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1.
PLoS Negl Trop Dis ; 18(5): e0012222, 2024 May.
Article in English | MEDLINE | ID: mdl-38805553

ABSTRACT

Dengue poses a significant public health concern worldwide. It is identified as a recent emerging infectious disease in Nepal. Understanding the situation and dynamics between knowledge, attitudes, and practices (KAP) related to dengue among students is crucial for effective prevention and control strategies. This study aimed to assess the KAP and their associated factors of dengue among non-health undergraduate students of Nepal to identify gaps and suggest appropriate interventions. A web-based cross-sectional study was conducted among 429 non-health undergraduate students at eleven Nepalese Universities, with 80% of participants from the four most prominent ones in the country. Self-administered online forms were administered via Google Forms platform predominantly through social media for data collection. Data was cleaned and then exported to IBM SPSS Statistics 20.0 for analysis. Demographic characteristics of respondents were described using descriptive statistics. Multivariate logistic regression was conducted to determine the association between individual characteristics and KAP. Pearson's correlation coefficient was used to determine the association between knowledge-attitude, attitude-practice, and knowledge-practice. Statistical significance was determined at the P-value < 0.05. Around half of the participants were female (50.3%). The majority of participants were between 22 to 37 years, unmarried, and belonged to the Brahmin/Chhetri ethnic group. This study demonstrated a significant gap in KAP. Only 15.2% of participants had good knowledge while 25.9% and 68.3% of participants exhibited good attitudes and practices respectively. Marital status (AOR = 3.32, CI: 1.32-8.34), third-year educational level (AOR = 3.59, CI:1.34-9.57), and fourth-year educational level (AOR = 4.93, CI:1.88-12.94) were significantly associated with knowledge regarding dengue. Age (AOR = 1.73, CI: 1.10-3.01) was significantly associated with preventive practice regarding dengue. None of the demographic or socio-economic characteristics of respondents was associated with attitude on dengue. The knowledge-attitude (rka = 0.01), knowledge-practice (rkp = 0.22), and attitude-practice (rap = 0.01) were positively correlated in this study.


Subject(s)
Dengue , Health Knowledge, Attitudes, Practice , Students , Humans , Dengue/prevention & control , Dengue/epidemiology , Female , Male , Nepal/epidemiology , Adult , Cross-Sectional Studies , Young Adult , Students/psychology , Surveys and Questionnaires , Universities , Adolescent
2.
Comput Intell Neurosci ; 2022: 8657313, 2022.
Article in English | MEDLINE | ID: mdl-35875768

ABSTRACT

The current work describes a blockchain-based optimization approach that mimics the psychological mental illness evaluation procedure and evaluates mental fitness. Combining lightweight models with blockchains can give a variety of benefits in the healthcare business. This study aims to offer an improved review and learning optimization technique (SPLBO) based on the social psychology theory to overcome the biogeography-based optimization (BBO) algorithm's shortcomings of low optimization accuracy and instability. It also creates high-accuracy solutions in recognized domains quickly. To retain student individuality, students can be divided into two groups: Human psychological variables are incorporated in the algorithm's improvement: in the "teaching" step of the original BBO algorithm; the "expectation effect" theory of social psychology is combined: "field-independent" and "field-dependent" cognitive styles. As a consequence, low-weight deep neural networks have been designed in such a manner that they require fewer resources for optimal design while also improving quality. A responsive student update component is also introduced to duplicate the effect of the environment on students' learning efficiency, increase the method's global search capabilities, and avoid the problem of falling into a local optimum in the first repetition.


Subject(s)
Blockchain , Mental Disorders , Algorithms , Humans , Learning , Mental Health
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