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Results: 59
Psychological morbidity among suicide-bereaved and non-bereaved parents
OBJECTIVE: To determine how psychological premorbidity affects the risk of depression in parents who lost a child through suicide. DESIGN: Population-based survey. SETTING: Sweden, between 2009 and 2010. PARTICIPANTS: All...
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Viewing the body after bereavement due to suicide
BACKGROUND: Research on the assumed, positive and negative, psychological effects of viewing the body after a suicide loss is sparse. We hypothesized that suicide-bereaved parents that viewed their childs body in a formal...
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Depression among Parents Two to Six Years Following the Loss of a Child by Suicide
BACKGROUND: Parents who lose a child by suicide have elevated risks of depression. No clinical prediction tools exist to identify which suicide-bereaved parents will be particularly vulnerable; we aimed to create a prediction...
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Constructing Culturally-Authentic Differentiated Access Points Using the Content Imperatives
The need to create culturally authentic and specific learning experiences is a call to action that all teachers must answer. Current definitions of differentiation either avoid or exclude topics of culture and race. These...
The Home and Community Connections Model
A major myth of gifted education is the idea that gifted and advanced learners should already possess the knowledge and skills necessary to engage in rigorous learning experiences. This myth reinforces the underrepresentation of...
Insufficient communication and anxiety in cancer-bereaved siblings
OBJECTIVE: The purpose of this study was to examine siblings' long-term psychological health in relation to their perception of communication with their family, friends, and healthcare professionals during a brother or sister's...
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Accuracy in local staging of prostate cancer by adding a three-dimensional T2-weighted sequence with radial reconstructions in magnetic resonance imaging.
BACKGROUND: The evidence supporting the use of magnetic resonance imaging (MRI) in prostate cancer detection has been established, but its accuracy in local staging is questioned. PURPOSE: To investigate the additional value of...
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Distrust in the End-of-Life Care Provided to a Parent and Long-Term Negative Outcomes Among Bereaved Adolescents
Purpose Previous research shows that the death of a parent places children at risk for a number of negative outcomes. The role of trust in health care at the end of life has been acknowledged as crucial for patients and adult...
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Unresolved grief and its consequences. A nationwide follow-up of teenage loss of a parent to cancer 6-9 years earlier.
PURPOSE: The early loss of a parent is a tragedy and a serious life event. This study investigated grief resolution and morbidity in cancer-bereaved teenagers 6 to 9 years after the loss of a parent to cancer. METHODS: In a...
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Effect of Comorbidity on Prostate Cancer-Specific Mortality
Purpose To determine the effect of comorbidity on prostate cancer (PCa)-specific mortality across treatment types. Patients and Methods These are the results of a population-based observational study in Sweden from 1998 to 2012...
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Care at End of Life Influences Grief
BACKGROUND: A majority of cancer-bereaved siblings report long-term unresolved grief, thus it is important to identify factors that may contribute to resolving their grief. OBJECTIVE: To identify modifiable or avoidable family...
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Acute and long-term grief reactions and experiences in parentally cancer-bereaved teenagers.

Background

Previous research shows that many cancer-bereaved youths report unresolved grief several years after the death of a parent. Grief work hypothesis suggests that, in order to heal, the bereaved needs to process...
Published by: BMC palliative care
Machine Learning and Pharmacometrics for Prediction of Pharmacokinetic Data
Pharmacometrics (PM) and machine learning (ML) are both valuable for drug development to characterize pharmacokinetics (PK) and pharmacodynamics (PD). Pharmacokinetic/pharmacodynamic (PKPD) analysis using PM provides mechanistic...
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Machine Learning and Pharmacometrics for Prediction of Pharmacokinetic Data
Pharmacometrics (PM) and machine learning (ML) are both valuable for drug development to characterize pharmacokinetics (PK) and pharmacodynamics (PD). Pharmacokinetic/pharmacodynamic (PKPD) analysis using PM provides mechanistic...
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