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Evaluating a complex model designed to increase access to high quality primary mental health care for under-served groups: a multi-method study

Overview of attention for article published in BMC Health Services Research, February 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

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Title
Evaluating a complex model designed to increase access to high quality primary mental health care for under-served groups: a multi-method study
Published in
BMC Health Services Research, February 2016
DOI 10.1186/s12913-016-1298-5
Pubmed ID
Authors

Christopher Dowrick, Peter Bower, Carolyn Chew-Graham, Karina Lovell, Suzanne Edwards, Jonathan Lamb, Katie Bristow, Mark Gabbay, Heather Burroughs, Susan Beatty, Waquas Waheed, Mark Hann, Linda Gask

Abstract

Many people with mental distress are disadvantaged because care is not available or does not address their needs. In order to increase access to high quality primary mental health care for under-served groups, we created a model of care with three discrete elements: community engagement, primary care training and tailored wellbeing interventions. We have previously demonstrated the individual impact of each element of the model. Here we assess the effectiveness of the combined model in increasing access to and improving the quality of primary mental health care. We test the assumptions that access to the wellbeing interventions is increased by the presence of community engagement and primary care training; and that quality of primary mental health care is increased by the presence of community engagement and the wellbeing interventions. We implemented the model in four under-served localities in North-West England, focusing on older people and minority ethnic populations. Using a quasi-experimental design with no-intervention comparators, we gathered a combination of quantitative and qualitative information. Quantitative information, including referral and recruitment rates for the wellbeing interventions, and practice referrals to mental health services, was analysed descriptively. Qualitative information derived from interview and focus group responses to topic guides from more than 110 participants. Framework analysis was used to generate findings from the qualitative data. Access to the wellbeing interventions was associated with the presence of the community engagement and the primary care training elements. Referrals to the wellbeing interventions were associated with community engagement, while recruitment was associated with primary care training. Qualitative data suggested that the mechanisms underlying these associations were increased awareness and sense of agency. The quality of primary mental health care was enhanced by information gained from our community mapping activities, and by the offer of access to the wellbeing interventions. There were variable benefits from health practitioner participation in community consultative groups. We also found that participation in the wellbeing interventions led to increased community engagement. We explored the interactions between elements of a multilevel intervention and identified important associations and underlying mechanisms. Further research is needed to test the generalisability of the model. Current Controlled Trials, reference ISRCTN68572159 . Registered 25 February 2013.

X Demographics

X Demographics

The data shown below were collected from the profiles of 18 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 176 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Congo, The Democratic Republic of the 1 <1%
Unknown 174 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 13%
Researcher 21 12%
Student > Master 20 11%
Student > Bachelor 15 9%
Student > Postgraduate 11 6%
Other 35 20%
Unknown 51 29%
Readers by discipline Count As %
Medicine and Dentistry 27 15%
Nursing and Health Professions 26 15%
Psychology 19 11%
Social Sciences 18 10%
Unspecified 5 3%
Other 24 14%
Unknown 57 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 March 2016.
All research outputs
#2,970,076
of 23,881,329 outputs
Outputs from BMC Health Services Research
#1,297
of 7,949 outputs
Outputs of similar age
#46,616
of 300,426 outputs
Outputs of similar age from BMC Health Services Research
#18
of 89 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,949 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done well, scoring higher than 83% 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 300,426 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 84% of its contemporaries.
We're also able to compare this research output to 89 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.