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    A Cross-Sectional Analysis of Psychological and Dermatologic Manifestations Post-February 6 Earthquakes in Dermatology Patients
    (Korean Dermatological Assoc, 2026) Gencoglu, Sule; Cansel, Neslihan
    Background: Earthquakes are major natural disasters that can trigger both psychological and dermatological disturbances. The complex interaction between post-disaster mental health and skin disease remains underexplored, particularly beyond the acute phase. Objective: To investigate the prevalence of anxiety, depression, and post-traumatic stress disorder (PTSD) and their associations with dermatologic diagnoses in patients attending a dermatology clinic one year after the February 6, 2023 earthquakes in T & uuml;rkiye. Methods: This cross-sectional study included 673 dermatology outpatients who had resided in Malatya during the earthquakes. Sociodemographic and clinical data were collected. Psychological distress was assessed using the Hospital Anxiety and Depression Scale and Posttraumatic Stress Disorder-Short Scale. Results: Clinically significant anxiety, depression, and PTSD were observed in 44.0%, 69.2%, and 15.8% of participants, respectively. The most frequent dermatologic diagnoses were telogen effluvium (18.7%), pruritus (16.0%), and urticaria (10.1%). Telogen effluvium was more common among patients with anxiety (p=0.004) and PTSD (p=0.009), whereas alopecia areata and psoriasis showed higher rates in patients with anxiety and depression (p<0.05). Female sex, a history of psychiatric illness, and high education level were associated with the presence of PTSD. Conclusion: High levels of psychological distress persist among dermatology patients even one year after the earthquakes, underscoring the importance of integrated dermatologic and mental health assessment.
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    A NEW ARTIFICIAL INTELLIGENCE-BASED CLINICAL DECISION SUPPORT SYSTEM FOR DIAGNOSIS OF MAJOR PSYCHIATRIC DISEASES BASED ON VOICE ANALYSIS
    (Medicinska Naklada Zagreb, 2023) Cansel, Neslihan; Alcin, Ömer Faruk; Yılmaz, Ömer Furkan; Ari, Ali; Akan, Mustafa; Ucuz, İlknur
    Background: Speech features are essential components of psychiatric examinations, serving as important markers in the recognition and monitoring of mental illnesses. This study aims to develop a new clinical decision support system based on artificial intelligence, utilizing speech signals to distinguish between bipolar, depressive, anxiety and schizophrenia spectrum disorders. Subjects and methods: A total of 79 patients, who were admitted to the psychiatry clinic between 2020-2021, including 15 with schizophrenia spectrum disorders, 24 with anxiety disorders, 25 with depressive disorders, and 15 with bipolar affective disorder, alongside with 25 healthy individuals were included in the study. The speech signal dataset was created by recording participants’ readings of two texts determined by the Russell emotion model. The number of speech samples was increased by using random sampling in speech signals. The sample audio signals were decomposed into time-frequency coefficients using Wavelet Packet Transform (WPT). Feature extraction was performed using each coefficient obtained from both Mel-Frequency Cepstral Coefficients (MFCC) and Gammatone Cepstral Coefficient (GTCC) methods. The disorder classification was carried out using k-Nearest Neighbor (kNN) and Support Vector Machine (SVM) classifiers. Results: The success rate of the developed model in distinguishing the disorders was 96.943%. While the kNN model exhibited the highest performance in diagnosing bipolar disorder, it performed the least effectively in detecting depressive disorders. Whereas, the SVM model demonstrated close and high performance in detecting anxiety and psychosis, but its performance was low in identifying bipolar disorder. The findings support the utilization of speech analysis for distinguishing major psychiatric disorders. In this regard, the future development of artificial intelligence-based systems has the potential to enhance the psychiatric diagnosis process. © Medicinska naklada – Zagreb, Croatia.
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    Factors Affecting Patient Satisfaction in Breast Reduction Surgeries: A Retrospective Clinical Study
    (Springer, 2021) Özbey, Rafet; Cansel, Neslihan; Fırat, Cemal; Baydemir, Muhammed Bedir
    Background: Breast reduction surgeries increase the individual's comfort of life by eliminating the problems caused by breast hypertrophy. We aimed to evaluate the effects of patients' demographic and operational data on satisfaction by using Breast-Q Questionnaire. Methods: Breast-Q Questionnaire breast reduction module was applied to patients who had undergone breast reduction surgery by a single surgeon between 2016 and 2020 and who agreed to participate in the study. Demographic and operational data and Questionnaire results were analyzed with the help of SPSS Statistics V21.0 program by considering p < 0.05 as significant. Results: Of the 94 patients who had undergone surgery, 52 who agreed to fill in the questionnaire were included in the study. Mean age was 39 and mean body mass index was (BMI) 28.6 kg/m2. Forty eight (92.3%) patients had undergone surgery for noncosmetic reasons. Significant differences were found between the physical well-being scores of the participants whose BMI was <25 and those whose BMI was >30. It was found that physical well-being (p= 0.001) and the amount of tissue removed increased with the increase in BMI (p = 0.018). No association was found between the tissue removed, the change in bra sizes and satisfaction. Satisfaction with outcome of surgery was found as 84.51% ± 24.28. Linear association was found between pre-information given and Breast-Q scores (p < 0.001). Conclusions: In our study, it was found that the tissue removed, breast size and the change in bra size had no effect on patient satisfaction. Being informed was found to be directly related to satisfaction. Providing sufficient information, understanding the expectations and obtaining the desired cosmetic results is important. Although physical complaints are at the forefront in the decision of surgery, aesthetic appearance is more effective in being satisfied with the surgery. A breast the weight of which is reduced through breast reduction and which looks aesthetically beautiful can only please the patient. Level of Evidence IV This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .