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Record W4417502259 · doi:10.1097/cnj.0000000000001362

Improving Depression Management in Primary Care

2025· article· en· W4417502259 on OpenAlexaff
Shayanna Stryd, Nicole Wheeler, Sally Villaseñor

Bibliographic record

VenueJournal of Christian Nursing · 2025
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsAssembly of First Nations
Fundersnot available
KeywordsPrimary careDepression (economics)Protocol (science)Mental healthManagement of depressionQuality managementQuality (philosophy)

Abstract

fetched live from OpenAlex

ABSTRACT: Depression is a common mental illness. Primary care providers are uniquely positioned to screen and manage patients with depression. A clinical pathway protocol may ensure timely screening, diagnosis, and treatment of depression. This evidence-based quality improvement project used an integrated team approach to implement a depression clinical pathway protocol (DCPP) at a multisite faith-based federally qualified health center. Results showed an improvement in one clinical quality measure, screening, and follow-up for depression, whereas center providers reported the protocol saved time and was easy to use. Using a DCPP may bridge the gap in depression screening and follow-up care.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.972
Threshold uncertainty score0.268

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
Research integrity0.0000.000
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 head0.051
GPT teacher head0.440
Teacher spread0.389 · 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 designOther design
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

Citations0
Published2025
Admission routes1
Has abstractyes

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