Community participation in health: a meta-narrative review

Community participation in health A meta-narrative t ti review i Marie-Hélène Paré Lecturer in Qualitative Methods Open University of Catalonia Barcelona, Spain [email protected] Background Planning In health service community participation stems from the Alma-Ata Declaration (1978) The people have the right and duty to participate individually and collectively in the planning and implementation of their health care to the right and duty to participate in health However, the concept can be traced back to the WHO Constitution (1956) Informed opinion and active co-operation Planningon the part of the public are of the utmost importance in the improvement of the health of the people from the active co-operation of the public What has changed? 2 Problem Planning • A research gap exists in the conceptualisation of – – – – the factors that shaped how participation evolved over time the degrees of participation that communities engage in the relationship between degrees and worldviews about health the contribution of the WHO to participatory practice and theory • Confusion about the terms used in the literature on health service & research to refer to 'community' and 'participation' 3 Design • • Aim: to uncover the narratives calling for community participation in health service and research in WHO global health policies Obj i Objective: to generate a typology l off participation i i i d degrees as a benchmark for reporting and assessing community participation Research question • 4 Planning what h t narratives ti shaped h d th the d development, l t implementation, and evolution of community participation in WHO's global health policies? Method: meta-narrative of policy evidence Search • Inclusion criteria – published by HQ – prescribe community participation in health service or in research – target common health problems seen in PMC – Available online Search Search terms cooperat$ OR collaborat$ OR consult$ OR contribut$ OR engage$ OR empower$ OR involve$ OR leader$ OR participat$ AND beneficiar$ OR "civil society" OR communit$ OR consumer$ OR citizen$ OR lay OR patient$ OR people OR population OR public OR survivor$ OR user Search in WHOLIS + Iris + Official records + World Health Assembly + WHO library + hand search + expert contact • N No d date lilimitation i i • In English, French or Spanish p Total titles screened Excluded N= 602 N= 384 T t l reports Total t screened d Excluded N= 218 N= 167 Total reports for metay synthesis N= 51 5 Results How did I go from hundreds of pages of health policies… Synthesis Typology of community participation in health Meta-Narratives of Participation Public Cooperation 1946-1968 - Biomedical model - Goal to change behaviour People’s Participation 1969-1979 - Individual responsibility model - Goal to foster self-help Community Involvement 1980-1999 - Social determinants model - Goal to influence lifestyles …to a typology yp gy of p participation? p 6 User Empowerment 2000-2009 - Social change model - Goal is on prevention Degrees of Participation Definition Reception p • Users are at the receiving g end: they y sit as audience,, theyy receive care, or are given medication • Their input is their presence • No decision power Execution • Users receive instructions to perform tasks as employees, volunteers, or research respondents • They are instrumental in achieving other people's goals • Have power to accept or decline the completion of tasks Consultation • Users are consulted on a topic by the health authorities • Have no assurance that their suggestions are taken on board • Have power to accept or decline to be consulted Contribution • Users' work or time is required in exchange of services • Have limited power regarding what they’ll get in exchange of their contribution Co-production • Users and health authorities join their resources to develop a service or conduct research • Power is shared during all phases, and decisions are jointly taken Leadership • Users lead a health service or conduct research with the support of the health authority • They have power and experience in project management from beginning to the end Outline of the talk 1. Use Endnote to create a meta-narrative dataset 2. Start with deductive keywords search 3. Establish semantic association between keywords 4. Discover relationship between narratives and time 5. Generate the dimensions of the meta-narratives 6 Checkout conceptual cohesion of the meta-narratives 6. meta narratives 7. Integrate participation degrees into the narratives 8. Report the process transparently and rigorously 7 1. Use Endnote to create a meta-narrative dataset 2. Start with deductive keywords search 3. Establish semantic association between keywords 4. Discover relationship between narratives and time 5. Generate the dimensions of the meta-narratives 6 Checkout conceptual cohesion of the meta-narratives 6. meta narratives 7. Integrate participation degrees into the narratives 8. Report the process transparently and rigorously 8 Starting in Endnote • Import Endnote library to setup the meta-narrative d t dataset t in i NVivo NVi Appraisal • Use Endnote custom fields to set up attributes in NVivo for comparative analysis Also available with 9 1. Use Endnote to create a meta-narrative dataset 2. Start with deductive keywords search 3. Establish semantic association between keywords 4. Discover relationship between narratives and time 5. Generate the dimensions of the meta-narratives 6 Checkout conceptual cohesion of the meta-narratives 6. meta narratives 7. Integrate participation degrees into the narratives 8. Report the process transparently and rigorously 10 Search keywords • • After reading the data, a pattern appeared in which some keywords occurred together, i.e. communityy involvement or public cooperation. 1st hunch: Is there a semantic association between the different terms used to refer to 'community' and participation' Mapping user people the public consumers patients beneficiaries community civil society involvement engagement collaboration consultation cooperation empowerment participation contribution 11 Cross-tabulate results 12 • 16 text searches were performed to identify the occurrence of each keyword in the data • Each result was saved as a node (N=16) • Nodes were crosstabulated in a matrix to identify terms that cooccurred within a paragraph Mapping Text searches Results saved as nodes Participants tabulated against degrees 1. Use Endnote to create a meta-narrative dataset 2. Start with deductive keywords search 3. Establish semantic association between keywords 4. Discover relationship between narratives and time 5. Generate the dimensions of the meta-narratives 6 Checkout conceptual cohesion of the meta-narratives 6. meta narratives 7. Integrate participation degrees into the narratives 8. Report the process transparently and rigorously 13 But… Mapping • It is not because two words co-occur that they mean something • To ascertain semantic association, data in each node were screened d • Non-relevant entries were uncoded, i.e. international community • 'Cleaned' Cleaned nodes were cross-tabulated cross tabulated to identify the range of semantic associations and their density Participants tabulated against degrees 14 1. Use Endnote to create a meta-narrative dataset 2. Start with deductive keywords search 3. Establish semantic association between keywords 4. Discover relationship between narratives and time 5. Generate the dimensions of the meta-narratives 6 Checkout conceptual cohesion of the meta-narratives 6. meta narratives 7. Integrate participation degrees into the narratives 8. Report the process transparently and rigorously 15 What about time? 16 • 2nd hunch: Is there an association between the terms used over time? • Cells of the matrix were saved as nodes (32) • Document sets were created for four periods • Documentt sets D t and d nodes d were cross-tabulated to identify what keywords occurred over time Mapping Participants tabulated against degrees Cells saved as nodes Documents sets Doc sets tabulated against nodes 1. Use Endnote to create a meta-narrative dataset 2. Start with deductive keywords search 3. Establish semantic association between keywords 4. Discover relationship between narratives and time 5. Generate the dimensions of the meta-narratives 6 Checkout conceptual cohesion of the meta-narratives 6. meta narratives 7. Integrate participation degrees into the narratives 8. Report the process transparently and rigorously 17 Generate dimensions Mapping Iterative process of coding • Next phase: to code the data inductively to generate the dimensions of the meta-narratives • Blank slate mindset • Coding unit: the sentence(s) so that enough meaning is conveyed in each unit • 18 QCA to coding: not all the documents were coded; only relevant sentences / paragraphs keep on coding coding at dimensions amending nodes memoing teasing emerging hunches Codes evolution Mapping Codes evolution Mapping 19 20 Codes evolution • *Do export your coding scheme outside NVivo* NVivo • This is the best piece of evidence you have to account for the analytic process behind months of coding • Right click on the codes list > Export > Export List Mapping 21 Coding features Mapping teasing emerging hunches Organising the codes Coding at dimensions 22 Reflecting in memos Stay close to data • Staying close to what the data said (micro) while keeping in mind the temporal frame of each meta-narrative (macro), was key to the coding process • See Also Links were central • These are links that connect data segments together or, that connect a segment to an item it (node ( d or source)) Mapping 23 1. Use Endnote to create a meta-narrative dataset 2. Start with deductive keywords search 3. Establish semantic association between keywords 4. Discover relationship between narratives and time 5. Generate the dimensions of the meta-narratives 6 Checkout conceptual cohesion of the meta-narratives 6. meta narratives 7. Integrate participation degrees into the narratives 8. Report the process transparently and rigorously 24 Conceptual cohesion • Checkout conceptual cohesion of each metanarrative with cluster analysis (CA) • CA groups together codes that co co-occurred occurred the most in cluster • Underlying logic: codes th t co-occurred that d share h similar characteristics than those located far apart Mapping 25 1. Use Endnote to create a meta-narrative dataset 2. Start with deductive keywords search 3. Establish semantic association between keywords 4. Discover relationship between narratives and time 5. Generate the dimensions of the meta-narratives 6 Integrate participation degrees into the narratives 6. 7. Report the process transparently and rigorously 26 Integration Synthesis Typology in chapter • The integration of the participation degrees in the meta-narratives meta narratives occurred at the end of coding • A matrix cross-tabulated the document sets against the degrees of participation Doc sets tabulated against nodes 27 7. Report the process transparently and rigorously Some key tips: – At the planning place, foresee the attribute values (discipline, year of publication, etc) you'll you ll want to cross analyse and store them in the ref management software – Use the most suitable approach to start coding: deductive, inductive, or abductive – Codes Codes' name and location will change greatly as the coding processes: record changes in an audit trail (memos, exporting the coding scheme in excel) – Use visualization features (cluster analysis, diagram, model) to look at the data differently and decide accordingly 28 Questions? 29 References • Greenhalgh, T., Robert, G., MacFarlane, F., Bate, P., Kyriakidou, O., & Peacock, R. (2005). Storylines of research in diffusion of innovation: A meta-narrative approach to systematic review. Social Science and Medicine, 61(2), 417-430. • WHO. Constitution of the World Health Organization. Official Records. New York, 22 July 1946. • WHO & UNICEF. International Conference on Primary Health Care, Alma-Ata, USSR, 6-12 September 1978. Declaration of Alma-Ata. 1978. Geneva. • Wong, G., Greenhalgh, T., Westhorp, G., Buckingham, J., & Pawson, R. (2013). RAMESES publication standards: meta-narrative reviews. Journal of advanced nursing, 69(5), 987-1004. 30