MOTHER AND CHILD RESIDENTIAL TREATMENT FROM AN ADULT CHILD PERSPECTIVE: THE FORGOTTEN VOICES

These days most everyone can say that they know someone who has been impacted by substance abuse and today’s society is very familiar with the fact that it can wreak havoc on families. There has been a significant amount of research devoted to finding not only the best practices to treat families who are impacted by the disease of addiction but there has also been a great deal of attention focused on the adult perspective on these services once they have been received. Where the research is definitely lacking is how the children involved with the services perceive their own involvement. How are their lives impacted by being involved in treatment with their caretaker? The children seem to be the forgotten voices in this scenario. This study focuses on the adult/child perspective of children who have experienced at least one residential treatment episode with their mothers. The sample came from a long-term residential drug treatment facility that is primary focused on treating families impacted by substance abuse. These adult children experienced treatment with their mothers before they were 12 years old. They will share their perspectives on this experience

One Size Does Not Fit All: Meeting the Health Care Needs of Diverse Populations

Proposes a framework for meeting patients' cultural and linguistic needs: policies and procedures that support cultural competence, data collection, population-tailored services, and internal and external collaborations. Includes a self-assessment tool

Scientific Literacy in Central Appalachia Through Contextually Relevant Experiences: The “Reading the River” Project

Despite the best intentions of the United States educational system, implementing science reform efforts equitably and consistently throughout the nation is still a long-term goal. The light of scientific literacy has yet to shine brightly in many rural, isolated and economically depressed regions. Using Appalachia as a case in point, this paper provides a synopsis of the challenges of quality rural science education in the United States and the hope of new contextual and culturally relevant pedagogies aimed at engaging science students in inquiry research using their environmental surroundings as cognitive scaffoldings. The program Reading the River is showcased as an exemplary use of the students’ ‘backyard’ to integrate content knowledge in biology, chemistry, geology, physical science, social studies, practical living and mathematics

Factors Influencing Sleep Difficulty and Sleep Quantity in the Citizen Pscientist Psoriatic Cohort.

IntroductionSleep is essential for overall health and well-being, yet more than one-third of adults report inadequate sleep. The prevalence is higher among people with psoriasis, with up to 85.4% of the psoriatic population reporting sleep disruption. Poor sleep among psoriasis patients is particularly concerning because psoriasis is independently associated with many of the same comorbidities as sleep dysfunction, including cardiovascular disease, obesity, and depression. Given the high prevalence and serious consequences of disordered sleep in psoriasis, it is vital to understand the nature of sleep disturbance in this population. This study was designed to help meet this need by using survey data from Citizen Pscientist, an online patient portal developed by the National Psoriasis Foundation.MethodsOur analysis included 3118 participants who identified as having a diagnosis by a physician of psoriasis alone or psoriasis with psoriatic arthritis. Demographic information, psoriasis severity and duration, sleep apnea status, smoking and alcohol consumption, itch timing, and sleep characteristics were included. Two separate multivariate logistic regression models in STATA were used to determine whether the presence of psoriatic arthritis, age, gender, body mass index, comorbid sleep apnea, psoriasis severity, timing of worst itch, smoking status, or high-risk alcohol consumption were associated with sleep difficulty or low sleep quantity, defined by the American Academy of Sleep Medicine as less than 7 h of sleep per night on average.ResultsResults from the multivariate logistic regressions found that sleep difficulty was associated with psoriatic arthritis (OR 2.15, 95% CI [1.79-2.58]), female gender (2.03 [1.67-2.46]), obese body mass index (BMI ≥ 30) (1.25 [1.00-1.56]), sleep apnea (1.41 [1.07-1.86]), psoriasis severity of moderate (1.59 [1.30-1.94]) or severe (2.40 [1.87-3.08]), and smoking (1.60 [1.26-2.02]). Low sleep quantity was associated with obese BMI (1.62 [1.29-2.03]), sleep apnea (1.30 [1.01-1.68]), psoriasis severity of moderate (1.41 [1.16-1.72]) or severe (1.40 [1.11-1.76]), and smoking (1.62 [1.31-2.00]). Sleep difficulty and low sleep quantity were not associated with age, alcohol consumption, or timing of worst itch.ConclusionThese results are potentially meaningful in several aspects. We identify an important distinction between sleep difficulty and sleep quantity in psoriatic disease, whereby having psoriatic arthritis and being female are each associated with sleep difficulty despite no association with low sleep quantity. Furthermore, there is conflicting evidence from prior studies as to whether psoriasis severity is associated with sleep difficulty, but this well-powered, large study revealed a strong, graded relationship between psoriasis severity and both sleep difficulty and low sleep quantity. Overall, our results show that both sleep difficulty and low sleep quantity were associated with multiple factors in this analysis of a large psoriatic cohort. These findings suggest that dermatologists may gather clinically useful information by screening psoriatic patients for trouble sleeping and low sleep quantity to identify potential comorbidities and to more effectively guide disease management

Accuracy and Efficiency of Recording Pediatric Early Warning Scores Using an Electronic Physiological Surveillance System Compared With Traditional Paper-Based Documentation

Pediatric Early Warning Scores are advocated to assist health professionals to identify early signs of serious illness or deterioration in hospitalized children. Scores are derived from the weighting applied to recorded vital signs and clinical observations reflecting deviation from a predetermined "norm." Higher aggregate scores trigger an escalation in care aimed at preventing critical deterioration. Process errors made while recording these data, including plotting or calculation errors, have the potential to impede the reliability of the score. To test this hypothesis, we conducted a controlled study of documentation using five clinical vignettes. We measured the accuracy of vital sign recording, score calculation, and time taken to complete documentation using a handheld electronic physiological surveillance system, VitalPAC Pediatric, compared with traditional paper-based charts. We explored the user acceptability of both methods using a Web-based survey. Twenty-three staff participated in the controlled study. The electronic physiological surveillance system improved the accuracy of vital sign recording, 98.5% versus 85.6%, P < .02, Pediatric Early Warning Score calculation, 94.6% versus 55.7%, P < .02, and saved time, 68 versus 98 seconds, compared with paper-based documentation, P < .002. Twenty-nine staff completed the Web-based survey. They perceived that the electronic physiological surveillance system offered safety benefits by reducing human error while providing instant visibility of recorded data to the entire clinical team

Ovarian Cancer Epidemiology, Healthcare Access and Disparities (ORCHiD): Methodology for a Population-Based Study of Black, Hispanic and White Patients with Ovarian Cancer

INTRODUCTION: Less than 40% of patients with ovarian cancer (OC) in the USA receive stage-appropriate guideline-adherent surgery and chemotherapy. Black patients with cancer report greater depression, pain and fatigue than white patients. Lack of access to healthcare likely contributes to low treatment rates and racial differences in outcomes. The Ovarian Cancer Epidemiology, Healthcare Access and Disparities study aims to characterise healthcare access (HCA) across five specific dimensions-Availability, Affordability, Accessibility, Accommodation and Acceptability-among black, Hispanic and white patients with OC, evaluate the impact of HCA on quality of treatment, supportive care and survival, and explore biological mechanisms that may contribute to OC disparities. METHODS AND ANALYSIS: We will use the Surveillance Epidemiology and Ends Results dataset linked with Medicare claims data from 9744 patients with OC ages 65 years and older. We will recruit 1641 patients with OC (413 black, 299 Hispanic and 929 white) from cancer registries in nine US states. We will examine HCA dimensions in relation to three main outcomes: (1) receipt of quality, guideline adherent initial treatment and supportive care, (2) quality of life based on patient-reported outcomes and (3) survival. We will obtain saliva and vaginal microbiome samples to examine prognostic biomarkers. We will use hierarchical regression models to estimate the impact of HCA dimensions across patient, neighbourhood, provider and hospital levels, with random effects to account for clustering. Multilevel structural equation models will estimate the total, direct and indirect effects of race on treatment mediated through HCA dimensions. ETHICS AND DISSEMINATION: Result dissemination will occur through presentations at national meetings and in collaboration with collaborators, community partners and colleagues across othercancer centres. We will disclose findings to key stakeholders, including scientists, providers and community members. This study has been approved by the Duke Institutional Review Board (Pro00101872). Safety considerations include protection of patient privacy. All disseminated data will be deidentified and summarised

Importance sampling method of correction for multiple testing in affected sib-pair linkage analysis

Using the Genetic Analysis Workshop 13 simulated data set, we compared the technique of importance sampling to several other methods designed to adjust p-values for multiple testing: the Bonferroni correction, the method proposed by Feingold et al., and naïve Monte Carlo simulation. We performed affected sib-pair linkage analysis for each of the 100 replicates for each of five binary traits and adjusted the derived p-values using each of the correction methods. The type I error rates for each correction method and the ability of each of the methods to detect loci known to influence trait values were compared. All of the methods considered were conservative with respect to type I error, especially the Bonferroni method. The ability of these methods to detect trait loci was also low. However, this may be partially due to a limitation inherent in our binary trait definitions