scholarly journals Digital Pain Drawings Can Improve Doctors’ Understanding of Acute Pain Patients: Survey and Pain Drawing Analysis

10.2196/11412 ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. e11412 ◽  
Author(s):  
Nour Shaballout ◽  
Anas Aloumar ◽  
Till-Ansgar Neubert ◽  
Martin Dusch ◽  
Florian Beissner
Keyword(s):  
Acute Pain ◽  
Pain Drawing ◽  
Pain Drawings ◽  
Pain Patients

scholarly journals Figure Correction: Digital Pain Drawings Can Improve Doctors’ Understanding of Acute Pain Patients: Survey and Pain Drawing Analysis (Preprint)

2019 ◽  
Author(s):  
Nour Shaballout ◽  
Anas Aloumar ◽  
Till-Ansgar Neubert ◽  
Martin Dusch ◽  
Florian Beissner
Keyword(s):  
Acute Pain ◽  
Pain Drawing ◽  
Pain Drawings ◽  
Pain Patients

scholarly journals Figure Correction: Digital Pain Drawings Can Improve Doctors’ Understanding of Acute Pain Patients: Survey and Pain Drawing Analysis

10.2196/16017 ◽  
2019 ◽  
Vol 7 (9) ◽  
pp. e16017
Author(s):  
Nour Shaballout ◽  
Anas Aloumar ◽  
Till-Ansgar Neubert ◽  
Martin Dusch ◽  
Florian Beissner
Keyword(s):  
Acute Pain ◽  
Pain Drawing ◽  
Pain Drawings ◽  
Pain Patients

scholarly journals Pain drawing as a screening tool for anxiety, depression and reduced health-related quality of life in back pain patients: A cohort study

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0258329
Author(s):  
Katharina Weßollek ◽  
Ana Kowark ◽  
Michael Czaplik ◽  
Rolf Rossaint ◽  
Pascal Kowark
Keyword(s):  
Quality Of Life ◽  
Back Pain ◽  
Body Surface ◽  
Screening Tool ◽  
Regression Analyses ◽  
Pain Drawing ◽  
Pain Drawings ◽  
Anxiety Depression ◽  
Pain Patients

Background Back pain patients are more likely to suffer from depression, anxiety and reduced quality of life. Pain drawing is a simple, frequently used anamnesis tool that facilitates communication between physicians and patients. This study analysed pain drawings to examine whether pain drawing is suitable as a screening tool for signs of anxiety, depression or reduced quality of life, as the detection of these symptoms is essential for successful treatment. Methods Pain drawings of 219 patients with lower back pain were evaluated retrospectively. Pain drawings are a schematic drawing of a human being. Six variables of the pain drawing were analysed. Subscales of the Hospital Anxiety and Depression Scale (HADS) and the Mental Component Summary (MCS) of the Short Form 12 (SF-12) were used to measure anxiety, depression and quality of life, respectively. Descriptive statistics, uni- and multivariate linear regression analyses and analysis of variance were performed. Logistic regression analyses were conducted for suitable variables. Results We revealed significant positive correlations between the variables "filled body surface" and "number of pain sites" and the anxiety (HADS-A) and depression subscales (HADS-D) of the HADS (p<0.01). The same predictors had significant negative correlations with the MCS (p<0.01). However, the sensitivity and specificity of the variable "number of pain sites" were too low compared to those for existing screening tests to consider it as a screening tool for anxiety, depression and quality of life (HADS-A: sensitivity: 45.2%, specificity: 83.3%; HADS-D: sensitivity: 61.1%, specificity: 51%; MCS: sensitivity: 21.2%, specificity: 85.7%). Conclusions There were significant correlations between the amount of filled body surface and the number of pain sites in the pain drawing and anxiety, depression and quality of life. Although useful in routine clinical practice, pain drawing cannot be used as a screening tool based on our results.

scholarly journals The Effect of Social Observational Learning, Empathy and Catastrophizing in Chronic Pain Patients During Acute Pain Induction

Pain Medicine ◽  
2016 ◽  
pp. pnw186
Author(s):  
Dmitry Y. Yakunchikov ◽  
Camille J. Olechowski ◽  
Mark K. Simmonds ◽  
Michelle J. Verrier ◽  
Saifudin Rashiq ◽  
...  
Keyword(s):  
Chronic Pain ◽  
Acute Pain ◽  
Observational Learning ◽  
Chronic Pain Patients ◽  
Pain Patients

Acute Pain Nursing

2019 ◽  
pp. 609-616
Keyword(s):  
Acute Pain ◽  
Effective Management ◽  
Pain Patients

This chapter defines the importance of nursing in the effective management of acute pain patients.

scholarly journals Computerized quantification of pain drawings

2019 ◽  
Vol 20 (1) ◽  
pp. 175-189
Author(s):  
Søren O’Neill ◽  
Tue Secher Jensen ◽  
Peter Kent
Keyword(s):  
Visual Inspection ◽  
Principal Component ◽  
Visual Assessment ◽  
Spinal Pain ◽  
Correct Choice ◽  
Significant Degree ◽  
Clinical Registry ◽  
Pain Drawing ◽  
Pain Drawings ◽  
Pain Area

AbstractBackground and aimsUsing a computer algorithm to quantify pain drawings could be useful, especially when large numbers of drawings need to be assessed. Whilst informal visual assessment of pain drawings can give clinicians a quick impression of the extent of pain and its location, formal quantification of pain drawings by computer for research purposes is not necessarily trivial. The current study compared seven different approaches to quantification in a large sample of clinical spinal pain drawings.MethodsA large number (n = 55,720) of pain drawings were extracted from the SpineData database, a clinical registry of spinal pain patients in the Region of Southern Denmark. Drawings were analyzed both as pixel (raster) and vector based images, with different approaches based on the raw pain drawing, simple encircling polygons, convex-hull encircling polygons and discrete anatomical regions. Data were analyzed using principal component analysis, correlation and linear regression, as well as informal visual inspection of outlier pain drawings.ResultsEighty-one percent of the variance could be explained by the first principal component, which we interpreted as the true score variance, i.e. the variance attributable to differences in pain area between individuals. The second principal component explained 10% of the variance and was loaded differentially by polygon-based methods and non-polygon-based methods. Correlations between the different approaches ranged from 0.66 to 1.00. Some approaches correlated so strongly as to be interchangeable, others tended to bias area estimates significantly. Visual inspection of outlier pain drawing indicated that when the different approaches to quantification yielded different results, characteristic patterns could be identified in the style and patterns of those pain drawings.ConclusionsThe different approaches reflected the same underlying construct (pain area), but could not be relied upon to produce the same area estimates and were affected by the interaction between drawing style and quantification approach. To some extend, the “correct” choice of quantification method is specific to and dictated by the style of each pain drawing. A differentiated approach is required in which the results of quantification and the drawing style are considered in combination. We provide suggestions for such differentiated approaches taking into account the nature of the drawing data (raster vs. vector) and the method of analysis (partly vs completely automated).ImplicationsThe chosen method of quantifying pain drawings in combination with the drawing style of the individual patient, can impact the resulting area estimate to a significant degree. These issues should be considered before undertaking computerized area estimation of pain drawings.

Postoperative Pain Trajectories in Chronic Pain Patients Undergoing Surgery: The Effects of Chronic Opioid Pharmacotherapy on Acute Pain

2011 ◽  
Vol 12 (12) ◽  
pp. 1240-1246 ◽  
Author(s):  
C. Richard Chapman ◽  
Jennifer Davis ◽  
Gary W. Donaldson ◽  
Justin Naylor ◽  
Daniel Winchester
Keyword(s):  
Chronic Pain ◽  
Postoperative Pain ◽  
Acute Pain ◽  
Chronic Pain Patients ◽  
Pain Trajectories ◽  
Pain Patients
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