What do we know about interventions to improve educator wellbeing? A systematic literature review
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
Abstract This systematic literature review summarises the research into interventions intended to improve the wellbeing of educators in the early childhood to secondary sectors. A search of articles published between 2000 and 2020 yielded 23 articles that met our inclusion criteria. Studies were included if they collected quantitative or qualitative data about educator wellbeing pre-intervention and post-intervention from the same group(s) of educators. We classified articles into five categories based on their content: multi-foci (several content areas included in a program), mindfulness, gratitude, professional development (classroom practice oriented), and physical environment. The articles revealed wide variations in: wellbeing theories underpinning interventions, the phenomena measured, and the effectiveness of the interventions. In some studies wellbeing was conceptualised as the absence of negative states (such as stress), in other studies to the presence of positive states (such as satisfaction), and in a few studies as the combination of both these approaches. Some of the gaps noted across the research include the lack of attention to the role of the school climate in determining the success of an intervention, and the lack of analysis to explore whether interventions work better for some individuals than others (for example, a lack of reporting of the characteristics of participants who drop out of the interventions). Overall, the multi-foci interventions show the most promise for improving educator wellbeing.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 0.001 |
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