Lebanese Social Media Dependency Scale

1. Abstract

The Lebanese Social Media Dependency Scale (LSMDS) is an empirically rigorous, culturally contextualized psychometric instrument developed to assess problematic social media engagement and behavioral dependency among young adults and university students in Lebanon. Conventional instruments evaluating digital and internet-use disorders have largely originated within Western industrialized nations, frequently failing to encapsulate the distinct intersection of sociopolitical volatility, multi-layered economic crises, trilingual communicative norms, and collectivist kinship networks characteristic of the contemporary Lebanese landscape. Developed by Samar Younes, Pascale Salameh, and colleagues, the LSMDS synthesizes theoretical paradigms from behavioral addiction models, the fear of missing out (FoMO) literature, and compensatory internet use theory into a unified tri-dimensional assessment framework.

Comprising 27 self-report items derived through systematic item reduction from an initial 55-item pool, the scale captures three correlated latent dimensions: Problematic Smartphone Use (11 items), Social Media Validation Seeking (8 items), and Social Media Withdrawal Symptoms (8 items). Psychometric evaluation within a normative validation cohort of 511 Lebanese university undergraduates demonstrated exceptional internal consistency, yielding an overall Cronbach's alpha of α = 0.931, with subscale reliabilities ranging from α = 0.847 to α = 0.913. Exploratory factor analysis employing oblique rotation verified a robust tri-factor architecture accounting for 52.91% of the total cumulative variance. The scale exhibited substantial convergent validity against legacy measurement tools, correlating strongly with the Smartphone Addiction Inventory (SPAI; r = 0.863), the Online Fear of Missing Out Inventory (ON-FoMO; r = 0.888), and moderately with the Social Media Disorder Scale (SMD; r = 0.621). The LSMDS serves as an essential diagnostic and epidemiological screening instrument for clinical psychologists, educational counselors, and public health researchers seeking to identify digital dependency patterns and implement targeted digital wellbeing interventions across Middle Eastern populations.

2. Keywords

Lebanese Social Media Dependency Scale, behavioral addiction, problematic social media use, psychometrics, scale validation, university students, fear of missing out, smartphone addiction, digital wellbeing, cross-cultural psychology, Lebanon

3. Authors

The Lebanese Social Media Dependency Scale was conceptualized, operationalized, and psychometrically validated by a collaborative consortium of researchers affiliated with pharmacy faculties and public health epidemiology institutes in Lebanon:

• Samar Younes, PharmD, PhD (Corresponding Author) — School of Pharmacy, Lebanese International University, Bekaa, Lebanon. Email: [email protected]
• Zeinab Abbas, MSc — INSPECT-LB (Institut National de Santé Publique, d'Épidémiologie Clinique et de Toxicologie-Liban), Beirut, Lebanon.
• Chadia Haddad, PhD — INSPECT-LB (Institut National de Santé Publique, d'Épidémiologie Clinique et de Toxicologie-Liban), Beirut, Lebanon.
• Daniele Saade, MPH — INSPECT-LB (Institut National de Santé Publique, d'Épidémiologie Clinique et de Toxicologie-Liban), Beirut, Lebanon.
• Nisreen Mourad, PhD — School of Pharmacy, Lebanese International University, Bekaa, Lebanon.
• Hala Sacre, PharmD — INSPECT-LB (Institut National de Santé Publique, d'Épidémiologie Clinique et de Toxicologie-Liban), Beirut, Lebanon.
• Amal Al-Hajje, PhD — INSPECT-LB (Institut National de Santé Publique, d'Épidémiologie Clinique et de Toxicologie-Liban), Beirut, Lebanon.
• Pascale Salameh, PharmD, PhD, HDR — INSPECT-LB (Institut National de Santé Publique, d'Épidémiologie Clinique et de Toxicologie-Liban), Beirut, Lebanon.

4. Purpose

The primary psychometric purpose of the Lebanese Social Media Dependency Scale (LSMDS) is to provide an ecologically valid, culturally calibrated assessment tool designed to quantify the severity of social media dependency among Lebanese university students and young adults. Over the past two decades, academic inquiry into problematic smartphone use and behavioral addiction has burgeoned; however, the overwhelming majority of diagnostic screeners (e.g., the Bergen Social Media Addiction Scale or the Internet Addiction Test) were established and standardized within North American, East Asian, or Western European contexts. When imported into the Arab world through crude direct translation, these instruments frequently exhibit substantial construct drift, failing to capture how culture-specific communicative practices modify the manifestation of technological dependency.

In Lebanon, digital devices are not merely instruments of leisure or productivity; they serve as critical survival lifelines amidst profound structural destabilization. The compounded effects of severe national economic collapse, hyperinflation, electricity and fuel shortages, sociopolitical gridlock, and the aftermath of the 2020 Beirut port explosion have dramatically transformed how young citizens utilize communication networks. University students, who operate under elevated levels of academic distress and bleak future employment prospects, turn to platforms such as Instagram, TikTok, WhatsApp, and X (formerly Twitter) as primary coping mechanisms for stress regulation, social cohesion, alternative monetization, and real-time crisis navigation. Furthermore, the Lebanese societal milieu is characterized by a trilingual communication habitus (fluidly interweaving Arabic, French, and English) and pronounced collectivist values that place heavy premiums on social surveillance, community cohesion, and outward presentation of personal status.

Existing international tools often categorize heavy daily screen time as inherently pathological, overlooking that constant connectivity in modern Lebanon can represent an adaptive mechanism for obtaining public safety updates or conducting transnational banking and freelancing. Conversely, international instruments often under-sample the cultural nuances of online interpersonal validation, social comparison within dense communal networks, and the intense psychological distress generated by sudden disconnection in an unstable environment. The LSMDS fulfills a critical public health objective by untangling non-pathological, context-driven connectivity from genuine compulsive, maladaptive dependency. It equips university mental health centers, epidemiological monitoring agencies, and psychotherapists with an empirically validated instrument capable of identifying at-risk youth, facilitating targeted clinical interventions, and providing empirical baselines for nationwide youth digital wellbeing campaigns.

5. Psychological Construct

The LSMDS conceptualizes social media dependency not as a superficial habits-based deficit, but as a complex, multifaceted behavioral addiction governed by compulsive behavioral repetition, sociocognitive vulnerability, and neuroaffective dysregulation. The construct does not treat social media dependency as a monolithic entity; rather, it operationalizes dependency through three distinct yet hierarchically integrated dimensions identified via exploratory factor modeling:

Problematic Smartphone Use (11 Items)

This dimension operationalizes the behavioral, motoric, and functional impairments associated with unrestrained, compulsive device engagement. It assesses the user's progressive loss of behavioral control over screen time, automatic checking habits, and the intrusion of technological usage into vital functional domains such as academic lectures, study routines, interpersonal physical interactions, and vehicular navigation. Within this subscale, items capture behavioral salience (where device interaction dominates thought processes and daily routines) and conflict (where excessive usage induces interpersonal friction with family members, peers, and professors, or degrades academic performance). For example, this subscale identifies the compulsive habit of continuously unlocking the device without deliberate communicative intent, sacrificing critical sleep hygiene to scroll algorithmic feeds late into the night, and struggling unsuccessfully to moderate screen duration despite conscious attempts at self-regulation.

Social Media Validation Seeking (8 Items)

Grounding itself in social cognitive theory and the psychopathology of interpersonal comparison, this subscale measures the psychological reliance on digital platforms for self-worth regulation, social status affirmation, and fear-based peer surveillance. In collectivist and highly status-conscious cultures, the algorithmic reinforcement mechanics of social media — such as likes, positive commentary, story views, and follower increments — function as potent social commodities. This dimension evaluates the extent to which an individual's self-esteem is contingent upon peer feedback, the compulsive need to curate an idealized digital identity, and the distressing cognitive state of fear of missing out (FoMO). Users scoring high on this dimension experience pervasive apprehension that their peers are participating in rewarding offline experiences or online discussions from which they are excluded, driving relentless upward social comparison, envy, and an insatiable appetite for algorithmic social proof.

Social Media Withdrawal Symptoms (8 Items)

This subscale captures the negative affective and psychological sequelae experienced when an individual is involuntarily separated from their digital networks or when network infrastructure collapses. Rather than assessing purely physiological withdrawal as observed in substance-use disorders, this dimension assesses the intense emotional dysregulation, autonomic restlessness, generalized anxiety, and irritable agitation that occur during periods of forced offline disconnection. In Lebanon, where prolonged blackouts, telecommunication network outages, and financial battery exhaustion frequently terminate network access abruptly, withdrawal manifests distinctly. High-scoring individuals report profound subjective distress, feelings of severe disorientation, panicky dread regarding what events might be unfolding in their absence, and an overwhelming, intrusive craving to re-establish connectivity that impairs their ability to concentrate on real-world demands.

6. Theoretical Framework

The theoretical architecture of the Lebanese Social Media Dependency Scale is informed by a multi-theoretical convergence of contemporary behavioral addiction models, cognitive motivational theories, and communication science frameworks.

The Interaction of Person-Affect-Cognition-Execution (I-PACE) Model

Centrally, the LSMDS is grounded in the I-PACE model developed by Matthias Brand and colleagues. The I-PACE paradigm posits that specific internet-use disorders do not develop in a psychological vacuum; rather, they evolve through dynamic, cyclical interactions between predisposing personal characteristics (e.g., personality traits, biological predispositions, psychopathological symptoms), affective and cognitive mediators, and executive functions. In the context of the LSMDS, predisposing sociodemographic stress and emotional distress trigger cognitive biases (such as the belief that online validation stabilizes self-worth) and affective tension (such as social anxiety and FoMO). When an individual engages with social media algorithms, temporary emotional relief and dopamine-mediated reinforcement occur, progressively weakening inhibitory executive control. Over time, what began as goal-directed coping transforms into habitual, compulsive behavioral execution (reflected in the Problematic Smartphone Use subscale) and profound emotional dysregulation upon platform deprivation (reflected in the Withdrawal Symptoms subscale).

Griffiths' Components Model of Addiction

The operational definitions underpinning the LSMDS align with Mark Griffiths' widely accepted six-component framework for behavioral addictions: salience, mood modification, tolerance, withdrawal symptoms, conflict, and relapse. The 27 items of the LSMDS systematically integrate these clinical hallmarks. Salience and conflict are clearly encapsulated within the behavioral disruptions of problematic smartphone usage, mood modification and emotional coping are embedded within validation-seeking behaviors, while psychological tolerance and withdrawal are explicitly quantified when individuals must increase their platform immersion to feel satisfied or suffer emotional collapse when network connectivity is severed.

Compensatory Internet Use Theory (CIUT) and Uses and Gratifications Theory (UGT)

Complementing clinical addiction frameworks, the LSMDS incorporates Compensatory Internet Use Theory (Kardefelt-Winther) and Uses and Gratifications Theory (Blumler and Katz). CIUT posits that individuals experiencing offline psychological distress, socioeconomic helplessness, or psychosocial deprivation actively employ digital technologies to alleviate negative feelings or fulfill unmet psychological needs. In the Lebanese context, where real-world sociopolitical and economic avenues for youth self-actualization have been constrained, social media acts as a compensatory arena. Concurrently, UGT explains that users deliberately select platforms to satisfy socio-affective integrative needs — specifically peer recognition, information monitoring, and identity formation — directly underpinning the latent mechanisms of the Social Media Validation Seeking dimension.

7. Validity

The construct, convergent, and discriminant validity of the Lebanese Social Media Dependency Scale were established through thorough empirical testing across a multi-center sample of 511 Lebanese university undergraduates. Psychometricians utilize cross-instrument correlation matrices to ensure that a novel instrument aligns with established gold standards while retaining unique explanatory variance.

Convergent Validity

To evaluate convergent validity, the developers tested bivariate Pearson correlations between the total LSMDS score and three internationally validated measurement tools evaluating technological overuse, social media distress, and digital anxiety:

• Smartphone Addiction Inventory (SPAI): The LSMDS exhibited a robust, statistically significant positive correlation with the SPAI (r = 0.863, p < 0.001). This large coefficient confirms that the behavioral components of device over-attachment, physical interference, and loss of self-control measured by the LSMDS correspond directly with established models of problematic mobile hardware dependency.
• Online Fear of Missing Out Inventory (ON-FoMO): A very strong positive correlation was observed between the LSMDS and the ON-FoMO inventory (r = 0.888, p < 0.001). This empirical finding validates the central conceptualization of the LSMDS: that compulsive social media checking behavior in young adults is fundamentally propelled by sociocognitive anxieties surrounding peer exclusion, relational tracking, and online status monitoring.
• Social Media Disorder Scale (SMD): The LSMDS demonstrated a moderate-to-strong, statistically significant correlation with the clinical DSM-5-adapted SMD scale (r = 0.621, p < 0.001). This moderate magnitude is methodologically advantageous; it confirms that while the LSMDS shares core diagnostic features with Western-derived formal disorder scales, it also captures distinct cultural, social-compensatory, and behavioral variance that older instruments systematically omit.

Discriminant and Content Validity

Content validity was verified prior to factor analysis by a multidisciplinary expert committee comprising clinical psychologists, psychiatric epidemiologists, and university health professionals who reviewed the initial 55 items for cultural clarity, semantic equivalence, and clinical relevance. Translation and cultural adaptation followed rigorous forward- and back-translation protocols between English and formal Arabic, ensuring semantic and conceptual equivalence. The systematic reduction of items during exploratory modeling eliminated cross-loading and theoretically ambiguous questions, yielding high discriminant validity across the three extracted subscales, as evidenced by clean factor separation and low inter-factor cross-loadings (< 0.40).

8. Reliability

The reliability of the Lebanese Social Media Dependency Scale was examined using rigorous classical test theory metrics, focusing on internal consistency reliability across the composite scale and each isolated latent subscale.

Internal Consistency Metrics

For the overall 27-item LSMDS, the composite internal consistency reached an exceptional level, yielding a Cronbach's alpha of α = 0.931. In psychometric testing, a Cronbach's alpha exceeding 0.90 reflects outstanding item cohesion and minimal measurement error, indicating that the 27 items operate synergistically to quantify the overarching latent construct of social media dependency without exhibiting high item-content redundancy.

Subscale Reliability Estimates

All three subscales exhibited robust reliability metrics, confirming that researchers and clinicians can reliably calculate and interpret both composite scores and isolated dimension sub-scores:

• Problematic Smartphone Use (11 items): Cronbach's α = 0.913, demonstrating excellent homogeneity in capturing compulsive device handling, automatic checking, and behavioral interference.
• Social Media Validation Seeking (8 items): Cronbach's α = 0.884, indicating strong reliability for assessing peer approval dependency and fear of missing out.
• Social Media Withdrawal Symptoms (8 items): Cronbach's α = 0.847, demonstrating solid internal consistency for measuring negative affective states and cognitive distress during disconnection.

All item-total correlation coefficients exceeded 0.50, and deletion of any single item did not result in an increase in the composite or subscale alpha values, verifying that each of the retained 27 items contributes meaningfully to the scale's measurement precision.

9. Factor Analysis

The latent structural architecture of the LSMDS was established through a structured exploratory factor analysis (EFA) conducted on the normative sample of 511 university students.

Extraction and Rotation Procedures

Prior to factor extraction, the adequacy of the data matrix for factorization was verified using the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and Bartlett's test of sphericity. The KMO index yielded an exceptional value (> 0.90), and Bartlett's test reached strong statistical significance (p < 0.001), indicating adequate correlation structures among the variables. Because psychological constructs within the domain of behavioral addiction are theoretically interrelated rather than orthogonal, the researchers employed an oblimin (oblique) rotation, allowing latent dimensions to correlate naturally.

Dimensionality and Variance Explained

The determination of factor retention was guided by multiple converging psychometric criteria: Kaiser-Guttman eigenvalue thresholds (eigenvalues > 1.0), visual inspection of Cattell's scree plot inflection points, and Horn's parallel analysis. These criteria consistently converged on a clear three-factor model. Together, the three extracted factors explained 52.91% of the total cumulative variance across the dataset, representing an optimal balance between parsimony and explanatory power for behavioral health inventories.

Item Reduction Process

The initial instrument pool comprised 55 prospective items developed to capture the full breadth of digital dependency. A rigorous item-reduction protocol was systematically implemented:

• Items with factor pattern loadings lower than 0.40 on their primary target factor were eliminated.
• Items demonstrating substantial cross-loadings (loading ≥ 0.30 on two or more factors with a differential < 0.15) were removed due to lack of specificity.
• Items exhibiting high semantic redundancy or poor corrected item-total correlations were eliminated.

This pruning eliminated 28 underperforming or conceptually ambiguous items, producing the final 27-item instrument. The resulting factor pattern matrix revealed high, unambiguous primary loadings ranging from 0.48 to 0.86 across all three components:

• Factor 1: Problematic Smartphone Use: 11 items capturing compulsive physical checking, prolonged unmonitored use, and life interference.
• Factor 2: Social Media Validation Seeking: 8 items mapping onto peer comparison, digital social approval, and FoMO.
• Factor 3: Social Media Withdrawal Symptoms: 8 items evaluating disconnection-induced irritability, nervousness, and cognitive preoccupation.

10. Instrument / Measurement Tool

The Lebanese Social Media Dependency Scale is formatted as a standardized, brief self-report psychometric questionnaire designed for rapid administration across research and educational clinical settings.

• Instrument Name: Lebanese Social Media Dependency Scale (LSMDS)
• Test Type: Standardized self-report psychometric inventory / behavioral rating scale
• Target Population: University undergraduates, college students, and emerging adults (ages 18 and older)
• Primary Application: Screening for problematic digital platform use, assessing social media dependency, empirical behavioral health research, and student mental health counseling triage
• Total Item Count: 27 items
• Dimensional Subscales:
  • Problematic Smartphone Use (11 items)
  • Social Media Validation Seeking (8 items)
  • Social Media Withdrawal Symptoms (8 items)
• Response Format: Continuous rating scale across 27 operationalized inventory items, evaluating frequency and subjective intensity of behaviors and emotional experiences
• Language: Arabic (original validated target version; developed using systematic forward- and back-translation methodology alongside English psychometric frameworks)
• Administration Modality: Self-administered online digital survey or traditional supervised paper-and-pencil questionnaire
• Estimated Completion Time: Approximately 7 to 10 minutes
• Scoring Protocol: Dimensional subscale scores are computed by summing the numerical weights of items loading on each specific factor; a global Social Media Dependency Composite Score is derived by summing all 27 items. Higher scores reflect greater behavioral dependency, more pronounced validation anxiety, and more severe withdrawal distress.

11. Permissions & Fee and Test Year

The Lebanese Social Media Dependency Scale was formally validated and published in 2026 under the open-access terms of the peer-reviewed medical and scientific journal PLOS ONE (Public Library of Science). While the methodological research article detailing its psychometric properties is distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), the complete itemized questionnaire bank is controlled by the primary instrument development team at the Lebanese International University and INSPECT-LB.

Researchers, academic faculty, and non-commercial clinicians may utilize the scale free of financial charge for scholarly and clinical screening purposes. However, formal permission and access to the complete 27-item Arabic testing schedule must be obtained directly from the corresponding developer:

Samar Younes, PharmD, PhD
School of Pharmacy, Lebanese International University, Bekaa, Lebanon
Contact: [email protected]

Commercial exploitation, digital commercial application embedding, or paid testing dissemination requires explicit written licensing agreements from the copyright holders.

12. References

Below is the formal reference list detailing foundational literature, comparative validation inventories, and the primary validation study of the Lebanese Social Media Dependency Scale formatted in strict American Psychological Association (APA 7th edition) style:

• Aichner, T., Grünfelder, M., Maurer, O., & Jegeni, O. (2021). Twenty-five years of social media: A review of social media applications and definitions from 1994 to 2019. Cyberpsychology, Behavior, and Social Networking, 24(4), 215–222. https://doi.org/10.1089/cyber.2020.0134
• Andreassen, C. S., Torsheim, T., Brunborg, G. S., & Pallesen, S. (2012). Development of a Facebook addiction scale. Psychological Reports, 110(2), 501–517. https://doi.org/10.2466/02.09.18.PR0.110.2.501-517
• Bakioğlu, F., & Çapan, B. E. (2022). Adaptation and validation of the Online-Fear of Missing Out Inventory into Turkish and the association with social media addiction, smartphone addiction, and life satisfaction. BMC Psychology, 10(1), Article 154. https://doi.org/10.1186/s40359-022-00856-y
• Barbar, S., Haddad, C., Sacre, H., Obeid, S., & Salameh, P. (2021). Factors associated with problematic social media use among a sample of Lebanese adults: The mediating role of emotional intelligence. Perspectives in Psychiatric Care, 57(3), 1313–1322. https://doi.org/10.1111/ppc.12692
• Boer, M., Stevens, G. W. J. M., Finkenauer, C., de Looze, M. E., & van den Eijnden, R. J. J. M. (2022). Validation of the Social Media Disorder Scale in adolescents: Findings from a large-scale nationally representative sample. Assessment, 29(8), 1658–1674. https://doi.org/10.1177/10731911211027232
• Brand, M., Wegmann, E., Stark, R., Müller, A., Wölfling, K., Robbins, T. W., & Potenza, M. N. (2019). The Interaction of Person-Affect-Cognition-Execution (I-PACE) model for addictive behaviors: An update. Neuroscience & Biobehavioral Reviews, 104, 252–269. https://doi.org/10.1016/j.neubiorev.2019.06.032
• Griffiths, M. D. (2005). A ‘components’ model of addiction within a biopsychosocial framework. Journal of Substance Use, 10(4), 191–197. https://doi.org/10.1080/14659890500114359
• Hamam, B., Sacre, H., Hallit, S., & Salameh, P. (2024). Social media addiction in university students in Lebanon and its effect on student performance. Journal of American College Health, 72(8), 3042–3051. https://doi.org/10.1080/07448481.2022.2152690
• Kardefelt-Winther, D. (2014). A conceptual and methodological critique of internet addiction research: Towards a model of compensatory internet use. Computers in Human Behavior, 31, 351–354. https://doi.org/10.1016/j.chb.2013.10.059
• Kuss, D. J., & Griffiths, M. D. (2017). Social networking sites and addiction: Ten lessons learned. International Journal of Environmental Research and Public Health, 14(3), Article 311. https://doi.org/10.3390/ijerph14030311
• Lin, Y.-H., Chang, L.-R., Lee, Y.-H., Tseng, H.-W., Kuo, T. B. J., & Chen, S.-H. (2014). Development and validation of the Smartphone Addiction Inventory (SPAI). PLOS ONE, 9(6), Article e98312. https://doi.org/10.1371/journal.pone.0098312
• Sette, C. P., Cassotti, M., Lucidi, F., & Presaghi, F. (2020). The Online Fear of Missing Out Inventory (ON-FoMO): Development and validation of a new tool. Journal of Technology in Behavioral Science, 5(1), 20–33. https://doi.org/10.1007/s41347-019-00110-0
• Younes, S., Abbas, Z., Haddad, C., Saade, D., Mourad, N., Sacre, H., Al-Hajje, A., & Salameh, P. (2026). Lebanese Social Media Dependency Scale. PLOS ONE, Article e0344535. https://doi.org/10.1371/journal.pone.0344535

13. Items of the Scale