Protecting into emotion: therapeutic enactments with military veterans transitioning back into civilian life
Bibliographic record
Abstract
Over 18.5% of military personnel returning from war zones to civilian life suffer mental health issues, which can lead to family breakdown, homelessness and other problems. Almost 4000 Australian soldiers have returned home from active service in the last decade suffering from combat stress and mental health conditions. A 2009 Australian independent government review warned that a new generation of veterans with posttraumatic stress disorder (PTSD) and severe mental health disorders will emerge in the next five years, with as many as one in four likely to need mental health treatment. The Difficult Return: arts-based approaches to mental health literacy and building resilience with recently returned military personnel and their families is a three-year Australian Research Council funded arts project aimed at supporting the mental health and well-being of recently returned veterans in Australia, USA and Canada. The project combines a range of arts-based strategies to help returning veterans, including online digital films to improve awareness and help seeking motivation, a performance project with ex-soldiers and actors, and a process-based group work programme. The paper will focus specifically on the development of the Veterans Transition Programme (VTP) a partnership between Griffith University and the University of British Columbia, Vancouver. The VTP leverages the resilience and resources of veterans, providing help to participants attempting to better understand the impact of military experience on their lives. It draws on a range of psycho-educational and action-based approaches, including life review and drama enactments to engage participants in ways of dealing with disturbing events from their lives. The paper will describe and reflect on a number of the strategies used in the VTP, for example, how the drama enactments help to integrate emotion, cognition and embodied awareness, the significance of contact when working with trauma, and the importance of a therapeutic milieu in constructing ‘units’ of support for the veterans.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".