Distinctive subgroups derived by cluster analysis based on pain and psychological symptoms in Swedish older adults with chronic pain - a population study (PainS65+)

Cracking the Chronic Pain code: A scoping review of Artificial Intelligence in Chronic Pain research

OBJECTIVE

The aim of this review is to identify gaps and provide a direction for future research in the utilization of Artificial Intelligence (AI) in chronic pain (CP) management.

METHODS

A comprehensive literature search was conducted using various databases, including Ovid MEDLINE, Web of Science Core Collection, IEEE Xplore, and ACM Digital Library. The search was limited to studies on AI in CP research, focusing on diagnosis, prognosis, clinical decision support, self-management, and rehabilitation. The studies were evaluated based on predefined inclusion criteria, including the reporting quality of AI algorithms used.

RESULTS

After the screening process, 60 studies were reviewed, highlighting AI's effectiveness in diagnosing and classifying CP while revealing gaps in the attention given to treatment and rehabilitation. It was found that the most commonly used algorithms in CP research were support vector machines, logistic regression and random forest classifiers. The review also pointed out that attention to CP mechanisms is negligible despite being the most effective way to treat CP.

CONCLUSION

The review concludes that to achieve more effective outcomes in CP management, future research should prioritize identifying CP mechanisms, CP management, and rehabilitation while leveraging a wider range of algorithms and architectures.

SIGNIFICANCE

This review highlights the potential of AI in improving the management of CP, which is a significant personal and economic burden affecting more than 30% of the world's population. The identified gaps and future research directions provide valuable insights to researchers and practitioners in the field, with the potential to improve healthcare utilization.

The Adaptive, Pain Sensitive, and Global Symptoms Clusters: Evidence from a Patient-Based Study

OBJECTIVES

The largest epidemiologic study conducted about painful temporomandibular disorders (pTMDs) to date identified 3 clusters of individuals with similar symptoms-adaptive, pain sensitive, and global symptoms-which hold promise as a means of personalizing pain care. Our goal was to compare the clinical and psychological characteristics that are consistent with a pTMD clinical examination among patients who are seeking care and assigned to the different clusters.

METHODS

This cross-sectional study used data from the medical records of patients attending Duke Innovative Pain Therapies between August 2017 and April 2021 who received a pTMD diagnosis (i.e., myalgia) and consented to have their data used for research. Data included orofacial and pain-related measures, dental features, and psychological measures. We used the Rapid OPPERA Algorithm to assign clusters to patients and multinomial regression to determine the likelihood (odds ratios [OR] and 95% confidence intervals [CI]) of being assigned to the pain sensitive or global symptoms cluster attributed to each measure.

RESULTS

In total, 131 patients were included in this study and assigned a cluster: adaptive (n = 54, 41.2%), pain sensitive (n = 49, 37.4%), and global symptoms (n = 28, 21.4%). The PS cluster displayed greater numbers of temporomandibular joint sites (OR, 1.29; 95% CI, 1.01 to 1.65) and masticatory (1.48; 1.19 to 1.83) and cervical (1.23; 1.09 to 1.39) muscles with pain evoked by palpation. The GS cluster displayed greater scores of pain catastrophizing (1.04; 1.01 to 1.06) and perceived stress (1.23; 1.03 to 1.46) and was more likely to report persistent pain (16.23; 1.92 to 137.1) of higher impact (1.43; 1.14 to 1.80).

CONCLUSION

Our findings support that care-seeking patients with pTMDs who are assigned to the GS cluster display a poorer psychological profile, even though those assigned to the PS cluster display more measures consistent with orofacial pain. Findings also establish the PS cluster as a group that does not display psychological comorbidities despite being hypersensitive.

KNOWLEDGE TRANSFER STATEMENT

This study informs clinicians that patients seeking care for painful temporomandibular disorders, in specific cases of myalgia, can be classified into 1 of 3 groups that display unique profiles of symptoms. Most importantly, it emphasizes the importance of examining patients with painful temporomandibular disorders in a holistic manner that includes assessing symptoms of psychological distress. Patients with greater psychological distress will likely benefit from multidisciplinary treatment strategies that may include psychological treatments.

Demographics moderated the association of symptom burden with falls and fall-related outcomes

OBJECTIVES

To examine whether (1) prior-year symptom burden predicted later-year falls and fall-related outcomes and (2) demographics moderated the longitudinal effects of symptom burden on falls and fall-related outcomes among community-dwelling older adults.

METHODS

We used 2011-2018 National Health and Aging Trends Study data that included 9,060 community-dwelling older adults (contributed 34,327 observations). Falls and fall-related outcomes included self-reported falls, multiple falls, fear of falling (FOF), and FOF limiting activity. Symptom burden was defined as the presence of pain, insomnia, breathing difficulty, depressive symptoms, anxiety, and fatigue, and calculated the number of symptoms (range from 0 to 6). Binomial logistic regression was used to examine the associations between symptom burden and falls and fall-related outcomes and the moderation effects of demographic factors.

RESULTS

The majority of the sample were aged between 65 and 79 years old (57.7%), non-Hispanic White (70.5%), and female (58.4%). Each additional symptom was associated with an increased risk of falls (Adjusted Odds Ratio [AOR]: 1.13, 95% CI: 1.10-1.15), multiple falls (AOR: 1.15, 95% CI: 1.12-1.18), FOF (AOR: 1.20, 95% CI: 1.18-1.23), and FOF limiting activity (AOR: 1.24, 95% CI: 1.20-1.28). Age, race/ethnicity, education, and living arrangement statistically significantly moderated the relationships between symptom burden and falls and fall-related outcomes.

CONCLUSIONS

Symptom burden predicted falls, multiple falls, FOF and FOF limiting activity, and demographics may differentially modify this risk. Individually tailored symptom assessment and management plans should be incorporated into fall risk assessment and interventions for community-dwelling older adults living.

Unsupervised learning for prognostic validity in patients with chronic pain in transdisciplinary pain care

Chronic pain is not a singular disorder and presents in various forms and phenotypes. Here we show data from a cohort of patients seeking treatment in a transdisciplinary pain clinic. Patients completed a multidimensional patient-reported battery as part of routine initial evaluation at baseline and at each of the four subsequent visits over 1-year follow-up (0, 1, 3, 6, 12 months). The goal of this work was to use unsupervised modeling approach to identify whether patients with chronic pain undergoing transdisciplinary intensive rehabilitation treatment: (1) can be derived based upon self-reported outcome measures at baseline (or before treatment initiation), (2) are clinically validated based on their clinical diagnosis and medication use, and (3) differ in treatment trajectories over 1 year of transdisciplinary treatment. We applied unsupervised clustering on baseline outcomes using nine patient-reported symptoms and examined treatment trajectories. The three-cluster solution was internally validated. Psychiatric diagnosis, chronic back pain-related disability and symptoms severity determined cluster assignment and treatment prognosis. Conversely, clinical pain severity had lesser effect. Furthermore, clusters showed stability over time despite symptoms improvement. The accurate and meaningful subgrouping of the underlying chronic pain phenotypes would greatly enhance treatment and provide personalized and effective pain management.

Brain Activation of Unpleasant Emotions Increases Catastrophizing in Patients with Chronic Pain

BACKGROUND

Catastrophic thinking among patients with chronic pain impairs their quality of life and increases anxiety levels. Further, severe pain causes high emotional brain sensitivity and unpleasant feelings. However, the effects of emotional changes on catastrophic thinking in patients with chronic pain remain unclear.

AIMS

We hypothesised that emotional brain activity during mild pain stimuli would affect catastrophic thinking in these patients. We aimed to examine the relationship between unpleasant emotional brain activation and catastrophic thinking due to pain stimuli in patients with chronic pain.

DESIGN

This was a prospective observational study.

PARTICIPANTS

We included patients with chronic pain and healthy individuals.

METHODS

The impact of emotional brain activity on catastrophic thinking was evaluated, specifically, the skin conductance response and oxygenated haemoglobin levels using near-infrared spectroscopy. After receiving three different pain stimuli, the participants were evaluated using the Numeric Rating Scale, Pain Catastrophising Scale, and McGill Pain Questionnaire.

RESULTS

There were 28 patients in the chronic pain group and 33 patients in the healthy group. There was no between-group difference in oxygenated haemoglobin levels during pain stimulation. The chronic pain group showed a higher Pain Catastrophising Scale score and skin conductance response than the healthy group (p < .05). In the chronic pain group, oxygenated haemoglobin levels after pain stimuli were significantly associated with the Pain Catastrophising Scale score and skin conductance response (p < .05).

CONCLUSIONS

Brain activity of unpleasant emotions may influence catastrophic thinking in patients with chronic pain.

Self-reported physical function is strongly related to pain behavior and pain interference and weakly related to physical capacity in people with chronic low back pain

BACKGROUND

Inclusion of self-reported and capacity-based measures may help to further elucidate the interactive link between how people think and move.

OBJECTIVE

To characterize the relationship between self-reported factors of physical function and pain with objective physical capacity measures.

DESIGN

Cross-sectional study of 328 adults with chronic low back pain (CLBP).

METHOD

Spearman correlations assessed the relationship between pairs of measures. Multiple linear regression models assessed the association between self-reported measures of physical function and the grouping of physical capacity measures. Self-reported measures included Roland Morris Disability Questionnaire (RMDQ), PROMIS Physical Function, Pain Behavior, and Pain Interference; Fear-Avoidance Beliefs Questionnaire (FABQ), Pain Catastrophizing Scale (PCS), and Chronic Pain Acceptance Questionnaire (CPAQ). Capacity measures included walking speed and endurance, lower extremity functional strength, lumbopelvic range of motion, and trunk endurance.

RESULTS

PROMIS Physical Function was directly and weakly correlated with walking speed (ρ = 0.26, 2-min walk) and inversely and weakly correlated with lower extremity strength (ρ = -0.29, 5x sit-to-stand). RMDQ was not correlated with any of the capacity-based measures. PROMIS Physical Function was inversely and moderately correlated with Pain Interference (ρ = -0.48) and Pain Behavior (ρ = -0.43), PCS (ρ = -0.36), and FABQ (ρ = -0.31). The RMDQ was strongly correlated with PROMIS Physical Function (ρ = -0.56), Pain Behavior (ρ = 0.51) and Pain Interference (ρ = 0.49); and moderately correlated with PCS (ρ = 0.37) and FABQ (ρ = 0.33). PROMIS Physical Function and RMDQ were not correlated with CPAQ. Lower scores on PROMIS Physical Function were weakly associated with lower measures of lower extremity strength (-0.30, 95% CI: -0.51 to -0.09, p = 0.005). Higher scores on RMDQ were also weakly associated with lower measures of lower extremity strength (0.26, 95% CI: 0.11 to 0.41, p = 0.001).

CONCLUSIONS

A strong association emerged between self-reported limitations in physical function, pain behavior, and pain interference. A weak association emerged between self-reported physical function and lower extremity strength.

Pain-coping types among older community-dwelling care receivers with chronic pain

OBJECTIVES

There is a lack of knowledge on coping with pain and sub-group specific pain-coping profiles among older home care receivers with chronic pain. To describe pain-coping strategies, identify subgroups based on cognitive and behavioral pain-coping strategies and pain-related psychological impairment and to compare these groups with regard to socio-demographic, medical, pharmacological and psychological characteristics.

METHOD

Data of 212 care receivers were examined using the German pain-coping questionnaire (FESV) to determine how they cope with pain. Subgroups were identified using hierarchic agglomerative cluster analysis, using Ward's algorithm and squared Euclidean distance, and characterized using socio-demographic, medical, pharmacological and psychological parameters. Multinomial logistic regression was used to identify variables associated with the subgroups.

RESULTS

Older care receivers apply cognitive and behavioral strategies to manage pain. Three subgroups were identified: Cluster 1 (25.9%) with good coping competences and little psychological impairment, Cluster 2 (40.1%) with poor coping competences and high psychological impairment, and Cluster 3 (34%) with good coping competences and high psychological impairment. Significant differences between the clusters were observed for age, pain intensity, pain-related interference, daily activities, depression and resilience. Logistic regression demonstrated that belonging to Cluster 2 was associated with the number of pain-reducing medications, depression and resilience. Belonging to Cluster 3 was significantly linked to daily activities, the number of pain medications, depression and the level of care required.

CONCLUSION

Differentiating between pain-coping profiles in the group of older care receivers with chronic pain necessitates target group-specific pain-oriented psychotherapeutic interventions, which can result in improved pain management.

Intraindividual pain variability and phenotypes of pain in sickle cell disease: a secondary analysis from the Pain in Sickle Cell Epidemiology Study

ABSTRACT

Mean pain intensity alone is insufficient to describe pain phenotypes in sickle cell disease (SCD). The objective of this study was to determine impact of day-to-day intraindividual pain variability on patient outcomes in SCD. We calculated metrics of pain variability and pain intensity for 139 participants with <10% missing data in the first 28 days of the Pain in Sickle Cell Epidemiology Study. We performed Spearman rank correlations between measures of intraindividual pain variability and outcomes. We then used k-means clustering to identify phenotypes of pain in SCD. We found that pain variability was inversely correlated with health-related quality of life, except in those with daily or near-daily pain. Pain variability was positively correlated with affective coping, catastrophizing, somatic symptom burden, sickle cell stress, health care utilization, and opioid use. We found 3 subgroups or clusters of pain phenotypes in SCD. Cluster 1 included individuals with the lowest mean pain, lowest temporal instability and dependency, lowest proportion of days with pain and opioid use, and highest physical function. Cluster 2 included individuals with the highest mean pain, highest temporal dependency, highest proportion of days with pain and opioid use, and lowest physical function. Cluster 3 included individuals with high levels of mean pain, highest temporal instability, but with lower temporal dependency, proportion of days with pain and opioid use, and physical function compared with cluster 2. We conclude that intraindividual pain variability is associated with patient outcomes and psychological characteristics in SCD and is useful in delineating phenotypes of pain in SCD.

Machine Learning-Based Analysis of Treatment Sequences Typology in Advanced Non-Small-Cell Lung Cancer Long-Term Survivors Treated With Nivolumab

PURPOSE

Immune checkpoint inhibitors substantially changed advanced non-small-cell lung cancer (aNSCLC) management and can lead to long-term survival. The aims of this study were (1) to use a machine learning method to establish a typology of treatment sequences on patients with aNSCLC who were alive 2 years after initiating a treatment with anti-programmed death-ligand 1 monoclonal antibody nivolumab and (2) to describe the patients' characteristics according to the typology of treatment sequences.

MATERIALS AND METHODS

This retrospective observational study was based on data from the comprehensive French hospital discharge database for all patients with lung cancer with at least one line of platinum-based chemotherapy, starting nivolumab between January 1, 2015, and December 31, 2016, and alive 2 years after nivolumab treatment initiation. Patients were followed until December 31, 2018. A typology of most common treatment sequences was established using hierarchical clustering with time sequence analysis.

RESULTS

Two thousand two hundred twelve study patients were, on average, 63.0 years old, 69.9% of them were men, and 61.9% had a nonsquamous cell carcinoma. During the 2 years after nivolumab treatment initiation, clusters of patients with four basic types of treatment sequences were identified: (1) almost continuous nivolumab treatment (44% of patients); (2) nivolumab most of the time followed by a treatment-free interval or a chemotherapy (15% of patients); and a short or medium nivolumab treatment, followed by (3) a long systemic treatment-free interval (17% of patients) or (4) a long chemotherapy (23% of patients).

CONCLUSION

This machine learning approach enabled the identification of a typology of four representative treatment sequences observed in long-term survival. It was noted that most long-term survivors were treated with nivolumab for well over 1 year.

Psychosocial and psychophysical assessment in pediatric patients and young adults with chronic back pain: a cluster analysis

Background

Identifying subgroups with different clinical profiles may inform tailored management and improve outcomes. The objective of this study was to identify psychosocial and psychophysical profiles of children and adolescents with chronic back pain.

Methods

One hundred and ninety‐eight patients with chronic back pain were recruited for the study. Pain assessment was mainly conducted in the form of an interview and with the use of validated pain‐related questionnaires assessing their psychosocial factors and disability. All patients underwent mechanical and thermal quantitative sensory tests assessing detection and pain thresholds, and conditioned pain modulation efficacy.

Results

Hierarchal clustering partitioned our patients into three clusters accounting for 34.73% of the total variation of the data. The adaptive cluster represented 45.5% of the patients and was characterized to display high thermal and pressure pain thresholds. The high somatic symptoms cluster, representing 19.2% of patients, was characterized to use more sensory, affective, evaluative and temporal descriptors of pain, more likely to report their pain as neuropathic of nature, report a more functional disability, report symptoms of anxiety and depression and report poor sleep quality. The pain‐sensitive cluster, representing 35.4% of the cohort, displayed deep tissue sensitivity and thermal hyperalgesia.

Conclusions

This study identified clinical profiles of children and adolescents experiencing chronic back pain based on specific psychophysical and psychosocial characteristics highlighting that chronic pain treatment should address underlying nociceptive and non‐nociceptive mechanisms.

Significance

To our current knowledge, this study is the first to conduct cluster analysis with youth experiencing chronic back pain and displays clinical profiles based on specific physical and psychosocial characteristics. This study highlights that in a clinical context, chronic pain assessment should include multiple elements contributing to pain which can be assessed in a clinical context and addressed when pathoanatomical symptoms are unidentifiable.

Composite psychosocial risk based on the fear avoidance model in patients undergoing anterior cruciate ligament reconstruction: Cluster-based analysis

OBJECTIVES

To examine associations between preoperative fear-avoidance model (FAM) risk subgroup status and patient expectation of surgical success with postoperative outcomes at 6 and 12 months after anterior cruciate ligament reconstruction (ACLR).

DESIGN

Cohort study.

SETTING

Academic medical center.

PARTICIPANTS

54 patients (25 females) undergoing unilateral ACLR.

MAIN OUTCOME MEASURES

Cluster analysis distinguished FAM risk subgroups based on preoperative fear of movement/reinjury, self-efficacy, and pain catastrophizing. Preoperative expectation for surgical success was assessed with a numeric rating scale. Six and 12-month outcomes included Subjective Patient Outcomes for Return to Sport, Knee Injury and Osteoarthritis Outcome Score (KOOS) sports/recreation and quality of life, and International Knee Documentation Committee (IKDC) Subjective Knee Form.

RESULTS

Thirteen (24%) patients were "moderate-to-high FAM risk." Moderate-to-high FAM risk patients had lower odds of return to sport at 12 months (OR = 0.3, p = .05) and lower KOOS sports/recreation at 6 months (st. beta = -0.27, p = .05), KOOS quality of life at 12 months (st. beta = -0.42, p = .007), and IKDC at 6 (st. beta = -0.29, p = .04) and 12 months (st. beta = -0.47, p = .001). Higher expectation was associated with lower 6-month IKDC (st. beta = -0.36, p = .008) and 12-month KOOS quality of life (st. beta = -0.29, p = .05).

CONCLUSIONS

Preoperative FAM risk influences patient-reported outcomes and return to sport at 6 and 12 months.

Establishing Central Sensitization-Related Symptom Severity Subgroups: A Multicountry Study Using the Central Sensitization Inventory

OBJECTIVES

The goal of this study was to identify central sensitization-related symptom severity subgroups in a large multicountry sample composed of patients with chronic pain and pain-free individuals using the Central Sensitization Inventory (CSI).

METHODS

A large, pooled international (N = 8 countries) sample of chronic pain patients plus healthy subjects (total N = 2,620) was randomly divided into two subsamples for cross-validation purposes. First, a hierarchical cluster analysis (HCA) was performed using CSI item-level data as clustering variables (test sample; N = 1,312). Second, a latent profile analysis (LPA) was conducted to confirm the optimal number of CSI clusters (validation sample; N = 1,308). Finally, to promote implementation in real-world clinical practice, we built a free online Central Sensitization Inventory Symptom Severity Calculator.

RESULTS

In both HCA (N = 1,219 valid cases) and LPA (N = 1,245 valid cases) analyses, a three-cluster and three-profile solution, respectively, emerged as the most statistically optimal and clinically meaningful. Clusters were labeled as follows: (i) Low Level of CS-Related Symptom Severity, (ii) Medium Level of CS-Related Symptom Severity, and (iii) High Level of CS-Related Symptom Severity.

CONCLUSIONS

Our results indicated that a three-cluster solution clearly captured the heterogeneity of the CSI data. The calculator might provide an efficient way of classifying subjects into the cluster groups. Future studies should analyze the extent to which the CSI cluster classification correlates with other patient-reported and objective signs and symptoms of CS in patients with chronic pain, their associations with clinical outcomes, health-related costs, biomarkers, (etc.), and responsiveness to treatment.

Phenotypic profile clustering pragmatically identifies diagnostically and mechanistically informative subgroups of chronic pain patients

ABSTRACT

Traditional classification and prognostic approaches for chronic pain conditions focus primarily on anatomically based clinical characteristics not based on underlying biopsychosocial factors contributing to perception of clinical pain and future pain trajectories. Using a supervised clustering approach in a cohort of temporomandibular disorder cases and controls from the Orofacial Pain: Prospective Evaluation and Risk Assessment study, we recently developed and validated a rapid algorithm (ROPA) to pragmatically classify chronic pain patients into 3 groups that differed in clinical pain report, biopsychosocial profiles, functional limitations, and comorbid conditions. The present aim was to examine the generalizability of this clustering procedure in 2 additional cohorts: a cohort of patients with chronic overlapping pain conditions (Complex Persistent Pain Conditions study) and a real-world clinical population of patients seeking treatment at duke innovative pain therapies. In each cohort, we applied a ROPA for cluster prediction, which requires only 4 input variables: pressure pain threshold and anxiety, depression, and somatization scales. In both complex persistent pain condition and duke innovative pain therapies, we distinguished 3 clusters, including one with more severe clinical characteristics and psychological distress. We observed strong concordance with observed cluster solutions, indicating the ROPA method allows for reliable subtyping of clinical populations with minimal patient burden. The ROPA clustering algorithm represents a rapid and valid stratification tool independent of anatomic diagnosis. ROPA holds promise in classifying patients based on pathophysiological mechanisms rather than structural or anatomical diagnoses. As such, this method of classifying patients will facilitate personalized pain medicine for patients with chronic pain.

Cluster analysis of Canadian Armed Forces veterans living with chronic pain: Life After Service Studies 2016

Objective: This study explored the heterogeneity of Canadian Armed Forces veterans living with chronic pain to inform service needs planning and research using cluster analysis. Design: We used a national cross-sectional Statistics Canada population survey. Participants: Participants included 2754 Canadian Armed Forces (CAF) Regular Force veterans released from service between 1998 and 2015 and surveyed in 2016. Methods: We used cluster analysis of veterans with chronic pain based on pain severity, mental health, and activity limitation characteristics. We compared clusters for sociodemographic, health, and service utilization characteristics. Results: Of 2754 veterans, 1126 (41%) reported chronic pain. Veterans in cluster I (47%) rarely had severe pain (2%) or severe mental health problems (8%), and none had severe activity limitations. Veterans in cluster II (26%) more often than veterans in cluster I but less often than veterans in cluster III endorsed severe pain (27%) and severe mental health problems (22%) and were most likely to report severe activity limitation (91%). Veterans in cluster III (27%) were most likely to report severe pain (36%) and severe mental health problems (96%), and a majority reported severe activity limitations (72%). There was evidence of considerable heterogeneity among individuals in terms of socioeconomic characteristics, pain characteristics, mental and physical health status, activity limitations, social integration, and service utilization indicators. Conclusions: About half of Canadian veterans living with chronic pain infrequently endorse severe pain or serious mental health issues without severe activity limitations. The other half had more complex characteristics. The heterogeneity of CAF veterans with chronic pain emphasizes the need for support systems that can address variability of needs.

Homelessness Is Socially Created: Cluster Analysis of Social Determinants of Homelessness (SODH) in North West England in 2020

Poverty creates social conditions that increase the likelihood of homelessness. These include exposure to traumatic life experiences; social disadvantages such as poor educational experiences; being raised in a broken family, care homes or foster care; physical, emotional, and sexual abuse; and neglect at an early age. These conditions reduce people’s ability to negotiate through life challenges. This cross-sectional study documents the clustering and frequency of adverse social conditions among 152 homeless people from four cities in North West England between January and August 2020. Two-step cluster analysis showed that having parents with a criminal record, care history, and child neglect/abuse history was predictive of homelessness. The cluster of indicator variables among homeless people included sexual abuse (χ2 (N = 152) = 220.684, p < 0.001, Cramer’s V = 0.7), inappropriate sexual behaviour (χ2 (N = 152) = 207.737, p < 0.001, Cramer’s V = 0.7), emotional neglect (χ2 (N = 152) = 181.671, p < 0.001, Cramer’s V = 0.7), physical abuse by step-parent (χ2 (N = 152) = 195.882, p < 0.001, Cramer’s V = 0.8), and physical neglect (χ2 (N = 152) = 205.632, p < 0.001, Cramer’s V = 0.8). Poverty and homelessness are intertwined because of the high prevalence of poverty among the homeless. Poverty sets up a chain of interactions between social conditions that increase the likelihood of unfavourable outcomes: homelessness is at the end of the interaction chain. Interventions supporting families to rise out of poverty may also reduce entry into homelessness.

Association between Participation Activities, Pain Severity, and Psychological Distress in Old Age: A Population-Based Study of Swedish Older Adults

Although chronic pain is common in old age, previous studies on participation activities in old age seldom consider pain aspects and its related consequences. This study analyses associations between participation activities, pain severity, and psychological distress in an aging population of Swedish older adults (N = 6611). We examined older adults' participation in five common leisure activities using the Multidimensional Pain Inventory (MPI), sociodemographic factors, pain severity, weight status, comorbidities, and pain-related psychological distress (anxiety, depression, insomnia severity, and pain catastrophising). We found that gender, body mass index (BMI) levels, and psychological distress factors significantly affected older adults' participation in leisure activities. Pain severity and multimorbidity were not significantly associated with older adults' participation in leisure activities nor with gender stratification in generalised linear regression models. The potentially modifiable factors, such as high levels of BMI and psychological distress, affected activity participation in men and women differently. Health professionals and social workers should consider gender and target potentially modifiable factors such as weight status and psychological distress to increase older adults' participation in leisure activities.

Clustering of patients with chronic low back pain in terms of physical and psychological factors: A cross-sectional study based on the STarT Back Screening Tool

BACKGROUND

The STarT Back Screening Tool (SBT) is a multidimensional questionnaire consisting of physical and psychological factors which categorizes the patients in the low, medium or high risk subgroups.

OBJECTIVE

To investigate the relationship between SBT-based subgrouping and clustering of patients with LBP using uni-dimensional psychological, clinical and physical examination measures.

METHODS

One hundred and fifty-seven patients with chronic LBP completed the SBT and uni-dimensional psychological, disability and pain questionnaires. Physical impairments were evaluated through the Physical Impairment Index (PII). Hierarchical and K-means methods were used for cluster analysis. Between-clusters differences and the association between the clusters and SBT-based subgrouping were investigated.

RESULTS

Three clusters were identified. The derived clusters were labeled severe, moderate and mild physical-psychological-distress clusters, because pain intensity, disability, psychological and physical factors were relatively high, moderate or low, respectively. Most of the patients in moderate and mild physical-psychological distress clusters were categorized as medium risk based on SBT. The mean difference for the PII was higher than that of psychological factors between moderate and mild physical-psychological-distress clusters.

CONCLUSIONS

Patients in low and high risk subgroups of SBT were sufficiently differentiated, but patients in a medium risk subgroup had a different profile based on PII. Including additional physical factors in the SBT may be required to better differentiate among patients.

Pain Catastrophizing in Older Adults with Chronic Pain: The Mediator Effect of Mood Using a Path Analysis Approach

Cognitive models of pain propose that catastrophic thinking is negatively associated with chronic pain. However, pain catastrophizing is a complex phenomenon requiring a multivariate examination. This study estimates the effects of mood variables (anxiety and depression) on pain catastrophizing in older adults with chronic pain. A postal survey addressing pain aspects was sent to 6611 people ≥ 65 years old living in south-eastern Sweden. Pain catastrophizing was measured using the pain catastrophizing scale. Anxiety and depression were assessed using two subscales of the general well-being schedule. Data were analysed using a path analysis approach. A total of 2790 respondents (76.2 ± 7.4 years old) reported chronic pain (≥three months). The mediation model accounted for 16.3% of anxiety, 17.1% of depression, and 30.9% of pain catastrophizing variances. Pain intensity, insomnia, number of comorbidities, and lifestyle factors (smoking, alcohol consumption, and weight) significantly affected both pain catastrophizing and mood. Anxiety (standardized path coefficient (b_std) = 0.324, p < 0.001) in comparison to depression (b_std = 0.125, p < 0.001) had a greater effect on pain catastrophizing. Mood mediated the relationship between pain catastrophizing and pain-related factors accounting for lifestyle and sociodemographic factors.

Factors Associated with Life Satisfaction in Older Adults with Chronic Pain (PainS65+)

Background

Chronic pain in later life is a worldwide problem. In younger patients, chronic pain affects life satisfaction negatively; however, it is unknown whether this outcome will extend into old age.

Objective

This study examines which factors determine life satisfaction in older adults who suffer from chronic pain with respect to socio-demographics, lifestyle behaviors, pain, and comorbidities.

Methods

This cross-sectional study recruited a random sample of people ≥65 years old living in south-eastern Sweden (N= 6611). A postal survey addressed pain aspects and health experiences. Three domains from the Life Satisfaction Questionnaire (LiSat-11) were used to capture the individual’s estimations of overall satisfaction (LiSat-life), somatic health (LiSat-somhealth), and psychological health (LiSat-psychhealth).

Results

Respondents with chronic pain (2790, 76.2±7.4 years old) rated lower on life satisfaction than those without chronic pain, with medium effect size (ES) on LiSat-somhealth (r = 0.38, P < 0.001) and small ES on the other two domains (r < 0.3). Among the respondents with chronic pain, severe pain (OR 0.29–0.59) and pain spreading (OR 0.87–0.95) were inversely associated with all three domains of the LiSat-11. Current smoking, alcohol overconsumption, and obesity negatively affected one or more domains of the LiSat-11. Most comorbidities were negatively related to LiSat-somhealth, and some comorbidities affected the other two domains. For example, having tumour or cancer negatively affected both LiSat-life (OR 0.62, 95% CI 0.44–0.88) and LiSat-somhealth (OR 0.42, 95% CI 0.24–0.74). Anxiety or depression disorders had a negative relationship both for LiSat-life (OR 0.54, 95% CI 0.38–0.78) and LiSat-psychhealth (OR 0.10, 95% CI 0.06–0.14).

Conclusion

Older adults with chronic pain reported lower life satisfaction but the difference from their peers without chronic pain was trivial, except for satisfaction with somatic health. Pain management in old age needs to consider comorbidities and severe pain to improve patients’ life satisfaction.

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Novel approach towards musculoskeletal phenotypes

BACKGROUND

The multidimensional array of clinical features and prognostic factors makes it difficult to optimize management within the heterogeneity of patients with common musculoskeletal pain. This study aimed to identify phenotypes across prognostic factors and musculoskeletal complaints. Concurrent and external validity were assessed against an established instrument and a new sample, respectively, and treatment outcome was described.

METHODS

We conducted a longitudinal observational study of 435 patients (aged 18-67 years) seeking treatment for nonspecific complaints in the neck, shoulder, low back or multisite/complex pain in primary health care physiotherapy in Norway. Latent class analysis was used to identify phenotypes based on 11 common prognostic factors within four biopsychosocial domains; pain, beliefs and thoughts, psychological and activity and lifestyle.

RESULTS

Five distinct phenotypes were identified. Phenotype 1 (n = 77, 17.7%) and 2 (n = 142, 32.6%) were characterized by the lowest scores across all biopsychosocial domains. Phenotype 2 showed somewhat higher levels of symptoms across the biopsychosocial domains. Phenotype 3 (n = 89, 20.5%) and 4 (n = 78, 17.9%) were more affected across all domains, but phenotype 3 and 4 had opposite patterns in the psychological and pain domains. Phenotype 5 (n = 49, 11.3%) were characterized by worse symptoms across all domains, indicating a complex phenotype. The identified phenotypes had good external and concurrent validity, also differentiating for the phenotypes in function and health-related quality of life outcome at 3-month follow-up.

CONCLUSION

The phenotypes may inform the development of targeted interventions aimed at improving the treatment efficiency in patients with common musculoskeletal disorders.

SIGNIFICANCE

This observational prospective study identified five distinct and clinically meaningful phenotypes based on biopsychosocial prognostic factors across common musculoskeletal pain. These phenotypes were independent of primary pain location, showed good external validity, and clear variation in treatment outcome. The findings are particularly valuable as they describe the heterogeneity of patients with musculoskeletal pain and points to a need for more targeted interventions in common musculoskeletal disorders to improve treatment outcome.

Maintenance of affective wellbeing following acute pain in healthy older and younger adults

Over 70% of older adults report chronic or acute pain, and pain threatens affective wellbeing. The strategies older adults use to maintain affective wellbeing following acute pain remain unknown. Specific strategies that can be used to manage pain include recalling, recognizing, and responding to positive stimuli and prioritizing close over knowledgeable social partners. The study tested whether older adults used positivity-enhancing strategies and maintained affective wellbeing following acute pain better than younger adults. Fifty older (ages 65-85) and 50 younger (ages 18-30) pain-free adults experienced a control and a pain condition and were given the chance to employ positivity-enhancing strategies. Older and younger adults similarly used positivity-enhancing strategies following pain. Younger adults demonstrated reduced preference for knowledgeable social partners after experiencing pain. Pain-related affective changes were similar between age groups. Older and younger adults may cope with acute pain similarly, highlighting future directions for exploring age differences in pain coping.

Nonmalignant Pain Symptom Subgroups in Nursing Home Residents

CONTEXT

Despite many nursing home residents experiencing pain, research about the multidimensional nature of nonmalignant pain in these residents is scant.

OBJECTIVES

To identify and describe pain symptom subgroups and to evaluate whether subgroups differed by sex.

METHODS

Using Minimum Data Set 3.0 data (2011-2012), we identified newly admitted nursing home residents reporting pain (n = 119,379). A latent class analysis included 13 indicators: markers for pain (i.e., severity, frequency, impacts sleep, and function) and depressive symptoms. Sex was evaluated as a grouping variable. Multinomial logistic models identified the association between latent class membership and covariates, including age and cognitive impairment.

RESULTS

Four latent subgroups were identified: severe (15.2%), moderate frequent (26.4%), moderate occasional with depressive symptoms (26.4%), and moderate occasional without depressive symptoms (32.0%). Measurement invariance by sex was ruled out. Depressed mood, sleep disturbances, and fatigue distinguished subgroups. Age ≥75 years was inversely associated with belonging to the severe, moderate frequent, or moderate occasional with depressive symptoms subgroups. Residents with severe cognitive impairment had reduced odds of membership in the severe pain subgroup (adjusted odds ratio [aOR]: 0.84; 95% confidence interval [CI]: 0.78-0.90) and moderate frequent pain subgroup (aOR: 0.60; 95% CI: 0.56-0.64) but increased odds in the moderate occasional pain with depressive symptoms subgroup (aOR: 1.12; 95% CI: 1.06-1.18).

CONCLUSION

Identifying subgroups of residents with different patterns of pain and depressive symptoms highlights the need to consider physical and psychological components of pain. Expanding knowledge about pain symptom subgroups may provide a promising avenue to improve pain management in nursing home residents.

Cluster analysis of psychiatric profile, its correlates, and using mental health services among the young people aged 15-34: findings from the first phase of Iranian youth cohort in Ravansar

PURPOSES

(1) Cluster analysis of psychiatric disorders and partitioning the youth; (2) determining socio-demographic correlates and parental histories for each one of the clusters; and (3) comparing clusters based on the extent and type of using psychotherapeutic services.

METHODS

The current cross-sectional study is a part of the first phase of PERSIAN Youth Cohort. The sample of the study includes 2991 participants aged 15-34 (27 ± 5.1 years, 55.6% female) from Ravansar district in western Iran. Enrollment and data collection for this phase were performed from October, 2014 to January, 2017. The data were collected through structured interviews, including the Composite International Diagnostic Interview (CIDI; version 2.1), mental health-related Sheehan Disability Scale, and Service Use Questionnaire. The obtained data were analyzed using two-step cluster analysis, multinomial logistic regression, and Chi-square test.

RESULTS

Our model proposed three clusters: a clinical cluster with significant mental disability; a healthy cluster with significant disability; and a healthy cluster with mild disability. There is a direct relationship between widow/divorced marital status and psychiatric maternal history with the clinical cluster (P < 0.05). Clinical and non-clinical clusters with medium to severe disability used services for mental health more often that the healthy cluster with mild functional disability (P < 0.05).

CONCLUSIONS

The results of the study show that 28.7% of the youth in the general population of western Iran are suffering from psychiatric disorders and nearly two-thirds of the total population reported a medium-severe functional disability. Considering the wide range of mental disorders and the functional disability levels created by these disorders, cluster analysis could provide invaluable information regarding the partitioning of the youth population.

Is excess weight a burden for older adults who suffer chronic pain?

Background

Obesity and chronic pain are common comorbidities and adversely influence each other. Advanced age is associated with more comorbidities and multi-morbidities. In this study, we investigated the burden of overweight/obesity and its comorbidities and their associations with chronic pain in a random population sample of Swedish older adults.

Methods

The cross-sectional analysis involved a random sample of a population ≥ 65 years in south-eastern Sweden (N = 6243). Data were collected from a postal questionnaire that addressed pain aspects, body mass index (BMI), and health experiences. Chronic pain was defined as pain during the previous three months. According to the 0–10 Numeric Rating Scale, pain scored ≥7 corresponds to severe pain. Binary logistic regression was used to determine the variables associated to pain aspects.

Results

A total of 2633 (42%) reported chronic pain. More obese older adults (BMI ≥30 kg/m²) experienced chronic pain (58%) than those who were low-normal weight (BMI < 25 kg/m², 39%) or overweight (25 ≤ BMI < 30 kg/m², 41%). Obese elderly more frequently had pain in extremities and lower back than their peers. In the multivariate model, obesity (Odds Ratio (OR) 1.59, 95% Confidence Interval (CI) 1.33–1.91) but not overweight (OR 1.08, 95% CI 0.95–1.22) was associated with chronic pain. Obesity (OR 1.53, 95% CI 1.16–2.01) was also significantly related to severe pain. We also found other comorbidities – i.e., traumatic history (OR 2.52, 95% CI 1.99–3.19), rheumatic diseases (OR 5.21, 95% CI 4.54–5.97), age ≥ 85 years (OR 1.66, 95% CI 1.22–2.25), and depression or anxiety diagnosis (OR 1.83, 95% CI 1.32–2.53) – showed stronger associations with pain aspects than weight status. Conclusion: In older adults, excess weight (BMI 30 or above) is a potentially modifiable factor but not the only risk factor that is associated with chronic pain and severe pain. Future studies should investigate the effectiveness of interventions that treat comorbid pain and obesity in older adults.