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Enregistrement W355090155 · doi:10.1155/2007/571598

Pain in Older Persons

2007· article· en· W355090155 sur OpenAlexaffabout
Thomas Hadjistavropoulos

Notice bibliographique

RevuePain Research and Management · 2007
Typearticle
Langueen
DomaineMedicine
ThématiquePain Management and Opioid Use
Établissements canadiensUniversity of Regina
Organismes subventionnairesnon disponible
Mots-clésMedicinePsychologyMEDLINEGerontologyPhysical medicine and rehabilitationPhysical therapyPsychiatryBiology

Résumé

récupéré en direct d'OpenAlex

It gave me great pleasure to accept the invitation to serve as guest editor for this special issue, which recognizes the International Association for the Study of Pain (IASP) Global Year Against Pain in Older Persons. In 2001, I had the pleasure of guest editing another special issue of Pain Research & Management on Pain and Aging. My 2001 editorial (1) recognized the increasing interest that researchers and clinicians were showing in the topic of pain in older adults, and pointed out as evidence of that interest the efforts to create an IASP Special Interest Group on Pain in Older Persons, the publication of several related volumes (2–4) and the United States Joint Commission on Accreditation of Health Care Organisations guidelines for assessing geriatric pain (5). We have come such a long way in the six years that have passed since the 2001 special issue. The IASP Special Interest Group on Pain in Older Persons is now well established and the IASP has named 2006/2007 as its Global Year Against Pain in Older Adults. In addition, specialized and up-to-date volumes on the topic continue to be published (6,7) and tremendous progress has been made in both the areas of pain assessment (6,8–10) and management (6). The present issue of Pain Research & Management is well balanced. The contributing authors represent a variety of clinical and research disciplines (eg, nursing, medicine and clinical psychology). Two of the four original papers (11,12) are empirical while the other two (13,14) are systematic literature reviews. Two papers focus primarily on older adults residing in long-term care facilities (11,13), one paper focuses on palliative care (14) and one on seniors undergoing total knee arthroplasty (12). This special issue also includes a review of the book Clinical Management of the Elderly Patient in Pain (7). The review was prepared by Romayne Gallagher. Last but not least, Laurence Jerome contributed a case study of an older woman with a 20-year history of vulvodynia (15). The paper by Lucia Gagliese and colleagues (14) helps clarify some of the questions that exist concerning age-related patterns in the relationship between cancer pain and depression. The study by Maya Roth et al (12) helps fill a gap in the literature by examining some of the psychosocial determinants of acute postoperative total knee arthroplasty pain among seniors. In the area of long-term care, the investigation by Sandra Zwakhalen and colleagues (11) provides evidence of knowledge gaps among nursing staff. Such knowledge gaps often relate to insufficient information about assessment tools that have been specifically designed for older persons who have limited ability to communicate due to dementia (16). Systematic information comparing such specialized assessment tools is needed not only by clinicians but also by researchers. Information allowing comparisons across pain assessment tools for patients with dementia is provided by Michele Aubin and colleagues (13). The Aubin et al article also marks an important milestone for the Journal because it is written in French. Although Pain Research & Management has the mandate to publish papers in both French and English, this is the first time that a paper in French has been published. I thank the Editor-in-Chief of Pain Research & Management, Dr Kenneth D Craig, for encouraging this initiative. I extend thanks to all contributors for their important work in this area, and for sharing their findings and ideas with the 18,000 readers of Pain Research & Management (the journal of the Canadian Pain Society). I also extend my thanks to Kenneth D Craig for the opportunity to guest edit this special issue.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,024
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,428
Score d'incertitude au seuil0,826

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0240,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,050
Tête enseignante GPT0,370
Écart entre enseignants0,320 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations8
Publié2007
Routes d'admission2
Résumé présentoui

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