Cross‐curricular IT tools for university students: Developing an effective model

Information technology is now recognized as a key study‐enhancement measure in higher education, and there is increasing demand for the provision of basic IT awareness and skills across the whole range of subject departments. One response to this demand is the central provision of a generic IT course or programme of courses. We draw upon the experience of such courses at the Universities of Glasgow and York to identify some of the significant dimensions in the development and operation of generic IT programmes. These include the policy context, the structure, content and educational stance of the programme, relationship of the programme to existing curricula, and the extent and nature of resourcing, assessment and certification. Operation of such courses raises important issues, such as questions of compulsory IT preparation, study skills, staff development, standardization, institutional policy and evaluation. This discussion is set within current trends in higher education

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Teaching and Learning Materials and the Internet by Ian Forsyth, London: Kogan Page, 1996. ISBN: 0–7494‐ 20596. 181 pages, paperback. £18.99

The harvest plot: a method for synthesising evidence about the differential effects of interventions.

BACKGROUND: One attraction of meta-analysis is the forest plot, a compact overview of the essential data included in a systematic review and the overall 'result'. However, meta-analysis is not always suitable for synthesising evidence about the effects of interventions which may influence the wider determinants of health. As part of a systematic review of the effects of population-level tobacco control interventions on social inequalities in smoking, we designed a novel approach to synthesis intended to bring aspects of the graphical directness of a forest plot to bear on the problem of synthesising evidence from a complex and diverse group of studies. METHODS: We coded the included studies (n = 85) on two methodological dimensions (suitability of study design and quality of execution) and extracted data on effects stratified by up to six different dimensions of inequality (income, occupation, education, gender, race or ethnicity, and age), distinguishing between 'hard' (behavioural) and 'intermediate' (process or attitudinal) outcomes. Adopting a hypothesis-testing approach, we then assessed which of three competing hypotheses (positive social gradient, negative social gradient, or no gradient) was best supported by each study for each dimension of inequality. RESULTS: We plotted the results on a matrix ('harvest plot') for each category of intervention, weighting studies by the methodological criteria and distributing them between the competing hypotheses. These matrices formed part of the analytical process and helped to encapsulate the output, for example by drawing attention to the finding that increasing the price of tobacco products may be more effective in discouraging smoking among people with lower incomes and in lower occupational groups. CONCLUSION: The harvest plot is a novel and useful method for synthesising evidence about the differential effects of population-level interventions. It contributes to the challenge of making best use of all available evidence by incorporating all relevant data. The visual display assists both the process of synthesis and the assimilation of the findings. The method is suitable for adaptation to a variety of questions in evidence synthesis and may be particularly useful for systematic reviews addressing the broader type of research question which may be most relevant to policymakers

The harvest plot: a method for synthesising evidence about the differential effects of interventions.

BACKGROUND: One attraction of meta-analysis is the forest plot, a compact overview of the essential data included in a systematic review and the overall 'result'. However, meta-analysis is not always suitable for synthesising evidence about the effects of interventions which may influence the wider determinants of health. As part of a systematic review of the effects of population-level tobacco control interventions on social inequalities in smoking, we designed a novel approach to synthesis intended to bring aspects of the graphical directness of a forest plot to bear on the problem of synthesising evidence from a complex and diverse group of studies. METHODS: We coded the included studies (n = 85) on two methodological dimensions (suitability of study design and quality of execution) and extracted data on effects stratified by up to six different dimensions of inequality (income, occupation, education, gender, race or ethnicity, and age), distinguishing between 'hard' (behavioural) and 'intermediate' (process or attitudinal) outcomes. Adopting a hypothesis-testing approach, we then assessed which of three competing hypotheses (positive social gradient, negative social gradient, or no gradient) was best supported by each study for each dimension of inequality. RESULTS: We plotted the results on a matrix ('harvest plot') for each category of intervention, weighting studies by the methodological criteria and distributing them between the competing hypotheses. These matrices formed part of the analytical process and helped to encapsulate the output, for example by drawing attention to the finding that increasing the price of tobacco products may be more effective in discouraging smoking among people with lower incomes and in lower occupational groups. CONCLUSION: The harvest plot is a novel and useful method for synthesising evidence about the differential effects of population-level interventions. It contributes to the challenge of making best use of all available evidence by incorporating all relevant data. The visual display assists both the process of synthesis and the assimilation of the findings. The method is suitable for adaptation to a variety of questions in evidence synthesis and may be particularly useful for systematic reviews addressing the broader type of research question which may be most relevant to policymakers.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

The harvest plot: A method for synthesising evidence about the differential effects of interventions

<p>Abstract</p> <p>Background</p> <p>One attraction of meta-analysis is the forest plot, a compact overview of the essential data included in a systematic review and the overall 'result'. However, meta-analysis is not always suitable for synthesising evidence about the effects of interventions which may influence the wider determinants of health. As part of a systematic review of the effects of population-level tobacco control interventions on social inequalities in smoking, we designed a novel approach to synthesis intended to bring aspects of the graphical directness of a forest plot to bear on the problem of synthesising evidence from a complex and diverse group of studies.</p> <p>Methods</p> <p>We coded the included studies (n = 85) on two methodological dimensions (suitability of study design and quality of execution) and extracted data on effects stratified by up to six different dimensions of inequality (income, occupation, education, gender, race or ethnicity, and age), distinguishing between 'hard' (behavioural) and 'intermediate' (process or attitudinal) outcomes. Adopting a hypothesis-testing approach, we then assessed which of three competing hypotheses (positive social gradient, negative social gradient, or no gradient) was best supported by each study for each dimension of inequality.</p> <p>Results</p> <p>We plotted the results on a matrix ('harvest plot') for each category of intervention, weighting studies by the methodological criteria and distributing them between the competing hypotheses. These matrices formed part of the analytical process and helped to encapsulate the output, for example by drawing attention to the finding that increasing the price of tobacco products may be more effective in discouraging smoking among people with lower incomes and in lower occupational groups.</p> <p>Conclusion</p> <p>The harvest plot is a novel and useful method for synthesising evidence about the differential effects of population-level interventions. It contributes to the challenge of making best use of all available evidence by incorporating all relevant data. The visual display assists both the process of synthesis and the assimilation of the findings. The method is suitable for adaptation to a variety of questions in evidence synthesis and may be particularly useful for systematic reviews addressing the broader type of research question which may be most relevant to policymakers.</p

Obinutuzumab in Combination with Chemotherapy for the First-Line Treatment of Patients with Advanced Follicular Lymphoma: An Evidence Review Group Evaluation of the NICE Single Technology Appraisal

The National Institute for Health and Care Excellence (NICE), as part of the institute’s single technology appraisal (STA) process, invited the company that makes obinutuzumab (Roche Products Limited) to submit evidence of the clinical and cost effectiveness of the drug in combination with chemotherapy, with or without obinutuzumab as maintenance therapy for adult patients with untreated, advanced follicular lymphoma (FL) in the UK. Kleijnen Systematic Reviews Ltd (KSR), in collaboration with Erasmus University Rotterdam, was commissioned to act as the Evidence Review Group (ERG). This paper describes the company’s submission, the ERG review, and NICE’s subsequent decisions. The clinical evidence was derived from two phase III, company-sponsored, randomised, open-label studies. Most evidence on obinutuzumab was based on the GALLIUM trial that compared obinutuzumab in combination with chemotherapy as induction followed by obinutuzumab maintenance monotherapy with rituximab in combination with chemotherapy as induction followed by rituximab maintenance monotherapy in previously untreated patients with FL (grades 1–3a). Long-term clinical evidence was based on the PRIMA trial, studying the benefit of two years of rituximab maintenance after first-line treatment in patients with FL. The cost-effectiveness evidence submitted by the company relied on a partitioned survival cost-utility model, implemented in Microsoft® Excel. The base-case incremental cost-effectiveness ratio (ICER) presented in the company submission was <£20,000 per quality-adjusted life-year (QALY) gained. Although the ERG concluded that the economic model met the NICE reference case to a reasonable extent, some errors were identified and several assumptions made by the company were challenged. A new base-case scenario produced by the ERG suggested an ICER that was higher than the company base case, but still below £30,000 per QALY gained. However, some ERG scenario analyses were close to or even above the threshold. This was the case in particular for assuming a treatment effect that did not extend beyond trial follow-up. These results led to an initial negative recommendation by the appraisal committee. Subsequently, the company submitted a revised base case focu

Increasing participation of cancer patients in randomised controlled trials: a systematic review

BACKGROUND: There are many barriers to patient participation in randomised controlled trials of cancer treatments. To increase participation in trials, strategies need to be identified to overcome these barriers. Our aim was to assess the effectiveness of interventions to overcome barriers to patient participation in randomised controlled trials (RCTs) of cancer treatments. METHODS: A systematic review was conducted. Published and unpublished studies in any language were searched for in fifteen electronic databases, including MEDLINE, EMBASE, CINAHL and PsycINFO, from inception to the end of 2004. Studies of any interventions to improve cancer patient participation in RCTs, which reported the change in recruitment rates, were eligible for inclusion. RCTs and non-randomised controlled trials as well as before and after studies reporting baseline rates specific to the population being investigated were included. Data were extracted by one reviewer into structured summary tables and checked for accuracy by a second reviewer. Each included study was assessed against a checklist for methodological quality by one reviewer and checked by a second reviewer. A narrative synthesis was conducted. RESULTS: Eight studies were identified that met the inclusion criteria: three RCTs, two non-randomised controlled trials and three observational studies. Six of the studies had an intervention that had some relevance to the UK. There was no robust evidence that any of the interventions investigated led to an increase in cancer patient participation in RCTs, though one good quality RCT found that urologists and nurses were equally effective at recruiting participants to a treatment trial for prostate cancer. Although there was no evidence of an effect in any of the studies, the evidence was not of sufficient quality to be able to conclude that these interventions therefore do not work. CONCLUSION: There is not a strong evidence-base for interventions that increase cancer patient participation in randomised trials. Further research is required to evaluate the effectiveness of strategies to increase participation in cancer treatment trials