Title |
Evaluating a complex model designed to increase access to high quality primary mental health care for under-served groups: a multi-method study
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Published in |
BMC Health Services Research, February 2016
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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
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 12 | 67% |
Canada | 2 | 11% |
United States | 1 | 6% |
Unknown | 3 | 17% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 9 | 50% |
Members of the public | 5 | 28% |
Practitioners (doctors, other healthcare professionals) | 4 | 22% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | <1% |
Congo, The Democratic Republic of the | 1 | <1% |
Unknown | 170 | 99% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 23 | 13% |
Researcher | 21 | 12% |
Student > Master | 20 | 12% |
Student > Bachelor | 15 | 9% |
Student > Postgraduate | 11 | 6% |
Other | 30 | 17% |
Unknown | 52 | 30% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 27 | 16% |
Nursing and Health Professions | 26 | 15% |
Psychology | 19 | 11% |
Social Sciences | 18 | 10% |
Biochemistry, Genetics and Molecular Biology | 4 | 2% |
Other | 20 | 12% |
Unknown | 58 | 34% |