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Record W203905660 · doi:10.1155/2015/501616

Gestion de la douleur chronique par les infirmières des Groupes de médecine de famille

2015· article· en· W203905660 on OpenAlexaffabout
Dave A. Bergeron, Patricia Bourgault, Frances Gallagher

Bibliographic record

VenuePain Research and Management · 2015
Typearticle
Languageen
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsUniversité du Québec à RimouskiUniversité de Sherbrooke
Fundersnot available
KeywordsPain managementNursingPsychological interventionMedicineFamily medicineChronic painDescriptive researchPopulationPsychologyPsychiatryPhysical therapy

Abstract

fetched live from OpenAlex

INTRODUCTION: Thousands of people treated in primary care are currently experiencing chronic pain (CP), for which management is often inadequate. In Quebec, nurses in family medicine groups (FMGs) play a key role in the management of chronic health problems. OBJECTIVE: The present study aimed to describe the activities performed by FMG nurses in relation to CP management and to describe barriers to those activities. METHOD: A descriptive correlational cross-sectional postal survey was used. The accessible population includes FMG nurses on the Ordre des infirmières et infirmiers du Québec list. All nurses on the list who provided consent to be contacted at home for research purposes were contacted. A self-administered postal questionnaire (Pain Management Activities Questionnaire) was completed by 53 FMG nurses. RESULTS: Three activities most often performed by nurses were to establish a therapeutic relationship with the client; discuss the effectiveness of therapeutic measures with the physician; and conduct personalized teaching for the patient. The average number of individuals seen by interviewed nurses that they believe suffer from CP was 2.68 per week. The lack of knowledge of possible interventions in pain management (71.7%) and the nonavailability of information on pain management (52.8%) are the main barriers perceived by FMG nurses. CONCLUSION: FMG nurses are currently performing few activities in CP management. The nonrecognition of CP may explain this situation.

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)0.012
metaresearch head score (Gemma)0.001
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 score0.097
Threshold uncertainty score0.473

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
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 head0.073
GPT teacher head0.368
Teacher spread0.295 · 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

Citations11
Published2015
Admission routes2
Has abstractyes

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