Factors Influencing Patient Disclosure of Parkinson's Disease Genetic Testing Results to Relatives.

BACKGROUND: Persons with Parkinson's disease (PD) who have received genetic test results are faced with the decision of whether, and how, to share that information with family. Studies in other specialties have shown high rates of disclosure motivated by a sense of responsibility. Rates of, and attitudes surrounding, disclosure have yet to be reported in this population. OBJECTIVES: To explore the disclosure practices and motivations of patients with PD regarding genetic test results, allowing insight to guide genetic counseling and navigation of test result discussions. METHODS: A cross-sectional online survey was distributed to adults with PD and previous genetic test results. Survey questions assessed demographics, genetic testing results and delivery, sharing behaviors, perceptions of PD, and motivations and barriers to family disclosure. RESULTS: Among respondents, 88.9% shared results with at least one family member, most often a child (73.5%) or sibling (65.4%). Seventy-four percent reported sharing results with someone outside of their family, most frequently a friend (88.4%). The most common motivation for disclosure was the perception that family members would want to know. Barriers to disclosure were lack of close relationships, understanding results, and perceived utility. CONCLUSIONS: Disclosure rates in this PD population were consistent with those in previously reported populations. Motivations were anchored in perceptions of utility and family desire for information, suggesting a need to adjust patient education to improve retention and to explore family dynamics and perceptions of results.

Genetic counseling, 2030: An on-demand service tailored to the needs of a price conscious, genetically literate, and busy world.

The practice of genetic counseling is going to be impacted by the public's expectation that goods, services, information, and experiences happen on demand, wherever and whenever people want them. Building from trends that are currently taking shape, this article looks just over a decade into the future-to 2030-to provide a description of how the field of genetics and genetic counseling will be changed, as well as advice for genetic counselors for how to prepare. We build from the prediction that a large portion of the general public will have access to their digitized whole genome sequence anytime, any place, on any device. We focus on five topics downstream of this prediction: public health, personal autonomy, polygenic scores (PGS), evolving clinical practices, and genetic privacy.

Why do parents discontinue health services for managing paediatric obesity? A multi-centre, qualitative study.

OBJECTIVE: To explore parents' reasons for discontinuing tertiary-level care for paediatric weight management. METHODS: Participants were parents of 10-17year olds (body mass index [BMI] ≥85th percentile) who were referred for paediatric weight management. Parents were recruited from three Canadian sites (Vancouver, BC; Edmonton, AB; Hamilton, ON) and were eligible if their children attended at least one clinical appointment and subsequently discontinued care. Data were collected using semi-structured individual interviews that were digitally recorded, transcribed, and analysed using an inductive manifest content analysis. RESULTS: Parents (n=29) of children [mean age: 14.7±1.8years; mean BMI percentile: 98.9±1.6; n=17 (58.6%) boys] were primarily female (n=26; 89.7%), Caucasian (n=22; 75.9%), and had a university degree (n=23; 79.3%). Reasons for discontinuing care were grouped into three categories: (i) family factors (e.g., perceived lack of progress, lack of family support, children's lack of motivation), (ii) logistical factors (e.g., monetary costs, distance, scheduling), and (iii) health services factors (e.g., unmet expectations of care, perceived limited menu of services, no perceived need for further support). CONCLUSIONS: A range of multi-level factors influenced attrition from tertiary-level paediatric weight management. Our data suggest that experimental research is needed to examine whether addressing reasons for attrition can enhance families' retention in care and ultimately improve health outcomes for children living with obesity.

Attrition and the management of pediatric obesity: an integrative review.

BACKGROUND: A key challenge in managing pediatric obesity is the high degree of program attrition, which can reduce therapeutic benefits and contribute to inefficient health services delivery. Our aim was to document and characterize predictors of, and reasons for, attrition in pediatric obesity management. METHODS: We searched literature published until January 2014 in five databases (CINAHL, EMBASE, MEDLINE, PsycINFO, and Scopus). Articles were included if they were English, included participants 0-18 years of age, focused on pediatric obesity management, incorporated lifestyle and behavioral changes without pharmacotherapy, provided attrition data, and reported information about predictors of, and/or reasons for, attrition from family-based interventions provided in research or clinical settings. Twenty-three articles (n=20 quantitative; n=2 qualitative; n=1 mixed methods) met our inclusion criteria. Clarity of study aims, objectives, methods, and data analysis were appraised using Bowling's checklist. RESULTS: Attrition varied according to definition (minimum to maximum, 4-83%; median, 37%). There were few consistent predictors of attrition between studies, although dropout was higher among US-based families receiving public health insurance. Older children were also more likely to discontinue care, but sex and baseline weight status did not predict attrition. The most commonly reported reasons for attrition were logistical barriers and programs not meeting families' needs. CONCLUSIONS: Developing and evaluating strategies designed to minimize the risk of attrition, especially among families who receive public health insurance and older boys and girls, are needed to optimize the effectiveness of pediatric obesity management.

Predictors of metabolically healthy obesity in children.

OBJECTIVE: To determine the prevalence of metabolically healthy obesity (MHO) in children and examine the demographic, adiposity, and lifestyle predictors of MHO status. RESEARCH DESIGN AND METHODS: This cross-sectional study included 8-17 year olds with a BMI ≥85th percentile who were enrolled in a multidisciplinary pediatric weight management clinic from 2005-2010. Demographic, anthropometric, lifestyle, and cardiometabolic data were retrieved by retrospective medical record review. Participants were dichotomized as either MHO or metabolically unhealthy obese (MUO) according to two separate classification systems based on: 1) insulin resistance (IR) and 2) cardiometabolic risk (CR) factors (blood pressure, serum lipids, and glucose). Multivariable logistic regression was used to determine predictors of MHO using odds ratios (ORs) with 95% CIs. RESULTS: The prevalence of MHO-IR was 31.5% (n = 57 of 181) and MHO-CR was 21.5% (n = 39 of 181). Waist circumference (OR 0.33 [95% CI 0.18-0.59]; P = 0.0002) and dietary fat intake (OR 0.56 [95% CI 0.31-0.95]; P = 0.04) were independent predictors of MHO-IR; moderate-to-vigorous physical activity (OR 1.80 [95% CI 1.24-2.62]; P = 0.002) was the strongest independent predictor of MHO-CR. CONCLUSIONS: Up to one in three children with obesity can be classified as MHO. Depending on the definition, adiposity and lifestyle behaviors both play important roles in predicting MHO status. These findings can inform for whom health services for managing pediatric obesity should be prioritized, especially in circumstances when boys and girls present with CR factors.

Can computerized clinical decision support systems improve practitioners' diagnostic test ordering behavior? A decision-maker-researcher partnership systematic review.

BACKGROUND: Underuse and overuse of diagnostic tests have important implications for health outcomes and costs. Decision support technology purports to optimize the use of diagnostic tests in clinical practice. The objective of this review was to assess whether computerized clinical decision support systems (CCDSSs) are effective at improving ordering of tests for diagnosis, monitoring of disease, or monitoring of treatment. The outcome of interest was effect on the diagnostic test-ordering behavior of practitioners. METHODS: We conducted a decision-maker-researcher partnership systematic review. We searched MEDLINE, EMBASE, Ovid's EBM Reviews database, Inspec, and reference lists for eligible articles published up to January 2010. We included randomized controlled trials comparing the use of CCDSSs to usual practice or non-CCDSS controls in clinical care settings. Trials were eligible if at least one component of the CCDSS gave suggestions for ordering or performing a diagnostic procedure. We considered studies 'positive' if they showed a statistically significant improvement in at least 50% of test ordering outcomes. RESULTS: Thirty-five studies were identified, with significantly higher methodological quality in those published after the year 2000 (p = 0.002). Thirty-three trials reported evaluable data on diagnostic test ordering, and 55% (18/33) of CCDSSs improved testing behavior overall, including 83% (5/6) for diagnosis, 63% (5/8) for treatment monitoring, 35% (6/17) for disease monitoring, and 100% (3/3) for other purposes. Four of the systems explicitly attempted to reduce test ordering rates and all succeeded. Factors of particular interest to decision makers include costs, user satisfaction, and impact on workflow but were rarely investigated or reported. CONCLUSIONS: Some CCDSSs can modify practitioner test-ordering behavior. To better inform development and implementation efforts, studies should describe in more detail potentially important factors such as system design, user interface, local context, implementation strategy, and evaluate impact on user satisfaction and workflow, costs, and unintended consequences.