Teaching medical students about children with disabilities in a rural setting in a school

Background: To describe and implement a community paediatric placement in a school setting that teaches undergraduate medical students about intellectual disability that provides benefit to the community and is acceptable to both students and teachers. Methods: Twenty six 4th year undergraduate medical students of the University of Newcastle completed their Paediatric studies based in Tamworth in 2004 & 2005 including an 8 week placement at Bullimbal School for Specific Purposes. The placement involved the students being actively involved in assisting with the delivery of a variety of activities aimed at improving the motor skills of a group of disabled children. De-identified data were obtained from completed evaluation surveys from 75% (21 of 26) of the medical students and from 100% (5 of 5) of the teachers. Results: All students and teachers found the placement was acceptable and enjoyed the placement and felt that it gave the medical students a greater understanding of children with disabilities. 80% (4 of 5) of the teachers involved in the program did not feel that its implementation added to their workload and all were enthusiastic to continue with the program. Conclusion: Medical students can be effectively taught and have a valuable clinical experience in a school setting to learn about children with a disability. This educational innovation has provided a mutual benefit for both the medical students and the school children who participated in the program without impacting on the workloads of teachers

Suicide ideation of individuals in online social networks

Suicide explains the largest number of death tolls among Japanese adolescents in their twenties and thirties. Suicide is also a major cause of death for adolescents in many other countries. Although social isolation has been implicated to influence the tendency to suicidal behavior, the impact of social isolation on suicide in the context of explicit social networks of individuals is scarcely explored. To address this question, we examined a large data set obtained from a social networking service dominant in Japan. The social network is composed of a set of friendship ties between pairs of users created by mutual endorsement. We carried out the logistic regression to identify users' characteristics, both related and unrelated to social networks, which contribute to suicide ideation. We defined suicide ideation of a user as the membership to at least one active user-defined community related to suicide. We found that the number of communities to which a user belongs to, the intransitivity (i.e., paucity of triangles including the user), and the fraction of suicidal neighbors in the social network, contributed the most to suicide ideation in this order. Other characteristics including the age and gender contributed little to suicide ideation. We also found qualitatively the same results for depressive symptoms.Comment: 4 figures, 9 table

Network 'small-world-ness': a quantitative method for determining canonical network equivalence

Background: Many technological, biological, social, and information networks fall into the broad class of 'small-world' networks: they have tightly interconnected clusters of nodes, and a shortest mean path length that is similar to a matched random graph (same number of nodes and edges). This semi-quantitative definition leads to a categorical distinction ('small/not-small') rather than a quantitative, continuous grading of networks, and can lead to uncertainty about a network's small-world status. Moreover, systems described by small-world networks are often studied using an equivalent canonical network model-the Watts-Strogatz (WS) model. However, the process of establishing an equivalent WS model is imprecise and there is a pressing need to discover ways in which this equivalence may be quantified. Methodology/Principal Findings: We defined a precise measure of 'small-world-ness' S based on the trade off between high local clustering and short path length. A network is now deemed a 'small-world' if S. 1-an assertion which may be tested statistically. We then examined the behavior of S on a large data-set of real-world systems. We found that all these systems were linked by a linear relationship between their S values and the network size n. Moreover, we show a method for assigning a unique Watts-Strogatz (WS) model to any real-world network, and show analytically that the WS models associated with our sample of networks also show linearity between S and n. Linearity between S and n is not, however, inevitable, and neither is S maximal for an arbitrary network of given size. Linearity may, however, be explained by a common limiting growth process. Conclusions/Significance: We have shown how the notion of a small-world network may be quantified. Several key properties of the metric are described and the use of WS canonical models is placed on a more secure footing

Statins in Candidemia: clinical outcomes from a matched cohort study

<p>Abstract</p> <p>Background</p> <p>HMG CoA reductase inhibitors (statins) in patients with bacteremic sepsis have shown significant survival benefits in several studies. There is no data on the effect of statins in candidemic patients, however in-vitro models suggest that statins interfere with ergesterol formation in the wall of yeasts.</p> <p>Methods</p> <p>This retrospective matched- cohort study from 1/2003 to 12/2006 evaluated the effects of statins on patients with candidemia within intensive care units. Statin-users had candidemia as a cause of their systemic inflammatory response and were on statins throughout their antifungal therapy, while non-statin users were matched based on age +/- 5 years and co-morbid factors. Primary analysis was 30-day survival or discharge using bivariable comparisons. Multivariable comparisons were completed using conditional logistic regression. All variables with a p-value less than 0.10 in the bivariable comparisons were considered for inclusion in the conditional logistic model.</p> <p>Results</p> <p>There were 15 statin-users and 30 non-statin users that met inclusion criteria, all with similar demographics and co-morbid conditions except the statin group had more coronary artery disease (P < 0.01) and peripheral vascular disease (P = 0.03) and lower median APCAHE II scores (14.6 vs 17, p = 0.03). There were no differences in duration of candidemia, antifungal therapy or <it>Candida </it>species between the groups. Statins were associated with lower mortality on bivariable (OR 0.09, 95% CI 0.11-0.75, p = 0.03) and multivariable (OR 0.22, 95% CI 0.02-2.4, p = 0.21) analyses compared to controls; although, in the latter the protective effect lacked statistical signficance.</p> <p>Conclusion</p> <p>In our small, single-center matched-cohort study, statins may provide a survival benefit in candidemia, however further studies are warranted to validate and further explore this association.</p

Playing with networks : How economists explain

Peer reviewe

Social networks and implementation of evidence-based practices in public youth-serving systems: a mixed-methods study

<p>Abstract</p> <p>Background</p> <p>The present study examines the structure and operation of social networks of information and advice and their role in making decisions as to whether to adopt new evidence-based practices (EBPs) among agency directors and other program professionals in 12 California counties participating in a large randomized controlled trial.</p> <p>Methods</p> <p>Interviews were conducted with 38 directors, assistant directors, and program managers of county probation, mental health, and child welfare departments. Grounded-theory analytic methods were used to identify themes related to EBP adoption and network influences. A web-based survey collected additional quantitative information on members of information and advice networks of study participants. A mixed-methods approach to data analysis was used to create a sociometric data set (n = 176) for examination of associations between advice seeking and network structure.</p> <p>Results</p> <p>Systems leaders develop and maintain networks of information and advice based on roles, responsibility, geography, and friendship ties. Networks expose leaders to information about EBPs and opportunities to adopt EBPs; they also influence decisions to adopt EBPs. Individuals in counties at the same stage of implementation accounted for 83% of all network ties. Networks in counties that decided not to implement a specific EBP had no extra-county ties. Implementation of EBPs at the two-year follow-up was associated with the size of county, urban versus rural counties, and in-degree centrality. Collaboration was viewed as critical to implementing EBPs, especially in small, rural counties where agencies have limited resources on their own.</p> <p>Conclusions</p> <p>Successful implementation of EBPs requires consideration and utilization of existing social networks of high-status systems leaders that often cut across service organizations and their geographic jurisdictions.</p> <p>Trial Registration</p> <p><a href="http://www.clinicaltrials.gov/ct2/show/NCT00880126">NCT00880126</a></p

Infectious Disease Modeling of Social Contagion in Networks

Many behavioral phenomena have been found to spread interpersonally through social networks, in a manner similar to infectious diseases. An important difference between social contagion and traditional infectious diseases, however, is that behavioral phenomena can be acquired by non-social mechanisms as well as through social transmission. We introduce a novel theoretical framework for studying these phenomena (the SISa model) by adapting a classic disease model to include the possibility for ‘automatic’ (or ‘spontaneous’) non-social infection. We provide an example of the use of this framework by examining the spread of obesity in the Framingham Heart Study Network. The interaction assumptions of the model are validated using longitudinal network transmission data. We find that the current rate of becoming obese is 2 per year and increases by 0.5 percentage points for each obese social contact. The rate of recovering from obesity is 4 per year, and does not depend on the number of non-obese contacts. The model predicts a long-term obesity prevalence of approximately 42, and can be used to evaluate the effect of different interventions on steady-state obesity. Model predictions quantitatively reproduce the actual historical time course for the prevalence of obesity. We find that since the 1970s, the rate of recovery from obesity has remained relatively constant, while the rates of both spontaneous infection and transmission have steadily increased over time. This suggests that the obesity epidemic may be driven by increasing rates of becoming obese, both spontaneously and transmissively, rather than by decreasing rates of losing weight. A key feature of the SISa model is its ability to characterize the relative importance of social transmission by quantitatively comparing rates of spontaneous versus contagious infection. It provides a theoretical framework for studying the interpersonal spread of any state that may also arise spontaneously, such as emotions, behaviors, health states, ideas or diseases with reservoirs.National Institutes of Health (U.S.) (grant R01GM078986)National Science Foundation (U.S.)Bill & Melinda Gates FoundationTempleton FoundationNational Institute on Aging (grant P01 AG031093)Framingham Heart Study (contract number N01-HC-25195