Lived experience adaptation of a psychosocial intervention for young adults with bipolar spectrum disorders: Process description and adaptation outcomes
Bibliographic record
Abstract
AIM: Lived experience adaptation of mental health interventions can help ensure that the intervention is appropriate for the target population. This paper describes a youth-led adaptation of a self-stigma reduction intervention for young adults with bipolar spectrum disorders, that is, Narrative Enhancement and Cognitive Therapy. METHODS: Standard guidelines for youth engagement were followed. A youth lived experience adaptation lead and a five-member youth lived experience advisory panel reviewed the intervention and made a number of adaptations to increase its relevance for young people with bipolar disorders. A brief evaluation of the engagement process was conducted. RESULTS: The primary adaptations made to the intervention fell into five areas: (1) wording revisions for recovery-oriented language accessible to youth with a wide variety of language and literacy levels; (2) updating and tailoring to the diagnostic category, with the addition of new quotes describing the lived experience of stigma; (3) integration of a new, engaging graphic design; (4) development of a goal-setting module, as recommended by the research team; and (5) identification of the role of a peer co-facilitator. An evaluation of the engagement process showed that the engagement was extremely meaningful for the youth engaged. CONCLUSIONS: Using a youth lived experience adaptation process, young people can make relevant, important changes to a psychosocial intervention. The resulting early intervention materials are research-ready and are hypothesized to meet the needs of young people with BD in a youth-friendly manner. Research on the acceptability, efficacy, and effectiveness of the newly adapted intervention will be required.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".