A grounded theory of Creating Connection between peer support workers and clients
Bibliographic record
Abstract
BACKGROUND: It has been widely reported that peer support workers (PSWs) in addictions services are an invaluable part of supporting clients. However, it is unknown how PSWs create benefits with clients through a therapeutic relationship. AIM: We aim to identify the process by which PSWs create better outcomes with clients with addictions. METHOD: We used grounded theory methodology to study the process of peer support worker engagement with clients. We completed semi-structured interviews with 17 peer support workers via Zoom, for up to 60 min. RESULTS: We identified a four-stage process of Creating Connection PSWs apply with clients: the first step is building trust with clients, which offers the predictive capacity in this grounded theory. The second step is fostering the relationship, followed by PSWs bridging clients to other services. The final step is PSWs launching clients towards their independence and use of natural supports. CONCLUSION: Our grounded theory illustrates how PSWs create benefits with clients, which can inform workplace and professional supports for PSWs. This grounded theory can help PSWs move away from nebulous job descriptions to be fully realized members of the healthcare team.
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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 | 0.014 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.033 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".