Utilising a web-based e-learning platform for orthodontic case analysis training: a randomised controlled trial

Clinical Snapshot

Key Findings

• P Value: Overall performance improvement: p=0.005; Baseline knowledge equivalence: p=0.842; Extraoral assessment: p<0.001; Radiographic evaluation: p=0.002; UEQ dimensions (pragmatic, hedonic, overall quality): all p<0.001

• Effect Size: Overall group performance improvement: β=8.31 score units. Exploratory subarea effects: analogue superiority in extraoral assessment (b=23.37); digital superiority in radiographic evaluation (b=-17.34). SUS score: digital M=78.89±14.11 vs. analogue M=40.30±11.19.

• Primary Outcome: Overall diagnostic performance improvement across two training sessions was significant for both groups combined (β=8.31, 95% CI [2.66, 13.96], p=0.005), with no statistically significant difference in improvement between the digital and analogue training groups. No between-group difference was detected in the final analogue module examination.

• Nnt Or Sensitivity: No Number Needed to Treat calculated or applicable; no formal non-inferiority margin defined. SUS score of 78.89 for digital training falls within the 'Good' usability range (70–85) per published SUS benchmarks. The analogue group SUS score of 40.30 falls in the 'Poor' range, though this comparison is methodologically unusual as SUS was designed for digital systems.

• Confidence Interval: Overall performance improvement: 95% CI [2.66, 13.96]; Extraoral assessment analogue advantage: 95% CI [7.31, 39.42]; Radiographic evaluation digital advantage: 95% CI [-33.40, -1.29]; SUS comparison p<0.001 (CI not reported for SUS difference)

Clinical Application

Web-based platforms such as Orthotrainer are technically feasible in institutions with reliable internet infrastructure and digital radiographic records. Implementation requires initial investment in platform development or licensing, case library curation, and faculty training. The educator survey data suggesting high time burden of analogue correction supports an institutional efficiency argument for digital adoption. However, the proprietary nature of Orthotrainer and absence of cost data limit immediate replication. Australian dental schools (University of Melbourne, University of Sydney, University of Queensland, Griffith University, and others) are increasingly integrating digital workflows into preclinical and clinical orthodontic training, consistent with the Australian Dental Council's competency standards for digital literacy. The findings are broadly consistent with the direction of Australian dental education policy, though direct adoption of Orthotrainer would require TGA-equivalent software validation if used for clinical decision support rather than purely educational purposes. The RACGP and ADC do not currently provide specific guidance on e-learning platform standards for orthodontic education. PBS considerations are not directly applicable to this educational intervention. Australian dental schools should note the analogue superiority finding in extraoral assessment, as facial analysis remains a core clinical competency assessed in OSCE-format examinations across Australian programmes. Undergraduate dental students in university-based orthodontic training programmes, particularly those with access to digital case libraries and web-based learning infrastructure. Most directly applicable to students in the mid-to-late preclinical or early clinical years of dental education.

Abstract

BACKGROUND: In orthodontic case analysis, structured clinical reasoning is required to achieve a diagnosis and establish a treatment decision. In this randomised controlled trial, a web-based training app was compared with conventional analogue case planning in undergraduate dental students. METHODS: Twenty-eight undergraduate dental students from RWTH Aachen University were randomised to either a digital training group, using the web-based app Orthotrainer, or an analogue training group, performing conventional case analyses with physical models and printed diagnostic records. After a baseline knowledge and online readiness assessment, both groups completed two standardised training sessions. Following the sessions, the ease of use was assessed using the System Usability Scale and the User Experience Questionnaire. The final analogue module exam tested knowledge transfer. Additionally, 27 orthodontic educators from four university orthodontic departments were surveyed regarding analogue correction practices. RESULTS: Baseline orthodontic knowledge was comparable between groups (analogue: M = 13.07 ± 3.15 vs digital: M = 12.86 ± 2.41, p = 0.842). Both groups demonstrated significant performance improvement across training sessions separated by three weeks, ß = 8.31, 95% CI [2.66, 13.96], p = 0.005, without overall group differences. Exploratory subarea analyses revealed analogue superiority in extraoral assessment (b = 23.37, 95% CI [7.31, 39.42], p < 0.001), digital advantage in radiographic evaluation (b = -17.34, 95% CI [-33.40, -1.29], p = 0.002) and no difference in the model analysis. There were no differences between the groups in the final module exam. The usability assessment yielded a mean SUS score of M = 78.89 ± 14.11 for digital training (compared to the analogue training, M = 40.30 ± 11.19, p < 0.001), while students rated the UEQ for the digital version higher in the dimensions of pragmatic, hedonic quality and overall quality (all p < 0.001). Among 27 surveyed educators, analogue correction was rated time-intensive, with preference for digitalisation. CONCLUSIONS: The Orthotrainer web application delivered diagnostic performance equivalent to that of conventional analogue training, proving particularly effective in radiographic analysis. Higher usability and user experience ratings support its integration into routine teaching. These findings suggest that structured digital tools can support the development of diagnostic reasoning and serve as a valuable addition to traditional orthodontic education.