Prosthodontic Program Directors' Perceptions Regarding Implant Placement by Prosthodontic Residents: A 2004 Survey Conducted by the Educational Policy Subcommittee of the American College of Prosthodontists
Bibliographic record
Abstract
PURPOSE: In 2004, a survey regarding implant placement by prosthodontic residents was conducted by the Educational Policy Subcommittee of the American College of Prosthodontists (ACP). The aim of the survey was to assess the current trends in implant curricula at advanced graduate prosthodontics programs in the United States and Canada and determine the issues surrounding surgical implant training for prosthodontic residents. MATERIALS AND METHODS: The survey was mailed to the prosthodontic/maxillofacial prosthetic program directors of the 59 prosthodontic graduate programs in the United States and Canada in 2004. Of these, 27 program directors replied, yielding a response rate of 46%. RESULTS: Of the replying programs, 43% either required residents to place or offered the option to have residents place implants. Forty-four percent reported that residents participate by functioning as first assistants for some of their implant patients, 40% have a specific curriculum to train residents in implant placement, 50% reported not having any institutional barriers that prevent program directors from training prosthodontic residents in implant placement, 51% provide implant training using plastic jaws, and 66% of the programs required residents to observe implant surgery in the clinic before they are permitted to place implants. Of prosthodontic residents who treated implant-related patients, the majority treated 11 to 20 patients during their residency. In 2004, 40% of program directors were not trained in the placement of dental implants, and if they did have the implant training, the majority (82%) stated that the nature of their training was 1- to 3-day course(s). CONCLUSIONS: This survey showed that implant dentistry has become an integral part of the postgraduate prosthodontic curriculum. The trends to incorporate implant placement into the postgraduate prosthodontic curriculum were already evident prior to 2004. To address the demand for implant treatment in patient care and enhance surgical implant knowledge, the ACP in 2005 added placement of implants to its Accreditation Standards for Advanced Specialty Education Programs in Prosthodontics.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".