No Talent Required: Using Drama Therapy in Support Groups for Cancer Patients
Bibliographic record
Abstract
Objectives: It is well known that a cancer diagnosis impacts a person’s mental, emotional and spiritual well-being as well as their body. Many patients and caregivers seek out support groups to bolster themselves in this challenging time. While talk and peer-based groups can provide validation and understanding, drama therapy can provide a beneficial approach for support groups.Methods: Drama therapy is a gentle form of creative therapy between a trained therapist and one or more clients with a specific therapeutic intention. It uses action methods (such as role play, storytelling, improvisation, writing, and projective tools) to facilitate creativity, imagination, learning, insight and growth. Drama therapy provides a creative-expressive basis for support groups within a humanistic framework.Results: Drama therapy-based support groups encompass the patient’s holistic experience and address all aspects of their cancer experience in order to provide meaning. In addition to validating participants’ perspectives, they help participants to come to terms with their experiences and emotions, to gain insight into their responses and to learn new ways of dealing with them. Drama therapy utilizes the concepts of distance, projection and witnessing to allow clients to explore challenging issues in a safe – and potentially playful – way. It is a flexible approach that can be adapted to the specific needs of participants and therefore is well equipped to serve a broad spectrum of issues and concerns in varying and supportive ways.Conclusions: This poster will highlight some of the theory behind drama therapy-based support groups to show the advantages these groups entail. It will also showcase various creative interventions that have been used with cancer patients.
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.
How this classification was reachedexpand
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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".