Background: The revised NEO Personality Inventory (NEO-PI-3) includes 240 items corresponding to the Big Five personality traits (Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness to Experience) and subordinate dimensions (facets). It is suitable for use with adolescents and adults (12 years or older). The aim of the current study was to validate the Greek translation of the NEO-PI-3 in the general Greek population.
Material And Methods: The study sample included 734 subjects from the general Greek population of whom 59.4% were females and 40.6% males aged 40.80 ± 11.48. The NEO-PI-3 was translated into Greek and back-translated into English, and the accuracy of the translation was confirmed and established. The statistical analysis included descriptive statistics, confirmatory factorial analysis (CFA), the calculation of Cronbach's alpha, and the calculation of Pearson product-moment correlations. Sociodemographics groups were compared by ANOVA.
Results: Most facets had Cronbach's alpha above 0.60. Confirmatory factor analysis showed acceptable loading of the facets on their own hypothesized factors and very good estimations of Cronbach's alphas for the hypothesized factors, so it was partially supportive of the five-factor structure of the NEO-PI-3.The factors extracted with Procrustes rotation analysis can be considered reasonably homologous to the factors of the American normative sample. Correlations between dimensions were as expected and similar to those reported in the literature.
Discussion: The literature suggests that overall, the psychometric properties of NEO-PI-3 scales have been found to generalize across ages, cultures, and methods of measurement. In accord with this, the results of the current study confirm the reliability of the Greek translation and adaptation of the NEO-PI-3. The inventory has comparable psychometric properties in its Greek version in comparison to the original and other national translations, and it is suitable for clinical as well as research use.
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http://dx.doi.org/10.1186/s12991-014-0036-9 | DOI Listing |
Trials
December 2024
Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
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Mahidol University Health Technology Assessment (MUHTA) Graduate Program, Mahidol University, Bangkok, 10400, Thailand.
No cost-effectiveness information of preventive strategies for mother-to-child transmission (MTCT) of hepatitis B virus (HBV) has existed for policy decision making. This study aimed to compare the cost-effectiveness of alternative strategies to prevent MTCT of HBV in Vietnam. Cost-utility analysis using a hybrid decision-tree and Markov model were performed from healthcare system and societal perspectives.
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December 2024
Department of Nursing and Midwifery, College of Health, Wellbeing and Life Sciences, Sheffield Hallam University, Sheffield, UK.
Background: Despite progress made towards SDG 3, sub-Saharan Africa lags behind the rest of the world, accounting for over 50% of global neonatal deaths. The increased number of hospital births in the region has not reciprocated the reduction in neonatal mortality rates. Sick newborns face uncertain journeys from peripheral facilities to specialized centres arriving in suboptimal conditions, which impacts their outcomes, due partly to the scarcity of dedicated neonatal transport services.
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Department of Orthopedics, Guru Gobind Singh Medical College and Hospital, Faridkot, Punjab, 151203, India.
Generative Artificial Intelligence (AI), characterized by its ability to generate diverse forms of content including text, images, video and audio, has revolutionized many fields, including medical education. Generative AI leverages machine learning to create diverse content, enabling personalized learning, enhancing resource accessibility, and facilitating interactive case studies. This narrative review explores the integration of generative artificial intelligence (AI) into orthopedic education and training, highlighting its potential, current challenges, and future trajectory.
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