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Identifying determinants of diabetes risk and outcomes for people with severe mental illness: a mixed-methods study
Jennie Lister, Lu Han, Sue Bellass, Jo Taylor, Sarah L Alderson, Tim Doran, Simon Gilbody, Catherine Hewitt, Richard IG Holt, Rowena Jacobs, Charlotte EW Kitchen, Stephanie L Prady, John Radford, Jemimah R Ride, David Shiers, Han-I Wang, Najma Siddiqi · 11 sections in 11 chapters. Each section is its own page.
Background
Study aims and objectives
Study framework
Identifying potential variables: determinants, outcomes and health-care interventions for diabetes in severe mental illness
Interrogation of patient health records
Qualitative interview study with people with diabetes and severe mental illness, family members and supporters, and health-care staff (objective 5)
Integration of quantitative and qualitative findings: understanding the relationship between severe mental illness and diabetes
Discussion
References
Acknowledgements
List of supplementary material
Attribution. Jennie Lister; Lu Han; Sue Bellass; Jo Taylor; Sarah L Alderson; Tim Doran et al. (2021). Identifying determinants of diabetes risk and outcomes for people with severe mental illness: a mixed-methods study. NIHR Journals Library. Copyright © 2021 Lister et al. This work was produced by Lister et al. under the terms of a commissioning contract issued by the Secretary of State for Health and Social Care. This is an Open Access publication distributed under the terms of the Creative Commons Attribution CC BY 4.0 licence, which permits unrestricted use, distribution, reproduction and adaption in any medium and for any purpose provided that it is properly attributed. See: https://creativecommons.org/licenses/by/4.0/. For attribution the title, original author(s), the publication source – NIHR Journals Library, and the DOI of the publication must be cited. Licensed under CC BY 4.0. NCBI Bookshelf NBK570523. CC BY 4.0. Original source ↗. Text reproduced from the Bookshelf XML without changing wording; figures, images and supplements are not reproduced.