↓ Skip to main content

A programme theory for liaison mental health services in England

Overview of attention for article published in BMC Health Services Research, September 2018
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

blogs
1 blog
twitter
11 X users

Citations

dimensions_citation
16 Dimensions

Readers on

mendeley
43 Mendeley
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.
Title
A programme theory for liaison mental health services in England
Published in
BMC Health Services Research, September 2018
DOI 10.1186/s12913-018-3539-2
Pubmed ID
Authors

Allan House, Elspeth Guthrie, Andrew Walker, Jenny Hewsion, Peter Trigwell, Cathy Brennan, Mike Crawford, Carolyn Czoski Murray, Matt Fossey, Claire Hulme, Adam Martin, Alan Quirk, Sandy Tubeuf

Abstract

Mechanisms by which liaison mental health services (LMHS) may bring about improved patient and organisational outcomes are poorly understood. A small number of logic models have been developed, but they fail to capture the complexity of clinical practice. We synthesised data from a variety of sources including a large national survey, 73 in-depth interviews with acute and liaison staff working in hospitals with different types of liaison mental health services, and relevant local, national and international literature. We generated logic models for two common performance indicators used to assess organisational outcomes for LMHS: response times in the emergency department and hospital length of stay for people with mental health problems. We identified 8 areas of complexity that influence performance, and 6 trade-offs which drove the models in different directions depending upon the balance of the trade-off. The logic models we developed could only be captured by consideration of more than one pass through the system, the complexity in which they operated, and the trade-offs that occurred. Our findings are important for commissioners of liaison services. Reliance on simple target setting may result in services that are unbalanced and not patient-centred. Targets need to be reviewed on a regular basis, together with other data that reflect the wider impact of the service, and any external changes in the system that affect the performance of LMHS, which are beyond their control.

X Demographics

X Demographics

The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 43 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 9 21%
Researcher 6 14%
Student > Bachelor 5 12%
Lecturer 4 9%
Other 3 7%
Other 7 16%
Unknown 9 21%
Readers by discipline Count As %
Nursing and Health Professions 10 23%
Medicine and Dentistry 6 14%
Social Sciences 5 12%
Psychology 5 12%
Biochemistry, Genetics and Molecular Biology 1 2%
Other 2 5%
Unknown 14 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 10 January 2019.
All research outputs
#2,419,086
of 24,307,517 outputs
Outputs from BMC Health Services Research
#1,002
of 8,191 outputs
Outputs of similar age
#50,471
of 345,652 outputs
Outputs of similar age from BMC Health Services Research
#36
of 165 outputs
Altmetric has tracked 24,307,517 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,191 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has done well, scoring higher than 87% 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 345,652 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 85% of its contemporaries.
We're also able to compare this research output to 165 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.