More Insight on the Role of Personality Traits and Sensitivity to Experimental Pain

Unpacking the relationship between Big Five personality traits and experimental pain: A systematic review and meta-analysis

Pain is essential for survival, but individual responses to painful stimuli vary, representing a complex interplay between sensory, cognitive, and affective factors. Individual differences in personality traits and in pain perception covary but it is unclear which traits play the most significant role in understanding the pain experience and whether this depends on pain modality. A systematic search identified 1534 records (CINAHL, MEDLINE, PsycInfo, PubMed and Web of Science), of which 22 were retained and included in a systematic review. Only studies from the pressure pain domain (n=6) could be compared in a formal meta-analysis to evaluate the relationship between Big Five traits and experimental pain. Pressure pain tolerance correlated positively with Extraversion and negatively with Neuroticism with a trivial effect size (<0.1). While these findings suggest personality might be only weakly related to pain in healthy individuals, we emphasize the need to consider standardization, biases, and adequate sample sizes in future research, as well as additional factors that might affect experimental pain sensitivity.

Effect of verbal and written information on the perception of pain and analgesic consumption, in adolescent orthodontic patients: A randomised controlled trial

OBJECTIVE

To investigate the impact of written instructions, about post-bonding pain, on patients' pain perception and analgesic consumption and to evaluate the correlation of pain with personality types.

DESIGN

Two-arm parallel randomised controlled trial.

SETTING

University Hospital Centre Zagreb, Zagreb, Croatia.

METHODS

Participants included adolescents in the permanent dentition with mild or moderate crowding.

RANDOMISATION

The participants were randomly allocated, using computer-generated random list, into two groups.

INTERVENTIONS

After bonding and archwire insertion, all participants received oral instructions on potential pain occurrence and pain control. Participants in the study group also received written information on post-bonding pain.

OUTCOMES

Pain intensity was evaluated using the Numerical Rating Scale immediately after (T0), 2 days (T1) and 7 days (T2) after the placement of the fixed orthodontic appliance. Analgesic consumption was assessed as yes or no, and personality traits were assessed using the Big Five Inventory. Operators who scored pain intensity and recorded analgesic consumption and personality traits were blinded to the group allocation. Statistical analyses included the t-test, Mann-Whitney U-test, Spearman correlations and stepwise regression analysis.

RESULTS

The highest rate of pain was recorded at T1 (P < 0.001). No statistically significant difference in pain perception between groups was observed. There was no statistically significant difference in analgesic consumption between the two groups (P = 0.81). The correlations between personality traits and pain perception were not significant.

CONCLUSION

The additional written information had little impact on pain perception, and it had no relationship to personality types. The perception of pain and analgesic consumption were not affected by the provision of additional written information (P = 0.81). Participants' personality types did not affect the impact of the information given.

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.

Bidirectional Mendelian Randomization Study of Personality Traits Reveals a Positive Feedback Loop Between Neuroticism and Back Pain

We conducted a bidirectional Mendelian randomization study to examine the causal effects of six personality traits (anxiety, neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness) on back pain associated with health care use and the causal effect of back pain on the same risk factors. Genetic instruments for the personality traits and back pain were obtained from the largest published genome-wide association studies conducted in individuals of European ancestry. We used inverse weighted variance meta-analysis and Causal Analysis Using Summary Effect for primary analyses and sensitivity analyses to examine evidence for causal associations. We interpreted exposure-outcome associations as being consistent with a causal relationship if results of at least one primary analysis were statistically significant after accounting for multiple statistical testing (P-value < .0042), and the direction and magnitude of effect estimates were concordant between primary and sensitivity analyses. We found evidence for statistically significant bidirectional causal associations between neuroticism and back pain, with odds ratio 1.51 (95% confidence interval 1.37; 1.67) of back pain per neuroticism sum score standard deviation, P-value = 7.80e-16; and beta = .12, se = .04 of neuroticism sum score standard deviation per log odds of back pain, P-value = 2.48e-03. Other relationships did not meet our predefined criteria for causal association. PERSPECTIVE: The significant positive feedback loop between neuroticism and back pain highlights the importance of considering neuroticism in the management of patients with back pain.

Modulation of vestibular input by short-term head-down bed rest affects somatosensory perception: implications for space missions

Introduction

On Earth, self-produced somatosensory stimuli are typically perceived as less intense than externally generated stimuli of the same intensity, a phenomenon referred to as somatosensory attenuation (SA). Although this phenomenon arises from the integration of multisensory signals, the specific contribution of the vestibular system and the sense of gravity to somatosensory cognition underlying distinction between self-generated and externally generated sensations remains largely unknown. Here, we investigated whether temporary modulation of the gravitational input by head-down tilt bed rest (HDBR)-a well-known Earth-based analog of microgravity-might significantly affect somatosensory perception of self- and externally generated stimuli.

Methods

In this study, 40 healthy participants were tested using short-term HDBR. Participants received a total of 40 non-painful self- and others generated electrical stimuli (20 self- and 20 other-generated stimuli) in an upright and HDBR position while blindfolded. After each stimulus, they were asked to rate the perceived intensity of the stimulation on a Likert scale.

Results

Somatosensory stimulations were perceived as significantly less intense during HDBR compared to upright position, regardless of the agent administering the stimulus. In addition, the magnitude of SA in upright position was negatively correlated with the participants' somatosensory threshold. Based on the direction of SA in the upright position, participants were divided in two subgroups. In the subgroup experiencing SA, the intensity rating of stimulations generated by others decreased significantly during HDBR, leading to the disappearance of the phenomenon of SA. In the second subgroup, on the other hand, reversed SA was not affected by HDBR.

Conclusion

Modulation of the gravitational input by HDBR produced underestimation of somatosensory stimuli. Furthermore, in participants experiencing SA, the reduction of vestibular inputs by HDBR led to the disappearance of the SA phenomenon. These findings provide new insights into the role of the gravitational input in somatosensory perception and have important implications for astronauts who are exposed to weightlessness during space missions.

Using AI to Detect Pain through Facial Expressions: A Review

Pain assessment is a complex task largely dependent on the patient's self-report. Artificial intelligence (AI) has emerged as a promising tool for automating and objectifying pain assessment through the identification of pain-related facial expressions. However, the capabilities and potential of AI in clinical settings are still largely unknown to many medical professionals. In this literature review, we present a conceptual understanding of the application of AI to detect pain through facial expressions. We provide an overview of the current state of the art as well as the technical foundations of AI/ML techniques used in pain detection. We highlight the ethical challenges and the limitations associated with the use of AI in pain detection, such as the scarcity of databases, confounding factors, and medical conditions that affect the shape and mobility of the face. The review also highlights the potential impact of AI on pain assessment in clinical practice and lays the groundwork for further study in this area.

Evaluation of the Analgesic Efficacy of Undiluted Intraperitoneal and Incisional Ropivacaine for Postoperative Analgesia in Dogs after Major Abdominal Surgery

Recommendations for intraperitoneal (IP) and incisional (INC) administration of local anaesthetics after visceral surgery exist, but evidence is scarce. This prospective, randomized, blinded, controlled, clinical trial compared postoperative pain in dogs undergoing major abdominal surgery. Sixteen client-owned dogs were anaesthetized with a standardized balanced protocol including opioids and received either 2 mg/kg ropivacaine IP (0.27 mL/kg) and a 1 mg/kg INC splash (0.13 mL/kg) or equal volumes of saline. Influence of the treatment on heart rate (HR) and postoperative pain was assessed using the Short Form of the Glasgow Composite Pain Scale (GCPS-SF), a dynamic interactive visual analogue scale (DIVAS) and mechanical nociceptive threshold testing (MNT). Data was tested with mixed ordinal regression and log linear mixed models for 0.5, 1, 2, 3, 4, 6, 8, 10 and 12 h after extubation. Rescue analgesia was given to 3/8 dogs after ropivacaine and 0/8 dogs after saline. GCPS-SF and MNT were not different between groups. DIVAS was slightly higher after ropivacaine (odds increased by 5.44 (confidence interval (CI) 1.17-9.96, p = 0.012)), and HR after ropivacaine was 0.76 * that after saline (CI 0.61-0.96, p = 0.02) with no effect of time (p = 0.1). Undiluted ropivacaine IP and INC was not beneficial for postoperative analgesia.

Machine Learning Based on Event-Related EEG of Sustained Attention Differentiates Adults with Chronic High-Altitude Exposure from Healthy Controls

(1) Objective: The aim of this study was to examine the effect of high altitude on inhibitory control processes that underlie sustained attention in the neural correlates of EEG data, and explore whether the EEG data reflecting inhibitory control contain valuable information to classify high-altitude chronic hypoxia and plain controls. (2) Methods: 35 chronic high-altitude hypoxic adults and 32 matched controls were recruited. They were required to perform the go/no-go sustained attention task (GSAT) using event-related potentials. Three machine learning algorithms, namely a support vector machine (SVM), logistic regression (LR), and a decision tree (DT), were trained based on the related ERP components and neural oscillations to build a dichotomous classification model. (3) Results: Behaviorally, we found that the high altitude (HA) group had lower omission error rates during all observation periods than the low altitude (LA) group. Meanwhile, the ERP results showed that the HA participants had significantly shorter latency than the LAs for sustained potential (SP), indicating vigilance to response-related conflict. Meanwhile, event-related spectral perturbation (ERSP) analysis suggested that lowlander immigrants exposed to high altitudes may have compensatory activated prefrontal cortexes (PFC), as reflected by slow alpha, beta, and theta frequency-band neural oscillations. Finally, the machine learning results showed that the SVM achieved the optimal classification F1 score in the later stage of sustained attention, with an F1 score of 0.93, accuracy of 92.54%, sensitivity of 91.43%, specificity of 93.75%, and area under ROC curve (AUC) of 0.97. The results proved that SVM classification algorithms could be applied to identify chronic high-altitude hypoxia. (4) Conclusions: Compared with other methods, the SVM leads to a good overall performance that increases with the time spent on task, illustrating that the ERPs and neural oscillations may provide neuroelectrophysiological markers for identifying chronic plateau hypoxia.

The Effect of Electrical Stimulation-Induced Pain on Time Perception and Relationships to Pain-Related Emotional and Cognitive Factors: A Temporal Bisection Task and Questionnaire-Based Study

Pain has not only sensory, but also emotional and cognitive, components. Some studies have explored the effect of pain on time perception, but the results remain controversial. Whether individual pain-related emotional and cognitive factors play roles in this process should also be explored. In this study, we investigated the effect of electrical stimulation–induced pain on interval timing using a temporal bisection task. During each task session, subjects received one of five types of stimulation randomly: no stimulus and 100 and 300 ms of non-painful and painful stimulation. Pain-related emotional and cognitive factors were measured using a series of questionnaires. The proportion of “long” judgments of a 1,200-ms visual stimulus duration was significantly smaller with 300 ms painful stimulation than with no stimulus (P < 0.0001) and 100 ms (P < 0.0001) and 300 ms (P = 0.021) non-painful stimulation. The point of subjective equality (PSE) did not differ among sessions, but the average Weber fraction (WF) was higher for painful sessions than for no-stimulus session (P = 0.022). The pain fear score correlated positively with the PSE under 100 ms non-painful (P = 0.031) and painful (P = 0.002) and 300 ms painful (P = 0.006) stimulation. Pain catastrophizing and pain anxiety scores correlated significantly with the WF under no stimulus (P = 0.005) and 100 ms non-painful stimulation (P = 0.027), respectively. These results suggest that electrical stimulation–induced pain affects temporal sensitivity, and that pain-related emotional and cognitive factors are associated with the processing of time perception.