Students' resilience and mental health in the dental curriculum
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: Dental education is perceived as a source of students' psychological and occupational stress. Resilience has been proposed as a protective factor that may support students' in managing that stress. The objectives of this study were twofold: to map the mental health and well-being content in the curriculum of the Faculty of Dentistry (FoD) at the University of British Columbia (UBC) and to investigate factors influencing resilience levels amongst dental students at UBC. METHODS: The curricular database and website of UBC's FoD were used to gather information on mental health content. A survey with the Connor-Davidson 10-Item Resilience Scale was distributed to dental students at UBC (N = 289). Students' de-identified demographic data were also collected. RESULTS: Two main mental health and well-being curricular components were identified: one didactic session on stress management and one interactive workshop on resilience. The response rate for the survey was 68.2%. Students who did not receive any mental health content (2020/21 year 1 students) had higher resilience scores (p = .043) when compared to students who received both components (2019/20 year 1 students and 2018/19 year 2 students). The multiple regression analysis highlighted North American/European ethnic origins as a predictor for higher resilience levels (p = .008). CONCLUSIONS: The results of this study showed that ethnic origins and major life events, such as the pandemic, influenced resilience. Curricular activities promoting resilience seemed to not necessarily impact students' resilience. Further longitudinal studies are needed to assess the curricular and non-curricular activities influence over dental students' well-being.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it