Akbari, M., Hossein Bahadori, M., Khanbabaei, S., Boruki Milan, B., Horvath, Z., Griffiths, M. D., & Demetrovics, Z. (2023). Metacognitions as a predictor of problematic social media use and internet gaming disorder: Development and psychometric properties of the Metacognitions about Social Media Use Scale (MSMUS). Addictive Behaviors, 137, Article 107541. https://doi.org/10.1016/j.addbeh.2022.107541

Article  PubMed  Google Scholar 

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

Article  Google Scholar 

Andreassen, C., & Pallesen, S. (2014). Social network site addiction - An overview. Current Pharmaceutical Design. https://doi.org/10.2174/13816128113199990616

Article  PubMed  Google Scholar 

Bahrami, F., & Yousefi, N. (2011). Females are more anxious than males: A metacognitive perspective. Iranian Journal of Psychiatry and Behavioral Sciences, 5(2), 83. https://pmc.ncbi.nlm.nih.gov/articles/PMC3939970/

Bentler, P. M. (1995). EQS structural equations program manual. Multivariate Software.

Google Scholar 

Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588–606. https://doi.org/10.1037/0033-2909.88.3.588

Article  Google Scholar 

Bottesi, G., Ghisi, M., Altoè, G., Conforti, E., Melli, G., & Sica, C. (2015). The Italian version of the Depression Anxiety Stress Scales-21: Factor structure and psychometric properties on community and clinical samples. Comprehensive Psychiatry, 60, 170–181. https://doi.org/10.1016/j.comppsych.2015.04.005

Article  PubMed  Google Scholar 

Brand, M., Laier, C., & Young, K. S. (2014). Internet addiction: Coping styles, expectancies, and treatment implications. Frontiers in Psychology, 5, Article 1256. https://doi.org/10.3389/fpsyg.2014.01256

Article  PubMed  PubMed Central  Google Scholar 

Brand, M., Wegmann, E., Stark, R., Müller, A., Wolfling, K., Robbins, T. W., et al. (2019). The interaction of Person-Affect-Cognition-Execution (I-PACE) model for addictive behaviors: Update, generalization to addictive behaviors beyond Internet use disorders, and specification of the process character of addictive behaviors. Neuroscience and Biobehavioral Reviews, 104, 1–10. https://doi.org/10.1016/j.neubiorev.2019.06.032

Article  PubMed  Google Scholar 

Brislin, R. W. (1986). The wording and the translation of research instruments. In W. Lonner, & J. Berry (Eds.), Fields methods in cross-cultural research (pp. 137–164). Sage.

Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen and J. S. Long (Eds.), Testing structural equation models (pp. 136-162). Newbury Park, CA: Sage.

Casale, S., Caponi, L., & Fioravanti, G. (2020). Metacognitions about problematic Smartphone use: Development of a self-report measure. Addictive Behaviors, 109, Article 106484. https://doi.org/10.1016/j.addbeh.2020.106484

Article  PubMed  Google Scholar 

Casale, S., Fioravanti, G., Gori, A., Nigro, F., & Benucci, S. B. (2025). Investigating the role of avoidance expectancies and metacognitions about social compensation through SNSs in the pathway from psychological distress to problematic social networking sites use. Psychological Reports. https://doi.org/10.1177/00332941251320309

Casale, S., Musicò, A., & Spada, M. M. (2021). A systematic review of metacognitions in Internet Gaming Disorder and problematic Internet, smartphone and social networking sites use. Clinical Psychology & Psychotherapy, 28(6), 1494–1508. https://doi.org/10.1002/cpp.2588

Article  Google Scholar 

Casale, S., Rugai, L., & Fioravanti, G. (2018). Exploring the role of positive metacognitions in explaining the association between the fear of missing out and social media addiction. Addictive Behaviors, 85, 83–87. https://doi.org/10.1016/j.addbeh.2018.05.020

Article  PubMed  Google Scholar 

Caselli, G., Martino, F., Spada, M. M., & Wells, A. (2018). Metacognitive therapy for alcohol use disorder: A systematic case series. Frontiers in Psychology, 9, Article 2619. https://doi.org/10.3389/fpsyg.2018.02619

Article  PubMed  PubMed Central  Google Scholar 

Cheung, G. W., & Rensvold, R. B. (2002). Evaluating Goodness-of-Fit Indexes for Testing Measurement Invariance. Structural Equation Modeling, 9, 233-255. https://doi.org/10.1207/S15328007SEM0902_5

Clark, L. A., & Watson, D. (1995). Constructing validity: Basic issues in objective scale development. Psychological Assessment, 7(3), 309–319. https://doi.org/10.1037/1040-3590.7.3.309

Article  Google Scholar 

Curran, P. J., West, S. G., & Finch, J. F. (1996). The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis. Psychological Methods, 1(1), 16–29. https://doi.org/10.1037/1082-989X.1.1.16

Article  Google Scholar 

Halvorsen, M., Hagen, R., Hjemdal, O., Eriksen, M. S., Sørli, Å. J., Waterloo, K., Eisemann, M., & Wang, C. E. A. (2015). Metacognitions and thought control strategies in unipolar major depression: A comparison of currently depressed, previously depressed, and never-depressed individuals. Cognitive Therapy and Research, 39(1), 31–40. https://doi.org/10.1007/s10608-014-9638-4

Article  Google Scholar 

Hamonniere, T., & Varescon, I. (2018). Metacognitive beliefs in addictive behaviours: A systematic review. Addictive Behaviors, 85, 51–63. https://doi.org/10.1016/j.addbeh.2018.05.018

Article  PubMed  Google Scholar 

Hu, L., & Bentler, P. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118

Article  Google Scholar 

Jöreskog, K. G., & Sörbom, D. (1993). LISREL8 user’s reference guide. Scientific Software International.

Google Scholar 

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.

Article  Google Scholar 

Kardefelt-Winther, D. (2017). Conceptualizing Internet use disorders: Addiction or coping process? Psychiatry and Clinical Neurosciences, 71(7), 459–466. https://doi.org/10.1111/pcn.12413

Article  PubMed  Google Scholar 

Kenny, D. A., Kaniskan, B., & McCoach, D. B. (2015). The performance of RMSEA in models with small degrees of freedom. Sociological Methods & Research. https://doi.org/10.1177/0049124114543236

Article  Google Scholar 

Kuhn, D. (2000). Metacognitive development. Current Directions in Psychological Science, 9(5), 178–181. https://doi.org/10.1111/1467-8721.00088

Article  Google Scholar 

Landis, R. S., Beal, D. J., & Tesluk, P. E. (2000). A comparison of approaches to forming composite measures in structural equation models. Organizational Research Methods, 3(2), 186–207. https://doi.org/10.1177/109442810032003

Article  Google Scholar 

Lovibond, P. F., & Lovibond, S. H. (1995). The structure of negative emotional states: Comparison of the depression anxiety stress scales (DASS) with the Beck Depression and Anxiety inventories. Behaviour Research and Therapy, 33, 335–343. https://doi.org/10.1016/0005-7967(94)00075-U

Article  CAS  PubMed  Google Scholar 

MacKinnon, D. P., Lockwood, C. M., & Williams, J. (2004). Confidence limits for the indirect effect: Distribution of the product and resampling methods. Multivariate Behavioral Research, 39(1), 99–128. https://doi.org/10.1207/s15327906mbr3901_4

Article  PubMed  PubMed Central  Google Scholar 

Mardia, K. V. (1970). Measures of multivariate skewness and kurtosis with applications. Biometrika, 57(3), 519–530. https://doi.org/10.1093/biomet/57.3.519

Article  Google Scholar 

Monacis, L., De Palo, V., Griffiths, M. D., & Sinatra, M. (2017). Social networking addiction, attachment style, and validation of the Italian version of the Bergen Social Media Addiction Scale. Journal of Behavioral Addictions, 6(2), 178–186. https://doi.org/10.1556/2006.6.2017.023

Article  PubMed  PubMed Central  Google Scholar 

Morrison, A. P., & Wells, A. (2003). A comparison of metacognitions in patients with hallucinations, delusions, panic disorder, and non-patient controls. Behaviour Research and Therapy, 41(2), 251–256. https://doi.org/10.1016/S0005-7967(02)00095-5

Article  PubMed  Google Scholar 

Naghibsadati, N. S., Mesrabadi, J., & Farid, A. (2023). Meta-analysis of gender differences in metacognition and its components. Biquarterly Journal of Cognitive Strategies in Learning, 11(20), 163–188. https://doi.org/10.22084/j.psychogy.2023.26688.2498

Article  Google Scholar 

Olstad, S., Solem, S., Hjemdal, O., & Hagen, R. (2015). Metacognition in eating disorders: Comparison of women with eating disorders, self-reported history of eating disorders or psychiatric problems, and healthy controls. Eating Behaviors, 16, 17–22. https://doi.org/10.1016/j.eatbeh.2014.10.019

Article  PubMed  Google Scholar 

Politte-Corn, M., Nick, E. A., & Kujawa, A. (2023). Age-related differences in social media use, online social support, and depressive symptoms in adolescents and emerging adults. Child and Adolescents Mental Health, 28(4), 497–503. https://doi.org/10.1111/camh.12640

Article  Google Scholar 

Rioux, M., Little, T. D., & O’Brien, M. (2020). Item parcels as indicators: Why, when, and how to use them in small sample research. In M. R. Hank & T. D. Little (Eds.), Small simple size solutions (pp. 203–214). Guilford Press. https://doi.org/10.4324/9780429273872-17.

Rosseel, Y. (2012). Lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48, 1–36.

Article  Google Scholar 

Schneider, W., Tibken, C., & Richter, T. (2022). The development of metacognitive knowledge from childhood to young adulthood: Major trends and educational implications. Advances in Child Development and Behavior, 63, 273–307. https://doi.org/10.1016/bs.acdb.2022.04.006

Article