Dropout Patterns Research Articles

Reduced vessel density in the superficial and deep plexuses in diabetic retinopathy is associated with structural changes in corresponding retinal layers.

PurposeTo explore the relationships between vessel density (VD) in the retinal vascular plexuses with the thickness and structural changes of their corresponding retinal layers in patients with diabetic retinopathy (DR).MethodsRetrospective analysis of 17 eyes of 17 Type 1 diabetes (T1D) patients with severe non-proliferative or proliferative DR and no current or past macular edema. Seventeen age- and sex-matched healthy subjects were included as controls. Using optical coherence tomography (OCT) and OCT-angiography (OCTA), VD was measured in the superficial vascular plexus (SVP) and deep vascular complex (DVC) that includes the intermediate (ICP) and deep capillary plexuses (DCP), and compared to the retinal thickness (RT) of the inner (from the inner limiting membrane to the inner plexiform layer) and intermediate (inner nuclear and outer plexiform layer) retinal layers. The correlation between the inner and intermediate RT and the VD of the corresponding vascular networks (SVP and DVC, respectively) was assessed. All OCT and OCTA examinations were performed using the RTVue XR Avanti (Optovue, Fremont, CA).ResultsThe inner RT and VD in all plexuses were significantly reduced in T1D patients compared to healthy subjects. The capillary drop-out patterns were polygonal and well-defined in the SVP while the ICP and DCP showed a more diffuse capillary rarefaction and a VD that varied in the same proportion. The inner RT significantly correlated with VD in the SVP (r = 0.71 in healthy subjects and r = 0.62 in T1D patients, p <0.01). The intermediate RT did not significantly correlate with VD in the DVC.ConclusionsIn T1D subjects, OCTA allowed observing different capillary drop-out patterns in the SVP and in the ICP-DCP, with different structural changes in the corresponding retinal layers, suggesting that they should be considered as distinct anatomical and functional entities.

Dropout Patterns and Cultural Context in Online Networked Learning Spaces

Dropout is a major concern in networked learning practices, however, little is known about the issue within the perspective of cultural contexts. On this basis, cultural context and dropout patterns were examined through a mixed-methods approach in which social network analysis and two-way between-group comparisons (culture vs. dropout) were conducted. The sample comprised 179 MOOC learners who were active in a networked extension of the Introduction to Open Education MOOC (#openEDMOOC). The dependent variables of interest were centrality metrics, whereas the independent variables were dropout (i.e., yes-no) and cultural contexts (i.e., high-low). The findings of the social network analysis suggested that non-dropout learners hold central positions in the network. Furthermore, learners from high cultural contexts tend to drop out, whereas those from low contexts tend not to drop out.

Alleles dropout patterns of Y-short tandem repeats in infertile males with Y chromosome microdeletions

Y chromosomal short tandem repeat (Y-STR) typing is the most commonly used genetic technique in forensic studies. However, there may be a limit to the application of Y-STR in forensic science as Y-STR loci are subject to loss or variation caused by the higher chromosomal structures' spontaneous mutation rate. Located in the long arm of the Y chromosome, azoospermia factor (AZF) have been shown to participate in spermatogenesis and its deletion could cause infertility. However, little is known about the Y-STR dropout pattern in individuals with Y chromosome microdeletions. In this study, 85 infertile males with Y chromosome interstitial deletion were identified and special Y-STR allele dropout patterns were analyzed by employing a Y-STR Commercial Kit and a Y chromosome Deletion Kit. Results demonstrate that AZF a region deletion are related to DYS439-DYS389I-DYS389II alleles dropout, while AZF b region or c region deletions correlate to DYS448 allele dropout. Null DYS385-DYS392-DYS448 alleles were observed in AZF b+c+d region deletion individuals. While null DYS390-Y-GATA-H4-DYS385-DYS392-DYS448 alleles were observed in AZF a+b+c+d large region deletion individuals. Our data suggest that Y chromosome microdeletions may indicate specific Y-STR locus dropout patterns.

Identifying change-dropout patterns during an Internet-based intervention for depression by applying the Muthen-Roy model

ABSTRACTTo date, only few studies have attempted to investigate non-ignorable dropout during Internet-based interventions by applying an NMAR model, which includes missing data indicators in its equations. Here, the Muthen-Roy model was used to investigate change and dropout patterns in a sample of patients with mild-to-moderate depression symptoms (N = 483) who were randomized to a 12-week Internet-based intervention (deprexis, identifier: NCT01636752). Participants completed the PHQ-9 biweekly during the treatment. We identified four change-dropout patterns: Participants showing high impairment, improvement and low dropout probability (C3, N = 134) had the highest rate of reliable change at 6- and 12-month follow-up. A further pattern was characterized by high impairment, deterioration and high dropout probability (C2, N = 32), another by low impairment, improvement and high dropout probability (C1, N = 198). The last pattern was characterized by high impairment, no change and low dropout probability (C4, N = 119). In addition to deterioration, also rapid improvement may lead to dropout as a result of a perceived “good enough” dosage of treatment. This knowledge may strengthen sensitivity for the mechanisms of dropout and help to consider its meaning in efforts to optimize treatment selection.

Student throughput variables and properties: Varying cohort sizes

&#x0D; &#x0D; &#x0D; A recent research paper described how student throughput variables and properties combine to explain the behaviour of stationary or simplified throughput systems. Such behaviour can be understood in terms of the locus of a point in the triangular admissible region of the H-S plane, where H represents headcounts and S successful credits, each depending on the system properties at that point. The efficiency of the student throughput process is given by the ratio S/H. Simplified throughput systems are characterised by stationary graduation and dropout patterns of students as well as by annual intakes of student cohorts of equal size. The effect of varying the size of the annual intakes of student cohorts is reported on here. The observations made lead to the establishment of a more generalised student throughput theory which includes the simplified theory as a special case. The generalised theory still retains the notion of a triangular admissible region in the H-S plane but with the size and shape of the triangle depending on the size of the student cohorts. The ratio S/H again emerges as the process efficiency measure for throughput systems in general with unchanged roles assigned to important system properties. This theory provides for a more fundamental understanding of student throughput systems encountered in real life.&#x0D; &#x0D; &#x0D; &#x0D; &#x0D; Significance: &#x0D; &#x0D; &#x0D; &#x0D; A generalised stationary student throughput theory through varying cohort sizes allows for a far better understanding of real student throughput systems.&#x0D; &#x0D; &#x0D; &#x0D;

Predictors and Patterns of Psychiatric Treatment Dropout During Pregnancy Among Low-Income Women.

Objective This study compared psychiatric treatment discontinuation rates among pregnant women using psychotropic medications, outpatient psychotherapy, or both before conception. Methods Using data from Pennsylvania Medicaid Fee-For-Service and Managed Care Organization claims and Medicaid enrollment, 3030 women were identified who gave birth between 2007 and 2009, had ≥ 1 claim for psychiatric treatment during the 120days prior to pregnancy, and were enrolled in Medicaid until they delivered. Kaplan-Meier and Cox regression analyses were used to estimate psychiatric treatment dropout rate during pregnancy and examine relationships between treatment dropout and age, race/ethnicity, and pre-pregnancy psychiatric diagnosis and treatment pattern. Results After the first trimester, the probability of discontinuing psychotropic medications was 83 versus 37.8% for cessation of psychotherapy among combined treatment users. Two or more psychotherapy sessions in the 4months prior to pregnancy were associated with decreased psychotherapy dropout during pregnancy. Psychotherapy during pregnancy was associated with prenatal psychotropic medication adherence. Conclusions To retain women in treatment during pregnancy, when discontinuation from care is common, innovative models of care should consider type of pre-pregnancy mental healthcare and individual characteristics.

When Does Premature Treatment Termination Occur? Examining Session-by-Session Dropout Among Clients with Gambling Disorder.

Premature termination challenges the successful outcomes of psychological treatments for gambling disorder. To date, research has primarily identified clients who are at particular risk for dropping out of treatment. A smaller but growing body of literature has investigated when dropout occurs. Typically, those studies have not considered improvement in psychological distress within their operationalizations of dropout and therefore may have misrepresented when dropout occurs. The current study examined when dropout occurs using an operationalization based on the criteria of attaining reliable change in a naturalistic sample of clients with gambling disorder, and the classification rates yielded fromthat operationalization were compared to the rates froma more common operationalization. Participants (n=334) were clients meeting diagnostic criteria for gambling disorder at an outpatient private practice who completed a measure of psychological distress at baseline and prior to each subsequent treatment session. A survival analysis was conducted to determine temporal patterns of treatment dropout (i.e., clients who discontinued treatment before realizing reliable changes in psychological distress) and completion (i.e., clients who discontinued treatment after realizing reliable changes in distress) at each treatment session. Forty-nine percent of clients were classified as dropouts, and the majority of those clients did so in the first few sessions. The more common operationalization of dropout classified clients as dropouts when they had improved in their distress and clients as completers when they had not improved in their distress. Discussion centers on the implications of dropout occurring at various stages of treatment and future directions.

The impact of different modalities on student retention and overall engagement patterns in open online courses

ABSTRACTThis article presents an analysis of tracking data collected over eight years on 43,000 users on Icelandic Online (IOL), seven open, guided online courses in Icelandic as a second language. The main objective in this study is to (a) map out retention for all the IOL courses, (b) compare retention on the same course delivered in three different modes; blended learning mode, distance learning mode, and self-directed mode, and (c) to investigate overall engagement patterns on IOL. The findings reveal low completion rates that vary by mode of delivery, identifying blended learning mode as most effective in retaining students. The results also reveal regular attrition patterns across all modes of delivery, with sharp drop-outs initially and concentrations of drop-outs at certain junctures in the courses. The drop-out patterns revealed in this study called for a re-evaluation of earlier parameters by which retention is measured, and especially what it means to ‘complete a course’. Instead of considering course completion in light of 100% coverage, the findings show considerably higher retention on IOL when the parameters for course completion are adjusted to for instance 90% coverage of course content.

An Overview of School Dropout in Central America: Unresolved Issues and New Challenges for Education Progress

&lt;p style="text-align:justify"&gt;School dropout is a growing concern in Central America, and in Latin America as a whole, because of its consequences for economic productivity, the inclusiveness of growth, social cohesion, and increasing youth risks. This paper utilizes more than two decades of household survey data to construct a systematic overview of school dropout at the primary and secondary levels in Central America, focusing on recent trends in dropout patterns and their underlying causes. Within each country, poverty, rurality, and indigenous group membership are the strongest correlates of dropout, reflecting several underlying factors that affect the marginal benefits and costs of staying in school. Global and regional evidence increasingly points to common policy priorities for reducing dropout across Central America, including addressing remaining gaps in access at the pre-primary and secondary levels, improving the quality of education at all levels, and strengthening the coverage, targeting, and coherence of existing programs aimed at improving education outcomes. However, additional rigorous evaluations, including cost data, are needed to identify the most effective specific approaches in each country. JEL Classification: I2, I24, I25, I26, I28, O15&lt;/p&gt;

Patterns of Multisystem Service Use and School Dropout Among Seventh-, Eighth-, and Ninth-Grade Students

Youth who receive services from public mental health, child welfare and delinquency, and homeless systems are often exposed to a number of overlapping child, family, school, and community risk factors. Minimal research, however, has focused on the extent to which single- or multiple-system involvement influences school dropout. Relying on an integrated data set, the associations between single- and multiple-system utilization and risk for dropping out, or actually dropping out of school, among youth in Grades 7 through 9 were examined. Results showed dropout rates more than doubled among public youth system users compared with those in the overall sample. With a few exceptions, use of combinations of services systems translated into somewhat higher likelihoods of dropping out of school when compared with single-system use. Future research is warranted to identify the underlying processes by which single- and multiple-system involvement influences school dropout rates.

Baseline Motivation Type as a Predictor of Dropout in a Healthy Eating Text Messaging Program.

BackgroundGrowing evidence suggests that text messaging programs are effective in facilitating health behavior change. However, high dropout rates limit the potential effectiveness of these programs.ObjectiveThis paper describes patterns of early dropout in the HealthyYou text (HYTxt) program, with a focus on the impact of baseline motivation quality on dropout, as characterized by Self-Determination Theory (SDT).MethodsThis analysis included 193 users of HYTxt, a diet and physical activity text messaging intervention developed by the US National Cancer Institute. Descriptive statistics were computed, and logistic regression models were run to examine the association between baseline motivation type and early program dropout.ResultsOverall, 43.0% (83/193) of users dropped out of the program; of these, 65.1% (54/83; 28.0% of all users) did so within the first 2 weeks. Users with higher autonomous motivation had significantly lower odds of dropping out within the first 2 weeks. A one unit increase in autonomous motivation was associated with lower odds (odds ratio 0.44, 95% CI 0.24–0.81) of early dropout, which persisted after adjusting for level of controlled motivation.ConclusionsApplying SDT-based strategies to enhance autonomous motivation might reduce early dropout rates, which can improve program exposure and effectiveness.

An Analysis of Primary School Dropout Patterns in Honduras

ABSTRACTThis study hypothesized that repeating a grade is one reason why Honduran primary students drop out of school but not the main reason. Using longitudinal data, we analyzed student enrollment patterns up until students left school. The results revealed that many students dropped out suddenly without having previously repeated a grade, although many dropouts had also repeated a grade at some point, and repeating a grade experience was not among the most frequently appearing dropout patterns in any of the completed grades. The findings indicated that low expectations of education and the need to enter the labor market were causes of immediate dropout.

Testing treatment effect in schizophrenia clinical trials with heavy patient dropout using latent class growth mixture models.

By examining the outcome trajectories of the dropout patients with different reasons in the schizophrenia trials, we note that although patients are recruited from the same protocol that have compatible baseline characteristics, they may respond differently even to the same treatment. Some patients show consistent improvement while others only have temporary relief. This creates different patient subpopulations characterized by their response and dropout patterns. At the same time, those who continue to improve seem to be more likely to complete the study while those who only experience temporary relief have a higher chance to drop out. Such phenomenon appears to be quite general in schizophrenia clinical trials. This simultaneous inhomogeneity both in patient response as well as dropout patterns creates a scenario of missing not at random and therefore results in biases when we use the statistical methods based on the missing at random assumption to test treatment efficacy. In this paper, we propose to use the latent class growth mixture model, which is a special case of the latent mixture model, to conduct the statistical analyses in such situation. This model allows us to take the inhomogeneity among subpopulations into consideration to make more accurate inferences on the treatment effect at any visit time. Comparing with the conventional statistical methods such as mixed-effects model for repeated measures, we demonstrate through simulations that the proposed latent mixture model approach gives better control on the Type I error rate in testing treatment effect. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

Changes in Weight Loss, Health Behaviors, and Intentions among 400 Participants Who Dropped out from an Insurance-Sponsored, Community-Based Weight Management Program.

The majority of weight management research is based on data from randomized controlled studies conducted in clinical settings. As these findings are translated into community-based settings, additional research is needed to understand patterns of lifestyle change and dropout. The purpose of this study was to examine reasons for and consequences associated with dropout (or removal) from an insurance-funded weight management program. Using a mixed methods approach with objectively measured changes in body weight and attendance along with quantitative and qualitative survey data, patterns of intention and behavior change were explored. The results from a sample of 400 respondents support the idea that there are both positive and negative consequences of program participation. Overall, 1 in 5 respondents lost a clinically significant amount of weight during the program (>5% of baseline body weight) and 1 in 3 experienced a positive consequence, while only 6% expressed a negative outcome of participation. Additionally, nearly 90% of all of the consequences that emerged from the data were positive. Attitude change was a major theme, including positive health intentions, perceived success, learning skills, and new appreciation of exercise.

Patterns and Factors of High School Dropout Risks of Racial and Linguistic Groups

This study examined the dropout trajectories of racial and linguistic minority students and explored the effects of students' contextual factors on their high school dropout risks. Our motivation was to identify the dropout patterns of Black, Hispanic, and Hispanic English language learner (ELL) students, who have comparatively high dropout rates, and to suggest ways to promote high school completion. We employed a survival analysis using the National Longitudinal Survey of Youth 1997 (NLSY97) from the U.S. Bureau of Labor Statistics. The results showed that the 3 minority groups displayed significantly higher dropout risks than the White group. The overall pattern of dropout risks increased over time, with the dropout rates of the Black students high in the 1st and 2nd years of high school and the highest dropout rates for Hispanic ELL students in their senior year. A gender difference was found among the students, with male students having higher dropout risks than female students. It was also found that students' positive relationships with their teachers were associated with lower dropout risks.

Out-of-School and Out-of-Work Youth in Latin America: A Persistent Problem in a Decade of Prosperity

This paper explores the persistent shares of youth that are out of school and out of work in Latin America, with special attention to those in the fifteen-to-eighteen age range. According to our calculations, 18.5 percent of Latin American youth in this age group (9.4 million individuals) are currently neither in school nor working. We present the patterns of the evolution of this group in eighteen countries across the region, identifying the set of microeconomic and aggregate variables that are correlated with their dynamics. We explore the relationship with the household’s socioeconomic characteristics and with the structure and evolution of labor markets. We identify the links with the schooling system and school dropout patterns; and we verify whether the group responds to changes in the environment, including overall GDP growth, or to economic shocks. We also explore the possibility that they are simply a transient demographic phenomenon.&#x0D; JEL Classification: J10, J21, I24.

Out-of-School and Out-of-Work Youth in Latin America: A Persistent Problem in a Decade of Prosperity

This paper explores the persistent shares of youth that are out of school and out of work in Latin America, with special attention to those in the fifteen-to-eighteen age range. According to our calculations, 18.5 percent of Latin American youth in this age group (9.4 million individuals) are currently neither in school nor working. We present the patterns of the evolution of this group in eighteen countries across the region, identifying the set of microeconomic and aggregate variables that are correlated with their dynamics. We explore the relationship with the household’s socioeconomic characteristics and with the structure and evolution of labor markets. We identify the links with the schooling system and school dropout patterns; and we verify whether the group responds to changes in the environment, including overall GDP growth, or to economic shocks. We also explore the possibility that they are simply a transient demographic phenomenon.

Patterns, Consequences, and Possible Causes of Dropout in Upper Secondary Education in Mexico

The present study provides a detailed analysis of upper secondary education dropout patterns in Mexico, exploring its consequences and possible causes. To perform the analysis we combine different databases and statistical methods ranging from the use of surveys with information on specific individuals to data aggregated at the municipal and state level. The main value added is the simultaneous analysis of the influence of individual-family, community, and macroaggregate factors, on school dropout in the country.

Enhanced low-template DNA analysis conditions and investigation of allele dropout patterns

Forensic DNA analysis applying PCR enables profiling of minute biological samples. Enhanced analysis conditions can be applied to further push the limit of detection, coming with the risk of visualising artefacts and allele imbalances. We have evaluated the consecutive increase of PCR cycles from 30 to 35 to investigate the limitations of low-template (LT) DNA analysis, applying the short tandem repeat (STR) analysis kit PowerPlex ESX 16. Mock crime scene DNA extracts of four different quantities (from around 8-84 pg) were tested. All PCR products were analysed using 5, 10 and 20 capillary electrophoresis (CE) injection seconds. Bayesian models describing allele dropout patterns, allele peak heights and heterozygote balance were developed to assess the overall improvements in EPG quality with altered PCR/CE settings. The models were also used to evaluate the impact of amplicon length, STR marker and fluorescent label on the risk for allele dropout. The allele dropout probability decreased for each PCR cycle increment from 30 to 33 PCR cycles. Irrespective of DNA amount, the dropout probability was not affected by further increasing the number of PCR cycles. For the 42 and 84 pg samples, mainly complete DNA profiles were generated applying 32 PCR cycles. For the 8 and 17 pg samples, the allele dropouts decreased from 100% using 30 cycles to about 75% and 20%, respectively. The results for 33, 34 and 35 PCR cycles indicated that heterozygote balance and stutter ratio were mainly affected by DNA amount, and not directly by PCR cycle number and CE injection settings. We found 32 and 33 PCR cycles with 10 CE injection seconds to be optimal, as 34 and 35 PCR cycles did not improve allele detection and also included CE saturation problems. We find allele dropout probability differences between several STR markers. Markers labelled with the fluorescent dyes CXR-ET (red in electropherogram) and TMR-ET (shown as black) generally have higher dropout risks compared with those labelled with JOE (green) and fluorescein (blue). Overall, the marker D10S1248 has the lowest allele dropout probability and D8S1179 the highest. The marker effect is mainly pronounced for 30-32 PCR cycles. Such effects would not be expected if the amplification efficiencies were identical for all markers. Understanding allele dropout risks and the variability in peak heights and balances is important for correct interpretation of forensic DNA profiles.

Analysis of allelic drop-out using the Identifiler(®) and PowerPlex(®) 16 forensic STR typing systems.

Low-template (LT) DNA profiles continue to present interpretational challenges to the forensic community. Whether the LT contribution comprises the main profile, or whether it is present as the minor component of a mixture, ambiguity arises from the possibility that alleles present in the biological sample may not be detected in the resulting DNA profile. This phenomenon is known as allelic drop-out. This ambiguity complicates both the assessment of the potential number of contributors and estimation of the weight of the DNA evidence for or against specific propositions. One solution to estimating the weight of the evidence is to use a likelihood ratio (LR) that incorporates the probability of allelic drop-out P(DO) estimated for the specific evidence sample under consideration. However, although a vast repository of data exists, few empirical studies to determine allelic drop-out probabilities have been performed to date. Here we characterized patterns of allelic drop-out in single-source samples using both universal and run-specific analytical thresholds. Not surprisingly, we found fewer instances of apparent drop-out when using a lower (run-specific) detection threshold. Also, unsurprisingly, a positive correlation exists between allele drop-out and allele length, even in good quality samples. We used logistic regression to model the fraction of alleles that dropped out of a profile as a function of the average height of the detected peaks. The equation derived from the logistic regression model allowed us to estimate the expected drop-out probability for an evidentiary sample based on the average peak height of the profile. We show that the LRs calculated using the estimated drop-out probabilities were similar to those calculated using the benchmark drop-out probabilities, suggesting that the estimates of the drop-out probability are accurate and useful. This trend holds even when using the data from the PowerPlex(®) 16 typing system to estimate the drop-out probability for an Identifiler(®) profile, and vice versa. Thus we demonstrate that use of a LR that incorporates empirically estimated allelic drop-out probabilities provides a reliable means for extracting additional information from LT forensic DNA profiles.