Needle and dread: Is it just a little poke? A call for implementation of evidence-based policies for the management of needle pain in clinical settings
Bibliographic record
Abstract
The present commentary calls for the implementation of evidence-based policies to manage paediatric needle pain in clinical settings. While there have been fundamental advances in the treatment of needle pain over the past three decades, relevant techniques are often not used in clinical practice. Evidence indicates that needle procedures do hurt, are frequently cited as the most painful experience by children and a subset of children are terrified of them. Pain and distress from needle procedures can and must be addressed because needle procedures are frequently performed on both healthy (eg, immunizations) and ill (eg, bone marrow aspirations, lumbar punctures) children. An essential step in translating research knowledge into practice is the creation of evidence-based policies. Policy statements regarding the management of needle pain must be incorporated at the hospital, clinic and individual office levels to reduce the amount of pain and distress children suffer from needle procedures. Specific suggestions for policies to be incorporated in clinical settings are provided. Le présent commentaire prône l'implantation de politiques probantes pour prendre en charge la douleur causée par une aiguille chez les enfants en milieu clinique. On a réalisé des avancées fondamentales dans le traitement de la douleur causée par les aiguilles depuis trente ans, mais on omet souvent d'utiliser les techniques pertinentes en pratique clinique. D'après les données probantes, les interventions à l'aiguille font mal; les enfants les citent souvent comme leur pire expérience de douleur, et un sous-groupe d'enfants en est terrifié. Il est possible et nécessaire de se pencher sur la douleur et la détresse que provoquent les interventions à l'aiguille, car on les pratique souvent à la fois chez des enfants en santé (p. ex., vaccins) et chez des enfants malades (p. ex., aspiration de la moelle osseuse, ponctions lombaires). La création de politiques probantes constitue une étape préparatoire essentielle pour transmettre les connaissances de recherche en pratique. Il faut intégrer des documents de principes sur la prise en charge de la douleur causée par les aiguilles en milieu hospitalier, en clinique et au cabinet des médecins pour réduire la douleur et la détresse que ressentent les enfants à cet égard. On propose des suggestions de politiques à adopter en milieu clinique.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.101 | 0.313 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.028 |
| Scholarly communication | 0.014 | 0.020 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.066 | 0.071 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".