999 resultados para Program Transformations


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Background: Evidence from the USA suggests that the home-based Family Nurse Partnership program (FNP), extending from early pregnancy until infants are 24 months, can reduce the risk of child abuse and neglect throughout childhood. FNP is now widely available in the UK. A new variant, Group Family Nurse Partnership (gFNP) offers similar content but in a group context and for a shorter time, until infants are 12 months old. Each group comprises 8 to 12 women with similar expected delivery dates and their partners. Its implementation has been established but there is no evidence of its effectiveness.

Methods/Design: The study comprises a multi-site randomized controlled trial designed to identify the benefits of gFNP compared to standard care. Participants (not eligible for FNP) must be either aged <20 years at their last menstrual period (LMP) with one or more previous live births, or aged 20 to 24 at LMP with low educational qualifications and no previous live births. 'Low educational qualifications' is defined as not having both Maths and English Language GCSE at grade C or higher or, if they have both, no more than four in total at grade C or higher. Exclusions are: under 20 years and previously received home-based FNP and, in either age group, severe psychotic mental illness or not able to communicate in English. Consenting women are randomly allocated (minimized by site and maternal age group) when between 10 and 16 weeks pregnant to either to the 44 session gFNP program or to standard care after the collection of baseline information. Researchers are blind to group assignment. The primary outcomes at 12 months are child abuse potential based on the revised Adult-Adolescent Parenting Inventory and parent/infant interaction coded using the CARE Index based on a video-taped interaction. Secondary outcomes are maternal depression, parenting stress, health related quality of life, social support, and use of services.

Discussion: This is the first study of the effectiveness of gFNP in the UK. Results should inform decision-making about its delivery alongside universal services, potentially enabling a wider range of families to benefit from the FNP curriculum and approach to supporting parenting.

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Presents the introductory welcome message from the conference proceedings.

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Background: Modern cancer research often involves large datasets and the use of sophisticated statistical techniques. Together these add a heavy computational load to the analysis, which is often coupled with issues surrounding data accessibility. Connectivity mapping is an advanced bioinformatic and computational technique dedicated to therapeutics discovery and drug re-purposing around differential gene expression analysis. On a normal desktop PC, it is common for the connectivity mapping task with a single gene signature to take >2h to complete using sscMap, a popular Java application that runs on standard CPUs (Central Processing Units). Here, we describe new software, cudaMap, which has been implemented using CUDA C/C++ to harness the computational power of NVIDIA GPUs (Graphics Processing Units) to greatly reduce processing times for connectivity mapping.

Results: cudaMap can identify candidate therapeutics from the same signature in just over thirty seconds when using an NVIDIA Tesla C2050 GPU. Results from the analysis of multiple gene signatures, which would previously have taken several days, can now be obtained in as little as 10 minutes, greatly facilitating candidate therapeutics discovery with high throughput. We are able to demonstrate dramatic speed differentials between GPU assisted performance and CPU executions as the computational load increases for high accuracy evaluation of statistical significance.

Conclusion: Emerging 'omics' technologies are constantly increasing the volume of data and information to be processed in all areas of biomedical research. Embracing the multicore functionality of GPUs represents a major avenue of local accelerated computing. cudaMap will make a strong contribution in the discovery of candidate therapeutics by enabling speedy execution of heavy duty connectivity mapping tasks, which are increasingly required in modern cancer research. cudaMap is open source and can be freely downloaded from http://purl.oclc.org/NET/cudaMap.

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This research explored the influence of children’s perceptions of a pro-social behavior after-school program on actual change in the children’s behavioral outcomes over the program’s duration. Children’s perceptions of three program processes were collected as well as self-reported pro-social and anti-social behavior before and after the program. Statistical models showed that: Positive perceptions of the program facilitators’ dispositions significantly predicted reductions in anti-social behavior; and positive perceptions with the program activities significantly predicted gains in pro-social behavior. The children’s perceptions of their peers’ behavior in the sessions were not found to a significant predictor of behavioral change. The two significant perceptual indicators predicted a small percentage of the change in the behavioral outcomes. However, as after-school social learning programs have a research history of problematic implementation children’s perceptions should be considered in future program design, evaluation and monitoring.

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Haematological malignancies (HM) represent over 6% of the total cancer incidence in Europe and affect all ages, ranging between 45% of all cancers in children and 7% in the elderly. Thirty per cent of childhood cancer deaths are due to HM, 8% in the elderly. Their registration presents specific challenges, mainly because HM may transform or progress in the course of the disease into other types of HM. In the context of cancer registration decisions have to be made about classifying subsequent notifications on the same patient as the same tumour (progression), a transformation or a new tumour registration. Allocation of incidence date and method of diagnosis must also be standardised. We developed European Network of Cancer Registries (ENCR) recommendations providing specific advice for cancer registries to use haematology and molecular laboratories as data sources, conserve the original date of incidence in case of change of diagnosis, make provision for recording both the original as well as transformed tumour and to apply precise rules for recording and counting multiple diagnoses. A reference table advising on codes which reflect a potential transformation or a new tumour is included. This work will help to improve comparability of data produced by population-based cancer registries, which are indispensable for aetiological research, health care planning and clinical research, an increasing important area with the application of targeted therapies.