From Paper to Digital Applications of the Pain Drawing: Systematic Review of Methodological Milestones

Exploring Chronic Pain Patterns and Associations With All-Cause Dementia: Results From UK Biobank

The count of locations with chronic pain is widely used in research and clinical practice. However, this approach might be too simplistic to fully capture the complexity of chronic pain experiences. This study identified prevalent patterns of chronic pain locations and evaluated their associations with incident dementia among middle-aged and older adults in the UK. Data were from 445,530 participants who were free of dementia at baseline (2006-2010) in the UK Biobank. We calculated the incidence rates of all-cause dementia by the 20 most prevalent combinations of pain locations assessed at baseline. Cox models were utilized to examine the hazard ratio of incident dementia among each of these 20 combinations compared to 3 groups: 1) participants without chronic pain, 2) participants with only a single chronic pain location not included in the combination, and 3) participants with only a single chronic pain location included in the combination. The 3 most prevalent combinations were neck and back (5.7%), back and knee (5.4%), and neck and knee (4.5%). Chronic back, neck, and knee pain was commonly present either individually or simultaneously in combinations associated with higher dementia rates than persons without chronic pain. The combinations involving back, neck, and knee were associated with higher dementia rates than groups with 1 pain location not included in the combination. Chronic pain is not randomly present in body locations. Understanding how different patterns of chronic pain locations relate to dementia provides new insights into dementia prevention through pain relief. PERSPECTIVE: This article unveils chronic pain patterns and dementia risks in the UK Biobank. Chronic pain in back, neck, and knee presents frequently, either individually or in combinations associated with increased dementia rates. Chronic pain combos correlate with diverse dementia rates, guiding targeted prevention strategies through pain management.

The use of abstract animations and a graphical body image for assessing pain outcomes among adults with sickle cell disease

Painimation, a novel digital pain assessment tool, allows patients to communicate their pain quality, intensity, and location using abstract animations and a paintable body image. This study determined the construct validity of pain animations and body image measures by testing correlations with validated pain outcomes in adults with sickle cell disease (SCD). Analyses used baseline data from a multisite randomized trial of 359 adults with SCD and chronic pain. Participants completed questionnaires on demographics, pain severity, frequency and interference, catastrophizing, opioid use, mood and quality of life, plus the Painimation app. Participants were categorized by selected pain animations, and were split into groups based on the proportion of painted body image. The "shooting" pain animation and greater body image scores associated with poorer pain outcomes in univariate analyses, except "happy" mood days. Potential confounding was evaluated by age, gender, race, education, disability, site, depression, and anxiety. Only depression scores significantly covaried in multivariate models, accounting for the effect of greater body image score and shooting animation on all outcomes except daily pain intensity. Both pain animations and body image measures correlated with validated pain outcomes, quality of life and mental health measures. This demonstrates animations and body image data can assess SCD pain severity, potentially with more accuracy than a 0-10 scale. In exploratory analyses, depression scores accounted for the association between Painimation and other pain outcomes. Future research will explore whether Painimation can differentiate biological and psychosocial pain components. PERSPECTIVE: This article presents the preliminary construct validity of Painimation in sickle cell disease (SCD) by examining the associations of "pain animations" and body area image data with daily e-diary and traditional self-report pain outcomes.

Data-driven identification of distinct pain drawing patterns and their association with clinical and psychological factors: a study of 21,123 patients with spinal pain

ABSTRACT

The variability in pain drawing styles and analysis methods has raised concerns about the reliability of pain drawings as a screening tool for nonpain symptoms. In this study, a data-driven approach to pain drawing analysis has been used to enhance the reliability. The aim was to identify distinct clusters of pain patterns by using latent class analysis (LCA) on 46 predefined anatomical areas of a freehand digital pain drawing. Clusters were described in the clinical domains of activity limitation, pain intensity, and psychological factors. A total of 21,123 individuals were included from 2 subgroups by primary pain complaint (low back pain (LBP) [n = 15,465]) or midback/neck pain (MBPNP) [n = 5658]). Five clusters were identified for the LBP subgroup: LBP and radiating pain (19.9%), radiating pain (25.8%), local LBP (24.8%), LBP and whole leg pain (18.7%), and widespread pain (10.8%). Four clusters were identified for the MBPNP subgroup: MBPNP bilateral posterior (19.9%), MBPNP unilateral posterior + anterior (23.6%), MBPNP unilateral posterior (45.4%), and widespread pain (11.1%). The clusters derived by LCA corresponded to common, specific, and recognizable clinical presentations. Statistically significant differences were found between these clusters in every self-reported health domain. Similarly, for both LBP and MBPNP, pain drawings involving more extensive pain areas were associated with higher activity limitation, more intense pain, and more psychological distress. This study presents a versatile data-driven approach for analyzing pain drawings to assist in managing spinal pain.

Automated Pain Spots Recognition Algorithm Provided by a Web Service-Based Platform: Instrument Validation Study

Background

Understanding the causes and mechanisms underlying musculoskeletal pain is crucial for developing effective treatments and improving patient outcomes. Self-report measures, such as the Pain Drawing Scale, involve individuals rating their level of pain on a scale. In this technique, individuals color the area where they experience pain, and the resulting picture is rated based on the depicted pain intensity. Analyzing pain drawings (PDs) typically involves measuring the size of the pain region. There are several studies focusing on assessing the clinical use of PDs, and now, with the introduction of digital PDs, the usability and reliability of these platforms need validation. Comparative studies between traditional and digital PDs have shown good agreement and reliability. The evolution of PD acquisition over the last 2 decades mirrors the commercialization of digital technologies. However, the pen-on-paper approach seems to be more accepted by patients, but there is currently no standardized method for scanning PDs.

Objective

The objective of this study was to evaluate the accuracy of PD analysis performed by a web platform using various digital scanners. The primary goal was to demonstrate that simple and affordable mobile devices can be used to acquire PDs without losing important information.

Methods

Two sets of PDs were generated: one with the addition of 216 colored circles and another composed of various red shapes distributed randomly on a frontal view body chart of an adult male. These drawings were then printed in color on A4 sheets, including QR codes at the corners in order to allow automatic alignment, and subsequently scanned using different devices and apps. The scanners used were flatbed scanners of different sizes and prices (professional, portable flatbed, and home printer or scanner), smartphones with varying price ranges, and 6 virtual scanner apps. The acquisitions were made under normal light conditions by the same operator.

Results

High-saturation colors, such as red, cyan, magenta, and yellow, were accurately identified by all devices. The percentage error for small, medium, and large pain spots was consistently below 20% for all devices, with smaller values associated with larger areas. In addition, a significant negative correlation was observed between the percentage of error and spot size (R=-0.237; P=.04). The proposed platform proved to be robust and reliable for acquiring paper PDs via a wide range of scanning devices.

Conclusions

This study demonstrates that a web platform can accurately analyze PDs acquired through various digital scanners. The findings support the use of simple and cost-effective mobile devices for PD acquisition without compromising the quality of data. Standardizing the scanning process using the proposed platform can contribute to more efficient and consistent PD analysis in clinical and research settings.

Encoding contact size using static and dynamic electrotactile finger stimulation: natural decoding vs. trained cues

Electrotactile stimulation through matrix electrodes is a promising technology to restore high-resolution tactile feedback in extended reality applications. One of the fundamental tactile effects that should be simulated is the change in the size of the contact between the finger and a virtual object. The present study investigated how participants perceive the increase of stimulation area when stimulating the index finger using static or dynamic (moving) stimuli produced by activating 1 to 6 electrode pads. To assess the ability to interpret the stimulation from the natural cues (natural decoding), without any prior training, the participants were instructed to draw the size of the stimulated area and identify the size difference when comparing two consecutive stimulations. To investigate if other "non-natural" cues can improve the size estimation, the participants were asked to enumerate the number of active pads following a training protocol. The results demonstrated that participants could perceive the change in size without prior training (e.g., the estimated area correlated with the stimulated area, p < 0.001; ≥ two-pad difference recognized with > 80% success rate). However, natural decoding was also challenging, as the response area changed gradually and sometimes in complex patterns when increasing the number of active pads (e.g., four extra pads needed for the statistically significant difference). Nevertheless, by training the participants to utilize additional cues the limitations of natural perception could be compensated. After the training, the mismatch in the activated and estimated number of pads was less than one pad regardless of the stimulus size. Finally, introducing the movement of the stimulus substantially improved discrimination (e.g., 100% median success rate to recognize ≥ one-pad difference). The present study, therefore, provides insights into stimulation size perception, and practical guidelines on how to modulate pad activation to change the perceived size in static and dynamic scenarios.

[Short paths to diagnosis with artificial intelligence: systematic literature review on diagnostic decision support systems]

BACKGROUND

Rare diseases are often recognized late. Their diagnosis is particularly challenging due to the diversity, complexity and heterogeneity of clinical symptoms. Computer-aided diagnostic aids, often referred to as diagnostic decision support systems (DDSS), are promising tools for shortening the time to diagnosis. Despite initial positive evaluations, DDSS are not yet widely used, partly due to a lack of integration with existing clinical or practice information systems.

OBJECTIVE

This article provides an insight into currently existing diagnostic support systems that function without access to electronic patient records and only require information that is easily obtainable.

MATERIALS AND METHODS

A systematic literature search identified eight articles on DDSS that can assist in the diagnosis of rare diseases with no need for access to electronic patient records or other information systems in practices and hospitals. The main advantages and disadvantages of the identified rare disease diagnostic support systems were extracted and summarized.

RESULTS

Symptom checkers and DDSS based on portrait photos and pain drawings already exist. The degree of maturity of these applications varies.

CONCLUSION

DDSS currently still face a number of challenges, such as concerns about data protection and accuracy, and acceptance and awareness continue to be rather low. On the other hand, there is great potential for faster diagnosis, especially for rare diseases, which are easily overlooked due to their large number and the low awareness of them. The use of DDSS should therefore be carefully considered by doctors on a case-by-case basis.

Reliability of the Pen-on-Paper Pain Drawing Analysis Using Different Scanning Procedures

INTRODUCTION

Pen-on-paper pain drawing are an easily administered self-reported measure that enables patients to report the spatial distribution of their pain. The digitalization of pain drawings has facilitated the extraction of quantitative metrics, such as pain extent and location. This study aimed to assess the reliability of pen-on-paper pain drawing analysis conducted by an automated pain-spot recognition algorithm using various scanning procedures.

METHODS

One hundred pain drawings, completed by patients experiencing somatic pain, were repeatedly scanned using diverse technologies and devices. Seven datasets were created, enabling reliability assessments including inter-device, inter-scanner, inter-mobile, inter-software, intra- and inter-operator. Subsequently, the automated pain-spot recognition algorithm estimated pain extent and location values for each digitized pain drawing. The relative reliability of pain extent analysis was determined using the intraclass correlation coefficient, while absolute reliability was evaluated through the standard error of measurement and minimum detectable change. The reliability of pain location analysis was computed using the Jaccard similarity index.

RESULTS

The reliability analysis of pain extent consistently yielded intraclass correlation coefficient values above 0.90 for all scanning procedures, with standard error of measurement ranging from 0.03% to 0.13% and minimum detectable change from 0.08% to 0.38%. The mean Jaccard index scores across all dataset comparisons exceeded 0.90.

CONCLUSIONS

The analysis of pen-on-paper pain drawings demonstrated excellent reliability, suggesting that the automated pain-spot recognition algorithm is unaffected by scanning procedures. These findings support the algorithm's applicability in both research and clinical practice.

Sex-specific differences in pain localization in female patients with endometriosis: A comparison of sexless and female human body outlines

BACKGROUND

This study explores sex-specific differences in pain localization using pain drawings in female patients with endometriosis. Traditional human body outlines (HBOs) used for pain drawings are often viewed as male, making accurate pain assessment difficult. The study aims to compare pain localization and extent between patients presented with sexless and female HBOs.

METHODS

A total of 49 female patients with endometriosis completed questionnaires and pain drawings (n = 24 and n = 26 with individually designed sexless and female HBOs, respectively). The Ruzika similarity index was used to investigate potential differences in pain drawings between sexless and female HBOs. Hypothesis testing was applied to compare the number of pixels marked in the pain extents and to investigate the suitability of the presented body outline.

RESULTS

Sex of HBOs used in pain drawings had no effect on pain area, and no statistically significant differences were found in pain localization or area between female and sexless outlines. Most, but not all participants found the body outlines suitable.

CONCLUSIONS

The findings suggest that differences in the resulting areas marked in the pain drawings were negligible and the preferences for sexless pain drawings were not significant, so that a sexless body outline for pain drawings could be a good choice, especially when a study does not focus on one specific sex.

Quantification of Patient-Reported Pain Locations: Development of an Automated Measurement Method

Patient-reported pain locations are critical for comprehensive pain assessment. Our study aim was to introduce an automated process for measuring the location and distribution of pain collected during a routine outpatient clinic visit. In a cross-sectional study, 116 adults with sickle cell disease-associated pain completed PAIN Report It Ⓡ . This computer-based instrument includes a two-dimensional, digital body outline on which patients mark their pain location. Using the ImageJ software, we calculated the percentage of the body surface area marked as painful and summarized data with descriptive statistics and a pain frequency map. The painful body areas most frequently marked were the left leg-front (73%), right leg-front (72%), upper back (72%), and lower back (70%). The frequency of pain marks in each of the 48 body segments ranged from 3 to 79 (mean, 33.2 ± 21.9). The mean percentage of painful body surface area per segment was 10.8% ± 7.5% (ranging from 1.3% to 33.1%). Patient-reported pain locations can be easily analyzed from digital drawings using an algorithm created via the free ImageJ software. This method may enhance comprehensive pain assessment, facilitating research and personalized care over time for patients with various pain conditions.

A diagnostic support system based on pain drawings: binary and k-disease classification of EDS, GBS, FSHD, PROMM, and a control group with Pain2D

BACKGROUND AND OBJECTIVE

The diagnosis of rare diseases (RDs) is often challenging due to their rarity, variability and the high number of individual RDs, resulting in a delay in diagnosis with adverse effects for patients and healthcare systems. The development of computer assisted diagnostic decision support systems could help to improve these problems by supporting differential diagnosis and by prompting physicians to initiate the right diagnostic tests. Towards this end, we developed, trained and tested a machine learning model implemented as part of the software called Pain2D to classify four rare diseases (EDS, GBS, FSHD and PROMM), as well as a control group of unspecific chronic pain, from pen-and-paper pain drawings filled in by patients.

METHODS

Pain drawings (PDs) were collected from patients suffering from one of the four RDs, or from unspecific chronic pain. The latter PDs were used as an outgroup in order to test how Pain2D handles more common pain causes. A total of 262 (59 EDS, 29 GBS, 35 FSHD, 89 PROMM, 50 unspecific chronic pain) PDs were collected and used to generate disease specific pain profiles. PDs were then classified by Pain2D in a leave-one-out-cross-validation approach.

RESULTS

Pain2D was able to classify the four rare diseases with an accuracy of 61-77% with its binary classifier. EDS, GBS and FSHD were classified correctly by the Pain2D k-disease classifier with sensitivities between 63 and 86% and specificities between 81 and 89%. For PROMM, the k-disease classifier achieved a sensitivity of 51% and specificity of 90%.

CONCLUSIONS

Pain2D is a scalable, open-source tool that could potentially be trained for all diseases presenting with pain.

Anterior Electronic Hip Pain Drawings Are Helpful for Diagnosis of Intra-articular Sources of Pain: Lateral or Posterior Drawings Are Unreliable

Purpose

The purpose of this study was to determine the accuracy of electronic hip pain drawing to diagnose intra-articular source of pain in nonarthritic hips, defined by response to an intra-articular injection.

Methods

A retrospective assessment was performed in consecutive patients who had an intra-articular injection completed within a 1-year period. Patients were classified as responders or nonresponders to intra-articular hip injection. A positive injection was defined as greater than 50% hip pain relief within 2 hours after injection. Electronic pain drawings collected before injection were then evaluated according to the hip region marked by the patients.

Results

Eighty-three patients were studied after applying inclusion and exclusion criteria. Anterior hip pain on drawing had a sensitivity of 0.69, specificity of 0.68, positive predictive value (PPV) of 0.86, and negative predictive value (NPV) of 0.44 for intraarticular source of pain. Posterior hip pain on drawing had a sensitivity of 0.59, specificity of 0.23, PPV of 0.68, and NPV of 0.17 for intra-articular source of pain. Lateral hip pain on drawing had a sensitivity of 0.62, specificity of 0.50, PPV of 0.78, and NPV of 0.32 for intraarticular source of pain.

Conclusion

Anterior hip pain on electronic drawing has a sensitivity of 0.69 and specificity of 0.68 for intra-articular source of pain in nonarthritic hips. Lateral and posterior hip pain on electronic pain drawings are not reliable to rule out intra-articular hip disease.

Level of Evidence

Level III, case-control study.

Visualizing and quantifying spatial and qualitative pain sensations

Similar to the purpose of an infographic, visualizing spatial and qualitative sensations on a body chart is a fast and digestible method for communicating complex information and experiences. Further, digitizing these body charts into an interactive medium creates unprecedented opportunities for collecting extensive data. Moreover, applying simple rule-based algorithms or more advanced machine learning approaches to these charts catapults the quantification and spatiotemporal relations of pain and qualitative pain sensations into a new field ripe for pioneering discoveries.

‘Painting my pain’: the use of pain drawings to assess multisite pain in women with primary dysmenorrhea

Background

To verify the use of pain drawing to assess multisite pain in with primary dysmenorrhea (PD) and to assess its divergent validity, test–retest reliability, intra- and inter-rater reliability and measurement errors.

Methods

Cross-sectional study. Adult women with self-reported PD three months prior to the study. Women answered the Numerical Rating Scale (NRS) and the pain drawing during two consecutive menstruations. The pain drawings were digitalized and assessed for the calculation of total pain area (%). Intra- and inter-rater reliability and the test–retest reliability between the first and the second menstruations were assessed with the intraclass correlation coefficient (ICC). Measurement errors were calculated with the standard error of measurement (SEM), smallest detectable change (SDC) and the Bland–Altman plot. Spearman correlation (rho) was used to check the correlation between the total pain area and pain intensity of the two menstruations.

Results

Fifty-six women (24.1 ± 3.1 years old) participated of the study. Their average pain was 6.2 points and they presented pain in the abdomen (100%), low back (78.6%), head (55.4%) and lower limbs (50%). All reliability measures were considered excellent (ICC > 0.75) for the total pain area; test–retest SEM and SDC were 5.7% and 15.7%, respectively. Inter-rater SEM and SDC were 8% and 22.1%, respectively. Correlation between total pain area and pain intensity was moderate in the first (rho = 0.30; p = 0.021) and in the second menstruations (rho = 0.40; p = 0.002).

Conclusion

Women with PD presented multisite pain, which could be assessed with the pain drawing, considered a reliable measurement.

The Significance of Pain Drawing as a Screening Tool for Cervicogenic Headache and Associated Symptoms in Chronic Fatigue

Purpose

Patients with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) present with a broad spectrum of symptoms, including headache. A simple, yet powerful tool – the pain drawing identifies essential aspects such as pain distribution. The aim with this study was to 1) evaluate the significance of pain drawing as a screening tool for cervicogenic headache using a predefined C2 pain pattern, 2) assess whether there was an association between dizziness/imbalance and a C2 pain pattern, and 3) compare subgroups according to the pain drawing with respect to pain characteristics and quality of life.

Patients and Methods

Pain drawings and clinical data from 275 patients investigated for ME/CFS were stratified into: 1) cervicogenic headache as determined by a C2 pain pattern, 2) headache with no C2 pain pattern, and 3) no headache. For inference logistic regression presented with odds ratios (OR) and 95% confidence intervals (95% CI) and Kruskal–Wallis test were applied.

Results

One hundred sixteen participants (42%) were stratified to the group for which the pain drawing corresponded to the C2 pain pattern, thus indicating putative cervicogenic origin of the headache. Dizziness/imbalance was strongly associated with a C2 pain pattern; OR 6.50 ([95% CI 2.42–17.40] p ˂ 0.00), whereas this association was non-significant for patients with headache and no C2 pain pattern. Those demonstrating a C2 pain pattern reported significantly higher pain intensity (p = 0.00) and greater pain extent (p = 0.00) than the other groups, and lower health-related quality of life (p = 0.00) than the group with no headache.

Conclusion

For patients with chronic fatigue who present with a C2 pain pattern (interpreted as cervicogenic headache) the pain drawing seems applicable as a screening tool for signs associated with neuropathic and more severe pain, dizziness and reduced quality of life as detection of these symptoms is essential for targeted treatment.

Quantification of Digital Body Maps for Pain: Development and Application of an Algorithm for Generating Pain Frequency Maps

BACKGROUND

Pain is an unpleasant sensation that signals potential or actual bodily injury. The locations of bodily pain can be communicated and recorded by freehand drawing on 2D or 3D (manikin) surface maps. Freehand pain drawings are often part of validated pain questionnaires (eg, the Brief Pain Inventory) and use 2D templates with undemarcated body outlines. The simultaneous analysis of drawings allows the generation of pain frequency maps that are clinically useful for identifying areas of common pain in a disease. The grid-based approach (dividing a template into cells) allows easy generation of pain frequency maps, but the grid's granularity influences data capture accuracy and end-user usability. The grid-free templates circumvent the problem related to grid creation and selection and provide an unbiased basis for drawings that most resemble paper drawings. However, the precise capture of drawn areas poses considerable challenges in producing pain frequency maps. While web-based applications and mobile-based apps for freehand digital drawings are widely available, tools for generating pain frequency maps from grid-free drawings are lacking.

OBJECTIVE

We sought to provide an algorithm that can process any number of freehand drawings on any grid-free 2D body template to generate a pain frequency map. We envisage the use of the algorithm in clinical or research settings to facilitate fine-grain comparisons of human pain anatomy between disease diagnosis or disorders or as an outcome metric to guide monitoring or discovery of treatments.

METHODS

We designed a web-based tool to capture freehand pain drawings using a grid-free 2D body template. Each drawing consisted of overlapping rectangles (Scalable Vector Graphics <rect> elements) created by scribbling in the same area of the body template. An algorithm was developed and implemented in Python to compute the overlap of rectangles and generate a pain frequency map. The utility of the algorithm was demonstrated on drawings obtained from 2 clinical data sets, one of which was a clinical drug trial (ISRCTN68734605). We also used simulated data sets of overlapping rectangles to evaluate the performance of the algorithm.

RESULTS

The algorithm produced nonoverlapping rectangles representing unique locations on the body template. Each rectangle carries an overlap frequency that denotes the number of participants with pain at that location. When transformed into an HTML file, the output is feasibly rendered as a pain frequency map on web browsers. The layout (vertical-horizontal) of the output rectangles can be specified based on the dimensions of the body regions. The output can also be exported to a CSV file for further analysis.

CONCLUSIONS

Although further validation in much larger clinical data sets is required, the algorithm in its current form allows for the generation of pain frequency maps from any number of freehand drawings on any 2D body template.

Assessing Pain Research: A Narrative Review of Emerging Pain Methods, Their Technosocial Implications, and Opportunities for Multidisciplinary Approaches

Pain research traverses many disciplines and methodologies. Yet, despite our understanding and field-wide acceptance of the multifactorial essence of pain as a sensory perception, emotional experience, and biopsychosocial condition, pain scientists and practitioners often remain siloed within their domain expertise and associated techniques. The context in which the field finds itself today-with increasing reliance on digital technologies, an on-going pandemic, and continued disparities in pain care-requires new collaborations and different approaches to measuring pain. Here, we review the state-of-the-art in human pain research, summarizing emerging practices and cutting-edge techniques across multiple methods and technologies. For each, we outline foreseeable technosocial considerations, reflecting on implications for standards of care, pain management, research, and societal impact. Through overviewing alternative data sources and varied ways of measuring pain and by reflecting on the concerns, limitations, and challenges facing the field, we hope to create critical dialogues, inspire more collaborations, and foster new ideas for future pain research methods.

Associations between Patient Report of Pain and Intervertebral Foramina Changes Visible on Axial-Loaded Lumbar Magnetic Resonance Imaging

The intervertebral foramen may influence spinal nerve roots and, therefore, be related to the corresponding dermatomal pain. In vivo evaluation of the intervertebral foramen–dermatome relationship is essential for understanding low back pain (LBP) pathophysiology. The study aimed to correlate the lumbar MRI unloaded-loaded foraminal area changes with dermatomal pain in the patient’s pain drawings. Dynamic changes of the dermatomal pain distribution related to the intervertebral foramen area changes between quantitative conventional supine MRI (unloaded MRI) and axial-loading MRI (alMRI) were analyzed. The MRI axial-loading intervertebral foramen area changes were observed, and the most significant effect of reducing the foraminal area (−6.9%) was reported at levels of L2–L3. The incidence of pain in the dermatomes increases linearly with the spine level, from 15.6% at L1 to 63.3% at L5 on the right and from 18.9% at L1 to 76.7% at L5 on the left. No statistically significant effect of changes in the intervertebral foramen area on the odds of pain along the respective dermatomes was confirmed. Changes in the foraminal area were observed between the unloaded and loaded phases, but differences in area changes between foramen assigned to painful dermatomes and foramen assigned to non-painful dermatomes were not significant.

Spatiotemporal patterns of pain distribution and recall accuracy: a dose-response study

OBJECTIVES

Clinical decisions rely on a patient's ability to recall and report their pain experience. Monitoring pain in real-time (momentary pain) may reduce recall errors and optimize the clinical decision-making process. Tracking momentary pain can provide insights into detailed changes in pain intensity and distribution (area and location) over time. The primary aims of this study were (i) to measure the temporal changes of pain intensity, area, and location in a dose-response fashion and (ii) to assess recall accuracy of the peak pain intensity and distribution seven days later, using a digital pain mapping application. The secondary aims were to (i) evaluate the influence of repeated momentary pain drawings on pain recall accuracy and (ii) explore the associations among momentary and recall pain with psychological variables (pain catastrophizing and perceived stress).

METHODS

Healthy participants (N=57) received a low (0.5 ml) or a high (1.0 ml) dose of hypertonic saline (5.8%) injection into the right gluteus medius muscle and, subsequently, were randomized into a non-drawing or a drawing group. The non-drawing groups reported momentary pain intensity every 30-s. Whereas the drawing groups reported momentary pain intensity and distribution on a digital body chart every 30-s. The pain intensity, area (pixels), and distribution metrics (compound area, location, radiating extent) were compared at peak pain and over time to explore dose-response differences and spatiotemporal patterns. All participants recalled the peak pain intensity and the peak (most extensive) distribution seven days later. The peak pain intensity and area recall error was calculated. Pain distribution similarity was determined using a Jaccard index which compares pain drawings representing peak distribution at baseline and recall. The relationships were explored among peak intensity and area at baseline and recall, catastrophizing, and perceived stress.

RESULTS

The pain intensity, area, distribution metrics, and the duration of pain were lower for the 0.5 mL than the 1.0 mL dose over time (p<0.05). However, the pain intensity and area were similar between doses at peak pain (p>0.05). The pain area and distribution between momentary and recall pain drawings were similar (p>0.05), as reflected in the Jaccard index. Additionally, peak pain intensity did not correlate with the peak pain area. Further, peak pain intensity, but not area, was correlated with catastrophizing (p<0.01).

CONCLUSIONS

This study showed differences in spatiotemporal patterns of pain intensity and distribution in a dose-response fashion to experimental acute low back pain. Unlike pain intensity, pain distribution and area may be less susceptible in an experimental setting. Higher intensities of momentary pain do not appear to influence the ability to recall the pain intensity or distribution in healthy participants.

IMPLICATIONS

The recall of pain distribution in experimental settings does not appear to be influenced by the intensity despite differences in the pain experience. Pain distribution may add additional value to mechanism-based studies as the distribution reports do not vary with pain catastrophizing. REC# N-20150052.

Novel Software for Pain Drawing Analysis

Introduction

Pain drawings (PDs) are an important component of the assessment of a patient with pain. Although analog pain drawings (APDs), such as pen-on-paper drawings, have been extensively used in clinical assessment and clinical research, there is a lack of digital pain drawing (DPD) software that would be able to quantify and analyze the digital pain distribution obtained by the patients. The aim of this work is to describe a method that can quantify the extent and location of pain through novel custom-built software able to analyze data from the digital pain drawings obtained from the patients.

Methods

The application analysis and software specifications were based on the information gathered from the literature, and the programmers created the custom-built software according to the published needs of the pain scientific community.

Results

We developed a custom-built software named “Pain Distribution,” which, among others, automatically calculates the number of the pixels the patient has chosen and therefore quantifies the pain extent, provides the frequency distribution from a group of images, and has the option to select the threshold over which the patient is considered with central sensitization (CS). Additionally, it delivers results and statistics for both every image and the frequency distribution, providing mean values, standard deviations, and CS indicators, as well as the ability to export them in *.txt file format for further analysis.

Conclusion

A novel Pain Distribution application was developed, freely available for use in any setting, clinical, research, or academic.

The Symmetry of Lower Back Pain as a Potential Screening Factor for Serious Pathology: A Survey Study

Background: Pain maps provide reliable information on pain location in various conditions. This study explored the feasibility of pain maps as a screening tools for serious underlying conditions. The pain symmetry was evaluated as the possible distinguishing feature. Methods: A Web-based survey on the correlation of pain-related disability and pain pattern was developed. Respondents with lower back pain were asked to mark the exact location of their pain over the pain chart. The symmetry index was calculated and used to divide subjects into two groups that were then compared in terms of the prevalence of red flags for serious pathologies, as well as the pain-related disability measured with COMI and ODI instruments. Results: Of the 4213 respondents who completed the survey, 1018 were included in the study. The pain related disability was greater in respondents with asymmetrical pain patterns, as shown with all instruments. The distribution of red flags was also dependent on pain symmetry. The history of weight loss (6.70 vs. 1.76 p < 0.001) and fever (4.91 vs. 2.14 p < 0.001) were more prevalent with symmetrical pain patterns, and the history of trauma was more frequent with asymmetrical pain (21.41 vs. 10.71 p < 0.001). Conclusions: It was shown that the symmetry of pain is correlated to the prevalence of red flags and pain-related disability.

Lateralization and Bodily Patterns of Segmental Signs and Spontaneous Pain in Acute Visceral Disease: Observational Study

Background

The differential diagnosis of acute visceral diseases is a challenging clinical problem. Older literature suggests that patients with acute visceral problems show segmental signs such as hyperalgesia, skin resistance, or muscular defense as manifestations of referred visceral pain in somatic or visceral tissues with overlapping segmental innervation. According to these sources, the lateralization and segmental distribution of such signs may be used for differential diagnosis. Segmental signs and symptoms may be accompanied by spontaneous (visceral) pain, which, however, shows a nonsegmental distribution.

Objective

This study aimed to investigate the lateralization (ie, localization on one side of the body, in preference to the other) and segmental distribution (ie, surface ratio of the affected segments) of spontaneous pain and (referred) segmental signs in acute visceral diseases using digital pain drawing technology.

Methods

We recruited 208 emergency room patients that were presenting for acute medical problems considered by triage as related to internal organ disease. All patients underwent a structured 10-minute bodily examination to test for various segmental signs and spontaneous visceral pain. They were further asked their segmental symptoms such as nausea, meteorism, and urinary retention. We collected spontaneous pain and segmental signs as digital drawings and segmental symptoms as binary values on a tablet PC. After the final diagnosis, patients were divided into groups according to the organ affected. Using statistical image analysis, we calculated mean distributions of pain and segmental signs for the heart, lungs, stomach, liver/gallbladder, and kidneys/ureters, analyzing the segmental distribution of these signs and the lateralization.

Results

Of the 208 recruited patients, 110 (52.9%) were later diagnosed with a single-organ problem. These recruited patients had a mean age of 57.3 (SD 17.2) years, and 40.9% (85/208) were female. Of these 110 patients, 85 (77.3%) reported spontaneous visceral pain. Of the 110, 81 (73.6%) had at least 1 segmental sign, and the most frequent signs were hyperalgesia (46/81, 57%), and muscle resistance (39/81, 48%). While pain was distributed along the body midline, segmental signs for the heart, stomach, and liver/gallbladder appeared mostly ipsilateral to the affected organ. An unexpectedly high number of patients (37/110, 33.6%) further showed ipsilateral mydriasis.

Conclusions

This study underlines the usefulness of including digitally recorded segmental signs in bodily examinations of patients with acute medical problems.

Hierarchical clustering by patient-reported pain distribution alone identifies distinct chronic pain subgroups differing by pain intensity, quality, and clinical outcomes

Background

In clinical practice, the bodily distribution of chronic pain is often used in conjunction with other signs and symptoms to support a diagnosis or treatment plan. For example, the diagnosis of fibromyalgia involves tallying the areas of pain that a patient reports using a drawn body map. It remains unclear whether patterns of pain distribution independently inform aspects of the pain experience and influence patient outcomes. The objective of the current study was to evaluate the clinical relevance of patterns of pain distribution using an algorithmic approach agnostic to diagnosis or patient-reported facets of the pain experience.

Methods and findings

A large cohort of patients (N = 21,658) completed pain body maps and a multi-dimensional pain assessment. Using hierarchical clustering of patients by body map selection alone, nine distinct subgroups emerged with different patterns of body region selection. Clinician review of cluster body maps recapitulated some clinically-relevant patterns of pain distribution, such as low back pain with radiation below the knee and widespread pain, as well as some unique patterns. Demographic and medical characteristics, pain intensity, pain impact, and neuropathic pain quality all varied significantly across cluster subgroups. Multivariate modeling demonstrated that cluster membership independently predicted pain intensity and neuropathic pain quality. In a subset of patients who completed 3-month follow-up questionnaires (N = 7,138), cluster membership independently predicted the likelihood of improvement in pain, physical function, and a positive overall impression of change related to multidisciplinary pain care.

Conclusions

This study reports a novel method of grouping patients by pain distribution using an algorithmic approach. Pain distribution subgroup was significantly associated with differences in pain intensity, impact, and clinically relevant outcomes. In the future, algorithmic clustering by pain distribution may be an important facet in chronic pain biosignatures developed for the personalization of pain management.

Evaluation of the Use of Colors and Drawings for Pain Communication for Hmong Patients

AIMS

The aim of the present study was to explore: (1) the feasibility of using color and pain drawing to describe pain; (2) the cultural appropriateness of pain body diagram (PBD); and (3) the cultural meaning of colors used in pain expression within one cultural group-the Hmong residing in the United States.

DESIGN

A qualitative-descriptive study.

METHODS

Data were collected sequentially in two phases with different Hmong participants from a Midwestern city using (1) focus groups to determine colors used for pain intensity and qualities along with preferences for drawing versus using the PBD; and (2) individual interviews to determine pain-related meanings of colors and cultural appropriateness of PBDs. Interviews were recorded, transcribed, and analyzed using summative and directed content analyses.

RESULTS

Of 67 participants, 73% were female, the average age was 53.7±14.9 years, and 67% received Medicaid. In Phase I, most participants were unable to draw their pain on a blank page and preferred using a PBD. Most could select colors for pain intensity levels, with white and red indicating no pain and severe pain, respectively. In Phase II, white, red, and black had cultural meanings related to pain while colors such as yellow, orange, and blue had personal meanings. All participants perceived the PBD to be culturally appropriate.

CONCLUSIONS

The study's findings have implications for how to use colors in pain communication and confirm that PBDs can be used with Hmong patients.

Colored Pain Drawing as a Clinical Tool in Differentiating Neuropathic Pain from Non-Neuropathic Pain

OBJECTIVES

This is a prospective, blinded, case-control study of patients with chronic pain using body diagrams and colored markers to show the distribution and quality of pain and sensory symptoms (aching, burning, tingling, numbness, and sensitivity to touch) experienced in affected body parts.

METHODS

Two pain physicians, blinded to patients' clinical diagnoses, independently reviewed and classified each colored pain drawing (CPD) for presence of neuropathic pain (NeuP) vs. non-neuropathic pain (NoP). A clinical diagnosis (gold standard) of NeuP was made in 151 of 213 (70.9%) enrolled patients.

RESULTS

CPD assessment at "first glance" by both examiners resulted in correctly categorizing 137 (64.3% by examiner 1) and 156 (73.2% by examiner 2) CPDs. Next, classification of CPDs by both physicians, using predefined criteria of spatial distribution and quality of pain-sensory symptoms, improved concordance to 212 of 213 CPDs (Kappa = 0.99). The diagnostic ability to correctly identify NeuP and NoP by both examiners increased to 171 (80.2%) CPDs, with 80.1% sensitivity and 80.6% specificity (Kappa = 0.56 [95% confidence interval: 0.44-0.68]). The severity scores for pain and sensory symptoms (burning, tingling, numbness, and sensitivity to touch) on the Neuropathic Pain Questionnaire were significantly elevated in NeuP vs. NoP (P < 0.001).

CONCLUSIONS

This study demonstrates good performance characteristics of CPDs in identifying patients with NeuP through the use of a simple and easy-to-apply classification scheme. We suggest use of CPDs as a bedside screening tool and as a method for phenotypic profiling of patients by the quality and distribution of pain and sensory symptoms.

Development and Validation of the Pain and State of Health Inventory (PHI): Application for the Perioperative Setting

Currently, general measurements and evaluations of the quality of recovery are difficult because no adequate measuring tools are available. Therefore, there is an urgent need for a universal tool that assesses patient-relevant criteria-postoperative pain, state of health, and somatic parameters. For this purpose, a pain and state of health inventory (PHI, Schmerz- und Befindlichkeitsinventar (SBI) in German) has been developed. In this study, we describe its development and validation. The development phase was led by an expert panel and was divided into three subphases: determining the conceptual structure, testing the first editions, and adjusting the inventory for a finalized edition. For the purpose of validation, the PHI was filled in by 132 patients who have undergone total knee replacement and was analyzed using principal component analysis. Construct validity was tested by correlating the items with validated questionnaires. The results showed that the inventory can test pain, state of health, and somatic parameters with great construct validity. Furthermore, the inventory is accepted by patients, map changes, and supports to initiate adequate treatment. In conclusion, the PHI is a universal tool that can be used to assess the quality of recovery in the perioperative setting and allow immediate intervention.

A picture is worth a thousand words: linking fibromyalgia pain widespreadness from digital pain drawings with pain catastrophizing and brain cross-network connectivity

ABSTRACT

Pain catastrophizing is prominent in chronic pain conditions such as fibromyalgia and has been proposed to contribute to the development of pain widespreadness. However, the brain mechanisms responsible for this association are unknown. We hypothesized that increased resting salience network (SLN) connectivity to nodes of the default mode network (DMN), representing previously reported pain-linked cross-network enmeshment, would be associated with increased pain catastrophizing and widespreadness across body sites. We applied functional magnetic resonance imaging (fMRI) and digital pain drawings (free-hand drawing over a body outline, analyzed using conventional software for multivoxel fMRI analysis) to investigate precisely quantified measures of pain widespreadness and the associations between pain catastrophizing (Pain Catastrophizing Scale), resting brain network connectivity (Dual-regression Independent Component Analysis, 6-minute multiband accelerated fMRI), and pain widespreadness in fibromyalgia patients (N = 79). Fibromyalgia patients reported pain in multiple body areas (most frequently the spinal region, from the lower back to the neck), with moderately high pain widespreadness (mean ± SD: 26.1 ± 24.1% of total body area), and high pain catastrophizing scale scores (27.0 ± 21.9, scale range: 0-52), which were positively correlated (r = 0.26, P = 0.02). A whole-brain regression analysis focused on SLN connectivity indicated that pain widespreadness was also positively associated with SLN connectivity to the posterior cingulate cortex, a key node of the DMN. Moreover, we found that SLN-posterior cingulate cortex connectivity statistically mediated the association between pain catastrophizing and pain widespreadness (P = 0.01). In conclusion, we identified a putative brain mechanism underpinning the association between greater pain catastrophizing and a larger spatial extent of body pain in fibromyalgia, implicating a role for brain SLN-DMN cross-network enmeshment in mediating this association.

Digital manikins to self-report pain on a smartphone: A systematic review of mobile apps

BACKGROUND

Chronic pain is the leading cause of disability. Improving our understanding of pain occurrence and treatment effectiveness requires robust methods to measure pain at scale. Smartphone-based pain manikins are human-shaped figures to self-report location-specific aspects of pain on people's personal mobile devices.

METHODS

We searched the main app stores to explore the current state of smartphone-based pain manikins and to formulate recommendations to guide their development in the future.

RESULTS

The search yielded 3,938 apps. Twenty-eight incorporated a pain manikin and were included in the analysis. For all apps, it was unclear whether they had been tested and had end-user involvement in the development. Pain intensity and quality could be recorded in 28 and 13 apps, respectively, but this was location specific in only 11 and 4. Most manikins had two or more views (n = 21) and enabled users to shade or select body areas to record pain location (n = 17). Seven apps allowed personalising the manikin appearance. Twelve apps calculated at least one metric to summarise manikin reports quantitatively. Twenty-two apps had an archive of historical manikin reports; only eight offered feedback summarising manikin reports over time.

CONCLUSIONS

Several publically available apps incorporated a manikin for pain reporting, but only few enabled recording of location-specific pain aspects, calculating manikin-derived quantitative scores, or generating summary feedback. For smartphone-based manikins to become adopted more widely, future developments should harness manikins' digital nature and include robust validation studies. Involving end users in the development may increase manikins' acceptability as a tool to self-report pain.

SIGNIFICANCE

This review identified and characterised 28 smartphone apps that included a pain manikin (i.e. pain drawings) as a novel approach to measure pain in large populations. Only few enabled recording of location-specific pain aspects, calculating quantitative scores based on manikin reports, or generating manikin feedback. For smartphone-based manikins to become adopted more widely, future studies should harness the digital nature of manikins, and establish the measurement properties of manikins. Furthermore, we believe that involving end users in the development process will increase acceptability of manikins as a tool for self-reporting pain.

Clinical Significance and Diagnostic Value of Pain Extent Extracted from Pain Drawings: A Scoping Review

The current scoping review aimed to map current literature investigating the relationship between pain extent extracted from pain drawings with clinical, psychological, and psycho-physiological patient-reported outcome measures in people with pain. Electronic databases were searched for cross-sectional cohort studies that collected pain drawings using digital technology or a pen-on-paper approach and assessed for correlations between pain extent and clinical, psychological or psycho-physical outcomes. Data were extracted by two different reviewers. The methodological quality of studies was assessed using the Newcastle–Ottawa Quality Assessment Scale. Mapping of the results included: 1, description of included studies; 2, summary of results; and 3, identification of gaps in the existing literature. Eleven cross-sectional cohort studies were included. The pain disorders considered were heterogeneous, ranging from musculoskeletal to neuropathic conditions, and from localized to generalized pain conditions. All studies included pain and/or pain-related disability as clinical outcomes. Psychological outcomes included depression and anxiety, kinesiophobia and catastrophism. Psycho-physical measures included pressure or thermal pain thresholds. Ten studies were considered of high methodological quality. There was heterogeneity in the associations between pain extent and patient-reported outcome measures depending on the pain condition. This scoping review found that pain extent is associated with patient-reported outcome measures more so in patients presenting with musculoskeletal pain, e.g., neck pain or osteoarthritis, rather than for those with neuropathic pain or headache.

Therapeutic Sensations: A New Unifying Concept

Physical sensations of tingling, warmth, dull pain, and heaviness are a common phenomenon in mind-body interventions, such as acupuncture, hypnotherapy, osteopathy, qigong, meditation, and progressive muscle relaxation. Even though there are striking parallels between sensations produced by many different interventions, no attempt has yet been made to understand them from a unifying perspective that combines information from different therapies and practices. Therefore, this narrative systematic review introduces the concept of therapeutic sensations and summarizes studies of their sensory quality, bodily topography, and the meaning that patients attach to them. Furthermore, it highlights the essential role of therapeutic sensations in the development of vital energy concepts, such as qi, prana, pneuma, and orgone, in various traditional medicine systems, body-oriented psychotherapy, and so-called energy medicine. Finally, the assessment of therapeutic sensations may help to gain a deeper understanding of such concepts, finding a common language between scientists, patients and practitioners, and bridging the wide gap between materialistic and vitalistic views.

Behavioral Pain Assessment Implementation in Long-Term Care Using a Tablet App: Case Series and Quasi-Experimental Design

BACKGROUND

Pain is often underassessed and undertreated among long-term care (LTC) residents living with dementia. When used regularly, the Pain Assessment Checklist for Seniors With Limited Ability to Communicate (PACSLAC) scales have been shown to have beneficial effects on pain assessment and management practices and stress and burnout levels in frontline staff in LTC facilities. Such scales, however, are not utilized as often as recommended, which is likely to be related to additional record-keeping and tracking over time involved with their paper-and-pencil administration.

OBJECTIVE

Using implementation science principles, we assessed the introduction of the PACSLAC-II scale by comparing two methods of administration-a newly developed tablet app version and the original paper-and-pencil version-with respect to the frequency of pain assessment and facility staff feedback.

METHODS

Using a case series approach, we tracked pain-related quality indicators at baseline, implementation, and follow-up periods. A quasi-experimental design was used to evaluate the effect of the method of administration (ie, paper-and-pencil only [n=18], tablet only [n=12], paper-and-pencil followed by tablet app [n=31], and tablet app followed by paper-and-pencil [n=31]) on pain assessment frequency and frontline staff stress and burnout levels. Finally, semistructured interviews were conducted with frontline staff to obtain perspectives on each method of administration.

RESULTS

The implementation effort resulted in a great increase in pain assessment frequency across 7 independent LTC units, although these increases were not maintained during the follow-up period. Frontline staff reported lower levels of workload in the paper-and-pencil followed by tablet app condition than those in the paper-and-pencil only (P<.001) and tablet app followed by paper-and-pencil (P<.001) conditions. Frontline staff also reported lower levels of workload in the tablet-only condition than those in the paper-and-pencil only condition (P=.05). Similarly, lower levels of emotional exhaustion were reported by frontline staff in the paper-and-pencil followed by tablet app condition than those in the paper-and-pencil only (P=.002) and tablet app followed by paper-and-pencil (P=.002) conditions. Finally, frontline staff reported higher levels of depersonalization in the paper-and-pencil only condition than those in the tablet app only (P=.008), paper-and-pencil followed by tablet app (P<.001), and tablet app followed by paper-and-pencil (P<.001) conditions. Furthermore, narrative data from individual interviews with frontline staff revealed a preference for the tablet app over the paper-and-pencil method of administration.

CONCLUSIONS

This study provides support for the use of either the tablet app or the paper-and-pencil version of the PACSLAC-II to improve pain-related quality indicators, but a reported preference for and lower levels of stress and burnout with the use of the tablet app method of administration suggests that the use of the tablet app may have more advantages compared with the paper-and-pencil method of administration.