Interactive media-based dance and art therapies as interventions for treating posttraumatic symptoms among school children with abduction experience.

OBJECTIVE: This study aimed to compare the effectiveness of interactive media-based dance and art therapies in reducing symptoms of posttraumatic stress disorder among school children in Nigeria who have experienced abduction. METHOD: The study utilised a quasi-experimental design using a sample of 470 school children in Nigeria aged 10-18. The participants were divided into three groups, namely control, dance and art therapy groups. While participants in the art therapy group took part in art therapy sessions, those in dance therapy took part in dance therapy sessions. Participants in the control group received no intervention at all. RESULTS: The result showed a drop in PTSD scores of participants in art and dance therapies at post-intervention and follow-up assessment after six months. However, those in the control group did not report a significant drop in their PTSD symptoms even after six months. Dance therapy was found to be more effective than art therapy. CONCLUSION: The conclusion of this study is that dance therapy is more effective even though both art and dance therapies assist children exposed to traumatic events. PRACTICAL IMPLICATIONS: This study has offered empirical evidence that could guide the planning and implementation of therapies aimed at assisting school children aged 10-18 to recover from traumatic experiences.

Communicating COVID-19 Vaccine Safety: Knowledge and Attitude Among Residents of South East, Nigeria.

BACKGROUND: The fight against the coronavirus disease (COVID-19), which has continued to threaten human existence globally, has led to the development of vaccines in order to control the rate of infection and death associated with the disease. Media messages on the COVID-19 vaccine are geared towards raising audience awareness and understanding of health risks, knowledge and attitudes about the vaccine safety. OBJECTIVE: The study examined the knowledge and attitude towards COVID-19 vaccine safety media messages amongst residents of South East, Nigeria. METHODS: A cross-sectional descriptive study was conducted among 399 respondents (18-47 years) in both urban and rural communities of South East, Nigeria from May 6th to July 4th, 2021. The survey was carried out using structured self administered questionnaire containing the respondents' demographics, knowledge and attitudes towards media messages regarding COVID-19 vaccine safety. The data were analysed using the SPSS version 26 software. Result was presented in frequencies, percentages and charts showing the interrelatedness of the variables examined. Regression ANOVA was used to test hypotheses on the extent to which level of exposure to COVID-19 media messages predict their knowledge and attitude towards COVID-19 vaccine safety at P<0.05 level of significance. RESULTS: Data indicate respondents are apprehensive of taking the COVID-19 vaccine. Approximately, 91% of respondents are between the ages of 18 and 27 years. Meanwhile, 26.1% of the respondents agreed that media messages on COVID-19 vaccine is very assuring and convincing as regards human safety; 42.4% disagreed on the safety of COVID-19 vaccine safety messages; 26.1% rated vaccine messages as moderate as regards human safety, while 5.5% rated the vaccine messages as poor. Knowledge of respondents regarding the safety of the vaccine was low and respondents' attitude was negative in South East, Nigeria. The implication is indicative of the failure of the main stream media in educating the general public on pertinent health issues relevant to them. CONCLUSION: Knowledge regarding media messages on COVID-19 vaccine safety is low. Messages on COVID-19 vaccine safety were not sufficient and convincing. Consequently, there is a negative attitude towards the vaccine. Hence, improving knowledge and adoptive attitude amongst respondents amidst COVID-19 is critical.

VGEA: an RNA viral assembly toolkit.

Next generation sequencing (NGS)-based studies have vastly increased our understanding of viral diversity. Viral sequence data obtained from NGS experiments are a rich source of information, these data can be used to study their epidemiology, evolution, transmission patterns, and can also inform drug and vaccine design. Viral genomes, however, represent a great challenge to bioinformatics due to their high mutation rate and forming quasispecies in the same infected host, bringing about the need to implement advanced bioinformatics tools to assemble consensus genomes well-representative of the viral population circulating in individual patients. Many tools have been developed to preprocess sequencing reads, carry-out de novo or reference-assisted assembly of viral genomes and assess the quality of the genomes obtained. Most of these tools however exist as standalone workflows and usually require huge computational resources. Here we present (Viral Genomes Easily Analyzed), a Snakemake workflow for analyzing RNA viral genomes. VGEA enables users to map sequencing reads to the human genome to remove human contaminants, split bam files into forward and reverse reads, carry out de novo assembly of forward and reverse reads to generate contigs, pre-process reads for quality and contamination, map reads to a reference tailored to the sample using corrected contigs supplemented by the user's choice of reference sequences and evaluate/compare genome assemblies. We designed a project with the aim of creating a flexible, easy-to-use and all-in-one pipeline from existing/stand-alone bioinformatics tools for viral genome analysis that can be deployed on a personal computer. VGEA was built on the Snakemake workflow management system and utilizes existing tools for each step: fastp (Chen et al., 2018) for read trimming and read-level quality control, BWA (Li & Durbin, 2009) for mapping sequencing reads to the human reference genome, SAMtools (Li et al., 2009) for extracting unmapped reads and also for splitting bam files into fastq files, IVA (Hunt et al., 2015) for de novo assembly to generate contigs, shiver (Wymant et al., 2018) to pre-process reads for quality and contamination, then map to a reference tailored to the sample using corrected contigs supplemented with the user's choice of existing reference sequences, SeqKit (Shen et al., 2016) for cleaning shiver assembly for QUAST, QUAST (Gurevich et al., 2013) to evaluate/assess the quality of genome assemblies and MultiQC (Ewels et al., 2016) for aggregation of the results from fastp, BWA and QUAST. Our pipeline was successfully tested and validated with SARS-CoV-2 (n = 20), HIV-1 (n = 20) and Lassa Virus (n = 20) datasets all of which have been made publicly available. VGEA is freely available on GitHub at: https://github.com/pauloluniyi/VGEA under the GNU General Public License.