Journal of evaluation in clinical practice
-
Breastfeeding provides optimal nutrition for infants, and health literacy significantly influences breastfeeding rates. This study aimed to develop a tool to assess the breastfeeding health literacy levels of pregnant women. ⋯ The BFHLS developed for pregnant women is a valid and reliable tool. Higher scores on the scale indicate a greater level of breastfeeding health literacy in pregnant women. This scale can effectively be used to assess the breastfeeding health literacy levels of pregnant women.
-
Anemia due to malnutrition may develop as a result of iron, folate and vitamin B12 deficiencies. This situation poses a higher risk of morbidity and mortality in the geriatric population than in other age groups. Therefore, early diagnosis of anemia and early initiation of treatment is very important. This study aims to predict the diagnosis of anemia with using machine learning (ML) methods in geriatric patients followed in an outpatient clinic. ⋯ The study showed that anemia can be predicted with high accuracy in geriatric patients without hemogram data. Additionally, our geriatric data set was shared with researchers for future research. Thus, it has contributed to the literature by opening a new path for studies on subjects such as comparing classification performances with new methodologies or predicting different diseases in geriatric patients.
-
To evaluate the methodological and reporting quality of systematic reviews (SR) of randomized controlled trials on esthetics and reconstructive breast surgery. ⋯ Methodological and reposting quality of SR of randomized clinical trials on esthetic or reconstructive breast surgery is poor. Half of the authors referred to the use of valid guidance to plan and conduct their reviews and none of them referred the use of a guidance for reporting their results.
-
In clinical and research settings, the validity and reliability of measurement instruments are crucial for reliable results. Current methods for computing validation metrics like Aiken's coefficients are often complex and error-prone, highlighting the need for a standardized computational tool to simplify and enhance this process. ⋯ AikenCalc represents a significant improvement in the validation of measurement instruments by automating and simplifying the calculation of Aiken's coefficients through a Shiny web application. Additionally, it fills a knowledge gap, as there is currently no similar calculator available in the field of research.