Designing a Library of Lived Experience for Mental Health: integrated realist synthesis and experience-based co-design study
Bibliographic record
Abstract
ABSTRACT Objective Living Library ‘Readers’ can learn about experiences of others through conversations with living ‘Books’. This study sought to generate a realist programme theory and a theory-informed implementation guide for a Library of Lived Experience for Mental Health (LoLEM). Design Integrated realist synthesis and experience-based co-design. Setting Ten online workshops with participants based in the North of England. Participants Thirty-one participants with a combination of personal experience of using mental health services, caring for someone with mental health difficulties, and/or working in mental health support roles. Results Database searches identified 30 published and grey literature evidence sources which were integrated with data from 10 online co-design workshops. The analysis generated a programme theory comprising five context-mechanism-outcome (CMO) configurations. For Readers, direct conversations humanise others’ experiences (CMO 2) and provide the opportunity to flexibly explore new ways of living (CMO 3). Through participation in a Living Library, Books may experience personal empowerment (CMO 4), while the process of self-authoring and co-editing their story (CMO 5) can contribute to personal development. This programme theory informed the co-design of an implementation guide highlighting the importance of tailoring event design and participant support to the contexts in which LoLEM events are held. Conclusions The LoLEM has appeal across stakeholder groups and can be applied flexibly in a range of mental health-related settings. Implementation and evaluation are required to better understand the positive and negative impacts on Books and Readers. Registration PROSPERO CRD42022312789 Strengths and limitations of this study This study used a novel, iterative, and creative approach to integrating theory development and intervention co-design. The programme theory provides a conceptual basis for further evaluation of a LoLEM, including outcomes for those participating in events as ‘Books’ and ‘Readers’. This study informed detailed, co-designed implementation guidance for use by LoLEM organisers. However, the LoLEM is yet to be delivered as a sustained programme of events, so long-term impacts require further investigation.
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 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 | 0.059 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".