information – AQuAS Blog

Altmetrics: complementary metrics focused on the article

19 Apr

The traditional system in assessing the quality of a scientific publication (a journal article, for example) has fundamentally been based on the calculation of the citations it generates. In an article published in Science (1995), Eugene Garfield (1925 – 2017) proposed a citation index as a system that would help authors find articles on a subject. It was a great innovation without doubt. Later, with the creation of the Institute for Scientific Information (today the Web of Science) and the Journal Citation Reports, this system became very prominent and centred its work on the assessment of journals because it helped authors decide in which journal to publish (based on the impact factor calculated for each one).It is a system that has been criticised from the humanities and social sciences and also because it does not focus on the article itself but instead gives the reference value to the journal in which it is published (and presupposes that an article should “inherit” the journal’s impact factor).

From 2010, people started talking about altmetrics, a set of indicators (for example, how often an article is shared, its re-dissemination, the comments it has generated, mentions (likes), etc…) that measure the presence of a publication in social and academic networks, which complement citation indexes considerably. Altmetrics, therefore, assess the repercussion of an article itself and not that of a journal as a whole (the way impact factors do, for example).

At present, several scientific editors have taken this information into consideration. One of the first examples was the journal PLOS, followed by Nature and others. Its use has also spread to data bases (e.g. Scopus) and to academic networks (e.g. ResearchGate). The altmetric data that accompany an article tend to have the sections that appear in figures 1 and 2, even though there can be small differences depending on the programme used (ImpactStory, PLUM, Article Level Metrics, altimetrics.com, etc…).

Figure 1.

Figure 1. Example of the altmetrics of an article in PLOS

And so we can see that it is not only the statistics of presence in social networks that are included (mentions, blogs, etc…) but also the use of data (visualisations and downloads) as well as the citations of an article (in Scopus, CrossRef, PubMed, GoogleScholar, etc…). We are talking about very complete quantitative information for the reader and also for the author of the article.

Figure 2. Example of the altmetrics of an article in Nature

In the case of Nature (figure 2) there is also a graphic representation in the form of a circle or “ring” in which each colour is a type of channel (twitter, blogs, facebook, wikipedia, etc…), where a contextualised percentage is given in relation to articles which are similar in age and it also indicates its precise presence in the general media (“news articles”) and scientific blogs.

Let us do a quick assessment of altmetrics. Their main strengths lie in the fact that they measure the impact of publications beyond academic circles, strictly speaking, that they can be applied to all types of documents (be it an article, a book or a doctoral thesis), that the results are immediate (there is no need to wait for the annual value of the impactor factor) and that they focus on the article (and not on the journal).

In terms of their weak points, it should be said that the indicators need to be collected very quickly (they are very volatile), that it is difficult to compare the indicators between each other (which is of more value, a retweet or a “like”?), that there is great difficulty in the normalisation and homogeneity when collecting data (which does not occur in the case of citations) and that different measuring tools produce different results (e.g. ImpactStory or Altmetrics).

Altmetrics, therefore, help to measure the impact of a specific publication in social networks. This is why we should define them as complementary metrics rather than alternative metrics. In contrast to the traditional impact factor – which is applied to a journal – altmetrics are centred on the article and this is a significant innovation. Despite them having some weak points they are in a consolidation phase and have long-term potential.

From a researcher’s perspective, it is clear that at present publishing an article in a journal is not enough and one needs to be fully involved in its dissemination in social networks (especially Twitter, blogs, etc…) and also in academic networks (Researchgate, Mendeley, etc…) so as to give visibility to the contents published. In this new scenario, altmetrics are fundamental because they are able to measure this impact in networks and offer authors (and readers) a general view of the dissemination of their publications.

Post by Ernest Abadal, Faculty of Library and Information Science, University of Barcelona.

Why is difficult to reduce low value clinical practices in a Hospital?

15 Dec

Within the framework of the Programa de Millora de la Pràctica Clínica (Programme for improvement in Clinical Practice) of the Vall d’Hebron University Hospital – VHIR Institut de Recerca (VHIR Research Institute) and in collaboration with the Essencial project, work has been done to explore what barriers health professionals (hospital doctors and nurses) come up against in order to implement clinical recommendations aimed at reducing inadequate practices or those of low clinical value. A group of 15 health professionals (with medical or surgical specialities) collaborated in two discussion sessions to identify these barriers. The work done by Dimelza Osorio of the Vall d’Hebron University Hospital and by Liliana Arroyo of the University of Barcelona has been really outstanding.

When talking about inadequate practices or those of low clinical value, we are referring to inappropriate health interventions in certain circumstances, whether it be because the risks involved outweigh the benefits, because their efficiency is not proven or because there is not a clear cost-benefit correlation. These low value practices are present in everyday clinical practice and can lead to an over-diagnosis and/or over-treatment, meaning diagnosing or treating a clinical condition in which there are no notable health benefits for patients.

The barriers identified can be classified into four levels: micro, meso, macro and those of the context. At a first level (micro), those deriving from the characteristics of professionals themselves were identified, such as the tendency for self-protection in the face of claims or legal problems (defensive medicine), dealing with uncertainty or having had bad experiences previously; scepticism towards scientific evidence as a result of out-dated or contradictory information; other attitudes of professionals such as inertia or resistance to change; and the lack of training. All these constitute barriers. Patients’ characteristics were also identified, such as their reluctances and demands; the figure of the expert patient or beliefs acquired in the past.

At a second level (meso), barriers as a result of the interaction between professionals and patients were identified. Some barriers have to do with the relationship between professionals; that is to say, difficulties related to clinical leadership, the coordination between different professionals (or specialists), or the cohesion within teams. There are also barriers of organisational leadership such as a lack of institutional support in legal issues, the inertia of the organisation itself, economic incentives, wrongly applied penalties or the lack of foresight of certain costs. And then barriers of information flow, namely, the inefficiency of information systems such as the lack of operating capacity of e-mailing, or intoxication due to an excess of corporate information.

At a third level (macro), barriers are influenced by the structure and management characteristics of a hospital and the Catalan health system. The healthcare conditions stand out, such as the burden of healthcare, the duration of the attention given to patients, or how much technology is used in care, that is, greater access to facilities and tests. But also the design of the health system, such as in the lack of systemic leadership, or the lack of coordination between different levels of healthcare (primary care, hospital care, social healthcare, ….) . And then also the characteristics of the health system like territorial differences and the legal and bureaucratic context.

Lastly, certain external factors to the health system (the context) can also lead to low value clinical practices persisting. Although a lot less present in this case, the political context and the influence from the media are included.

The importance of each barrier is shown in the following graph:

barreres-en

Potential solutions were explored or proposed in the same session so as to eliminate these barriers; a series of solutions have been proposed mainly related to the creation of a leadership strategy and a series of clear options, which require rationlising processes and using available information properly.

Post written by Maite Solans (@SolansMaite).