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Record W2546481248 · doi:10.1177/084456211404600305

An Integrative Review of the Literature on Pain Management Barriers: Implications for the Canadian Clinical Context

2014· article· en· W2546481248 on OpenAlexaffvenueabout
Mia Ortiz, Eloise Carr, Anastasia Dikareva

Bibliographic record

VenueCanadian Journal of Nursing Research · 2014
Typearticle
Languageen
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCognitive reframingContext (archaeology)Pain managementPsychological interventionThematic analysisHealth careMedicineNursingPsychologyQualitative researchPolitical scienceSociologyPsychotherapistPhysical therapyGeographySocial science

Abstract

fetched live from OpenAlex

Despite decades of pain research, substandard pain management continues to be distressingly prevalent across health-care settings. This integrative literature review analyzes and synthesizes barriers to effective pain management and identifies areas for future investigation in a Canadian context. Three sets of key barriers were identified through thematic analysis of 24 original research studies published in the period 2003-13: patient, professional, and organizational. These barriers rarely occurred in isolation, with many studies reporting examples in all three categories. This suggests that interventions need to reflect the multifactorial nature of pain management. Reframing pain education as a public health initiative could lead to sustainable improvement, as could the strengthening of partnerships between patients and health-care providers. There are tremendous opportunities for the advanced practice nurse to take a lead in pain management. The delivery of high-quality care that encompasses effective pain management strategies must be a priority for nursing. Research approaches, such as pragmatic mixed methods, that offer contextual understanding of how pain is managed are suggested.

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)0.011
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.970
Threshold uncertainty score0.882

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.109
GPT teacher head0.473
Teacher spread0.364 · 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 designNot applicable
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

Citations15
Published2014
Admission routes3
Has abstractyes

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