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Record W3175941350 · doi:10.1136/bmjopen-2021-051190

Mixed-methods study protocol for an evaluation of the mental health transition navigator model in child and adolescent mental health services: the Navigator Evaluation Advancing Transitions (NEAT) study

2021· article· en· W3175941350 on OpenAlexafffundabout
Kristin Cleverley, Katye Stevens, Julia Davies, Emma McCann, Tracy Ashley, Daneisha Brathwaite, Mana Gebreyohannes, Saba Nasir, Katelyn O'Reilly, Kathryn Bennett, Sarah Brennenstuhl, Alice Charach, Joanna Henderson, Lianne Jeffs, Daphne J. Korczak, Suneeta Monga, Claire de Oliveira, Péter Szatmári

Bibliographic record

VenueBMJ Open · 2021
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsSinai Health SystemImpactHospital for Sick ChildrenMcMaster UniversityUniversity of TorontoCentre for Addiction and Mental Health
FundersCanadian Institutes of Health Research
KeywordsMental healthMedicinePsychological interventionReferralProtocol (science)NursingMental health servicePsychiatryAlternative medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Transition from child and adolescent mental health services (CAMHS) to community or adult mental health services (AMHS) is a highly problematic health systems hurdle, especially for transition-aged youth. A planned and purposeful transition process is often non-existent or experienced negatively by youth and their caregivers. Stakeholders, including youth and their caregivers, have demanded interventions to support more effective transitions, such a transition navigator. The transition navigator model uses a navigator to facilitate complex transitions from acute care CAMHS to community or AMHS. However, despite the widespread implementation of this model, there has been no evaluation of the programme, hindering its scalability. This paper describes the study protocol of the Navigator Evaluation Advancing Transitions study that aims to collaborate with patients, caregivers and clinicians in the evaluation of the navigator model. METHODS AND ANALYSIS: A pre and post mixed-method study will be conducted, using the Triple Aim Framework, to evaluate the navigator model. We will recruit participants from one large tertiary and two community hospitals in Toronto, Canada. For the quantitative portion of the study, we will recruit a sample of 45 youth (15 at each site), aged 16-18, and their caregivers at baseline (referral to navigator) (T1) and 6 months (T2). Youth and caregiver participants will complete a set of standardised measures to assess mental health, service utilisation, and satisfaction outcomes. For the qualitative portion of the study, semistructured interviews will be conducted at 6 months (T2) with youth, their caregivers and clinicians to better understand their experience and satisfaction with the model. ETHICS AND DISSEMINATION: Research Ethics Board (REB) approval has been obtained from the lead research sites, the University of Toronto and the Hospital for Sick Children. The results of the study will be reported in peer-reviewed publications, webinars and conferences and to all relevant stakeholders.

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 imitation

Not 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.

metaresearch head score (Codex)0.144
metaresearch head score (Gemma)0.133
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.144
Threshold uncertainty score0.763

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1440.133
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0060.005
Bibliometrics0.0040.005
Science and technology studies0.0050.003
Scholarly communication0.0050.003
Open science0.0060.004
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.1260.023

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 head0.254
GPT teacher head0.614
Teacher spread0.360 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

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

Citations3
Published2021
Admission routes3
Has abstractyes

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