Defining suffering in pain: a systematic review on pain-related suffering using natural language processing

ABSTRACT

Understanding, measuring, and mitigating pain-related suffering is a key challenge for both clinical care and pain research. However, there is no consensus on what exactly the concept of pain-related suffering includes, and it is often not precisely operationalized in empirical studies. Here, we (1) systematically review the conceptualization of pain-related suffering in the existing literature, (2) develop a definition and a conceptual framework, and (3) use machine learning to cross-validate the results. We identified 111 articles in a systematic search of Web of Science, PubMed, PsychINFO, and PhilPapers for peer-reviewed articles containing conceptual contributions about the experience of pain-related suffering. We developed a new procedure for extracting and synthesizing study information based on the cross-validation of qualitative analysis with an artificial intelligence-based approach grounded in large language models and topic modeling. We derived a definition from the literature that is representative of current theoretical views and describes pain-related suffering as a severely negative, complex, and dynamic experience in response to a perceived threat to an individual's integrity as a self and identity as a person. We also offer a conceptual framework of pain-related suffering distinguishing 8 dimensions: social, physical, personal, spiritual, existential, cultural, cognitive, and affective. Our data show that pain-related suffering is a multidimensional phenomenon that is closely related to but distinct from pain itself. The present analysis provides a roadmap for further theoretical and empirical development.

Pain and related suffering reduce attention toward others

BACKGROUND

It has been proposed that the expression of pain-related suffering may lead to an enhanced focus on oneself and reduced attention toward the external world. This study aimed at investigating whether experimentally induced painrelated suffering may lead persons to withdraw into themselves, causing a reduced focus on external stimuli as reflected by impaired performance in a facial recognition task and heightened perception of internal stimuli measured by interoceptive awareness.

METHODS

Thirty-two participants had to recognize different emotional facial expressions (neutral, sad, angry, happy), or neutral geometrical figures under conditions of no pain, low, and high prolonged pain intensities. Interoceptive accuracy was measured using a heartbeat-detection task prior to and following the pain protocol.

RESULTS

Males but not females were slower to recognize facial expressions under the condition of high painful stimulation compared to the condition of no pain. In both, male and female participants, the difficulty in recognizing another person's emotions from a facial expression was directly related to the level of suffering and unpleasantness experienced during pain. Interoceptive accuracy was higher after the pain experiment. However, neither the initial interoceptive accuracy nor the change were significantly related to the pain ratings.

CONCLUSIONS

Our results suggest that long-lasting and intense painful stimuli, which induce suffering, lead to attentional shifts leading to withdrawal from others. These findings contribute to a better understanding of the social dynamics of pain and pain-related suffering.

Measuring pain and nociception: Through the glasses of a computational scientist. Transdisciplinary overview of methods

In a healthy state, pain plays an important role in natural biofeedback loops and helps to detect and prevent potentially harmful stimuli and situations. However, pain can become chronic and as such a pathological condition, losing its informative and adaptive function. Efficient pain treatment remains a largely unmet clinical need. One promising route to improve the characterization of pain, and with that the potential for more effective pain therapies, is the integration of different data modalities through cutting edge computational methods. Using these methods, multiscale, complex, and network models of pain signaling can be created and utilized for the benefit of patients. Such models require collaborative work of experts from different research domains such as medicine, biology, physiology, psychology as well as mathematics and data science. Efficient work of collaborative teams requires developing of a common language and common level of understanding as a prerequisite. One of ways to meet this need is to provide easy to comprehend overviews of certain topics within the pain research domain. Here, we propose such an overview on the topic of pain assessment in humans for computational researchers. Quantifications related to pain are necessary for building computational models. However, as defined by the International Association of the Study of Pain (IASP), pain is a sensory and emotional experience and thus, it cannot be measured and quantified objectively. This results in a need for clear distinctions between nociception, pain and correlates of pain. Therefore, here we review methods to assess pain as a percept and nociception as a biological basis for this percept in humans, with the goal of creating a roadmap of modelling options.

Pain and the Triple Network Model

Acute pain is a physiological response that causes an unpleasant sensory and emotional experience in the presence of actual or potential tissue injury. Anatomically and symptomatically, chronic pathological pain can be divided into three distinct but interconnected pathways, a lateral “painfulness” pathway, a medial “suffering” pathway and a descending pain inhibitory circuit. Pain (fullness) can exist without suffering and suffering can exist without pain (fullness). The triple network model is offering a generic unifying framework that may be used to understand a variety of neuropsychiatric illnesses. It claims that brain disorders are caused by aberrant interactions within and between three cardinal brain networks: the self-representational default mode network, the behavioral relevance encoding salience network and the goal oriented central executive network. A painful stimulus usually leads to a negative cognitive, emotional, and autonomic response, phenomenologically expressed as pain related suffering, processed by the medial pathway. This anatomically overlaps with the salience network, which encodes behavioral relevance of the painful stimuli and the central sympathetic control network. When pain lasts longer than the healing time and becomes chronic, the pain- associated somatosensory cortex activity may become functionally connected to the self-representational default mode network, i.e., it becomes an intrinsic part of the self-percept. This is most likely an evolutionary adaptation to save energy, by separating pain from sympathetic energy-consuming action. By interacting with the frontoparietal central executive network, this can eventually lead to functional impairment. In conclusion, the three well-known pain pathways can be combined into the triple network model explaining the whole range of pain related co-morbidities. This paves the path for the creation of new customized and personalized treatment methods.

The anatomy of pain and suffering in the brain and its clinical implications

Pain is an unpleasant sensory and emotional experience associated with actual or potential tissue damage. Chronic pain, with a prevalence of 20-30 % is the major cause of human suffering worldwide, because effective, specific and safe therapies have yet to be developed. It is unevenly distributed among sexes, with women experiencing more pain and suffering. Chronic pain can be anatomically and phenomenologically dissected into three separable but interacting pathways, a lateral 'painfulness' pathway, a medial 'suffering' pathway and a descending pain inhibitory pathway. One may have pain(fullness) without suffering and suffering without pain(fullness). Pain sensation leads to suffering via a cognitive, emotional and autonomic processing, and is expressed as anger, fear, frustration, anxiety and depression. The medial pathway overlaps with the salience and stress networks, explaining that behavioural relevance or meaning determines the suffering associated with painfulness. Genetic and epigenetic influences trigger chronic neuroinflammatory changes which are involved in transitioning from acute to chronic pain. Based on the concept of the Bayesian brain, pain (and suffering) can be regarded as the consequence of an imbalance between the two ascending and the descending pain inhibitory pathways under control of the reward system. The therapeutic clinical implications of this simple pain model are obvious. After categorizing the working mechanisms of each of the available treatments (pain killers, psychopharmacology, psychotherapy, neuromodulation, psychosurgery, spinal cord stimulation) to 1 or more of the 3 pathways, a rational combination can be proposed of activating the descending pain inhibitory pathway in combination with inhibition of the medial and lateral pathway, so as to rebalance the pain (and suffering) pathways.

Patients´ experiences of pain in the intensive care - The delicate balance of control

AIM

To explore the patients´ experiences of pain when being cared for in the intensive care.

DESIGN

An exploratory, qualitative design was chosen.

METHOD

Interviews were performed with patients (October 2015-March 2017) within a week of post-intensive care (N = 16). Thematic analysis was used as method for analysis.

RESULTS

The findings generated two themes - a lack of control and to struggle for control. Pain was described as overwhelming, both in body and mind and generating the experience of a lack of control, with feelings of incapacitation, isolation, and having their needs unmet. Feeling in control of the pain and thus in control of the situation was experienced as a constant struggle. Well-planned care, finding ways to handle the pain and good communication were all helpful in this struggle.

CONCLUSION

The participants recalled their experience of pain in the ICU and control seems to be crucial for how pain is experienced. They experienced a lack of control due to not only the pain but also the treatment, which can be avoided by the nurse continuously evaluating and individualising the care. Balanced care, meeting the patients' needs and good communication helps the patient feel more in control when experiencing pain.

IMPACT

The experience of pain is dependent on control for the intensive care patient. The nurse may help them gain control and thereby handle the experience of pain through including the patient, striving for better communication and implementing individualised care that continuously assesses and treats pain.

Deconstructing chronicity of musculoskeletal pain: intensity-duration relations, minimal dimensions and clusters of chronicity

Background and aims Evaluating the degree to which pain has become chronic beyond mere duration poses several problems. The IASP Pain Taxonomy Axis IV employs intensity and duration combined to nine ordered categories. The Chronic Pain Grade links intensity and disability, but only the latter contributes to higher grades. The Mainz Pain Staging System includes temporal and spatial aspects, medication and health care utilization. Their interrelations, scale properties and construct validity are not always known or debatable. The study challenges the generality and homogeneity of the chronicity construct of musculoskeletal pain aiming at necessary and sufficient sub-constructs identified by separable marker clusters. We show chronicity to vary in content and structure with severity and duration and between different populations. This raises the question of validity conditions of general chronicity indices and requires further work on adequate chronicity measures. Methods Diagnostic entrance data of 185 patients with chronic regional vs. widespread musculoskeletal pain (unspecific back pain, fibromyalgia) from regional pain clinics and 170 active employees in a nationwide prevention program were included in a retrospective cross-sectional analysis of the combined marker sets of the three chronicity indices above. The samples of patients and employees provided intensity, duration and disability degrees over the whole range of the assumed chronicity. Intensity-duration relations were quantified by correlations and frequency distributions of successive duration classes. The dimensional structure of pain and chronicity variables was assessed by factor and cluster analyses. Results Pain intensity distributions showed inhomogeneous courses from short to long durations - lowest intensities predominating at longer durations in patients and at shorter in employees. Moreover, pain intensity and duration related nonlinearly to Chronic Pain Grade and Mainz Pain Stage and differently in patients compared to employees, and these indices correlated only moderately to each other. Factor and cluster analyses revealed different dimensions and clusters of chronicity markers for patients and employees. In the former, three dimensions with four clusters were identified with clinical characteristics (intensity, temporal and spatial aspects) separated from direct consequences (disability/interference with activities, medication usage) and chronic development (duration, healthcare utilization). In employees, only two dimensions with three clusters were obtained and clinical pain characteristics clustered with direct consequences both separated from chronic development. Similar differences were shown between unspecific back pain and fibromyalgia but were less well defined. Conclusions There appears to be no coherent "chronicity" entity over the entire range of severity and duration for all pain populations with different clinical pictures and social contexts. Statements about chronicity must be differentiated with respect to those aspects relative to patient career. Implications General indices do not capture the complex and changing composition of chronicity. There is evidence for at least three weakly coupled core domains of chronicity, i.e. the primary clinical characteristics, the direct consequences of current interference with activities, and aspects of the patient history. Hence, multivariate assessment is recommended. The particular syndrome, the diagnostic context and the population under investigation should likewise be considered.

Impact of controllability on pain and suffering

Supplemental Digital Content is Available in the Text.

Introduction:

Chronic pain and pain-related suffering are major health problems. The lack of controllability of experienced pain seems to greatly contribute to the extent of suffering. This study examined how controllability affects the perception of pain and pain-related suffering, and the modulation of this effect by beliefs and emotions such as locus of control of reinforcement, pain catastrophizing, and fear of pain.

Methods:

Twenty-six healthy subjects received painful electric stimulation in both controllable and uncontrollable conditions. Visual analogue scales and the “Pictorial Representation of Illness and Self Measure” were used to assess pain intensity, unpleasantness, pain-related suffering, and the level of perceived control. We also investigated nonverbal indicators of pain and suffering such as heart rate, skin conductance, and corrugator electromyogram.

Results:

Controllability selectively reduced the experience of pain-related suffering, but did not affect pain intensity or pain unpleasantness. This effect was modulated by chance locus of control but was unrelated to fear of pain or catastrophizing. Physiological responses were not affected by controllability. In a second sample of 25 participants, we varied the instruction. The effect of controllability on pain-related suffering was only present when instructions focused on the person being able to stop the pain.

Discussion:

Our data suggest that the additional measure of pain-related suffering may be important in the assessment of pain and may be more susceptible to the effects of perceived control than pain intensity and unpleasantness. We also show that this effect depends on personal involvement.

Psychological, cognitive factors and contextual influences in pain and pain-related suffering as revealed by a combined qualitative and quantitative assessment approach

Previous psychophysiological research suggests that pain measurement needs to go beyond the assessment of Pain Intensity and Unpleasantness by adding the evaluation of Pain-Related Suffering. Based on this three-dimensional approach, we attempted to elucidate who is more likely to suffer by identifying reasons that may lead individuals to report Pain and Pain-Related Suffering more than others. A sample of 24 healthy participants (age range 18-33) underwent four different sessions involving the evaluation of experimentally induced phasic and tonic pain. We applied two decision tree models to identify variables (selected from psychological questionnaires regarding pain and descriptors from post-session interviews) that provided a qualitative characterization of the degrees of Pain Intensity, Unpleasantness and Suffering and assessed the respective impact of contextual influences. The overall classification accuracy of the decision trees was 75% for Intensity, 77% for Unpleasantness and 78% for Pain-Related Suffering. The reporting of suffering was predominantly associated with fear of pain and active cognitive coping strategies, pain intensity with bodily competence conveying strength and resistance and unpleasantness with the degree of fear of pain and catastrophizing. These results indicate that the appraisal of the three pain dimensions was largely determined by stable psychological constructs. They also suggest that individuals manifesting higher active coping strategies may suffer less despite enhanced pain and those who fear pain may suffer even under low pain. The second decision tree model revealed that suffering did not depend on pain alone, but that the complex rating-related decision making can be shifted by situational factors (context, emotional and cognitive). The impact of coping and fear of pain on individual Pain-Related Suffering may highlight the importance of improving cognitive coping strategies in clinical settings.

Suffering: The darker side of ageing

Much of the literature on ageing is presaged upon a model of advocacy that seeks to combat what is seen as the negative stereotyping of old age and old people. One consequence is that ageing studies has difficulty in confronting the darker side of ageing except in so far as age associated disability and distress can be attributed to extrinsic disadvantage, such as low income, poor housing and inadequate services. The pain and suffering associated with age itself tend to be neglected as subject experiences. This paper seeks to shed some light on these topics, considered under the general heading of 'suffering'. Suffering can be viewed from the perspective of moral philosophy of medicine and of the social sciences. Serving as a witness to suffering has been proposed as the basis for an ethics of human dignity and as a call upon the collective moral agency of the community. Whether or not one accepts such an ethical viewpoint, it seems important for students of ageing to acknowledge document and explore the place of suffering in later life.

Assessing Suffering in Experimental Pain Models

Abstract. Although suffering is a central issue in pain, there is only little research on this topic. The aim of this study was to assess suffering in an experimental context using various stimulation methods and durations, and to examine which psychological or psychophysiological measures covary with pain-related suffering. Twenty-one healthy volunteers participated in two experiments in which we used tonic thermal and phasic electric stimuli with short and long stimulus durations. The participants rated pain intensity, unpleasantness, and pain-related suffering on separate visual analog scales (VAS) and completed the Pictorial Representation of Illness and Self Measure (PRISM), originally developed to assess suffering in chronic illness. We measured heart rate, skin conductance responses (SCRs), and the electromyogram (EMG) of the musculus corrugator supercilii. For both heat and electric pain, we obtained high ratings on the suffering scale confirming that suffering can be evoked in experimental pain conditions. Whereas pain intensity and unpleasantness were highly correlated, both scales were less highly related to suffering, indicating that suffering is distinct from pain intensity and unpleasantness. Higher suffering ratings were associated with more pronounced fear of pain and increased private self-consciousness. Pain-related suffering was also related to high resting heart rate, increased SCR, and decreased EMG during painful stimulation. These results offer an approach to the assessment of suffering in an experimental setting using thermal and electric pain stimulation and shed light on its psychological and psychophysiological correlates.

Children with chronic stress-induced recurrent muscle pain have enhanced startle reaction

BACKGROUND

Children with recurrent pain of negative chronic stress origin from different locations have a characteristic pattern of tender points in the temporal, trapezoid, great pectoral and abdominal muscles. We tested the hypothesis that the startle reaction is activated in these children and that some of the startle-activated muscles are related to the tender point pattern and the recurrent pain.

METHODS

In children/adolescents, aged 10-17 years, 19 with recurrent psychosomatic pain (PAIN) and 23 controls (CON) we measured and analysed resting activity and acoustic startle response with electromyography (EMG) for the muscles involved in the pattern of tender points and also the lumbar erector spinae.

RESULTS

The PAIN group showed higher resting activity and higher acoustic startle response values than the CON group for all six muscles together regarding the mean amplitude in the initial 200 ms, and during the burst of activity, and longer burst duration and shorter burst latency. For PAIN versus CON, all separate muscles showed generally higher values of EMG amplitudes and burst durations, and shorter latencies for the burst onset in all measures; with significance or strong trends for several parameters and muscles.

CONCLUSION

For the first time in children with recurrent psychosomatic pain, increased resting activity and potentiated startle response were demonstrated in the muscles involved in the stress tender point pattern.

SIGNIFICANCE

This study demonstrates in adolescents how recurrent pain of negative stress origin from the head, stomach, back and chest is related to increased startle reaction and increased muscular tension in these regions. This study contributes to the understanding of the mechanisms underlying the global burden of recurrent pain.

Pain Intensity Recognition Rates via Biopotential Feature Patterns with Support Vector Machines

BACKGROUND

The clinically used methods of pain diagnosis do not allow for objective and robust measurement, and physicians must rely on the patient's report on the pain sensation. Verbal scales, visual analog scales (VAS) or numeric rating scales (NRS) count among the most common tools, which are restricted to patients with normal mental abilities. There also exist instruments for pain assessment in people with verbal and / or cognitive impairments and instruments for pain assessment in people who are sedated and automated ventilated. However, all these diagnostic methods either have limited reliability and validity or are very time-consuming. In contrast, biopotentials can be automatically analyzed with machine learning algorithms to provide a surrogate measure of pain intensity.

METHODS

In this context, we created a database of biopotentials to advance an automated pain recognition system, determine its theoretical testing quality, and optimize its performance. Eighty-five participants were subjected to painful heat stimuli (baseline, pain threshold, two intermediate thresholds, and pain tolerance threshold) under controlled conditions and the signals of electromyography, skin conductance level, and electrocardiography were collected. A total of 159 features were extracted from the mathematical groupings of amplitude, frequency, stationarity, entropy, linearity, variability, and similarity.

RESULTS

We achieved classification rates of 90.94% for baseline vs. pain tolerance threshold and 79.29% for baseline vs. pain threshold. The most selected pain features stemmed from the amplitude and similarity group and were derived from facial electromyography.

CONCLUSION

The machine learning measurement of pain in patients could provide valuable information for a clinical team and thus support the treatment assessment.