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Record W4223952377 · doi:10.1186/s12875-022-01694-y

The challenge for general practitioners to keep in touch with vulnerable patients during the COVID-19 lockdown: an observational study in France

2022· article· en· W4223952377 on OpenAlexaff
Tiphanie Bouchez, Sylvain Gautier, Julien Le Breton, Yann Bourgueil, Aline Ramond‐Roquin

Bibliographic record

VenueBMC Primary Care · 2022
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsObservational studyGlobal Positioning SystemMultinomial logistic regressionCoronavirus disease 2019 (COVID-19)MedicineLogistic regressionMultidisciplinary approachService (business)Family medicineNursingPsychologyMarketingComputer scienceBusinessPolitical scienceInternal medicineDisease

Abstract

fetched live from OpenAlex

BACKGROUND: In France, the first COVID-19-related lockdown (17th March to 10th May 2020) resulted in a major decrease in healthcare service utilization. This raised concerns about the continuity of care for vulnerable patients. OBJECTIVES: To identify individual and organizational factors associated with the initiatives taken by French GPs to contact vulnerable patients during the lockdown. METHODS: A national observational survey using an online questionnaire was conducted to document French GPs' adaptations to the COVID-19 situation, their individual and organizational characteristics, including practice type (individual, group, multidisciplinary) and size. Data were collected from 7th to 20th May 2020 using mailing lists of GPs from the study partners and GPs who participated in a previous survey. This paper analysed answers to the question exploring whether and how GPs took initiatives to contact vulnerable patients. Responses were categorized in: no initiative; selection of patients to contact with a criteria-based strategy; initiative of contact without criteria-based strategy. Multivariate multinomial logistic regression identified factors associated with each category. Key components of the reported initiatives were described by inductive analysis of verbatim material. RESULTS: Among the 3012 participant GPs (~ 5.6% of French GPs), 1419 (47.1%) reported initiatives to contact some patients without criteria-based strategy, and 808 (26.8%) with a strategy using various clinical/psychological/social criteria. Women GPs more often declared initiatives of contacts with a criteria-based strategy (OR = 1.41, 95% CI [1.14-1.75]) as well as GPs with more than two patients who died due to COVID-19 in comparison with those having none (OR = 1.84, 95% CI [1.43-2.36]). Teaching GPs more often used criteria-based strategies than the other GPs (OR = 1.94, 95% CI [1.51-2.48]). Compared with those working in small monodisciplinary practice, GPs working alone were less likely to implement criteria-based initiatives of contacts (OR = 0.70, 95% CI [0.51-0.97]), while GPs working in multidisciplinary practice were more likely (OR = 1.94, 95% CI [1.26-2.98] in practices > 20 professionals). CONCLUSION: French GPs took various initiatives to keep in touch with vulnerable patients, more frequently when working in group practices. These findings confirm the importance of primary care organization to ensure continuity of care for vulnerable people.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.097
Threshold uncertainty score0.193

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.133
GPT teacher head0.413
Teacher spread0.280 · 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 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

Citations19
Published2022
Admission routes1
Has abstractyes

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