ResearchPod Summary
Continuity of Midwifery Care (CMC) is a core component of Scottish maternity policy, yet its implementation has been hindered by a lack of a unified research strategy. While CMC is globally recognized for improving maternal and neonatal outcomes, Scottish efforts have previously lacked a proactive, evidence-based roadmap. This study aimed to bridge this gap by developing a systematic, stakeholder-informed research mission, vision, and agenda to guide future CMC research in Scotland.
Guided by implementation science, the researchers engaged 24 diverse stakeholders, including midwives, academics, policymakers, and service user advocates. The team employed a multi-stage process involving online polling, brainstorming sessions, and plenary discussions to gather insights. Data were synthesized through structural text reduction and interquartile ranking to identify key content elements. The team used the Tailored Implementation for Chronic Diseases (TICD) framework to categorize determinants affecting the functionality of the proposed mission and vision. Finally, stakeholders ranked 16 potential research topics to establish a prioritized agenda.
The study successfully formulated a clear mission and vision for CMC research, emphasizing the empowerment of midwives, the expansion of the evidence base, and the elevation of the 'being with women' philosophy. The analysis revealed that the 'capacity for organizational change'—specifically the priority of necessary change and capable leadership—is the most critical determinant for the success of this research strategy. Among the research agenda priorities, economic evaluation of CMC was ranked highest, followed by topics concerning the organization and management of care and the needs of future generations of users and providers.
Alex: Welcome to another episode of ResearchPod. Today we're looking at how to build a coherent research strategy for Continuity of Midwifery Care in Scotland — and more specifically, at the methodological challenge of getting there.
Sam: Which is what, exactly? Midwifery care models aren't exactly a new topic.
Alex: Right, but the problem this paper attacks isn't the care model itself — it's the research infrastructure around it. Continuity of Midwifery Care, CMC, has decent evidence for clinical outcomes, but the implementation literature is fragmented. Different health boards, different priorities, no shared agenda. So the question becomes: how do you build one that's actually actionable, rather than a wishlist?
Sam: And the answer involves implementation science rather than just another stakeholder survey?
Alex: That's the key design choice. They anchored the whole process to the Tailored Implementation for Chronic Diseases framework — TICD — which maps determinants of change across levels: the individual practitioner, the team, the organisation, the system. Using that as the scaffold meant stakeholder input had to be sorted against a theory of what actually drives implementation, not just what people feel is important.
Sam: So how did they operationalise that? Twenty-four stakeholders is a small N for something this ambitious.
Alex: It is, and that's worth flagging. The sample included managers, clinicians, and service users — so the range is there — but the numbers constrain how much you can claim about representativeness. What they did methodologically was use a multi-stage reduction process. They started with open brainstorming to generate a broad topic pool, then applied structural text reduction to collapse that into discrete, non-overlapping units of significance. Think of it as a principled thematic compression — the goal is to get rid of redundancy without losing conceptual coverage.
Sam: And then ranking?
Alex: Then interquartile ranking. Rather than majority vote or simple frequency counts, they used the interquartile range to identify topics with both high central tendency and low dispersion — meaning broad agreement, not just popularity among a vocal subset. That's a meaningful methodological choice because it filters out topics that one or two stakeholders feel strongly about but that don't have cross-group traction.
By providing a structured, stakeholder-validated research agenda, this study offers a roadmap for researchers, funders, and policymakers to align their efforts. It shifts the focus from reactive, fragmented studies to a cohesive strategy that supports the long-term sustainability and evidence-based development of CMC, ultimately aiming to improve maternity care outcomes and professional practice in Scotland.
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Sam: What survived that filter?
Alex: The two load-bearing findings — the ones the paper's central claim actually rests on — are that "priority of necessary change" and "capable leadership" mapped as the primary determinants of whether a research strategy could function in practice. Those aren't just high-ranked topics; they're the conditions under which any of the other research questions become answerable. If health board leadership doesn't treat CMC implementation as a priority, the evidence base doesn't get used regardless of its quality.
Sam: That's almost a structural argument rather than an empirical one.
Alex: Exactly, and I think that's where the paper is most interesting to a methodologically-minded reader. They're not just reporting what stakeholders want studied — they're arguing that the feasibility of a research agenda is itself a function of organisational determinants. The TICD framework forces that question to be explicit.
Sam: What were the substantive research priorities that came out of the ranking?
Alex: Economic evaluation and the management of continuity of care were the highest-ranked substantive topics. The economic evaluation piece is particularly telling — health board managers are the ones holding implementation budgets, and without a credible cost-effectiveness case, CMC expansion stalls at the commissioning stage. That's not a new problem in implementation science, but it's useful to see it surface so clearly in the ranking rather than being assumed.
Sam: A careful referee would push on generalisability here. This is a Scottish context with a specific NHS structure.
Alex: That's the central limitation, and the authors are candid about it. The specific priority rankings are context-dependent — a different health system with different commissioning structures would likely produce a different ordering. What the paper is actually offering is the methodology for building a stakeholder-informed, implementation-grounded research agenda, not a universal list of questions. The TICD mapping process is portable; the outputs aren't meant to be.
Sam: So the contribution is more about the process than the product.
Alex: Which is a legitimate contribution, but it does mean you have to read the paper at the right level of abstraction. If you're a Scottish health board researcher, the specific priorities matter. If you're working in a different system, the value is in the funnel — brainstorming to structural reduction to interquartile ranking to framework mapping — as a replicable approach to agenda-setting under conditions of stakeholder heterogeneity.
Sam: Are there things the paper doesn't test that a follow-up should?
Alex: A few. The ranking tells you what stakeholders agreed was important, but it doesn't tell you whether acting on those priorities actually shifts implementation outcomes. That's the next empirical step — does a research agenda built this way produce studies that health boards actually use? There's also a question about whether the TICD framework itself is the right scaffold for maternity care specifically, given it was developed for chronic disease management. The authors use it pragmatically, but a more critical treatment of that choice would strengthen the theoretical grounding.
Sam: So it's a well-executed first step in a longer methodological programme.
Alex: That's a fair read. It establishes a replicable process, surfaces the organisational conditions that constrain implementation research, and produces a ranked agenda grounded in cross-stakeholder consensus. The limitations are real — small N, single context, no outcome validation — but they're appropriate to the stage of work. Thanks for listening to ResearchPod.