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Record W3082692820 · doi:10.1111/camh.12419

Narrative Matters: Mental health recovery – considerations when working with youth

2020· article· en· W3082692820 on OpenAlexaff
Émmanuelle Khoury

Bibliographic record

VenueChild and Adolescent Mental Health · 2020
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMental healthPsychologyPerspective (graphical)NarrativeFocus groupMental health lawHealth carePsychiatrySociologyPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Youth mental health and well-being is of increasing concern to practitioners and policy-makers. Youth experiencing mental health problems face many barriers in accessing care and often have different needs to those of adults experiencing mental health problems. In order to adequately respond to the needs of young people aged 12-25, it is necessary to understand, from their perspective, their diverse needs and their different realities, using a global health approach and through participation in the development of mental health services and care. There are documented difficulties in implementing a recovery-oriented practice approach that have led to misapplications, misunderstandings and critiques. That said, there is little research or discussion on mental health recovery by and for young people and young adults. PURPOSE: To help child and adolescent mental health practitioners better assess the pertinence of the mental health recovery model in their practice, a focus on the emergence of the model can be helpful in order to adapt the current conceptions of mental health recovery for work with youth. CONCLUSION: Child and adolescent mental health professionals might want to consider the following three suggestions - consider developmental processes, focus on hope and create strong community ties.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.382
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.183
GPT teacher head0.358
Teacher spread0.175 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreCommentary

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".

Quick stats

Citations14
Published2020
Admission routes1
Has abstractyes

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