STAYING CONNECTED: SERVICE-USER EXPERIENCE OF THE RECOVERY JOURNEY AND LONG-TERM ENGAGEMENT WITH A MENTAL HEALTH CLINIC
Bibliographic record
Abstract
While there has been much interest in recent years about the potential impact that short-term therapy can have on those needing mental health support, relatively little attention has been paid to the needs of those who require long-term support. In this phenomenological study exploring long-term service-users’ experiences of the recovery journey and the role of mental health support in facilitating that journey, a sample (n = 6) of service-users who had a minimum of five years of continuous involvement with a community-based mental health clinic participated in a pair of focus groups designed to help them share their experience of the recovery journey. Our analysis revealed themes of contending not just with extreme violence and other adversities, but also with an often unhelpful helping system, as service-users expended effort in locating the consistent, accessible support they needed in order to find a reason to go on in the wake of devastating personal experiences. The study also emphasized how prioritizing the top-down need for efficiency over the bottom-up need for consistent, flexible support can have the inadvertent effect of extending rather than shortening treatment. Implications of these findings for the delivery of mental health services are discussed.
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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 | 0.012 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".