Background: One of the most common problems in children that pain can not be managed adequately by the health workers. Knowledge level of nurses is an important factor in effective pain management.
Aims: This study was designed to determine intern nursing students' level of pediatric pain management knowledge (PPMK) and the affecting factors.
Design: The study used a descriptive, comparative, correlational, and cross-sectional design.
Settings: Research was conducted at a Nursing School of a State University.
Participants/subjects: The study was carried out on 72 pediatric nursing internship students.
Methods: Data were collected using a demographic data form for affecting factors such as grade point averages, age, gender, previous pain education, and self-sufficiency, and a pain management knowledge questionnaire consisting of six subdimensions: awareness of pain, pain physiopathology, barriers to pain management, pain diagnosis, pain assessment, and pain control. Data were analyzed using quartiles, correlation, regression analysis, and the Structural Equation Model.
Results: The mean age of the participants was 22.64 ± 1.02, and 63.9% of them self-evaluated their current knowledge as inadequate. The PPMK score was 67.58 ± 7.37 and the students got medium level scores from the overall subdimensions. On the other hand, they got the lowest scores from the pain control (29.35 ± 4.29) and the highest scores from the pain assessment (5.49 ± 1.55). A moderate level of significant relationship was found in the Structural Equation Model (p < .05).
Conclusions: The students were determined to have a moderate PPMK level and get the lowest scores, particularly from the pain control.
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http://dx.doi.org/10.1016/j.pmn.2019.06.012 | DOI Listing |
Background: Coronary heart disease (CHD) and depression frequently co-occur, significantly impacting patient outcomes. However, comprehensive health status assessment tools for this complex population are lacking. This study aimed to develop and validate an explainable machine learning model to evaluate overall health status in patients with comorbid CHD and depression.
View Article and Find Full Text PDFJMIR Res Protoc
January 2025
Department of Pediatrics, School of Medicine, University of Virginia, Charlottesville, VA, United States.
Background: Low back pain (LBP) is highly prevalent and disabling, especially in agriculture sectors. However, there is a gap in LBP prevention and intervention studies in these physically demanding occupations, and to date, no studies have focused on horticulture workers. Given the challenges of implementing interventions for those working in small businesses, self-management offers an attractive and feasible option to address work-related risk factors and manage LBP.
View Article and Find Full Text PDFPurpose: To determine the status of depression and its key influencing factors among Chinese older adults in different living situations.
Method: Data of 7,092 older adults were obtained from the China Health and Retirement Longitudinal Survey. This study analyzed key variables influencing depressive symptoms using random forest modeling and logistic regression.
Anesth Analg
January 2025
From the Discipline of Surgery, Medical School, The University of Western Australia, Perth, Western Australia, Australia.
PLoS One
January 2025
Clinical Research Center, University Hospitals Cleveland Medical Center, Cleveland, Ohio, United States of America.
Background: Patients receiving chiropractic spinal manipulation (CSM) for spinal pain are less likely to be prescribed opioids, and some evidence suggests that these patients have a lower risk of any type of adverse drug event. We hypothesize that adults receiving CSM for sciatica will have a reduced risk of opioid-related adverse drug events (ORADEs) over a one-year follow-up compared to matched controls not receiving CSM.
Methods: We searched a United States (US) claims-based data resource (Diamond Network, TriNetX, Inc.
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