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Record W2129120650 · doi:10.1177/0969733010378932

Unresolved pain in children: A relational ethics perspective

2010· article· en· W2129120650 on OpenAlexafffund
Deborah Olmstead, Shannon D. Scott, Wendy Austin

Bibliographic record

VenueNursing Ethics · 2010
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsPerspective (graphical)Pain managementPsychologyEmpirical evidenceMedicineNursingPhysical therapy

Abstract

fetched live from OpenAlex

It is considered the right of children to have their pain managed effectively. Yet, despite extensive research findings, policy guidelines and practice standard recommendations for the optimal management of paediatric pain, clinical practices remain inadequate. Empirical evidence definitively shows that unrelieved pain in children has only harmful consequences, with no benefits. Contributing factors identified in this undermanaged pain include the significant role of nurses. Nursing attitudes and beliefs about children's pain experiences, the relationships nurses share with children who are suffering, and knowledge deficits in pain management practices are all shown to impact unresolved pain in children. In this article, a relational ethics perspective is used to explore the need for nurses to engage in authentic relationships with children who are experiencing pain, and to use evidence-based practices to manage that pain in order for this indefensible suffering of children to end.

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)0.009
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.036
Scholarly communication0.0070.006
Open science0.0010.005
Research integrity0.0040.008
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 head0.075
GPT teacher head0.396
Teacher spread0.321 · 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 designTheoretical or conceptual
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

Citations47
Published2010
Admission routes2
Has abstractyes

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