Teacher Candidate Mental Health and Mental Health Literacy
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
Providing teacher candidates with a strong foundation in mental health literacy during their teacher education program is crucial in ensuring novice teachers are prepared to support the mental health needs of their students. In addition to responding to students, teacher candidates are typically at an age when mental health disorders are common and their personal mental health during the program also needs to be considered. In the current study, a survey was conducted with 375 teacher candidates in order to extend our understanding of the personal mental health and mental health literacy of pre-service teachers. Results showed that teacher candidate mental health was similar to the general population, with 77% reporting positive personal mental health. Teacher candidates did report high levels of stress. Teacher candidates had considerable personal and professional experience with mental health prior to starting the program and reported positive attitudes and moderate levels of knowledge about mental health disorders. Despite considerable experience and a positive perspective, teacher candidates did not feel ready or competent to support the mental health of students. Current teacher education programs should consider building on the knowledge and experience the teacher candidates bring, and enhancing their capacity to translate that knowledge into the classroom setting.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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