Background: Several factors have been shown to influence first-time pass rates on the National Physical Therapy Examination (NPTE). It is unclear to what extent academic difficulty experienced by students in a physical therapist education program may affect NPTE pass rates. The effects of institutional status (public or private) and Carnegie Classification on NPTE pass rates also are unknown.
Objective: The aim of this study was to quantify the odds of failure on the NPTE for students experiencing academic difficulty and for institutional status and Carnegie Classification.
Design: This investigation was a retrospective population-based cohort study.
Methods: Quota sampling was used to recruit a random sample of 20 professional physical therapist education programs across the United States. Individual student demographic, preadmission, and academic performance data were collected, as were data on program-level variables and data indicating pass/fail performance on the NPTE. A generalized linear mixed-effects logistic regression model was used to adjust for confounding factors and to describe relationships among the key predictor variables-academic difficulty, institutional status, and Carnegie Classification-and the dependent variable, NPTE performance.
Results: Academic difficulty during a student's professional training was an independent predictor for NPTE failure. The odds of students who had academic difficulty (relative to students who did not experience academic difficulty) failing the NPTE were 5.89 (95% confidence interval=4.06-8.93). The odds of NPTE failure also varied depending on institutional status and Carnegie Classification.
Limitations: The findings related to Carnegie Classification and institutional status should be considered preliminary.
Conclusions: Student performance on the NPTE was influenced by multiple factors, but the most important, potentially modifiable risk factor for poor NPTE performance likely is academic difficulty during professional training.
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http://dx.doi.org/10.2522/ptj.20080400 | DOI Listing |
J Relig Health
January 2025
School of Social Work, Hadassah Academic College, Jerusalem, Israel.
Religious informal helpers may play a crucial role in recognizing and providing referrals to mental health professional for at-risk individuals, including those with mental illness, especially since members of religious communities tend to conceal their difficulties and to view religious leaders as a sole source of assistance. This quantitative study aimed to explore Jewish bathhouse attendants ("balaniyot") who assist women in their monthly immersion, a unique situation in which mental health symptoms (e.g.
View Article and Find Full Text PDFAnn Fam Med
January 2025
University of Saskatchewan, School of Rehabilitation Sciences, Saskatoon, Saskatchewan, Canada
Purpose: People who are transgender or gender diverse (PTGD) often experience difficulties navigating the health care system due to a variety of factors such as lack of knowledgeable and/or culturally competent clinicians, discrimination, and structural and/or socioeconomic barriers. We sought to determine whether a peer health navigator service in the Canadian province of Saskatchewan helped connect transgender and gender-diverse clients and health care practitioners (HCPs) to resources, and how this service changed their health care experiences.
Methods: Semistructured interviews were conducted with 9 clients and 9 HCPs.
MethodsX
June 2025
Department of Networking & Communications, School of Computing, SRM Institute of Science and Technology, Kattankulathur, Chennai, India.
Forecasting student performance with precision in the educational space is paramount for creating tailor-made interventions capable to boost learning effectiveness. It means most of the traditional student performance prediction models have difficulty in dealing with multi-dimensional academic data, can cause sub-optimal classification and generate a simple generalized insight. To address these challenges of the existing system, in this research we propose a new model Multi-dimensional Student Performance Prediction Model (MSPP) that is inspired by advanced data preprocessing and feature engineering techniques using deep learning.
View Article and Find Full Text PDFMidwifery
January 2025
Faculty of Nursing, University of Murcia, Department of Nursing, Spain.
Aim: To analyze the experiences of midwifery students in the care of pregnancy loss during their training.
Background: The care of pregnancy losses requires the acquisition of very specific non-technical skills by midwifery students. The training received by students about gestational grief requires the use of different methodologies to obtain the required skills.
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