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DİJİTAL HİKÂYELEŞTİRME ATÖLYESİ KAPSAMINDA HAZIRLANAN OLUMLU DOĞUM HİKÂYEVİDEOLARININ KADINLARIN DOĞUM KORKUSU, DOĞUM ÖZYETERLİLİĞİ ve DOĞUM TERCİHİNEETKİSİ: RANDOMİZE KONTROLLÜ ÇALIŞMA
No full textInvestigating the Developmental Capacity of Latent Fingerprints Exposed to Cold Weather Conditions: An Experimental Study
No full textDietary total antioxidant capacity and frailty in Turkish community-dwelling and nursing home: cross-sectional study
No full textBackground: This study examines the relationship between dietary total antioxidant capacity, frailty, and nutritional status in Turkish older adults living in the community and nursing homes. Methods: This study included 160 older adults (50% female) living in the community (n = 80) and a nursing home (n = 80). Anthropometric measurements were taken, and BMI was calculated. Demographic characteristics, nutritional status (MNA-SF: Mini Nutritional Assessment Short Form), frailty (FRAIL Scale), activities of daily living (Katz ADL), and three-day food consumption records were assessed. Dietary total antioxidant capacity was determined based on the three-day food consumption record. Results: The mean ages of the groups were similar (72.5 ± 6.0 and 72.2 ± 5.9 years). Nursing home residents had significantly higher rates of chronic disease (91.3%) and regular medication use (90.0%) (p 0.05). Frail (32.5%) and pre-frail (40.0%) rates were higher in nursing home residents compared to elderly community dwellers (21.2 and 38.8%, respectively). Dependence ratios were similar between the groups (p > 0.05). Community-dwelling participants had a lower risk of malnutrition. While their daily carbohydrate intake was lower, nursing home residents had higher intakes of protein, fat, ω-3 fatty acids, fiber, vitamins (except vitamin E), and minerals. Frailty showed a strong negative correlation with Katz (r = −0.56, p < 0.001) and MNA-SF scores (r = −0.44, p < 0.001), while weak positive correlations were observed with TRAP, TEAC, and FRAP3 values. A negative correlation was observed between the residential setting and TORAC (r = −0.424, p < 0.001), TRAP (r = −0.190, p < 0.001), TEAC (r = −0.257, p < 0.001), and total VCEAC (r = −0.241, p = 0.002) values. Conclusion: Residential setting may affect nutrient intake, frailty, dietary total antioxidant capacity, and overall health in older adults
Elektronik Sağlık Kaydı Verilerinden Derin Öğrenme Yöntemleri ile Alkol Kullanıcısı Tahmini
No full textAlkol tüketiminin bireyler ve toplumlar üzerinde sağlıksal, ekonomik, sosyal ve kültürel yönler dedâhil olmak üzere çeşitli alanlarda olumsuz etkileri vardır. Alkol kullanımının öngörülmesi, alkolünolumsuz etkilerini önlemek için çok önemli bir araştırma konusudur. Literatürde genellikle dozabağlı alkol kullanım bozukluğu tahmin edilirken, bu çalışmada literatürden farklı olarak dozdanbağımsız alkol kullanıcısı tahmini yapılmaktadır. Bu tahmin popüler derin öğrenme yöntemlerikullanılarak elektronik sağlık kaydı verilerinden yapılmaktadır. Çalışmada kullanılan veri kümesi,Kore'deki Ulusal Sağlık Sigortası Hizmetinden toplanan 991346 bireye ait kişisel özellikler vesağlık parametrelerini içeren 24 farklı öznitelikten oluşmaktadır. Veriler, sayısallaştırma venormalizasyon ön işleme adımlarından sonra optimize edilmiştir. Veri kümesine belirli miktardaeğitim ve test ayrımı uygulanmıştır. Ardından, yapay sinir ağları, LSTM ve CNN yöntemikullanılarak bir alkol kullanıcısı tahmin modeli geliştirilmiştir. Elde edilen sonuçlara göre modellerbirbirine yakın tahmin başarısı elde etse de en iyi sonucu yapay sinir ağları elde etti. Yapay sinirağlarından sonra CNN ikinci sırada, LSTM ise son sırada yer aldı. Çalışmada birden fazla derinöğrenme yöntemi bir arada kullanılarak derin öğrenme yöntemlerinin mevcut problem üzerindekigenel başarısı hakkında bir sonuca varılmış ve problemin çözümüne önemli katkı sağlayacak biryöntem ortaya konulmuştur.Alcohol consumption has negative effects on individuals and societies in various areas, including health, economic, social and cultural aspects. Alcohol use prediction is a very important research topic to prevent the negative effects of alcohol. While dose-dependent alcohol use disorder is usually predicted in the literature, in this study, unlike the literature, dose-independent alcohol users are predicted. This prediction is made from electronic health record data using popular deep learning methods. The dataset used in the study consists of 24 different attributes including personal characteristics and health parameters of 991346 individuals collected from the National Health Insurance Service in Korea. The data were optimised after digitisation and normalisation preprocessing steps. A certain amount of training and test separation was applied to the dataset. Then, an alcohol user prediction model was developed using artificial neural networks, LSTM and CNN method. According to the results obtained, although the models achieved close prediction success, artificial neural networks achieved the best result. After artificial neural networks, CNN ranked second, and LSTM ranked last. By using more than one deep learning method together in the study, a conclusion about the general success of deep learning methods on the current problem has been made and a method that will make an important contribution to the solution of the problem has been put forward.</p
The impact of caregiver burden and associated factors on trait anger levels and anger expression styles in family caregivers of palliative care patients
No full textObjectives. This study aimed to examine the impact of perceived caregiver burden and associated factors on the anger levels and anger expression styles of family caregivers for patients receiving palliative care at home. Methods. This cross-sectional and exploratory correlational type study was conducted with 343 family caregivers. Data were collected face-to-face between March and September 2022 using a Caregiver and Care Recipient Information Form, the Burden Interview, and the Trait Anger and Anger Expression Scale. Results. There was a significant from very weak to weak correlation between the caregiver burden scores and trait anger, anger-in, anger-out, and anger control scores. The caregiver burden increased trait anger, anger-in, and anger-out while decreasing anger control. The caregiver burden, daily caregiving hours, presence of another dependent at home, presence of a separate room for the care recipient, income level, chronic illness of caregiver, duration of caregiving per month, and care recipient gender explained 17.2% of the total variation in anger control scores. Significance of results. The caregiver burden levels and anger expression styles of family caregivers vary depending on the characteristics of both the caregiver and the care recipient. Family members may experience an increase in perceived caregiver burden, which can lead to elevated levels of trait anger, suppression of anger, and reduced anger control. Healthcare professionals should monitor the family caregivers’ caregiver burden and anger levels. Family caregivers should be encouraged and given opportunities to express their feelings and thoughts about caregiving. Strategies aimed at reducing the caregiver burden and coping with feelings of anger should be planned for the family members of patients receiving palliative care at home
