Journal articles: 'Attrition rates'

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Airey, Jo. "Attrition rates: the student perspective." British Journal of Nursing 21, no. 5 (March 6, 2012): 310. http://dx.doi.org/10.12968/bjon.2012.21.5.310.

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Kennedy, Donald. "Attrition Rates of Mature Engineers." Engineering Management Journal 18, no. 3 (September 2006): 36–40. http://dx.doi.org/10.1080/10429247.2006.11431702.

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Scott, Graham. "Fines for high student attrition rates." Nursing Standard 19, no. 9 (November 10, 2004): 5. http://dx.doi.org/10.7748/ns.19.9.5.s7.

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Coakley, Ann Louise. "Nurse education: attrition rates in the UK." Nursing Standard 11, no. 48 (August 20, 1997): 45–47. http://dx.doi.org/10.7748/ns.11.48.45.s44.

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Parish, Colin. "Student attrition rates in England fall dramatically." Nursing Standard 16, no. 43 (July 10, 2002): 4. http://dx.doi.org/10.7748/ns.16.43.4.s3.

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Hughes, Hazel Alexandra. "Factors influencing attrition rates in midwifery students." Nursing Standard 27, no. 26 (February 27, 2013): 42–48. http://dx.doi.org/10.7748/ns2013.02.27.26.42.e7130.

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Sibson, Robin. "Statistics agency does not calculate attrition rates." Nursing Standard 20, no. 49 (August 16, 2006): 32. http://dx.doi.org/10.7748/ns.20.49.32.s40.

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Ferguson, Charles M. "Trends in Attrition Rates for Surgical Faculty." Journal of the American College of Surgeons 217, no. 3 (September 2013): 560. http://dx.doi.org/10.1016/j.jamcollsurg.2013.05.022.

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Esbensen, Finn-Aage, Michelle Hughes Miller, Terrance Taylor, Ni He, and Adrienne Freng. "Differential Attrition Rates and Active Parental Consent." Evaluation Review 23, no. 3 (June 1999): 316–35. http://dx.doi.org/10.1177/0193841x9902300304.

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Jones-Berry, Stephanie. "Survey confirms failure to tackle attrition rates." Nursing Standard 33, no. 6 (September 5, 2018): 19–22. http://dx.doi.org/10.7748/ns.33.6.19.s12.

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SMITH, ROBERT L., KENNETH MARONEY, KAYE W. NELSON, ANNETTE L. ABEL, and HOLLY S. ABEL. "Doctoral Programs: Changing High Rates of Attrition." Journal of Humanistic Counseling, Education and Development 45, no. 1 (March 2006): 17–31. http://dx.doi.org/10.1002/j.2161-1939.2006.tb00002.x.

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Kola, Ismail, and John Landis. "Can the pharmaceutical industry reduce attrition rates?" Nature Reviews Drug Discovery 3, no. 8 (August 2004): 711–16. http://dx.doi.org/10.1038/nrd1470.

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Akiba, Motoko, and Robert Reichardt. "What predicts the mobility of elementary schoolleaders? An analysis of longitudinal data in Colorado." education policy analysis archives 12 (April 24, 2004): 18. http://dx.doi.org/10.14507/epaa.v12n18.2004.

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While many studies have reported the predictors of teacher attrition, we know little about what predicts the attrition of school leaders. Using the Colorado state data on elementary school principals’ and assistant principals’ career paths from 1999 to 2001 and school achievement-level data, we addressed two research questions: 1) How do the age-specific attrition rates differ by gender and race? and 2) What other conditional factors are associated with the attrition of school leaders? We found that female and minority groups generally had higher attrition rates at age 40 or younger and at age 56 or older than male and non-minority groups. Our data also indicated that school size and salary increase were associated with the attrition of both male and female leaders. Large schools were more likely to have higher rates of school leader attrition, and the leaders who expected relatively higher salary increases by transferring were more likely to leave their schools. Lower school achievement predicted higher attrition of female leaders only. These findings have important implications for policy-makers when they plan and implement strategies for preventing high attrition rates of school leaders.

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Kennedy, Kathleen A., Matthew C. Brennan, William F. Rayburn, and Sarah E. Brotherton. "Attrition Rates Between Residents in Obstetrics and Gynecology and Other Clinical Specialties, 2000–2009." Journal of Graduate Medical Education 5, no. 2 (June 1, 2013): 267–71. http://dx.doi.org/10.4300/jgme-d-12-00141.1.

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Abstract Background As resident attrition disrupts educational and workload balance and reduces the number of graduating physicians to care for patients, an ongoing goal of graduate medical education programs is to retain residents. Objective We compared annual rates of resident attrition in obstetrics and gynecology (Ob-Gyn) with other clinical specialties of similar or larger size during a recent 10-year period, and explored the reasons for resident attrition. Methods In this observational study, we analyzed annual data from the American Medical Association Graduate Medical Education Census between academic years 2000 and 2009 for residents who entered Ob-Gyn and other core clinical specialties. Our primary outcome was the trend in averaged annual attrition rates. Results The average annual attrition was 196 ± 12 (SD) residents, representing 4.2% ± 0.5% of all Ob-Gyn residents. Rates of attrition were consistently higher among men (5.3%) and international medical school graduates (7.6%). The annual rate of attrition was similar to that for other clinical specialties (mean: 4.0%; range: from 1.5% in emergency medicine to 7.9% in psychiatry). The attrition rates for Ob-Gyn residents were relatively stable for the 10-year period (range: 3.6% in 2008 to 5.1% in 2006). Common reasons for attrition were transition to another specialty (30.0%), withdrawal/dismissal (28.2%), transfer to another Ob-Gyn program (25.4%), and leave of absence (2.2%). These proportions remained fairly constant during this 10-year period. Conclusions The average annual attrition rate of residents in Ob-Gyn was 4.2%, comparable to most other core clinical specialties.

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Lynn, P. "Alternative Sequential Mixed-Mode Designs: Effects on Attrition Rates, Attrition Bias, and Costs." Journal of Survey Statistics and Methodology 1, no. 2 (September 18, 2013): 183–205. http://dx.doi.org/10.1093/jssam/smt015.

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Wamser-Nanney, Rachel. "Risk Factors for Attrition From Pediatric Trauma-Focused Treatment." Child Maltreatment 25, no. 2 (September 11, 2019): 172–81. http://dx.doi.org/10.1177/1077559519874406.

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Rates of attrition from pediatric trauma-focused treatments are high, yet few studies have examined predictors of dropout. The aim of the study was to investigate whether higher levels of caregiver- and child-reported pretreatment difficulties predicted attrition from trauma-focused therapy. One hundred seventy-two children aged 6–18 ( M = 10.53, SD = 3.36; 64% female, 64% Black) and their caregivers were included in the study. Two operational definitions of attrition were utilized: (1) clinician-rated dropout and (2) whether the child received an adequate dose of treatment (i.e., 12 or more sessions). Rates of clinician-rated attrition were high (76.2%); however, 73.8% received an adequate dose. Despite expectations, higher levels of rule-breaking and aggressive behavior were related to clinician-rated dropout ( d = 0.59, .63, respectively) but were not significant predictors in a logistic regression model. Child-reported symptoms were unrelated to clinician-rated attrition. Higher levels of caregiver-reported anxiety/depression, somatic complaints, and trauma-related difficulties corresponded with adequate dose ( ds = 0.52–1.06). Yet only caregiver-reported sexual concerns predicted adequate dose in a regression model ( OR = 1.09). Caregiver- and child-reported symptoms may be unrelated to clinician-rated treatment completion and appear to play a small role in understanding whether the child received an adequate dose of treatment.

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Litwin Miller, Kimberly, and Douglas Jerolmack. "Controls on the rates and products of particle attrition by bed-load collisions." Earth Surface Dynamics 9, no. 4 (July 23, 2021): 755–70. http://dx.doi.org/10.5194/esurf-9-755-2021.

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Abstract. River rocks round through the process of impact attrition, whereby energetic collisions during bed-load transport induce chipping of the grain surface. This process is also important for bedrock erosion. Although previous work has shown that impact energy, lithology, and shape are controlling factors for attrition rates, the functional dependence among these quantities is not settled. Here we examine these factors using a double-pendulum apparatus that generates controlled collisions between two grains under conditions relevant for bed-load transport. We also determine the grain size distributions (GSDs) of the attrition products. Two experimental results appear to support previous treatments of impact erosion as brittle fracture: (i) mass loss is proportional to kinetic energy, and this proportionality is a function of previously identified material properties; and (ii) attrition-product GSDs are well described by a Weibull distribution. Chipping results from the development of shallow and surface-parallel cracks, a process that is distinct from bulk fragmentation that occurs at higher energies. We suggest that Hertzian fracture is the dominant mechanism of impact attrition for bed-load transport. We also identify an initial phase of rapid mass loss in which attrition is independent of energy and material properties; this is a shape effect associated with removal of very sharp corners. The apparent universality of both mass loss curves and attrition-product GSDs requires further investigation. Nonetheless, these findings are useful for interpreting the contribution of in-stream attrition to downstream fining and the production of sand resulting from bed-load transport of river pebbles.

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Taylor, Gloria, Lin Johnson McGaw, Gwen Mayes, Thomas J. Cossé, and Terry M. Weisenberger. "The Coordinator Attrition Problem in the United States: Myth or Reality?" Journal of Transplant Coordination 8, no. 2 (June 1998): 88–92. http://dx.doi.org/10.1177/090591999800800206.

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Excessive attrition among organ procurement coordinators has been a suspected problem for many years. In 1994 the United Network for Organ Sharing undertook a procurement coordinator attrition study. Initially, focus groups were conducted in conjunction with the 1994 North American Transplant Coordinators Organization's annual meeting. In 1996, 69 executive directors from organ procurement organizations were surveyed on the subject of procurement coordinator attrition. Thirty-five executive directors responded, resulting in a 51% response rate. The UNOS procurement coordinator attrition study explored actual attrition rates, relationships of certain demographic factors to attrition rates, economic impact of attrition on the organizations, and various job tenure issues. The period under study was January 1, 1990 through December 31, 1993. Results did not demonstrate an industry-wide attrition problem. Additionally, the study revealed no enduring attrition problem in any single organization, and some organizations were found to have no attrition during the entire study period.

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Guttman, Irwin, and Ingram Olkin. "Retention or Attrition Models." Journal of Educational Statistics 14, no. 1 (March 1989): 1–20. http://dx.doi.org/10.3102/10769986014001001.

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A model for retention and its counterpart, attrition, is presented. In a prototype example, students enter a program in each of k terms; some of the students complete the program, and the remainder leave. A key feature in the models proposed is that there is a dampening effect from term to term because the probability of leaving the program diminishes as the terms progress. The focus of this paper is the study of alternative models for the dampening in attrition rates. A number of alternative dampening effects are proposed that provide for different rates of attrition. Approximate maximum likelihood estimates for the underlying parameters in each model and a Bayesian analysis are provided.

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Cooper, Cindy L., Amy Whitehead, Edward Pottrill, Steven A. Julious, and Stephen J. Walters. "Are pilot trials useful for predicting randomisation and attrition rates in definitive studies: A review of publicly funded trials." Clinical Trials 15, no. 2 (January 23, 2018): 189–96. http://dx.doi.org/10.1177/1740774517752113.

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Background/aims: External pilot trials are recommended for testing the feasibility of main or confirmatory trials. However, there is little evidence that progress in external pilot trials actually predicts randomisation and attrition rates in the main trial. To assess the use of external pilot trials in trial design, we compared randomisation and attrition rates in publicly funded randomised controlled trials with rates in their pilots. Methods: Randomised controlled trials for which there was an external pilot trial were identified from reports published between 2004 and 2013 in the Health Technology Assessment Journal. Data were extracted from published papers, protocols and reports. Bland–Altman plots and descriptive statistics were used to investigate the agreement of randomisation and attrition rates between the full and external pilot trials. Results: Of 561 reports, 41 were randomised controlled trials with pilot trials and 16 met criteria for a pilot trial with sufficient data. Mean attrition and randomisation rates were 21.1% and 50.4%, respectively, in the pilot trials and 16.8% and 65.2% in the main. There was minimal bias in the pilot trial when predicting the main trial attrition and randomisation rate. However, the variation was large: the mean difference in the attrition rate between the pilot and main trial was −4.4% with limits of agreement of −37.1% to 28.2%. Limits of agreement for randomisation rates were −47.8% to 77.5%. Conclusion: Results from external pilot trials to estimate randomisation and attrition rates should be used with caution as comparison of the difference in the rates between pilots and their associated full trial demonstrates high variability. We suggest using internal pilot trials wherever appropriate.

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Ellsworth, Richard K. "Beyond Attrition Analysis for Estimating Customer Relationship Remaining Life." Business Valuation Review 27, no. 2 (January 1, 2008): 85–89. http://dx.doi.org/10.5791/0882-2875-27.2.85.

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Abstract Attrition analysis is recognized by valuation professionals as a simple method to estimate customer population life characteristics. With attrition analysis, customer retirement rates are assumed to be constant across the age vintages of the population. However, many customer populations exhibit irregular retirement rates across population age vintages such that relaxation of the constant attrition rate assumption alters the population remaining life characteristics.

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Parish, Colin. "Less focus on academic ability cuts attrition rates." Nursing Standard 17, no. 51 (September 3, 2003): 5. http://dx.doi.org/10.7748/ns.17.51.5.s4.

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Binning, Rae. "Part-Time courses help keep attrition rates low." Nursing Standard 22, no. 33 (April 23, 2008): 32. http://dx.doi.org/10.7748/ns.22.33.32.s40.

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Waters, Adele. "Government data on attrition rates unreliable, experts claim." Nursing Standard 20, no. 47 (August 2, 2006): 12. http://dx.doi.org/10.7748/ns.20.47.12.s13.

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Kirby, Craig. "RCN to begin research on high attrition rates." Nursing Standard 12, no. 36 (May 27, 1998): 51. http://dx.doi.org/10.7748/ns.12.36.51.s54.

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Glisic, Sanja, Slobodan Paessler, Nevena Veljkovic, Vladimir R. Perovic, Jelena Prljic, and Veljko Veljkovic. "Improving attrition rates in Ebola virus drug discovery." Expert Opinion on Drug Discovery 10, no. 9 (June 30, 2015): 1025–32. http://dx.doi.org/10.1517/17460441.2015.1062872.

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Gahn, C., and A. Mersmann. "Theoretical Prediction and Experimental Determination of Attrition Rates." Chemical Engineering Research and Design 75, no. 2 (February 1997): 125–31. http://dx.doi.org/10.1205/026387697523570.

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Christensen, Larissa, Stefanie Sharman, and Martine Powell. "Professionals' Views on Child Sexual Abuse Attrition Rates." Psychiatry, Psychology and Law 22, no. 4 (November 14, 2014): 542–58. http://dx.doi.org/10.1080/13218719.2014.960036.

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O’Donnell, Hugh. "The emotional impact of nursing student attrition rates." British Journal of Nursing 17, no. 12 (June 2008): 745–54. http://dx.doi.org/10.12968/bjon.2008.17.12.42891.

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van Zanten, Marta, John R. Boulet, Danette McKinley, and Gerald P. Whelan. "Attrition Rates of Residents in Postgraduate Training Programs." Teaching and Learning in Medicine 14, no. 3 (July 2002): 175–77. http://dx.doi.org/10.1207/s15328015tlm1403_7.

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Hall, Steven E. "Chemoproteomics-driven drug discovery: addressing high attrition rates." Drug Discovery Today 11, no. 11-12 (June 2006): 495–502. http://dx.doi.org/10.1016/j.drudis.2006.04.014.

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Lang, Marvel. "Student Retention in Higher Education: Some Conceptual and Programmatic Perspectives." Journal of College Student Retention: Research, Theory & Practice 3, no. 3 (November 2001): 217–29. http://dx.doi.org/10.2190/l0rl-328m-4vvg-wkub.

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Over the past two decades the attrition of students in higher education has raised grave concerns. These concerns were raised initially over the higher rates of attrition of minority students in the early 1980s following a decade of record rates of minority enrollment in higher education institutions during the 1970s. However, by the mid-1980s the rates of high attrition of African-American and Hispanic students had grabbed the attention of the academic community across the country. When scholars and higher education administrators began to take notice of the higher rates of attrition of minority students they found out that student dropout and attrition in higher education institutions was a problem with all students, not just students of color. This article summarizes and presents perspectives on the causes of attrition and the problems of the retention of students in higher education. These ideas and perspectives are based on what has been learned from research on student retention over the past two decades. Also, programmatic strategies that have been implemented at institutions are summarized as examples of student retention initiatives that have had significant impacts.

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Zhu, Jinhui, Mohammed Adnan Yousuf, Wenmin Yang, Qiuying Zhu, Zhiyong Shen, Guanghua Lan, Yi Chen, et al. "Mortality and Attrition Rates within the First Year of Antiretroviral Therapy Initiation among People Living with HIV in Guangxi, China: An Observational Cohort Study." BioMed Research International 2021 (February 10, 2021): 1–10. http://dx.doi.org/10.1155/2021/6657112.

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Objective. To assess the mortality and attrition rates within the first year of antiretroviral therapy (ART) initiation among people living with human immunodeficiency virus (PLHIV) in rural Guangxi, China. Design. Observational cohort study. Setting. The core treatment indicators and data were collected with standard and essential procedures as per the Free ART Manual guidelines across all the rural health care centers of Guangxi. Participants. 58,115 PLHIV who were under ART were included in the study. Interventions. The data collected included sociodemographic characteristics that consist of age, sex, marital status, route of HIV transmission, CD4 cell count before ART, initial ART regimen, level of ART site, and year of ART initiation. Primary and Secondary Outcome Measures. Mortality and attrition rate following ART initiation. Results. The average mortality rate was 5.94 deaths, and 17.52 attritions per 100 person-years within the first year of ART initiation among PLHIV. The mortality rate was higher among intravenous drug users (Adjusted Hazard Ratio (AHR) 1.27, 95% Confidence Interval (CI) 1.14-1.43), prefecture as a level of ART site (AHR 1.14, 95% CI 1.02-1.28), and county as the level of ART site (AHR 2.12, 95% CI 1.90-2.37). Attrition was higher among intravenous drug users (AHR 1.87, 95% CI 1.75-2.00), the first-line ART containing AZT (AHR 1.09, 95% CI 1.03-1.16), and first-line ART containing LVP/r (AHR 1.34, 95% CI 1.23-1.46). Conclusion. The mortality and attrition rates were both at the highest level in the first year of post-ART; continued improvement in the quality of HIV treatment and care is needed.

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Glitza, Isabella Claudia, David Hui, Gary B. Chisholm, and Eduardo Bruera. "Attrition rates, reasons, and predictive factors in supportive/palliative oncology clinical trials at a comprehensive cancer center." Journal of Clinical Oncology 30, no. 15_suppl (May 20, 2012): 9069. http://dx.doi.org/10.1200/jco.2012.30.15_suppl.9069.

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9069 Background: Attrition is common among supportive/palliative oncology clinical trials. Few studies have documented the reasons and predictors for dropout. We aimed to determine the rate, reasons and factors associated with attrition both before reaching the primary endpoint (PE) and the end of study (EOS). Methods: We conducted a review of all prospective interventional supportive/palliative oncology trials by our department between 1999-2010. Patient and study characteristics and attrition data were extracted. We determined factors associated with attrition using multivariate logistic regression analysis. Results: 15 blinded randomized trials and 3 single arm trials were included. 16 of 18 studies did not reach accrual target. Baseline demographics for the 1214 patients were: median age 60 (range 23-93 years), female 56%, Caucasians 69%, ECOG performance status ≥3 41%, gastrointestinal malignancies (23%), median fatigue 7/10, appetite 5/10 and pain 4/10. Attrition rate was 26% (N=311) for PE and 44% (N=535) for EOS. Common reasons for EOS dropout were patient preference (N=93, 17%), symptom burden (N=87, 16%), death (N=45, 8%) and hospital admission (N=43, 8%), and were similar for PE dropouts. No predictors were identified for PE attrition. The Table shows poor performance status, anorexia and dyspnea are associated with EOS attrition in multivariate analysis. Conclusions: We found that attrition rate was high amongsupportive/palliative oncology clinical trials, and was associated with poor function and high baseline symptom burden. These findings have implications for future study designs including eligibility criteria and sample size calculation. [Table: see text]

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Stadler, Dora J., Halah Ibrahim, Debalina Dutta, Joseph Cofrancesco, and Sophia Archuleta. "Program Director Retention and Attrition Rates in International Graduate Medical Education." Journal of Graduate Medical Education 12, no. 5 (October 1, 2020): 624–27. http://dx.doi.org/10.4300/jgme-d-20-00014.1.

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ABSTRACT Background Program directors (PDs) are integral to the education of the next generation of physicians. Yet, administrative burdens, substantial patient care responsibilities, and lack of protected time for teaching may contribute to work-life imbalance and physician burnout, leading to high rates of attrition. Data on international residency program leadership turnover are lacking. Objective This study aimed to quantify PD turnover in Accreditation Council for Graduate Medical Education-International (ACGME-I) accredited programs in Singapore, United Arab Emirates (UAE), and Qatar, and to compare to US PD attrition rates. Methods Data on PD turnover in international programs was extracted from the ACGME-I Accreditation Data System for academic years 2010–2011 through 2018–2019 for Singapore and 2013–2014 through 2018–2019 for UAE and Qatar. Rates of PD turnover were calculated by country and by ACGME-I medical-, surgical-, and hospital-based specialty groupings and compared using χ2 test. Annual US PD turnover data was extracted from the ACGME's Data Resource Book. Results Seventy programs met inclusion criteria. International PD attrition was high, with 56 programs (80%) changing PDs since program inception, and 16 programs (29%) having 2 or more PD turnovers. There was no significant difference between PD turnover rates in hospital (83%), medical (79%), or surgical (78%) specialties. International PD attrition rates varied from 7% to 20% annually and were comparable to PD turnover in US programs (range 12%–15%). Conclusions High PD turnover rates in newly accredited international residency programs were noted, although annual attrition rates were comparable to US residency programs.

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Arentze, Theo, Aloys Borgers, Maarten Ponjé, and Harry Timmermans. "Determinants of Attrition Rates in Two-Wave, Two-Day Household Activity Diary: Probit Analysis." Transportation Research Record: Journal of the Transportation Research Board 1719, no. 1 (January 2000): 159–64. http://dx.doi.org/10.3141/1719-21.

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Transportation researchers often have used panel data to examine the dynamics of travel behavior. Although panel data are probably the best means by which to better understand choice dynamics, they present various challenges to the analyst, with attrition or dropout one of the most critical. Presented are the results of an analysis of the determinants of attrition in a two-wave panel, conducted in the Netherlands. Panelists reported their activities for a consecutive 2 days with 1 year between. Attrition rates between the two waves were predicted as a function of sociodemographics; number of activities, trips and tours; and the amount of reporting error in the first wave, by using a probit model. The results of the study indicate that none of these variables was significant, suggesting that no systematic attrition occurred between the two waves.

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Higgins, Bonnie. "Strategies for Lowering Attrition Rates and Raising NCLEX-RN® Pass Rates." Journal of Nursing Education 44, no. 12 (December 1, 2005): 541–47. http://dx.doi.org/10.3928/01484834-20051201-03.

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Sass, Daniel Allen, Belinda Bustos Flores, Lorena Claeys, and Bertha Pérez. "Identifying Personal and Contextual Factors that Contribute to Attrition Rates for Texas Public School Teachers." education policy analysis archives 20 (May 30, 2012): 15. http://dx.doi.org/10.14507/epaa.v20n15.2012.

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Teacher attrition is a significant problem facing schools, with a large percentage of teachers leaving the profession within their first few years. Given the need to retain high-quality teachers, research is needed to identify those teachers with higher retention rates. Using survival analyses and a large state dataset, researchers examined teacher data to identify those teacher and school variables associated with attrition. Unique to this study was the investigation of testing era (basic competency vs. higher standards based), school districts’ yearly ratings based on state-mandated testing, and charter school status. Analyses revealed that teacher attrition was greater during the high stakes-testing era, at low-performing schools, and for charter schools; however, beginning teacher age, gender, and school level moderated several attrition rates. Implications for public policy are discussed.

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Egilsson, Erlendur, Ragnar Bjarnason, and Urdur Njardvik. "Usage and Weekly Attrition in a Smartphone-Based Health Behavior Intervention for Adolescents: Pilot Randomized Controlled Trial." JMIR Formative Research 5, no. 2 (February 17, 2021): e21432. http://dx.doi.org/10.2196/21432.

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Background The majority of adolescents own smartphones, although only 8% of them use health apps. Attrition rates from adolescent mobile health (mHealth) interventions for treating mental health problems such as anxiety and depression are an issue with a high degree of variation. Attrition in mHealth interventions targeting adolescent populations is frequently presented in a two-point fashion, from initiation of the intervention to the end of treatment, lacking more time-specific information on usage and times of attrition. Self-efficacy could provide an avenue to lower attrition rates, although a better understanding of the relationship between mental health factors and time-specific attrition rates is needed. Objective The aims of this study were to obtain time-specific attrition rates among adolescents in an mHealth intervention, and to describe the intervention’s usage and feasibility in relation to adolescent self-efficacy levels, and emotional and physical health. Methods A single-center randomized controlled public school pilot trial was undertaken with 41 adolescents. Outcome measures were assessed at baseline and after 6 weeks, while in-app activity and attrition rates were continually assessed throughout the intervention period. The primary outcome was attrition based on time and type of in-app health behavior usage, and feasibility of the mHealth app. Secondary outcome measures were self-efficacy levels, depressive and anxiety symptoms, as well as standardized BMI and sleep. Analyses of group mean variances with adjusted α levels through Bonferroni corrections were used to assess main outcome effects. Results The attrition from initiation of the intervention to 6-week follow up was 35%. Attrition started in the third week of the intervention and was related to daily time of app usage (Rt=0.43, P<.001). The number of average weekly in-app health exercises completed decreased significantly from the first week of the intervention (mean 55.25, SD 10.96) to the next week (mean 13.63, SD 2.94). However, usage increased by 22% between week 2 and the last week of the intervention (mean 16.69, SD 8.37). Usability measures revealed satisfactory scores (mean 78.09, SD 9.82) without gender differences (P=.85). Self-reported daily physical activity increased by 19.61% in the intervention group but dropped by 26.21% among controls. Self-efficacy levels increased by 8.23% in the invention arm compared to a 3.03% decrease in the control group. Conclusions This pilot study demonstrated the feasibility and usability of an mHealth intervention among adolescent participants. Indications were toward beneficial effects on physical and mental health that warrant further research. Focus on time-specific attrition measures alongside daily times of usage and ways to increase participants’ self-efficacy levels appear to be a promising avenue for research on mHealth interventions for adolescent populations with the aim to ultimately lower attrition rates.

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Glitza, Isabella Claudia, David Hui, Eduardo Bruera, and Gary B. Chisholm. "Attrition rates, reasons, and predictive factors in supportive/palliative oncology clinical trials at a comprehensive cancer center." Journal of Clinical Oncology 30, no. 34_suppl (December 1, 2012): 108. http://dx.doi.org/10.1200/jco.2012.30.34_suppl.108.

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108 Background: Attrition is common among supportive/palliative oncology clinical trials. Few studies have documented the reasons, and predictors for dropout. We aimed to determine the rate, reasons, and factors associated with attrition both before reaching the primary endpoint (PE) and the end of study (EOS). Methods: We conducted a review of all prospective interventional supportive/palliative oncology trials in our department between 1999 to 2011. Patient and study characteristics and attrition data were extracted. Results: 1,214 patients were included in 18 clinical trials. The median age was 60, performance status ≥3 41%, median fatigue 7/10, and median dyspnea 2/10. The attrition rate was 26% (95% confidence interval [CI] 23%-28%) for PE and 44% (95% confidence interval 41%-47%) for EOS. Common reasons for EOS dropout were patient preference (N=93, 17%), symptom burden (N=87, 16%), death (N=45, 8%), and hospital admission (N=43, 8%). At the patient level, EOS attrition was associated with Hispanic race (OR=1.88, 95% CI 1.27-2.78), higher baseline intensity of fatigue (odds ratio [OR]=1.09 per point, 95% CI 1.02-1.16), and dyspnea (OR=1.06, 95% CI 1.02-1.11) in multivariate analysis. At the study level, longer study duration (Spearman correlation 0.59, P=0.01) and outpatient studies (47% vs. 6%, P=0.05) were also associated with higher EOS dropouts. Higher dyspnea, fatigue, and longer study duration were associated with PE attrition. Conclusions: The attrition rate was high amongsupportive/palliative oncology clinical trials, and was associated with various patient characteristics and high baseline symptom burden. These findings have implications for future study designs including eligibility criteria and sample-size calculation.

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Tsang, Erica S., Howard John Lim, Daniel John Renouf, Janine Marie Davies, Jonathan M. Loree, and Sharlene Gill. "Real-world treatment attrition rates in advanced esophagogastric cancer." Journal of Clinical Oncology 38, no. 15_suppl (May 20, 2020): e19301-e19301. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.e19301.

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e19301 Background: Over the last decade, multiple agents have demonstrated efficacy for advanced esophagogastric cancer (EGC). Despite the availability of later lines of therapy, there remains limited real-world data about the treatment attrition rates between lines of therapy. We sought to characterize the use and attrition rates between lines of therapy for patients with advanced EGC. Methods: We identified patients who received at least one cycle of chemotherapy for advanced EGC between July 1, 2017 and July 31, 2018 across 6 regional centers in British Columbia (BC), Canada. Clinicopathologic, treatment, and outcomes data were extracted by chart review. Patients who continued on treatment were censored at the date of last contact. Results: Of 245 patients who received at least one line of therapy, median age was 65.7 years (IQR 58.2-72.3) and 186 (76%) were male, ECOG PS 0/1 (80%), gastric vs. GEJ (36% vs. 64%). Histologies included adenocarcinoma (78%), squamous cell carcinoma (8%), and signet ring (14%), with 31% HER2 positive. 72% presented with de novo disease, and 25% had received previous chemoradiation. There was a high level of treatment attrition, with patients receiving only one line of therapy (n = 122, 50%), two lines (n = 83, 34%), three lines (n = 34, 14%), and four lines (n = 6, 2%). Kaplan-Meier survival analysis demonstrated improved survival with increasing lines of therapy (median overall survival 7.7 vs. 16.6 vs. 22.8 vs. 40.4 months, p< 0.05). On multivariable Cox regression, improved survival was associated with better baseline ECOG and increased lines of therapy ( p< 0.05). Conclusions: The steep attrition rates between therapies highlight the unmet need for more efficacious earlier-line treatment options for patients with advanced EGC. [Table: see text]

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Tsang, Erica S., Howard John Lim, Daniel John Renouf, Janine Marie Davies, Jonathan M. Loree, and Sharlene Gill. "Real-world treatment attrition rates in advanced esophagogastric cancer." Journal of Clinical Oncology 38, no. 4_suppl (February 1, 2020): 317. http://dx.doi.org/10.1200/jco.2020.38.4_suppl.317.

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317 Background: Over the last decade, multiple agents have demonstrated efficacy for advanced esophagogastric cancer (EGC), including ramucirumab, irinotecan, trifluridine/tipiracil, and immunotherapy. Despite the availability of later lines of therapy, there remains limited real-world data about the treatment attrition rates between lines of therapy. We sought to characterize the use and attrition rates between lines of therapy for patients with advanced EGC. Methods: We identified patients who received at least one cycle of chemotherapy for advanced EGC between July 1, 2017 and July 31, 2018 across 6 regional centers in British Columbia (BC), Canada. Clinicopathologic, treatment, and outcomes data were extracted by chart review. Results: Of 169 patients who received at least one line of therapy, median age was 65.2 years (IQR 58-72) and 128 (76%) were male, ECOG PS 0/1 (84%), gastric vs GEJ (35% vs 65%). Histologies included adenocarcinoma (76%), squamous cell carcinoma (10%) and signet ring (14%), with 26% HER2 positive. 62% presented with de novo disease, and 35% had received previous chemoradiation. There was a high level of treatment attrition, with patients receiving only one line of therapy (n = 73, 43%), two lines (n = 65, 38%), three lines (n = 25, 15%), and four lines (n = 6, 4%). Kaplan-Meier survival analysis demonstrated improved survival with increasing lines of therapy (median overall survival 9.6 vs. 18.5 vs. 25.8 vs. 40.7 months, p< 0.05). On multivariable Cox regression, improved survival was associated with better baseline ECOG, longer duration of first-line therapy, and increased lines of therapy ( p< 0.01). Conclusions: The steep attrition rates between therapies highlight the unmet need for more efficacious earlier-line treatment options for patients with advanced EGC. [Table: see text]

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Wang, Alan L. T., and John F. Stubington. "Char Attrition from Australian Black Coals in Pressurized Fluidized Bed Combustion." Journal of Energy Resources Technology 125, no. 2 (June 1, 2003): 113–18. http://dx.doi.org/10.1115/1.1524330.

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Char attrition is the main mechanism for the fine char generation in PFBC. The char attrition rates were significantly different for each of the two coal chars tested. Specific char attrition rate increased with the surface porosity of burning char particles. A coal with higher ratio of telocollinite/inertinite contents formed chars in PFBC with larger pores or higher porosity during devolatilization, which resulted in a higher specific attrition rate.

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Rose, Helen. "Attrition rates mean caution is needed over nurse numbers." Nursing Standard 24, no. 3 (September 23, 2009): 32–33. http://dx.doi.org/10.7748/ns.24.3.32.s45.

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Tsang, Erica S., Howard J. Lim, Daniel J. Renouf, Janine M. Davies, Jonathan M. Loree, and Sharlene Gill. "Real-world treatment attrition rates in advanced esophagogastric cancer." World Journal of Gastroenterology 26, no. 39 (October 21, 2020): 6027–36. http://dx.doi.org/10.3748/wjg.v26.i39.6027.

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Gillen, Sally. "Is enough being done to reduce undergraduate attrition rates?" Nursing Standard 27, no. 8 (October 24, 2012): 12–13. http://dx.doi.org/10.7748/ns2012.10.27.8.12.p9716.

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Arrowsmith, John, and Philip Miller. "Phase II and Phase III attrition rates 2011–2012." Nature Reviews Drug Discovery 12, no. 8 (August 2013): 569. http://dx.doi.org/10.1038/nrd4090.

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Ormrod, David, and Benjamin Turnbull. "Attrition rates and maneuver in agent-based simulation models." Journal of Defense Modeling and Simulation: Applications, Methodology, Technology 14, no. 3 (February 2017): 257–72. http://dx.doi.org/10.1177/1548512917692693.

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Hutchinson, Lisa, and Rebecca Kirk. "High drug attrition rates—where are we going wrong?" Nature Reviews Clinical Oncology 8, no. 4 (March 30, 2011): 189–90. http://dx.doi.org/10.1038/nrclinonc.2011.34.

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Withiel, Toni, Lucinda Marr, and Genevieve Juj. "'Right fit, right job, right time': case study of a new model for allied health recruitment in public health settings." Australian Health Review 44, no. 1 (2020): 52. http://dx.doi.org/10.1071/ah18095.

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Objective Staff turnover remains a significant financial burden across the healthcare sector. Traditional approaches to recruitment continue to prioritise competency-based outcomes over the cultural fit of applicants. This brief case study sought to evaluate the effectiveness of a new recruitment intervention on allied health staff attrition rates at the Royal Melbourne Hospital, Australia. Methods The study used a single-site, prospective, mixed-methodology research design. Staff attrition rate, defined as the number of staff who ceased employment within 12 months of starting (both voluntarily and involuntarily), was selected as the primary outcome measure. Baseline data were collected in the 12 months before intervention roll out. Data were supplemented by surveying staff on interview panels and by feedback from consumer interview panel members. Results Descriptive analysis revealed that there was a decrease in the overall staff attrition rates following the introduction of the new recruitment model. Survey data revealed that interviewers rated the new recruitment strategy as more effective than traditional approaches. Several unique benefits associated with the inclusion of consumer advocates were also identified. Conclusion A behaviourally grounded recruitment approach to allied health improves overall staff attrition over traditional competency-based models.

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Journal articles on the topic 'Attrition rates'

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