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Record W2912256594 · doi:10.2196/11022

Access to Resources in the Community Through Navigation: Protocol for a Mixed-Methods Feasibility Study

2018· article· en· W2912256594 on OpenAlexafffundvenue
Simone Dahrouge, Alain P. Gauthier, François Chiocchio, Justin Presseau, Claire Kendall, Manon Lemonde, Marie‐Hélène Chomienne, Andrea Perna, Darene Toal-Sullivan, Rose Anne Devlin, Patrick Timony, Denis Prud’homme

Bibliographic record

VenueJMIR Research Protocols · 2018
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsInstitut du Savoir MontfortOntario Tech UniversityOttawa HospitalLaurentian UniversityBruyèreUniversity of Ottawa
FundersAustralian Primary Health Care Research Institute, Australian National UniversityCanadian Institutes of Health Research
KeywordsProtocol (science)Health careNursingKnowledge managementMedicineComputer scienceAlternative medicinePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Community-based health and social resources can help individuals with complex health and social needs achieve their health goals. However, there is often inadequate access to these resources due to a lack of physician and patient awareness of available resources and the presence of social barriers that limit an individual's ability to reach these services. Navigation services, where a person is tasked with helping connect patients to community resources, embedded within primary care may facilitate access and strengthen the continuity of care for patients. OBJECTIVE: This study aims to describe the protocol to assess whether the implementation of the Access to Resources in the Community (ARC) navigation model (an innovative approach to navigation services) is feasible, including its potential to achieve its intended outcomes, and to assess the viability of the evaluation approach. METHODS: The study consists of a single-arm, prospective, explanatory, mixed-methods, pre-post design feasibility study focusing on primary care practice settings with vulnerable populations. Participants include primary care providers and patients. RESULTS: Enrollment is closed with 82 patients. Navigation services have ended for 69 patients. CONCLUSIONS: The study of an innovative complex intervention requires an adequate assessment of the feasibility of the intended approach during which the potential challenges of the planned intervention and need for its adaptation may be uncovered. Undertaking a feasibility study of the ARC navigation model from a conceptually clear and methodologically solid protocol will inform on the practicality and acceptability of the approach, demand for the services, ease of implementation, quality of integration of the new services within primary care, and practicality and potential for efficacy prior to initiating a randomized controlled trial. TRIAL REGISTRATION: ClinicalTrials.gov NCT03105635; https://clinicaltrials.gov/ct2/show/NCT03105635 (Archived by WebCite at hhttp://www.webcitation.org/75FrwXORl). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/11022.

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)0.137
metaresearch head score (Gemma)0.081
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 score0.137
Threshold uncertainty score0.726

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1370.081
Meta-epidemiology (narrow)0.0050.004
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0050.005
Science and technology studies0.0060.005
Scholarly communication0.0040.004
Open science0.0040.004
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0520.014

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 head0.956
GPT teacher head0.876
Teacher spread0.080 · 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

Citations13
Published2018
Admission routes3
Has abstractyes

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