How service users and carers understand, perceive, rephrase, and communicate about “depressive episode” and “schizophrenia” diagnoses: an international participatory research
Bibliographic record
Abstract
BACKGROUND: For ICD-11, the WHO emphasized the clinical utility of communication and the need to involve service users and carers in the revision process. AIMS: The objective was to assess whether medical vocabulary was accessible, which kinds of feelings it activated, whether and how users and carers would like to rephrase terms, and whether they used diagnosis to talk about mental health experiences. METHOD: An innovative protocol focused on two diagnoses (depressive episode and schizophrenia) was implemented in 15 different countries. The same issues were discussed with users and carers: understanding, feelings, rephrasing, and communication. RESULTS: Most participants reported understanding the diagnoses, but associated them with negative feelings. While the negativity of "depressive episode" mostly came from the concept itself, that of "schizophrenia" was largely based on its social impact and stigmatization associated with "mental illness". When rephrasing "depressive episode", a majority kept the root "depress*", and suppressed the temporal dimension or renamed it. Almost no one suggested a reformulation based on "schizophrenia". Finally, when communicating, no one used the phrase "depressive episode". Some participants used words based on "depress", but no one mentioned "episode". Very few used "schizophrenia". CONCLUSION: Data revealed a gap between concepts and emotional and cognitive experiences. Both professional and experiential language and knowledge have to be considered as complementary. Consequently, the ICD should be co-constructed by professionals, service users, and carers. It should take the emotional component of language, and the diversity of linguistic and cultural contexts, into account.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".