Evaluating dental student competency in forensic rugoscopy for human identification

Rugoscopy is a recognized method for human identification. Its reliability, however, may be compromised when general dentists with limited forensic training perform identification. Evaluating the role of future practitioners-dental students-is essential to address this competency gap. This study assessed the ability of dental students in recognizing and interpreting palatal rugae patterns for forensic identification. Fifty-four final-year dental students were evaluators. Forty maxillary casts (10 pre-orthodontic, 30 post-orthodontic) were used. All casts were duplicated and modified to retain only the palatal rugae area, with all teeth removed to prevent dental feature-based recognition. Participants matched each Set 1 cast to one in Set 2. The procedure was repeated after one week to determine test-retest reliability, assessed using prevalence-adjusted bias-adjusted kappa (PABAK). The mean accuracy for rugoscopy-based identification was 83.06% (± 15.49%), with an average time of 1.37 (± 0.34) minutes per matching. Reliability ranged from substantial to almost perfect, showing agreement rates between 74.07% and 96.30%. This simulated exercise demonstrated that trained dental students could achieve good accuracy and reliability in identifying individuals based on palatal rugae patterns. Consequently, trained dental students may play a valuable supportive role in forensic identification tasks when specialized forensic odontologists are unavailable. Further research is recommended to establish standardized criteria to improve both accuracy and reliability.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-12-25
DOI
https://doi.org/10.1038/s41598-025-33373-0
Primary Topic
Forensic Anthropology and Bioarchaeology Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluating dental student competency in forensic rugoscopy for human identification

Natchalee Srimaneekarn, P. Chunhabundit, Asst. Prof Tawepong Arayapisit
Scientific Reports
Forensic Anthropology and Bioarchaeology Studies
article

Evaluating dental student competency in forensic rugoscopy for human identification

Natchalee Srimaneekarn, P. Chunhabundit, Asst. Prof Tawepong Arayapisit
article en

Abstract

Rugoscopy is a recognized method for human identification. Its reliability, however, may be compromised when general dentists with limited forensic training perform identification. Evaluating the role of future practitioners-dental students-is essential to address this competency gap. This study assessed the ability of dental students in recognizing and interpreting palatal rugae patterns for forensic identification. Fifty-four final-year dental students were evaluators. Forty maxillary casts (10 pre-orthodontic, 30 post-orthodontic) were used. All casts were duplicated and modified to retain only the palatal rugae area, with all teeth removed to prevent dental feature-based recognition. Participants matched each Set 1 cast to one in Set 2. The procedure was repeated after one week to determine test-retest reliability, assessed using prevalence-adjusted bias-adjusted kappa (PABAK). The mean accuracy for rugoscopy-based identification was 83.06% (± 15.49%), with an average time of 1.37 (± 0.34) minutes per matching. Reliability ranged from substantial to almost perfect, showing agreement rates between 74.07% and 96.30%. This simulated exercise demonstrated that trained dental students could achieve good accuracy and reliability in identifying individuals based on palatal rugae patterns. Consequently, trained dental students may play a valuable supportive role in forensic identification tasks when specialized forensic odontologists are unavailable. Further research is recommended to establish standardized criteria to improve both accuracy and reliability.

Scientific ReportsVol. 16(1)
Mahidol University (TH)
Quality Education
Openalex Percentile: Top 23%
Forensic Anthropology and Bioarchaeology Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.