advocating for the cultural adaptation
of such tools to ensure their reliability and effectiveness
in diverse settings. The study by Copez-Lonzoy et al.
[18] further emphasized the necessity of local valida-
tion for such diagnostic instruments, ensuring their rel-
evance and efficacy across varying cultural landscapes.
Lastly, Cheng et al. [16] and Seo et al. [45] discussed the
cultural impact on social media and mobile phone usage
and noted that societal expectations of connectivity, par-
ticularly among women, intensified symptoms of ADHD.
This observation was further explored by Pellegrino et al.
[33] and Wright et al. [59] who discussed the significant
impact of social media on individual well-being, particu-
larly in collectivist societies where the cultural emphasis
on group harmony and interconnectedness can amplify
the effects of social media on mental health.

Adolescence is characterized by significant transfor-
mations in the cognitive and social-affective domains of
the developing brain [7], and it is hypothesized that this
developmental phase involves increased social processing
[10]. The imbalance hypothesis states that the adolescent
brain is particularly predisposed to rewards, whether
social (e.g., favorable peer feedback) or non-social (e.g.,
financial) [14, 48]. Research confirms these theories,
indicating that brain activity in the reward system (e.g.,
ventral striatum) reaches peak levels in response to
rewards during adolescence, whereas the brain regions

responsible for cognitive control (e.g., dorsolateral pre-
frontal cortex) develop at a more gradual rate [12, 44, 49].

The neurobiological traits of ADHD, including deficits
in executive functions like response inhibition, working
memory, and planning, along with a strong preference
for immediate rewards, are evident at the behavioral
level [20, 29]. For adolescents with ADHD, digital media's
rapid information flow and instant feedback may be par-
ticularly appealing [37]. Since reward-related brain activ-
ity is heightened in social contexts, social media can be
especially reinforcing, compounded by limited cogni-
tive control in ADHD [21]. Consequently, regular social
media use may more easily escalate into problematic use
in this population.

ADHD frequently coexists with comorbid illnesses,
including addiction disorders. Numerous studies have
found correlations between ADHD and addictions [51].
The research conducted by Porteret et al. [35] indicated
that individuals with potential ADHD engaged in com-
pulsive buying (23.4%), problematic gambling (7.4%),
and compulsive sexual behaviors (2.4%). Leménager
et al. [27] identified elevated prevalence rates of lifetime
and current ADHD among Internet-addicted individu-
als compared to those in problematic and healthy groups.
Furthermore, Kim et al. [26] demonstrated that the inten-
sity of Internet addiction strongly forecasted the majority
of ADHD symptom dimensions.

Moreover, Andreassen et al. [6] established a positive
association between ADHD and addictive technological
behaviors. Addictive social networking exhibited mod-
erately high correlations with ADHD measures. ADHD
accounted for a greater proportion of the variance in
addictive social networking (β=0.268) than in video
gaming (β=0.176). The link between ADHD and addic-
tive social networking, especially through mobile phones,
may be due to the distractions from notifications, con-
stant updates from many friends, and the nature of these
platforms. These factors may compel vulnerable individ-
uals, such as those who are easily distracted or impulsive,
to engage in excessive or compulsive use of social net-
works as a form of self-medication [60].

## Limitations

While this systematic review provides valuable insights
into the cultural influences on ADHD and social media
addiction among adults, several limitations should be
acknowledged. First, the majority of included studies
were cross-sectional, limiting the ability to draw causal
inferences about the relationships between cultural fac-
tors, ADHD symptoms, and social media use. Second,
the exclusion of grey literature may contribute to publ-
cation bias, as the review primarily incorporated peer-
reviewed articles available in academic databases. Third,
reliance on self-reported data introduces social desirability and recall biases. In addition, the heterogeneity of assessment tools used across studies introduces limitations. Furthermore, the review excluded studies not published in English, introducing potential language bias.

## Clinical implications

The findings of this review underscored the complicated interaction between cultural factors and the management of ADHD and social media addiction. Future studies should prioritize the development of cross-cultural validation of diagnostic and screening tools to ensure their accuracy and sensitivity across diverse populations. Longitudinal designs and mixed-methods approaches are particularly encouraged to capture the evolving nature of social media engagement and ADHD symptoms in culturally specific contexts.

Clinically, the review highlights the need for gender-sensitive and culturally tailored intervention strategies. Mental health practitioners must be aware of the cultural narratives that shape perceptions of ADHD and social media addiction, and should incorporate this awareness into diagnostic assessments, treatment planning, and psychoeducational interventions.

Culturally appropriate psychoeducation programs can empower individuals and communities, reduce stigma, and improve treatment uptake. Also, expanding telehealth services, subsidizing treatment costs, and offering community-based awareness programs are all potential strategies to bridge mental health disparities.

## Conclusion

This review highlights the significant impact of cultural factors on the epidemiology and treatment of these conditions. Studies from regions like Saudi Arabia and the UAE demonstrate how societal norms, economic conditions, and gender expectations can deeply affect the prevalence and recognition of ADHD and related disorders like Internet Gaming Disorder. Notably, these cultural factors influence diagnostic rates and the perception of symptoms, suggesting the necessity for culturally informed healthcare practices. Gender disparities and societal biases particularly impact how ADHD is diagnosed and managed, which points to the importance of healthcare approaches that are sensitive to cultural and gender differences. Additionally, the review points out the relationship between educational pressures and social media addiction, advocating for targeted interventions that address cultural pressures. The findings support including cultural views in mental health research and practices to improve treatment effectiveness and make sure mental health services fit different cultural

backgrounds, ultimately promoting fairness in mental health worldwide.

## Acknowledgements

This systematic review was conducted as part of the doctoral research of Tayeb Almoayad at Paris Nanterre University (Student ID: 43019676), within the Doctor of Philosophy (DOC) program in Clinical Neuropsychology, under the subject: ED 139 CLM. The author gratefully acknowledges the support of Paris Nanterre University and the guidance received throughout the research process.

## Authors' contributions

A.T. conceived the research idea, conducted the systematic literature review, and drafted the manuscript. L.R. supervised the research process, provided critical revisions, and contributed to the interpretation of findings. O.Z. assisted in methodological refinement, reviewed the search strategy, and contributed to the final manuscript editing. All authors read and approved the final version of the manuscript.

## Funding

This research received no external funding. The study was entirely self-funded by the authors, with no financial support from governmental, private, or non-profit organizations. The authors declare that there were no financial influences or sponsorships that could have affected the objectivity, methodology, or findings of this systematic review.

## Data availability

No datasets were generated or analysed during the current study.

## Declarations

### Ethics approval and consent to participate

This study is a systematic review of previously published data and does not involve human participants or animals.

### Consent for publication

This article does not contain any individual personal data or unpublished material requiring consent for publication.

### Competing interests

The authors declare no competing interests.

Received: 1 April 2025 Accepted: 8 August 2025

Published online: 20 August 2025

## References

1. Ahad AA, Sanchez-Gonzalez M, Junquera P (2023) Understanding and addressing mental health stigma across cultures for improving psychiatric care: a narrative review. Cureus 15(5):e39549. https://doi.org/10.7759/cureus.39549

2. Al-Samarraie H (2021) Young users' social media addiction: causes, consequences, and preventions. Inf Technol People 34(4):1084-1129

3. Al-Yateem N, Slewa-Younan S, Halimi A, Saeed SA, Tliti D, Mohammad M, Ridwan M, Zeidan R, Hammash MH, Ahmed FR, Dias JM, Rahman SA, Subu MA, Hijazi H, Yeganeh F, Momani A, Zandi M, Mottershead R (2023) Prevalence of undiagnosed attention deficit hyperactivity disorder (ADHD) symptoms in the young adult population of the United Arab Emirates: a national cross-sectional study. J Epidemiol Glob Health. https://doi.org/10.1007/s44197-023-00167-4

4. Al Hadi AN, Aldussary DM, Abanumy JA, Alghamdi MA, Alsalhi NA, Alghamdi SA (2021) The prevalence of attention deficit hyperactivity disorder, internet gaming disorder and their association among adults in Saudi Arabia: a cross-sectional study. Aljouf Univ Med J 8(2):45-56. https://doi.org/10.12816/0058988

5. Alshalan LZ, Mohammed S, Yati A, Alaryni A (2024) Examining the Effects of Social Media on Mental Health Among Adolescents in Saudi Arabia
Study design and setting 16(1):10-12. https://doi.org/10.7759/cureus.53261

6. Andreassen CS, Billieux J, Griffiths MD, Kuss DJ, Demetrovics Z, Mazzoni E, Pallesen S (2016) The relationship between addictive use of social media and video games and symptoms of psychiatric disorders: a large-scale cross-sectional study. Psychol Addict Behav 30(2):252

7. Andrews JL, Ahmed SP, Blakemore S-J (2021) Navigating the social environment in adolescence: the role of social brain development. Biol Psychiatry 89(2):109-118

8. Atroszko PA, El Abididine FZ, Malik S, Mamun MA, Vally Z, Czerwiński SK (2022) Lack of measurement invariance in a widely used Facebook addiction scale may thwart progress in research on social-network-use disorder: a cross-cultural study. Comput Hum Behav 128:107106. https://doi.org/10.1016/j.chb.2021.107132

9. Aydin T, Parris BA, Arabaci G, Kilintari M, Taylor J (2024) Trait-level non-clinical ADHD symptoms in a community sample and their association with technology addictions. Curr Psychol 43(12):10682-10692. https://doi.org/10.1007/s12144-023-05203-x

10. Blakemore S-J, Mills KL (2014) Is adolescence a sensitive period for socio-cultural processing? Annu Rev Psychol 65(1):187-207

11. Borges G, Orozco R, Benjet C, et al. (2021) (Internet) Gaming Disorder in DSM-5 and ICD-11: A Case of the Glass Half Empty or Half Full. Can J Psychiatry 66(5):477-484. https://doi.org/10.1177/0706743720948431

12. Braams BR, van Duijvenvoorde ACK, Peper JS, Crone EA (2015) Longitudinal changes in adolescent risk-taking: a comprehensive study of neural responses to rewards, pubertal development, and risk-taking behavior. J Neurosci 35(18):7226-7238

13. Carli V, Durkee T, Wasserman D, Hadlaczky G, Despalins R, Kramarz E, Wasserman C, Sarchiapone M, Hoven CW, Brunner R (2012) The association between pathological internet use and comorbid psychopathology: a systematic review. Psychopathology 46(1):1-13

14. Casey BJ, Galván A, Somerville LH (2016) Beyond simple models of adolescence to an integrated circuit-based account: a commentary. Dev Cogn Neurosci 17:128-130

15. Chan WWY, Shum KK-M, Sonuga-Barke EJS (2022) Attention-deficit/hyperactivity disorder (ADHD) in cultural context: do parents in Hong Kong and the United Kingdom adopt different thresholds when rating symptoms, and if so why? Int J Methods Psychiatr Res 31(3):e1923. https://doi.org/10.1002/mpr.1923

16. Cheng C, Lau Y, Chan L, Luk JW (2021) Prevalence of social media addiction across 32 nations: meta-analysis with subgroup analysis of classification schemes and cultural values. Addict Behav 117:106845. https://doi.org/10.1016/j.addbeh.2021.106845

17. Chung W, Jiang S, Paksarian D, Nikolaidis A, Castellanos FX (2019) Trends in the prevalence and incidence of attention-deficit/hyperactivity disorder among adults and children of different racial and ethnic groups. JAMA Netw Open 2(10):e1914344. https://doi.org/10.1001/jamanetworkopen.2019.14344

18. Copez-Lonzoy A, Vallejos-Flores M, Capa-Luque W, Salas-Blas E, Montero Doig AM, Dias PC, Bazo-Alvarez JC (2023) Adaptation of the Bergen Social Media Addiction Scale (BSMAS) in Spanish. Acta Psychol 241:104072. https://doi.org/10.1016/j.acplysy.2023.104072

19. Das D, Cherbuin N, Butterworth P, Anstey KJ, Easteal S (2012) A population-based study of attention deficit/hyperactivity disorder symptoms and associated impairment in middle-aged adults. PLoS One 7(2):e31500

20. Dekkers TJ, de Water E, Scheres A (2022) Impulsive and risky decision-making in adolescents with attention-deficit/hyperactivity disorder (ADHD): the need for a developmental perspective. Curr Opin Psychol 44:330-336

21. Dekkers TJ, van Hoorn J (2022) Understanding problematic social media use in adolescents with attention-deficit/hyperactivity disorder (ADHD): a narrative review and clinical recommendations. Brain Sci. https://doi.org/10.3390/brainsci12121625

22. Gómez-Benito J, Van de Vijver FJR, Balluerka N, Caterino L (2019) Cross-cultural and gender differences in ADHD among young adults. J Atten Disord 23(1):22-31. https://doi.org/10.1177/1087054715611748

23. Griffiths MD (2021) The associations between problematic social networking site use and sleep quality, attention-deficit hyperactivity disorder, depression, anxiety and stress. Psychiatr Hungar 36(4):686-700.

24. Hammad MA, Awed HS (2023) Investigating the relationship between social media addiction and mental health. Nurture 17(3):149-156. https://doi.org/10.55951/NURTURE.V17I3.282

25. Hussain Z, Wegmann E (2021) Computers in Human Behavior Reports Problematic social networking site use and associations with anxiety, attention deficit hyperactivity disorder, and resilience. Computers in Human Behavior Reports 4:100125. https://doi.org/10.1016/j.chbr.2021.100125

26. Kim D, Lee D, Lee J, Namkoong K, Jung Y-C (2017) Association between childhood and adult attention deficit hyperactivity disorder symptoms in Korean young adults with internet addiction. J Behav Addict 6(3):345-353

27. Leménager T, Hoffmann S, Dieter J, Reinhard I, Mann K, Kiefer F (2018) The links between healthy, problematic, and addicted internet use regarding comorbidities and self-concept-related characteristics. J Behav Addict 7(1):31-43

28. Li T, Higgins JPT, Deeks JJ (2021) Chapter 5: Collecting data. In: Cochrane Handbook for Systematic Reviews of Interventions version 6.2 (updated February 2021). Cochrane Training.

29. Marx I, Hacker T, Yu X, Cortese S, Sonuga-Barke E (2021) ADHD and the choice of small immediate over larger delayed rewards: a comparative meta-analysis of performance on simple choice-delay and temporal discounting paradigms. J Atten Disord 25(2):171-187

30. Newcom JH, Krone B, Coghill D, Halperin JM (2023) Neurodevelopmental disorders: attention-deficit/hyperactivity disorder. Tasman's Psychiatry pp. 1-40.

31. Page MJ, McKenzie JE, Bossuyt PM, et al. (2021) The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ (Clinical Research Ed.) 372:n71. https://doi.org/10.1136/bmj.n71

32. Paulina LR, Csejtei I, Miklósi M (2023) [Attention deficit/hyperactivity symptoms, quality of sleep, and social media use in young adults during the COVID-19 epidemic]. Neuropsychopharmacologia Hungarica: A Magyar Pszichofarmakologiai Egyesulet Lapja = Official Journal of the Hungarian Association of Psychopharmacology 25(2):70-81.

33. Pellegrino A, Stasi A, Bhatiasevi V (2022) Research trends in social media addiction and problematic social media use: a bibliometric analysis. Front Psychiatry 13:1017506. https://doi.org/10.3389/fpsyt.2022.1017506

34. Popat A, Tarrant C (2023) Exploring adolescents' perspectives on social media and mental health and well-being - a qualitative literature review. Clin Child Psychol Psychiatry 28(1):323-337. https://doi.org/10.1177/13591045221092884

35. Porteret R, Bouchez J, Baylé FJ, Varescon I (2016) L'impulsivité dans le TDAH: Prévalence des troubles du contrôle des impulsions et autres comorbidités, chez 81 adultes présentant un trouble déficit de l'attention/hyperactivité (TDAH). Encephale 42(2):130-137

36. Quinn PO, Madhoo M (2014) A review of attention-deficit/hyperactivity disorder in women and girls: uncovering this hidden diagnosis. Prim Care Companion CNS Disord 16(3). https://doi.org/10.4088/PCC.13r01596

37. Ra CK, Cho J, Stone MD, De La Cerda J, Goldenson NI, Moroney E, Tung I, Lee SS, Leventhal AM (2018) Association of digital media use with subsequent symptoms of attention-deficit/hyperactivity disorder among adolescents. JAMA 320(3):255-263

38. Rahm C (2024) Case Study on ADHD with Supportive Literature. 4(1). https://doi.org/10.56831/PSSRP-04-113

39. Ricci V, De Berardis D, Maina G, Martinotti G (2023) Internet gaming disorders and early onset psychosis in young people: a case study and clinical observations. Int J Environ Res Public Health 20(5):4452. https://doi.org/10.3390/ijerph20053920

40. Romo L, Ladner J, Kotbagi G, Morvan Y, Saleh D, Tavolacci MP, Kern L (2018) Attention-deficit hyperactivity disorder and addictions (substance and behavioral): prevalence and characteristics in a multicenter study in France. J Behav Addict 7(3):743-751. https://doi.org/10.1556/2006.7.2018.58

41. Ryu S, Fan L (2023) The relationship between financial worries and psychological distress among US adults. J Fam Econ Issues 44(1):16-33

42. Sagar S, Kumar N (2021) Usages of social media and symptoms of attention deficit hyperactivity disorder (ADHD): a cross-sectional study. Psychology and Education Journal 58(4):879-887

43. Schou Andreassen C, Pallesen S (2014) Social network site addiction-an overview. Curr Pharm Des 20(25):4053-4061
44. Schreuders E, Braams BR, Blankenstein NE, Peper JS, Güroğlu B, Crone EA (2018) Contributions of reward sensitivity to ventral striatum activity across adolescence and early adulthood. *Child Dev* 89(3):797–810

45. Seo M, Kim JH, David P (2015) Always connected or always distracted? ADHD symptoms and social assurance explain problematic use of mobile phone and multicommunicating. *J Comput-Mediat Commun* 20(6):667–681. https://doi.org/10.1111/jcc4.12140

46. Shen X, Wang C, Chen C, Wang Y, Wang Z, Zheng Y, Liu H (2023) Stress and internet addiction: mediated by anxiety and moderated by self-control. *Psychol Res Behav Manag* 16:1975–1986. https://doi.org/10.2147/PRBM.S411412

47. Shi Y, Hunter Guevara LR, Dykhoff HJ, Sangaralingham LR, Phelan S, Zac-cariello MJ, Warner DO (2021) Racial disparities in diagnosis of attention-deficit/hyperactivity disorder in a US national birth cohort. *JAMA Netw Open* 4(3):e210321. https://doi.org/10.1001/jamanetworkopen.2021.0321

48. Shulman EP, Smith AR, Silva K, Icenogle G, Duell N, Chein J, Steinberg L (2016) The dual systems model: review, reappraisal, and reaffirmation. *Dev Cogn Neurosci* 17:103–117

49. Silverman MH, Jedd K, Luciana M (2015) Neural networks involved in adolescent reward processing: an activation likelihood estimation meta-analysis of functional neuroimaging studies. *Neuroimage* 122:427–439

50. Singh AB, Mishra AK, Vijay M, Karanth V, Mittal K (2023) Prevalence and correlates of social networking addiction and its association with adult ADHD and stress among students of a medical college. *Indian J Community Fam Med*. https://doi.org/10.4103/ijcfm.ijcfm_56_21

51. Starcevic V, Khazaal Y (2017) Relationships between behavioural addictions and psychiatric disorders: What is known and what is yet to be learned? *Front Psychiatry* 8:53

52. Subu MA, Holmes D, Arumugam A, Dias JM, Rahman SA, Waluyo I, Ahmed R, Abraham MS, Arsyad M, Al-N (2022) Traditional, religious, and cultural perspectives on mental illness: a qualitative study on causal beliefs and treatment use. *Int J Qual Stud Health Well-being* 17(1). https://doi.org/10.1080/17482631.2022.2123090

53. Tsilosani A, Chan K, Steffens A, Bolton TB, Kowalczyk WJ (2023) Prob-lematic social media use is associated with depression and similar to behavioral addictions: physiological and behavioral evidence. *Addict Behav* 145:107781. https://doi.org/10.1016/j.addbeh.2023.107781

54. Turel O, Bechara A (2016). Social networking site use while driving: ADHD and the mediating roles of stress, self-esteem and craving. *Front in Psychol* 7(MAR). https://doi.org/10.3389/fpsyg.2016.00455

55. Uzun Ö, Yıldırım V, Uzun E (2016) Habit of using social media and correla-tion of social media addiction, self esteem, perceived social support in adolescent with attention deficit hyperactivity disorder. *Turk J Fam Med Prim Care* 10(Issue 3):142–147

56. Wartberg L, Kriston L, Thomasius R (2020) Internet gaming disorder and problematic social media use in a representative sample of German adolescents: prevalence estimates, comorbid depressive symptoms and related psychosocial aspects. *Comput Human Behav* 103:31–36

57. WHO. (n.d.-a). — Gaming Disorder —.

58. WHO. (n.d.-b). Study on Global AGEing and Adult Health (SAGE).

59. Wright PJ, Raynor PA, Bowers D, Combs EM, Corbett CF, Hardy H, Patel K (2023) Leveraging digital technology for social connectedness among adults with chronic conditions: A systematic review. *Digital Health* 9:20552076231204744. https://doi.org/10.1177/20552076231204746

60. Zheng F, Gao P, He M, Li M, Wang C, Zeng Q, Zhou Z, Yu Z, Zhang L (2014) Association between mobile phone use and inattention in 7102 Chinese adolescents: a population-based cross-sectional study. *BMC Public Health* 14:1–7

61. Zubair U, Khan MK, Albashari M (2023) Link between excessive social media use and psychiatric disorders. *Ann Med Surg* 85(4):875–878. https://doi.org/10.1097/MS9.0000000000000112

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