A large proportion (28% up to 75%) of the treatments in youth mental health care results in premature termination (dropout). It is important to gain knowledge of the determinants of dropout because ...it can have very severe consequences. The aim of our meta-analytic review was to provide an overview of findings from empirical studies on this subject. We structured the often contradicting results from two perspectives. First, we compared studies with efficacy and effectiveness designs. Second, we compared studies which used a dropout definition based on the opinion of therapists, with those that took the number of predetermined completed sessions as a criterion. Third, we studied three groups of predictors, i.e., pre-treatment child variables, pre-treatment family or parent variables, and treatment and therapist variables or treatment participation barriers.
The meta-analytic review showed that dropout percentages were strongly influenced by study design: Percentages were lower in efficacy than in effectiveness studies. Within effectiveness studies, the dropout percentages were lower when the therapist's opinion was used rather than when the number of sessions was used as a criterion. In efficacy studies on the contrary, the dropout percentages were similar for studies using the first or the second criterion. With respect to dropout predictors, results were less clear. Some of the dropout predictors were influenced by study design or dropout definition, but for most predictors this influence could not be analyzed because they were not studied in all groups of studies or because the effect sizes were small or non-significant. Treatment and therapist variables or experienced treatment participation barriers were overall stronger dropout predictors than the pre-treatment child variables and pre-treatment family or parent variables, although some strong predictive pre-treatment variables emerged as well.
•Dropout percentages were higher in effectiveness than in efficacy studies.•Dropout definition influenced dropout percentages only in effectiveness studies.•Some dropout predictors were influenced by study design or dropout definition.•Treatment/therapist variables were strong overall dropout predictors.•Pre-treatment child/family variables were overall less strong dropout predictors.
Background: Despite the established efficacy of psychological therapies for post-traumatic stress disorder (PTSD) there has been little systematic exploration of dropout rates.
Objective: To ...ascertain rates of dropout across different modalities of psychological therapy for PTSD and to explore potential sources of heterogeneity.
Method: A systematic review of dropout rates from randomized controlled trials (RCTs) of psychological therapies was conducted. The pooled rate of dropout from psychological therapies was estimated and reasons for heterogeneity explored using meta-regression.
Results:: The pooled rate of dropout from RCTs of psychological therapies for PTSD was 16% (95% CI 14-18%). There was evidence of substantial heterogeneity across studies. We found evidence that psychological therapies with a trauma-focus were significantly associated with greater dropout. There was no evidence of greater dropout from therapies delivered in a group format; from studies that recruited participants from clinical services rather than via advertisements; that included only military personnel/veterans; that were limited to participants traumatized by sexual traumas; that included a higher proportion of female participants; or from studies with a lower proportion of participants who were university educated.
Conclusions: Dropout rates from recommended psychological therapies for PTSD are high and this appears to be particularly true of interventions with a trauma focus. There is a need to further explore the reasons for dropout and to look at ways of increasing treatment retention.
This paper combines a theoretical-based model with a data-driven approach to develop an Early Warning System that detects students who are more likely to dropout. The model uses innovative multilevel ...statistical and machine learning methods. The paper demonstrates the validity of the approach by applying it to administrative data from a leading Italian university.
Higher education dropout rates in Colombia are the second highest in Latin-America. Almost 50% of students who start an undergraduate program in Colombia drop out. In this paper, we present a ...systematic literature review that surveys publications related to university dropout in Colombia between 2000 and 2021. This review followed the Kitchenham guidelines. Databases such as Publindex, Scielo, Wos, Scopus were reviewed. To create cause and solution taxonomies, we identified causes and/or solutions reported by researchers in each revised article. Each cause/solution was then grouped using the university dropout taxonomy proposed by Castaño. 107 papers, 66 different causes, and 62 proposed solutions related to university dropout were reported in the papers analyzed. The results suggest there is an increasing interest in understanding (i) the undergraduate dropout phenomenon, and (ii) the use of data science to solve the problem. These studies also evince a lack of integration between stakeholders for developing crosscutting solutions. The information related to some of the reported solutions is not sufficiently developed to enable a better classification, or they lacked information on implementation, results, or impact. This makes it difficult to make progress with designing new strategies based on previous studies.
Using a model of student dropout with only two possible outcomes– "still in school" or "dropout" –hides the complex reasons that students leave high school. We offer a model with three outcomes: in ...school, pushed out or pulled out. Using data from the Educational Longitudinal Survey, we find that for black students, differences in SES explain higher likelihoods of being either pushed or pulled out as compared to white students, but Latino students remain more likely to be pulled out even after we control for SES. We also find that SES moderates the relationship between race/gender and being pushed out, and that higher levels of SES may be detrimental to students of color in the context of high poverty schools.
Studies of student risk of school dropout have shown that present predictors of at-risk status do not accurately identify a large percentage of students who eventually drop out. Through the analysis ...of the entire Grade 1-12 longitudinal cohort-based grading histories of the class of 2006 for two school districts in the United States, the author extends past longitudinal conceptions of dropout to a longitudinal risk perspective, using survival analysis, life tables, and discrete-time hazard modeling to appropriately account for student graduation, transfer, or dropout. The risk of dropout began in Grade 7, with the most hazardous years at Grades 8 and 11. A novel calculation of teacher-assigned grades, noncumulative GPA, is identified as a strong predictor of student dropout.
Education is a key determinant of future employment and income prospects of young people. Poor mental health is common among young people and is related to risk of dropping out of school (dropout). ...Educational level and gender might play a role in the association, which remains to be studied.
Mental health was measured in 3146 Danish inhabitants aged 16-29 years using the 12-Item Short-Form Health Survey and examined across genders and educational levels. For students, educational level at baseline was used; for young people who were not enrolled in school at baseline (non-students), the highest achieved educational level was used. The risk of dropout in students was investigated in administrative registers over a 4.8-year period (1(st) March 2010-31(th) December 2014). Odds ratios (OR) and 95 % confidence intervals (CI) were calculated for mental health and in relation to dropout in logistic regression models, adjusting for age, gender, educational level, parental education, parental income and ethnicity.
Poor mental health was present in 24 % (n = 753) of the participants, 29 % (n = 468) in females and 19 % (n = 285) in males (p < 0.0001). The prevalence differed from 19 to 39 % across educational levels (p < 0.0001). Females had a statistically significantly higher adjusted risk of poor mental health than males (OR = 1.8, CI = 1.5-2.2). Among the students the lowest risk was found at the elementary level (OR = 1.3, CI = 0.8-2.3), while students in higher education had a statistically significantly higher risk (OR = 1.9, CI = 1.2-2.9). The lowest-educated non-students had the highest OR of poor mental health (OR = 3.3, CI = 2.1-5.4). Dropout occurred in 8 % (n = 124) of the students. Poor mental health was associated to dropout in vocational (OR = 1.8, CI = 1.0-3.2) and higher education (OR = 2.0, CI = 1.0-4.2). For males in higher education, poor mental health was a predictor of dropout (OR = 5.2, CI = 1.6-17.3), which was not seen females in higher education (OR = 1.2, CI = 0.5-3.1).
Poor mental health was significantly associated to dropout among students in vocational and higher education. Males in higher education had five times the risk of dropout when reporting poor mental health, while no such association was found for females.
Despite the increasing popularity of doctoral education, many students do not complete their studies, and very little information is available about them. Understanding why some students consider ...that they do not want to, or cannot, continue with their studies is essential to reduce dropout rates and to improve the overall quality of doctoral programmes. This study focuses on the motives students give for considering dropping out of their doctoral degree. Participants were 724 social sciences doctoral students from 56 Spanish universities, who responded to a questionnaire containing doctoral degree conditions questions and an open-ended question on motives for dropping out. Results showed that a third of the sample, mainly the youngest, female and part time students, stated that they had intended to drop out. The most frequent motives for considering dropping out were difficulties in achieving a balance between work, personal life and doctoral studies and problems with socialization. Overall, results offer a complex picture that has implications for the design of doctoral programmes, such as the conditions and demands of part-time doctoral studies or the implementation of educational proposals that facilitate students' academic and personal integration into the scientific community in order to prevent the development of a culture of institutional neglect.
Dan Bloom of MDRC examines policies and programs designed to help high school dropouts improve their educational attainment and labor market outcomes. So called "second-chance" programs, he says, ...have long provided some combination of education, training, employment, counseling, and social services. But the research record on their effectiveness is fairly thin, he says, and the results are mixed. Bloom describes eleven employment- or education-focused programs serving high school dropouts that have been rigorously evaluated over the past thirty years. Some relied heavily on paid work experience, while others focused more on job training or education. Some programs, especially those that offered paid work opportunities, generated significant increases in employment or earnings in the short term, but none of the studies that followed participants for more than a couple of years found lasting improvements in economic outcomes. Nevertheless, the findings provide an important foundation on which to build. Because of the high individual and social costs of ignoring high school dropouts, the argument for investing more public funds in services, systems, and research for these young people is strong. The paucity of conclusive evidence, however, makes it hard to know how to direct resources and magnifies the importance of ensuring that all new initiatives provide for rigorous evaluation of their impacts. Bloom concludes with recommendations for policy and research aimed at building on current efforts to expand and improve effective programs for dropouts while simultaneously developing and testing new approaches that might be more effective and strengthening local systems to support vulnerable young people. He stresses the importance of identifying and disseminating strategies to engage young people who are more seriously disconnected and unlikely to join programs. A recurring theme is that providing young people with opportunities for paid work may be useful both as an engagement tool and as a strategy for improving long-term labor market outcomes.
John Tyler and Magnus Lofstrom take a close look at the problems posed when students do not complete high school. The authors begin by discussing the ongoing, sometimes heated, debate over how ...prevalent the dropout problem is. They note that one important reason for discrepancies in reported dropout rates is whether holders of the General Educational Development (GED) credential are counted as high school graduates. The authors also consider the availability of appropriate student data. The overall national dropout rate appears to be between 22 and 25 percent, but the rate is higher among black and Hispanic students, and it has not changed much in recent decades. Tyler and Lofstrom conclude that schools are apparently doing about as well now as they were forty years ago in terms of graduating students. But the increasingly competitive pressures associated with a global economy make education ever more important in determining personal and national well-being. A student's decison to drop out of school, say the authors, is affected by a number of complex factors and is often the culmination of a long process of disengagement from school. That decision, not surprisingly, carries great cost to both the student and society. Individual costs include lower earnings, higher likelihood of unemployment, and greater likelihood of health problems. Because minority and low-income students are significantly more likely than well-to-do white students to drop out of school, the individual costs fall unevenly across groups. Societal costs include loss of tax revenue, higher spending on public assistance, and higher crime rates. Tyler and Lofstrom go on to survey research on programs designed to reduce the chances of students' dropping out. Although the research base on this question is not strong, they say, close mentoring and monitoring of students appear to be critical components of successful programs. Other dropout-prevention approaches associated with success are family outreach and attention to students' out-of-school problems, as well as curricular reforms. The authors close with a discussion of second-chance programs, including the largest such program, the GED credential.
PDF
