You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Improving interpretation of publically reported statistics on health and healthcare: the Figure Interpretation Assessment Tool (FIAT-Health)
|
|---|---|
| Published in |
Health Research Policy and Systems, March 2018
|
| DOI | 10.1186/s12961-018-0279-z |
| Pubmed ID | |
| Authors |
Reinie G. Gerrits, Dionne S. Kringos, Michael J. van den Berg, Niek S. Klazinga |
| Abstract |
Policy-makers, managers, scientists, patients and the general public are confronted daily with figures on health and healthcare through public reporting in newspapers, webpages and press releases. However, information on the key characteristics of these figures necessary for their correct interpretation is often not adequately communicated, which can lead to misinterpretation and misinformed decision-making. The objective of this research was to map the key characteristics relevant to the interpretation of figures on health and healthcare, and to develop a Figure Interpretation Assessment Tool-Health (FIAT-Health) through which figures on health and healthcare can be systematically assessed, allowing for a better interpretation of these figures. The abovementioned key characteristics of figures on health and healthcare were identified through systematic expert consultations in the Netherlands on four topic categories of figures, namely morbidity, healthcare expenditure, healthcare outcomes and lifestyle. The identified characteristics were used as a frame for the development of the FIAT-Health. Development of the tool and its content was supported and validated through regular review by a sounding board of potential users. Identified characteristics relevant for the interpretation of figures in the four categories relate to the figures' origin, credibility, expression, subject matter, population and geographical focus, time period, and underlying data collection methods. The characteristics were translated into a set of 13 dichotomous and 4-point Likert scale questions constituting the FIAT-Health, and two final assessment statements. Users of the FIAT-Health were provided with a summary overview of their answers to support a final assessment of the correctness of a figure and the appropriateness of its reporting. FIAT-Health can support policy-makers, managers, scientists, patients and the general public to systematically assess the quality of publicly reported figures on health and healthcare. It also has the potential to support the producers of health and healthcare data in clearly communicating their data to different audiences. Future research should focus on the further validation of the tool in practice. |
X Demographics
The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 33% |
| Australia | 1 | 8% |
| Unknown | 7 | 58% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 58% |
| Practitioners (doctors, other healthcare professionals) | 2 | 17% |
| Scientists | 2 | 17% |
| Science communicators (journalists, bloggers, editors) | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 44 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 16% |
| Student > Bachelor | 4 | 9% |
| Researcher | 4 | 9% |
| Student > Master | 3 | 7% |
| Professor | 2 | 5% |
| Other | 4 | 9% |
| Unknown | 20 | 45% |
| Readers by discipline | Count | As % |
|---|---|---|
| Social Sciences | 7 | 16% |
| Medicine and Dentistry | 5 | 11% |
| Nursing and Health Professions | 4 | 9% |
| Psychology | 2 | 5% |
| Philosophy | 1 | 2% |
| Other | 2 | 5% |
| Unknown | 23 | 52% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 August 2021.
All research outputs
#2,469,655
of 23,798,792 outputs
Outputs from Health Research Policy and Systems
#353
of 1,248 outputs
Outputs of similar age
#53,541
of 334,050 outputs
Outputs of similar age from Health Research Policy and Systems
#22
of 32 outputs
Altmetric has tracked 23,798,792 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,248 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.1. This one has gotten more attention than average, scoring higher than 71% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 334,050 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.