3 resultados para Java script


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Background: Potentially inappropriate prescribing (PIP) is common in older people in primary care and can result in increased morbidity, adverse drug events and hospitalisations. We previously demonstrated the success of a multifaceted intervention in decreasing PIP in primary care in a cluster randomised controlled trial (RCT).
Objective: We sought to determine whether the improvement in PIP in the short term was sustained at 1-year follow-up.
Methods: A cluster RCT was conducted with 21 GP practices and 196 patients (aged ≥70) with PIP in Irish primary care. Intervention participants received a complex multifaceted intervention incorporating academic detailing, medicine review with web-based pharmaceutical treatment algorithms that provide recommended alternative treatment options, and tailored patient information leaflets. Control practices delivered usual care and received simple, patient-level PIP feedback. Primary outcomes were the proportion of patients with PIP and the mean number of potentially inappropriate prescriptions at 1-year follow-up. Intention-to-treat analysis using random effects regression was used.
Results: All 21 GP practices and 186 (95 %) patients were followed up. We found that at 1-year follow-up, the significant reduction in the odds of PIP exposure achieved during the intervention was sustained after its discontinuation (adjusted OR 0.28, 95 % CI 0.11 to 0.76, P = 0.01). Intervention participants had significantly lower odds of having a potentially inappropriate proton pump inhibitor compared to controls (adjusted OR 0.40, 95 % CI 0.17 to 0.94, P = 0.04).
Conclusion: The significant reduction in the odds of PIP achieved during the intervention was sustained after its discontinuation. These results indicate that improvements in prescribing quality can be maintained over time.

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The popularity of Computing degrees in the UK has been increasing significantly over the past number of years. In Northern Ireland, from 2007 to 2015, there has been a 40% increase in acceptances to Computer Science degrees with England seeing a 60% increase over the same period (UCAS, 2016). However, this is tainted as Computer Science degrees also continue to maintain the highest dropout rates.
In Queen’s University Belfast we currently have a Level 1 intake of over 400 students across a number of computing pathways. Our drive as staff is to empower and motivate the students to fully engage with the course content. All students take a Java programming module the aim of which is to provide an understanding of the basic principles of object-oriented design. In order to assess these skills, we have developed Jigsaw Java as an innovative assessment tool offering intelligent, semi-supervised automated marking of code.
Jigsaw Java allows students to answer programming questions using a drag-and-drop interface to place code fragments into position. Their answer is compared to the sample solution and if it matches, marks are allocated accordingly. However, if a match is not found then the corresponding code is executed using sample data to determine if its logic is acceptable. If it is, the solution is flagged to be checked by staff and if satisfactory is saved as an alternative solution. This means that appropriate marks can be allocated and should another student have submitted the same placement of code fragments this does not need to be executed or checked again. Rather the system now knows how to assess it.
Jigsaw Java is also able to consider partial marks dependent on code placement and will “learn” over time. Given the number of students, Jigsaw Java will improve the consistency and timeliness of marking.

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Background
The OPTI-SCRIPT cluster randomised controlled trial (RCT) found that a three-phase multifaceted intervention including academic detailing with a pharmacist, GP-led medicines reviews, supported by web-based pharmaceutical treatment algorithms, and tailored patient information leaflets, was effective in reducing potentially inappropriate prescribing (PIP) in Irish primary care. We report a process evaluation exploring the implementation of the intervention, the experiences of those participating in the study and lessons for future implementation.

Methods
The OPTI-SCRIPT trial included 21 GP practices and 196 patients. The process evaluation used mixed methods. Quantitative data were collected from all GP practices and semi-structured interviews were conducted with GPs from intervention and control groups, and a purposive sample of patients from the intervention group. All interviews were transcribed verbatim and analysed using a thematic analysis.

Results
Despite receiving a standardised academic detailing session, intervention delivery varied among GP practices. Just over 70 % of practices completed medicines review as recommended with the patient present. Only single-handed practices conducted reviews without patients present, highlighting the influence of practice characteristics and resources on variation. Medications were more likely to be completely stopped or switched to another more appropriate medication when reviews were conducted with patients present. The patient information leaflets were not used by any of the intervention practices. Both GP (32 %) and patient (40 %) recruitment rates were modest. For those who did participate, overall, the experience was positively viewed, with GPs and patients referring to the value of medication reviews to improve prescribing and reduce unnecessary medications. Lack of time in busy GP practices and remuneration were identified as organisational barriers to future implementation.

Conclusions
The OPTI-SCRIPT intervention was positively viewed by both GPs and patients, both of whom valued the study’s objectives. Patient information leaflets were not a successful component of the intervention. Academic detailing and medication reviews are important components in changing PIP, and having patients present during the review process seems to be a more effective approach for decreasing PIP.