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Record W4406274900 · doi:10.1186/s12875-024-02674-0

Profiles of physician follow-up care, correlates and outcomes among patients affected by an incident mental disorder

2025· article· en· W4406274900 on OpenAlexafffundabout
Marie‐Josée Fleury, Louis Rochette, Zhirong Cao, Guy Grenier, Victoria Massamba, Alain Lesage

Bibliographic record

VenueBMC Primary Care · 2025
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsInstitut universitaire en santé mentale de MontréalInstitut National de Santé Publique du QuébecUniversité de MontréalInstitut Universitaire en Santé Mentale de QuébecDouglas CollegeMcGill UniversityDouglas Mental Health University Institute
FundersCanadian Institutes of Health ResearchInstitut National de Santé Publique du Québec
KeywordsMedicineCohortBivariate analysisMental healthLogistic regressionAmbulatory careLatent class modelHealth carePsychiatryFamily medicineInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: This study identified profiles of outpatient physician follow-up care and other practice features, mostly after detection of incident mental disorders (MD), and associated these profiles with patient characteristics and subsequent adverse outcomes. METHODS: A cohort of 170,957 patients age 12 + with a new or recurrent MD detected in 2019-20 was investigated based on data from the Quebec Integrated Chronic Disease Surveillance System. Latent class analysis was performed to identify follow-up care profiles, mostly within one year of MD detection. Bivariate analyses tested associations between profiles and patient characteristics; logistic regressions examined relationships between profiles and adverse outcomes after one year. RESULTS: Five profiles were identified: Profiles 2 and 5 (64%) offered low mental health (MH) outpatient follow-up care, while the others dispensed higher MH follow-up care. Profiles differed in patient characteristics and related outcomes. Labelled "Follow-up care by usual psychiatrist", Profile 1 (1% of sample) included younger patients with the most health and social issues. Profile 2 (50%), "Low MH follow-up care but high prior consultations for physical reasons", mostly integrated older patients with chronic physical illnesses. Profile 3 (11%), "Follow-up care by general practitioners (GP) and psychiatrists", referred to physicians other than the usual ones (e.g., walk-in practice) and encompassed patients with severe MD conditions. Profile 4 (23%), "High follow-up care by usual GP and prior consultations for physical reasons", showed the typical characteristics of patients treated in primary care (more common MD, women, less materially and socially deprived). Profile 5 (15%), "Low MH follow-up care and prior consultations for physical reasons", integrated more younger men, materially deprived patients, and with substance-related disorders (SRD) or co-occurring MD-SRD. More Profile 1 and 3 patients lived in university regions - those of Profile 4 were the least numerous in such regions. More Profile 5 patients lived in metropolitan and rural areas. Risk of death was higher in Profiles 5, 2, 3, and risk of frequent ED use and hospitalization higher in Profiles 1, 3, and 5 - patients with severe health and social issues. CONCLUSION: The study confirmed the need to improve prompt, adequate and continuous follow-up care for patients with incident MD.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.733

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.007
GPT teacher head0.298
Teacher spread0.291 · 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

Citations5
Published2025
Admission routes3
Has abstractyes

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