Recep Tayyip Erdoğan Üniversitesi Kurumsal Akademik Arşivi
DSpace@RTEÜ, Recep Tayyip Erdoğan Üniversitesi tarafından doğrudan ve dolaylı olarak yayınlanan; kitap, makale, tez, bildiri, rapor, araştırma verisi gibi tüm akademik kaynakları uluslararası standartlarda dijital ortamda depolar, Üniversitenin akademik performansını izlemeye aracılık eder, kaynakları uzun süreli saklar ve yayınların etkisini artırmak için telif haklarına uygun olarak Açık Erişime sunar.
Güncel Gönderiler
Deprem bölgesinde çalışan hemşirelerin deneyimleri: nitel bir çalışma
(Association of Executive Nurses, 2025) Gümüşler Başaran, Ayşe; Kefeli Çol, Bahar; Genç Köse, Burcu
Aim: The demand for health services increases after disasters, and nurses assume essential roles in health service delivery. Natural disasters such as earthquakes can negatively affect the quality of nurses' health care. This study aimed to understand the problems experienced by nurses who experienced the February 6, 2023 earthquake and worked in this region, their views on the future of nursing, the impact of the earthquake on nursing and the feelings of nurses. Method: This qualitative study is a phenomenological study conducted with seven nurses working in the earthquake zone in September 2023. Data were collected using a semi-structured questionnaire of 4 questions. Descriptive and content analysis were used to analyse the data. Results: It was determined that the participants experienced a lack of resources, a lack of physical environment, a lack of coordination and communication, hygiene problems, and security problems while providing health services in the earthquake zone. Nurses primarily stated that lack of resources and hygiene problems should be eliminated. They are concerned that there will be a lack of workforce in the future. When asked about the emotions they felt, the theme of negative emotions such as anxiety, hopelessness, fear, panic and loneliness was reached. Conclusion: Nurses providing healthcare services in the earthquake zone experienced various inadequacies and deficiencies and felt negative emotions such as anxiety and hopelessness. Since this situation may negatively affect the quality of care, nurses should be supported, and health services should be improved.
Not being in education, employment, or training (NEET) in a collectivist Turkish culture: exploring the experiences of social studies teachers
(Springer Nature, 2025) Kabadayı, Fedai; Akıncı, Muhammed; Öztürk, Fatih; Beldağ, Adem
This study explores the experiences of social studies teachers in Türkiye who are not in education, employment, or training (NEET), within a collectivist cultural context. A qualitative design was used to analyze the narratives of 22 individuals experiencing NEET status, identified through a two-stage process involving semi-structured oral and written interviews. A problem–solution oriented narrative analysis approach guided the exploration of reasons for NEET status, lived challenges, and coping strategies. Findings were organized around revealing how cultural norms, family expectations, and systemic barriers shaped NEET experiences. The study offers implications for educators, policymakers, and community leaders.
Assessing microplastic pollution in marine mammals: evidence from three cetacean species in the southeastern Black Sea
(Frontiers Media SA, 2025) Onay, Hatice; Er, Akif; Minaz, Mert; Emanet, Muhammet; Ceylan, Yusuf; Akdemir, Tolga; Karslı, Barış; Dalgıç, Göktuğ
Microplastic (MP) pollution has emerged as a pervasive environmental threat, with growing evidence of its accumulation across various marine trophic levels, including top predators such as cetaceans. This study investigates MP abundance, size distribution, morphology, color, and polymer composition in the gastrointestinal tracts (GITs) of three cetacean species sampled from the southeastern Black Sea. A total of seven individuals were examined, with MP abundances ranging from 5 to 139 particles per individual. Fiber-type MPs were predominant (75%), with black, green, and transparent colors being the most frequently observed. The majority of MPs were small in size, with an average length of 2002 ± 1961 µm, suggesting possible trophic transfer from lower-level organisms such as copepods and fish. Polymer analysis revealed polyamide (PA), polyacrylonitrile (PAN), and ethylene-vinyl acetate (EVA) as the most common polymer types, indicating both fishing gear and domestic wastewater as primary MP sources. Spatial patterns in stomach fullness and MP load suggest that local environmental conditions, such as fishing activity and tourism, influence exposure levels. The study highlights the significance of both incidental ingestion during feeding—especially through net interactions—and trophic transfer as key MP exposure pathways in cetaceans. These findings demonstrate the potential ecological risks posed by MPs at higher trophic levels and emphasize the urgent need for biodegradable alternatives to synthetic fishing gear and improved wastewater management. Moreover, collaborative efforts among local authorities and NGOs are recommended to raise awareness and support adaptive environmental management in the region.
Factors influencing the transition time from psoriasis to psoriatic arthritis: a real-world multicenter analysis
(Springer, 2025) Kılıç, Gamze; Kılıç, Erkan; Tekeoğlu, İbrahim; Sargın, Betül; Cengiz, Gizem; Balta, Nihan Cüzdan; Devrimsel, Gül; Nas, Kemal
To identify clinical and demographic predictors associated with the timing of transition from psoriasis (PsO) to psoriatic arthritis (PsA), and to compare the characteristics of patients with concurrent PsO-PsA onset versus those with prolonged transition. A multi-center, observational study was conducted using data from the Turkish League Against Rheumatism (TLAR) network including PsA patients fulfilling CASPAR criteria. Patients were categorized into two groups: Group 1 (concurrent PsO and PsA onset within ± 1 year) and Group 2 (prolonged transition to PsA, > 1 year after PsO). Demographic, clinical, and laboratory characteristics, disease activity, and patient-reported outcomes were compared between groups. Logistic regression was employed to determine independent predictors of prolonged transition. Among 799 patients (mean age 46.8 ± 12.3 years), 237 (29.7%) had concurrent onset and 562 (70.3%) had a prolonged transition, with a mean PsO-to-PsA interval of 12.9 ± 9.6 years. Depression (p = 0.005) and fatigue levels (p = 0.011) were significantly higher in patients with prolonged transition to PsA. Multivariate analysis revealed that scalp psoriasis (OR = 7.162), nail psoriasis (OR = 3.270), family history of PsO (OR = 1.813), and enthesitis ever (OR = 2.187) were associated with prolonged transition. Conversely, family history of PsA (OR = 0.421) and older age at PsO onset (OR = 0.957) predicted shorter transition. Prolonged transition from PsO to PsA is influenced by distinct clinical and demographic factors. Scalp/nail psoriasis, family history of PsO, and enthesitis ever may signal higher risk for prolonged PsA onset. Recognizing these markers can support timely referral and intervention, minimizing diagnostic delay and improving long-term patient outcomes.
Category-aware two-stage divide-and-ensemble framework for sperm morphology classification
(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Türkoğlu, Aydın Kağan; Serbes, Görkem; Uzun, Hakkı; Aktaş, Abdulsamet; Yiğit, Merve Hüner; İlhan, Hamza Osman
Introduction: Sperm morphology is a fundamental parameter in the evaluation of male infertility, offering critical insights into reproductive health. However, traditional manual assessments under microscopy are limited by operator dependency and subjective interpretation caused by biological variation. To overcome these limitations, there is a need for accurate and fully automated classification systems. Objectives: This study aims to develop a two-stage, fully automated sperm morphology classification framework that can accurately identify a wide spectrum of abnormalities. The framework is designed to reduce subjectivity, minimize misclassification between visually similar categories, and provide more reliable diagnostic support in reproductive healthcare. Methods: A novel two-stage deep learning-based framework is proposed utilizing images from three staining-specific versions of a comprehensive 18-class dataset. In the first stage, sperm images are categorized into two principal groups: (1) head and neck region abnormalities, and (2) normal morphology together with tail-related abnormalities. In the second stage, a customized ensemble model—integrating four distinct deep learning architectures, including DeepMind’s NFNet-F4 and vision transformer (ViT) variants—is employed for detailed abnormality classification. Unlike conventional majority voting, a structured multi-stage voting strategy is introduced to enhance decision reliability. Results: The proposed framework consistently outperforms single-model baselines, achieving accuracies of 69.43%, 71.34%, and 68.41% across the three staining protocols. These results correspond to a statistically significant 4.38% improvement over prior approaches in the literature. Moreover, the two-stage system substantially reduces misclassification among visually similar categories, demonstrating enhanced ability to detect subtle morphological variations. Conclusions: The proposed two-stage, ensemble-based framework provides a robust and accurate solution for automated sperm morphology classification. By combining hierarchical classification with structured decision fusion, the method advances beyond traditional and single-model approaches, offering a reliable and scalable tool for clinical decision-making in male fertility assessment.
