Digital Pain Drawings Can Improve Doctors' Understanding of Acute Pain Patients: Survey and Pain Drawing Analysis

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.

Changes in Multiple Aspects of Pain Outcomes After Rehabilitation: Analysis of Pain Data in a Randomized Controlled Trial Evaluating the Effects of Adding Sensorimotor Training to Manual Therapy and Exercise for Chronic Neck Pain

OBJECTIVES

To examine changes in pain outcomes to fully evaluate the effect of adding sensorimotor training to manual therapy and exercise in patients with chronic neck pain and sensorimotor deficits. Concordance was examined between pain distribution and pain intensity and patient-reported outcomes.

METHODS

Participants (n=152) were randomly allocated into 4 intervention groups: One group received local neck treatment (NT) comprising manual therapy and exercise and the other 3 groups received additional sensorimotor training (either joint position sense/oculomotor exercises, balance exercises or both). Treatment was delivered twice a week for 6 weeks. Pain and patient-reported outcomes were measured at baseline, posttreatment, and 3-, 6- and 12-month follow-ups.

RESULTS

There were greater changes in pain location, extent, and intensity at 6- and 12-month follow-ups in the sensorimotor training groups compared with the NT group ( P <0.05). A greater number of patients in the sensorimotor training groups gained ≥50% reduction in pain extent and intensity relative to the NT group at 6 and 12 months ( P <0.05). Clinical improvement in pain extent was concordant with pain intensity (adjusted kappa=056 to 0.66, %agreement=78.3 to 82.9, P <0.001) and disability (adjusted kappa=0.47 to 0.58, % agreement=73.7 to 79.0, P <0.01) at 3-, 6- and 12-month follow-ups, but not with function and well-being. The concordance tended to decline with time.

DISCUSSION

Multiple aspects of the pain experience improved in the longer term by adding sensorimotor training to NT for patients with neck pain and sensorimotor deficits. The concordance between pain and patient-reported outcomes was not always evident and varied over time, suggesting the need for multidimensional assessments of pain.

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.

Digital mapping of shoulder pain in patients with shoulder disorders: a reliability study

INTRODUCTION

Digital body mapping can be used to document and quantify the area and location (distribution) of pain and discomfort and support assessment, monitoring, and treatment in clinical populations. This study determines the test-retest reliability of drawings detailing pain and pins and needles using digital body charts and their relationship to pain intensity and patient-reported shoulder function.

METHODS

Sixty-two participants with shoulder disorder completed pain and pins and needles drawings with test-retest interval of 30 minutes. Pain intensity in the last week and the patient-reported shoulder function questionnaires were completed. Area and radiating extent were determined using customized software. To assess relative and absolute test-retest reliability, the intraclass correlation coefficient (ICC3,1), standard error of measurement (SEM) and minimal detectable change (MDC95) were calculated. Regression analysis evaluated relation between area and radiating extent of pain and pins and needles with patient-reported function questionnaires.

RESULTS

Relative reliability for pain area and radiating extent was excellent (>0.90). Absolute reliability (SEM and MDC95) values for the pain area and radiating extent were 0.20%/34 pixels and 0.57%/94 pixels. Absolute reliability improves for smaller pain areas. Regression analysis revealed the area and radiation extent for both pain and pins and needles are independent constructs to the patient-reported function outcome when adjusted for pain intensity.

CONCLUSIONS

Digital body mapping assessing pain area and radiation extent in patients with shoulder disorders are reliable. The magnitude of absolute reliability suggests other sources of variability on repeat testing in this population. Pain area and radiation extent appear to be independent constructs.

Bodily maps of emotions and pain: tactile and hedonic sensitivity in healthy controls and patients experiencing chronic pain

ABSTRACT

Pain is an unpleasant sensory and emotional experience. Both pain and emotions are warning signals against outside harm. Interoception, bodily sensations of emotions can be assessed with the emBODY tool where participants colour the body parts where they feel different emotions. Bodily maps of emotions (BMoE) have been shown to be similar between healthy individuals independent of age, sex, cultural background, and language. We used this tool to analyze how these body maps may differ between healthy controls and patients with persistent pain. We recruited 118 patients with chronic pain. An algorithm-selected matched controls from 2348 individuals who were recruited through social media, message boards, and student mailing lists. After providing background information, the participants completed the bodily topography colouring tasks with the emBODY tool using tablets (patients) and online using their own devices (controls), for pain, sensitivity for tactile, nociceptive and hedonic stimuli, and for the 6 basic emotions and a neutral state. Patients with pain coloured significantly larger areas for pain and more negative emotions. On the whole, their BMoEs were dampened compared with healthy controls. They also coloured more areas for nociceptive but not for tactile or hedonic sensitivity. Patients and controls marked different body areas as sensitive to nociceptive and tactile stimulation, but there was no difference in sensitivity to hedonic touch. Our findings suggest that emotional processing changes when pain persists, and this can be assessed with these colouring tasks. BMoEs may offer a new approach to assessing pain.

Do metrics derived from self-reported and clinician-reported pain drawings agree for individuals with chronic low back pain?

BACKGROUND

Clinicians commonly use pain drawings to define the spatial extent and location of a person's pain, but limited research has investigated who should perform the drawing.

OBJECTIVES

To establish the inter-rater reliability of pain extent and location derived from three sets of pain drawings for people with chronic low back pain: one self-reported and two clinician-reported. Additionally, convergent validity of pain extent was assessed using the same dataset.

DESIGN

Repeated-measures cross-sectional study.

METHOD

Fifteen patients with chronic low back pain and a pool of eight clinicians were involved to assess the reliability of pain extent and location extracted by self-report and clinician-reported pain drawings. Inter-rater reliability of pain extent was computed using intraclass correlation coefficients (ICC) and Bland Altman analysis. Convergent validity of pain extent was assessed using Spearman's rank correlation. Inter-rater reliability of pain location was assessed using the Jaccard similarity index.

RESULTS

The inter-reliability analysis for pain extent, derived from self-reported and clinician-reported pain drawings, revealed ICC scores ranging from 0.39 to 0.51, all with wide confidence intervals. The mean Jaccard similarity indexes computed for pain location ranged from 0.60 to 0.65. Moderate to good correlation was found for pain extent derived by the sets of pain drawings.

CONCLUSIONS

Inter-rater reliability of pain extent and pain location derived from self-reported and clinician-reported pain drawings is poor in patients with chronic low back pain. The lack of reliability is also confirmed when considering only clinician-reported PDs. The convergent validity analysis of pain extent revealed that the two pain drawing approaches measure a similar construct.

Test-retest reliability of pain extent and pain location using a novel pain drawing analysis software application, on patients with shoulder pain

OBJECTIVES

A method of pain assessment is the drawing of pain on a specially designed manikin where the patients color the area representing their pain distribution. In recent years, software applications have been developed for the purpose of digital pain drawing data acquisition and processing. Although such specific software applications have already been released, they have been built with obsolete programming tools. The purpose of the study was to investigate the test - retest reliability of a new pain drawing analysis software, in a sample of patients with shoulder pain.

METHODS

Data collected from 31 subjects with shoulder pain. Participants were asked twice to color their pain distribution in the painting environment of a tablet software application called 'Pain Distribution.'

RESULTS

The reliability of pain extent was found to be good (ICC = 0.80). The Jaccard index for the reliability of pain location was found to be moderate, equal to 42.02 ± 19.13%.

CONCLUSION

The results demonstrated good reliability of pain extent and moderate reliability of pain location using the new pain distribution analysis application 'Pain Distribution.' This pain drawing software application could be a reliable, inexpensive, and clinically usable solution for assessing the distribution of pain in patients with shoulder pain.

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.

Self-reported bio-psycho-social factors partially distinguish rotator cuff tendinopathy from other shoulder problems and explain shoulder severity: A case-control study

OBJECTIVE

Examine how rotator cuff (RC) tendinopathy differed from other shoulder problems (OSP) by measuring a variety of self-reported bio-psycho-social factors, and establish which explain severity.

METHODS

A validated online survey battery was used to collect self-reported biopsychosocial variables in an international population. Diagnostic group and severity were the dependent variables. Multiple logistic and linear regression analyses were utilised to generate explanatory models for group differences and severity after group comparison and univariate regression analysis.

RESULTS

82 people with RC tendinopathy (50 female, 42.8 ± 13.9 years) and 54 with OSP (33 female, 40.2 ± 14.1 years) were recruited. Both groups had comparable severity results (Shoulder Pain and Disability Index = 37.3 ± 24.5 vs. 33.7 ± 22.5). Seven factors individually differentiated RC tendinopathy from OSP. The multivariable model included 4 factors: activity effect on pain (OR(95%CI) = 2.24(1.02-4.90)), previous injury in the shoulder (OR(95% CI) = 0.30(0.13-0.69)), activity level (moderate OR(95% CI) = 3.97(1.29-12.18), high OR(95% CI) = 3.66(1.41-9.48)) and self-efficacy (OR(95%CI) = 1.12(1.02-1.22)) demonstrating acceptable accuracy. The second multivariable model for RC tendinopathy severity included one demographic, three psychological and two biomedical variables (β(range) = 0.19-0.38) and explained 68% of the variance.

CONCLUSION

Self-reported bio-psycho-social variables may be beneficial for further detailed clinical assessment as they partially distinguish RC tendinopathy from OSP, even when the groups have comparable overall pain and functional problems. Moreover, these variables were shown to be substantially associated with RC tendinopathy severity variance, implying that the clinical evaluation might be improved, perhaps by pre-consultation online data collection. The models should be validated in the future and considered alongside data from physical and imaging examinations.

Artificial Intelligence-Enabled Evaluation of Pain Sketches to Predict Outcomes in Headache Surgery

BACKGROUND

Recent evidence has shown that patient drawings of pain can predict poor outcomes in headache surgery. Given that interpretation of pain drawings requires some clinical experience, the authors developed a machine learning framework capable of automatically interpreting pain drawings to predict surgical outcomes. This platform will allow surgeons with less clinical experience, neurologists, primary care practitioners, and even patients to better understand candidacy for headache surgery.

METHODS

A random forest machine learning algorithm was trained on 131 pain drawings provided prospectively by headache surgery patients before undergoing trigger-site deactivation surgery. Twenty-four features were used to describe the anatomical distribution of pain on each drawing for interpretation by the machine learning algorithm. Surgical outcome was measured by calculating percentage improvement in Migraine Headache Index at least 3 months after surgery. Artificial intelligence predictions were compared with clinician predictions of surgical outcome to determine artificial intelligence performance.

RESULTS

Evaluation of the data test set demonstrated that the algorithm was consistently more accurate (94%) than trained clinical evaluators. Artificial intelligence weighted diffuse pain, facial pain, and pain at the vertex as strong predictors of poor surgical outcome.

CONCLUSIONS

This study indicates that structured algorithmic analysis is able to correlate pain patterns drawn by patients to Migraine Headache Index percentage improvement with good accuracy (94%). Further studies on larger data sets and inclusion of other significant clinical screening variables are required to improve outcome predictions in headache surgery and apply this tool to clinical practice.

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.

A window into pain: American Indian cancer survivors' drawings

In order to explore the cultural constructs of pain, a series of focus groups were held among adult American Indian (AI) cancer survivors and their caregivers in the Southwest USA. Thirteen focus groups held at four sites (reservation, urban setting, hospital and clinic) elicited information on the barriers to cancer pain management. In response to facilitator questions about cancer pain and existing measurement scales, participants drew pictures to better explain their pain type (i.e., "pounding"), intensity (i.e., "spider web-like"), and other more abstract aspects of their pain episodes. Noting this novel outlet, subsequent groups were prompted for illustrations of pain. A total of 17 drawings were collected from focus group participants. We discuss seven of the drawings that best opened a window into the lived experience of pain, reflected through the eyes of cancer survivors. This study provides evidence that self-expression through color, imagery and written personal accounts provides more accurate depictions of pain for Southwest AI cancer survivors than pain scales alone. It is hypothesized that cultural modes of communication (i.e., storytelling) and intergenerational influences of artwork led to the depiction of pain in drawings. Suggestions for further exploration of the use of the pain drawings for pain assessment in healthcare settings are included.

Comparing what the clinician draws on a digital pain map to that of persons who have greater trochanteric pain syndrome

OBJECTIVES

To assess the agreements and differences in pain drawings (pain area, shape and location) between individuals who have greater trochanteric pain syndrome (GTPS) and their clinician.

METHODS

In this study, 23 patients with GTPS (21 female, pain duration range 8-24 months) underwent clinical evaluation by a registered physiotherapist. Digital 2d full body pain drawings were independently performed by the clinician during the subjective examination and by the patient following the physical examination. Levels of agreement [LoA] in the pain area were assessed with Bland-Altman plots. Differences in pain drawings were assessed visually by overlaying images, and by quantifying the differences in shape and location with the bounding box, and Jaccard index, respectively.

RESULTS

Pain areas (/total pixels of the charts) did not differ in size (LoA mean difference less than -0.5%; range -2.35-1.56%) or shape (bounding box p>0.17). However, there was minimal overlap in location (Jaccard index range 0.09-0.18/1 for perfect overlap).

CONCLUSIONS

Patients and the clinician displayed differences in location of pain areas, but not size or shape, when they independently performed digital pain drawings. The reasons that underlie and the clinical impact of these differences remains unclear.

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.

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.

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.

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

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.

Supporting Medical Staff from Psycho-Oncology with Smart Mobile Devices: Insights into the Development Process and First Results

Cancer is a very distressing disease, not only for the patients themselves, but also for their family members and relatives. Therefore, patients are regularly monitored to decide whether psychological treatment is necessary and applicable. However, such monitoring processes are costly in terms of required staff and time. Mobile data collection is an emerging trend in various domains. The medical and psychological field benefits from such an approach, which enables experts to quickly collect a large amount of individual health data. Mobile data collection applications enable a more holistic view of patients and assist psychologists in taking proper actions. We developed a mobile application, FeelBack, which is designed to support data collection that is based on well-known and approved psychological instruments. A controlled pilot evaluation with 60 participants provides insights into the feasibility of the developed platform and it shows the initial results. 31 of these participants received paper-based questionnaire and 29 followed the digital approach. The results reveal an increase of the overall acceptance by 58.5% in the mean when using a digital screening as compared to the paper-based. We believe that such a platform may significantly improve cancer patients’ and relatives’ psychological treatment, as available data can be used to optimize treatment.

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.

Pain drawings as a diagnostic tool for the differentiation between two pain-associated rare diseases (Ehlers-Danlos-Syndrome, Guillain-Barré-Syndrome)

Background

The diagnosis of rare diseases poses a particular challenge to clinicians. This study analyzes whether patients’ pain drawings (PDs) help in the differentiation of two pain-associated rare diseases, Ehlers-Danlos Syndrome (EDS) and Guillain-Barré Syndrome (GBS).

Method

The study was designed as a prospective, observational, single-center study. The sample comprised 60 patients with EDS (3 male, 52 female, 5 without gender information; 39.2 ± 11.4 years) and 32 patients with GBS (10 male, 20 female, 2 without gender information; 50.5 ± 13.7 years). Patients marked areas afflicted by pain on a sketch of a human body with anterior, posterior, and lateral views. PDs were electronically scanned and processed. Each PD was classified based on the Ružička similarity to the EDS and the GBS averaged image (pain profile) in a leave-one-out cross validation approach. A receiver operating characteristic (ROC) curve was plotted.

Results

60–80% of EDS patients marked the vertebral column with the neck and the tailbone and the knee joints as pain areas, 40–50% the shoulder-region, the elbows and the thumb saddle joint. 60–70% of GBS patients marked the dorsal and plantar side of the feet as pain areas, 40–50% the palmar side of the fingertips, the dorsal side of the left palm and the tailbone. 86% of the EDS patients and 96% of the GBS patients were correctly identified by computing the Ružička similarity. The ROC curve yielded an excellent area under the curve value of 0.95.

Conclusion

PDs are a useful and economic tool to differentiate between GBS and EDS. Further studies should investigate its usefulness in the diagnosis of other pain-associated rare diseases. This study was registered in the German Clinical Trials Register, No. DRKS00014777 (Deutsches Register klinischer Studien, DRKS), on 01.06.2018.

Digital Pain Mapping and Tracking in Patients With Chronic Pain: Longitudinal Study

Background

Digital pain mapping allows for remote and ecological momentary assessment in patients over multiple time points spanning days to months. Frequent ecological assessments may reveal tendencies and fluctuations more clearly and provide insights into the trajectory of a patient’s pain.

Objective

The primary aim of this study is to remotely map and track the intensity and distribution of pain and discomfort (eg, burning, aching, and tingling) in patients with nonmalignant spinal referred pain over 12 weeks using a web-based app for digital pain mapping. The secondary aim is to explore the barriers of use by determining the differences in clinical and user characteristics between patients with good (regular users) and poor (nonregular users) reporting compliance.

Methods

Patients (N=91; n=53 women) with spinal referred pain were recruited using web-based and traditional in-house strategies. Patients were asked to submit weekly digital pain reports for 12 weeks. Each pain report consisted of digital pain drawings on a pseudo–three-dimensional body chart and pain intensity ratings. The pain drawings captured the distribution of pain and discomfort (pain quality descriptors) expressed as the total extent and location. Differences in weekly pain reports were explored using the total extent (pixels), current and usual pain intensity ratings, frequency of quality descriptor selection, and Jaccard similarity index. Validated e-questionnaires were completed at baseline to determine the patients’ characteristics (adapted Danish National Spine Register), disability (Oswestry Disability Index and Neck Disability Index), and pain catastrophizing (Pain Catastrophizing Scale) profiles. Barriers of use were assessed at 6 weeks using a health care–related usability and acceptance e-questionnaire and a self-developed technology-specific e-questionnaire to assess the accessibility and ease of access of the pain mapping app. Associations between total extent, pain intensity, disability, and catastrophizing were explored to further understand pain. Differences between regular and nonregular users were assessed to understand the pain mapping app reporting compliance.

Results

Fluctuations were identified in pain reports for total extent and pain intensity ratings (P<.001). However, quality descriptor selection (P=.99) and pain drawing (P=.49), compared using the Jaccard index, were similar over time. Interestingly, current pain intensity was greater than usual pain intensity (P<.001), suggesting that the timing of pain reporting coincided with a more intense pain experience than usual. Usability and acceptance were similar between regular and nonregular users. Regular users were younger (P<.001) and reported a larger total extent of pain than nonregular users (P<.001).

Conclusions

This is the first study to examine digital reports of pain intensity and distribution in patients with nonmalignant spinal referred pain remotely for a sustained period and barriers of use and compliance using a digital pain mapping app. Differences in age, pain distribution, and current pain intensity may influence reporting behavior and compliance.

Patient Pain Sketches Can Predict Surgical Outcomes in Trigger-Site Deactivation Surgery for Headaches

BACKGROUND

Patient selection for headache surgery is an important variable to ensure successful outcomes. In the authors' experience, a valuable method to visualize pain/trigger sites is to ask patients to draw their pain. The authors have found that there are pathognomonic pain patterns for each site, and typically do not operate on patients with atypical pain sketches, as they believe such patients are poor surgical candidates. However, a small subset of these atypical patients undergo surgery based on other strong clinical findings. In this study, the authors attempt to quantify this clinical experience.

METHODS

Patients were prospectively enrolled and completed pain sketches at screening. One hundred six diagrams were analyzed/categorized by two independent, blinded reviewers as follows: (1) typical (pain over nerve distribution, expected radiation); (2) intermediate (pain over nerve distribution, atypical radiation); or (3) atypical (pain outside of normal nerve distribution, atypical radiation). Preoperative and postoperative Migraine Headache Index was compared between subgroups using unpaired t tests.

RESULTS

Migraine Headache Index improvement was 73 ± 38 percent in the typical group, 78 ± 30 percent in the intermediate group, and 30 ± 40 percent in the atypical group. There was a significant difference in Migraine Headache Index between the typical and atypical groups (p = 0.03) and between the intermediate and atypical groups (p < 0.01). The chance of achieving Migraine Headache Index improvement greater than 30 percent in the atypical group was 20 percent.

CONCLUSIONS

Patient pain sketches classified as atypical (facial pain, atypical pain point origin, diffuse pain) can predict poor outcomes in headache surgery. As the authors continue to develop patient selection criteria for headache surgery, patient sketches should be considered as an effective, cheap, and simple-to-interpret tool for selecting candidates for surgery.

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.

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

Background

In a pain drawing (PD), the patient shades or marks painful areas on an illustration of the human body. This simple yet powerful tool captures essential aspects of the subjective pain experience, such as localization, intensity, and distribution of pain, and enables the extraction of meaningful information, such as pain area, widespreadness, and segmental pattern. Starting as a simple pen-on-paper tool, PDs are now sophisticated digital health applications paving the way for many new and exciting basic translational and clinical applications.

Objective

Grasping the full potential of digital PDs and laying the groundwork for future medical PD apps requires an understanding of the methodological developments that have shaped our current understanding of uses and design. This review presents methodological milestones in the development of both pen-on-paper and digital PDs, thereby offering insight into future possibilities created by the transition from paper to digital.

Methods

We conducted a systematic literature search covering PD acquisition, conception of PDs, PD analysis, and PD visualization.

Results

The literature search yielded 435 potentially relevant papers, from which 53 methodological milestones were identified. These milestones include, for example, the grid method to quantify pain area, the pain-frequency maps, and the use of artificial neural networks to facilitate diagnosis.

Conclusions

Digital technologies have had a significant influence on the evolution of PDs, whereas their versatility is leading to ever new applications in the field of medical apps and beyond. In this process, however, there is a clear need for better standardization and a re-evaluation of methodological and technical limitations that no longer apply today.