Depth and Distance Perception of Dentists and Dental Students
Bibliographic record
Abstract
The quality of work carried out by dentists is dependent, among other things, on experience, training, and manual dexterity. Historical focus on the latter as a predictor of dental performance has failed to recognize that dental competence also requires good perceptual and visual skills, not only for gathering information but also for judging positions, distances, and the size of objects and shapes. Most predictive tests ignore visual and interpretative deficiencies that could make individual acquisition of skills and interpretation of instructions difficult. Ability to estimate depth and distance, the manner in which students learn this ability, whether and how it can be taught, or whether there is an association among ability, stereopsis, and dental performance has not been thoroughly examined; nor has the perception that dental students fully understand verbal and written instruction relating to depth and distance. This study investigated the ability of dentists and dental students to estimate and reproduce small depths and distances and the relationship of this ability to stereopsis, dental experience, and student performance. A total of 163 undergraduate dental students from three year groups and 20 experienced dentists and specialists performed three tasks. A depth-perception task involved estimation of the depth of two sets (2-mm or 4-mm wide) of nine computer milled slots ranging in depth from 0.5 to 4.0 mm. A distance task involved estimation of the width of specially prepared printed square blocks. In a writing task, participants recorded distances across a printed line on separate sheets of paper. All tasks were conducted at set positions in custom-made transportable light boxes. Stereopsis and visual acuity were also measured. Ability to perform perceptual tasks varied enormously, with the level of accuracy dependent on the type of task and dental experience. Many students had considerable difficulty in estimating depth. Inexperienced students performed poorly. Most participants overestimated depth and distance estimation tasks, but underestimated when required to draw distances. Smaller depths and distances were easier to estimate than larger ones. All groups overestimated depth more in 4-mm-wide blocks than in 2-mm-wide blocks. There was no correlation found between depth and distance estimation and stereopsis scores or with the overall grades tested. This study highlights that some dentists and many dental students, particularly early in their course, have great difficulty in accurately gauging depths and distances. It is proposed that that this could impact significantly on a student's ability to interpret verbal and written preclinical instruction and could make the acquisition of manual skills and interpretation of clinical instruction difficult. Routine testing of all undergraduate dental students for perceptual and visual difficulties is recommended, so that those with difficulties can be identified and problems remedied, if possible, early in their course.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".