The Cost of Caring: Compassion Fatigue among Peer Overdose Response Workers in British Columbia
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
Background: The drug toxicity crisis has had dramatic impacts on people who use drugs. Peer overdose response workers (peer responders), i.e., individuals with lived/living experience of drug use who work in overdose response settings, are particularly susceptible to negative physical and mental health impacts of the crisis. Despite that, the mental health impacts on peer responders have yet to be studied and measured. Methods: The Professional Quality of Life survey (Version 5) was completed by 47 peer responders at two organizations in British Columbia between September 2020 and March 2021 to assess compassion satisfaction and compassion fatigue. The Likert scale responses were converted into numerical values and scores were calculated for each sub-scale. The mean score was calculated for each sub-scale and categorized as low, medium, or high, based on the instructions for Version 5 of the instrument. Results: Our study uncovered a high mean score for compassion satisfaction, low mean score for burnout, and medium mean score for secondary traumatic stress among peer responders. These results may be due to the participants’ strong feelings of pride and recognition from their work, as well as the low number of participants that felt they had too much to do at work. Conclusion: Although peer responders derive pleasure and fulfillment from their jobs, i.e., compassion satisfaction, they also sometimes face burnout and stress due to continuous exposure to the trauma of the people they support. These results shed light on the areas that need to be targeted when creating supports for peer responders.
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) | 0.000 | 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 it