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dc.contributor.authorMaidment, Ian D
dc.contributor.authorWong, Geoffrey
dc.contributor.authorDuddy, Claire
dc.contributor.authorUpthegrove, Rachel
dc.contributor.authorOduola, Sheri
dc.contributor.authorRobotham, Dan
dc.contributor.authorHiggs, Suzanne
dc.contributor.authorAhern, Amy
dc.contributor.authorBirdi, Gurkiran
dc.date.accessioned2022-03-10T16:00:47Z
dc.date.available2022-03-10T16:00:47Z
dc.date.issued2022-03-09
dc.date.submitted2021-09-24
dc.identifier.issn2046-4053
dc.identifier.others13643-022-01912-9
dc.identifier.other1912
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/334845
dc.description.abstractBACKGROUND: People with severe mental illnesses (SMI) such as schizophrenia die on average 15 to 20 years earlier than everyone else. Two thirds of these deaths are from preventable physical illnesses such as hypertension, cardiovascular disease, and diabetes, which are worsened by weight gain. Antipsychotics are associated with significant weight gain. In REalist Synthesis Of non-pharmacologicaL interVEntions (RESOLVE), a realist synthesis, combining primary and secondary data, will be used to understand and explain how, why, for whom, and in what contexts non-pharmacological interventions can help service users to manage antipsychotic-induced weight gain. METHODS: A five-step approach will be used to develop guidance: 1. Developing the initial programme theory An initial (candidate) programme theory, which sets out how and why outcomes occur within an intervention, will be developed. 2. Developing the search The initial programme theory will be refined using academic and grey literature. The proposed initial sampling frame are as follows: Context: people living with SMI, taking antipsychotics, different types of SMI. INTERVENTION: non-pharmacological interventions. MECHANISMS: triggered by the intervention. Outcomes e.g. weight, metabolic adverse events, quality of life, adherence, burden, economic. Searching for relevant documents will continue until sufficient data is found to conclude that the refined programme theory is coherent and plausible. Lived experience (service users) and stakeholder (practitioners) groups will provide feedback. 3. Selection, appraisal and data extraction Documents will be screened against inclusion and exclusion criteria. The text extracted from these documents will be coded as contexts, mechanisms and their relationships to outcomes. 4. Primary data collection Realist interviews with up to 30 service users and informal carers, and 20 practitioners will gather data to support, refute or refine the programme theory. 5. Data analysis A realist logic of analysis will be used to develop and refine the programme theory from secondary and primary data. The analysis will aim to identify practical intervention strategies to change contexts so that key mechanisms are triggered to produce desired outcomes. Guidance will be produced based on these strategies. DISCUSSION: This realist synthesis aims to develop guidance for service users and practitioners on the most appropriate interventional strategies to manage and limit antipsychotic weight gain. SYSTEMATIC REVIEW REGISTRATION: PROSPERO: CRD42021268697.
dc.languageen
dc.publisherSpringer Science and Business Media LLC
dc.subjectProtocol
dc.subjectAntipsychotics
dc.subjectWeight gain
dc.subjectSevere mental illness
dc.subjectRealist research
dc.titleREalist Synthesis Of non-pharmacologicaL interVEntions for antipsychotic-induced weight gain (RESOLVE) in people living with severe mental illness (SMI).
dc.typeArticle
dc.date.updated2022-03-10T16:00:47Z
prism.issueIdentifier1
prism.publicationNameSyst Rev
prism.volume11
dc.identifier.doi10.17863/CAM.82282
dcterms.dateAccepted2022-03-01
rioxxterms.versionofrecord10.1186/s13643-022-01912-9
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
dc.contributor.orcidMaidment, Ian D [0000-0003-4152-9704]
dc.contributor.orcidAhern, Amy [0000-0001-5069-4758]
dc.identifier.eissn2046-4053
pubs.funder-project-idHealth Services and Delivery Research Programme (131871)
cam.issuedOnline2022-03-09


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