Reduce Attrition Rates Research Articles

Behavioral predictors of attrition in adolescents participating in a multidisciplinary obesity treatment program: EVASYON study.

The aims of this study were to identify the cognitive and behavioral predictors of dropping out and to estimate the attrition rate during different phases of an intervention program to treat overweight and obesity in adolescents. Overweight/obese adolescents (n=156, aged: 13-16 years; 71 male and 85 female subjects) were included in a multicomponent (diet, physical activity and psychological support) family-based group treatment program. At baseline and after 2 months (intensive phase) and 13 months (extensive phase) of follow-up, we measured adolescents' cognitive and behavioral dimensions, together with the parents' perception of their child's behavior. Of the 156 adolescents selected, 112 completed the full program (drop-out rate of 28.2%). The risk of dropping out during the extensive phase increased by 20% for each unit increase in the adolescent's social insecurity score (odds ratio=1.20, 95% confidence interval=1.07-1.34, P=0.002). The adolescents who had a high interoceptive awareness showed a significant decrease of 13.0% in the probability of dropping out (odds ratio=0.87, 95% confidence interval=0.77-0.99, P=0.040). Adolescents' social insecurity was the main predictor of drop-out in a multicomponent family-group-based obesity treatment program. To reduce attrition rates in these programs, the individual's social insecurity level needs to be reduced, whereas the family's awareness of eating-related behavior needs adjustment.

Calls for ‘living bursary’ as students visit food banks or drop out

Unison is preparing a campaign for nursing students to receive an adequate wage to address hardship and reduce attrition rates. Jennifer Sprinks reports

Urodynamic Measurement of Urethral Closure Function in Women with Stress Urinary Incontinence: A Single Dose Study of Duloxetine

This urodynamic double‐blind crossover study in women with stress urinary incontinence (SUI) was performed to evaluate the effect of duloxetine, a serotonin and noradrenaline reuptake inhibitor, on urethral function and to determine an appropriate method for making go/no‐go decisions in drug development. The urethral pressure profiles at rest and during coughing were measured before and 6 h after single oral administration of placebo or 40 mg duloxetine in 10 women aged 36 to 53 years with SUI (蠅1 episode/wk). Compared with placebo, duloxetine significantly increased the mean and maximal urethral closure pressures at rest calculated over the entire urethra. In the distal third of the urethra, during coughing, duloxetine significantly increased the mean closure pressure and the change from baseline in the maximal amplitudes of the negative closure pressure spikes compared with placebo. Our data indicate the facilitatory effects of duloxetine on both smooth muscle contractions and reflex contractions of the striated sphincters. Thus, the method for this urodynamic study in women with SUI could be used to reduce attrition rates by providing decision‐making data in early clinical studies of new drugs developed to treat SUI. Supported in part by Takeda Pharmaceutical Company Limited.

How can We Discover Safer Drugs?

How can We Discover Safer Drugs?

Demographic and Attitudinal Factors Influencing Doctoral Student Satisfaction

Higher education administrators face challenges in providing a welcoming environment for doctoral students in higher education institutions, as they must identify factors influencing students’ satisfaction in order to provide a supportive environment, reduce attrition rates, and promote persistence. Thus, the purpose of this study was to identify predictors of doctoral student satisfaction from demographics and attitudes concerning the campus environment. Participants were 132 (33 male, 99 female) doctoral students from two private nonprofit universities in the New York metropolitan area of the United States who completed either a web-based or paper/pencil survey in which demographics and opinions regarding student satisfaction were sought. Regression analysis on participant attitudes found that university services, advisor, and students were all significant predictor variables. Other demographic predictor variables included years in graduate school, race, and ethnicity. Of particular importance, as doctoral students progress in their program by year, dissatisfaction increases. This could be due to the increasing pressures of successfully completing the dissertation, the progress of which can be heavily influenced by advisor-student relationship. Overall findings may assist education administrators and institutional planners in making campus environments welcoming to students thereby increasing both student satisfaction and retention.

Systems biology‐embedded target validation: improving efficacy in drug discovery

The pharmaceutical industry is faced with a range of challenges with the ever-escalating costs of drug development and a drying out of drug pipelines. By harnessing advances in -omics technologies and moving away from the standard, reductionist model of drug discovery, there is significant potential to reduce costs and improve efficacy. Embedding systems biology approaches in drug discovery, which seek to investigate underlying molecular mechanisms of potential drug targets in a network context, will reduce attrition rates by earlier target validation and the introduction of novel targets into the currently stagnant market. Systems biology approaches also have the potential to assist in the design of multidrug treatments and repositioning of existing drugs, while stratifying patients to give a greater personalization of medical treatment.

Research on the Internet of Things Network Experiment System Based on Virtual Instrument Technology

Aiming at the condition that laboratory instrument resource can not meet the demands of experimental teaching,management and upgrading because of shortage, decentralization, obsolescence and aging, therefore, a design proposal of network experiment system based on Lab VIEW is presented. The data transmission of tree modules which are virtual instruments, simulation and real time measure is achieved with application of Data at Socket technology and Remote Panels technology. Practical application shows that this system can reduce attrition rate of machines and improve the utilization efficiency of instruments and it has some other advantages including short development period, low cost, good compatibility, good extensibility and easy update for equipments. The network construction based on virtual instrument technology has broad prospects in industry and scientific experiment.

Integrative relational machine-learning for understanding drug side-effect profiles

BackgroundDrug side effects represent a common reason for stopping drug development during clinical trials. Improving our ability to understand drug side effects is necessary to reduce attrition rates during drug development as well as the risk of discovering novel side effects in available drugs. Today, most investigations deal with isolated side effects and overlook possible redundancy and their frequent co-occurrence.ResultsIn this work, drug annotations are collected from SIDER and DrugBank databases. Terms describing individual side effects reported in SIDER are clustered with a semantic similarity measure into term clusters (TCs). Maximal frequent itemsets are extracted from the resulting drug x TC binary table, leading to the identification of what we call side-effect profiles (SEPs). A SEP is defined as the longest combination of TCs which are shared by a significant number of drugs. Frequent SEPs are explored on the basis of integrated drug and target descriptors using two machine learning methods: decision-trees and inductive-logic programming. Although both methods yield explicit models, inductive-logic programming method performs relational learning and is able to exploit not only drug properties but also background knowledge. Learning efficiency is evaluated by cross-validation and direct testing with new molecules. Comparison of the two machine-learning methods shows that the inductive-logic-programming method displays a greater sensitivity than decision trees and successfully exploit background knowledge such as functional annotations and pathways of drug targets, thereby producing rich and expressive rules. All models and theories are available on a dedicated web site.ConclusionsSide effect profiles covering significant number of drugs have been extracted from a drug ×side-effect association table. Integration of background knowledge concerning both chemical and biological spaces has been combined with a relational learning method for discovering rules which explicitly characterize drug-SEP associations. These rules are successfully used for predicting SEPs associated with new drugs.

Developing Physical Capability Standards That are Predictive of Success on Special Forces Selection Courses

This study aimed to develop minimum standards for physical capability assessments (vertical jump, sit and reach, push-ups, seven-stage sit-ups, heaves, agility, 20-m shuttle run, loaded 5-km pack march, and 400-m swim) that candidates must pass before they can commence Australian Army Special Forces (SF) selection courses. Soldiers (Part A: n = 104; Part B: n = 92) completed the physical capability assessments before commencing a SF selection course. At the beginning of these selection courses, participants attempted two barrier assessments (3.2-km battle run and 20-km march). Statistical analysis revealed several physical capability assessments were associated with performance on the barrier assessments and selection course outcome (Part A); however, these statistical models were unable to correctly classify all candidates as likely to pass or fail the selection course. Alternatively, manual analysis identified a combination of physical capability standards that correctly classified 14% to 18% of candidates likely to fail, without excluding any candidates able to pass (Part A). The standards were applied and refined through Part B and included completing the 5-km pack march in ≤45:45 minutes : seconds, achieving ≥level five on the sit-up test, or completing ≥66 push-ups. Implementation of these standards may reduce attrition rates and enhance the efficiency of the SF recruitment process.

<em>The Enhanced Flipped Classroom: Increasing Academic Performance with Student-recorded Lectures and Practice Testing in a "Flipped" STEM Course</em>

Undergraduate psychology students at a mid-Atlantic HBCU were assessed on their knowledge of synaptic transmission, the multi-step process of brain cell communication. Comparison of final grades revealed that the use of the flipped classroom format along with learning techniques, self-explanation and practice testing increased the final course grade over previous semesters. Multiple sessions of practice testing integrated the use of mobile technology to make grading easier. Self-explanation required that students use online videos to explain the process in their own words. These techniques increased time studying the course material and led to higher exam grades. Thus, the use of effective learning techniques, embedded within STEM courses may play a significant role in increasing retention in STEM disciplines among African Americans.Keywords: STEM, education, flipped classroom, academic performance, HBCUIntroductionIn a required course, Physiological Psychology, undergraduate psychology students at a midAtlantic historically Black college and university (HBCU) were assessed on their knowledge of synaptic transmission, the multi-step physiological process of brain cell communication. The students were asked to describe the neural network communication process in terms of the anatomy of the nerve cell, ion transfer across the cell membrane, and how ionic changes would register on an oscilloscope graph. These topics comprised the majority of the midterm exam and were a major component of the cumulative final exam.All students enrolled in the course were Psychology majors and most were seniors. During discussions held during the introductory lecture, many students routinely expressed a dislike for biological science. Students commented that courses with a focus on math or biology content are more challenging. One reason for this view may be the fact that required courses within the Psychology curriculum, such as Qualitative Methods, Experimental Psychology, and Anatomy and Physiology are spread out, if taken in the recommended sequence, across six semesters. In addition, earlier math/sciences courses in General Education are ordinarily taken during freshmen or sophomore years. Therefore, it is often difficult for students to see the relationships and similarities between the subject matter of each course.Addressing the myriad and varied reasons behind the lower numbers of college students, particularly minority students, who attain degrees in science, technology, engineering, and mathematics (STEM) disciplines are necessary in order to reverse current trends. As of 2008, less than 10% of all bachelor's degrees are awarded to African American and Hispanic students (National Science Foundation, 2010; Palmer, Maramba, & Dancy, 2011). Nonetheless, according to U.S. Census Bureau data, 2020 population projections indicate that minority populations will comprise nearly 40% (66 million people) of the American workforce (Toosie, 2012). Reducing attrition rates in STEM majors and increasing enrollment and graduation rates is vital for increasing the number of future workers and for ensuring that the STEM workforce is diverse and inclusive (National Science Foundation, 2010; Palmer, Maramba, & Dancy, 2011; Soldner et al., 2012). Therefore, the factors influencing these students to drop out of college or to switch to nonSTEM majors must be assessed (Palmer, Maramba, & Dancy, 2011).At the university in which this study was conducted, psychology professors who teach courses with more biology or math content commonly report lower average class grades than other courses in the department. The activities communicated in this report were undertaken by a newly hired instructor in response to consistently lower average course grades (approximately 68%). Low averages were recorded for 3 consecutive semesters in the course Psychology 412, Physiological Psychology. A grade of C (70%) is considered passing and is necessary to meet graduation requirements. …

Barriers to Participation in a Randomized Controlled Trial of Qigong Exercises Amongst Cancer Survivors: Lessons Learnt

Clinical trials on cancer subjects have one of the highest dropout rates. Barriers to recruitment range from patient-related, through institutional-related to staff-related factors. This paper highlights the low response rate and the recruitment barriers faced in our Qigong exercises trial. The Qigong trial is a three-arm trial with a priori power size of 114 patients for 80% power. The University Malaya Medical Centre database showed a total of 1,933 patients from 2006-2010 and 751 patients met our inclusion criteria. These patients were approached via telephone interview. 131 out of 197 patients attended the trial and the final response rate was 48% (n=95/197). Multiple barriers were identified, and were regrouped as patient- related, clinician-related and/or institutional related. A major consistent barrier was logistic difficulty related to transportation and car parking at the Medical Centre. conclusions: All clinical trials must pay considerable attention to the recruitment process and it should even be piloted to identify potential barriers and facilitators to reduce attrition rate in trials.

Torching the Haystack: modelling fast-fail strategies in drug development

By quickly clearing the development pipeline of failing or marginal products, fast-fail strategies release resources to focus on more promising molecules. The Quick-Kill model of drug development demonstrates that fast-fail strategies will: (1) reduce the expected time to market; (2) reduce expected R&D costs; and (3) increase R&D productivity. This paper outlines the model and demonstrates the impact of fast-fail strategies. The model is illustrated with costs and risks data from pharmaceutical and biopharmaceutical companies.

Enumeration of 166 Billion Organic Small Molecules in the Chemical Universe Database GDB-17

Drug molecules consist of a few tens of atoms connected by covalent bonds. How many such molecules are possible in total and what is their structure? This question is of pressing interest in medicinal chemistry to help solve the problems of drug potency, selectivity, and toxicity and reduce attrition rates by pointing to new molecular series. To better define the unknown chemical space, we have enumerated 166.4 billion molecules of up to 17 atoms of C, N, O, S, and halogens forming the chemical universe database GDB-17, covering a size range containing many drugs and typical for lead compounds. GDB-17 contains millions of isomers of known drugs, including analogs with high shape similarity to the parent drug. Compared to known molecules in PubChem, GDB-17 molecules are much richer in nonaromatic heterocycles, quaternary centers, and stereoisomers, densely populate the third dimension in shape space, and represent many more scaffold types.

Development of an assessment tool to measure the prior experiential learning of adult learners: The case of Wawasan Open University

Recognition of prior experiential learning offers a vital contribution to supporting lifelong learning around the globe. The Malaysian government has placed great emphasis on lifelong learning in developing a knowledge society to achieve its goal of becoming a developed nation by the year 2020. Hence, the efficacy of recognition of prior experiential learning acts as a mechanism to enhance social equity and social inclusion in the Malaysian higher education context. In tandem with this, Wawasan Open University (WOU)'s vision and mission is to enculturise lifelong learning and provide access to adult learners who may have previously missed the opportunity to pursue higher education. Since its inception in 2007, WOU has developed a mechanism to review, recognise and accord validity to all prior experiential learning (PEL) of the learners. WOU's PEL comprises a series of assessment filters in three stages that are systematically utilised to gauge the learner's level of preparedness to embark on their tertiary education. These stages are (i) Certificate Attestation and Work Experience Portfolio, (ii) Diagnostic Test and (iii) a six-month HeadStart programme. This study investigated the effectiveness of the mechanism and its assessment tools in measuring prior experiential learning of the students. The authors examined the GPA/ CGPA performance of two groups of learners. The first group consisted of those who have passed the diagnostic test and proceeded directly to undertake their degree studies. The second group comprised learners who were unsuccessful in their diagnostic test and had to undertake a six-month HeadStart programme prior to commencing their degree studies. The authors then conducted an analysis on the correlation between the Diagnostic Test results and the GPA/CGPA scores obtained. Similar correlation analysis was also carried out to examine whether learners who had undergone the six-month HeadStart programme performed better in their tertiary studies. Support services offered to these two groups of learners were also identified. The findings from this study also reveal the appropriateness of the various components embedded in the Diagnostic Test as well as the courses offered in the six-month HeadStart programme that aimed to strengthen the learners' knowledge, skills and attitudes prior to pursuing their tertiary studies. Open Universities that subscribe to the philosophy of broadening access to higher education may explore the possibility of adopting the tested bridging programme developed by WOU for weaker Open Entry students to enhance the success rate of students and reduce attrition rate.

Abstract CN04-01: Contribution of polymorphic transporters to oncology drug disposition and safety.

Abstract CN04-01: Contribution of polymorphic transporters to oncology drug disposition and safety.

Developing Quality Learning Materials for Effective Teaching and Learning in an ODL environment: Making the jump from print modules to online modules

This paper highlights the need to develop quality learning materials for effective teaching and learning in an online and distance learning (ODL) environment. This is especially important today as ODL institutions mushroom and compete on an increasingly global platform. While this has helped to widen access to education, it also means that more attention needs to be paid to the quality of teaching and learning materials if ODL institutions wish to continue attracting learners, reduce attrition rate and stay relevant. Attempts must be made to come up with good learning material which can offer ODL learners a fulfilling and enriching learning experience. At Open University Malaysia, a number of e-learning initiatives have been launched towards this end. One of these is the online, hypertext-linked or html modules. The first phase of this project has already been implemented. The rationale for this latest e-learning initiative is outlined. The paper also comes up with a taxonomy of best practice beliefs which identify the characteristics html modules should have if they are to be truly effective. It is hoped that this will provide some sort of benchmark, or standards, for html modules to strive for, as well as a set of criteria for a formative evaluation of the modules. Ultimately, this may provide guidelines for improving html modules and useful pointers for fine tuning this e-learning initiative in the future.

Understanding drug‐likeness

Abstract‘Drug‐likeness’, a qualitative property of chemicals assigned by experts committee vote, is widely integrated into the early stages of lead and drug discovery. Its conceptual evolution paralleled work related to Pfizer's ‘rule of five’ and lead‐likeness, and is placed within this framework. The discrimination between ‘drugs’ (represented by a collection of pharmaceutically relevant small molecules, some of which are marketed drugs) and ‘nondrugs’ (typically, chemical reagents) is possible using a wide variety of statistical tools and chemical descriptor systems. Here we summarize 18 papers focused on drug‐likeness, and provide a comprehensive overview of progress in the field. Tools that estimate drug‐likeness are valuable in the early stages of lead discovery, and can be used to filter out compounds with undesirable properties from screening libraries and to prioritize hits from primary screens. As the goal is, most often, to develop orally available drugs, it is also useful to optimize drug‐like pharmacokinetic properties. We examine tools that evaluate drug‐likeness and some of their shortcomings, challenges facing these tools, and address the following issues: What is the definition of drug‐likeness and how can it be utilized to reduce attrition rate in drug discovery? How difficult is it to distinguish drugs from nondrugs? Are nondrug datasets reliable? Can we estimate oral drug‐likeness? We discuss a drug‐like filter and recent advances in the prediction of oral drug‐likeness. The heuristic aspect of drug‐likeness is also addressed. © 2011 John Wiley & Sons, Ltd. WIREs Comput Mol Sci 2011 1 760–781 DOI: 10.1002/wcms.52This article is categorized under: Computer and Information Science > Chemoinformatics

Minimising attrition: strategies for assisting students who are at risk of withdrawal

This paper explores strategies aimed at minimising attrition by encouraging persistence among online graduate students who are considering withdrawal. It builds upon earlier studies conducted by a team of researchers who teach online graduate students in health care at Athabasca University. First, in 2008–2009, Park, Boman, Care, Edwards, and Perry reviewed assumptions held related to attrition of online learners and defined key terms such as persistence and attrition. Next, Perry, Boman, Care, Edwards, and Park explored factors that influenced online students’ decisions to withdraw. Reported in this paper are strategies related to course design, course delivery, and programme organisation that could reduce attrition rates. An additional section of the paper focuses on strategies to ease the re‐integration of students who have withdrawn and subsequently want to return to their studies. Rovai’s Composite Persistence Model and Harter and Szurminski’s Project Assuring Student Success (PASS) programme are used as a framework for analysis and for generation of recommended strategies.

Innovative approaches to clinical development and trial design.

Pharmaceutical innovation is increasingly risky, costly and at times inefficient, which has led to a decline in industry productivity. Despite the increased investment in R&D by the industry, the number of new molecular entities achieving marketing authorization is not increasing. Novel approaches to clinical development and trial design could have a key role in overcoming some of these challenges by improving efficiency and reducing attrition rates. The effectiveness of clinical development can be improved by adopting a more integrated model that increases flexibility and maximizes the use of accumulated knowledge. Central to this model of drug development are novel tools, including modelling and simulation, Bayesian methodologies, and adaptive designs, such as seamless adaptive designs and sample-size re-estimation methods. Applications of these methodologies to early- and late-stage drug development are described with some specific examples, along with advantages, challenges, and barriers to implementation. Because they are so flexible, these new trial designs require significant statistical analyses, simulations and logistical considerations to verify their operating characteristics, and therefore tend to require more time for the planning and protocol development phase. Greater awareness of the distinct advantages of innovative designs by regulators and sponsors are crucial to increasing the adoption of these modern tools.

Support network

Making students feel valued will reduce attrition rates and result in a higher level of patient care