Measuring the performance of a regional cluster in innovation facilitation

Regional industry clusters have been promoted for several years as effective mechanisms to assist firms become more innovative and more competitive. But do they really achieve this goal, and more importantly, just how should an assessment of cluster performance in supporting and facilitating innovation within its members, be undertaken? In this paper we report on a study of a regional IT cluster in Western Sydney, Australia, develop some criteria for assessing the innovation facilitation performance of industry clusters, and discuss the cluster in relation to these criteria. We suggest that engagement with a cluster may enhance the innovation capacity of a firm, and the type of required innovation support varies significantly with the maturity and absorptive capacity of individual firms.

An exploratory cluster randomised controlled trial of knowledge translation strategies to support evidence-informed decision-making in local governments (The KT4LG study)

Background: Childhood overweight and obesity is the most prevalent and, arguably, politically complex child health problem internationally. Governments, communities and industry have important roles to play, and are increasingly expected to deliver an evidence-informed system-wide prevention program. However, efforts are impeded by a lack of organisational access to and use of research evidence. This study aims to identify feasible, acceptable and ideally, effective knowledge translation (KT) strategies to increase evidence-informed decision making in local governments, within the context of childhood obesity prevention as a national policy priority.
Methods/Design: This paper describes the methods for KT4LG, a cluster randomised controlled trial which is exploratory in nature, given the limited evidence base and methodological advances. KT4LG aims to examine a program of KT strategies to increase the use of research evidence in informing public health decisions in local governments. KT4LG will also assess the feasibility and acceptability of the intervention. The intervention program comprises a facilitated program of evidence awareness, access to tailored research evidence, critical appraisal skills development, networking and evidence summaries and will be compared to provision of evidence summaries alone in the control program. 28 local governments were randomised to intervention or control, using computer generated numbers, stratified by budget tertile (high, medium or low). Questionnaires will be used to measure impact, costs, and outcomes, and key informant interviews will be used to examine processes, feasibility, and experiences. Policy tracer studies will be included to examine impact of intervention on policies within relevant government policy documents.
Discussion: Knowledge translation intervention studies with a focus on public health and prevention are very few in number. Thus, this study will provide essential data on the experience of program implementation and evaluation of a system-integrated intervention program employed within the local government public health context. Standardised programs of system, organisational and individual KT strategies have not been described or rigorously evaluated. As such, the findings will make a significant contribution to understanding whether a facilitated program of KT strategies hold promise for facilitating evidence-informed public health decision making within complex multisectoral government organisations.

Mothers' AdvocateS In the Community (MOSAIC)- non-professional mentor support to reduce intimate partner violence and depression in mothers: a cluster randomised trial in primary care

Background : Effective interventions to increase safety and wellbeing of mothers experiencing intimate partner violence (IPV) are scarce. As much attention is focussed on professional intervention, this study aimed to determine the effectiveness of non-professional mentor support in reducing IPV and depression among pregnant and recent mothers experiencing, or at risk of IPV.

Methods : MOSAIC was a cluster randomised trial in 106 primary care (maternal and child health nurse and general practitioner) clinics in Melbourne, Australia. 63/106 clinics referred 215 eligible culturally and linguistically diverse women between January 2006 and December 2007. 167 in the intervention (I) arm, and 91 in the comparison (C) arm. 174 (80.9%) were recruited. 133 (76.4%) women (90 I and 43 C) completed follow-up at 12 months.

Intervention: 12 months of weekly home visiting from trained and supervised local mothers, (English & Vietnamese speaking) offering non-professional befriending, advocacy, parenting support and referrals.

Main outcome measures: Primary outcomes; IPV (Composite Abuse Scale CAS) and depression (Edinburgh Postnatal Depression Scale EPDS); secondary measures included wellbeing (SF-36), parenting stress (PSI-SF) and social support (MOS-SF) at baseline and follow-up.

Analysis: Intention-to-treat using multivariable logistic regression and propensity scoring.

Results : There was evidence of a true difference in mean abuse scores at follow-up in the intervention compared with the comparison arm (15.9 vs 21.8, AdjDiff -8.67, CI -16.2 to -1.15). There was weak evidence for other outcomes, but a trend was evident favouring the intervention: proportions of women with CAS scores ≥7, 51/88 (58.4%) vs 27/42 (64.3%) AdjOR 0.47, CI 0.21 to 1.05); depression (EPDS score ≥13) (19/85, 22% (I) vs 14/43, 33% (C); AdjOR 0.42, CI 0.17 to 1.06); physical wellbeing mean scores (PCS-SF36: AdjDiff 2.79; CI -0.40 to 5.99); mental wellbeing mean scores (MCS-SF36: AdjDiff 2.26; CI -1.48 to 6.00). There was no observed effect on parenting stress. 82% of women mentored would recommend mentors to friends in similar situations.

Conclusion : Non-professional mentor mother support appears promising for improving safety and enhancing physical and mental wellbeing among mothers experiencing intimate partner violence referred from primary care.

Classification of malware based on string and function feature selection

Anti-malware software producers are continually challenged to identify and counter new malware as it is released into the wild. A dramatic increase in malware production in recent years has rendered the conventional method of manually determining a signature for each new malware sample untenable. This paper presents a scalable, automated approach for detecting and classifying malware by using pattern recognition algorithms and statistical methods at various stages of the malware analysis life cycle. Our framework combines the static features of function length and printable string information extracted from malware samples into a single test which gives classification results better than those achieved by using either feature individually. In our testing we input feature information from close to 1400 unpacked malware samples to a number of different classification algorithms. Using k-fold cross validation on the malware, which includes Trojans and viruses, along with 151 clean files, we achieve an overall classification accuracy of over 98%.

A technology to expose a cluster as a service in a cloud

Clouds refer to computational resources (in particular, clusters) that are accessible as scalable, on demand, pay-as- you-go services provided in the Internet. However, clouds are in their infancy and lack a high level abstraction. Specifically, there is no effective discovery and selection service for clusters and offer little to no ease of use for clients. Here we show a technology that exposes clusters as Web services in the form of a Cluster as a Service for publishing via WSDL, discovering, selecting and using clusters.

The 6-PACK programme to decrease fall-related injuries in acute hospitals: protocol for a cluster randomised controlled trial

Background and aims In-hospital fall-related injuries are a source of personal harm, preventable hospitalisation costs, and access block through increased length of stay. Despite increased fall prevention awareness and activity over the last decade, rates of reported fall-related fractures in hospitals appear not to have decreased. This cluster randomised controlled trial (RCT) aims to determine the efficacy of the 6-PACK programme for preventing fall-related injuries, and its generalisability to other acute hospitals.

Methods 24 acute medical and surgical wards from six to eight hospitals throughout Australia will be recruited for the study. Wards will be matched by type and fall-related injury rates, then randomly allocated to the 6-PACK intervention (12 wards) or usual care control group (12 wards). The 6-PACK programme includes a nine-item fall risk assessment and six nursing interventions: ‘falls alert’ sign; supervision of patients in the bathroom; ensuring patient’s walking aids are within reach; establishment of a toileting regime; use of a low-low bed; and use of bed/chair alarm. Intervention wards will be supported by a structured implementation strategy. The primary outcomes are fall and fall-related injury rates 12 months following 6-PACK implementation.

Discussion This study will involve approximately 16 000 patients, and as such is planned to be the largest hospital fall prevention RCT to be undertaken and the first to be powered for the important outcome of fall-related injuries. If effective, there is potential to implement the programme widely as part of daily patient care in acute hospital wards where fall-related injuries are a problem.