Temporal dynamics of pain: an application of regime-switching models to ecological momentary assessments in patients with rheumatic diseases

Day-to-day associations between pain intensity and sleep outcomes in an adult chronic musculoskeletal pain population: A systematic review

BACKGROUND

In individuals with chronic musculoskeletal pain, a reciprocal relationship between sleep and pain across short and long-term evaluations exists. Sleep influences pain levels, while the level of pain also impairs sleep. However, given the day-to-day variability of both sleep and pain intensity, assessing this relationship within a daily time frame should be considered.

OBJECTIVES

To systematically review the literature concerning the bidirectional day-to-day relationship between night-time sleep variables and day-time pain intensity in individuals with chronic musculoskeletal pain.

METHODS

A systematic search (final search on October 12, 2023) in four databases (PubMed, Web of Science, Embase, PsycInfo) identified eligible articles based on pre-defined criteria. Three independent reviewers executed data extraction and risk of bias assessment using the "Quality In Prognosis Studies" tool. The study findings were synthesized narratively.

RESULTS

Eleven articles (1014 study participants; 83 associations) were included. A bidirectional relationship between pain intensity and sleep was found. Nine articles indicated night-time sleep quality to be a more consistent predictor for next day pain intensity than vice versa.

CONCLUSION

Nonetheless the bidirectional day-to-day sleep-pain relationship in individuals with chronic musculoskeletal pain, results suggest that self-reported sleep quality has a stronger predictive value on pain intensity then vice versa.

Development and preliminary testing of a comprehensive Ecological Momentary Assessment of people with chronic pain

Ecological Momentary Assessment (EMA) is a data collection method to understand people's real-time experience in daily life. To date, no standard instrument exists to measure the pain experience using EMA that provides relevant information for most chronic pain conditions. The goal of this study was to fill this gap by developing a comprehensive EMA pain instrument (cEMAp). Drawing on extant validated retrospective pain measures, the items represented the following pain-relevant constructs: (1) pain intensity, (2) pain fluctuations and patterns, (3) time in pain, (4) pain sensations, (5) pain location, (6) focusing on pain and distraction, (7) pain behavior, (8) other pain sensations, (9) pain impact, (10) pain concerns, (11) causes of pain relief and exacerbations, and (12) pain typicality. Subsequently, interviews with fifty-three adults (mean age=57 years, SD=13.4; female: 74%) with chronic pain were conducted to confirm the relevance and appropriateness of the selected items for real-time pain measurement. We then created an electronic version of the instrument utilizing information from 2-h intervals. We examined its feasibility and acceptability in a 1-week EMA design in a separate sample of twenty adults with chronic pain (mean age=56 years, SD=14.2). Results showed that EMA completion time was reasonable (mean=3.8 min, SD=2.5). Participants reported that the prompts were non-disruptive, the questions overall captured their pain experience, and the frequent pain assessments were useful. We expect this new instrument will allow researchers and clinicians to paint a fine-grained and nuanced picture of people's everyday pain in a comprehensive and standardized way. PERSPECTIVE: This article presents the development of a new pain assessment based on Ecological Momentary Assessment to comprehensively measure chronic pain in daily life. Continued use and examination of the new instrument could facilitate standardization and comparability of momentary pain assessment methods across studies and chronic pain conditions.

Improving neuropathic pain treatment - by rigorous stratification from bench to bedside

Chronic pain is a constantly recurring and persistent illness, presenting a formidable healthcare challenge for patients and physicians alike. Current first-line analgesics offer only low-modest efficacy when averaged across populations, further contributing to this debilitating disease burden. Moreover, many recent trials for novel analgesics have not met primary efficacy endpoints, which is particularly striking considering the pharmacological advances have provided a range of highly relevant new drug targets. Heterogeneity within chronic pain cohorts is increasingly understood to play a critical role in these failures of treatment and drug discovery, with some patients deriving substantial benefits from a given intervention while it has little-to-no effect on others. As such, current treatment failures may not result from a true lack of efficacy, but rather a failure to target individuals whose pain is driven by mechanisms which it therapeutically modulates. This necessitates a move towards phenotypical stratification of patients to delineate responders and non-responders in a mechanistically driven manner. In this article, we outline a bench-to-bedside roadmap for this transition to mechanistically informed personalised pain medicine. We emphasise how the successful identification of novel analgesics is dependent on rigorous experimental design as well as the validity of models and translatability of outcome measures between the animal model and patients. Subsequently, we discuss general and specific aspects of human trial design to address heterogeneity in patient populations to increase the chance of identifying effective analgesics. Finally, we show how stratification approaches can be brought into clinical routine to the benefit of patients.

Randomized controlled trial of intrathecal oxytocin on speed of recovery after hip arthroplasty

ABSTRACT

Recovery from surgery is quicker in the postpartum period, and this may reflect oxytocin action in the spinal cord. We hypothesized that intrathecal injection of oxytocin would speed recovery from pain and disability after major surgery. Ninety-eight individuals undergoing elective total hip arthroplasty were randomized to receive either intrathecal oxytocin (100 μg) or saline. Participants completed diaries assessing pain and opioid use daily and disability weekly, and they wore an accelerometer beginning 2 weeks before surgery until 8 weeks after. Groups were compared using modelled, adjusted trajectories of these measures. The study was stopped early due to the lack of funding. Ninety patients received intrathecal oxytocin (n = 44) or saline (n = 46) and were included in the analysis. There were no study drug-related adverse effects. Modelled pain trajectory, the primary analysis, did not differ between the groups, either in pain on day of hospital discharge (intercept: -0.1 [95% CI: -0.8 to 0.6], P = 0.746) or in reductions over time (slope: 0.1 pain units per log of time [95% CI: 0-0.2], P = 0.057). In planned secondary analyses, postoperative opioid use ended earlier in the oxytocin group and oxytocin-treated patients walked nearly 1000 more steps daily at 8 weeks ( P < 0.001) and exhibited a clinically meaningful reduction in disability for the first 21 postoperative days ( P = 0.007) compared with saline placebo. Intrathecal oxytocin before hip replacement surgery does not speed recovery from worst daily pain. Secondary analyses suggest that further study of intrathecal oxytocin to speed functional recovery without worsening pain after surgery is warranted.

Automatic detection of pain using machine learning

Pain is one of the most common symptoms reported by individuals presenting to hospitals and clinics and is associated with significant disability and economic impacts; however, the ability to quantify and monitor pain is modest and typically accomplished through subjective self-report. Since pain is associated with stereotypical physiological alterations, there is potential for non-invasive, objective pain measurements through biosensors coupled with machine learning algorithms. In the current study, a physiological dataset associated with acute pain induction in healthy adults was leveraged to develop an algorithm capable of detecting pain in real-time and in natural field environments. Forty-one human subjects were exposed to acute pain through the cold pressor test while being monitored using electrocardiography. A series of respiratory and heart rate variability features in the time, frequency, and nonlinear domains were calculated and used to develop logistic regression classifiers of pain for two scenarios: (1) laboratory/clinical use with an F1 score of 81.9% and (2) field/ambulatory use with an F1 score of 79.4%. The resulting pain algorithms could be leveraged to quantify acute pain using data from a range of sources, such as ECG data in clinical settings or pulse plethysmography data in a growing number of consumer wearables. Given the high prevalence of pain worldwide and the lack of objective methods to quantify it, this approach has the potential to identify and better mitigate individual pain.

Little evidence for consistent initial elevation bias in self-reported momentary affect: A coordinated analysis of ecological momentary assessment studies

Response bias characterized by decreases in self-reported subjective states when measured repeatedly over short time-frames is a potential concern in social science. Recent work suggests that this initial elevation bias (IEB) is pronounced among young adult students' self-reports of affect when using ambulatory methods, but it is unclear if such bias extends broadly across samples, designs, and constructs. We examined the conditions wherein reliable and robust IEB may manifest by conducting a coordinated analysis of seven ecological momentary assessment (EMA) studies with diverse lifespan samples to test the generalizability of IEB across study designs and affective constructs (momentary negative and positive affect). Overall, evidence for substantial IEB across studies was weak. No reliable evidence emerged for IEB in negative affect, with evidence for a small magnitude IEB for positive affect when comparing initial reports with reports made 1 week later, although the latter was not evident in other comparisons and was attenuated to nonsignificance when controlling for temporal factors. The magnitude and direction of IEB varied, but in mostly nonsystematic ways, as a function of study design and affective valence. Meta-analytic summary revealed consistently low combined effect sizes (Cohen's ds ranging from -.05 to .14). We found little evidence that IEB in momentary affect is sufficiently reliable, robust, or generalizable across designs and constructs to pose broad and/or serious concerns for EMA studies. Nonetheless, we recommend systematically examining the potential for IEB across study designs and constructs to help identify the conditions/contexts where IEB may or may not manifest. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

An Ecological Momentary Assessment Study of Pain Intensity Variability: Ascertaining Extent, Predictors, and Associations With Quality of Life, Interference and Health Care Utilization Among Individuals Living With Chronic Low Back Pain

This ecological momentary assessment (EMA) study examined the extent of pain intensity variability among 140 individuals with chronic low back pain and explored predictors of such variability and psychosocial and health care utilization outcomes. Individuals completed momentary pain intensity reports (0-10 numeric rating scale) several times daily for two periods of seven consecutive days, one month apart. Participants also completed online questionnaires at baseline which tapped into pain characteristics, pain-related catastrophization, kinesiophobia, activity patterns, and depression and anxiety symptoms. Questionnaires assessing quality of life and health care utilization were administered online one month after completion of the last EMA report. Data were analyzed using linear hierarchical location-scale models. Results showed that pain intensity fluctuated over the course of a week as shown by an average standard deviation of 1.2. The extent of variability in pain intensity scores was heterogeneous across participants but stable over assessment periods. Patients' baseline characteristics along with psychosocial and health care utilization outcomes were not significantly associated with pain intensity variability. We conclude that pain intensity variability differs across patients yet correlates remain elusive. There is an important gap in our knowledge of what affects this variability. Future EMA studies should replicate and extend current findings. PERSPECTIVE: This study provides evidence indicating that there is substantial variability in momentary reports of pain intensity among individuals living with chronic low back pain. However, risk and protective factors for greater lability of pain are elusive as is evidence that greater pain intensity variability results in differential health care utilization.

Beyond Average: Providers' Assessments of Indices for Measuring Pain Intensity in Patients With Chronic Pain

Introduction: Effective clinical care for chronic pain requires accurate, comprehensive, meaningful pain assessment. This study investigated healthcare providers' perspectives on seven pain measurement indices for capturing pain intensity.

Methods: Semi-structured telephone interviews were conducted with a purposeful sample from four US regions of 20 healthcare providers who treat patients with chronic pain. The qualitative interview guide included open-ended questions to address perspectives on pain measurement, and included quantitative ratings of the importance of seven indices [average pain, worst pain, least pain, time in no/low pain, time in high pain, fluctuating pain, unpredictable pain]. Qualitative interview data were read, coded and analyzed for themes and final interpretation. Standard quantitative methods were used to analyze index importance ratings.

Results: Despite concerns regarding 10-point visual analog and numeric rating scales, almost all providers used them. Providers most commonly asked about average pain, although they expressed misgivings about patient reporting and the index's informational value. Some supplemented average with worst and least pain, and most believed pain intensity is best understood within the context of patient functioning. Worst pain received the highest mean importance rating (7.60), average pain the second lowest rating (5.65), and unpredictable pain the lowest rating (5.20).

Discussion: Assessing average pain intensity obviates obtaining clinical insight into daily contextual factors relating to pain and functioning. Pain index use, together with timing, functionality and disability, may be most effective for understanding the meaning to patients of high pain, how pain affects their life, how life affects their pain, and how pain changes and responds to treatment.

I. Indices of Pain Intensity Derived From Ecological Momentary Assessments: Rationale and Stakeholder Preferences

Pain assessment that fully represents patients' pain experiences is essential for chronic pain research and management. The traditional primary outcome measure has been a patient's average pain intensity over a time period. In this series of 3 articles, we examine whether pain assessment can be enhanced by considering additional outcome measures capturing temporal aspects of pain, such as pain maxima, duration, and variability. Ecological momentary assessment makes the assessment of such indices readily available. In this first article, we discuss the rationale for considering additional pain indices derived from ecological momentary assessment and examine which are most important to stakeholders. Patients (n = 32), clinicians (n = 20), and clinical trialists (n = 20) were interviewed about their preference rankings for Average, Worst, and Least Pain, Time in High Pain, Time in No/Low Pain, Pain Variability, and Pain Unpredictability. Each stakeholder group displayed a distinct preference hierarchy for different indices, and there were few commonalities between groups. Patients favored Worst Pain and Time in High Pain, followed by Pain Variability and Unpredictability. Trialists favored Average Pain, whereas clinicians favored Worst Pain. Results suggest that multiple temporal aspects of pain are relevant for stakeholders and should be considered when evaluating the efficacy of pain management. PERSPECTIVE: Examining which aspects of pain are most important to measure from the perspective of different stakeholders can facilitate efforts to include all relevant treatment outcomes. Our study suggests that multiple temporal aspects of pain intensity are important to stakeholders. This should be considered when evaluating the efficacy of pain management.

II. Indices of Pain Intensity Derived From Ecological Momentary Assessments and Their Relationships With Patient Functioning: An Individual Patient Data Meta-analysis

Pain intensity is a complex and dynamic experience. A focus on assessing patients' average pain levels may miss important aspects of pain that impact functioning in daily life. In this second of 3 articles investigating alternative indices of pain intensity derived from Ecological Momentary Assessments (EMA), we examine the indices' associations with physical and psychosocial functioning. EMA data from 10 studies (2,660 patients) were reanalyzed to construct indices of Average Pain, Maximum Pain, Minimum Pain, Pain Variability, Time in High Pain, Time in Low Pain, Pain after Wake-up. Three sets of individual patient data meta-analyses examined 1) the test-retest reliability of the pain indices, 2) their convergent validity in relation to physical functioning, fatigue, depression, mental health, and social functioning, and 3) the incremental validity of alternative indices above Average Pain. Reliabilities approaching or exceeding a level of .7 were observed for all indices, and most correlated significantly with all functioning domains, with small to medium effect sizes. Controlling for Average Pain, Maximum Pain and Pain Variability uniquely predicted all functioning measures, and Time in High Pain predicted physical and social functioning. We suggest that alternative pain indices can provide new perspectives for understanding functioning in chronic pain. PERSPECTIVE: Alternative summary measures of pain intensity derived from EMA have the potential to help better understand patients' pain experience. Utilizing EMA for the assessment of Maximum Pain, Pain Variability, and Time in High Pain may provide an enhanced window into the relationships between pain and patients' physical and psychosocial functioning.

III. Detecting Treatment Effects in Clinical Trials With Different Indices of Pain Intensity Derived From Ecological Momentary Assessment

Pain intensity represents the primary outcome in most pain clinical trials. Identifying methods to measure aspects of pain that are most sensitive to treatment may facilitate discovery of effective interventions. In this third of 3 articles examining alternative indices of pain intensity derived from ecological momentary assessments (EMA), we compare treatment effects based on Average Pain, Maximum Pain, Minimum Pain, Pain Variability, Time in High Pain, Time in Low Pain, and Pain After Wake-Up. We also examine which indices contribute to Patient Global Impressions of Change (PGIC). Data came from 2 randomized, double-blind, placebo-controlled trials examining the efficacy of milnacipran for fibromyalgia treatment; 2,084 patients provided >1 million EMA pain intensity ratings over 24 (Study 1) or 26 (Study 2) treatment weeks. Pain Variability and Time in High Pain produced significantly smaller treatment effects than Average Pain; other pain indices showed effects that were numerically smaller, but not significantly different from Average Pain. Changes in all pain indices were significantly associated with PGIC, with improvements in Maximum Pain and in Pain Variability offering small incremental contributions to understanding PGIC over Average Pain. Results suggest that different pain indices could be used to detect treatment effects in pain clinical trials. PERSPECTIVE: Alternative summary measures of pain intensity derived from EMA may broaden the scope of outcomes useful in pain clinical trials. In this analysis of a pharmacological treatment for fibromyalgia, most pain summary measures indicated similar effects; improvements in Maximum Pain and Pain Variability contributed to understanding PGIC over Average Pain.

Time series analysis of intensive longitudinal data in psychosomatic research: A methodological overview

Time series analysis of intensive longitudinal data provides the psychological literature with a powerful tool for assessing how psychological processes evolve through time. Recent applications in the field of psychosomatic research have provided insights into the dynamical nature of the relationship between somatic symptoms, physiological measures, and emotional states. These promising results highlight the intrinsic value of employing time series analysis, although application comes with some important challenges. This paper aims to present an approachable, non-technical overview of the state of the art on these challenges and the solutions that have been proposed, with emphasis on application towards psychosomatic hypotheses. Specifically, we elaborate on issues related to measurement intervals, the number and nature of the variables used in the analysis, modeling stable and changing processes, concurrent relationships, and extending time series analysis to incorporate the data of multiple individuals. We also briefly discuss some general modeling issues, such as lag-specification, sample size and time series length, and the role of measurement errors. We hope to arm applied researchers with an overview from which to select appropriate techniques from the ever growing variety of time series analysis approaches.

Recovery of physical activity after cesarean delivery and its relationship with pain

Pain and physical activity are tightly intertwined. Although their relationship has been explored in chronic pain conditions, we know little about the pattern of recovery in activity and its short- and long-term relationship with pain after surgery. We recruited 103 women undergoing elective cesarean delivery and acquired daily pain assessments and hourly steps in 98 of them for 2 months after surgery. Compliance was good, with 78% of subjects missing less than 7 days of activity. Study personnel required daily checking for compliance and 20 minutes per subject per week in study. Activity increased over the first 2 postoperative months in a log(time) manner. The slope of each modeled individual curve for activity was inversely correlated (r = -0.54; P < 0.0001) with worst daily pain. After removing these 2-month trends, pain and activity within an individual day were negatively associated with each point increase in pain being inversely associated with -119 steps (95% confidence interval [CI] = -214 to -25; P = 0.013). A patient's previous experience of pain was not associated with current activity as well as current activity was not associated with future pain scores. These data, although limited by the study of a single operation in a unique social circumstance with low risk of chronic postsurgical pain, demonstrate feasibility of measuring hourly activity for 2 months after surgery. Recovery from pain and inactivity are tightly correlated, and the negative relationship between within-day pain and activity without interday carryover relationships is in stark contrast to findings in chronic pain conditions.

EEG, behavioural and physiological recordings following a painful procedure in human neonates

We present a dataset of cortical, behavioural, and physiological responses following a single, clinically required noxious stimulus in a neonatal sample. Cortical activity was recorded from 112 neonates (29–47 weeks gestational age at study) using a 20-channel electroencephalogram (EEG), which was time-locked to a heel lance. This data is linked to pain-related behaviour (facial expression), physiology (heart rate, oxygenation) and a composite clinical score (Premature Infant Pain Profile, PIPP). The dataset includes responses to non-noxious sham and auditory controls. The infants’ relevant medical and pain history was collected up to the day of the study and recorded in an extensive database of variables including clinical condition at birth, diagnoses, medications, previous painful procedures, injuries, and selected maternal information. This dataset can be used to investigate the cortical, physiological, and behavioural pain-related processing in human infants and to evaluate the impact of medical conditions and experiences upon the infant response to noxious stimuli. Furthermore, it provides information on the formation of individual pain phenotypes.