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Accepted for/Published in: JMIR Research Protocols

Date Submitted: Jan 15, 2019
Open Peer Review Period: Jan 16, 2019 - Jan 30, 2019
Date Accepted: Apr 28, 2019
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Exploring Severe Mental Illness and Diabetes: Protocol for a Longitudinal, Observational, and Qualitative Mixed Methods Study

Bellass S, Taylor J, Han L, Prady SL, Shiers D, Jacobs R, Holt RIG, Radford J, Gilbody S, Hewitt C, Doran T, Alderson SL, Siddiqi N

Exploring Severe Mental Illness and Diabetes: Protocol for a Longitudinal, Observational, and Qualitative Mixed Methods Study

JMIR Res Protoc 2019;8(9):e13407

DOI: 10.2196/13407

PMID: 31493324

PMCID: 6786849

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Exploring Severe Mental Illness and Diabetes: Protocol for a Longitudinal, Observational, and Qualitative Mixed Methods Study

  • Sue Bellass; 
  • Johanna Taylor; 
  • Lu Han; 
  • Stephanie L Prady; 
  • David Shiers; 
  • Rowena Jacobs; 
  • Richard Ian Gregory Holt; 
  • John Radford; 
  • Simon Gilbody; 
  • Catherine Hewitt; 
  • Tim Doran; 
  • Sarah L Alderson; 
  • Najma Siddiqi

Background:

The average life expectancy for people with a severe mental illness (SMI) such as schizophrenia or bipolar disorder is 15 to 20 years less than that for the population as a whole. Diabetes contributes significantly to this inequality, being 2 to 3 times more prevalent in people with SMI. Various risk factors have been implicated, including side effects of antipsychotic medication and unhealthy lifestyles, which often occur in the context of socioeconomic disadvantage and health care inequality. However, little is known about how these factors may interact to influence the risk of developing diabetes and poor diabetic outcomes, or how the organization and provision of health care may contribute.

Objective:

This study aims to identify the determinants of diabetes and to explore variation in diabetes outcomes for people with SMI.

Methods:

This study will employ a concurrent mixed methods design combining the interrogation of electronic primary care health records from the Clinical Practice Research Datalink (CPRD GOLD) with qualitative interviews with adults with SMI and diabetes, their relatives and friends, and health care staff. The study has been funded for 2 years, from September 2017 to September 2019, and data collection has recently ended.

Results:

CPRD and linked health data will be used to explore the association of sociodemographics, illness, and health care–related factors with both the development and outcomes of type 2 diabetes in people with SMI. Experiences of managing the comorbidity and accessing health care will be explored through qualitative interviews using topic guides informed by evidence synthesis and expert consultation. Findings from both datasets will be merged to develop a more comprehensive understanding of diabetes risks, interventions, and outcomes for people with SMI. Findings will be translated into recommendations for interventions and services using co-design workshops.

Conclusions:

Improving diabetes outcomes for people with SMI is a high-priority area nationally and globally. Understanding how risk factors combine to generate high prevalence of diabetes and poor diabetic outcomes for this population is a necessary first step in developing health care interventions to improve outcomes for people with diabetes and SMI.

ClinicalTrial:

ClinicalTrials.gov NCT03534921; https://clinicaltrials.gov/ct2/show/NCT03534921


 Citation

Please cite as:

Bellass S, Taylor J, Han L, Prady SL, Shiers D, Jacobs R, Holt RIG, Radford J, Gilbody S, Hewitt C, Doran T, Alderson SL, Siddiqi N

Exploring Severe Mental Illness and Diabetes: Protocol for a Longitudinal, Observational, and Qualitative Mixed Methods Study

JMIR Res Protoc 2019;8(9):e13407

DOI: 10.2196/13407

PMID: 31493324

PMCID: 6786849

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© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.