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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Developing a decision tool to identify patients with personality disorders in need of highly specialized care
|
|---|---|
| Published in |
BMC Psychiatry, August 2017
|
| DOI | 10.1186/s12888-017-1460-6 |
| Pubmed ID | |
| Authors |
M. Goorden, E. M. C. Willemsen, C. A. M. Bouwmans-Frijters, J. J. V. Busschbach, M. J. Noomx, C. M. van der Feltz-Cornelis, C. A. Uyl-de Groot, L. Hakkaart-van Roijen |
| Abstract |
Current guidelines recommend referral to highly specialized care for patients with severe personality disorders. However, criteria for allocation to highly specialized care are not clearly defined. The aim of the present study was to develop a decision tool that can support clinicians to identify patients with a personality disorder in need of highly specialized care. Steps taken to develop a decision tool were a literature search, concept mapping, a meeting with experts and a validation study. The concept mapping method resulted in six criteria for the decision tool. The model used in concept mapping provided a good fit (stress value = 0.30) and reasonable reliability (ρ = 0.49). The bridging values were low, indicating homogeneity. The decision tool was subsequently validated by enrolling 368 patients from seven centers. A multilevel model with a Receiver Operating Characteristic Curve (ROC) was applied. In this way, an easily implementable decision tool with relatively high sensitivity (0.74) and specificity (0.69) was developed. A decision tool to identify patients with personality disorders for highly specialized care was developed using advanced methods to combine the input of experts with currently available scientific knowledge. The tool appeared to be able to accurately identify this group of patients. Clinicians can use this decision tool to identify patients who are in need of highly specialized treatment. |
X Demographics
The data shown below were collected from the profiles of 9 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 Kingdom | 4 | 44% |
| Netherlands | 2 | 22% |
| Unknown | 3 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 89% |
| Practitioners (doctors, other healthcare professionals) | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 53 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 21% |
| Student > Bachelor | 5 | 9% |
| Student > Ph. D. Student | 4 | 8% |
| Student > Postgraduate | 4 | 8% |
| Professor | 3 | 6% |
| Other | 11 | 21% |
| Unknown | 15 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 14 | 26% |
| Medicine and Dentistry | 9 | 17% |
| Nursing and Health Professions | 5 | 9% |
| Social Sciences | 3 | 6% |
| Business, Management and Accounting | 1 | 2% |
| Other | 5 | 9% |
| Unknown | 16 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 06 September 2017.
All research outputs
#4,525,136
of 22,999,744 outputs
Outputs from BMC Psychiatry
#1,713
of 4,738 outputs
Outputs of similar age
#78,930
of 316,373 outputs
Outputs of similar age from BMC Psychiatry
#37
of 93 outputs
Altmetric has tracked 22,999,744 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,738 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.9. This one has gotten more attention than average, scoring higher than 63% 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 316,373 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 75% of its contemporaries.
We're also able to compare this research output to 93 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.