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Multimorbidity and Knowledge Architectures: An Interdisciplinary Global Health Collaboration (KnowM): Qualitative Dataset, Zimbabwe (2021-2024)
Creator
Dixon, J, London School of Hygiene & Tropical Medicine
Mundoga, F, Biomedical Research and Training Institute
Study number / PID
857310 (UKDA)
10.5255/UKDA-SN-857310 (DOI)
Data access
Restricted
Series
Not available
Abstract
Multimorbidity, commonly defined as the co-occurrence of two-or-more long-term conditions in one individual, has been argued to be among the greatest global health challenges of our time. Health systems remain largely organised around specialist rather than generalist knowledge, which in many African nations translates into ‘siloed’ organisation of care, fuelled by ‘vertical’ single-disease programming. Multimorbidity has recently emerged on the health agendas of many lower-income countries, including in Africa. Yet with its conceptual origins in higher-income settings the global North, its meaning and utility in lower-resource settings remains abstract.
KnowM (2021-2024) was an interdisciplinary research collaboration to characterize the meaning, significance, and transformative potential of the concept of multimorbidity within a global health context, centred on a case study of Zimbabwe. In Zimbabwe, KnowM brought together stakeholders from across the country’s health system to critically interrogate the concept of multimorbidity and co-produce a formative agenda for responding to it in this setting. The specific objectives were: to understand how multimorbidity is being defined and framed as a global health challenge; to describe concepts, experiences, and responses to multimorbidity across different spaces within Zimbabwe’s health system; and to co-produce a conceptual framework and formative agenda for responding to multimorbidity in Zimbabwe.
The study was conducted in four provinces of Zimbabwe, including Harare, Bulawayo, Mashonaland East, and Matabeleland South, to represent both urban and rural settings. Within a participatory ethnographic study design, specific research methods included a health facility survey, participant-observation, in-depth interviews, audio-visual diaries, and participatory workshops. Through this holistic, bottom-up approach, KnowM sought to push thinking beyond the single disease paradigm and to open new conceptual pathways...
Terminology used is generally based on DDI controlled vocabularies: Time Method, Analysis Unit, Sampling Procedure and Mode of Collection, available at CESSDA Vocabulary Service.
Methodology
Data collection period
Not available
Country
Zimbabwe
Time dimension
Not available
Analysis unit
Individual
Organization
Geographic Unit
Object
Universe
Not available
Sampling procedure
Not available
Kind of data
Numeric
Text
Data collection mode
Primary data collection in Zimbabwe took place between September 2022 and December 2023. A participatory ethnographic study design was used, comprising of a health facility survey (n=30), participant-observation (n=23 fieldnote summaries), in-depth interviews (n=45 transcripts), audio-visual diaries (n=10, not included within this dataset), and participatory workshops (n=2, not included within this dataset). Following principles of ‘slow co-production’, methods were designed to iteratively assemble viewpoints on multimorbidity and formulate these into a holistic description of and agenda for responding to multimorbidity that was commensurate across different disciplines, fields, and perspectives. Participants were purposively sampled and included people living with multimorbidity (PLWMM) (n=23), healthcare professionals (n=46), policymakers and public health practitioners (n=5), clinical academics including medical educators (n=7), health informaticians and data experts (n=2), and non-governmental organisation (NGO) representatives (n=10) (sub-total n=93; an additional n=37 participants took part in participatory workshops the data from which are not included in this dataset, n=130). Some participants were classified according to multiple categories, which are specified in the metadata provided; the above participant totals are based on participants’ primary classification. Fields and specialties represented by healthcare professionals and clinical academics included: general practice ('GPs’), general nursing, midwifery, infectious disease (mostly HIV and TB), rheumatology, endocrinology, oncology, psychiatry, mental health, epidemiology, and public health. PLWMM were selected to represent various long-term conditions related to multimorbidity, including but not limited to HIV, diabetes, hypertension, and chronic respiratory disease.
Funding information
Grant number
222177
Access
Publisher
UK Data Service
Publication year
2024
Terms of data access
The Data Collection is available for download to users registered with the UK Data Service. All requests are subject to the permission of the data owner or his/her nominee. Please email the contact person for this data collection to request permission to access the data, explaining your reason for wanting access to the data, then contact our Access Helpdesk.