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Record W2947164070 · doi:10.2196/13955

Validation of the InnoWell Platform: Protocol for a Clinical Trial

2019· article· en· W2947164070 on OpenAlex
Tracey A Davenport, Haley M LaMonica, Lisa Whittle, Amelia English, Frank Iorfino, Shane Cross, Ian B. Hickie

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJMIR Research Protocols · 2019
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthProtocol (science)Health careDigital healthIntervention (counseling)MedicineWeb applicationNursingComputer scienceWorld Wide WebAlternative medicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: New electronic health technologies are being rapidly developed to improve the delivery of mental health care for both health professionals and consumers and better support self-management of care. We developed a Web-based platform (the InnoWell Platform) that supports the prevention, early intervention, treatment, and continuous monitoring of mental health and maintenance of well-being in people aged 2 years and older. The platform is a customizable digital tool kit that operates through existing service providers who utilize the system to provide their consumers with access to evidence-based assessments and feedback, intervention options, and outcome monitoring. It does this by collecting, storing, and reporting personal and health information back to consumers and their health professionals to promote collaborative care partnerships that aim to improve the management of mental ill health and maintenance of well-being. OBJECTIVE: The aim of this study was to describe the research protocol for a naturalistic prospective clinical trial wherein all consumers presenting for care to a traditional face-to-face or Web-based mental health service in which the InnoWell Platform is being offered as part of standard clinical care will be given the opportunity to use the platform. METHODS: The Web-based platform is a configurable and customizable digital tool that assists in the assessment, monitoring and management of mental ill health, and maintenance of well-being. It does this by collecting, storing, and reporting health information back to the person and his or her clinician to enable transformation to person-centered care. The clinical trial will be conducted with individuals aged 2 years and older presenting to participating services for care, including persons from the veteran community, Aboriginal and Torres Strait Islander people, people from culturally and linguistically diverse backgrounds, the lesbian, gay, bisexual, transgender, and intersex community, and those from broader education and workforce sectors, as well as people with disabilities, lived experience of comorbidity, complex disorders, and suicidality. RESULTS: Project Synergy was funded in June 2017, and data collection began in November 2018 at a youth mental health service. At the time of this publication, 5 additional services have also begun recruitment, including 4 youth mental health services and a veteran's service. The first results are expected to be submitted in 2020 for publication. CONCLUSIONS: This clinical trial will promote access to comprehensive, high-quality mental health care to improve outcomes for consumers and health professionals. The data collected will be used to validate a clinical staging algorithm designed to match consumers with the right level of care and reduce the rate of suicidal thoughts and/or behaviors and suicide by suggesting pathways to care that are appropriate for the identified level of need, while simultaneously enabling a timely service response. TRIAL REGISTRATION: Australian New Zealand Clinical Trial Registry ACTRN12618001676202; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=374632 (Archived by WebCite at http://www.webcitation.org/78TOi5jwl). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/13955.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.509
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.699
GPT teacher head0.731
Teacher spread0.032 · 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