Congruence of pain assessment between nurses and emergency department patients: A replication

Duignan, Martin; Dunn, Virginia

doi:10.1016/j.ienj.2007.09.003

Cited by 41 publications

(47 citation statements)

References 28 publications

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“…[9,27] Most of the studies comparing nurses' pain assessments with patients' pain ratings confirm that there is underestimation. [8,11,[16][17][18][19][20][21][22][23][24][25] In the present study; it was found that the pain scores given by nurses were significantly lower than patients' pain scores. In addition; the second main purpose of this study was investigating the pain perception of the relatives in the hospital and was found no signifi- …”

Section: Discussionsupporting

confidence: 40%

“…[12] Previous studies show that nurses have tendency to underestimate their patients' pain. [8,11,[16][17][18][19][20][21][22][23][24][25] Underestimation of pain may result with inadequate nursing care and treatment, certain physical and psychological problems and also brings greater annual economic costs. [6,19,26,27] There are many reasons behind the underestimation of pain by nurses.…”

Section: ıNtroductionmentioning

confidence: 99%

“…Data Collecting Form is prepared by the researchers in accordance with the literature [8,11,[16][17][18][19][20][21][22][23][24][25] and includes questions related to demographic characteristics, past hospital experiences, pain beliefs and attitudes.…”

Section: Data Collectingmentioning

confidence: 99%

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Pain Levels of Orthopedic Surgery Patients and Pain Perceptions of Their Relatives and Nurses

Yildirim¹

2015

Agri

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ÖzetAmaç: Bu tanımlayıcı araştırma, ortopedik cerrahi hastalarında ağrının hasta yakını ile hemşire tarafından algılanışının incelenmesi amacıyla gerçekleştirildi. Gereç ve Yöntem: Araştırmanın örneklemini ortopedi kliniğinde yatan 150 hasta, hastaların yanındaki 150 hasta yakını ve hastanın bakımından sorumlu 50 hemşire oluşturdu. Her hemşire araştırmaya yalnızca üç kere katıldı. Ağrı düzeyi, Görsel Analog Skala ile değerlendirildi. Hasta yakını ve hemşirenin, hastanın ağrı skalasını görmemesi sağlandı. Verilerin değerlendiril-mesinde; yüzdelik, ortalama, standart sapma, Mann-Whitney-U, Eşleştirilmiş Örneklem t-Testi, Lineer Regresyon ve Spearman Korelasyon Analizi kullanıldı. Bulgular: Hemşirelerin puan ortalamasının, hastaların puan ortalamasından istatistiksel olarak anlamlı düzeyde düşük olduğu (t=9.136, p<0.001); hasta yakını ile hastanın verdikleri puanlar arasında istatistiksel olarak anlamlı bir fark olmadığı saptandı. Regresyon analizinde; hasta yakınlarının, hastanın verdiği ağrı puanının yaklaşık %40'ını verirken, hemşirelerin %60 kadarını tahmin edebildiği saptandı. Sonuç: Hemşirelerin; ağrının hastadaki fiziksel ve emosyonel yansımalarını yorumlayabilmeleri için, ağrının fizyolojisi hakkın-da bilgilendirilmelerinin yanı sıra empatik becerilerinin geliştirilmesine yönelik eğitimlerin planlanması gereklidir. Bununla birlikte hastayla çokça vakit geçiren hasta yakınının da; cerrahi girişim sonrası hastanın gösterebileceği ağrı davranışları konusunda bilgilendirilmesi önerilmektedir.Anahtar sözcükler: Hemşire; ortopedik cerrahi; ağrı şiddeti; ağrı algısı; hasta yakını. SummaryObjectives: This descriptive study investigated pain levels of orthopedic surgery patients, and how this pain is perceived by their relatives and nurses. Methods: The study was carried out with 150 patients, 150 relatives and 50 nurses to determine pain intensity levels of orthopedic surgery patients and perceptions of this among their relatives and nurses. Intensity of pain was measured on a 0 to 10 visual analogue scale. Relatives and nurses were not allowed to see the patient's pain intensity score, and each nurse was allowed to participate in pain measurement three times. The data were analyzed by descriptive statistics, the Mann Whitney-U test, Paired Sample t-Test, Linear Regression and Spearman Correlation Analysis. results: The pain intensity scores given by nurses (t=9.136, p<0.001) were significantly lower than patients' own scores. There was no significant difference between relatives' and patients' pain scores. In the regression analysis, pain intensity scores given by relatives were approximately 40% lower than those given by patients, while nurses' scores were approximately 60% lower. conclusion: Education on pain management and the physical and emotional reactions of patients to pain should be provided for nurses working in surgical clinics. Meanwhile, as those who spend most time with the patient, relatives should be informed about possible pain behaviors in the postoperative period in order to prepare them for the...

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Section: Discussionsupporting

confidence: 40%

Section: ıNtroductionmentioning

confidence: 99%

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Pain Levels of Orthopedic Surgery Patients and Pain Perceptions of Their Relatives and Nurses

Yildirim¹

2015

Agri

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“…These findings are similar to those reported in the literature demonstrating a discrepancy between children's pain ratings and nurses' perceptions of pain severity in children. [8][9][10]48 Our findings demonstrated a tendency for nurses to underestimate pain relative to children's self-ratings, and this discrepancy was statistically significantly larger for endogenous (ongoing) pain than for the exogenous (transient) pain. The CVML approach presented here, on the other hand, demonstrated no discrepancy for both types of pain.…”

Section: Comparison With Proxy Pain Assessment By Nurses and Parentsmentioning

confidence: 58%

“…[8][9][10][11][12] Observational scales focusing on nonverbal behaviors in response to pain have been developed, 13 but place substantial demands on clinician time, have notable variability in pain cue definitions, 14,15 and are subject to observer bias. [15][16][17][18][19][20][21][22] Similar to pain self-report, observational scales often lack the ability to meaningfully alter pain interventions in a time-sensitive fashion.…”

mentioning

confidence: 99%

Automated Assessment of Children’s Postoperative Pain Using Computer Vision

et al. 2015

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BACKGROUND: Current pain assessment methods in youth are suboptimal and vulnerable to bias and underrecognition of clinical pain. Facial expressions are a sensitive, specific biomarker of the presence and severity of pain, and computer vision (CV) and machine-learning (ML) techniques enable reliable, valid measurement of pain-related facial expressions from video. We developed and evaluated a CVML approach to measure pain-related facial expressions for automated pain assessment in youth. METHODS:A CVML-based model for assessment of pediatric postoperative pain was developed from videos of 50 neurotypical youth 5 to 18 years old in both endogenous/ongoing and exogenous/transient pain conditions after laparoscopic appendectomy. Model accuracy was assessed for self-reported pain ratings in children and time since surgery, and compared with by-proxy parent and nurse estimates of observed pain in youth.RESULTS: Model detection of pain versus no-pain demonstrated good-to-excellent accuracy (Area under the receiver operating characteristic curve 0.84-0.94) in both ongoing and transient pain conditions. Model detection of pain severity demonstrated moderate-to-strong correlations (r = 0.65-0.86 within; r = 0.47-0.61 across subjects) for both pain conditions. The model performed equivalently to nurses but not as well as parents in detecting pain versus no-pain conditions, but performed equivalently to parents in estimating pain severity. Nurses were more likely than the model to underestimate youth self-reported pain ratings. Demographic factors did not affect model performance.CONCLUSIONS: CVML pain assessment models derived from automatic facial expression measurements demonstrated good-to-excellent accuracy in binary pain classifications, strong correlations with patient self-reported pain ratings, and parent-equivalent estimation of children's pain levels over typical pain trajectories in youth after appendectomy. WHAT'S KNOWN ON THIS SUBJECT:Clinical pain assessment methods in youth are vulnerable to underestimation bias and underrecognition. Facial expressions are sensitive, specific biomarkers of the presence and severity of pain. Computer vision-based pattern recognition enables measurement of painrelated facial expressions from video. WHAT THIS STUDY ADDS:This study demonstrates initial validity for developing computer vision algorithms for automated pain assessment in children. The system developed and tested in this study could provide standardized, continuous, and valid patient monitoring that is potentially scalable. Mr Sikka performed the machine learning under the guidance of Dr Bartlett, drafted the initial manuscript, and reviewed and revised the manuscript; Mr Ahmed carried out a portion of the initial analyses and reviewed and revised the manuscript; Dr Diaz performed data collection, performed a portion of the initial analyses, and reviewed and revised the manuscript; Drs Craig and Goodwin reviewed all analyses, and critically reviewed and revised the manuscript; Drs Bartlett and Huang concep...

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