Background: The Pediatric Symptom Checklist-17 (PSC-17) is a widely used, briefer version of the PSC-35, a parent-completed measure of children's psychosocial functioning. Despite the extensive use of the PSC-17 over the past 15 years there has not been a large-scale replication of the original derivation study.
Objective: To examine the prevalence of positive screens, reliability, and factor structure of PSC-17 scores in a new national sample and compare them with the derivation sample.
Methods: Data were collected on 80 680 pediatric outpatients, ages 4 to 15 years, whose parents filled out the PSC-17 from 2006 to 2015 via the Child Health and Development Interactive System, an electronic system that presents and scores clinical measures.
Results: The rates of positive screening on the overall PSC-17 (11.6%) and on the internalizing (10.4%) and attention (9.1%) subscales were comparable to rates found in the original sample, although the rate of externalizing problems (10.2%) was lower than in the derivation study. Reliability was high (internal consistency 0.89; test-retest 0.85), and a confirmatory factor analysis provided support for the original 3-factor model.
Conclusions: Fifteen years after the PSC-17 was derived in a large nationally representative outpatient pediatric sample, a new and larger national sample found rates of positive screening, reliability, and factor structure that were comparable. Findings from this study support the continued use of the PSC-17 clinically as a screening tool in pediatric settings and in research.
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http://dx.doi.org/10.1542/peds.2016-0038 | DOI Listing |
PLoS One
January 2025
School of Civil and Architectural Engineering, Harbin University, Harbin, China.
This work explores an intelligent field irrigation warning system based on the Enhanced Genetic Algorithm-Backpropagation Neural Network (EGA-BPNN) model in the context of smart agriculture. To achieve this, irrigation flow prediction in agricultural fields is chosen as the research topic. Firstly, the BPNN principles are studied, revealing issues such as sensitivity to initial values, susceptibility to local optima, and sample dependency.
View Article and Find Full Text PDFLearn Health Syst
January 2025
Bioethics Research Center, Division of General Medical Sciences, Department of Medicine Washington University School of Medicine St. Louis Missouri USA.
Objectives: Patient engagement is critical for the effective development and use of artificial intelligence (AI)-enabled tools in learning health systems (LHSs). We adapted a previously validated measure from pediatrics to assess adults' openness and concerns about the use of AI in their healthcare.
Study Design: Cross-sectional survey.
JSES Int
November 2024
Brighton and Sussex Medical School, Brighton, United Kingdom.
Background: Coronoid fracture size is one important factor in decision-making on surgical vs. nonsurgical management. There is currently no reliable, standardized technique to measure coronoid fracture size or bone loss.
View Article and Find Full Text PDFF1000Res
January 2025
Economic, Universitas Diponegoro, Semarang, Central Java, 50275, Indonesia.
Background: The potential of Islamic crowdfunding to encourage the development of Islamic fintech globally, even in countries with non-Muslim majority populations, needs to be examined in a literature study on this issue. More extensive research is needed regarding the factors that most reliably predict the success of Islamic crowdfunding, such as compliance with Islamic crowdfunding laws, sustainability, and the potential of Islamic finance. This article describes a comprehensive and systematic Literature Review (SLR) regarding papers published in the field of Islamic crowdfunding.
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