Sedation in dental medicine: a new competency framework to secure practice

The global expansion of conscious sedation in dental practices raises critical safety issues specific to non-operating room anesthesia (NORA) environments. In this context of "comfort dentistry," the specialized nurse is no longer limited to simple technical assistance; they become the guarantor of hemodynamic monitoring and airway management in often cramped spaces, with sometimes delayed access to critical emergency resources. However, current protocols frequently remain modeled on hospital general anesthesia, omitting the specificities of crisis response in outpatient dental settings.

The objective of this study was to design and validate a standardized competency framework for dental sedation nurses. Based on the "Onion Competency Model," the study integrates both observable technical skills and deep personality traits necessary for clinical excellence. To achieve this, the authors consulted a multidisciplinary panel of 25 experts — anaesthetists, oral surgeons, and nursing specialists. The methodology is based on a modified Delphi process to stabilize consensus and the use of the Analytic Hierarchy Process (AHP) to determine, with mathematical rigour, the weight of each competency in perioperative safety.

Methodology for constructing the repository

This study adopted a sequential exploratory mixed-methods design, drawing on the "Onion" competency model and CREDES guidelines to structure the competency framework for dental sedation nurses (NORA).

• Phase 1: Initial pool development – A structured literature review (546 articles identified) combined with seven behavioral interviews (BEI) using the STAR technique allowed for the extraction of a preliminary reservoir of 58 competency indicators.
• Phase 2: Validation by modified Delphi method – Between August and October 2025, a two-round consultation was conducted with a multidisciplinary panel of 25 experts (anaesthetists, dental surgeons, and nursing managers) from 9 provinces. Consensus was evaluated on a five-point Likert scale, supplemented by anonymous qualitative feedback.
• Prioritization and Weighting – The authors used the Analytic Hierarchy Process (AHP) to determine the relative weight of the indicators. The final tree structure consists of 4 primary domains, 11 secondary indicators, and 40 tertiary indicators.
• Reliability analyses – The rigor of the framework was validated by calculating the experts' authority coefficient (Cr), Kendall's coefficient of concordance (W), and consistency ratios to ensure the logic of the weighting matrices.

Competency framework validation results

The study resulted in the creation of a competency framework structured into three levels, validated by a panel of 25 multidisciplinary experts. The reliability of the consensus was confirmed by an expert authority coefficient (Cr) of 0.847 and a global consistency ratio (AHP) of 0.034, demonstrating high logical rigor.

Structure and weighting of the competency framework

The final framework consists of 4 primary, 11 secondary, and 40 tertiary indicators. Analysis using the Analytic Hierarchy Process (AHP) established the following hierarchy of importance for the main domains:

Primary Domain (Indicator)	Relative Weight (AHP)
Professional skills	0.361
Professional Knowledge	0.315
Personal Traits	0.179
Professional Accomplishment	0.151

Consensus and critical indicators

La coordination entre les experts s'est avérée statistiquement significative lors du second tour de consultation Delphi, avec un coefficient W de Kendall montrant un consensus fort (p < 0,001).

• Risk alert management: Identified as the most critical secondary competency with a weight of 0.289.
• Evolution of the indicator pool: Initially composed of 58 items from the literature review and behavioral interviews (BEI), the pool was refined to retain only 40 tertiary indicators meeting the consensus criteria (mean importance score ≥ 4.0 and coefficient of variation < 0.2).

Qualitative observations from the STAR (Situation, Task, Action, Result) interviews highlighted that, unlike traditional perioperative nursing care, dental office sedation (NORA) requires increased vigilance regarding human factors and an immediate response capacity in the absence of heavy on-site resuscitation resources.

Dental sedation: towards a standardisation of the nursing role

The results of this study highlight a major transition: the dental sedation nurse is no longer a mere operative assistant, but the guarantor of perioperative safety. The preponderance of the "Professional Skills" domain (weight 0.361) and the "Risk Alert Management" sub-indicator (0.289) demonstrates that, for the practitioner, the clinical vigilance of their team takes precedence over pure technical execution. In NORA (Non-Operating Room Anaesthesia) settings, where access to resuscitation resources may be delayed, this "situational awareness" is the true safeguard against adverse events.

Unlike standard perioperative protocols that are often too general, this framework validated by 25 experts integrates the specificities of outpatient dentistry: restricted spaces, rapid patient turnover, and shared airway management. The use of the Onion model allows for linking visible skills (technical care) to deep personal attributes, which are essential for managing the stress of respiratory depression or unforeseen cardiovascular instability in the dental practice.

The study does, however, present a geographical limitation, as the data were sourced from experts practicing in China. Although the methodological rigor is high (authority coefficient Cr of 0.847 and AHP consistency ratio of 0.034), adaptation to European regulatory frameworks remains necessary. Nevertheless, this framework provides a solid scientific basis for structuring recruitment and continuous training, filling a normative gap that had previously hindered the secure development of sedation in dental practice.

Summary of results

This study validates a framework of 55 competency indicators for nurses specialized in dental sedation. The results place technical skills (weight 0.361) and theoretical knowledge (0.315) at the top of the priorities, with a critical emphasis on early warning risk management (0.289), essential for preventing incidents in non-operating room anesthesia (NORA) environments.

In concrete terms, for the practitioner:

• Secure your recruitment: Prioritize profiles capable of proactively detecting signs of hypoventilation or hemodynamic instability, well beyond simple chairside assistance.
• Standardise monitoring: Integrate the concept of "alert management" into your internal protocols to compensate for limited access to intensive care resources within the dental practice.
• Target continuing education: Focus your team's updates on situational awareness and crisis management, the pillars of patient safety in outpatient sedation.

Refers to anesthesia performed outside conventional operating theaters. In the dental context, this involves specific challenges such as shared airways and limited emergency resources compared to a hospital environment. Theoretical framework structuring competencies hierarchically: the outer layers represent observable technical skills, while the core contains deep and stable personal traits influencing clinical excellence. Structured expert consultation process (here in two rounds) aimed at establishing a consensus. It is termed 'modified' because the initial indicators are derived from a literature review rather than generated by the experts themselves. Multi-criteria mathematical decision-making procedure used to calculate the relative weight of each competency indicator, ensuring logical rigor through consistency ratios. Interview technique based on the narration of real critical incidents (STAR method: Situation, Task, Action, Result) to identify tacit competencies essential to clinical practice. Expert reliability index calculated from their judgment coefficient (Ca) and their familiarity coefficient (Cs) with the subject, reaching 0.847 in this study. Statistical measure used to assess the degree of overall consensus among members of the expert panel during the Delphi consultation rounds.

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