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Yayın Exploring the impact of Flash technique on test anxiety among adolescents(SAGE Publications Ltd, 2025-07) Çitil Akyol, Canan; İnci İzmir, Sevim BerrinThis study aims to investigate the specific effects of Flash Technique (FT) on adolescents with test anxiety. This follow-up study consists of 38 adolescents, 14–17 years of age (M = 15.39, SD = 1.13). Pre-post assessments were conducted using the Test Anxiety Inventory (TAI), Scale of Attitudes Negatively Affecting the Performance I/Test (POET), and Beck Anxiety Inventory (BAI) at baseline, at the end of the 4thand 12thweeks of therapy. The FT was applied for 12 weeks, with one weekly session as an intervention. As a result of the therapy process, the baseline means of total BAI scores decreased from 25.26 to 2.18; the baseline means of TAI decreased from 149.79 to 39.13, and the baseline mean of POET decreased from 298.47 to 73.84 at the end of the 12th week of therapy. Also, the baseline means of SUD scores decreased from 9.42 to zero at the end of the 12th week of treatment. All the adolescents showed complete improvement after the 12th week of the FT. The study findings showed that the test anxiety symptoms significantly decreased with the treatment of the FT. FT can be an effective intervention for test anxiety in adolescents.Yayın Theta and Beta1 frequency band values predict dyslexia classification(John Wiley and Sons Ltd, 2025-12-29) Eroğlu, Günet; Harb, Mhd Raja AbouDyslexia, impacting children's reading skills, prompts families to seek cost-effective neurofeedback therapy solutions. Utilising machine learning, we identified predictive factors for dyslexia classification. Employing advanced techniques, we gathered 14-channel Quantitative Electroencephalography (QEEG) data from 200 participants, achieving 99.6% dyslexic classification accuracy through cross-validation. During validation, 48% of dyslexic children's sessions were consistently classified as normal, with a 95% confidence interval of 47.31 to 48.68. Focusing on individuals consistently diagnosed with dyslexia during therapy, we found that dyslexic individuals exhibited higher theta values and lower beta1 values compared to typically developing children. This study pioneers machine learning in predicting dyslexia classification factors, offering valuable insights for families considering neurofeedback therapy investment.
