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

Italian versions of the Neurophysiology of Pain Questionnaire (NPQ): psychometric properties and an investigation on the understanding of pain neurophysiology in physical therapists

OBJECTIVES

The Neurophysiology of Pain Questionnaire (NPQ) is widely used to assess pain knowledge among clinicians and patients with pain, but an Italian version is not available. This study aimed to translate and cross-culturally adapt the NPQ into Italian, to test its psychometric properties, to assess the knowledge of Italian physical therapists (PTs) on pain, and to evaluate which characteristics are associated with pain knowledge.

METHODS

The NPQ was translated into Italian, integrated with some additional questions (IT-NPQ-New), and sent by email via the Italian Association of Physiotherapy newsletter. Rasch analysis (RA) was used to test the psychometric properties of the Italian versions. Multivariable regression analyses were used to check for associations between participants' characteristics and their NPQ scores.

RESULTS

A sample of 753 PTs completed the survey. RA of the NPQ-19 and IT-NPQ-New revealed that 10 (IT-NPQ-10) and 18 (IT-NPQ-18) items fit the model. Both questionnaires showed good psychometric properties. The overall median score among Italian PTs was 6.0 [5.0-7.0] and 11.0 [9.0-13.0] points for the IT-NPQ-10 and the IT-NPQ-18, respectively. These scores were statistically different among groups according to gender, age, years of professional activity, post-graduate specialization and days attended of targeted pain courses, with the latter being the most influential variable.

CONCLUSIONS

Italian PTs now dispose of two tools to assess their basic knowledge related to pain science. Our study also showed that pain knowledge among Italian PTs needs improvement, especially considering recent biopsychosocial approaches to pain.

Novel neurophysiological evidence for preserved pain habituation across chronic pain conditions

OBJECTIVE

The present study aimed to investigate whether subjective and objective measures of pain habituation can be used as potential markers for central sensitization across various chronic pain patients.

METHODS

Two blocks of contact-heat stimuli were applied to a non-painful area in 93 chronic pain patients (low back pain, neuropathic pain, and complex regional pain syndrome) and 60 healthy controls (HC). Habituation of pain ratings, contact-heat evoked potentials (CHEP), and sympathetic skin responses (SSR) was measured.

RESULTS

There was no significant difference in any measure of pain habituation between patients and HC. Even patients with apparent clinical signs of central sensitization showed no reduced pain habituation. However, prolonged baseline CHEP and SSR latencies (stimulation block 1) were found in patients compared to HC (CHEP: Δ-latency = 23 ms, p = 0.012; SSR: Δ-latency = 100 ms, p = 0.022).

CONCLUSION

Given the performed multimodal neurophysiological testing protocol, we provide evidence indicating that pain habituation may be preserved in patients with chronic pain and thereby be of limited use as a sensitive marker for central sensitization. These results are discussed within the framework of the complex interactions between pro- and antinociceptive mechanism as well as methodological issues. The prolonged latencies of CHEP and SSR after stimulation in non-painful areas may indicate subclinical changes in the integrity of thermo-nociceptive afferents, or a shift towards antinociceptive activity. This shift could potentially affect the relay of ascending signals.

SIGNIFICANCE

Our findings challenge the prevailing views in the literature and may encourage further investigations into the peripheral and central components of pain habituation, using advanced multimodal neurophysiological techniques.

Incorporation of "Artificial Intelligence" for Objective Pain Assessment: A Comprehensive Review

Pain is a significant health issue, and pain assessment is essential for proper diagnosis, follow-up, and effective management of pain. The conventional methods of pain assessment often suffer from subjectivity and variability. The main issue is to understand better how people experience pain. In recent years, artificial intelligence (AI) has been playing a growing role in improving clinical diagnosis and decision-making. The application of AI offers promising opportunities to improve the accuracy and efficiency of pain assessment. This review article provides an overview of the current state of AI in pain assessment and explores its potential for improving accuracy, efficiency, and personalized care. By examining the existing literature, research gaps, and future directions, this article aims to guide further advancements in the field of pain management. An online database search was conducted via multiple websites to identify the relevant articles. The inclusion criteria were English articles published between January 2014 and January 2024). Articles that were available as full text clinical trials, observational studies, review articles, systemic reviews, and meta-analyses were included in this review. The exclusion criteria were articles that were not in the English language, not available as free full text, those involving pediatric patients, case reports, and editorials. A total of (47) articles were included in this review. In conclusion, the application of AI in pain management could present promising solutions for pain assessment. AI can potentially increase the accuracy, precision, and efficiency of objective pain assessment.

Novel dental anesthetic and associated devices: a scoping review

The efficient management of pain and discomfort is essential for successful dental treatment and patient compliance. Dental professionals are commonly evaluated for their ability to perform treatment with minimal patient discomfort. Despite advancements in traditional local dental anesthesia techniques, the pain and discomfort associated with injections remain a concern. This scoping review aims to provide a comprehensive overview of the literature on novel dental anesthetics and associated devices designed to alleviate pain and discomfort during dental procedures. The Joanna Briggs Institute and the Preferred Reporting Items for Systematic reviews and Meta-Analyses Extension for Scoping Reviews guidelines were used to prepare the review. Six databases and two sources of gray literature were searched. This review analyzed 107 sources from 1994 to 2023. Local anesthesia devices were grouped into computer-controlled local anesthetic delivery (CCLAD) systems, intraosseous anesthesia (IOA), vibratory stimulation devices, and electronic dental anesthesia (EDA). CCLAD systems, particularly the Wand and Single-Tooth Anesthesia, have been the most researched, with mixed results regarding their effectiveness in reducing pain during needle insertion compared to traditional syringes. However, CCLAD systems often demonstrated efficacy in reducing pain during anesthetic deposition, especially during palatal injections. Limited studies on IOA devices have reported effective pain alleviation. Vibrating devices have shown inconsistent results in terms of pain reduction, with some studies suggesting their primary benefit is during needle insertion rather than during the administration phase. EDA devices are effective in reducing discomfort but have found limited applicability. These findings suggest that the CCLAD systems reduce injection pain and discomfort. However, the evidence for other devices is limited and inconsistent. The development and research of innovative technologies for reducing dental pain and anxiety provides opportunities for interdisciplinary collaboration and improved patient care in dental practice.

How to make calibration less painful-A proposition for an automatic, reliable and time-efficient procedure

In behavioral and neurophysiological pain studies, multiple types of calibration methods are used to quantify the individual pain sensation stimuli. Often, studies lack a detailed calibration procedure description, data linearity, and quality quantification and omit required control for sex pain differences. This hampers study repetition and interexperimental comparisons. Moreover, typical calibration procedures require a high number of stimulations, which may cause discomfort and stimuli habituation among participants. To overcome those shortcomings, we present an automatic calibration procedure with a novel stimuli estimation method for intraepidermal stimulation. We provide an in-depth data analysis of the collected self-reports from 70 healthy volunteers (37 males) and propose a method based on a dynamic truncated linear regression model (tLRM). We compare its estimates for the sensation (t) and pain (T) thresholds and mid-pain stimulation (MP), with those calculated using traditional estimation methods and standard linear regression models. Compared to the other methods, tLRM exhibits higher R2 and requires 36% fewer stimuli applications and has significantly higher t intensity and lower T and MP intensities. Regarding sex differences, t and T were found to be lower for females compared to males, regardless of the estimation method. The proposed tLRM method quantifies the calibration procedure quality, minimizes its duration and invasiveness, and provides validation of linearity between stimuli intensity and subjective scores, making it an enabling technique for further studies. Moreover, our results highlight the importance of control for sex in pain studies.

Applied Artificial Intelligence in Healthcare: A Review of Computer Vision Technology Application in Hospital Settings

Computer vision (CV), a type of artificial intelligence (AI) that uses digital videos or a sequence of images to recognize content, has been used extensively across industries in recent years. However, in the healthcare industry, its applications are limited by factors like privacy, safety, and ethical concerns. Despite this, CV has the potential to improve patient monitoring, and system efficiencies, while reducing workload. In contrast to previous reviews, we focus on the end-user applications of CV. First, we briefly review and categorize CV applications in other industries (job enhancement, surveillance and monitoring, automation, and augmented reality). We then review the developments of CV in the hospital setting, outpatient, and community settings. The recent advances in monitoring delirium, pain and sedation, patient deterioration, mechanical ventilation, mobility, patient safety, surgical applications, quantification of workload in the hospital, and monitoring for patient events outside the hospital are highlighted. To identify opportunities for future applications, we also completed journey mapping at different system levels. Lastly, we discuss the privacy, safety, and ethical considerations associated with CV and outline processes in algorithm development and testing that limit CV expansion in healthcare. This comprehensive review highlights CV applications and ideas for its expanded use in healthcare.

The Verbal Numerical Rating Scale and Faces Pain Scale-Revised for Children With Acute Pain: A Comparative Study for Determining the Need for Analgesia

Introduction The primary complaint in all age groups of patients, including children, is pain, which drives the patient to the hospital. A good assessment of pain severity is necessary to determine the right therapy for this primary complaint. Pain scales, especially in children, are given little importance in all hospitals in India. We need more data about its effectiveness. As a result, we conducted this study to compare the effectiveness of two pain scales in an admitted patient. Methods An observational study was conducted on pediatric patients aged 8-17 admitted to a tertiary care unit in pediatric wards included in the study. The study team identified the participants with painful and nonpainful conditions by asking patients of the above age group if they had "any pain" or "any hurt." The verbal numerical rating scale (vNRS) was determined by asking, "On a scale of zero to 10, where zero signifies no pain and ten means severe pain." The child was advised to select from among the six faces using the faces pain scale-revised (FPS-R), showing increasing levels of pain intensity (from left to right), with score options 0, 2, 4, 6, 8, and 10 demonstrated below each face. Result We enrolled 140 children, of which 22 of vNRS and 15 of FPS-R were removed from the study as these children did not understand vNRS and FPS-R. The two-tailed t-test revealed that the p-value was 0.9144. By conventional criteria, in the context of statistical analysis, conventional criteria typically refer to commonly accepted thresholds for determining statistical significance. The most common threshold for significance is a p-value of 0.05 or less. In the provided scenario, the two-tailed t-test resulted in a p-value of 0.9144. By conventional criteria (i.e., using the threshold of 0.05), this p-value is considered not significant. This means that there is not enough evidence to reject the null hypothesis, which suggests that there is no significant difference between the two groups being compared (in this case, the efficacy and reliability of the two scales). Therefore, based on conventional criteria, the difference in efficacy and reliability between the two scales is considered not significant, indicating that they are likely to be equally effective and reliable. This difference is considered not significant. Hence, it is suggestive of equal efficacy and reliability on both scales.  Conclusion Pain scales are a practical guide for managing and recognizing pain in children. It needs to be considered in identifying children's pain. They can provide a valuable outcome for measuring pain, which, when practiced regularly, can save time and extra burden on health staff. In the present study, both pain scales (vNRS and FPR-R) have equal efficacy.

Novel Techniques for Musculoskeletal Pain Management after Orthopedic Surgical Procedures: A Systematic Review

Effective postoperative pain management is critical for recovery after orthopedic surgery, but often remains inadequate despite multimodal analgesia. This systematic review synthesizes evidence on innovative modalities for enhancing pain control following major orthopedic procedures. Fifteen randomized controlled trials and comparative studies evaluating peripheral nerve blocks, local anesthetic infiltration, cryotherapy, transcutaneous electrical stimulation, adjunct medications, and other techniques are included. Thematic analysis reveals that peripheral nerve blocks and local anesthetic infiltration consistently demonstrate reduced pain scores, opioid consumption, and side effects versus conventional analgesia alone. Oral multimodal medications also show promise as part of opioid-sparing regimens. Adjunctive approaches like cryotherapy, music, and dexmedetomidine require further research to optimize protocols. Despite promising innovations, critical knowledge gaps persist regarding comparative effectiveness, optimal interventions and dosing, combination strategies, cost-effectiveness, and implementation. High-quality randomized controlled trials using standardized protocols are essential to guide the translation of enhanced multimodal regimens into clinical practice. This review provides a framework for pursuing research priorities and advancing evidence-based postoperative pain management across orthopedic surgeries.

The Challenges of Pain Assessment in Geriatric Patients With Dementia: A Review

Pain in dementia patients is common, poorly measured, and undertreated. It is important to discuss the challenges in the pain assessment and management to find a possible solution for adequate pain management. The aim of this article is to discuss the challenges in the assessment of pain in geriatric patients with dementia. An extensive online database search was conducted via multiple websites using the following keywords: "dementia," "pain assessments," "pain assessment with dementia," "causes of pain with dementia," "pain assessments using recent technology," "geriatric," and "old age" to identify the relevant articles. Our inclusion criteria were articles that focused on pain in geriatric patients diagnosed with dementia, in English, published between January 2018 and January 2023, and available as free full text and those which were clinical trials, observational studies, review articles, systemic reviews, meta-analysis, or case series. The exclusion criteria were articles that did not have pain in geriatric patients diagnosed with dementia as their primary focus, involving geriatric or non-geriatric patients with major psychological distress, not in the English language, not published between January 2018 and January 2023, and not available as free full-text and those which were case reports and editorial articles. After manually excluding the articles that did not meet our inclusion criteria, we ended up with 38 articles. In conclusion, any instruments have been made for the pain assessment in patients with dementia. The two most common tools used to assess pain in this vulnerable population are the Pain Assessment in Advanced Dementia (PAINAD) and Pain Assessment Checklist for Seniors with Limited Ability to Communicate (PACSLAC) scales. The utilization of new technology may offer promising solutions for the pain assessment in patients with dementia.

Pain Management in the Most Vulnerable Intellectual Disability: A Review

This review is made up of two parts; the first part discussing intellectual disability (ID) in general, while the second part covers the pain associated with intellectual disability and the challenges and practical tips for the management of pain associated with (ID). Intellectual disability is characterized by deficits in general mental abilities, such as reasoning, problem solving, planning, abstract thinking, judgment, academic learning, and learning from experience. ID is a disorder with no definite cause but has multiple risk factors, including genetic, medical, and acquired. Vulnerable populations such as individuals with intellectual disability may experience more pain than the general population due to additional comorbidities and secondary conditions, or at least the same frequency of pain as in the general population. Pain in patients with ID remains largely unrecognized and untreated due to barriers to verbal and non-verbal communication. It is important to identify patients at risk to promptly prevent or minimize those risk factors. As pain is multifactorial, thus, a multimodal approach using both pharmacotherapy and non-pharmacological management is often the most beneficial. Parents and caregivers should be oriented to this disorder, given adequate training and education, and be actively involved with the treatment program. Significant work to create new pain assessment tools to improve pain practices for individuals with ID has taken place, including neuroimaging and electrophysiological studies. Recent advances in technology-based interventions such as virtual reality and artificial intelligence are rapidly growing to help give patients with ID promising results to develop pain coping skills with effective reduction of pain and anxiety. Therefore, this narrative review highlights the different aspects regarding the current status of the pain associated with intellectual disability, with more emphasis on the recent pieces of evidence for the assessment and management of pain among populations with intellectual disability.

A Review of Voice-Based Pain Detection in Adults Using Artificial Intelligence

Pain is a complex and subjective experience, and traditional methods of pain assessment can be limited by factors such as self-report bias and observer variability. Voice is frequently used to evaluate pain, occasionally in conjunction with other behaviors such as facial gestures. Compared to facial emotions, there is less available evidence linking pain with voice. This literature review synthesizes the current state of research on the use of voice recognition and voice analysis for pain detection in adults, with a specific focus on the role of artificial intelligence (AI) and machine learning (ML) techniques. We describe the previous works on pain recognition using voice and highlight the different approaches to voice as a tool for pain detection, such as a human effect or biosignal. Overall, studies have shown that AI-based voice analysis can be an effective tool for pain detection in adult patients with various types of pain, including chronic and acute pain. We highlight the high accuracy of the ML-based approaches used in studies and their limitations in terms of generalizability due to factors such as the nature of the pain and patient population characteristics. However, there are still potential challenges, such as the need for large datasets and the risk of bias in training models, which warrant further research.

Sex Differences in Pain and Its Treatment

Pain is a highly personal experience. Pain is often considered to be a purely neurologic phenomenon, but in actuality, it is a combination of both sensory and emotional experiences. This has sometimes been translated clinically toward a more mechanistic approach to the assessment and treatment of pain instead of one that does not discount pain mechanisms, but also is more inclusive of the need for humanism - considering the individual. In today's medical environment, more than ever before there is a significant amount of attention being paid to educating clinicians to better understand that several physiological, neurophysiological, and psychosocial factors can significantly impact responses to pain. The composition of these factors will be unique to that individual's life narrative, context, sex, and prior life experiences. Thus, the concept that a templated approach to pain assessment and pharmacotherapeutic treatment planning should not be expected to provide optimal patient satisfaction and treatment outcomes in the majority. The hypotheses that there may be sex-based differences in the pain experience in a variety of ways including pain sensitivity, tolerance to pain, threshold at which something becomes painful, and the effectiveness of endogenous pain modulation systems are not new and have been well represented in the literature. This chapter reviews important key findings in the scientific literature with respect to sex-based differences in pain and pain responses to experimentally induced painful stimuli, pain experienced in commonly occurring painful medical conditions, and variations in responses to pain treatments. Possible explanations to account for observed differences or similarities will also be discussed.