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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Recognizing difficult trade-offs: values and treatment preferences for end-of-life care in a multi-site survey of adult patients in family practices
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, December 2017
|
| DOI | 10.1186/s12911-017-0570-x |
| Pubmed ID | |
| Authors |
Michelle Howard, Nick Bansback, Amy Tan, Doug Klein, Carrie Bernard, Doris Barwich, Peter Dodek, Aman Nijjar, Daren K. Heyland |
| Abstract |
Decisions about care options and the use of life-sustaining treatments should be informed by a person's values and treatment preferences. The objective of this study was to examine the consistency of ratings of the importance of the values statements and the association between values statement ratings and the patient's expressed treatment preference. We conducted a multi-site survey in 20 family practices. Patients aged 50 and older self-completed a questionnaire assessing the importance of eight values (rated 1 to 10), and indicated their preference for use of life-sustaining treatment (5 options). We compared correlations among values to a priori hypotheses based on whether the value related to prolonging or shortening life, and examined expected relationships between importance of values and the preference option for life-sustaining treatment. Eight hundred ten patients participated (92% response rate). Of 24 a priori predicted correlations among values statements, 14 were statistically significant but nearly all were negligible in their magnitude and some were in the opposite direction than expected. For example, the correlation between importance of being comfortable and suffering as little as possible and the importance of living as long as possible should have been inversely correlated but was positively correlated (r = 0.08, p = 0.03). Correlations between importance of values items and preference were negligible, ranging from 0.03 to 0.13. Patients may not recognize that trade-offs in what is most important may be needed when considering the use of treatments. In the context of preparation for decision-making during serious illness, decision aids that highlight these trade-offs and connect values to preferences more directly may be more helpful than those that do not. |
X Demographics
The data shown below were collected from the profiles of 19 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 12 | 63% |
| New Zealand | 1 | 5% |
| South Africa | 1 | 5% |
| Unknown | 5 | 26% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 42% |
| Practitioners (doctors, other healthcare professionals) | 7 | 37% |
| Scientists | 3 | 16% |
| Science communicators (journalists, bloggers, editors) | 1 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 47 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 17% |
| Student > Master | 6 | 13% |
| Student > Bachelor | 5 | 11% |
| Researcher | 5 | 11% |
| Student > Doctoral Student | 3 | 6% |
| Other | 10 | 21% |
| Unknown | 10 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 12 | 26% |
| Nursing and Health Professions | 12 | 26% |
| Psychology | 2 | 4% |
| Engineering | 2 | 4% |
| Social Sciences | 2 | 4% |
| Other | 4 | 9% |
| Unknown | 13 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 31 January 2018.
All research outputs
#2,922,789
of 24,914,266 outputs
Outputs from BMC Medical Informatics and Decision Making
#207
of 2,116 outputs
Outputs of similar age
#61,881
of 451,568 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#7
of 29 outputs
Altmetric has tracked 24,914,266 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,116 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has done particularly well, scoring higher than 90% 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 451,568 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 86% of its contemporaries.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.