Table of Contents
Abstract
The Lebanese Social Media Dependency Scale (LSMDS) is a newly developed psychometric instrument designed to evaluate problematic social media habits among young adults in Lebanon. Recognizing that digital behaviors are heavily influenced by cultural and socioeconomic environments, researchers created this tool to address the limitations of existing Western-centric measures. The scale synthesizes elements from prior inventories measuring smartphone addiction, online Fear of Missing Out, and social media disorder into a single, culturally attuned framework.
By capturing the nuances of digital engagement in a society characterized by multilingualism, collectivist values, and recent infrastructural challenges, the LSMDS offers a highly contextualized assessment. It breaks down dependency into three core dimensions: problematic device usage, the psychological drive for online validation, and the distress experienced when disconnected. This makes it an essential resource for public health professionals and psychologists aiming to track and mitigate the adverse impacts of digital overconsumption in the region.
📊 Psychometric Scorecard
Authors
Purpose
The primary objective behind the LSMDS is to provide a culturally valid metric for assessing digital addiction in a non-Western, specifically Lebanese, context. While numerous tools exist to measure internet or social media addiction, they often fail to account for the unique socio-cultural dynamics of the Arab world, and more specifically, Lebanon's distinct trilingual and collectivist environment. Furthermore, Lebanon's recent economic crises have shifted how its population relies on digital communication, making standard international tools potentially less accurate.
This instrument fills a critical methodological gap by offering a tailored assessment for University Students—a demographic highly vulnerable to the academic and psychological detriments of excessive screen time. For clinicians and researchers, having a localized tool ensures that the data collected accurately reflects the population's lived experiences, leading to better-targeted interventions for digital wellbeing and mental health support.
Construct
The psychological construct of Social Media Dependency measured by the LSMDS is conceptualized as a multifaceted Behavioral Addiction. Rather than treating digital dependency as a single monolithic issue, the scale's theoretical framework integrates the physical habit of device usage with the emotional and social drivers of online behavior.
Specifically, the construct is operationalized through three distinct but interrelated dimensions. The first captures the compulsive nature of smartphone use, reflecting the behavioral loop of constant checking. The second dimension taps into the social psychology of the user, focusing on the intense need for peer validation and the fear of social exclusion. Finally, the construct includes a withdrawal component, measuring the psychological distress, anxiety, or irritability that manifests when access to social platforms is restricted.
Validity
To establish the instrument's construct validity, the developers rigorously tested how well the LSMDS aligns with established measures of digital addiction. The scale demonstrated robust convergent validity, showing strong positive correlations with existing tools like the Smartphone Addiction Inventory (r = 0.863) and the Online Fear of Missing Out Inventory (r = 0.888). These high correlation coefficients confirm that the new scale successfully captures the core elements of digital dependency and anxiety about social exclusion.
Additionally, the scale showed a moderate, significant relationship with the Social Media Disorder Scale (r = 0.621). This pattern of correlations is exactly what psychometricians look for: it proves the LSMDS is measuring the intended Behavioral Addiction constructs while still offering a unique, culturally adapted perspective that does not merely duplicate older scales.
Convergent & Discriminant Validation Correlations
| Reference Instrument | Correlation Coefficient (r) |
|---|---|
| Smartphone Addiction Inventory (SPAI) | r=0.863 |
| Online Fear of Missing Out Inventory (ON-FoMO) | r=0.888 |
| Social Media Disorder Scale (SMD) | r=0.621 |
Reliability
The internal consistency of the LSMDS is exceptionally strong, indicating that the items reliably measure the same underlying psychological construct. The overall scale achieved a Cronbach's alpha of 0.931, which is well above the standard 0.80 threshold and is generally considered excellent in psychometric evaluation. This suggests a high degree of cohesion among the 27 items without indicating excessive redundancy.
Furthermore, the individual subscales also demonstrated robust reliability, with alpha values ranging from 0.847 to 0.913. This level of internal consistency ensures that researchers and clinicians can confidently use both the total score and the specific subscale scores to make reliable inferences about a student's level of Social Media Dependency, validation seeking, and withdrawal symptoms.
Factor Analysis
The underlying architecture of the scale was determined through exploratory factor analysis utilizing an oblimin rotation, an appropriate choice given that dimensions of Behavioral Addiction are naturally correlated. By applying multiple extraction criteria—including eigenvalue thresholds, scree plot examination, and parallel analysis—the researchers confidently identified a three-factor structure.
This tri-dimensional model accounts for 52.91% of the total variance in the data. The rigorous item reduction process trimmed the initial 55-item pool down to 27 strongly performing questions. Items that failed to load sufficiently onto a single factor (below 0.40) or that showed conceptual overlap were systematically eliminated, resulting in a clean, interpretable factor structure that maps perfectly onto the theoretical dimensions of problematic use, validation seeking, and withdrawal.
Subscales
| Subscale | Items | Description |
|---|---|---|
| Problematic Smartphone Use | 11 items | Measures the compulsive behavioral habits and excessive time spent on smartphone devices. |
| Social Media Validation Seeking | 8 items | Assesses the psychological need for peer approval, social comparison, and Fear of Missing Out online. |
| Social Media Withdrawal Symptoms | 8 items | Evaluates the negative emotional and psychological reactions experienced when social media access is restricted or unavailable. |
Instrument
| Test Type | Self-report questionnaire |
| Format | 27 items |
| Language | Arabic |
| Population | College students |
| Age Group | 18 and older |
| Administration | Online survey |
| Completion Time | 7-10 minutes |
Lebanese Social Media Dependency Scale Items
Items are currently not available
The individual items of this scale are not publicly available. Researchers interested in using this instrument should contact the original authors directly to request the scale materials.
Sample
The validation sample consisted of 511 University Students recruited across multiple public and private universities in Lebanon. The participants had a mean age of 21.04 years (SD = 3.52), and the majority were female (70.6%), single (97.1%), and unemployed (75.3%).
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References
50 references
- T Aichner (2021). Twenty-five years of social media: a review of social media applications and definitions from 1994 to 2019. Cyberpsychol Behav Soc Netw, 24 (4), 215. 🔗 https://doi.org/10.1089/cyber.2020.0134
- J.D BW. Forbes Advisor [Internet]; 2023 [cited 2025 Jun 20]. Available from: https://www.forbes.com/advisor/business/social-media-statistics/
- Z Jafar (2023). Social media for public health: reaping the benefits, mitigating the harms. Health Promot Perspect, 13 (2), 105. 🔗 https://doi.org/10.34172/hpp.2023.13
- R Jeminiwa (2021). Pharmacy students’ personal and professional use of social media. Curr Pharm Teach Learn, 13 (6), 599. 🔗 https://doi.org/10.1016/j.cptl.2021.01.043
- CS Andreassen (2012). Development of a Facebook addiction scale. Psychol Rep, 110 (2), 501. 🔗 https://doi.org/10.2466/02.09.18.PR0.110.2.501-517
- DJ Kuss (2017). Social networking sites and addiction: ten lessons learned. Int J Environ Res Public Health, 14 (3), 311. 🔗 https://doi.org/10.3390/ijerph14030311
- O Ahmed (2024). Social media use, mental health and sleep: a systematic review with meta-analyses. J Affect Disord, 367 701. 🔗 https://doi.org/10.1016/j.jad.2024.08.193
- LS Lopes (2022). Problematic social media use and its relationship with depression or anxiety: a systematic review. Cyberpsychol Behav Soc Netw, 25 (11), 691. 🔗 https://doi.org/10.1089/cyber.2021.0300
- GK Koh (2024). Social media use and its impact on adults’ mental health and well-being: a scoping review. Worldviews Evid Based Nurs, 21 (4), 345. 🔗 https://doi.org/10.1111/wvn.12727
- A Khan (2023). Excessive smartphone use is associated with depression, anxiety, stress, and sleep quality of Australian adults. J Med Syst, 47 (1), 109. 🔗 https://doi.org/10.1007/s10916-023-02005-3
- P-C Huang (2024). Association between problematic social media use and physical activity: the mediating roles of nomophobia and the tendency to avoid physical activity. J Soc Media Res, 1 (1), 14. 🔗 https://doi.org/10.29329/jsomer.4
- H Shannon (2022). Problematic social media use in adolescents and young adults: systematic review and meta-analysis. JMIR Ment Health, 9 (4), 🔗 https://doi.org/10.2196/33450
- Y Zheng (2020). Upward social comparison and state anxiety as mediators between passive social network site usage and online compulsive buying among women. Addict Behav, 111 106569. 🔗 https://doi.org/10.1016/j.addbeh.2020.106569
- W Wu (2024). Social anxiety and problematic social media use: a systematic review and meta-analysis. Addict Behav, 153 107995. 🔗 https://doi.org/10.1016/j.addbeh.2024.107995
- H Shannon (2024). Longitudinal problematic social media use in students and its association with negative mental health outcomes. Psychol Res Behav Manag, 17 1551. 🔗 https://doi.org/10.2147/PRBM.S450217
- R Shiraly (2024). Psychological distress, social media use, and academic performance of medical students: the mediating role of coping style. BMC Med Educ, 24 (1), 999. 🔗 https://doi.org/10.1186/s12909-024-05988-w
- AM Bhandarkar (2021). Impact of social media on the academic performance of undergraduate medical students. Med J Armed Forces India, 77 🔗 https://doi.org/10.1016/j.mjafi.2020.10.021
- N Salari (2025). The impact of social networking addiction on the academic achievement of University Students globally: a meta-analysis. Public Health Pract (Oxf), 9 100584. 🔗 https://doi.org/10.1016/j.puhip.2025.100584
- CE Davis (2024). Social media use and psychological distress among undergraduate nursing students: a review. J Nurs Educ, 63 (8), 540. 🔗 https://doi.org/10.3928/01484834-20240502-03
- D Jabbour (2023). Social media medical misinformation: impact on mental health and vaccination decision among University Students. Ir J Med Sci, 192 (1), 291. 🔗 https://doi.org/10.1007/s11845-022-02936-9
- X Sun (2023). Social media use for coping with stress and psychological adjustment: a transactional model of stress and coping perspective. Front Psychol, 14 1140312. 🔗 https://doi.org/10.3389/fpsyg.2023.1140312
- Y-H Lin (2014). Development and validation of the Smartphone Addiction Inventory (SPAI). PLoS One, 9 (6),
- CP Sette (2019). The online Fear of Missing Out inventory (ON-FoMO): development and validation of a new tool. J Technol Behav Sci, 5 (1), 20. 🔗 https://doi.org/10.1007/s41347-019-00110-0
- M Boer (2022). Validation of the social media disorder scale in adolescents: findings from a large-scale nationally representative sample. Assessment, 29 (8), 1658. 🔗 https://doi.org/10.1177/10731911211027232
- JP Stein (2024). Attitudes towards AI: measurement and associations with personality. Sci Rep, 14 (1), 2909. 🔗 https://doi.org/10.1038/s41598-024-53335-2
- J Al-Menayes (2015). Psychometric properties and validation of the Arabic social media addiction scale. J Addict, 2015 291743. 🔗 https://doi.org/10.1155/2015/291743
- FZE Abiddine (2024). The psychometric properties of the Arabic Bergen social media addiction scale. Int J Ment Health and Addiction,
- B Alwuqaysi (2024). Cross-cultural study on social media usage and its correlation with mental health and family functioning. Comput Hum Behav Rep, 16 100513. 🔗 https://doi.org/10.1016/j.chbr.2024.100513
- DataReportal – Global Digital Insights [Internet]; 2025 [cited 2025 Oct 1]. Digital 2025: Lebanon. Available from: https://datareportal.com/reports/digital-2025-Lebanon 🔗 https://doi.org/10.5089/9798229034104.029
- NN Bacha (2011). Foreign language education in Lebanon: a context of cultural and curricular complexities. JLTR, 2 (6), 🔗 https://doi.org/10.4304/jltr.2.6.1320-1328
- Hijazi M, Saad M, Sidani S. Financial inclusion in Lebanon after the economic crisis. Cogent Bus Manag [Internet]. 2025 [cited 2025 Oct 1]. Located at: world. Available from: https://www.tandfonline.com/doi/abs/10.1080/23311975.2025.2483966 🔗 https://doi.org/10.1080/23311975.2025.2483966
- AL Comrey (2013). A first course in factor analysis. 442. 🔗 https://doi.org/10.4324/9781315827506
- C Simó-Sanz (2018). Smartphone Addiction Inventory (SPAI): translation, adaptation and validation of the tool in Spanish adult population. PLoS One, 13 (10), 🔗 https://doi.org/10.1371/journal.pone.0205389
- F Bakioğlu (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 Psychol, 10 (1), 154. 🔗 https://doi.org/10.1186/s40359-022-00856-y
- B Hamam (2024). Social media addiction in University Students in Lebanon and its effect on student performance. J Am Coll Health, 72 (8), 3042. 🔗 https://doi.org/10.1080/07448481.2022.2152690
- S Barbar (2021). Factors associated with problematic social media use among a sample of Lebanese adults: the mediating role of emotional intelligence. Perspect Psychiatr Care, 57 (3), 1313. 🔗 https://doi.org/10.1111/ppc.12692
- J Stirnberg (2024). Problematic smartphone use, depression symptoms, and Fear of Missing Out: Can reasons for smartphone use mediate the relationship? A longitudinal approach. J Soc Media Res, 1 (1), 3. 🔗 https://doi.org/10.29329/jsomer.3
- E Mitropoulou (2024). Exploration of the association between social media addiction, self-esteem, self-compassion and loneliness. J Soc Media Res, 1 (1), 25. 🔗 https://doi.org/10.29329/jsomer.2
- J Amirthalingam (2024). Understanding social media addiction: a deep dive. Cureus, 16 (10),
- E Stănculescu (2022). The Bergen social media addiction scale validity in a Romanian sample using item response theory and network analysis. Int J Ment Health Addict, 21 (4), 2475. 🔗 https://doi.org/10.1007/s11469-021-00732-7
- R Mojtabai (2024). Problematic social media use and psychological symptoms in adolescents. Soc Psychiatry Psychiatr Epidemiol, 59 (12), 2271. 🔗 https://doi.org/10.1007/s00127-024-02657-7
- DK Ahorsu (2024). Pathways to social media addiction: examining its prevalence, and predictive factors among Ghanaian youths. J Soc Media Res, 1 (1), 47. 🔗 https://doi.org/10.29329/jsomer.9
- S Obeid (2023). Psychometric properties of the Problematic Use of Social Networks (PUS) scale in Arabic among adolescents. PLoS One, 18 (9), 🔗 https://doi.org/10.1371/journal.pone.0291616
- A Almutarie (2024). Reliability and validity study of the social media addiction scale. مجلة إتحاد الجامعات العربية لبحوث الإعلام و تکنولوجيا الإتصال, 🔗 https://doi.org/10.21608/jcts.2024.345008
- M Wolgast (2025). Motives for social media use in adults: associations with platform-specific use, psychological distress, and problematic engagement. J Soc Media Res, 2 (3), 179. 🔗 https://doi.org/10.29329/jsomer.45
- E Awad (2022). Association between desire thinking and problematic social media use among a sample of Lebanese adults: the indirect effect of suppression and impulsivity. PLoS One, 17 (11), 🔗 https://doi.org/10.1371/journal.pone.0277884
- M Nahas (2018). Problematic smartphone use among Lebanese adults aged 18–65 years using MPPUS-10. Comput Hum Behav, 87 348. 🔗 https://doi.org/10.1016/j.chb.2018.06.009
- C Montag (2025). The darker side of positive AI attitudes: investigating associations with (problematic) social media use. Addict Behav Rep, 22 100613.
- W Li (2024). Social media use and attitudes toward AI: the mediating roles of perceived AI fairness and threat. Hum Behav Emerg Technol,
- AB Haque (2024). To explain or not to explain: an empirical investigation of ai-based recommendations on social media platforms. Electron Markets, 35 (1), 🔗 https://doi.org/10.1007/s12525-024-00741-z
Cite this article
Mohammed looti (2026). Lebanese Social Media Dependency Scale. PSYCHOLOGICAL SCALES. Retrieved from https://scales.arabpsychology.com/s/lebanese-social-media-dependency-scale/
Mohammed looti. "Lebanese Social Media Dependency Scale." PSYCHOLOGICAL SCALES, 14 Aug. 2026, https://scales.arabpsychology.com/s/lebanese-social-media-dependency-scale/.
Mohammed looti. "Lebanese Social Media Dependency Scale." PSYCHOLOGICAL SCALES, 2026. https://scales.arabpsychology.com/s/lebanese-social-media-dependency-scale/.
Mohammed looti (2026) 'Lebanese Social Media Dependency Scale', PSYCHOLOGICAL SCALES. Available at: https://scales.arabpsychology.com/s/lebanese-social-media-dependency-scale/.
[1] Mohammed looti, "Lebanese Social Media Dependency Scale," PSYCHOLOGICAL SCALES, vol. X, no. Y, ص Z-Z, August, 2026.
Mohammed looti. Lebanese Social Media Dependency Scale. PSYCHOLOGICAL SCALES. 2026;vol(issue):pages.