Secondary prevention of osteoporosis in Australia: Analysis of government-dispensed prescription data

Background Osteoporosis is a common cause of disability and death in elderly men and women. Until 2007, Australian Government-subsidized use of oral bisphosphonates, raloxifene and calcitriol (1α,25-dihydroxycholecalciferol) was limited to secondary prevention (requiring x-ray evidence of previous low-trauma fracture). The cost to the Pharmaceutical Benefits Scheme was substantial (164 million Australian dollars in 2005/6). Objective To examine the dispensed prescriptions for oral bisphosphonates, raloxifene, calcitriol and two calcium products for the secondary prevention of osteoporosis (after previous low-trauma fracture) in the Australian population. Methods We analysed government data on prescriptions for oral bisphosphonates, raloxifene, calcitriol and two calcium products from 1995 to 2006, and by sex and age from 2002 to 2006. Prescription counts were converted to defined daily doses (DDD)/1000 population/day. This standardized drug utilization method used census population data, and adjusts for the effects of aging in the Australian population. Results Total bisphosphonate use increased 460% from 2.19 to 12.26 DDD/1000 population/day between June 2000 and June 2006. The proportion of total bisphosphonate use in June 2006 was 75.1% alendronate, 24.6% risedronate and 0.3% etidronate. Raloxifene use in June 2006 was 1.32 DDD/1000 population/day. The weekly forms of alendronate and risedronate, introduced in 2001 and 2003, respectively, were quickly adopted. Bisphosphonate use peaked at age 80–89 years in females and 85–94 years in males, with 3-fold higher use in females than in males. Conclusions Pharmaceutical intervention for osteoporosis in Australia is increasing with most use in the elderly, the population at greatest risk of fracture. However, fracture prevalence in this population is considerably higher than prescribing of effective anti-osteoporosis medications, representing a missed opportunity for the quality use of medicines.

Twitter-archive und die Herausforderungen von "Big Social Data" für die Medien- und Kommunikationswissenschaft

Twitter ist eine besonders nützliche Quelle für Social-Media-Daten: mit dem Twitter-API (dem Application Programming Interface, das einen strukturierten Zugang zu Kommunikationsdaten in standardisierten Formaten bietet) ist es Forschern möglich, mit ein wenig Mühe und ausreichenden technische Ressourcen sehr große Archive öffentlich verbreiteter Tweets zu bestimmten Themen, Interessenbereichen, oder Veranstaltungen aufzubauen. Grundsätzlich liefert das API sehr langen Listen von Hunderten, Tausenden oder Millionen von Tweets und den Metadaten zu diesen Tweets; diese Daten können dann auf verschiedentlichste Weise extrahiert, kombiniert, und visualisiert werden, um die Dynamik der Social-Media-Kommunikation zu verstehen. Diese Forschung ist häufig um althergebrachte Fragestellungen herum aufgebaut, wird aber in der Regel in einem bislang unbekannt großen Maßstab durchgeführt. Die Projekte von Medien- und Kommunikationswissenschaftlern wie Papacharissi und de Fatima Oliveira (2012), Wood und Baughman (2012) oder Lotan et al. (2011) – um nur eine Handvoll der letzten Beispiele zu nennen – sind grundlegend auf Twitterdatensätze aufgebaut, die jetzt routinemäßig Millionen von Tweets und zugehörigen Metadaten umfassen, erfaßt nach einer Vielzahl von Kriterien. Was allen diesen Fällen gemein ist, ist jedoch die Notwendigkeit, neue methodische Wege in der Verarbeitung und Analyse derart großer Datensätze zur medienvermittelten sozialen Interaktion zu gehen.

Stop-signal response inhibition in schizophrenia : Behavioural, event-related potential and functional neuroimaging data

Inhibitory control deficits are well documented in schizophrenia, supported by impairment in an established measure of response inhibition, the stop-signal reaction time (SSRT). We investigated the neural basis of this impairment by comparing schizophrenia patients and controls matched for age, sex and education on behavioural, functional magnetic resonance imaging (fMRI) and event-related potential (ERP) indices of stop-signal task performance. Compared to controls, patients exhibited slower SSRT and reduced right inferior frontal gyrus (rIFG) activation, but rIFG activation correlated with SSRT in both groups. Go stimulus and stop-signal ERP components (N1/P3) were smaller in patients, but the peak latencies of stop-signal N1 and P3 were also delayed in patients, indicating impairment early in stop-signal processing. Additionally, response-locked lateralised readiness potentials indicated response preparation was prolonged in patients. An inability to engage rIFG may predicate slowed inhibition in patients, however multiple spatiotemporal irregularities in the networks underpinning stop-signal task performance may contribute to this deficit.

Twitter data: what do they represent?

Scholarly research into the uses of social media has become a major area of growth in recent years, as the adoption of social media for public communication itself has continued apace. While social media platforms provide ready avenues for data access through their Application Programming interfaces, it is increasingly important to think through exactly what these data represent, and what conclusions about the role of social media in society the research which is based on such data therefore enables. This article explores these issues especially for one of the currently leading social media platforms: Twitter.