Impact Of Dropout Research Articles

대학상담센터 내담자의 조기종결 경험에 대한 질적 연구

This study aimed to find out what factors led to the dropout of college counseling center clients and the impact of dropout on the clients. In-depth interviews were conducted with 11 clients who experienced dropout before the 10th session at the university counseling center, and the data were analyzed using Braun and Clarke's Thematic Analysis method. Four themes, 10 sub-themes, and 26 units of meaning emerged from the data analysis. The themes were 'distrust and anxiety about counseling', 'inappropriate behavior of counselors', 'low counseling competence of counselors', and 'negative perceptions of counseling'. In the dropout experience of university counseling center clients, inappropriate counselor behavior and low counselor competence were found to be the main factors that led to dropout. In addition, the consequences of dropout include rejection of counseling and negative perception changes. The significance of this study is that it discussed the problems and development plans for college counseling centers through the experiences of dropout of college counseling center clients, and presented basic data on them. This will provide a basis for the development of effective counseling and training in the practice of college counseling. Finally, limitations of this study and suggestions for further research were discussed.

Who will drop out of voluntary social health insurance? Evidence from the New Cooperative Medical Scheme in China.

Although public voluntary health insurance (VHI) has been adopted in many low- and middle-income countries to improve access to care for the population, a common issue with VHI is its high dropout rate. Using the New Cooperative Medical Scheme (NCMS)—a public VHI in China—as a case study, this article employs a fixed-effects negative binomial regression model combining the difference-in-difference-in-differences approach and multivariate distance matching to examine the factors associated with dropping out and the impact of dropout on outpatient care utilization among middle-aged and older people in rural China. Drawing data from the China Health and Retirement Longitudinal Study, our results showed that healthy people, vulnerable people and people who use less healthcare tended to drop out. Dropout had a significant negative impact on outpatient care utilization, especially for those with worse health statuses and those living in poorer provinces. We also found that the impact of dropout on outpatient utilization was more pronounced at secondary and tertiary hospitals than at primary care clinics. We urge policymakers to rethink the design of the NCMS by waiving premiums for the most vulnerable people.

PENERIMAAN DIRI PADA MAHASISWA DROP OUT

This study aims to provide an overview of self-acceptance to students who have dropped out, the factors that influence and impact of drop out. Subjects in this study were students or students who have dropped out of college with a variety of problems. The number of respondents in this study were 13 students. The research data in the form of a verbatim transcript were analyzed and divided into the categories that have been there, then spelled out in detail for the conclusion of the research results. Results of this study illustrate, picture yourself admission of students who have dropped out with characteristics that have the confidence, ability, confident, responsible, and do not blame him. The results also showed that while the factors that affect the self-acceptance that there are two external factors, namely social environmental factors and internal factors are feelings, thoughts and views of the self, and the impact of self-acceptance is divided into two positive impacts and effects negative. The impact experienced after drop out of feeling embarrassed and disappointed. Society is expected to understand and know what is felt by students who have dropped out and know how to react

Comparison of Modern Methods for Analyzing Repeated Measures Data With Missing Values

Missing data are a pervasive problem in many psychological applications in the real world. In this article we study the impact of dropout on the operational characteristics of several approaches that can be easily implemented with commercially available software. These approaches include the covariance pattern model based on an unstructured covariance matrix (CPM-U) and the true covariance matrix (CPM-T), multiple imputation-based generalized estimating equations (MI-GEE), and weighted generalized estimating equations (WGEE). Under the missing at random mechanism, the MI-GEE approach was always robust. The CPM-T and CPM-U methods were also able to control the error rates provided that certain minimum sample size requirements were met, whereas the WGEE was more prone to inflated error rates. In contrast, under the missing not at random mechanism, all evaluated approaches were generally invalid. Our results also indicate that the CPM methods were more powerful than the MI-GEE and WGEE methods and their superiority was often substantial. Furthermore, we note that little or no power was sacrificed by using CPM-U method in place of CPM-T, although both methods have less power in situations where some participants have incomplete data. Some aspects of the CPM-U and MI-GEE methods are illustrated using real data from 2 previously published data sets. The first data set comes from a randomized study of AIDS patients with advanced immune suppression, the second from a cohort of patients with schizotypal personality disorder enrolled in a prevention program for psychosis.

Using State Child Labor Laws to Identify the Causal Effect of Youth Employment on Deviant Behavior and Academic Achievement

On the basis of prior research findings that employed youth, and especially intensively employed youth, have higher rates of delinquent behavior and lower academic achievement, scholars have called for limits on the maximum number of hours per week that teenagers are allowed to work. We use the National Longitudinal Survey of Youth 1997 to assess the claim that employment and work hours are causally related to adolescent problem behavior. We utilize a change model with age-graded child labor laws governing the number of hours per week allowed during the school year as instrumental variables. We find that these work laws lead to additional number of hours worked by youth, which then lead to increased high school dropout but decreased delinquency. Although counterintuitive, this result is consistent with existing evidence about the effect of employment on crime for adults and the impact of dropout on youth crime.

Reply to Possible Impact of Dropout in a Study ofHigh-Dose Olanzapine and Prolactin Levels

Reply to Possible Impact of Dropout in a Study ofHigh-Dose Olanzapine and Prolactin Levels

An assessment of non-randomized medical treatment of long-term schizophrenia relapse using bivariate binary-response transition models.

The analyses of observational longitudinal studies involving concurrent changes in treatment and medical conditions present difficulties because of the multitude of directions of potential relationships: past medication influences current symptoms; past symptoms influence current medication; and current medication is associated with current symptoms. In the context of a long-term study of non-randomized pharmacological treatment of schizophrenic relapse, we present an analysis of bivariate discrete-time transitional data with binary responses in an attempt to understand the transitional and concurrent relationships between schizophrenia relapse and medication use. A naive analysis does not show any association between previous medication and current relapse. However, we provide evidence suggesting that current treatment may impact current relapse for those who have previously taken medication, but not for those who haven't taken medication in the past. When univariate models are specified to assess these associations, the bivariate nature of the problem requires a choice of which response, relapse or medication, should be the dependent variable. In this case, the choice of relapse or medication as a dependent variable does matter. Hence, our results derive from models where both relapse and medication are treated as dependent variables. Specifically, we specify a bivariate log odds ratio for current relapse and current medication use and a separate univariate logit component for each of these outcomes. Each of these components contains transitional associations with previous relapse and medication. Such models represent extensions of univariate transitional association models (e.g. Diggle et al. (1994)) and correspond to bivariate transitional models (e.g. Zeger and Liang (1991)). We incorporate changes in transitional associations into the full-data parametric model for final inference, and investigate if these temporal changes are due to learning effects or the impact of drop-out. We also perform residual analyses and sensitivity analyses in the context of missing data patterns.