Screening for health risks: A social science perspective

Health screening promises to reduce risks to individuals via probabilistic sifting of populations for medical conditions. The categorisation and selection of 'conditions' such as cardiovascular events, dementia and depression for screening itself requires prior interpretive labour which usually remains unexamined. Screening systems can take diverse organisational forms and varying relationships to health status, as when purported disease precursors, for example 'pre-cancerous' polyps, or supposed risk factors, such as high cholesterol themselves, become targets for screening. Screening at best yields small, although not necessarily unworthwhile, net population health gains. It also creates new risks, leaving some individuals worse-off than if they had been left alone. The difficulties associated with attempting to measure small net gains through randomised controlled trials are sometimes underestimated. Despite endemic doubts about its clinical utility, bibliometric analysis of published papers shows that responses to health risks are coming to be increasingly thought about in terms of screening. This shift is superimposed on a strengthening tendency to view health through the lens of risk. It merits further scrutiny as a societal phenomenon

Divine intervention? A Cochrane review on intercessory prayer gone beyond science and reason

We discuss in this commentary a recent Cochrane review of 10 randomised trials aimed at testing the religious belief that praying to a god can help those who are prayed for. The review concluded that the available studies merit additional research. However, the review presented a scientifically unsound mixture of theological and scientific arguments, and two of the included trials that had a large impact on the findings had problems that were not described in the review. The review fails to live up to the high standards required for Cochrane reviews

Patient and public involvement in reducing health and care research waste

Background Eighty five per cent of health research expenditure is potentially wasted due to failure to publish research, unclear reporting of research that is published, and the failure of new research studies to systematically review previous research in the same topic area, poor study design and conduct. A great deal of progress has been made to address this issue but the role of patients and the public has not been considered. Main A small survey was undertaken, as part of a larger programme of work on reducing health and care waste, to understand the role of patients in reducing research waste. The study showed that patients are interested in this issue particularly in relation to the prioritisation of research and patient and public involvement. Conclusions Patients undertake key roles in the research process including co-applicancy, project management, or as co-researchers. This brings responsibility for ensuring high quality research and value for money. Responsibility for recognition of the potential for wasteful practices is part of the conduct and operation of research studies

Measuring co-authorship and networking-adjusted scientific impact

Appraisal of the scientific impact of researchers, teams and institutions with productivity and citation metrics has major repercussions. Funding and promotion of individuals and survival of teams and institutions depend on publications and citations. In this competitive environment, the number of authors per paper is increasing and apparently some co-authors don't satisfy authorship criteria. Listing of individual contributions is still sporadic and also open to manipulation. Metrics are needed to measure the networking intensity for a single scientist or group of scientists accounting for patterns of co-authorship. Here, I define I1 for a single scientist as the number of authors who appear in at least I1 papers of the specific scientist. For a group of scientists or institution, In is defined as the number of authors who appear in at least In papers that bear the affiliation of the group or institution. I1 depends on the number of papers authored Np. The power exponent R of the relationship between I1 and Np categorizes scientists as solitary (R>2.5), nuclear (R=2.25-2.5), networked (R=2-2.25), extensively networked (R=1.75-2) or collaborators (R<1.75). R may be used to adjust for co-authorship networking the citation impact of a scientist. In similarly provides a simple measure of the effective networking size to adjust the citation impact of groups or institutions. Empirical data are provided for single scientists and institutions for the proposed metrics. Cautious adoption of adjustments for co-authorship and networking in scientific appraisals may offer incentives for more accountable co-authorship behaviour in published articles.Comment: 25 pages, 5 figure

Recommendations by Cochrane Review Groups for assessment of the risk of bias in studies

<p>Abstract</p> <p>Background</p> <p>Assessing the risk of bias in individual studies in a systematic review can be done using individual components or by summarizing the study quality in an overall score.</p> <p>Methods</p> <p>We examined the instructions to authors of the 50 Cochrane Review Groups that focus on clinical interventions for recommendations on methodological quality assessment of studies.</p> <p>Results</p> <p>Forty-one of the review groups (82%) recommended quality assessment using components and nine using a scale. All groups recommending components recommended to assess concealment of allocation, compared to only two of the groups recommending scales (P < 0.0001). Thirty-five groups (70%) recommended assessment of sequence generation and 21 groups (42%) recommended assessment of intention-to-treat analysis. Only 28 groups (56%) had specific recommendations for using the quality assessment of studies analytically in reviews, with sensitivity analysis, quality as an inclusion threshold and subgroup analysis being the most commonly recommended methods. The scales recommended had problems in the individual items and some of the groups recommending components recommended items not related to bias in their quality assessment.</p> <p>Conclusion</p> <p>We found that recommendations by some groups were not based on empirical evidence and many groups had no recommendations on how to use the quality assessment in reviews. We suggest that all Cochrane Review Groups refer to the Cochrane Handbook for Systematic Reviews of Interventions, which is evidence-based, in their instructions to authors and that their own guidelines are kept to a minimum and describe only how methodological topics that are specific to their fields should be handled.</p

Why we need easy access to all data from all clinical trials and how to accomplish it

International calls for registering all trials involving humans and for sharing the results, and sometimes also the raw data and the trial protocols, have increased in recent years. Such calls have come, for example, from the Organization for Economic Cooperation and Development (OECD), the World Health Organization (WHO), the US National Institutes of Heath, the US Congress, the European Commission, the European ombudsman, journal editors, The Cochrane Collaboration, and several funders, for example the UK Medical Research Council, the Wellcome Trust, the Bill and Melinda Gates Foundation and the Hewlett Foundation

The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials

Flaws in the design, conduct, analysis, and reporting of randomised trials can cause the effect of an intervention to be underestimated or overestimated. The Cochrane Collaboration’s tool for assessing risk of bias aims to make the process clearer and more accurat