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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Decision-making in healthcare: a practical application of partial least square path modelling to coverage of newborn screening programmes
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, August 2012
|
| DOI | 10.1186/1472-6947-12-83 |
| Pubmed ID | |
| Authors |
Katharina E Fischer |
| Abstract |
Decision-making in healthcare is complex. Research on coverage decision-making has focused on comparative studies for several countries, statistical analyses for single decision-makers, the decision outcome and appraisal criteria. Accounting for decision processes extends the complexity, as they are multidimensional and process elements need to be regarded as latent constructs (composites) that are not observed directly. The objective of this study was to present a practical application of partial least square path modelling (PLS-PM) to evaluate how it offers a method for empirical analysis of decision-making in healthcare. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 2 | 50% |
| United States | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 3 | 75% |
| Members of the public | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 107 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Portugal | 1 | <1% |
| Switzerland | 1 | <1% |
| Malaysia | 1 | <1% |
| Italy | 1 | <1% |
| Spain | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 101 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 33 | 31% |
| Student > Master | 14 | 13% |
| Researcher | 11 | 10% |
| Student > Bachelor | 9 | 8% |
| Student > Doctoral Student | 6 | 6% |
| Other | 17 | 16% |
| Unknown | 17 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Business, Management and Accounting | 21 | 20% |
| Social Sciences | 14 | 13% |
| Medicine and Dentistry | 10 | 9% |
| Nursing and Health Professions | 9 | 8% |
| Engineering | 8 | 7% |
| Other | 27 | 25% |
| Unknown | 18 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 22 January 2014.
All research outputs
#12,858,389
of 22,673,450 outputs
Outputs from BMC Medical Informatics and Decision Making
#875
of 1,978 outputs
Outputs of similar age
#87,378
of 164,813 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#28
of 53 outputs
Altmetric has tracked 22,673,450 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,978 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 53% 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 164,813 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 53 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.