Bergen Social Media Addiction Scale (BSMAS)

1. Abstract

The Bergen Social Media Addiction Scale (BSMAS) is a brief, theoretically anchored psychometric instrument engineered to evaluate excessive, compulsive, and problematic engagement with social networking applications. Adapted by Mark D. Griffiths, Cecilie Schou Andreassen, and Ståle Pallesen from the earlier Bergen Facebook Addiction Scale (BFAS), the instrument operationalizes problematic digital platform engagement through the lens of Griffiths' (2005) universally recognized Components Model of Addiction. The scale comprises six self-report items, with each individual item explicitly representing one of six core addiction criteria: salience, tolerance, mood modification, relapse, withdrawal, and conflict. Respondents indicate the frequency with which they have experienced each symptom over the preceding 12 months using a standardized five-point Likert scale ranging from 1 (Very rarely) to 5 (Very often).

Extensive cross-cultural validations across adolescent, collegiate, and adult cohorts consistently confirm a unidimensional factor structure characterized by robust psychometric properties. The instrument typically exhibits high internal consistency (Cronbach's alpha and McDonald's omega values routinely ranging from .82 to .90), solid test-retest reliability, and strong construct, convergent, and criterion-related validity. Total composite scores range between 6 and 30, with an empirically established clinical cut-off score of 19 points often applied to identify individuals at elevated risk for problematic or pathological social media use. Because of its brevity, conceptual clarity, and rigorous empirical grounding, the BSMAS has become an international gold standard in epidemiological monitoring, psychiatric screening, and contemporary behavioral addiction research.

2. Keywords

Bergen Social Media Addiction Scale, BSMAS, behavioral addiction, social networking sites, Griffiths components model, salience, tolerance, withdrawal symptoms, psychometrics, digital wellbeing

3. Authors

The Bergen Social Media Addiction Scale was developed through a longstanding academic collaboration between clinical psychologists and behavioral addiction specialists at the University of Bergen and Nottingham Trent University:

• Cecilie Schou Andreassen, Ph.D.: Professor of Clinical Psychology, Department of Clinical Psychology, University of Bergen, Bergen, Norway. Dr. Andreassen has led landmark international investigations into non-substance addictions, including workaholism, shopping addiction, and compulsive technology consumption.
• Ståle Pallesen, Ph.D.: Professor of Psychology, Department of Psychosocial Science, University of Bergen, Bergen, Norway. Dr. Pallesen specializes in behavioral medicine, sleep medicine, psychometrics, and quantitative research methodologies.
• Mark D. Griffiths, Ph.D.: Distinguished Professor of Behavioural Addiction and Director of the International Gaming Research Unit, Psychology Department, Nottingham Trent University, Nottingham, United Kingdom. Dr. Griffiths is an internationally recognized authority on technological addictions, responsible for establishing the core components model underlying the instrument.

4. Purpose

The Bergen Social Media Addiction Scale was established to provide an efficient, robust, and theoretically consistent assessment of problematic, compulsive use of social media platforms (e.g., Instagram, TikTok, Facebook, X/Twitter, Snapchat). As interpersonal communication, social validation, and digital entertainment increasingly shifted from single desktop-bound platforms to multi-channel mobile ecosystems, researchers recognized the critical necessity of transitioning beyond platform-specific tools (such as the Bergen Facebook Addiction Scale) toward an umbrella instrument capable of capturing addictive behaviors across all contemporary social networking sites (SNS).

The primary purpose of the BSMAS is twofold:

1. Epidemiological and Empirical Research: The scale enables behavioral scientists, sociologists, and public health researchers to measure the prevalence, severity, and correlates of problematic social media use across large population cohorts. By standardizing the construct around explicit addiction components, the instrument allows direct comparisons across cross-national studies examining antecedents such as fear of missing out (FoMO), low self-esteem, narcissism, neuroticism, and negative psychological outcomes including major depressive episodes, sleep impairment, and social anxiety.
2. Clinical Screening and Triage: Although social media addiction is not formally recognized as an independent psychiatric disorder within the Diagnostic and Statistical Manual of Mental Disorders (DSM-5-TR) or the International Classification of Diseases (ICD-11), clinicians routinely encounter patients exhibiting severe behavioral dysregulation, loss of control, and functional decline stemming from uncontrollable online habits. The BSMAS operates as an evidence-based clinical screening instrument, furnishing therapists with a rapid, objective metric to gauge whether an individual's usage patterns meet threshold criteria for behavioral addiction.

Unlike general social media engagement inventories that confound high involvement or heavy recreational use with pathology, the BSMAS explicitly measures cognitive, emotional, and behavioral disruption. It separates the sheer volume of time spent online from compulsive engagement, focusing instead on functional impairment, distress, interpersonal friction, and psychological distress.

5. Psychological Construct

The Bergen Social Media Addiction Scale operationalizes social media addiction as a distinct behavioral addiction characterized by six core dimensions, adapted directly from Griffiths' theoretical taxonomy. Each dimension represents an essential facet of the underlying latent construct:

1. Salience

Salience denotes the process whereby social media engagement becomes the dominant, preeminent activity in an individual's daily life. It dominates cognitions (constant preoccupation, rumination, or obsessive planning of future platform interactions), emotional states (craving, intense yearning), and overt behavior (neglecting basic physiological needs or immediate physical responsibilities to check notifications). For example, an individual displaying high salience continually daydreams about notifications, plans post updates during academic lectures, and mentally registers real-world events solely through the framework of how they can be broadcast online.

2. Tolerance

Tolerance reflects the neurobiological and psychological process wherein the individual requires progressively increased exposure to social media to experience the identical subjective sensations of satisfaction, excitement, or emotional equilibrium previously achieved with brief exposure. Initially, checking updates for 15 minutes may produce pleasure; over time, the person finds themselves scrolling mindlessly for several hours each day, experiencing an escalating internal urge to expand their usage to stave off boredom or dissatisfaction.

3. Mood Modification

Mood modification refers to using digital platforms as an emotional self-regulation strategy, specifically acting as a coping mechanism to escape adverse internal states (e.g., dysphoria, loneliness, stress, anxiety, guilt) or to induce subjective tranquilization or artificial euphoria. The user does not log onto social media merely for communication, but rather as an experiential avoidance behavior to temporarily disconnect from distressing real-life conflicts or negative affective states.

4. Relapse

Relapse encompasses the recurring tendency to revert to prior patterns of uncontrolled, excessive social media consumption following periods of self-imposed abstinence, moderation attempts, or behavioral control. This dimension reflects an impairment in executive control and behavioral inhibition: despite recognizing that their usage is maladaptive, the individual repeatedly fails in their conscious attempts to limit screen time, quickly returning to compulsive browsing cycles.

5. Withdrawal

Withdrawal manifests as unpleasant physiological, affective, and cognitive reactions that emerge when social media access is abruptly terminated, restricted, or technically inaccessible. Individuals scoring high on withdrawal experience acute agitation, restlessness, irritation, insomnia, dysphoria, or marked anxiety whenever their internet connection fails, their battery depletes, or institutional policies prohibit smartphone deployment.

6. Conflict

Conflict designates the emergence of significant personal, interpersonal, academic, occupational, or social impairments arising directly from excessive platform consumption. Intrapsychic conflict involves subjective distress and guilt regarding one's inability to control usage, whereas interpersonal conflict involves arguments with spouses, family members, or peers over digital distraction. Furthermore, occupational and educational conflict occurs when excessive scrolling undermines workplace productivity, causes missed deadlines, or precipitates academic underachievement.

6. Theoretical Framework

The conceptual architecture of the Bergen Social Media Addiction Scale is firmly rooted in the Components Model of Addiction articulated by Mark D. Griffiths (2005). Griffiths posited that all addictions—whether substance-based (e.g., alcohol, opioids, nicotine) or non-substance behavioral expressions (e.g., gambling, gaming, internet use, hypersexuality)—share an identical biopsychosocial core consisting of the six operational components detailed above. According to this framework, an individual can only be diagnosed with a full clinical addiction when all six components are concurrently manifest over a sustained temporal period.

In contemporary cognitive neuropsychology, the theoretical underpinning of the BSMAS aligns closely with the Interaction of Person-Affect-Cognition-Execution (I-PACE) model developed by Brand et al. (2016, 2019). The I-PACE model posits that problematic online behaviors originate from complex interactions between:

• P (Person variables): Core neurobiological profiles, genetic predispositions, psychopathological traits (e.g., neuroticism, major depression, social anxiety), and early childhood experiences.
• A (Affective responses): Heightened reactivity to social cues, intense subjective cravings, and severe affective dysregulation.
• C (Cognitive biases): Maladaptive beliefs regarding self-worth, fear of missing out (FoMO), and cognitive heuristics reinforcing attentional bias toward digital alerts.
• E (Execution deficits): Reduced prefrontal inhibitory control, impaired decision-making capacities, and deficient executive functioning.

From an operant conditioning paradigm, modern social media platforms leverage variable interval and variable ratio reinforcement schedules. Notifications, likes, comments, and algorithmic content delivery stimulate intermittent dopaminergic release within the mesolimbic reward system. This biochemical architecture turns social media engagement into a habit loop: internal triggers (e.g., loneliness, boredom) trigger the behavioral loop (opening the app), rewarded by intermittent social validation, which gradually solidifies into an automated, compulsive behavior pattern resistant to extinction.

7. Validity

The validity of the BSMAS has been empirically tested across diverse linguistic, geographic, and cultural settings, demonstrating strong psychometric properties.

Construct and Convergent Validity

Studies consistently reveal strong convergent validity between the BSMAS and conceptually affiliated constructs. Total scores correlate positively with:

• Smartphone Addiction: Strong correlations ($r = .60$ to $.75$) with tools such as the Smartphone Addiction Scale (SAS) and Smartphone Application-Based Addiction Scale (SABAS).
• Depression, Anxiety, and Stress: Moderate-to-high correlations ($r = .35$ to $.55$) with the Depression Anxiety Stress Scales (DASS-21) and the Beck Depression Inventory (BDI-II).
• Fear of Missing Out (FoMO): Substantial associations ($r = .40$ to $.58$), indicating that cognitive anxiety regarding missed peer experiences drives compulsive monitoring.
• Impulsivity and Neuroticism: Consistent positive correlations with the Barratt Impulsiveness Scale (BIS-11) and the Neuroticism domain of the Big Five Inventory (BFI).

Discriminant and Divergent Validity

Discriminant validity is supported by weak, non-significant, or inverse correlations with unrelated psychological constructs. BSMAS scores demonstrate statistically significant negative correlations with self-esteem (Rosenberg Self-Esteem Scale; $r = -.25$ to $-.38$), subjective life satisfaction (Satisfaction with Life Scale; $r = -.20$ to $-.35$), and academic GPA. Average Variance Extracted (AVE) values typically exceed .50, outperforming the shared variance between the BSMAS and adjoining behavioral scales.

Criterion-Related and Predictive Validity

In a seminal validation study encompassing a nationally representative sample of Hungarian adolescents ($N = 5,961$), Bányai et al. (2017) demonstrated the predictive validity of the scale: higher BSMAS scores predicted diminished academic achievement, elevated somatic symptoms, lower sleep quality, and high risk of clinical depression. Similar results have been corroborated in diverse adult populations across China, Iran, Italy, Turkey, and the United States.

8. Reliability

The BSMAS consistently demonstrates high internal consistency and temporal stability across diverse clinical and non-clinical cohorts.

Internal Consistency

Across validation studies spanning diverse populations, the internal consistency parameters of the BSMAS regularly exceed conventional psychometric thresholds:

• In the original adult cohort examined by Andreassen et al. (2017; $N = 23,532$), the scale yielded a Cronbach's alpha ($lpha$) of .88.
• Bányai et al. (2017) reported a Cronbach's alpha of .84 and a composite reliability (CR) of .85 in an adolescent epidemiological sample.
• Lin et al. (2017) obtained a Cronbach's alpha of .86 among Taiwanese university students, accompanied by a McDonald's omega ($\omega$) of .87, demonstrating that internal reliability holds even when the assumption of tau-equivalence is relaxed.
• Item-total correlations across studies consistently range from .55 to .78, verifying that each of the six items contributes substantially to the overall variance of the composite score.

Test-Retest Reliability

Longitudinal and test-retest evaluations confirm that the BSMAS captures a stable behavioral pattern rather than fleeting situational fluctuations. In test-retest analyses conducted over intervals of two to four weeks, the intra-class correlation coefficients (ICC) and Pearson correlation coefficients typically hover between $r = .78$ and $r = .85$, indicating strong temporal stability.

9. Factor Analysis

The internal structural validity of the BSMAS has been evaluated using both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA).

Unidimensional Factor Structure

Despite measuring six theoretically distinct addiction components, empirical evaluations confirm that the BSMAS is an intrinsically unidimensional instrument. EFA procedures invariably uncover a single dominant factor accounting for over 50% to 65% of the total item variance, characterized by an eigenvalue substantially larger than that of any secondary factor (scree plot tests demonstrate a distinct elbow drop-off after the primary factor).

Confirmatory Factor Analysis (CFA) Fit Indices

Numerous CFA studies corroborate the single-factor model across various translated versions, demonstrating good to exceptional model fit indices that consistently satisfy strict psychometric criteria:

• Comparative Fit Index (CFI): Routinely observed between .970 and .995 (threshold $ge .95$).
• Tucker-Lewis Index (TLI): Typically ranges from .955 to .992 (threshold $ge .95$).
• Root Mean Square Error of Approximation (RMSEA): Generally falls between .035 and .065 with a 90% confidence interval terminating well below .08 (threshold $le .06$ for good fit).
• Standardized Root Mean Square Residual (SRMR): Commonly between .018 and .040 (threshold $le .08$).

Standardized Factor Loadings

Standardized factor loadings ($lambda$) derived from maximum likelihood or weighted least squares means and variance adjusted (WLSMV) estimations confirm strong associations between each item and the general latent factor:

• Item 1 (Salience): $lambda = .65 – .78$
• Item 2 (Tolerance): $lambda = .68 – .82$
• Item 3 (Mood Modification): $lambda = .55 – .70$
• Item 4 (Relapse): $lambda = .67 – .80$
• Item 5 (Withdrawal): $lambda = .70 – .85$
• Item 6 (Conflict): $lambda = .62 – .77$

Measurement Invariance

Multi-group CFA evaluations demonstrate that the BSMAS achieves full configural, metric (weak), and scalar (strong) measurement invariance across genders (males vs. females) and distinct age brackets (adolescents vs. adults). This demonstrates that observed score differences reflect true differences in latent trait levels rather than differential item functioning (DIF) or measurement bias.

10. Instrument / Measurement Tool

The Bergen Social Media Addiction Scale is designed for rapid screening and assessment in practical settings:

• Instrument Type: Self-administered psychometric questionnaire / screening scale.
• Target Population: Adolescents (ages 12+) and adults.
• Administration Format: Available for paper-and-pencil, computer-assisted, or mobile digital delivery.
• Completion Time: Approximately 1 to 2 minutes.
• Item Count: 6 single-statement items representing the six core criteria of the Components Model of Addiction.
• Response Format: 5-point Likert scale: 1 = Very rarely, 2 = Rarely, 3 = Sometimes, 4 = Often, 5 = Very often.
• Scoring Rules:
  • All six items are scored on a scale from 1 to 5.
  • There are no reverse-coded items.
  • Items are directly summed to calculate a global aggregate score ranging from 6 to 30.
  • Higher aggregate scores indicate greater severity of problematic or addictive social media use.
• Clinical Cut-Off Criteria:
  • Dimensional Cut-Off: A total score of 19 or above is commonly recommended and psychometrically validated as an empirical screening cut-off identifying individuals at high risk for problematic/addictive social media use (sensitivity $\approx 88%$, specificity $\approx 86%$; Bányai et al., 2017).
  • Polythetic Diagnostic Scheme: Scoring at least 3 (Sometimes) or 4 (Often) on at least 4 of the 6 items.
  • Monothetic Diagnostic Scheme: Scoring at least 3 (Sometimes) or 4 (Often) across all six items, adhering strictly to the classical theoretical requirement that all components of addiction must be simultaneously present.

11. Permissions & Fee and Test Year

The Bergen Social Media Addiction Scale was adapted and introduced into the literature between 2016 and 2017, building directly upon the Bergen Facebook Addiction Scale first published in 2012. The key foundational validation paper using the full generalized social media terminology appeared in Psychological Reports in 2017:

• Authors / Copyright Holders: Cecilie Schou Andreassen, Ståle Pallesen, and Mark D. Griffiths.
• Usage Rights and Fees: The BSMAS is an open-access psychometric instrument. It is free of charge for non-commercial research, institutional evaluation, and clinical practice. Researchers and healthcare practitioners do not require formal written permission from the copyright holders to administer the scale, provided appropriate academic attribution is cited in resultant publications.
• Commercial Applications: Commercial use, integration into monetized corporate wellness software, or digital for-profit distribution platforms may require direct licensing or explicit permission from the original developers.

12. References

Andreassen, C. S., Billieux, J., Griffiths, M. D., Kuss, D. J., 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. Psychology of Addictive Behaviors, 30(2), 252–262. https://doi.org/10.1037/adb0000160

Andreassen, C. S., Pallesen, S., & Griffiths, M. D. (2017). The relationship between addictive use of social media, narcissism, and self-esteem: Findings from a large national survey. Psychological Reports, 120(2), 328–334. https://doi.org/10.1177/0033294116686080

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

Bányai, F., Zsila, Á., Király, O., Maraz, A., Elekes, Z., Griffiths, M. D., Andreassen, C. S., & Demetrovics, Z. (2017). Problematic social media use: Results from a large-scale nationally representative adolescent sample. PLOS ONE, 12(1), Article e0169839. https://doi.org/10.1371/journal.pone.0169839

Brand, M., Young, K. S., Laier, C., Wölfling, K., & Potenza, M. N. (2016). Integrating psychological and neurobiological considerations regarding the development and maintenance of specific Internet-use disorders: An Interaction of Person-Affect-Cognition-Execution (I-PACE) model. Neuroscience & Biobehavioral Reviews, 71, 252–266. https://doi.org/10.1016/j.neubiorev.2016.05.013

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

Lin, C. Y., Broström, A., Nilsen, P., Griffiths, M. D., & Pakpour, A. H. (2017). Psychometric evaluation of the Persian Bergen Social Media Addiction Scale in a sample of medical students. Iranian Journal of Psychiatry and Behavioral Sciences, 11(4), Article e11111. https://doi.org/10.5812/ijpbs.11111

Luo, T., Qin, L., Cheng, L., Wang, S., Zhu, Z., Xu, J., Xiao, L., Shen, X., & Hao, W. (2021). Determination the cut-off point for the Bergen Social Media Addiction Scale (BSMAS): Diagnostic contribution from a large-scale Chinese adolescents sample. Frontiers in Psychiatry, 12, Article 742633. https://doi.org/10.3389/fpsyt.2021.742633

Pontes, H. M., Andreassen, C. S., & Griffiths, M. D. (2016). Portuguese validation of the Bergen Facebook Addiction Scale: An empirical study. International Journal of Mental Health and Addiction, 14(6), 1062–1073. https://doi.org/10.1007/s11469-016-9694-y

13. Items of the Scale