Colorectal Cancer (CRC) Awareness in Lebanon among the Young, Highly Educated Population

The number of individuals diagnosed with colorectal cancer (CRC) is rising, coinciding with increased efforts to raise awareness about preventive healthcare. Awareness of CRC is crucial for early detection and higher survival rates. Although progress has been made globally, significant disparities still exist, especially in low- and middle-income regions like the Arab world. Lebanon's increasing CRC rates demand urgent, targeted actions to raise awareness, promote screening, and ultimately decrease mortality. This study involved 1,229 volunteers. The questionnaire consisted of two parts: the first assessed participants' willingness to undergo early screening and their knowledge of CRC signs, symptoms, and risk factors (including colonoscopy and FIT tests). The second gathered socio-demographic information such as age, gender, education level, living area, and marital status. Data analysis was conducted using IBM SPSS software, version 26.0. Results showed that among those with a university education, 50.6% had never been screened, 13.7% had performed fecal testing, 16.4% had colonoscopies, and 19.3% had undergone both procedures. These figures are lower than the global rates of 38.4% for colonoscopies and 27.0% for fecal testing. Moreover, only 53.2% of respondents who were aware of CRC believed that risk could be reduced. Alarmingly, among highly educated individuals, 45.7% shared the negative attitude found in less educated groups. The findings suggest that effective CRC awareness campaigns should be incorporated into educational curricula, and CRC screening awareness initiatives should be made mandatory in schools. Healthcare providers should be encouraged to recommend FIT as a primary screening method, especially for asymptomatic individuals aged 45 and older or those at moderate risk. Community health centers, NGOs, and the Ministry of Public Health play vital roles in distributing FIT kits, especially in underserved or rural areas

Technical Analysis: Exploring MACD in the Lebanese Stock Market

The stock markets have shown a great growth in the financial world that required traders to deal with many quantitative methods to analyze markets in order to predict commodities’ future prices. This study assesses the effect of technical analysis on the Lebanese stock markets by using a tool known as the Moving Average Convergence/Divergence (MACD) oscillator that explores how MACD can be utilized to optimize profits in the Lebanese stock exchange, during the trading process. The study is performed on closing prices of shares of six Lebanese banks and a real estate company, over a time period extending from the beginning of the year 2004 till the end of the year 2014. Results are meant to indicate whether MACD is able to optimize profits and forecast the Lebanese stock prices. It is concluded that the application of MACD in the decision making process for investing in the Lebanese stock market does not significantly contribute to the maximization of profitability on investments

An Assessment of the University Usage of Social Media Platforms: Case from Lebanon—Theoretical Foundations—Part 1

This paper, part of two, aims to assess how a selection of Lebanese Universities utilizes social media platforms to attract potential student candidates. Social Media is considered a significant recruitment tool universities use to attract high school graduates from the millennium digital generation. Different universities have dealt differently with social media, so capturing recorded activity is essential to assess such efforts and pinpoint gaps to justify student recruitment investments by universities. This study uses a mix of quantitative and qualitative methods. A descriptive comparative analysis is carried out based on collected data from the different university social media platforms to help categorize selected universities in their efforts, successes, and gaps. However, this paper, the first part of two, represents the theoretical foundations needed for the study. Paper part two (2) will follow to illustrate the numerical and graphical analysis. Results show a lack of motivation schemes to attract potential candidates and encourage them to interact with such platforms. Moreover, universities lack specialized digital marketing staff to produce the appropriate content and design marketing strategies that are attractive, interactive, and with high response rates to inquiries

Factors that influence the attitude of young people to participate in crowdfunding campaigns

This paper highlights the factors that influence young people’s attitude to participate in crowdfunding campaigns, and to what extent such factors impact their investment intentions. A quantitative approach is employed using a survey to gather information from Al Maaref University students about the determinants influencing their intentions to invest in crowdfunding and to explain how such factors affect their attitudes towards crowdfunding decisions. This study found that emotions and attitudes as well as attitudes and PBC are statistically and positively related. Moreover, personality types ‘Agreeableness (A) and Neuroticism (N)’ have a positive impact on PBC (with p ˂ 10%), and subjective norms (SN) have a direct influence on engagement intention (EI) (p ˂ 5%). PBC has a positive impact on EI (p ˂ 5%), and risk preferences have a positive impact on EI (with p ˂ 10%). In addition, results show that personality types do not have a positive impact on SN, and personality types Extraversion (E), Conscientiousness (C), and Openness (O), do not have a positive impact on PBC. Subjective norms do not have a positive impact on attitudes (p ˃ 5%). Moreover, PBC does not have a direct influence on SN or behavior, risk preferences do not have a positive impact on EI (p ˃ 5%), and demographic factors do not have a positive impact on EI. The findings of the study shall promote the comprehension of the influences that motivate young entrepreneurs to participate in crowdfunding campaigns. This paper’s findings benefit investors, fintech decision-makers, and policymakers

Neural Network Implementation for CRC Awareness Prediction

Artificial Intelligence (AI) is prevalent, driven by the resurgence of machine learning (ML) and advancements in data-driven applications, which have created new opportunities to surpass traditional statistical limits in health analytics. This study develops and assesses a deep artificial neural network (ANN) to predict public awareness of Colorectal Cancer (CRC) using six demographic and socioeconomic factors: age, gender, marital status, educational level, work status, and place of residence. Primary data were collected through a survey administered to a sample of 1,229 Lebanese individuals.We systematically describe the data preprocessing steps, including handling missing values, encoding categorical variables, and scaling features. We specify the model architecture, which includes input, output, and one or more hidden layers, along with training optimization methods such as class weighting, early stopping, and learning rate scheduling. The model is evaluated using thorough cross-validation and held-out testing, with metrics like discrimination and calibration assessments, including accuracy percentages and confidence scores. An explainability technique, including feature importance analysis, is employed to enhance transparency. The proposed network demonstrates reliable binary classification performance while emphasizing interpretability, deployment readiness, and the reproducible integration of machine learning into healthcare analytics

An Assessment of the University Usage of Social Media Platforms: Case from Lebanon—Analytics—Part 2

This paper, the second part of two, aims to provide results and findings to support the main objective of the research, i.e., to assess how a selection of Lebanese Universities utilizes social media platforms to attract potential student candidates. Social Media in the last decade has become a significant recruitment media adopted by universities around the globe, including Lebanon, to attract and effectively recruit millennial high school graduates who are digitally proficient and smart. Six universities were involved, so capturing recorded activity is essential to assess such efforts and pinpoint gaps that must be addressed to justify student recruitment investments by universities. This study is based on a mixed approach though with a concentration on the quantitative, deductive, and descriptive approaches capitalizing on collected data from the different university social media platforms and performing the required analysis to help categorize selected universities in their efforts, successes, and gaps. This paper shows the numerical, graphical, and discussion analyses of the results. Results confirm there is a lack of motivation schemes to attract potential candidates and encourage them to interact with such platforms. Moreover, universities lack specialized digital marketing staff to produce the appropriate content and design marketing strategies that are attractive, interactive, and with high response rates to inquiries

Forensic Analysis of WhatsApp SQLite Databases on the Unrooted Android Phones

WhatsApp is the most popular instant messaging mobile application all over the world. Originally designed for simple and fast communication, however, its privacy features, such as end-to-end encryption, eased private and unobserved communication for criminals aiming to commit illegal acts. In this paper, a forensic analysis of the artefacts left by the encrypted WhatsApp SQLite databases on unrooted Android devices is presented. In order to provide a complete interpretation of the artefacts, a set of controlled experiments to generate these artefacts were performed. Once generated, their storage location and database structure on the device were identified. Since the data is stored in an encrypted SQLite database, its decryption is first discussed. Then, the methods of analyzing the artefacts are revealed, aiming to understand how they can be correlated to cover all the possible evidence. In the results obtained, it is shown how to reconstruct the list of contacts, the history of exchanged textual and non-textual messages, as well as the details of their contents. Furthermore, this paper shows how to determine the properties of both the broadcast and the group communications in which the user has been involved, as well as how to reconstruct the logs of the voice and video calls. Doi: 10.28991/HIJ-2022-03-02-06 Full Text: PD

Students\u27 Perceptions of Student Evaluation of Teaching (SET) Process

Researchers have mixed views about Student Evaluation of Teaching (SET) as means to evaluate teaching where some agreed and others viewed SET as being biased. This study aims to measure students’ perceptions of the effectiveness and appropriateness of the evaluation process in Lebanon. A survey questionnaire was administered to students from five Lebanese universities. Findings revealed that students were positive and perceived the evaluation process as effective and appropriate to evaluate teaching. Students identified students’ perceptions, instructors’ behavior, and course characteristics as variables that may impact the process. Results and implications were discussed for future research

A Descriptive Analysis of Job Satisfaction among Faculty Members: Case of Private Vocational and Technical Education Institutions, Baabda, Mount Lebanon, Lebanon

The study aimed to assess Job Satisfaction (JS) among teaching staff in private vocational and technical education institutions in Mount Lebanon, Lebanon. The study is descriptive and analytic, using a sample of 200 teachers from 13 schools and institutes chosen according to the coordinated random method. A questionnaire created and validated by Warr, Cook, and Wall is adopted to measure job satisfaction. This questionnaire includes personal information like job status, educational level, number of years of work, monthly income, age, gender, and social status. Using a seven-level Likert scale, it also contains 15 items to measure various dimensions of job satisfaction (internal and external factors). Results show a low overall mean of 4.69 out of 7 with a standard deviation of 1.15 for job satisfaction, based on data analysis using the SPSS program. Also, the majority of respondents are not satisfied with the wage received (the overall mean of job satisfaction=3.83, with a standard deviation of 2.00); there is a low level of JS among teachers concerning the degree of job security (mean=4.13 with a standard deviation of 1.91); there are no statistically significant differences in JS among teachers due to demographics. Capitalizing on the results, recommendations are made