Journal of evaluation in clinical practice
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Identifying whether perceived stigma or personal stigma more significantly affects nurses' attitudes towards seeking psychological help is essential for effectively addressing current challenges and facilitating early intervention for the well-being of nurses and their patients. ⋯ High levels of personal stigma negatively affect attitudes towards seeking psychological help; however, when considered alongside working in oncology and having a chronic illness, the impact of personal stigma becomes positive. Future research should delve deeper into these dynamics to develop targeted strategies for reducing personal stigma and enhancing help-seeking behaviors among nurses. Interventions are necessary to foster positive help-seeking attitudes among nurses and reduce stigma. Aligned with the findings of this study, training and awareness initiatives aimed at improving mental health literacy among nurses can play a pivotal role in reducing stigma and encouraging proactive use of mental health resources.
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Observational Study
Implementation of an Early Referral Programme for Patients With Hand Arthralgia.
Rheumatoid arthritis (RA) is a progressive autoimmune inflammatory disease. According to the European League Against Rheumatism (EULAR), the stages of RA progression include pre-RA, preclinical RA, inflammatory arthralgia, arthralgia with positive antibodies, arthralgia suspected of progressing to RA, undifferentiated arthritis and finally established RA. According to the Community Oriented Program for Control of Rheumatic Diseases (COPCORD), the prevalence of RA in Mexico is 1.6% [2], with approximately 10% of health problems addressed at the primary care level. ⋯ The implementation of this early referral programme significantly reduced the time in months for patients to access rheumatologic care.
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Understanding students' learning approach, modifying teaching methods, curriculum and material accordingly is essential to deliver quality education. Knowing more about the learning approaches assists in upgrading the profession's quality for continuous professional development. ⋯ The predominant approach is the deep learning approach reflecting active learning. This may indicate that curriculum and strategies of teaching are employed over physiotherapy students to promote quality learning. Also, the teaching preferences varies between two group of physiotherapy students. Thus, this will also assist physiotherapy educators in planning and delivering learning activities according to learners by knowing their preferences.
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Cancer patients experience substantial psychological distress which causes the reduction of the quality of life. However, the risk of psychological distress has not been well predicted especially in young- and middle-aged gynaecological cancer patients. This study aimed to develop a prediction model for psychological distress in young- and middle-aged gynaecological cancer patients using the artificial neural network (ANN). ⋯ Compared with the LR model, the ANN model shows obvious superiority across all assessment index outcomes, and it may be used as a decision-support tool for early identification of young- and middle-aged gynaecological cancer patients suffering from psychological distress.
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Limited health literacy (HL) leads to poor health outcomes, psychological stress, and misutilization of medical resources. Although interventions aimed at improving HL may be effective, identifying patients at risk of limited HL in the clinical workflow is challenging. With machine learning (ML) algorithms based on readily available data, healthcare professionals would be enabled to incorporate HL screening without the need for administering in-person HL screening tools. ⋯ Elastic-Net Penalized Logistic Regression had the best performance when compared with other ML algorithms with a c-statistic of 0.766, calibration slope/intercept of 1.044/-0.037, and a Brier score of 0.179. Over one-third of patients presenting to an outpatient spine center were found to have limited HL. While this algorithm is far from being used in clinical practice, ML algorithms offer a potential opportunity for identifying patients at risk for limited HL without administering in-person HL assessments. This could possibly enable screening and early intervention to mitigate the potential negative consequences of limited HL without taxing the existing clinical workflow.