Attrition can jeopardize both internal and external validity. The goal of this secondary analysis was to examine predictors of attrition using baseline data of 432 participants in the Rural Breast Cancer Survivors study. Attrition predictors were conceptualized based on demographic, social, cancer treatment, physical health, and mental health characteristics. Baseline measures were selected using this conceptualization. Bivariate tests of association, discrete-time Cox regression models and recursive partitioning techniques were used in analysis. Results showed that 100 participants (23%) dropped out by Month 12. Non-linear tree analyses showed that poor mental health and lack of health insurance were significant predictors of attrition. Findings contribute to future research efforts to reduce research attrition among rural underserved populations.
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http://dx.doi.org/10.1002/nur.21576 | DOI Listing |
JMIR Ment Health
December 2024
Department of Systems and Information Engineering, University of Virginia, Charlottesville, VA, United States.
Background: Digital mental health is a promising paradigm for individualized, patient-driven health care. For example, cognitive bias modification programs that target interpretation biases (cognitive bias modification for interpretation [CBM-I]) can provide practice thinking about ambiguous situations in less threatening ways on the web without requiring a therapist. However, digital mental health interventions, including CBM-I, are often plagued with lack of sustained engagement and high attrition rates.
View Article and Find Full Text PDFJ Neurol
December 2024
Biostatistics and Research Support, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
Objectives: Attrition due to adverse events and disease progression impacts the integrity and generalizability of clinical trials. The aim of this study is to provide evidence-based estimates of attrition for clinical trials in amyotrophic lateral sclerosis (ALS), and identify study-related predictors, through a comprehensive systematic review and meta-analysis.
Methods: We systematically reviewed the literature to identify all randomized, placebo-controlled clinical trials in ALS and determined the number of patients who discontinued the study per randomized arm.
J Appl Gerontol
December 2024
1Florida ADRC, University of Florida, Gainesville, FL, USA.
Attrition is a significant methodological concern in longitudinal studies. Sample loss can limit generalizability and compromise internal validity. Wave one ( = 346) and wave two follow-ups ( = 196) of the 1Florida ADRC clinical core were examined using a 24-month visit window.
View Article and Find Full Text PDFContemp Clin Trials
January 2025
Department of Population Health Sciences, University of Utah School of Medicine, USA.
Background: The Randomized Evaluation of Decision Support Interventions for Atrial Fibrillation (RED-AF) trial is a multi-site, randomized controlled clinical trial examining the effectiveness of a patient decision aid and an encounter decision aid in promoting shared decision-making (SDM) during a clinical encounter for patients with atrial fibrillation (AF). We sought to describe baseline characteristics of patients and clinicians in the trial and compare them to the demographics of the larger AF population. We also conducted an analysis of possible predictors of attrition rates at baseline, 6 and 12 months.
View Article and Find Full Text PDFJ Perinat Med
December 2024
John A. Burns School of Medicine, University of Hawai'i, and Hawai'i Pacific Health Medical Group, Honolulu, Hawaii, USA.
The retention of academic faculty, particularly in the field of Obstetrics and Gynecology (OB/GYN), has become a growing challenge in the post-COVID era. The healthcare landscape has been dramatically altered, leading to a "Great Exit" where a large number of faculty members are resigning or retiring early. This phenomenon is not just a financial burden as recruitment costs have skyrocketed, but also poses a threat to the stability and reputation of academic institutions.
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