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  Subjects -> SCIENCES: COMPREHENSIVE WORKS (Total: 374 journals)
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American Academic & Scholarly Research Journal
Number of Followers: 4  

  This is an Open Access Journal Open Access journal
ISSN (Print) 2162-321X - ISSN (Online) 2162-3228
Published by American Academic and Scholarly Research Center Homepage  [1 journal]
  • Impact of Self-Instructional Therapy on Adolescents’ Truancy in
           Secondary Schools in Oredo Local Government Area of Edo State

    • Authors: IMAFIDON Iniabasi Faith, IKUERO Bright
      Abstract: This study investigated the effect of self-instructional therapy in managing adolescents with truancy in secondary school students in Oredo local government area of Edo State using parental socioeconomic status as an intervening variable. To guide the study, three research questions were raised and formulated into two hypotheses which were tested at 0.05 level of significance. The study adopted a pre-test, post-test, non-equivalent control group and quasi experimental design. The population of the study was thirteen thousand and fifty-one (13,051) senior secondary school students from the fourteen (14) public secondary schools in Oredo local government area of Edo State. A sample size of two hundred (200) students made up of one hundred males and one hundred females were selected using balloting without replacement. The research instrument Students Level of Truancy Questionnaire (SLTQ) was used and a reliability coefficient of 0.64 was obtained using the Cronbach Alpha method. Data were analyzed using descriptive statistics of mean, standard deviation and t-test. The results revealed that students exposed to self - instructional therapy had a higher truancy mean score than those in the control group at posttest, students in the experimental group had a higher posttest truancy score than their pretest and parental socioeconomic status has no significant interaction on the truancy level among secondary school students in Oredo Local Government Area of Edo State. Based on the findings, it was therefore recommended among others, that counselling psychologists should train and retrain students to help them reduce truancy irrespective of their parental socioeconomic status, using self–instructional therapy.

      PubDate: 2022-11-30
      Issue No: Vol. 14 (2022)
       
  • Prediction of Machine Learning vs. Artificial Neural Network for
           Classifying a Heart Fail Dataset

    • Authors: Mohammed A. Faraj
      Abstract: We have A Three Dataset Heart Attack Analysis and Prediction and the other one is cardiovascular disease and the last one is Car price Prediction. We used These Dataset to make a machine Learning Algorithms and deep learning Model. The medical industry generates a tremendous quantity of data, known to as "big data," it includes hidden information or tendencies which can be used to make a decision. The large amount of data is used to make more accurate decisions than intuition. Exploratory Data Analysis (EDA) identifies errors, locates necessary data, confirms assumptions, and discovers the relationship between explanatory factors. In this context, EDA is defined as data analysis without conclusions or statistical modelling. Analytics is a crucial skill for each career since it predicts the future and discovers underlying patterns. In the recent past, data analytics was deemed a cost-effective technology, and it now plays a major role in healthcare, encompassing new study discoveries, emergency scenarios, and disease outbreaks. In healthcare, analytics improve healthcare by facilitating preventive care, and EDA is a key step in data. The risk factors for cardiovascular disease are discussed.
      PubDate: 2022-10-26
      Issue No: Vol. 14 (2022)
       
  • Perspective of Healthcare Workers about Digitization in the Healthcare
           Sector in Armed Forces Hospitals in Taif Region, Saudi Arabia

    • Authors: Adnan A. Alsuwat, Dr. Waleed M. Kattan
      Abstract: Aim: The purpose of the present study was to determine the impact of digitization in healthcare on health workers' perceptions in Armed Forces Hospital, Taif. Methodology: A quantitative descriptive design based on deductive approach was used in the study. 370 participants employed in Armed Force hospitals in Taif were recruited based on convenience sampling. A survey was distributed among participants to collect demographic data and data on digitization benefits, challenges, and status and perceptions of health workers. The collected responses were then entered into SPSS software for performing descriptive stats, ANOVA test and regression analysis to determine the relationship between research variables. Results: The demographic results showed more male participants (64.9%) than females (35%), with more participants having a Master's education. Results from the ANOVA test and regression analysis revealed a positive and significant correlation between digitization benefits (0.842), digitization challenges (0.838), and digitization status (0.898) with health workers' perceptions. Also, a 1% change in digitization benefits, challenges, and status can result in an 18% change in perceptions. Conclusion: Overall, the study found a significant and positive relationship impact of digitization of health on perceptions of health workers. Recommendation: It is suggested that future studies investigate the factors and strategies influencing the change of perceptions associated with the digitization of health.
      PubDate: 2022-10-24
      Issue No: Vol. 14 (2022)
       
 
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