366 research outputs found

    Body appreciation around the world: Measurement invariance of the Body Appreciation Scale-2 (BAS-2) across 65 nations, 40 languages, gender identities, and age

    Get PDF
    The Body Appreciation Scale-2 (BAS-2) is a widely used measure of a core facet of the positive body image construct. However, extant research concerning measurement invariance of the BAS-2 across a large number of nations remains limited. Here, we utilised the Body Image in Nature (BINS) dataset - with data collected between 2020 and 2022 - to assess measurement invariance of the BAS-2 across 65 nations, 40 languages, gender identities, and age groups. Multi-group confirmatory factor analysis indicated that full scalar invariance was upheld across all nations, languages, gender identities, and age groups, suggesting that the unidimensional BAS-2 model has widespread applicability. There were large differences across nations and languages in latent body appreciation, while differences across gender identities and age groups were negligible-to-small. Additionally, greater body appreciation was significantly associated with higher life satisfaction, being single (versus being married or in a committed relationship), and greater rurality (versus urbanicity). Across a subset of nations where nation-level data were available, greater body appreciation was also significantly associated with greater cultural distance from the United States and greater relative income inequality. These findings suggest that the BAS-2 likely captures a near-universal conceptualisation of the body appreciation construct, which should facilitate further cross-cultural research

    Exploring the cost-effectiveness of high versus low perioperative fraction of inspired oxygen in the prevention of surgical site infections among abdominal surgery patients in three low- and middle-income countries

    No full text
    Background: This study assessed the potential cost-effectiveness of high (80–100%) vs low (21–35%) fraction of inspired oxygen (FiO2) at preventing surgical site infections (SSIs) after abdominal surgery in Nigeria, India, and South Africa. Methods: Decision-analytic models were constructed using best available evidence sourced from unbundled data of an ongoing pilot trial assessing the effectiveness of high FiO2, published literature, and a cost survey in Nigeria, India, and South Africa. Effectiveness was measured as percentage of SSIs at 30 days after surgery, a healthcare perspective was adopted, and costs were reported in US dollars ().Results:HighFiO2maybecosteffective(cheaperandeffective).InNigeria,theaveragecostforhighFiO2was). Results: High FiO2 may be cost-effective (cheaper and effective). In Nigeria, the average cost for high FiO2 was 216 compared with 222forlowFiO2leadingtoa 222 for low FiO2 leading to a −6 (95% confidence interval [CI]: −13to 13 to −1) difference in costs. In India, the average cost for high FiO2 was 184comparedwith184 compared with 195 for low FiO2 leading to a −11(9511 (95% CI: −15 to −6)differenceincosts.InSouthAfrica,theaveragecostforhighFiO2was6) difference in costs. In South Africa, the average cost for high FiO2 was 1164 compared with 1257forlowFiO2leadingtoa 1257 for low FiO2 leading to a −93 (95% CI: −132to 132 to −65) difference in costs. The high FiO2 arm had few SSIs, 7.33% compared with 8.38% for low FiO2, leading to a −1.05 (95% CI: −1.14 to −0.90) percentage point reduction in SSIs. Conclusion: High FiO2 could be cost-effective at preventing SSIs in the three countries but further data from large clinical trials are required to confirm this

    Generating Minimal Models of H1N1 NS1 Gene Sequences Using Alignment-Based and Alignment-Free Algorithms

    No full text
    For virus classification and tracing, one idea is to generate minimal models from the gene sequences of each virus group for comparative analysis within and between classes, as well as classification and tracing of new sequences. The starting point of defining a minimal model for a group of gene sequences is to find their longest common sequence (LCS), but this is a non-deterministic polynomial-time hard (NP-hard) problem. Therefore, we applied some heuristic approaches of finding LCS, as well as some of the newer methods of treating gene sequences, including multiple sequence alignment (MSA) and k-mer natural vector (NV) encoding. To evaluate our algorithms, a five-fold cross validation classification scheme on a dataset of H1N1 virus non-structural protein 1 (NS1) gene was analyzed. The results indicate that the MSA-based algorithm has the best performance measured by classification accuracy, while the NV-based algorithm exhibits advantages in the time complexity of generating minimal models

    Classification of Protein Sequences by a Novel Alignment-Free Method on Bacterial and Virus Families

    No full text
    The classification of protein sequences provides valuable insights into bioinformatics. Most existing methods are based on sequence alignment algorithms, which become time-consuming as the size of the database increases. Therefore, there is a need to develop an improved method for effectively classifying protein sequences. In this paper, we propose a novel accumulated natural vector method to cluster protein sequences at a lower time cost without reducing accuracy. Our method projects each protein sequence as a point in a 250-dimensional space according to its amino acid distribution. Thus, the biological distance between any two proteins can be easily measured by the Euclidean distance between the corresponding points in the 250-dimensional space. The convex hull analysis and classification perform robustly on virus and bacteria datasets, effectively verifying our method

    Use of Telemedicine for Post-discharge Assessment of the Surgical Wound: International Cohort Study, and Systematic Review with Meta-analysis