Collaborative Micro-Practices of Expert Healthcare Dyads: Implications for Medical Education

Research Design

We conducted a limited realist-perspective study using Template Analysis [16], a method well suited for exploring the nuanced collaborative micro-practices of healthcare dyads [17, 18]. We developed a preliminary coding “template” (informed by relational coordination and distributed cognition), applied the template to the data, and then iteratively modified it (adding, deleting, reorganising codes) as further data were coded. While template analysis allows for flexible, iterative application of both inductive and deductive coding, it differs from other analytical approaches such as directed content analysis which begins deductively with a set of theory-derived codes and seeks to validate or refine existing frameworks, only allowing new codes where data does not fit the template [19]. Using template analysis allowed us to generate inductive codes which we agreed gave richer insight to our data.

Theoretical Rationale and Sensitizing Frameworks

We selected relational coordination and distributed cognition as the apriori concepts for this thematic analysis to guide our study of expert healthcare dyads [11, 20]. Relational coordination theory conceptualizes coordination not purely as task alignment, but as relational work: relationships characterized by shared goals, shared knowledge, and mutual respect, which support frequent, timely, accurate, problem-solving communication (the core relational coordination theory dimensions). In high-stakes, interdependent clinical environments, relational coordination helps explain how relational dynamics underpin performance [21].

Distributed cognition shifts the focus from cognition as individual mental work toward cognition distributed across people, tools, environment, and time (i.e. shared mental models, artifacts, interactivity) [11]. Especially in procedural or acute care settings, where clinicians coordinate with instruments, displays, checklists, and environmental cues; distributed cognition helps us see how dyads extend cognition beyond individual minds.

Together, relational coordination and distributed cognition permitted us to scaffold our template analysis: relational coordination alerted us to relational codes (e.g. trust, communication patterns, shared understanding) while distributed cognition prompted codes about external supports, artifacts, cueing, distributed memory, and shared mental models. In our iterative coding process, we remained open to generating themes not anticipated by either theory, using relational coordination and distributed cognition more as lenses to organize and interpret the themes. Later, in discussing the expert dyad framework which we have developed, we map how each collaborative practice both aligns with and extends these theoretical lenses, demonstrating how micro-practices (e.g. gesture, calibration) embody and enrich the model. Relational coordination and distributed cognition emphasize the interdependent, contextual nature of teamwork; aligning well with our aim to examine how expert dyads enact collaborative expertise.

Research Setting and Participants

We recruited participants from acute care environments; specifically operating rooms (OR), intensive care units (ICU, NICU), emergency rooms (ED); and delivery suites within tertiary hospitals in Australia, Switzerland, and the United States. We used a multi-national design to more rapidly access high-performing dyads across Australia, Switzerland, and the United States thus enriching the study’s credibility and transferability. These diverse settings bring variation in training traditions, organizational norms, communication culture, and healthcare systems. Our goal was to uncover micro-practices of dyadic collaboration that are resilient across different contexts, while also identifying context-sensitive variations. The multi-country design mitigates local bias and facilitates theory generalisability. Ultimately, this approach strengthens our confidence that the Expert Dyad Framework (EDF) captures relational and cognitive behaviors broadly relevant to global medical education and clinical practice.

KW and MM reached out to these medical dyads through professional associations, both verbally and via email, outlining the research objectives, procedures, and the informed consent process. The participants responded either verbally or through email. The settings we chose are characterized by high clinical complexity and high prevalence of medical error, making them ideal contexts to study expert collaboration [22]. Twenty participants, forming 10 interprofessional dyads, were purposively selected based on external perception (peer review or reputation). Inclusion criteria included daily practice together for at least one year of shared work experience in an acute, multi-team environment. The dyadic teams were considered experts and high performing by their supervisors and facility leaders. We defined a high-performing dyad as one that demonstrated all ten competencies outlined in the Team FIRST framework by Greilich et al; including structured communication, mutual trust, reflection and debriefing [3]. They were also considered experienced and expert teams in their specialties. Table 1 summarizes participant demographics.

Data Collection

We created a semi-structured interview guide comprising questions based on educational theorist, Peggy Dettmer’s work on learning theory. She suggests four domains: interpersonal, emotional, cognitive, and physical/psychomotor [23]. To investigate how team members’ behaviours depend on one another and how recurring behaviour patterns emerge, we employed Kolbe’s adaptation of circular questions, a technique borrowed from family-therapy and simulation settings [24]. The guide (Appendix 1) as suggested by Morrison 2015, was not pilot tested, but refined iteratively as interviews progressed [25].

KW and MM conducted interviews between May and November 2022. Two interviews were co-conducted to establish alignment on approach; the remainder were administered by KW. Interviews were conducted with dyadic partners together, to foster naturalistic interaction and shared storytelling [26, 27]. Each session was conducted on the Zoom platform, was audio-recorded and auto-transcribed and lasted between 45–60 minutes. Interview topics included how the dyad managed trust, communication, coordination under pressure, and reflective practice.

Although participants came from different countries, disciplines, and contexts (which shaped how they described their dyadic collaborations), they all expressed mutual respect and willingness to share freely. This diversity enriched our findings by revealing both shared practices and setting-specific priorities. We treat this variation as a strength, expanding the interpretive scope rather than suggesting a single, monolithic model of dyadic practice.

Data Analysis

We approached analysis using template analysis as a hybrid deductive–inductive method. We began with a preliminary coding template informed by relational coordination and distributed cognition theories, containing initial apriori codes such as shared goals, shared knowledge, coordination cues, distributed cognition, and communication patterns. The first three interview transcripts were independently open coded by KW, MM, and MA to identify emergent behaviors or language beyond the initial template (e.g. emotional regulation, boundary norms, gestural communication). In iterative analytic meetings, we compared these initial codes, merged overlapping constructs, refined definitions, and developed a codebook with about 15 mid-level codes. Each code was accompanied by memos documenting the rationale for inclusion and boundaries.

Using that refined codebook, team members coded subsequent transcripts, meeting regularly to resolve discrepancies, discuss edge cases, and revise the codebook when we saw new patterns. We maintained an audit trail of code changes, recorded interpretive decisions, and used reflexive discussion to surface how our backgrounds shaped coding. Once coding was complete, we grouped codes into higher-order categories (for example, “coordination behaviors “and “relational dynamics,”) and iteratively tested whether these categories could cohere into a small set of collaborative practices across dyads. Through this process, we converged on four practices which surfaced repeatedly that included Connectedness, Situation Awareness, Physical Communication and Reflective Practice, and meaningfully captured dyadic dynamic patterns.

In the final interpretive phase, we mapped these practices back to relational coordination and distributed cognition theory, interpreting how each practice embodies or nuances theoretical constructs (e.g. gestural cueing as physical communication, connectedness as trust in relational coordination). Analysis continued until the data were judged to be sufficiently rich and that we had an adequate depth of understanding across participants [28, 29]. To promote trustworthiness, we used triangulation (multiple coders), detailed audit memos, exemplar quotations in results, and periodic reflexivity checks.

Reflexivity

Here we describe how the lenses our author team brought to our study may have influenced what we saw, valued, or emphasized in this study. By reflexivity, we mean cultivating explicit awareness of the ways our own perspectives and professional roles shaped how we framed the study and interpreted the data.

KW’s background is in sports doubles teams, clinical and administrative healthcare teams, and the development of programs designed to optimise team dynamics, and brings a lens shaped by both performance-based and systems-oriented perspectives to this study. MA is an educational scientist and instructional designer whose work focuses on translating theoretical frameworks into practical curriculum design within health professions education. Her extensive experience in faculty development and instructional innovation has likely heightened her sensitivity to the educational potential of dyadic interactions—particularly in how such relationships contribute to shaping meaningful learning experiences and fostering professional identity development. JWR is a lifelong athlete, simulation educator and researcher whose expertise in and affinity for deliberate practice, reflection, and mastery learning both informed—and may have biased—her take on study design and data interpretation. MK’s extensive experience in co-leading and researching simulation trainings, debriefing, and faculty development has likely shaped her view on the role of trust, relational coordination and candour in dyadic interactions. MM is an Emergency Physician and Simulation Educator. His work has a specific focus on resuscitation efforts of patients in critical care situations as well as training to those situations over the last 15 years. This work has likely piqued interest and built awareness around aspects of dyadic relationships and their impact on performance in critical care environments. As an obstetrician, PWT works in dyads of differing composition, for instance with anaesthesiology colleagues and with clinical midwifes. In his role as vice-dean, he has a dyadic relationship with the operational manager for education. In his experience, the value of dyadic work is recognized but not often explicitly discussed.

Ethical Approval

This study received ethics approval through the Biomedical Research Alliance of New York (BRANY), an AAHRPP accredited organization, file number #21-12-498-373(HHC).

Trust (Foundational Theme)

Trust fostered partners’ abilities to perform confidently, grow psychological safety, and underpinned all other practices. Table 2 includes subthemes, and illustrative participant quotes from expert dyads, demonstrating trust as a foundation for effective collaboration.

Connectedness

We define connectedness in healthcare dyads as comprising shared experience, transparency, humour, and remaining calm under pressure. Although no published work defines connectedness exactly this way, our formulation is informed by constructs in relational practice (which emphasize transparent relational atunement) and psychological safety (which supports emotional regulation and openness). We also draw on team literature on humour, where Lingard in 2013 defines humour as part of the drama of professional socialism [30]. Table 3 includes subthemes, and illustrative participant quotes from expert dyads demonstrating connectedness as a foundation for effective collaboration.

Situation Awareness

Wright, 2004 defines situation awareness “as a person’s perception of elements in the environment, comprehension of that information, and the ability to project future events based on this understanding”. Dyads cultivated situation awareness in both the clinical and emotional context through shared mental models and the ability to “read the room” Table 4. Table 4 includes subthemes, and illustrative participant quotes from expert dyads, demonstrating situation awareness as a foundation for effective collaboration.

Physical Communication

Eye contact and gestural communication, touch, and body language enabled silent coordination, reassurance, and emotion regulation. Table 5 includes subthemes, and illustrative participant quotes from expert dyads, demonstrating physical communication as a foundation for effective collaboration.

Reflective Practice

Reflection was embedded before, during, and after clinical tasks, supporting adaptation, shared learning, and psychological safety. Table 6 includes subthemes, and illustrative participant quotes, from expert dyads showing reflective practice as a foundation for effective collaboration.

Although the data were compelling from a qualitative perspective, we were interested from a quantitative perspective to understand how often certain behaviours and attitudes were stated and if experience correlated with certain statements or opinions. We uploaded the interviews to ChatGPT 5.0 and asked how often certain attitudes and behaviours were stated and if years of experience correlated with certain statements or opinions. We found that certain opinions were repeatedly stated and Table 7 is a record of how many dyads (of the 10) strongly or meaningfully invoked each theme. These words were either mentioned explicitly or implicitly through sub-themes and played a central role in the conversations.

Exploring these themes, we found the concepts of trust, physical communication, situation awareness, connectedness and reflective practice were nearly universal. These elements were “core pillars” in our dyad sample. Learning and debrief practices were very common, though sometimes informal or partially done. Psychological safety was mentioned regularly, though not universally, as some dyads spoke more explicitly about “safety to speak up” more than others. Boundary norms and emotional regulation were also quite common but less universal than the core pillars.

To demonstrate any patterns between familiarity, (described by the number of procedures performed together and length of experience together), and collaborative behaviours and attitudes, we created Table 8.

We found that there was meaningful variation in how often themes were repeated across dyads. The “core pillars” of trust, physical communication, situation awareness, connectedness and reflective practice were universal in our sample and themes such as psychological safety and emotional regulation seemed to vary with familiarity, setting norms, and how intentionally the dyad invested in relational practices (debriefs, feedback, etc.).

We were also interested to understand, of the collaborative practices described, how the relational and cognitive underpinnings were expressed by the participants. Table 9 describes the practices and the relational and cognitive behaviours and attitudes with sample indicators.

These findings informed the development of what we have called the expert dyad framework (EDF) which captures the nuanced behavioral patterns and collaborative micro-practices that characterize high-performing clinical partnerships.

Salas et al.’s Big Five model posits that effective teamwork rests on five core dimensions that include team leadership, mutual performance monitoring, backup behavior, adaptability, and team orientation, supported by coordinating mechanisms such as shared mental models, closed-loop communication, and mutual trust [4]. Gittell’s Relational Coordination framework emphasizes that high performance teamwork is demonstrated when relational ties (shared goals, shared knowledge, mutual respect) underpin frequent, timely, problem-solving communication across interdependent roles [5]. The EDF differs from both by zeroing in below the level of team and relationships to focus on moment-to-moment dyadic interactional micro practices (e.g. how two people negotiate turn-taking, repair, signalling). Where Salas captures team-level capacities and Gittell captures relational/communication infrastructures, EDF seeks to show how these are microprocesses between pairs in practice. See the EDF, Figure 2.

Figure 2

This framework zeroes in on the micro-practices deployed by expert health professions dyads working in acute settings and the behaviours and attitudes that embody these practices. During interviews the dyads described their experiences and Table 10 gives real examples of these micro-practices from the interviews.

The expert dyad framework offers a framework that extends current models of teamwork education by focusing on the micro-level dynamics that often go unaddressed in larger team training. While elements such as communication and reflective practice are not new to health professions education, our work emphasizes how these elements function specifically within dyadic interactions, where the stakes, intimacy, and interdependence are uniquely amplified [31]. Rather than duplicating existing models, the expert dyad framework draws attention to how trust, familiarity, and mutual support are enacted in real time. These insights gained from dyadic interviews can inform how we teach, assess, and support relational competence.

Conflict is a behaviour that requires attention when discussing high performing practices in medical dyads. In conversations with the participants, we found that conflict was less often named than other terms such as disagreement or maintaining boundaries. Many dyads preferred to frame ‘disagreement’ as discussion or negotiation, rather than ‘conflict.’ In many interviews, participants spoke of avoiding public conflict, they always engaged in private resolution, and often used micro-debriefs to manage small frictions rather than explicit ‘conflict management.’ The fact that conflict is rarely foregrounded may itself reflect cultural norms (e.g. in medicine, conflict is often handled subtly). Because we did not have ‘conflict management’ as a dedicated code originally, some nuances might have been subsumed under communications and boundaries.