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

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.

Physical therapist perceptions and use of clinical pain mechanism assessment in the musculoskeletal setting: a survey analysis

BACKGROUND

A mechanism-based approach to the evaluation and management of pain has been suggested across disciplines in contemporary research. However, the translation of pain mechanism assessment strategies in research to clinical practice is unclear. This study sought to explore perceptions and use of clinical pain mechanism assessment by physical therapists managing musculoskeletal pain.

METHODS

This was an electronic cross-sectional survey. After initial development, refinement, and piloting for comprehensiveness, comprehensibility and relevance, the survey was disseminated to members of the Academy of Orthopaedic Physical Therapy via email listserv. Data was maintained anonymously using the online database REDCap. Descriptive statistics and Spearman's correlations for non-parametric data were analyzed for frequencies and associations across variables.

RESULTS

In total, 148 respondents completed all aspects of the survey. Respondent age ranged from 26 to 73 years, with a mean (SD) of 43.9 (12.0). Most respondents (70.8%) reported performing clinical pain mechanism assessments at least 'sometimes'. A majority (80.4%) believed clinical pain mechanism assessments are useful in guiding management strategies while 79.8% reported specifically choosing interventions to alter aberrant pain mechanisms. The most commonly used pain severity, physical examination testing and questionnaires were the numeric pain rating scale, pressure pain thresholds and pain diagrams, respectively. However, the vast majority of instruments to clinically assess pain mechanisms were performed by a small proportion of respondents (< 30%). There were no significant correlations between age, years of experience, highest earned degree, completion of advanced training or specialist certification and testing frequency.

CONCLUSION

The evaluation of pain mechanisms involved in the pain experience is becoming common in research. The clinical application of pain mechanism assessment is unclear. Based on the results of this survey, physical therapists in the orthopedic setting believe pain mechanism assessment is useful, but data suggests it is infrequently performed. Additional research to uncover clinician motivation related to pain mechanism assessment is warranted.

Determining the level of cervical radiculopathy: Agreement between visual inspection of pain drawings and magnetic resonance imaging

BACKGROUND AND AIMS

Pain drawings are commonly used in the clinical assessment of people with cervical radiculopathy. This study aimed to assess (1) the agreement of clinical interpretation of pain drawings and MRI findings in identifying the affected level of cervical radiculopathy, (2) the agreement of these predictions based on the pain drawing among four clinicians from two different professions (i.e., physiotherapy and surgery) and (3) the topographical pain distribution of people presenting with cervical radiculopathy (C4-C7).

METHODS

Ninety-eight pain drawings were obtained from a baseline assessment of participants in a randomized clinical trial, in which single-level cervical radiculopathy was determined using MRI. Four experienced clinicians independently rated each pain drawing, attributing the pain distribution to a single nerve root (C4-C7). A post hoc analysis was performed to assess agreement.

OUTCOME MEASURES

Percentage agreement and kappa values were used to assess the level of agreement. Topographic pain frequency maps were created for each cervical radiculopathy level as determined by MRI.

RESULTS

The radiculopathy level determined from the pain drawings showed poor overall agreement with MRI (mean = 35.7%, K = -0.007 to 0.139). The inter-clinician agreement ranged from fair to moderate (K = 0.212-0.446). Topographic frequency maps revealed that pain distributions were widespread and overlapped markedly between patients presenting with different levels cervical radiculopathy.

CONCLUSION

This study revealed a lack of agreement between the segmental level affected determined from the patient's pain drawing and the affected level as identified on MRI. The large overlap of pain and non-dermatomal distribution of pain reported by patients likely contributed to this result.

‘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.

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.