Journal of evaluation in clinical practice
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This study aims to determine the effectiveness of the digital storytelling (DS) method in increasing human papilloma virus (HPV) awareness. ⋯ The DS method was effective in raising HPV awareness given to the intervention group. Health professionals and researchers can benefit from DS in providing health education and consultancy services such as HPV awareness.
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Parenting for individuals with visual impairments introduces unique challenges, requiring meticulous planning, attention and care in daily activities and child-rearing. ⋯ The findings highlight the importance of understanding and addressing the postpartum experiences of visually impaired mothers, advocating for more effective support programs tailored to their unique needs.
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Domestic violence against women is a pervasive issue globally, representing a severe violation of human rights and a significant public health concern. The hidden nature of such violence and its frequent underreporting make it a critical area for research. Recent advancements in artificial intelligence offer new avenues for identifying and predicting instances of domestic violence through machine learning (ML) algorithms. ⋯ The findings of our study demonstrate that ML algorithms have high accuracy rates in determining the frequency and risk factors of domestic violence against women, indicating that they can be used safely.
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This study was conducted to determine the effect of childhood adverse experiences on the risk of postpartum posttraumatic stress disorder (PP-PTSD) and postpartum depression (PPD). ⋯ The presence of ACE in mothers was found to increase the risk of developing PPD, both alone and when combined with traumatic birth experience. Therefore, we believe that screening for a history of ACE during pregnancy, investigating traumatic birth experiences in the postpartum period, closer follow-up of mothers with both ACE and traumatic birth experiences and increasing support systems will be beneficial in the prevention and early diagnosis of PPD.
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The previous studies demonstrated that the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system, a leading method for evaluating the certainty (quality) of scientific evidence (CoE), cannot reliably differentiate between various levels of CoE when the objective is to accurately assess the magnitude of the treatment effect. An estimated effect size is a function of multiple factors, including the true underlying treatment effect, biases, and other nonlinear factors that affect the estimate in different directions. We postulate that non-weighted, simple linear tallying can provide more accurate estimates of the probability of a true estimate of treatment effects as a function of CoE. ⋯ This study confirmed linear relationship between CoE and the probability of potentially 'true' estimates. We found that the probability of potentially "true" estimates decreases by about 20% for each drop in CoE (from about 80% for high to 55% for moderate to 35% to low and 15% to very low CoE).