Introduction: Only recently has perinatal posttraumatic stress disorder (PTSD) been researched in any depth; however, the causes and consequences of this serious illness remain unclear. Most commonly, childbirth trauma and interpersonal violence have been reported as contributing factors. However, not all Native Hawaiian/Pacific Islander (NHPI) women who experience these events experience PTSD. The factors affecting PTSD are many and complex, intertwining individual, family, and community contexts. Using a socioecological framework, 3 levels of contextual variables were incorporated in this study (individual, family, and social/community). The purpose of this study was to determine the socioecological predictors associated with prenatal PTSD among NHPI.
Methods: A case-control design was used to collect retrospective data about socioecological variables from medical record data. The sample was low-income, high-risk NHPI women receiving perinatal health care at a rural community health center in Hawaii who screened positive (n = 55) or negative (n = 91) for PTSD.
Results: Hierarchical logistic regression was conducted to determine socioecological predictors of positive PTSD screening. Although the majority of women (66.4%) experienced some form of interpersonal violence, a constellation of significant predictor variables from all 3 levels of the model were identified: depression (individual level), lack of family support and family stress (family level), and violence (social/community level).
Discussion: Each of the predictor variables has been identified by other researchers as significantly affecting perinatal PTSD. However, it is because these variables occur together that a more complex picture emerges, suggesting the importance of considering multiple variables in context when identifying and caring for these women. Although additional research is needed, it is possible that the significant predictor variables could be useful in identifying women who are at higher risk for PTSD in other similar populations.
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http://dx.doi.org/10.1111/jmwh.12211 | DOI Listing |
Hosp Pediatr
January 2025
Pediatric Critical Care, Lucile Packard Children's Hospital Stanford, Palo Alto, California.
Objectives: Pediatric neurocritical care (PNCC) patients experience high rates of morbidity, but comprehensive follow-up is not universal. We sought to identify predictors of functional decline in these children to guide future resource allocation.
Patients And Methods: We conducted a prospective observational study in a quaternary children's hospital pediatric intensive care unit (PICU) from July 2023 to December 2023.
Andes Pediatr
August 2023
Facultad de Medicina, Universidad de la República, Montevideo, Uruguay.
Unlabelled: Acute lower respiratory infections (ALRI) are the main cause of hospitalization during the winter season. High-flow nasal catheter (HFNC) has been established as part of the treatment of these infections.
Objective: To characterize the population of children with acute hypoxemic respiratory failure treated with HFNC and to determine the predictors of failure of this therapy.
Andes Pediatr
August 2023
Instituto de Cardiología, Bogotá, Colombia.
Unlabelled: The Pediatric Index of Mortality 3 (PIM3) is a scale that estimates the risk of mortality in children admitted to the Pediatric Intensive Care Unit (PICU) within the first hour of admission.
Objective: to validate the PIM3 scale in pediatric population admitted to PICU at altitudes over 2,500 meters above sea level (m.a.
This study aimed to assess the effectiveness of repeated subgingival instrumentation combined with 980 nm diode laser decontamination in the non-surgical treatment of deep periodontal pockets. A total of 40 otherwise healthy patients with generalized periodontitis, encompassing 1,168 sites with deep pockets, were included and baseline PPD, bleeding on probing (BOP), gingival recession (REC), clinical attachment level (CAL), and plaque index (PI) were recorded. Each patient underwent non-surgical laser-assisted periodontal therapy and was enrolled in a maintenance program with three-month recall visits during the first year of follow-up.
View Article and Find Full Text PDFJ Med Syst
January 2025
Department of Computing, University of North Florida, 1 UNF Dr., Jacksonville, 32246, FL, USA.
The "no-show" problem in healthcare refers to the prevalent phenomenon where patients schedule appointments with healthcare providers but fail to attend them without prior cancellation or rescheduling. In addressing this issue, our study delves into a multivariate analysis over a five-year period involving 21,969 patients. Our study introduces a predictive model framework that offers a holistic approach to managing the no-show problem in healthcare, incorporating elements into the objective function that address not only the accurate prediction of no-shows but also the management of service capacity, overbooking, and idle resource allocation resulting from mispredictions.
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