Demographic Characteristics, Level of Drug Use, and Self-Esteem Among Female Students in Kaduna, Nigeria

Starting the early 1990s, the prevalence of nonmedical prescription drug use in Nigeria has been increased, especially among college students. Potential adverse effects such as poor academic performance and low self-esteem are known, but it is not understood whether demographic factors, level of drug use, and self-esteem are related to drug use for female college students. The purpose of this quantitative correlational study of a cross-sectional nature was to determine if there were predictive relationships between demographics (age, socioeconomic level, educational level, and history of mental illness), level of drug use (as measured by the Drug Abuse Screening Test [DAST], and self-esteem (as measured by the Modified Rosenberg Self-Esteem Scale [MRSES] in female students in Kaduna in Nigeria. The theoretical framework was provided by the psychology of self-esteem theory, social learning theory, and identity theory. Primary data from a purposeful convenience and snowball sample of 300 female undergraduates (age 18-25) enrolled in three colleges was used to analyze data. The results of the multiple linear regression indicated that history of mental illness (p = .012) and DAST score (p = .000) were related to the MRSES score at statistically significant levels. Because the independent variables (age, socioeconomic levels, and educational level) were not related to the dependent variable (self-esteem) at a statistically significant level, the null hypothesis was not rejected. The results from this study could provide justification for college administrators to plan appropriate social, health, educational programs, and policies that could assist college students at risk of nonmedical prescription drug use and guide students in making right health choices and decisions

Spartan Daily, January 9, 1951

Volume 39, Issue 61https://scholarworks.sjsu.edu/spartandaily/11483/thumbnail.jp

Genre and Domain Dependencies in Sentiment Analysis

Genre and domain influence an author\''s style of writing and therefore a text\''s characteristics. Natural language processing is prone to such variations in textual characteristics: it is said to be genre and domain dependent. This thesis investigates genre and domain dependencies in sentiment analysis. Its goal is to support the development of robust sentiment analysis approaches that work well and in a predictable manner under different conditions, i.e. for different genres and domains. Initially, we show that a prototypical approach to sentiment analysis -- viz. a supervised machine learning model based on word n-gram features -- performs differently on gold standards that originate from differing genres and domains, but performs similarly on gold standards that originate from resembling genres and domains. We show that these gold standards differ in certain textual characteristics, viz. their domain complexity. We find a strong linear relation between our approach\''s accuracy on a particular gold standard and its domain complexity, which we then use to estimate our approach\''s accuracy. Subsequently, we use certain textual characteristics -- viz. domain complexity, domain similarity, and readability -- in a variety of applications. Domain complexity and domain similarity measures are used to determine parameter settings in two tasks. Domain complexity guides us in model selection for in-domain polarity classification, viz. in decisions regarding word n-gram model order and word n-gram feature selection. Domain complexity and domain similarity guide us in domain adaptation. We propose a novel domain adaptation scheme and apply it to cross-domain polarity classification in semi- and unsupervised domain adaptation scenarios. Readability is used for feature engineering. We propose to adopt readability gradings, readability indicators as well as word and syntax distributions as features for subjectivity classification. Moreover, we generalize a framework for modeling and representing negation in machine learning-based sentiment analysis. This framework is applied to in-domain and cross-domain polarity classification. We investigate the relation between implicit and explicit negation modeling, the influence of negation scope detection methods, and the efficiency of the framework in different domains. Finally, we carry out a case study in which we transfer the core methods of our thesis -- viz. domain complexity-based accuracy estimation, domain complexity-based model selection, and negation modeling -- to a gold standard that originates from a genre and domain hitherto not used in this thesis

CWU Faculty Senate Minutes - 03/05/1975

These are the official Central Washington University Faculty Senate Minutes for the 03/05/1975 regular meeting

Aggression in Dark Personalities: The Role of Self-Esteem

The relationship between self-esteem and the Dark Triad traits has not been subject to extensive, systematic empirical investigation. In particular, there is a dearth of research on the role of self-esteem, the Dark Triad traits, and aggression. The purpose of the present study was to investigate the associations between both explicit and implicit measures of self-esteem and aggression, and to examine these associations as they relate to the Dark Triad traits. Additionally, the present study set out to examine the test-retest reliability of the widely used Implicit Association Test (IAT) paradigm, as well as the effects of mood primers on the results of the IAT. The results showed that a) narcissism was negatively correlated with explicit self-esteem and none of the Dark Triad traits were associated with implicit self-esteem; b) individuals with discrepant high self-esteem did not score higher on trait aggression than other types of self-esteem; c) explicit self-esteem moderated the association between each of the Dark Triad traits and explicit aggression; and d) implicit self-esteem only moderated the association between narcissism and implicit aggression. Due to the pandemic-related cessation of data collection, we were unable to adequately test the test-retest reliability of the IAT paradigm or its susceptibility to priming effects. Overall, self-esteem appears to play a role in the relationship between Dark Triad traits and aggression, and as such, offers a multitude of implications for future research and the current theoretical understanding of aggressive behaviour. Furthermore, gender seems to be an important consideration for the study of the Dark Triad traits, as well as pathways to delinquency

ACUTA eNews September 1984, Vol. 13, No. 9

In This Issue PRESIDENT\u27S MESSAGE BOSTON CONFERENCE MULTIPLE POSSIBILITIES FOR MULTI-POINT NETWORK

The Effect of Tempo Variances on Listener\u27s Preference

A thesis presented to the faculty of the College of Humanities at Morehead State University In partial fulfillment of the requirements for the Degree of Master of Arts in Communications by Stephen D. Boyd on December 3, 1999

Annual Report: 1960

Statistics of conditions treated at St. Cloud Hospital in 196

Nurse Knowledge Sharing Portal

This study will be focusing on the Nurse Knowledge Sharing Portal. The purpose of this project is to use Knowledge Management in order to have good information sharing system among the medical staff. The project will be based on Knowledge management and web based development. By doing so, it will support and improve distributed information sharing among hospital staff especially nurses. Nurses can easily find the information of technique, procedure and way how to deal with disease by using this system it implement this project, and Joomla is used as the e-learntngmodel. Besides, the information about new disease technique, procedure and way how to deal with it is provided in this system and will represent in informational data. The scope of study of this proposed project is within nurses' community itself. The target users of course are among nurses as the designed of this sharing system will be within hospital local area network. To gather information for this project 1have do some research according to the problem that faced by medical staff. These are some methods, which I use to gather the information such as survey form, journal, health magazine, and also internet. Methodology to be used in executingthis project will be incremental and prototyping life cycle model where the development of the site will be based on prototype of component or module per module. To accomplish this project I will develop an online sharing work space like blogs, and forum. Information Sharing System will help medical staff especially nurses to efficiently do their job while doing it safely