Social Media Bashing Assessment Scale (SM-BASH): Development and Psychometric Testing.

The pervasive use of social media exposes individuals to negative experiences, including social media bashing, which profoundly impacts mental health, yet there is a conspicuous lack of a standardized scale to assess these experiences. This study assessed the psychometric properties of the Social Media Bashing Assessment Scale (SM-BASH). A total of 978 college students from the Philippines participated in the study.

Reassessing the Significance of Mycobacterium in Neglected Tropical Diseases: A Study Protocol in Nigeria.

Background: Neglected tropical diseases (NTDs) significantly impact the physical and mental well-being of affected individuals, particularly in Nigeria. This study aims to evaluate the effectiveness of integrating mental health services with self-care practices for individuals suffering from leprosy, Buruli ulcer (BU), and lymphatic filariasis (LF). The role of trained Healthcare Workers (HCWs) and NTD champions (NTD-Cs) will be explored to enhance health outcomes in this population.

THE NIGERIAN ATRIAL FIBRILLATION NATIONAL REGISTRY: RATIONALE, DESIGN AND EARLY FINDINGS.

Introduction/background: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia. The AF Atrial Fibrillation Registry, which commenced in June 2023, was designed to provide clinical epidemiological data on patients with AF in the country.

Objective(s): The objective is to describe the rationale, design, and early findings from the registry.

Enhancing transparency and fairness in automated credit decisions: an explainable novel hybrid machine learning approach.

This paper uses a generalised stacking method to introduce a novel hybrid model that combines a one-dimensional convolutional neural network 1DCNN with extreme gradient boosting XGBoost. We compared the predictive accuracies of the proposed hybrid architecture with three conventional algorithms-1DCNN, XGBoost and logistic regression (LR) using a dataset of over twenty thousand peer-to-peer (P2P) consumer credit observations. By leveraging the SHAP algorithm, the research provides a detailed analysis of feature importance, contributing to the model's predictions and offering insights into the overall and individual significance of different features.