Somatosensory Amplification and Psychological and Functional Status In Patients With Knee Osteoarthritis

This study is a screening study designed to reveal the relationship between the level of somatosensory amplification and the psychological-functional status and the level of pain felt in patients with knee pain due to knee OA. Considering the correlation of the features to be examined in the literature, it was found that the required sample size should be at least 80 with a test power of 95%, a type I error of 0.05 and an effect size of 0.34. 88 patients between the ages of 40-84 who have been diagnosed with knee OA and have complaints for at least 6 months will be included in the study. Patients with knee pain due to any rheumatologic disease other than OA and individuals with knee pain due to a recent traffic accident or other lower extremity trauma will be excluded from the study. The patients' sociodemographic characteristics such as age, height, weight, body mass index (BMI), gender, education level, marital status will be evaluated using the sociodemographic information form, somatosensory amplification levels will be evaluated with the 'Somatosensory Amplification Scale (SSAS)', the presence of kinesiophobia with the 'Tampa Kinesiophobia Scale (TSK)', pain levels with the Visual Analog Scale (VAS), the presence of depression with the 'Beck Depression Inventory (BDI)', and functional status with the total score of the 'Western Ontario and McMaster Universities Arthritis Index (WOMAC)'. Statistical analysis of the data will be done using IBM SPSS Statistics version 20.0 (SPSS Inc., New York, USA). Kolmogorov-Smirnov test will be used to determine whether the variables are normally distributed, and the socio-demographic information of the participants and the scores they received from the SSAS, TAMPA, VAS, BDI and WOMAC questionnaires will be expressed as percentages, ratios or averages. The linear relationship between quantitative variables will be analyzed with Pearson correlation analysis, and the correlation between qualitative and quantitative variables will be analyzed with variance analysis (ANOVA), and independent samples t-test. In all analyses, p\<0.05 will be considered statistically significant.