Humanistic environment, perceptions, and associated variables in predoctoral and allied dental programs: 2022 American Dental Education Association climate study results
Bibliographic record
Abstract
OBJECTIVES: The objectives were to determine if there are differences in perception of programs' humanistic environment, and overall climate, and to determine the correlations between a positive overall climate, a humanistic environment, and humanistic leadership in United States and Canadian dental and allied dental programs. METHODS: The 2022 American Dental Education Association Climate Survey included 258 US dental and Canadian dental schools and allied dental education programs. The study aimed to measure dental schools and allied dental education programs' efforts to provide a humanistic and inclusive environment. This article reviewed the findings in relation to the objectives. The significance of explanatory variables was tested using logistic regression in PROG GLIMMIX of SAS. Cramer's Variable was calculated to determine the multicollinearity, indicating strong correlations among independent variables. RESULTS: A total of 258 programs responded to the survey, 238 programs in the United States, and 20 programs in Canada. 66 Dental schools responded, 192 Allied Dental Programs, 49 Dental Assisting programs from the United States, 137 Dental Hygiene (125 United States and 12 Canada), five Dental Laboratory technologies in the United States, and one Dental Therapy in the US allied dental education programs were grouped together (i.e., dental hygiene, dental laboratory tech, dental assisting, and dental therapy). Allied dental respondents were twice as likely to report their educational environment is humanistic, they were satisfied with the overall climate, and their leadership was committed to fostering a humanistic environment (p < 0.01) compared with dental respondents. Participants who identified their program as being humanistic were 9.1 times more likely to be satisfied with the overall climate of their program (p < 0.01). Participants who felt their leadership was committed to fostering a humanistic environment were 4.5 times more likely to be satisfied with the overall climate of their program (p < 0.01). Variables were identified as important to overall climate, humanistic environment, and humanistic leadership, such as a sense of community, training, and leadership's response to events. CONCLUSION: Leadership that establishes a humanistic climate providing education, training, and support to faculty, students, and staff creates a more positive perception of the overall climate by members of the community. Allied dental programs had a significantly higher perception of an inclusive climate than dental programs.
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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 | 0.002 | 0.005 |
| 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 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".