Convergent parallel mixed-methods design in health policy analysis: A worked example from South Africa’s non-communicable disease policies

Convergent parallel mixed-methods design in health policy analysis: A worked example from South Africa’s non-communicable disease policies | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Convergent parallel mixed-methods design in health policy analysis: A worked example from South Africa’s non-communicable disease policies Richard Rasesemola This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9203247/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Background Health policy problems such as the rising burden of non-communicable diseases (NCDs) in South Africa are complex and cross-sectoral. Methodological approaches that integrate policy content, context, actors, and system capacities can yield more actionable insights for implementation than single-method designs. Methods This article presents a worked example of a convergent parallel mixed-methods design for health policy analysis, combining (i) qualitative document analysis of three purposively selected health policies and a quantitative provincial-level survey of policy-relevant health officials (n = 57) from seven provinces in South Africa. Analyses were conducted independently and integrated at the interpretation stage to develop and validate policy-improvement strategies through a Delphi process. The design was theoretically anchored in Stages Heuristics and the WHO Analytical Framework for Social Determinants of Health (SDH). Results The qualitative strand identified strong multi-stakeholder involvement in policy formulation with limited operationalisation of critical SDH domains such as socio-economic position, gender, race, and education. The quantitative strand revealed capacity constraints: human resources, financing, technology, and infrastructure that limit implementation readiness at provincial level and crowd out NCD activities relative to other priorities. Integrated interpretation produced six Delphi-validated strategies. Conclusions Convergent parallel mixed-methods design is feasible, informative, and well-suited to health policy analysis where actionable guidance requires the triangulation of policy content with system capacities and governance realities. The worked example demonstrates how to specify strands, preserve independence, integrate findings, and move from evidence to implementable strategies and indicators. mixed methods health policy analysis Stages Heuristics social determinants of health non-communicable diseases South Africa convergent parallel design Delphi technique Figures Figure 1 Background Non-communicable diseases (NCDs) account for most of the global mortality and represent a substantial and growing burden in sub-Saharan Africa [ 1 , 2 ]. In South Africa, several national strategies have been implemented to address NCD risk factors and strengthen service delivery; however, updated mortality surveillance indicates that deaths from NCDs have continued to rise, highlighting persistent implementation and health-system gaps [ 3 , 4 ]. This trend has been attributed to inadequate physical activity promotion, weak regulation of unhealthy food marketing to children, limited enforcement of trans-fat policies, and poor compliance with alcohol advertising controls [ 5 ]. These challenges highlight the need for methodological approaches that can meaningfully link policy design to on-the-ground system capacity and governance arrangements. Health policies addressing NCDs are inherently complex, operating across multiple sectors, levels of governance, and stages of the policy cycle [ 6 ]. Effective NCD prevention and control require coordinated action beyond the health sector, encompassing education, finance, trade, urban planning, and social development, while simultaneously addressing behavioural, environmental, commercial, and structural determinants of health [ 3 ]. Decisions taken during agenda-setting and formulation shape downstream processes of adoption, implementation, and evaluation, meaning that policy effectiveness is influenced not only by policy content but also by enforcement mechanisms, institutional capacity, accountability structures, and the broader socio-political context [ 7 ]. These interdependencies make it difficult to isolate the causes of policy underperformance without approaches capable of capturing both process and content alongside structural constraints. Historically, research on health policy has relied largely on single-method approaches, including descriptive policy reviews, qualitative case studies, or quantitative assessments of system performance and outcomes [ 8 ]. While such approaches have yielded valuable insights, they often examine policy content, implementation processes, or capacity constraints in isolation [ 9 ]. Policy analyses may document stated intentions without assessing feasibility, while quantitative evaluations may measure resource availability or outcomes without interrogating weaknesses in policy design, enforcement, or governance [ 10 ]. As a result, the interdependencies between policy intent and implementation realities are frequently under-specified [ 11 ], limiting the ability of such studies to identify root causes of persistent implementation gaps. Convergent parallel mixed-methods designs, which analyse qualitative and quantitative strands independently and integrate findings during interpretation, offer a coherent approach for addressing this complexity [ 12 ]. By examining what policies say, what systems can deliver, and where misalignments occur, such designs enable a more comprehensive understanding of policy effectiveness. Therefore, this article presents a worked example of a convergent parallel mixed-methods study applied to South Africa’s NCD policy environment. Grounded in a doctoral project, this article focuses explicitly on methodological architecture, integration logic, and validation processes that support the development of actionable, evidence-informed policy-improvement strategies. Methods Study design and rationale Convergent parallel mixed-methods design was used to examine complex gaps in NCD policy implementation. Qualitative policy document analysis and quantitative survey data were conducted contemporaneously, analysed independently and integrated through convergence, complementarity, and dissonance to inform evidence-based strategy development (Fig. 1 ). A convergent parallel mixed-methods design supported corroboration and complementarity, allowing discordant findings to surface and be reconciled into actionable strategies. Conceptual and analytical frameworks The study was underpinned by two complementary theoretical frameworks that informed the selection of data-collection tools, and guided strand-specific analyses. Stages Heuristics framework was used to guide a process-oriented analysis of policy development and implementation by conceptualising the policy cycle as a series of interconnected stages including agenda-setting, formulation, adoption, implementation, and evaluation [ 13 ]. This framework informed the design of data-collection tools by ensuring that questions and analytical categories captured stakeholder involvement, decision-making processes, and implementation experiences across each stage of the policy process. By structuring the inquiry along these stages, the study was able to systematically examine where participation, coordination, and accountability were strengthened or weakened, and how these dynamics influenced programme outcomes. In parallel, the World Health Organization’s (WHO) Analytical Framework for Social Determinants of Health (SDH) provided a substantive lens for examining policy content and implementation practices [ 14 ]. This framework guided the development of document-analysis criteria and survey items aimed at identifying whether, and how, structural and intermediary determinants such as socio-economic position, material circumstances, psychosocial factors, and health-system characteristics were explicitly addressed within policy activities and service delivery mechanisms. The SDH framework ensured that the analysis extended beyond procedural aspects of policymaking to interrogate the extent to which broader social and systemic drivers of health were operationalised in practice. Together, the integration of the Stages Heuristics and the SDH framework enabled a coherent alignment between theory, tools, and methods. While Stages Heuristics structured the examination of how policies were developed and implemented [ 13 ], the SDH framework illuminated what determinants were prioritised within those processes [ 14 ]. This combined theoretical grounding strengthened the study’s ability to generate context-responsive and actionable recommendations for improving policy design, delivery, and impact. Qualitative strand: Document analysis Sampling and data sources The three policies were purposively selected for analysis because the diseases they target. Obesity-related conditions such as endocrine, nutritional and metabolic diseases accounted for approximately 7% of all registered deaths between 2015 and 2017 [ 15 ]. Mental and behavioural disorders accounted for approximately 0.5–0.6% of registered deaths between 2015 and 2017 [ 15 ]. While deaths due to neoplasms increased steadily, with cancers accounting for approximately 9–10% of all registered deaths by 2017 which are among the leading contributors to morbidity and mortality in South Africa and collectively account for a substantial proportion of NCD deaths [ 15 ]. This article focuses on these policies to examine whether existing national responses adequately address the scale, drivers, and determinants of these high-burden conditions. Data extraction and coding A structured data-extraction tool designed by the researcher, captured policy provenance, agenda and stakeholder mapping, SDH domains embedded in key activities, and implementation/measurement plans. Thematic coding combined deductive categories from the two frameworks with inductive codes for context-specific features (e.g., industry resistance; provincial heterogeneity). Trustworthiness was supported through authenticity, portability, precision, and impartiality [ 16 – 18 ]. Quantitative strand: Provincial survey Setting and participants The survey targeted provincial Department of Health directorates/sub-directorates across nine provinces; 57 officials including Directors, Deputy Directors, and Assistant Directors from seven provinces returned complete questionnaires. The instrument elicited priority ranking, resource sufficiency such as human resources, budget, infrastructure, and technology, stakeholder collaboration across policy stages, and SDH inclusion in implementation. Descriptive statistics including frequencies and proportions were produced using Microsoft Excel. Integration and meta-inferences A joint display approach was used to align the findings examining convergence, complementarity, and dissonance. Where dissonance emerged such as documented multi-sectoral intent vs. limited agenda-setting participation, analytic memos were convened to articulate meta-inferences that directly informed strategy statements. Strategies were elaborated through logical reasoning inclusive of inductive generalisation from findings and deductive alignment with frameworks. Consensus validation (Delphi technique) A panel of 12 experts in NCD, policy specialists across academia, provincial services, and PHC participated in iterative Delphi rounds to rate the clarity, comprehensiveness, applicability, adaptability, credibility, and validity of each strategy and proposed monitoring and evaluation indicators. Consensus thresholds and item modifications were documented across rounds. Ethics Ethics approvals were granted by the Tshwane University of Technology Research Ethics Committee (FCRE 2020/01/007 [FCPS O1] [SCI]) and relevant Provincial Departments of Health. Participation was voluntary with written informed consent. Confidentiality and data security procedures adhered to institutional policies for human participant research. Results Qualitative strand All three policies embedded multi-sectoral language and identified diverse stakeholders. However, SDH operationalisation was partial; activities disproportionately targeted governance, selected public/social policies, material circumstances such as facilities for physical activity, and health system processes, with limited explicit mechanisms for socio-economic position, gender, race, education, and psychosocial determinants. Measurement plans often lacked actionable indicators or accountability structures beyond the health sector. Quantitative strand Provinces prioritised maternal/child/women’s health, system transformation, and TB/HIV above NCDs; officials reported insufficient human resources, financing, infrastructure, and technology to implement NCD activities at intended scale. Reported collaboration was high during formulation and implementation but rare in agenda-setting and absent in adoption and evaluation. Non-governmental organisations were frequent partners; faith-based and traditional structures and higher education were seldom included. Convergence Convergence across the two strands highlighted a consistent set of structural barriers that undermine the effective implementation and impact of NCD policies. Both the policy document analysis and the survey of policymakers pointed to limited multisectoral accountability mechanisms, insufficiently specified actions to address key SDH, and persistent constraints in human, financial, and infrastructural resources. Together, these barriers reflected systemic weaknesses that constrain the translation of policy intent into meaningful health outcomes. Complementarity was evident in how the two strands provided distinct but mutually reinforcing explanations of these challenges. The document analysis illuminated why critical SDH domains remain under-addressed, revealing narrow policy scope, weak enforcement provisions, and limited operational guidance for implementation beyond the health sector. In contrast, the quantitative survey data demonstrated how much capacity is lacking at the provincial level by quantifying deficits in staffing, funding, infrastructure, and technological resources necessary to operationalise policy commitments. This complementarity strengthened the overall interpretation by linking policy design limitations with measurable system-level constraints. Dissonance emerged around the policy process itself. Despite strong rhetorical commitments within policy documents to a whole-of-government and multisectoral approach, survey findings indicated that agenda-setting for NCD policies remained largely health-sector centric, with minimal participation from non-health stakeholders. This disconnection between stated policy intentions and observed practice indicates a critical gap in early-stage policy processes, with implications for coordination and long-term sustainability of NCD interventions. From meta-inferences to strategies Integration of findings from the qualitative and quantitative strands was essential for translating complex evidence into actionable policy-improvement strategies. The systematic examination of convergence, complementarity, and dissonance enabled a comprehensive interpretation of how policy design, implementation capacity, and governance processes interact to shape NCD policy effectiveness. Collectively, the integration of convergent, complementary, and dissonant findings ensured that the resulting policy-improvement strategies addressed both structural and operational barriers to NCD prevention and control. Convergence the findings strengthened confidence that the challenges identified were systemic rather than method-specific, justifying the prioritisation of strategies targeting governance reform and coordinated action across sectors. Complementarity enhanced explanatory depth by linking policy intent with implementation realities. The insights gained from both strands informed strategies focused on strengthening early interventions, expanding access to screening and counselling through primary health care, developing and retaining NCD-relevant human resources, and revitalising infrastructure and technology. While dissonance between policy rhetoric and practice was particularly informative as it allowed the researcher to recognise misalignment between policy intent and practice. Accordingly, subsequent strategies prioritised legislating cross-portfolio accountability and establishing a national multisectoral coordinating committee (Table 1 ). Table 1 Summary of policy gaps addressed during each strand (Source: Author’s own) Key gap identified How it showed up in strands Strategy to address the gap Weak multisectoral accountability Qualitative: No enforceable mechanisms Quantitative: Minimal non-health participation Legislate cross-portfolio accountability. National multisectoral coordinating committee Under specified SDH actions Qualitative: SDH not operationalised; Quantitative: Demand for guidance Early interventions across life course & settings. PHC screening/counselling expansion Resource constraints Quantitative: Survey quantified gaps across provinces Develop/retain NCD workforce. Infrastructure & technology with equitable distribution Weak enforcement and compliance Qualitative: Policies show limited enforcement levers Legislation to mandate/enable enforcement. Committee with regulatory powers Fragmented monitoring and evaluation, and unclear indicators Qualitative: Vague indicators; Quantitative: Limited use Embed monitoring and evaluation within committee mandate; indicator set tied to 3–6 interventions Discussion The strength of the convergent parallel design in health policy analysis lies in its ability to reveal policy gaps that would likely remain obscured if a single method were used [ 19 ]. Document analysis alone can reveal what policies state and where provisions are weak or absent [ 19 ] but cannot quantify implementation readiness or resource shortfalls such as provincial human resources gaps, diagnostic capacity, or technology access. While surveys alone can quantify deficits and priorities [ 20 ], but risk misattributing causes such as blaming “lack of resources” without recognising that policy scope, enforcement, and indicators are themselves under-specified in the texts meant to guide implementation. The complexity of NCD policy, spanning multi-stage processes, multi-domain content, and cross-sector structural arrangements makes it unlikely that a single lens would isolate both the design faults and the capacity bottlenecks that co-produce shortfalls [ 21 – 24 ]. Therefore, this worked example shows how a convergent parallel design can clarify causal bottlenecks between what policy requires and what systems can deliver. Running independent strands in parallel prevented premature cross-contamination of interpretations, while integration yielded meta-inferences neither strand could supply on its own, particularly the alignment of SDH scope with provincial readiness and the translation of findings into governable strategies and indicators. The frameworks further strengthened the design and the policy analysis. Stages Heuristics organised the qualitative inquiry around agenda-setting, formulation, adoption, implementation , and evaluation , ensuring that instruments and coding captured who participates when, where decisions concentrate, and how accountability is structured across the policy cycle [ 13 ]. This revealed the early-stage participation gap and weak adoption/evaluation mechanisms. The WHO Analytical Framework for SDH oriented both strands to look for structural and intermediary determinants such as the socioeconomic position, material circumstances, psychosocial factors, and health-system features; and to check whether these were operationalised in policy actions and resourced in provinces [ 14 ]. This exposed the selective SDH coverage in texts and the magnitude of capacity gaps on the ground. Conceptual and analytical frameworks belong in convergent parallel designs for health policy. From the current worked example it’s because they stabilised constructs across strands, which enabled commensurable coding and measurement, and support joint displays that link policy-cycle stages to SDH domains and provincial capacities. These frameworks made the cross-walk from policy intent to system readiness analytically tractable. Integration was deliberately planned a priori to ensure that the qualitative and quantitative strands informed one another in a systematic and transparent manner. Clear criteria were established in advance to determine what would constitute convergence, complementarity, or dissonance, alongside predefined decision rules for adjudicating inconsistencies and the use of joint displays to support the development of robust meta-inferences. Through this process, convergence played a confirmatory role by identifying systemic barriers such as deficits in multisectoral accountability consistently highlighted by both strands, thereby strengthening the case for governance-level reforms rather than isolated programme-specific solutions. Complementarity added explanatory depth by linking insights into why policy gaps persist, drawn from document analysis of policy scope, enforcement mechanisms and indicators, with evidence of how extensive implementation constraints are, as quantified through survey data on human resources, infrastructure and technology. Dissonance also proved analytically productive by exposing misalignments between policy rhetoric and practice, particularly where commitments to whole-of-government approaches were not reflected in health-sector-dominated agenda-setting processes. Rather than weakening the analysis, this dissonance directed attention to early-stage institutional arrangements requiring redesign, reinforcing the value of intentional integration in uncovering root causes of policy underperformance. Deep, framework-guided discussion allowed the study to pin-point root causes of implementation failure such as the missing legal levers for cross-portfolio accountability; under-specification of SDH actions; and non-aligned capacity planning and to translate them into six gap-focused policy-improvement strategies with corresponding monitoring and evaluation indicators. This closes the evidence-to-action loop by connecting diagnosis (what’s wrong and where) to prescription (what to change and how). In conclusion, the convergent parallel design was perfectly suited to probe the deeper structure of NCD policy gaps and shortfalls in South Africa. By protecting strand independence and then integrating with transparent rules, the study aligned what policies ask for with what systems can realistically deliver, identified root causes, and produced evidence-based, governable strategies capable of improving NCD policy implementation at scale. Strengths and limitations This study is strengthened by a theory-informed design, independent analysis of qualitative and quantitative strands, systematic mixed-methods integration, and consensus validation of findings. Methodologically, it offers a reproducible convergent parallel workflow that explicitly links policy processes, SDH content, and system capacity, demonstrating how mixed evidence can be translated into governable, indicator-linked policy-improvement strategies. The integration of Stages Heuristics and the SDH framework extends their use beyond analytic lenses to serve as design scaffolds that stabilise constructs across strands, support joint displays, and enhance the reliability of meta-inferences. Importantly, the study moves from diagnosis to adoption by delivering a Delphi-validated set of strategies directly aligned with identified gaps. Collectively, these elements provide a generalisable blueprint that offers practical guidance for analysing complex health policies beyond the NCD context, including framework anchoring, instrument design, a priori integration rules, and consensus closure. The study also has limitations. Policy selection was purposive and limited to three conditions, provincial survey coverage included seven of nine provinces, and the Delphi panel was weighted towards nursing and primary health-care expertise. While these factors may constrain generalisability, they are appropriate for a worked methodological example and for advancing mixed-methods approaches to health policy analysis. Conclusions For complex, multi-actor policy domains, convergent parallel mixed-methods provide a scalable template to connect policy content to system readiness and governance mechanisms. The South African NCD case shows how to specify, execute, and report such a design and how to translate integrated evidence into validated strategies and indicators suitable for national adoption. The approach generalises to other policy areas that require whole-of-government action. Abbreviations DoH Department of Health NCD Non-Communicable Disease NGO Non-Governmental Organisation PHC Primary Health Care SDH Social Determinants of Health TB Tuberculosis WHO World Health Organization Declarations Ethics approval and consent to participate Approved by the Tshwane University of Technology Research Ethics Committee (FCRE 2020/01/007 [FCPS O1] [SCI]) and Provincial Departments of Health; written informed consent obtained from all participants. Consent for publication Not applicable (No individual person’s data presented). Competing interests The authors declare no competing interests. Funding This article emanates from the Doctoral project supported by the Health and Welfare Sector Education and Training Authority (HWSETA). The funder had no role in study design, data collection/analysis, decision to publish, or manuscript preparation. Author Contribution Richard Rasesemola conceived the study, collected/analysed data, integrated findings, and drafted the manuscript. Acknowledgements The author thanks provincial health officials and Delphi panel experts for their time and insights, and the supervisors for guidance during the doctoral project. Data Availability The underlying policy documents are publicly accessible from the South African Department of Health websites. De-identified survey data are available from the corresponding author upon reasonable request in line with ethics approvals. References Niohuru I. Disease burden and mortality. In: Healthcare and disease burden in Africa: the impact of socioeconomic factors on public health . 2023 Mar 19. pp. 35–85. 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Berkeley (CA): University of California Press; 1984. World Health Organization. Global action plan for the prevention and control of noncommunicable diseases 2013–2020. Geneva: World Health Organization; 2013. Creswell JW, Plano Clark VL. Designing and conducting mixed methods research. 3rd ed. Thousand Oaks (CA): SAGE; 2018. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 06 Apr, 2026 Editor assigned by journal 25 Mar, 2026 Submission checks completed at journal 25 Mar, 2026 First submitted to journal 23 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9203247","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":618747974,"identity":"645828a5-fada-408d-8c8b-8b31f5580ce1","order_by":0,"name":"Richard Rasesemola","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzklEQVRIiWNgGAWjYDACZgY2MMnA3sBgQKIWngPEamGAaZFIIFK9eTvzswc/91hHm898Y1DAUGPHIN9+AL8WmcNs5oY9z9Jz59zOMTBgOJbMwNhDwDoJZh42CZ4Dh3NnSIO0sB0AupEILZJ/QFokzwC1/DvAwMb/gLAWabAtEjwGBoxtBxh4CIWDBDObmbTMgfTcGTxpBQaJfck8EhKEbOE//EzyzQHr3Bnsh7cZfPhmJyffT8AWZMBmAFTMQ7x6IGAm4KJRMApGwSgYqQAABgQ28SkJa6IAAAAASUVORK5CYII=","orcid":"","institution":"University of Johannesburg","correspondingAuthor":true,"prefix":"","firstName":"Richard","middleName":"","lastName":"Rasesemola","suffix":""}],"badges":[],"createdAt":"2026-03-23 17:09:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9203247/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9203247/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106626979,"identity":"1219780f-e5be-4559-a592-92d4413e1aad","added_by":"auto","created_at":"2026-04-10 15:06:48","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":78142,"visible":true,"origin":"","legend":"\u003cp\u003eConvergent parallel design (Source: Author’s own)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9203247/v1/6297b3af490b90f64d13e53a.png"},{"id":106725948,"identity":"f2dde4bc-0a1c-4cf3-809a-b6603a14a10a","added_by":"auto","created_at":"2026-04-12 18:34:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":719043,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9203247/v1/75d13a47-19da-4d4c-8eeb-643f8d44f47f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Convergent parallel mixed-methods design in health policy analysis: A worked example from South Africa’s non-communicable disease policies","fulltext":[{"header":"Background","content":"\u003cp\u003eNon-communicable diseases (NCDs) account for most of the global mortality and represent a substantial and growing burden in sub-Saharan Africa [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In South Africa, several national strategies have been implemented to address NCD risk factors and strengthen service delivery; however, updated mortality surveillance indicates that deaths from NCDs have continued to rise, highlighting persistent implementation and health-system gaps [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. This trend has been attributed to inadequate physical activity promotion, weak regulation of unhealthy food marketing to children, limited enforcement of trans-fat policies, and poor compliance with alcohol advertising controls [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. These challenges highlight the need for methodological approaches that can meaningfully link policy design to on-the-ground system capacity and governance arrangements.\u003c/p\u003e \u003cp\u003eHealth policies addressing NCDs are inherently complex, operating across multiple sectors, levels of governance, and stages of the policy cycle [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Effective NCD prevention and control require coordinated action beyond the health sector, encompassing education, finance, trade, urban planning, and social development, while simultaneously addressing behavioural, environmental, commercial, and structural determinants of health [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Decisions taken during agenda-setting and formulation shape downstream processes of adoption, implementation, and evaluation, meaning that policy effectiveness is influenced not only by policy content but also by enforcement mechanisms, institutional capacity, accountability structures, and the broader socio-political context [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These interdependencies make it difficult to isolate the causes of policy underperformance without approaches capable of capturing both process and content alongside structural constraints.\u003c/p\u003e \u003cp\u003eHistorically, research on health policy has relied largely on single-method approaches, including descriptive policy reviews, qualitative case studies, or quantitative assessments of system performance and outcomes [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. While such approaches have yielded valuable insights, they often examine policy content, implementation processes, or capacity constraints in isolation [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Policy analyses may document stated intentions without assessing feasibility, while quantitative evaluations may measure resource availability or outcomes without interrogating weaknesses in policy design, enforcement, or governance [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. As a result, the interdependencies between policy intent and implementation realities are frequently under-specified [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], limiting the ability of such studies to identify root causes of persistent implementation gaps.\u003c/p\u003e \u003cp\u003eConvergent parallel mixed-methods designs, which analyse qualitative and quantitative strands independently and integrate findings during interpretation, offer a coherent approach for addressing this complexity [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. By examining what policies say, what systems can deliver, and where misalignments occur, such designs enable a more comprehensive understanding of policy effectiveness. Therefore, this article presents a worked example of a convergent parallel mixed-methods study applied to South Africa\u0026rsquo;s NCD policy environment. Grounded in a doctoral project, this article focuses explicitly on methodological architecture, integration logic, and validation processes that support the development of actionable, evidence-informed policy-improvement strategies.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and rationale\u003c/h2\u003e \u003cp\u003eConvergent parallel mixed-methods design was used to examine complex gaps in NCD policy implementation. Qualitative policy document analysis and quantitative survey data were conducted contemporaneously, analysed independently and integrated through convergence, complementarity, and dissonance to inform evidence-based strategy development (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA convergent parallel mixed-methods design supported corroboration and complementarity, allowing discordant findings to surface and be reconciled into actionable strategies.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eConceptual and analytical frameworks\u003c/h3\u003e\n\u003cp\u003eThe study was underpinned by two complementary theoretical frameworks that informed the selection of data-collection tools, and guided strand-specific analyses. Stages Heuristics framework was used to guide a process-oriented analysis of policy development and implementation by conceptualising the policy cycle as a series of interconnected stages including agenda-setting, formulation, adoption, implementation, and evaluation [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. This framework informed the design of data-collection tools by ensuring that questions and analytical categories captured stakeholder involvement, decision-making processes, and implementation experiences across each stage of the policy process. By structuring the inquiry along these stages, the study was able to systematically examine where participation, coordination, and accountability were strengthened or weakened, and how these dynamics influenced programme outcomes.\u003c/p\u003e \u003cp\u003eIn parallel, the World Health Organization\u0026rsquo;s (WHO) Analytical Framework for Social Determinants of Health (SDH) provided a substantive lens for examining policy content and implementation practices [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. This framework guided the development of document-analysis criteria and survey items aimed at identifying whether, and how, structural and intermediary determinants such as socio-economic position, material circumstances, psychosocial factors, and health-system characteristics were explicitly addressed within policy activities and service delivery mechanisms. The SDH framework ensured that the analysis extended beyond procedural aspects of policymaking to interrogate the extent to which broader social and systemic drivers of health were operationalised in practice.\u003c/p\u003e \u003cp\u003eTogether, the integration of the Stages Heuristics and the SDH framework enabled a coherent alignment between theory, tools, and methods. While Stages Heuristics structured the examination of \u003cem\u003ehow\u003c/em\u003e policies were developed and implemented [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], the SDH framework illuminated \u003cem\u003ewhat\u003c/em\u003e determinants were prioritised within those processes [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. This combined theoretical grounding strengthened the study\u0026rsquo;s ability to generate context-responsive and actionable recommendations for improving policy design, delivery, and impact.\u003c/p\u003e\n\u003ch3\u003eQualitative strand: Document analysis\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eSampling and data sources\u003c/h2\u003e \u003cp\u003eThe three policies were purposively selected for analysis because the diseases they target. Obesity-related conditions such as endocrine, nutritional and metabolic diseases accounted for approximately 7% of all registered deaths between 2015 and 2017 [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Mental and behavioural disorders accounted for approximately 0.5\u0026ndash;0.6% of registered deaths between 2015 and 2017 [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. While deaths due to neoplasms increased steadily, with cancers accounting for approximately 9\u0026ndash;10% of all registered deaths by 2017 which are among the leading contributors to morbidity and mortality in South Africa and collectively account for a substantial proportion of NCD deaths [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. This article focuses on these policies to examine whether existing national responses adequately address the scale, drivers, and determinants of these high-burden conditions.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData extraction and coding\u003c/h3\u003e\n\u003cp\u003eA structured data-extraction tool designed by the researcher, captured policy provenance, agenda and stakeholder mapping, SDH domains embedded in key activities, and implementation/measurement plans. Thematic coding combined deductive categories from the two frameworks with inductive codes for context-specific features (e.g., industry resistance; provincial heterogeneity). Trustworthiness was supported through authenticity, portability, precision, and impartiality [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eQuantitative strand: Provincial survey\u003c/h2\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eSetting and participants\u003c/h2\u003e \u003cp\u003eThe survey targeted provincial Department of Health directorates/sub-directorates across nine provinces; 57 officials including Directors, Deputy Directors, and Assistant Directors from seven provinces returned complete questionnaires. The instrument elicited priority ranking, resource sufficiency such as human resources, budget, infrastructure, and technology, stakeholder collaboration across policy stages, and SDH inclusion in implementation. Descriptive statistics including frequencies and proportions were produced using Microsoft Excel.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eIntegration and meta-inferences\u003c/h3\u003e\n\u003cp\u003eA joint display approach was used to align the findings examining convergence, complementarity, and dissonance. Where dissonance emerged such as documented multi-sectoral intent vs. limited agenda-setting participation, analytic memos were convened to articulate meta-inferences that directly informed strategy statements. Strategies were elaborated through logical reasoning inclusive of inductive generalisation from findings and deductive alignment with frameworks.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eConsensus validation (Delphi technique)\u003c/h2\u003e \u003cp\u003eA panel of 12 experts in NCD, policy specialists across academia, provincial services, and PHC participated in iterative Delphi rounds to rate the clarity, comprehensiveness, applicability, adaptability, credibility, and validity of each strategy and proposed monitoring and evaluation indicators. Consensus thresholds and item modifications were documented across rounds.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eEthics\u003c/h2\u003e \u003cp\u003e \u003cstrong\u003eEthics approvals\u003c/strong\u003e \u003cp\u003ewere granted by the Tshwane University of Technology Research Ethics Committee (FCRE 2020/01/007 [FCPS O1] [SCI]) and relevant Provincial Departments of Health. Participation was voluntary with written informed consent. Confidentiality and data security procedures adhered to institutional policies for human participant research.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eQualitative strand\u003c/h2\u003e \u003cp\u003eAll three policies embedded multi-sectoral language and identified diverse stakeholders. However, SDH operationalisation was partial; activities disproportionately targeted governance, selected public/social policies, material circumstances such as facilities for physical activity, and health system processes, with limited explicit mechanisms for socio-economic position, gender, race, education, and psychosocial determinants. Measurement plans often lacked actionable indicators or accountability structures beyond the health sector.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eQuantitative strand\u003c/h2\u003e \u003cp\u003eProvinces prioritised maternal/child/women\u0026rsquo;s health, system transformation, and TB/HIV above NCDs; officials reported insufficient human resources, financing, infrastructure, and technology to implement NCD activities at intended scale. Reported collaboration was high during formulation and implementation but rare in agenda-setting and absent in adoption and evaluation. Non-governmental organisations were frequent partners; faith-based and traditional structures and higher education were seldom included.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eConvergence\u003c/h2\u003e \u003cp\u003eConvergence across the two strands highlighted a consistent set of structural barriers that undermine the effective implementation and impact of NCD policies. Both the policy document analysis and the survey of policymakers pointed to limited multisectoral accountability mechanisms, insufficiently specified actions to address key SDH, and persistent constraints in human, financial, and infrastructural resources. Together, these barriers reflected systemic weaknesses that constrain the translation of policy intent into meaningful health outcomes.\u003c/p\u003e \u003cp\u003eComplementarity was evident in how the two strands provided distinct but mutually reinforcing explanations of these challenges. The document analysis illuminated \u003cem\u003ewhy\u003c/em\u003e critical SDH domains remain under-addressed, revealing narrow policy scope, weak enforcement provisions, and limited operational guidance for implementation beyond the health sector. In contrast, the quantitative survey data demonstrated \u003cem\u003ehow much\u003c/em\u003e capacity is lacking at the provincial level by quantifying deficits in staffing, funding, infrastructure, and technological resources necessary to operationalise policy commitments. This complementarity strengthened the overall interpretation by linking policy design limitations with measurable system-level constraints.\u003c/p\u003e \u003cp\u003eDissonance emerged around the policy process itself. Despite strong rhetorical commitments within policy documents to a whole-of-government and multisectoral approach, survey findings indicated that agenda-setting for NCD policies remained largely health-sector centric, with minimal participation from non-health stakeholders. This disconnection between stated policy intentions and observed practice indicates a critical gap in early-stage policy processes, with implications for coordination and long-term sustainability of NCD interventions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eFrom meta-inferences to strategies\u003c/h2\u003e \u003cp\u003eIntegration of findings from the qualitative and quantitative strands was essential for translating complex evidence into actionable policy-improvement strategies. The systematic examination of convergence, complementarity, and dissonance enabled a comprehensive interpretation of how policy design, implementation capacity, and governance processes interact to shape NCD policy effectiveness. Collectively, the integration of convergent, complementary, and dissonant findings ensured that the resulting policy-improvement strategies addressed both structural and operational barriers to NCD prevention and control.\u003c/p\u003e \u003cp\u003eConvergence the findings strengthened confidence that the challenges identified were systemic rather than method-specific, justifying the prioritisation of strategies targeting governance reform and coordinated action across sectors. Complementarity enhanced explanatory depth by linking policy intent with implementation realities. The insights gained from both strands informed strategies focused on strengthening early interventions, expanding access to screening and counselling through primary health care, developing and retaining NCD-relevant human resources, and revitalising infrastructure and technology. While dissonance between policy rhetoric and practice was particularly informative as it allowed the researcher to recognise misalignment between policy intent and practice. Accordingly, subsequent strategies prioritised legislating cross-portfolio accountability and establishing a national multisectoral coordinating committee (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of policy gaps addressed during each strand\u003c/p\u003e \u003cdiv class=\"Credit\"\u003e\u003cp\u003e(Source: Author\u0026rsquo;s own)\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKey gap identified\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHow it showed up in strands\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStrategy to address the gap\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeak multisectoral accountability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQualitative: No enforceable mechanisms\u003c/p\u003e \u003cp\u003eQuantitative: Minimal non-health participation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLegislate cross-portfolio accountability.\u003c/p\u003e \u003cp\u003eNational multisectoral coordinating committee\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnder specified SDH actions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQualitative: SDH not operationalised; Quantitative: Demand for guidance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEarly interventions across life course \u0026amp; settings.\u003c/p\u003e \u003cp\u003ePHC screening/counselling expansion\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResource constraints\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuantitative: Survey quantified gaps across provinces\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDevelop/retain NCD workforce.\u003c/p\u003e \u003cp\u003eInfrastructure \u0026amp; technology with equitable distribution\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeak enforcement and compliance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQualitative: Policies show limited enforcement levers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLegislation to mandate/enable enforcement.\u003c/p\u003e \u003cp\u003eCommittee with regulatory powers\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFragmented monitoring and evaluation, and unclear indicators\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQualitative: Vague indicators; Quantitative: Limited use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEmbed monitoring and evaluation within committee mandate; indicator set tied to 3\u0026ndash;6 interventions\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe strength of the convergent parallel design in health policy analysis lies in its ability to reveal policy gaps that would likely remain obscured if a single method were used [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Document analysis alone can reveal \u003cem\u003ewhat\u003c/em\u003e policies state and \u003cem\u003ewhere\u003c/em\u003e provisions are weak or absent [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] but cannot quantify implementation readiness or resource shortfalls such as provincial human resources gaps, diagnostic capacity, or technology access. While surveys alone can quantify deficits and priorities [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], but risk misattributing causes such as blaming \u0026ldquo;lack of resources\u0026rdquo; without recognising that policy scope, enforcement, and indicators are themselves under-specified in the texts meant to guide implementation. The complexity of NCD policy, spanning multi-stage processes, multi-domain content, and cross-sector structural arrangements makes it unlikely that a single lens would isolate both the design faults and the capacity bottlenecks that co-produce shortfalls [\u003cspan additionalcitationids=\"CR22 CR23\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Therefore, this worked example shows how a convergent parallel design can clarify causal bottlenecks between what policy requires and what systems can deliver. Running independent strands in parallel prevented premature cross-contamination of interpretations, while integration yielded meta-inferences neither strand could supply on its own, particularly the alignment of SDH scope with provincial readiness and the translation of findings into governable strategies and indicators.\u003c/p\u003e \u003cp\u003eThe frameworks further strengthened the design and the policy analysis. Stages Heuristics organised the qualitative inquiry around \u003cem\u003eagenda-setting, formulation, adoption, implementation\u003c/em\u003e, and \u003cem\u003eevaluation\u003c/em\u003e, ensuring that instruments and coding captured who participates when, where decisions concentrate, and how accountability is structured across the policy cycle [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. This revealed the early-stage participation gap and weak adoption/evaluation mechanisms. The WHO Analytical Framework for SDH oriented both strands to look for structural and intermediary determinants such as the socioeconomic position, material circumstances, psychosocial factors, and health-system features; and to check whether these were operationalised in policy actions and resourced in provinces [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. This exposed the selective SDH coverage in texts and the magnitude of capacity gaps on the ground.\u003c/p\u003e \u003cp\u003eConceptual and analytical frameworks belong in convergent parallel designs for health policy. From the current worked example it\u0026rsquo;s because they stabilised constructs across strands, which enabled commensurable coding and measurement, and support joint displays that link policy-cycle stages to SDH domains and provincial capacities. These frameworks made the cross-walk from policy intent to system readiness analytically tractable.\u003c/p\u003e \u003cp\u003eIntegration was deliberately planned \u003cem\u003ea priori\u003c/em\u003e to ensure that the qualitative and quantitative strands informed one another in a systematic and transparent manner. Clear criteria were established in advance to determine what would constitute convergence, complementarity, or dissonance, alongside predefined decision rules for adjudicating inconsistencies and the use of joint displays to support the development of robust meta-inferences. Through this process, convergence played a confirmatory role by identifying systemic barriers such as deficits in multisectoral accountability consistently highlighted by both strands, thereby strengthening the case for governance-level reforms rather than isolated programme-specific solutions. Complementarity added explanatory depth by linking insights into \u003cem\u003ewhy\u003c/em\u003e policy gaps persist, drawn from document analysis of policy scope, enforcement mechanisms and indicators, with evidence of \u003cem\u003ehow extensive\u003c/em\u003e implementation constraints are, as quantified through survey data on human resources, infrastructure and technology. Dissonance also proved analytically productive by exposing misalignments between policy rhetoric and practice, particularly where commitments to whole-of-government approaches were not reflected in health-sector-dominated agenda-setting processes. Rather than weakening the analysis, this dissonance directed attention to early-stage institutional arrangements requiring redesign, reinforcing the value of intentional integration in uncovering root causes of policy underperformance.\u003c/p\u003e \u003cp\u003eDeep, framework-guided discussion allowed the study to pin-point root causes of implementation failure such as the missing legal levers for cross-portfolio accountability; under-specification of SDH actions; and non-aligned capacity planning and to translate them into six gap-focused policy-improvement strategies with corresponding monitoring and evaluation indicators. This closes the evidence-to-action loop by connecting diagnosis (what\u0026rsquo;s wrong and where) to prescription (what to change and how).\u003c/p\u003e \u003cp\u003eIn conclusion, the convergent parallel design was perfectly suited to probe the deeper structure of NCD policy gaps and shortfalls in South Africa. By protecting strand independence and then integrating with transparent rules, the study aligned what policies ask for with what systems can realistically deliver, identified root causes, and produced evidence-based, governable strategies capable of improving NCD policy implementation at scale.\u003c/p\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eThis study is strengthened by a theory-informed design, independent analysis of qualitative and quantitative strands, systematic mixed-methods integration, and consensus validation of findings. Methodologically, it offers a reproducible convergent parallel workflow that explicitly links policy processes, SDH content, and system capacity, demonstrating how mixed evidence can be translated into governable, indicator-linked policy-improvement strategies. The integration of Stages Heuristics and the SDH framework extends their use beyond analytic lenses to serve as design scaffolds that stabilise constructs across strands, support joint displays, and enhance the reliability of meta-inferences. Importantly, the study moves from diagnosis to adoption by delivering a Delphi-validated set of strategies directly aligned with identified gaps. Collectively, these elements provide a generalisable blueprint that offers practical guidance for analysing complex health policies beyond the NCD context, including framework anchoring, instrument design, \u003cem\u003ea priori\u003c/em\u003e integration rules, and consensus closure.\u003c/p\u003e \u003cp\u003eThe study also has limitations. Policy selection was purposive and limited to three conditions, provincial survey coverage included seven of nine provinces, and the Delphi panel was weighted towards nursing and primary health-care expertise. While these factors may constrain generalisability, they are appropriate for a worked methodological example and for advancing mixed-methods approaches to health policy analysis.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eFor complex, multi-actor policy domains, convergent parallel mixed-methods provide a scalable template to connect policy content to system readiness and governance mechanisms. The South African NCD case shows how to specify, execute, and report such a design and how to translate integrated evidence into validated strategies and indicators suitable for national adoption. The approach generalises to other policy areas that require whole-of-government action.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDoH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDepartment of Health\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNCD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNon-Communicable Disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNGO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNon-Governmental Organisation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePHC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePrimary Health Care\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSDH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSocial Determinants of Health\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTuberculosis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWHO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWorld Health Organization\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003eApproved by the Tshwane University of Technology Research Ethics Committee (FCRE 2020/01/007 [FCPS O1] [SCI]) and Provincial Departments of Health; written informed consent obtained from all participants.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable (No individual person\u0026rsquo;s data presented).\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis article emanates from the Doctoral project supported by the Health and Welfare Sector Education and Training Authority (HWSETA). The funder had no role in study design, data collection/analysis, decision to publish, or manuscript preparation.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eRichard Rasesemola conceived the study, collected/analysed data, integrated findings, and drafted the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThe author thanks provincial health officials and Delphi panel experts for their time and insights, and the supervisors for guidance during the doctoral project.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe underlying policy documents are publicly accessible from the South African Department of Health websites. De-identified survey data are available from the corresponding author upon reasonable request in line with ethics approvals.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eNiohuru I. Disease burden and mortality. 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Thousand Oaks (CA): SAGE; 2018.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-research-methodology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmrm","sideBox":"Learn more about [BMC Medical Research Methodology](http://bmcmedresmethodol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmrm/default.aspx","title":"BMC Medical Research Methodology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"mixed methods, health policy analysis, Stages Heuristics, social determinants of health, non-communicable diseases, South Africa, convergent parallel design, Delphi technique","lastPublishedDoi":"10.21203/rs.3.rs-9203247/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9203247/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eHealth policy problems such as the rising burden of non-communicable diseases (NCDs) in South Africa are complex and cross-sectoral. Methodological approaches that integrate policy content, context, actors, and system capacities can yield more actionable insights for implementation than single-method designs.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis article presents a worked example of a convergent parallel mixed-methods design for health policy analysis, combining (i) qualitative document analysis of three purposively selected health policies and a quantitative provincial-level survey of policy-relevant health officials (n\u0026thinsp;=\u0026thinsp;57) from seven provinces in South Africa. Analyses were conducted independently and integrated at the interpretation stage to develop and validate policy-improvement strategies through a Delphi process. The design was theoretically anchored in Stages Heuristics and the WHO Analytical Framework for Social Determinants of Health (SDH).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe qualitative strand identified strong multi-stakeholder involvement in policy formulation with limited operationalisation of critical SDH domains such as socio-economic position, gender, race, and education. The quantitative strand revealed capacity constraints: human resources, financing, technology, and infrastructure that limit implementation readiness at provincial level and crowd out NCD activities relative to other priorities. Integrated interpretation produced six Delphi-validated strategies.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eConvergent parallel mixed-methods design is feasible, informative, and well-suited to health policy analysis where actionable guidance requires the triangulation of policy content with system capacities and governance realities. The worked example demonstrates how to specify strands, preserve independence, integrate findings, and move from evidence to implementable strategies and indicators.\u003c/p\u003e","manuscriptTitle":"Convergent parallel mixed-methods design in health policy analysis: A worked example from South Africa’s non-communicable disease policies","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-10 15:06:45","doi":"10.21203/rs.3.rs-9203247/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-04-06T10:56:51+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-25T05:57:42+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-25T05:57:34+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Research Methodology","date":"2026-03-23T17:04:10+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-research-methodology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmrm","sideBox":"Learn more about [BMC Medical Research Methodology](http://bmcmedresmethodol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmrm/default.aspx","title":"BMC Medical Research Methodology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b693e377-998c-4eca-a6a2-fc4b81134127","owner":[],"postedDate":"April 10th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-10T15:06:45+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-10 15:06:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9203247","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9203247","identity":"rs-9203247","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}