Interprofessional Supervision in Health Professions Education: Narrative Synthesis of Current Evidence

Chaoyan Dong; Elizabeth Wen Yu Lee; Clement C. Yan; Vaikunthan Rajaratnam

doi:10.3390/ime5010004

,

and

¹

Education Office, Sengkang General Hospital, Singapore 544886, Singapore

²

Department of Intensive Care, Sengkang General Hospital, Singapore 544886, Singapore

³

Department of Physiotherapy, Sengkang General Hospital, Singapore 544886, Singapore

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Health & Social Science Cluster, Singapore Institute of Technology, Singapore 828608, Singapore

Int. Med. Educ.2026, 5(1), 4;https://doi.org/10.3390/ime5010004
(registering DOI)

This article belongs to the Special Issue New Advancements in Medical Education

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Abstract

(1) Background: Interprofessional supervision is an emerging approach in health professions education that strengthens collaborative practice competencies while maintaining profession-specific expertise. Understanding current evidence regarding supervision models, outcomes, and implementation factors is crucial for advancing this field. (2) Methods: This narrative review analyzed 28 studies, including quantitative, qualitative, mixed-methods studies, and systematic reviews. Studies were analyzed for supervision models, outcome measures, evidence of effectiveness, and implementation factors. (3) Results: Six categories of interprofessional supervision models were identified: clinical practice-based, group supervision, competency-based training, skills training, case-based learning, and mentorship/coaching. Across models, interprofessional supervision consistently enhanced collaborative competencies, professional development, clinical skills, and organizational outcomes. Organizational support, structured curricula, interprofessional leadership, and individual readiness facilitated implementation success. Barriers included limited resources, professional silos, and challenges in curriculum integration. (4) Conclusions: Interprofessional supervision shows consistently positive outcomes across diverse models and settings, though more rigorous research designs and standardized outcome measures are needed. Successful implementation requires systematic attention to multiple factors at multiple levels, from organizational support to individual readiness. Interprofessional supervision is positioned for significant advancement through the application of implementation science frameworks and continued research on optimal model characteristics and implementation strategies.

Keywords:

interprofessional education; clinical supervision; health professions education; collaborative practice; implementation science

1. Introduction

The evolution of healthcare delivery toward increasingly complex, team-based care models has created an urgent need for health professionals to function effectively in interprofessional teams [1]. Consequently, this recognition has led to growing interest in interprofessional education (IPE) approaches that cultivate collaborative practice competencies while maintaining the integrity of profession-specific expertise [2]. Within health professions education, these efforts increasingly emphasize workplace-based learning approaches that prepare learners for collaborative practice in clinical settings.

Interprofessional supervision has emerged as one such educational approach that directly addresses this challenge by integrating supervision and mentorship activities across health professional boundaries, within clinical contexts, and with an educational intent. In this review, interprofessional supervision is situated within health professions education and practice-based training, focusing on students, residents, and early-career healthcare professionals in medicine, nursing, and allied health professions in the clinical setting. Included settings are clinical and practice-based environments in which supervision is embedded in routine clinical services. It involves supervisors and supervisees from different health professions working together to develop both profession-specific and interprofessional competencies [3]. This approach has been shown to mitigate professional isolation, enhance exposure to other professional perspectives, and prepare learners for collaborative practice.

The theoretical foundations of interprofessional supervision draw from interprofessional education theory, clinical supervision frameworks, and collaborative practice models. The World Health Organization’s Framework for Action on Interprofessional Education and Collaborative Practice provides a foundational understanding of the conditions necessary for effective interprofessional learning, emphasizing the importance of institutional support, curriculum design, and faculty development [1]. Clinical supervision theory, particularly Proctor’s three-function model encompassing managerial, educational, and supportive functions, provides a framework for understanding the mechanisms by which supervision fosters professional development [4]. Complementing these perspectives, collaborative practice models emphasize the importance of shared decision-making, mutual respect, and role clarity as essential components for effective interprofessional teamwork [5].

Despite growing interest in interprofessional supervision, the evidence base remains fragmented and diverse, with studies utilizing different models, outcome measures, and implementation approaches. This diversity reflects both the field’s evolving nature and the complexity of interprofessional competency development across professions and settings. Understanding the current state of evidence regarding interprofessional supervision models, their effectiveness, and the factors that influence successful implementation is essential to inform practice, strengthen future research design, and guide policy.

This narrative review aims to provide a comprehensive synthesis of current evidence on interprofessional supervision in health professions education. The synthesis was structured around three primary domains: (1) supervision models and their characteristics, (2) outcomes and evidence of effectiveness, and (3) implementation factors, including facilitators and barriers. These domains were selected to align with narrative synthesis principles and to reflect the key questions relevant to both educational theory and practice: what interprofessional supervision looks like, what it achieves, and what influences its successful implementation in real-world settings. Perceived advantages and disadvantages of interprofessional supervision were not treated as a separate domain but were included within the outcomes and implementation factors. This approach enabled a more integrated, practice-relevant synthesis of literature.

2. Methods

2.1. Search Strategy

Two researchers (C.D., V.R.) did the literature search to identify studies examining interprofessional clinical supervision in healthcare and health professions education. Searches were performed in the databases PubMed, Scopus, CINAHL, and PsycINFO. These databases were selected to capture literature across medicine, nursing, allied health, and psychology.

Search terms combined keywords related to clinical supervision, interprofessional or multidisciplinary practice, and health professions education. Core search terms included combinations of: clinical supervision, educational supervision, professional supervision, interprofessional, multidisciplinary, healthcare, health professions education, training, and workplace learning. Search strategies were adapted for each database. The search covered studies published from January 2000 to December 2024, reflecting contemporary models of interprofessional practice and supervision.

2.2. Study Selection

Study selection followed a staged process. After duplicates were removed, titles and abstracts were screened for relevance to interprofessional supervision in healthcare or health professions education. Full-text reviews were conducted for studies that appeared to meet the inclusion criteria or for which eligibility was unclear.

Studies were included if they:

(1): Examined clinical supervision, educational supervision, or structured supervisory practices involving two or more health professions;
(2): Were conducted within healthcare, clinical training, or health professions education settings;
(3): Reported empirical findings from quantitative, qualitative, or mixed-methods studies, or were systematic, scoping, or rapid reviews with an explicit focus on supervision; and
(4): Addressed supervision-related outcomes, processes, or implementation factors relevant to interprofessional practice, learning, or workforce development.

Studies were excluded if they:

(1): Focused solely on single-profession supervision without an interprofessional or cross-disciplinary component;
(2): Examined mentoring, coaching, or informal support activities without an explicit supervisory function;
(3): Were opinion pieces, editorials, commentaries, or conference abstracts without sufficient empirical detail; or
(4): Were conducted outside healthcare or health professions education contexts.

2.3. Data Extraction

Data from each included study were extracted using a structured template adapted from the narrative synthesis framework described by Popay et al. [6]. The template was designed to capture both descriptive and analytical information to support the synthesis’s iterative stages.

The professional groups represented in the studies included medicine (14 studies), social work (13 studies), occupational therapy (6 studies), physiotherapy (6 studies), nursing (5 studies), psychology (5 studies), and pharmacy (4 studies), reflecting the multidisciplinary nature of interprofessional supervision research. Study settings ranged from academic medical centers and universities to community and rural healthcare facilities, as well as specialized clinical services, providing insights into interprofessional supervision across diverse practice environments.

Two authors (C.D., E.W.Y.L.) independently extracted data from 14 studies each. Following initial extraction, the two authors (C.D., E.W.Y.L.) independently reviewed the 14 studies extracted by the other to ensure completeness, accuracy, and consistency of interpretation. Any discrepancies or uncertainties were resolved through discussion and consensus. For each study, we recorded bibliographic details, study aims, design, setting, participant characteristics, and characteristics of supervision or educational interventions. We also extracted information on outcomes measured, key quantitative and qualitative findings, and reported implementation factors or contextual influences relevant to interprofessional supervision in healthcare.

The complete extraction table was used as the foundation for developing narrative synthesis, exploring relationships within and across studies, and assessing the robustness of the synthesis. To enhance readability and accommodate journal layout constraints, a condensed summary of key study characteristics is presented in the main manuscript (Table 1), while the full data extraction table is provided as Supplementary Table S1 and made available in an external repository.

Table 1. Characteristics of included studies.

2.4. Synthesis and Assessment of Study Quality

Our synthesis was informed by Popay et al.’s four-stage approach [6] (Figure 1). We began by outlining a preliminary theoretical framework to consider how, why, and for whom interprofessional supervision interventions in healthcare might work, drawing on existing conceptual models and insights from the included studies. We then organized and tabulated data from the 28 studies to construct an initial synthesis, grouping findings by intervention type, professional group, setting, and reported outcomes. Subsequently, we examined relationships within and across studies to explore how contextual factors, target populations, and implementation strategies might shape the observed effects. This included comparing findings from qualitative and quantitative evidence, identifying potential moderators and mediators, and considering the influence of methodological quality. Finally, we assessed the robustness of the synthesis through critical reflection on the strength and consistency of the evidence, attention to potential biases, and the use of multiple reviewers to check data interpretation. This iterative process allowed us to integrate diverse forms of evidence into a coherent account of the current state of knowledge on interprofessional supervision.

Figure 1. Popay et al.’s [6] four-stage approach.

Quality appraisal was conducted using a customized tool adapted from established critical appraisal frameworks, including the EPPI-Centre Weight of Evidence framework [35], the Critical Appraisal Skills Programme (CASP) checklists, and the Joanna Briggs Institute (JBI) Critical Appraisal Tools. The following criteria were assessed: relevance to the review question, methodological quality, clarity of reporting, risk of bias, and justification. Consistent with narrative synthesis approaches, quality appraisal was done to support transparent interpretation of the evidence rather than to exclude studies. Quality ratings were used during data extraction and synthesis to contextualize findings and guide the interpretation of results. Table 2 summarizes the quality of each reviewed study.

Table 2. Quality Appraisal of Studies.

3. Results

3.1. Interprofessional Supervision Models

As summarized in Table 3, the reviewed studies revealed considerable heterogeneity in interprofessional supervision models, reflecting differences in context, professional mix, and intended outcomes. Clinical practice-based models offered the most immersive integration of supervision with patient care, embedding supervision within clinical encounters such as interprofessional pain clinics or primary care settings [9,25]. These models enabled real-time application of profession-specific and interprofessional competencies; however, they typically required sustained faculty involvement, protected time, and coordination across professions, which may limit scalability in resource-constrained settings.

Table 3. Summary of interprofessional supervision models.

Group supervision models leveraged peer learning and facilitated interprofessional reflection around shared cases, ethical challenges, or professional experiences [8,13]. Participants commonly reported enhanced role understanding and reflective capacity, although evidence of sustained practice or knowledge change was less consistent and relied largely on self-reported outcomes.

Competency-based and skills-focused training models provide structured, measurable gains in targeted domains [10,11,31,34]; however, their narrower scope may overlook broader relational and identity-forming dimensions of interprofessional work. Case-based learning approaches similarly demonstrated promise for fostering deep engagement with complex scenarios through structured, sequential discussions. Still, outcome measures primarily captured self-reported learning rather than objective changes in practice [16].

Mentorship and coaching models showed potential for supporting long-term professional development and interdisciplinary collaboration, particularly within longitudinal or workforce development programs. However, the supporting evidence was predominantly qualitative and context-specific, relying heavily on participant narratives and experiential accounts, which limited generalizability [26,32].

Across models, positive trends in teamwork, role clarity, and clinical knowledge were reported in the majority of included studies (approximately two-thirds), particularly in clinical practice-based and group supervision models. These outcomes were commonly assessed using short-term, self-reported measures, and the overall evidence base was stronger for interprofessional competency development than for patient-level or organizational outcomes.

3.2. Organizational and System-Level Impacts

Organizational and system-level outcomes were reported in a smaller subset of studies, most commonly regarding staff satisfaction, retention, and interprofessional collaboration. They were typically measured indirectly through participant-reported outcomes rather than objective organizational indicators. Ducat & Kumar [12] reported that supervision reduced burnout and improved job satisfaction and retention, with rural practitioners reporting particular benefit. Gardner et al. [14] showed sustained effectiveness over five years following the implementation of an organizational supervision framework, with supervisor choice, seniority, and session frequency enhancing outcomes, contributing to stable Manchester Clinical Supervision Scale (MCSS-26) scores. Tatla et al. [32] demonstrated that collaborative coaching improved team cohesion and communication, though quantitative outcomes were less evident. Overall, organizational impacts were more robustly supported by moderate-quality longitudinal or mixed-methods studies than by short-term evaluations.

3.3. Patient Outcomes and Quality of Care

Evidence linking supervision to patient outcomes was limited but promising; however, this evidence was derived primarily from systematic and rapid reviews and a small number of moderate-quality primary studies, with few high-quality controlled designs directly measuring patient-level outcomes.

A review by Snowdon et al. [29] found improvements in processes of care in 12 of 14 studies, some gains in health outcomes in 3 of 6 studies, and positive patient experiences in 3 of 3 studies. Notably, most patient-related outcomes were indirect, focusing on care processes, communication, or patient satisfaction rather than clinical endpoints.

Cao & Hull [9] reported high satisfaction with team-based pain management delivered through a supervised interprofessional clinic, although specific health outcomes were not measured. The integration of interprofessional supervision with direct patient care appeared to create positive experiences for both learners and patients [11,29]. Across the reviewed literature, direct links between interprofessional supervision and patient-level clinical outcomes were infrequently examined and were primarily derived from reviews or moderate-quality primary studies.

3.4. Measurement Approaches

The studies included used diverse methods to assess interprofessional supervision outcomes. Common validated tools included the Interprofessional Education Perception Scale (IEPS) [9,16], the Interprofessional Collaborative Competency Attainment Survey (ICCAS) [25], and the Manchester Clinical Supervision Scale (MCSS-26) [14]. These instruments were used in approximately half of the included studies and primarily captured self-reported perceptions of learning, collaboration, or supervisory effectiveness.

Qualitative approaches, such as interviews and focus groups, offered rich insights into participants’ experiences, contextual influences, and perceived mechanisms of change [8,13]. Mixed-methods designs, such as the BU CHAMPs study [25], integrated survey data with qualitative findings related to patient-centered care, team dynamics, and role clarity. While qualitative and mixed-methods studies offered depth and contextual understanding, they also contributed to variability in outcome reporting and limited comparability across studies.

3.5. Implementation Factors

3.5.1. Organizational and System-Level Facilitators

Leadership support and organizational alignment were critical to success [11,19]. Dolansky et al. [11] showed that projects aligned with institutional priorities achieved the strongest outcomes. Goode et al. [15] highlighted the need for senior buy-in, protected time, and ongoing training; without these, programs struggled to secure resources and achieve intended outcomes. Organizational culture also shaped outcomes: Bullington et al. [8] observed that supportive environments or cultures fostered collaboration and psychological safety. Adequate resources and protected time were essential for sustained implementation [17].

3.5.2. Educational and Curricular Facilitators

Structured curricula promoted engagement and measurable outcomes. Gooding et al. [16] demonstrated that sequential case-based sessions improved confidence and role clarity. Faculty development was equally vital: Harvey et al. [17] reported substantial gains in supervisory knowledge, skills, and confidence following structured supervisor training. Embedding supervision in authentic clinical practice, as in the SSIPPC study [9], enhanced both competency development and patient satisfaction.

3.5.3. Professional and Interprofessional Facilitators

Interprofessional champions and leaders drove program success by modeling collaboration across professions [11]. Supervision also reinforced professional identity while promoting teamwork [8]. Peer support networks were particularly valuable in rural and resource-limited settings, where access to profession-specific supervision was more constrained [13].

3.5.4. Barriers to Implementation

Significant barriers included a lack of protected time and competing priorities [15], unsupportive organizational cultures resistant to new supervisory frameworks [8], and entrenched silos or professional hierarchies that hindered collaboration [8]. Faculty inexperience also posed challenges; Harvey et al. [17] emphasized the need for structured training to prepare supervisors for interprofessional roles. These barriers were most frequently reported in lower- and moderate-quality studies, underscoring the influence of contextual constraints on implementation outcomes.

4. Discussion

4.1. Synthesis of Evidence

The narrative synthesis reveals a promising but evolving evidence base for interprofessional supervision in health professions education. The consistency of positive outcomes across diverse models, settings, and populations suggests that interprofessional supervision interventions can produce meaningful improvements in interprofessional competencies, professional development, clinical knowledge and skills, and organizational outcomes. This consistency is particularly noteworthy given the diversity of approaches, measurement methods, and contexts represented in the studies [8,9,11,13,25].

The evidence suggests that multiple approaches to interprofessional supervision can be effective, ranging from intensive, clinical practice-based models to group supervision approaches and competency-based training programs [8,12,16]. This diversity indicates that the field has moved beyond a one-size-fits-all approach to recognize that different contexts, populations, and objectives may require different supervision models. The effectiveness of diverse approaches also suggests that the core principles of interprofessional supervision, such as collaborative learning, mutual respect, and shared reflection, can be operationalized through various mechanisms [11,12,32].

The strength of evidence varies considerably across outcome domains, with the most substantial evidence for interprofessional competencies and professional development outcomes, moderate evidence for clinical knowledge and skills outcomes, and limited evidence for patient outcomes and long-term sustainability [12,29]. This pattern reflects both the relative ease of measuring individual-level outcomes compared to system-level impacts and the field’s early stage of development.

4.2. Theoretical Implications

The evidence from this review has important implications for the theoretical understanding of interprofessional supervision. The consistent positive outcomes across diverse models suggest that interprofessional supervision operates through multiple mechanisms that may be more important than specific model characteristics. These mechanisms appear to include increased exposure to other professional perspectives, opportunities for collaborative problem-solving, peer support and mutual learning, and the integration of profession-specific and interprofessional competencies [8,32].

Importantly, the finding that interprofessional supervision can strengthen rather than threaten professional identity has important theoretical implications for understanding the relationship between profession-specific and interprofessional competencies. The evidence suggests that well-designed interprofessional supervision programs can enhance both domains simultaneously, challenging traditional assumptions about potential conflicts between professional and interprofessional identity development [8,19].

The importance of contextual factors in determining implementation success has implications for the theoretical understanding of interprofessional supervision as a complex intervention that must be adapted to local circumstances. The evidence suggests that successful implementation requires attention to multiple levels of factors, from organizational culture to individual readiness, and that these factors interact in complex ways to influence program outcomes [11,19].

4.3. Methodological Considerations

The diversity of measurement methods across studies reflects both the complex nature of interprofessional competencies and the challenges inherent in evaluating multifaceted educational interventions. While this diversity provides rich insights into different dimensions of interprofessional supervision effectiveness, it also complicates cross-study comparisons and limits the potential for evidence synthesis.

Many studies employed pre–post or cross-sectional designs without control groups, which limits causal inference [9,11,32]. Sample sizes were generally small, and few studies incorporated longitudinal follow-up. Measures of supervision effectiveness were often self-reported, introducing subjectivity and recall bias [12,25,29]. Although the consistent positive outcomes across diverse studies offer some confidence in the findings, greater methodological rigor is needed. Future research should prioritize mixed-methods and longitudinal designs to better capture developmental and behavioral changes over time [11,15,29].

The predominance of short-term follow-up periods in most studies limits understanding of the sustainability and long-term impact of interprofessional supervision interventions. The few studies that evaluated longer-term outcomes, such as the organizational framework study by Gardner et al. [14], provide valuable insights into sustainability but represent only a small proportion of the available evidence.

4.4. Practical Implications

The evidence has important practical implications for educators, administrators, and policymakers seeking to implement interprofessional supervision programs. The diversity of effective approaches suggests that organizations have flexibility in choosing supervision models that align with their contexts, resources, and objectives [11,19]. However, the evidence also suggests that certain core elements, such as organizational support, structured curriculum design, and faculty development, are important regardless of the chosen model.

The importance of implementation factors suggests that successful interprofessional supervision requires more than simply adopting a proven model. Organizations must carefully assess their readiness for implementation, address potential barriers, and develop comprehensive implementation strategies that attend to multiple levels of factors simultaneously [11,19].

The evidence for positive organizational outcomes, including improved job satisfaction and team dynamics, suggests that interprofessional supervision can provide value beyond individual professional development [12,14]. This broader value proposition may be important for securing organizational support and resources for supervision programs.

4.5. Limitations and Future Directions

The evidence base is limited by short follow-up, scarce use of control groups, and varied outcome measures, factors which weaken causal claims and comparability. Evidence linking supervision to patient outcomes is still sparse, despite its centrality to interprofessional care.

Future research should adopt rigorous designs, standardized outcome sets, and extended follow-up to examine sustainability and contextual influences. Integrating implementation-science frameworks can clarify how organizational culture, leadership, and professional hierarchies shape success. Continued research should also investigate cost-effectiveness and scalability, ensuring that interprofessional supervision becomes an embedded component of workforce and educational policy.

5. Conclusions

Interprofessional supervision shows clear potential to support collaborative practice by strengthening interprofessional competencies and professional development across diverse settings. The current evidence base, however, remains uneven, with comparatively limited and methodologically weaker evidence for patient-level outcomes and long-term sustainability.

Future research should prioritize rigorous and longitudinal study designs, adopt more standardized outcome measures, and apply implementation science frameworks to understand better how interprofessional supervision can be effectively embedded and sustained within healthcare systems. With appropriate institutional support and robust evaluation, interprofessional supervision can become a scalable, integral component of health professions education.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ime5010004/s1, Table S1: Overview of Included Studies and Key Characteristics.

Author Contributions

Conceptualization, V.R. and C.D.; methodology, V.R., C.D. and E.W.Y.L.; data extraction, C.D. and E.W.Y.L.; data validation, V.R., C.D., E.W.Y.L. and C.C.Y.; writing—original draft preparation, V.R. and C.D.; writing—review and editing, C.D., E.W.Y.L. and C.C.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Acknowledgments

We acknowledge the use of OpenAI’s ChatGPT-5.2 for assistance in language refinement and preliminary thematic analysis of qualitative data. All intellectual contributions, interpretations, and conclusions remain our own.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:

DTT	Discrete Trial Teaching
IPE	Interprofessional Education
IPES	Interprofessional Education Perception Scale
JBI	Joanna Briggs Institute
QI	Quality Improvement

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Figure 1. Popay et al.’s [6] four-stage approach.

Table 1. Characteristics of included studies.

Study (Author, Year)	Country	Study Design	Participants	Supervision/Educational Model	Format & Duration	Primary Competency Focus
Alfonsson et al., 2020 [7]	Sweden	Quantitative (single-case experimental)	6 CBT therapists	CTS-R–guided clinical supervision	Weekly individual sessions; 5–8 weeks	CBT competence, reflective practice
Bullington & Cronqvist, 2018 [8]	Sweden	Qualitative intervention pilot	6 primary care professionals	Phenomenological supervision model	Monthly group supervision; 6 months	Clinical reasoning, reflective practice
Cao & Hull, 2021 [9]	Australia	Quasi-experimental (pre–post)	6 interprofessional students	Supervised interprofessional pain clinic	Weekly team-based clinical sessions; 12 weeks	Interprofessional teamwork, pain management
Cruz et al., 2023 [10]	USA	Experimental (multiple baseline)	3 BCBAs and supervisees	Performance-based supervision training	Individual coaching to mastery	Supervisory skills, feedback delivery
Dolansky et al., 2024 [11]	USA	Quasi-experimental (pre–post)	74 postgraduate trainees	Longitudinal interprofessional QI curriculum	Weekly didactics + clinical projects; variable by profession	Quality improvement, systems thinking
Ducat & Kumar, 2015 [12]	Australia	Systematic review	Allied health practitioners	Professional supervision (varied models)	Individual/group; mixed modalities	Professional support, job satisfaction
Gardner et al., 2021 [13]	Australia	Mixed methods	16 allied health staff	Group clinical supervision (critical reflection)	Monthly/bimonthly group sessions	Reflective practice, peer learning
Gardner et al., 2022 [14]	Australia	Cross-sectional study	125 allied health staff	Organizational supervision framework	Mostly individual supervision; ongoing	Formative, normative, restorative supervision outcomes
Goode et al., 2024 [15]	UK	Quantitative observational	30 primary care staff	Core Clinical Supervision (NHS framework)	Mixed 1:1 and group; 18 months	Professional confidence, wellbeing
Gooding et al., 2016 [16]	USA	Mixed methods	7 postgraduate trainees	Case-based interprofessional curriculum	Weekly sessions; 6 months	Collaboration, adolescent healthcare
Harvey et al., 2020 [17]	Australia	Mixed methods	226 supervisors	Role Development Model training	8 days over 6–9 months	Supervisory competence, reflective capacity
Haynes et al., 2019 [18]	USA	Quasi-experimental	144 residents	Practice feedback curriculum	Longitudinal; 1 year	Practice-based learning, self-assessment
Jones et al., 2022 [19]	USA	Mixed methods	34 pediatric residents	Simulated patient–based curriculum	Workshops + simulations	Interprofessional communication
Martin, 2018 [20]	Australia	Mixed methods	Health professionals (unspecified)	Clinical supervision in rural settings	Flexible, context-driven	Supervision quality, workforce support
Martin et al., 2020 [21]	Australia	Review protocol	Qualified health professionals	One-to-one clinical supervision	Not applicable	Organizational outcomes
Martin et al., 2022 [22]	Australia	Rapid review	Healthcare workers and students	Adapted supervision during COVID-19	Virtual/in-person/hybrid	Continuity of supervision
McCarron et al., 2017 [23]	UK	Mixed methods	Nurses and HCAs	Organizational supervision interventions	Group and multidisciplinary supervision	Staff support, service improvement
McGuinness & Guerin, 2024 [24]	Ireland	Scoping review	Allied health professionals	Interprofessional supervision	Not applicable	Interprofessional supervision practices
Miselis et al., 2022 [25]	USA	Mixed methods	35 trainees	Longitudinal interprofessional clinic	Weekly 4-h clinic	Team-based care competencies
O’Mahony et al., 2020 [26]	USA	Mixed methods	26 clinicians	Interdisciplinary mentoring program	Hybrid; 2 years	Palliative care competencies
Riveros Perez et al., 2019 [27]	USA	Quasi-experimental	37 residents	Supervision skills training	Lecture + simulation; single session	Supervisory competence
Rothwell et al., 2021 [28]	UK	Rapid evidence review	Mixed professions	Proctor’s supervision model	Individual/group; ongoing	Professional development, wellbeing
Snowdon et al., 2017 [29]	Australia	Systematic review	Healthcare professionals	Clinical supervision (varied models)	Individual/group	Clinical effectiveness, patient outcomes
Starks et al., 2017 [30]	USA	Mixed methods	24 clinicians	Interprofessional palliative curriculum	9 months; blended learning	Communication, team practice
Suddarth et al., 2016 [31]	USA	Quasi-experimental	274 faculty	Milestones-based supervision tool	Workplace-based; ongoing	Assessment and feedback skills
Tatla et al., 2017 [32]	Canada	Mixed methods	36 providers	Collaborative coaching intervention	6 months	Coaching- and family-centered care
Wingo et al., 2024 [33]	USA	Mixed methods	172 team members	TeamSTEPPS-based curriculum	Longitudinal outpatient blocks	Team development, patient safety
Winn et al., 2018 [34]	USA	Mixed methods	48 interns	Intensive clinical orientation	3.5-day program	Clinical preparedness

Table 2. Quality Appraisal of Studies.

	Study Identification		Quality Appraisal
No.	Study Identification	Title	Relevance to Review Question	Methodological Quality	Clarity of Reporting	Risk of Bias	Justification
1	Alfonsson et al., 2020 [7]	Clinical supervision in cognitive behavior therapy improves therapists’ competence: A single-case experimental pilot study	High: demonstrates how structured supervision enhances specific therapeutic skills and therapist development, facilitating collaboration through competency growth	High clarity, appropriate methods for pilot single-case design; clear description of supervision protocol	High clarity, appropriate methods for pilot single-case design; clear description of supervision protocol	Low-moderate; randomization of baselines, blinded raters; small sample size limits generalizability	Clear rationale for standardization and focus on CTS-R competencies; aligns with gaps in supervision research
2	Bullington & Cronqvist, 2018 [8]	Group supervision for healthcare professionals within primary care for patients with psychosomatic health problems: A pilot intervention study	High: shows how clinical supervision supports interprofessional reflection, emotional processing, and shared care thinking, even when it does not lead to standardized strategies	Moderate to high: clear intervention description and analytic method, though small sample and no discipline-specific breakdown weakens generalizability	Moderate to high: clear intervention description and analytic method, though small sample and no discipline-specific breakdown weakens generalizability	Moderate: small, self-selecting sample; lack of diversity data; unclear fidelity to theoretical model; no triangulation of perspectives (e.g., patients, supervisors)	Well-grounded in challenges of treating psychosomatic cases in primary care; supervision is underutilized and this intervention fills a gap in reflective, low-cost interprofessional development
3	Cao & Hull, 2021 [9]	Effectiveness of Educating Health Care Professionals in Managing Chronic Pain Patients Through a Supervised Student Inter-professional Pain Clinic	Very high: demonstrates that supervised, structured IPE fosters team-based learning, improves communication and collaborative attitudes, and enhances student readiness for future interprofessional practice.	High: clear intervention design, validated tools, appropriate statistical tests (Wilcoxon, Kruskal–Wallis, RM ANOVA). Well-explained participant demographics and outcomes.	High: clear intervention design, validated tools, appropriate statistical tests (Wilcoxon, Kruskal–Wallis, RM ANOVA). Well-explained participant demographics and outcomes.	Moderate: No control group; possible selection bias (voluntary participation); limited generalizability beyond chronic pain and U.S. context	Strongly justified: addresses a known gap in pain education and interprofessional training. The real-world clinical setting adds relevance and feasibility.
4	Cruz et al., 2023 [10]	Teaching Supervisory Skills to Behavior Analysts and Improving Therapist-Delivered Discrete Trial Teaching	Moderate: focuses on supervision skill-building within one discipline. While not interprofessional, it strongly supports structured supervision to enhance team performance and skill transmission. Could inform supervision models in multi-disciplinary contexts.	High: clear design (multiple baseline), strong operational definitions, replication across participants, fidelity monitoring	High: clear design (multiple baseline), strong operational definitions, replication across participants, fidelity monitoring	Low to moderate: small sample size, no control group; participants from one setting; strong internal validity	Well-justified given supervision is core to ABA practice. Builds on evidence-based methods for training and feedback delivery.
5	Dolansky et al., 2024 [11]	An interprofessional postgraduate quality improvement curriculum: results and lessons learned over a 5-year implementation	This study demonstrates how a longitudinal, coached, interprofessional QI curriculum can enhance teamwork, practical learning, and collaborative care delivery. Coaches, experiential learning, and alignment with institutional goals were key to success—providing a model for supervisory practices that foster interprofessional competence and cooperation.	Moderate: appropriate for real-world educational settings (quasi-experimental), but lacks control group and formal measurement of interprofessional collaboration.	High: the article follows SQUIRE-EDU guidelines, provides detailed descriptions of curriculum, participants, outcomes, and lessons learned.	High: well-supported by existing literature and professional competency frameworks. Clear rationale for targeting interprofessional QI training.	High: well-supported by existing literature and professional competency frameworks. Clear rationale for targeting interprofessional QI training.
6	Ducat & Kumar, 2015 [12]	A systematic review of professional supervision experiences and effects for allied health practitioners working in non-metropolitan health care settings	Relevant: identifies supervision as a mechanism to support allied health professionals in collaborative, resource-limited contexts; highlights challenges in defining and structuring supervision to optimize collaboration	Moderate to Low: included studies were methodologically weak (small samples, lack of validated measures, inconsistent definitions)	High: clearly reported aims, methods, and narrative synthesis.	Moderate: limited number of included studies (n = 5), self-reported data, variable supervision models, lack of robust outcome measures or control groups	High: authors provide a clear rationale for focusing on rural allied health, citing gaps in previous reviews and workforce challenges
7	Gardner et al., 2021 [13]	Group clinical supervision for allied health professionals	High: demonstrates how structured group supervision with trained facilitators fosters peer learning and interprofessional collaboration in rural settings; supports supervision as a catalyst for team-based support.	Moderate: small sample, no control group, some bias risk acknowledged	High: well-described methods, tools, outcomes.	Moderate: small group sizes, self-reporting, 42% non-response; lead author was a facilitator in one group	High: clearly grounded in known rural supervision barriers; aligned with workforce development goals
8	Gardner et al., 2022 [14]	Effectiveness of allied health clinical supervision following the implementation of an organisational framework	High: demonstrates how organizational supervision frameworks, when implemented with interprofessional training and clear structure, can improve clinical supervision and contribute to team dynamics and collaboration	Moderate: strong design (action research), but limited by lack of true pre-post or control group	High: transparent reporting, well-documented tables, clear rationale	Moderate: self-reported data, 50% response rate, some professions under-represented; lead author involvement may introduce bias	High: clearly justified with literature and policy gaps; builds on prior internal survey and aligns with rural health workforce needs
9	Goode et al., 2024 [15]	An evaluation of a quality improvement initiative examining benefits and enablers and challenges and barriers of implementing and embedding core clinical supervision in primary care	High: demonstrates how structured, reflective clinical supervision models can enhance collaboration, professional growth, and team function in multidisciplinary primary care settings	Moderate: survey-based with low response rate and no pre-post comparison	High: well-described aims, methods, and visuals	Moderate: self-selection bias; survey conducted by trainer; limited participant diversity; small sample size (n = 30)	High: clearly linked to NHS LEAP strategy and national policy on supervision and staff wellbeing; addresses known gaps in primary care supervision literature
10	Gooding et al., 2016 [16]	Case-based teaching for interprofessional postgraduate trainees in adolescent health	High: demonstrates how structured supervision (via interprofessional faculty-led case-based sessions) fosters interprofessional collaboration and role clarity	High: clear structure, validated tools, strong mixed methods design	High: clear structure, validated tools, strong mixed methods design	Moderate: small sample, single-site, self-selection bias, high baseline scores may limit measurable gains	Methods and tools are well-justified and aligned with study objectives; limitations transparently discussed (e.g., ceiling effects, context specificity)
11	Harvey et al., 2019 [17]	Describing and evaluating a foundational education/training program preparing nurses, midwives and other helping professionals as supervisors of clinical supervision using the Role Development Model	High: the program equips professionals across disciplines with reflective supervisory skills, building confidence and interprofessional insight, though direct IPC outcomes were not assessed.	High: clear methodology, detailed theoretical foundation, and rich qualitative data	High: clear methodology, detailed theoretical foundation, and rich qualitative data	Moderate: no control group, potential self-report bias, non-standardized tools	Strong—grounded in established theories and supervisory practice literature; addresses a clear training gap
12	Haynes et al., 2019 [18]	Continuity clinic practice feedback curriculum for residents: A model for ambulatory education	Moderate: while focused on supervision of data feedback, the curriculum includes coaching, peer comparison, and teamwork, contributing to collaborative and reflective practice. However, interprofessional collaboration is not a direct focus.	High: comprehensive methods, detailed reporting of activities and outcomes	High: comprehensive methods, detailed reporting of activities and outcomes	Moderate: no control group; single-site study; surveys lacked validity evidence; low post-survey response rate	Curriculum grounded in PBLI and QI theory; EHR-linked data relevant and actionable; strong alignment with ACGME competencies
13	Jones et al., 2022 [19]	Integrated behavioral health education using simulated patients for pediatric residents engaged in a primary care community of practice	High: demonstrates clinical supervision in interprofessional learning leading to collaborative practice.	High: well-reported mixed-methods with thematic saturation and appropriate analysis.	High: well-reported mixed-methods with thematic saturation and appropriate analysis.	Moderate: no control group; self-reported outcomes	Appropriate justification of method and framework; supported by literature and qualitative rigor
14	Martin, 2018 [20]	Clinical supervision in the bush: Is it any different?	Moderate: although the study does not directly evaluate interprofessional collaboration, it highlights supervision characteristics and barriers relevant to implementing interprofessional models in rural settings.	Moderate: the abstract is clearly written with a basic description of methods and findings, but limited by the brevity of the conference format.	Moderate: Tthe abstract is clearly written with a basic description of methods and findings, but limited by the brevity of the conference format.	Moderate: lack of detailed participant data, sample size, and methodology limits robustness.	Yes: justified by the need for professional support and retention in rural/remote healthcare, where supervision resources are often lacking.
15	Martin et al., 2020 [21]	Impact of clinical supervision of health professionals on organizational outcomes: A mixed methods systematic review protocol	Moderate: while the review focuses on organizational outcomes rather than interprofessional collaboration per se, it provides important insights into how supervision infrastructure and support may indirectly enhance collaborative climates and workforce sustainability.	High: protocol is structured according to JBI methodology, includes clear inclusion criteria, defined outcomes, and robust mixed methods synthesis procedures.	High: protocol is structured according to JBI methodology, includes clear inclusion criteria, defined outcomes, and robust mixed methods synthesis procedures.	Low: strong protocol design; any risk will depend on the methodological quality of included studies.	Yes: CS is underutilized yet potentially impactful in healthcare organizations. The review addresses a critical knowledge gap related to systemic and workforce-level outcomes.
16	Martin et al., 2022 [22]	A rapid review of the impact of COVID-19 on clinical supervision practices of healthcare workers and students in healthcare settings	High: synthesizes evidence on clinical supervision disruptions during COVID-19	Most studies cross-sectional; some with methodological flaws; all included for synthesis	Generally clear; includes tables and thematic synthesis	Moderate: self-report data, limited psychometric testing, supervisee-only perspectives	First rapid review examining COVID-19’s impact on supervision; timely and needed for policy response
17	McCarron et al., 2017 [23]	The experience of clinical supervision for nurses and healthcare assistants in a secure adolescent service: Affecting service improvement	Directly relevant: examines supervision implementation, experience, and improvement strategies in mental health	Service evaluation; no validated questionnaire; rigorous coding with some limitations (e.g., different coders)	Detailed reporting of procedures, findings, and statistical analysis	Moderate: low response rate, lack of validation, insider researchers, no respondent validation	Provides empirical evidence of how organizational interventions affect supervision outcomes, including for HCAs
18	McGuinness & Guerin, 2024 [24]	Interprofessional supervision among allied health professionals: A systematic scoping review		Strong methodological framework (JBI), comprehensive search strategy, and clear inclusion/exclusion criteria; limitations due to study heterogeneity Moderate—study quality varied; majority descriptive or exploratory; no quality appraisal conducted as per scoping review convention	Clear and transparent reporting of methods, charting, and findings using PRISMA-ScR		Addresses a literature gap by systematically mapping existing knowledge, definitions, outcomes, and implementation barriers of interprofessional supervision
19	Miselis et al., 2022 [25]	Interprofessional education in the clinical learning environment: A mixed-methods evaluation of a longitudinal experience in the primary care setting	High: demonstrates implementation and impact of structured supervision within interprofessional, practice-based learning	Strong design with validated instruments and mixed methods; self-selection bias and limited validation of RIPC acknowledged	Excellent: clear description of intervention, participants, instruments, and findings	Moderate: volunteer bias, small sample size for subgroups, unvalidated instrument (RIPC)	Demonstrates successful implementation and evaluation of interprofessional clinical supervision and training in real-world settings
20	O’Mahony bet al., 2020 [26]	Expanding the interdisciplinary palliative medicine workforce: a longitudinal education and mentoring program for practicing clinicians	High: describes a comprehensive interdisciplinary training and supervision model with practical implementation outcomes	Non-validated survey instruments; robust qualitative data; structured and detailed reporting	Very clear description of intervention, participant demographics, curriculum, and evaluation results	Moderate: self-reported data, small sample, lack of control group	Demonstrates structured, scalable interdisciplinary supervision and training with measurable outcomes and actionable insights
21	Riveros Perez et al., 2019 [27]	Evaluation of anesthesiology residents’ supervision skills: A tool to assess transition towards independent practice	Directly relevant: examines supervision training for residents transitioning to supervisory roles	Validated tools used (De Oliveira Filho supervision scale); single-site, small sample, no control group	Detailed tables and explanation of intervention, metrics, and statistical analysis	Moderate: no randomization or control group; self-reported outcomes	Addresses an important training gap in supervision skills; offers replicable intervention model
22	Rothwell et al., 2021 [28]	Enablers and barriers to effective clinical supervision in the workplace: A rapid evidence review	High: focused on supervision delivery method and contextual enablers/barriers in healthcare settings	Transparent methods, but lacks formal critical appraisal due to rapid review format. Search strategy and inclusion criteria well defined.	Clear and structured presentation of both quantitative and qualitative findings	Clear and structured presentation using narrative synthesis; themes well described.	Synthesizes cross-disciplinary evidence on supervision in real-world healthcare systems. Practical implications for supervision training and organizational implementation. “Papers were limited to Western only and the last 10 years for pragmatic reasons… a rapid review necessarily pays less attention to study design and sample sizes.”
23	Snowdon et al., 2017 [29]	Does clinical supervision of healthcare professionals improve effectiveness of care and patient experience? A systematic review	High: systematic synthesis of supervision outcomes across care dimensions	Assessed using MERSQI; mean score = 13.1; 16/17 studies scored ≥ 11	Very clear structure following PRISMA; comprehensive data tables and methods	Moderate: many non-randomized studies and reliance on documentation	Non-randomized designs (14/17 studies); reliance on medical records; heterogeneity precluded meta-analysis
24	Starks et al., 2017 [30]	Pilot study of an interprofessional palliative care curriculum: Course content and participant-reported learning gains	High: examines interprofessional supervision, skill development, and application in real clinical settings	Well-structured; limited by reliance on self-reported outcomes; use of then-test improved retrospective baseline calibration	Very clear presentation of curriculum, methods, domains, and detailed skill-level changes	Moderate: no control group, all outcomes self-reported	Demonstrates impact of structured, longitudinal interprofessional training with replicable pedagogy
25	Suddarth et al., 2016 [31]	Implementation of milestones-based assessment for a safe and effective discharge	High: demonstrates structured supervision intervention and assessment across institutions	Moderate: faculty perceptions only; no patient or resident input; variable implementation across sites	Clear methods, tables, and defined outcomes; limited generalizability	Moderate: self-report data, limited scope of participants (faculty only)	Demonstrates scalable collaborative approach to improving supervision and assessment of discharge competence
26	Tatla et al., 2017 [32]	Implementing a collaborative coaching intervention for professionals providing care to children and their families: An exploratory study	High: focuses on interprofessional coaching and supervision for healthcare professionals in real-world settings	Moderate: participatory design with mixed methods; limited by self-report and lack of control group	Well-detailed intervention, clear results presentation, appropriate thematic analysis	Moderate: no control group, self-report bias, limited psychometric validation of coaching tool	Demonstrates promising interprofessional coaching model; suggests importance of team dynamics and organizational support
27	Wingo et al., 2024 [33]	Enhancing team development in an internal medicine resident continuity clinic	High: demonstrates impact of structured team-based supervision and education in real-world resident clinic setting	Robust design using validated tools (TDM, SAQ), though limited by some contamination and short intervention period	Very clear reporting of design, intervention, analysis, and limitations	Moderate: contamination risk, short duration, lack of patient-level change	First study evaluating ambulatory TeamSTEPPS in IM residency block schedule; relevant for educational innovation and supervision strategy
28	Winn et al., 2018 [34]	Development, implementation, and assessment of the Intensive Clinical Orientation for Residents (ICOR) curriculum: A pilot intervention to improve intern clinical preparedness	High: structured clinical supervision and orientation program directly linked to EPA performance and supervision quality	Moderate: small sample, subjective outcome measures, short-term evaluation, but well-structured and piloted intervention	Clear presentation of objectives, methods, and evaluation; well-aligned with adult learning theory	Moderate: no objective competency assessment, potential self-selection bias, unblinded evaluators	Provides a replicable and novel approach to hands-on, EPA-based intern orientation in real clinical settings

Table 3. Summary of interprofessional supervision models.

Model Type	Study/Example	Description	Key Outcomes
Clinical Practice-Based Supervision Models	SSIPPC—Cao & Hull [9]	12-week program at Mercy Pain Center with students from 6 professions; weekly clinics, didactics, communication & leadership training, role clarification, and supervised patient care.	↑ Team skills; ↑ pain knowledge (RNPQ, KnowPain50); positive IPE attitudes; high patient satisfaction; PT students showed largest improvement; qualitative: valued side-by-side learning, expected future collaboration.
	BU CHAMPs Clinic—Miselis et al. [25]	Weekly 4 h longitudinal sessions: didactics, huddles, patient care, debriefing, documentation; full continuum of interprofessional practice.	↑ Interprofessional competencies (ICCAS); ↑ socialization & valuing (ISVS-21); ↑ role clarity; qualitative: patient-centered care, stronger team dynamics, safe learning environments; med students benefited most.
Group Supervision Models	Phenomenological group model—Bullington & Cronqvist [8]	6 professionals in Swedish primary care; monthly 75 min sessions × 6 months; lectures, case reflection, phenomenological application.	↑ Understanding of psychosomatics; ↑ role identity, collaboration, confidence; ↓ isolation; relational gains > theoretical retention.
	Critical reflection group—Gardner et al. [13]	Allied health professionals in Australia; Proctor & Inskipp typologies; 1–1.5 h monthly/bimonthly sessions with reflection and solution-focused facilitation.	67% reported positive experiences; themes: safety, trust, peer support, efficient reflection; complemented 1:1 supervision; valuable in rural settings.
Competency-Based Training Models	QI curriculum—Dolansky et al. [11]	74 postgraduates across 5 professions; 5 years of structured didactics, QI projects, faculty mentorship.	↑ QI knowledge (QIKAT-R, p < 0.001); 100% QI project completion; national presentations; greatest success when aligned with institutional priorities.
	Milestones-based discharge assessment—Suddarth et al. [31]	Structured discharge observation & feedback during rounds; attendings oriented to assess competence.	↑ Direct observation; ↑ quality feedback; ↑ faculty awareness & confidence.
Skills Training Models	Supervision training protocol—Cruz et al. [10]	Behavior analysts trained in supervision skills (instruction, modeling, role-play, feedback, task analysis to mastery).	↑ Supervisor behaviors; ↑ therapist trial teaching; gains maintained post-training; cascading supervision effects.
	ICOR—Winn et al. [34]	3.5-day program: inpatient tasks, workshops, feedback.	↑ Preparedness (7.0 vs. 5.6, p = 0.0496); strong satisfaction; ↑ confidence; intensive training effective for practice readiness.
Case-Based Learning Models	Interprofessional case-based curriculum—Gooding et al. [16]	6 cases over 6 months; weekly 4 h sessions; interprofessional faculty facilitated; problem-solving, role modeling, reflection.	↑ Clinical confidence; ↑ role clarity; ↑ communication; RIPLS/IEPS stable; deep exploration & modeling valued.
Mentorship & Coaching Models	Collaborative coaching—Tatla et al. [32]	Participatory action research with child/family care professionals.	↑ Coaching skills; ↑ team cohesion & communication; limited quantitative change.
	Palliative mentoring—O’Mahony et al. [26]	2-year hybrid program (conferences, e-learning, observation, improvement projects).	↑ Confidence in palliative skills; ↑ interdisciplinary collaboration; successful improvement projects.
Clinical Knowledge & Skills Across Models	Multiple (Cao & Hull [9], Cruz et al. [10], Dolansky et al. [11])	Knowledge and skills gains varied by model focus (chronic pain, QI, supervision).	SSIPPC: ↑ pain knowledge; QI: ↑ QI knowledge (QIKAT-R, p < 0.001); Skills training: ↑ supervisor behavior, ↑ therapist competence; evidence of domain-specific clinical skill improvements.

↑ indicates improvement/increase; ↓ indicates reduction/decrease in the reported outcome following the intervention.

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