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Record W3092087614 · doi:10.3390/jpm10040163

Convergent and Concurrent Validity between Clinical Recovery and Personal-Civic Recovery in Mental Health

2020· article· en· W3092087614 on OpenAlexafffund
Jean‐François Pelletier, Larry Davidson, Charles‐Édouard Giguère, Nicolás Franck, Jonathan Bordet, Michael Rowe

Bibliographic record

VenueJournal of Personalized Medicine · 2020
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsInstitut Universitaire en Santé Mentale de Québec
FundersNational Center for Advancing Translational SciencesFonds de Recherche du Québec - Santé
KeywordsMental healthConcurrent validityMoodPsychologyAnxietyParticipatory action researchClinical psychologyMedicinePsychiatryPsychometricsInternal consistency

Abstract

fetched live from OpenAlex

Several instruments have been developed by clinicians and academics to assess clinical recovery. Based on their life narratives, measurement tools have also been developed and validated through participatory research programs by persons living with mental health problems or illnesses to assess personal recovery. The main objective of this project is to explore possible correlations between clinical recovery, personal recovery, and citizenship by using patient-reported outcome measures. All study participants are currently being treated and monitored after having been diagnosed either with (a) psychotic disorders or (b) anxiety and mood disorders. They have completed questionnaires for clinical evaluation purposes (clinical recovery) will further complete the Recovery Assessment Scale and Citizenship Measure (personal-civic recovery composite index). Descriptive and statistical analyses will be performed to determine internal consistency for each of the subscales, and assess convergent-concurrent validity between clinical recovery, citizenship and personal recovery. Recovery-oriented mental health care and services are particularly recognizable by the presence of Peer Support Workers, who are persons with lived experience of recovery. Upon training, they can personify personalized mental health care and services, that is to say services that are centered on the person's recovery project and not only on their symptoms. Data from our overall research strategy will lay the ground for the evaluation of the effects of the intervention of Peer Support Workers on clinical recovery, citizenship and personal recovery.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.523
Threshold uncertainty score0.816

Codex and Gemma teacher scores by category

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

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 head0.496
GPT teacher head0.515
Teacher spread0.019 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations23
Published2020
Admission routes2
Has abstractyes

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