An Online Course in Critical Mental Health Promotion: Teaching and Learning at Multiple Spheres of Influence
Bibliographic record
Abstract
Background: Supportive environments contribute to the mental health of individuals, local and global communities. Ways of thinking “critically” about what we know and ways of accomplishing mental health promotion work have a more contested history however. A critical perspective demands subjective awareness, and an openness to view the world from multiple perspectives. As such, a collaborative, international, and fully on-line course was developed between post-secondary educational institutions in Norway and Canada. This course intends to meet a need for critical awareness and understanding of the connect ion of diverse perspectives and environments to mental health promotion practices in the field. Purpose: Our study, of the development and implementation of an innovative critical mental health promotion course, was oriented around the following key questions: How is capacity for critical mental health promotion awareness developed through an on-line international learning environment? And how can supportive learning environments reshape mental health support across international borders? Our goal was to explore the work of students and faculty with the tensions that dominate current mental health promotion. This course began from the diverse locations, experiences and approaches of our students as important sites of critical exploration. Through the virtual world of electronic learning activities, students entered this diversity of worlds, and debated over the shape of health and mental health as notions themselves, as well as over the approaches that best produce support. Most importantly, students debated over the distribution of po wer, justice, and social and economic advantage held within mental health and various approaches to promoting mental health. Method: The overall approach was based on action research using collaborative enquiry of the case study of our pilot course offering. The enquiry was conducted over 3 years of course development and pilot course delivery. Results: Ultimately, through our reflection and study of the critical learning approaches in action, we were able to explore what supportive environments for mental health are and what particular approaches “do” locally and globally. Further we were able to reorient mental health promotion work through network building in ways that may potentially change nursing practice. Conclusions: The results and lessons learned, from development to implementation of an on-line collaborative international mental health promotion course, expanded the capacities of nursing programs, educational institutions, faculty and students, and expanded what can be known about supportive environments for mental health. © 2012 Published by Elsevier Ltd.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.034 | 0.005 |
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".