A Network Analysis of Depressive Symptoms in Individuals Seeking Treatment for Chronic Pain

Post-stroke Depressive Symptoms and Cognitive Performances: A Network Analysis

OBJECTIVE

To examine the relationships between post-stroke depression and cognition using network analysis. In particular, we identified central depressive symptoms, central cognitive performances, and bridge components that connect these 2 constructs.

DESIGN

An observational study. We applied network analysis to analyze baseline data to visualize and quantify the relationships between depression and cognition.

SETTING

Home and Community.

PARTICIPANTS

202 participants with mild-to-moderate stroke (N=202; mean age: 59.7 years; 55% men; 55% Whites; 90% ischemic stroke).

INTERVENTION

Not applicable.

MAIN OUTCOME MEASURES

Patient Health Questionnaire (PHQ-8) for depressive symptoms and the NIH Toolbox Cognitive Battery for cognitive performances.

RESULTS

Depressive symptoms were positively intercorrelated with the network, with symptoms from similar domains clustered together. Mood (expected influence=1.58), concentration (expected influence=0.67), and guilt (expected influence=0.63) were the top 3 central depressive symptoms. Cognitive performances also showed similar network patterns, with executive function (expected influence=0.89), expressive language (expected influence=0.68), and processing speed (expected influence=0.48) identified as the top 3 central cognitive performances. Psychomotor functioning (bridge expected influence=2.49) and attention (bridge expected influence=1.10) were the components connecting depression and cognition.

CONCLUSIONS

The central and bridge components identified in this study might serve as targets for interventions against these deficits. Future trials are needed to compare the effectiveness of interventions targeting the central and bridge components vs general interventions treating depression and cognitive impairment as a homogenous clinical syndrome.

Multilayer depressive symptom networks in adults with bodily pain living in precarious housing or homelessness

Housing insecurity is associated with co-occurring depression and pain interfering with daily activities. Network analysis of depressive symptoms along with associated risk or protective exposures may identify potential targets for intervention in patients with co-occurring bodily pain. In a community-based sample of adults (n = 408) living in precarious housing or homelessness in Vancouver, Canada, depressive symptoms were measured by the Beck Depression Inventory; bodily pain and impact were assessed with the 36-item Short Form Health Survey. Network and bootstrap permutation analyses were used to compare depressive symptoms endorsed by Low versus Moderate-to-Severe (Mod + Pain) groups. Multilayer networks estimated the effects of risk and protective factors. The overall sample was comprised of 78% men, mean age 40.7 years, with 53% opioid use disorder and 14% major depressive disorder. The Mod + Pain group was characterized by multiple types of pain, more persistent pain, more severe depressive symptoms and a higher rate of suicidal ideation. Global network connectivity did not differ between the two pain groups. Suicidal ideation was a network hub only in the Mod + Pain group, with high centrality and a direct association with exposure to lifetime trauma. Antidepressant medications had limited impact on suicidal ideation. Guilt and increased feelings of failure represented symptoms from two other communities of network nodes, and completed the shortest pathway from trauma exposure through suicidal ideation, to the non-prescribed opioid exposure node. Interventions targeting these risk factors and symptoms could affect the progression of depression among precariously housed patients.

A network analysis of pain intensity and pain-related measures of physical, emotional, and social functioning in US military service members with chronic pain

OBJECTIVE

The purpose of this study was to apply network analysis methodology to better understand the relationships between pain-related measures among people with chronic pain.

METHODS

We analyzed data from a cross-sectional sample of 4614 active duty service members with chronic pain referred to 1 military interdisciplinary pain management center between 2014 and 2021. Using a combination of Patient-Reported Outcomes Measurement Information System measures and other pain-related measures, we applied the "EBICglasso" algorithm to create regularized partial correlation networks that would identify the most influential measures.

RESULTS

Pain interference, depression, and anxiety had the highest strength in these networks. Pain catastrophizing played an important role in the association between pain and other pain-related health measures. Bootstrap analyses showed that the networks were very stable and the edge weights accurately estimated in 2 analyses (with and without pain catastrophizing).

CONCLUSIONS

Our findings offer new insights into the relationships between symptoms using network analysis. Important findings highlight the strength of association between pain interference, depression and anxiety, which suggests that if pain is to be treated depression and anxiety must also be addressed. What was of specific importance was the role that pain catastrophizing had in the relationship between pain and other symptoms suggesting that pain catastrophizing is a key symptom on which to focus for treatment of chronic pain.

Psychosocial Outcomes of Pain and Pain Management in Adults with Osteogenesis Imperfecta: A Qualitative Study

Osteogenesis imperfecta (OI) is a genetic disorder characterized by bone fragility and fractures, short stature, dental abnormalities, hearing loss, scoliosis, and chronic pain. Despite a growing literature on the functional outcomes of OI, limited research has explicitly examined the psychosocial outcomes of pain within OI. Adults with OI (N = 15) were interviewed to understand pain-related experiences through a thematic analysis of semi-structured interview data. Research team members, genetic research experts, and OI clinicians developed an interview guide focused on topics related to pain and mental health challenges. Participants' transcripts were coded by two independent coders; codes were then merged across coders and quotation outputs were subsequently abstracted (paraphrased then thematically classified) to identify common themes. Themes related to pain management variability regarding pain type, pain risk management and accessibility, pain outcomes (e.g., behavior, cognitive, affective), and pain exacerbating factors (e.g., individual, contextual) were identified. Participants reported chronic and acute pain, and despite the inaccessibility and stigmatization of pain medications (e.g., opioids), pharmacological treatments were the most common pain management approach. Participants reported negative pain outcomes, such as limited daily functioning and activity participation, fear, anger, anxiety, depression, and difficulty concentrating. Lastly, participants suggested that lack of physician and community knowledge on chronic pain in OI indirectly exacerbates both subjective pain intensity and outcomes. Although limited by a small, nondiverse sample, the current study provides valuable exploration of the unique pain experiences of adults with OI that may have implications for proactive management, treatment development, and clinician training.

Relations between PTSD symptom clusters and pain in three trauma-exposed samples with pain

OBJECTIVES

Little is known about how the individual PTSD symptom clusters relate to intensity and interference of pain and whether these relationships differ across clinical groups. The present study examines relations between PTSD symptom clusters and pain in three trauma-exposed, unique clinical groups: 1) adults seeking treatment for chronic pain with current symptoms of PTSD, 2) trauma affected refugees seeking treatment for PTSD and chronic pain; and 3) individuals identified at admission to the emergency ward after whiplash injury.

METHODS

Network analysis was used to assess unique relations between pain intensity, pain interference, re-experiencing, avoidance, numbing, hyperarousal, depression, and anxiety separately in each sample. Links between PTSD clusters and pain were then compared within and between samples.

RESULTS

No within-group differences were identified for the links between pain and any of PTSD clusters in the chronic pain and refugee groups. In the whiplash group, hyperarousal was more strongly related to pain than re-experiencing, avoidance, and numbing. Between group comparisons revealed a more pronounced relationship between hyperarousal and pain in the whiplash group, with no between-group differences between the chronic pain and refugee groups.

CONCLUSIONS

The findings suggest that when depression and anxiety are accounted for, few unique associations are found between pain and the PTSD symptom clusters in trauma-exposed samples with pain, with the exception of a link between pain and hyperarousal in individuals with whiplash-related PTSD symptoms.

Investigating the Physical and Mental Health Nexus: a Network Analysis of Depression, Cardiometabolic Health, Bone Mass, and Perceived Health Status Among Filipino Domestic Workers

BACKGROUND

Migrant domestic workers are vulnerable to physical and mental health problems given the many challenges they experience while working abroad. Using network analysis, this study examined the structure of depression, cardiometabolic health indicators (BMI, waist-hip ratio (WHR), blood pressure, and heart rate), bone mass, and perceived health status in this population. The network model allowed for an examination of central symptoms or symptoms with the most direct connections with other symptoms; bridge symptoms, or symptoms that link two or more communities; and edges, or relationships among symptoms.

METHOD

Cross-sectional data were gathered from 1375 Filipino domestic workers in Macao (SAR), China. Data from a subsample of 510 participants who met a cutoff indicating depression were analyzed. Anthropometric measurements and surveys were used to collect data, which was analyzed using R statistical software.

RESULTS

Results showed four community clusters: three communities consisted of at least two depression symptoms each and the fourth community included physical health indicators. Strong edges were formed between BMI-bone mass, psychomotor-concentration, BMI-WHR, and sad mood-anhedonia. The node with the highest expected influence was BMI. There were three bridges: worthlessness, psychomotor difficulties, and concentration difficulties.

CONCLUSION

The link between depression, cardiometabolic indicators, bone mass, and poor perceived health reinforces the need to address multimorbidity within migrant populations. Health promotion interventions that address mental and physical health may improve the health of this population.

A network analysis on biopsychosocial factors and pain-related outcomes assessed during a COVID-19 lockdown

Psychological stress, social isolation, physical inactivity, and reduced access to care during lockdowns throughout a pandemic negatively impact pain and function. In the context of the first COVID-19 lockdown in Spain, we aimed to investigate how different biopsychosocial factors influence chiropractic patients' pain-related outcomes and vice-versa. A total of 648 chiropractic patients completed online questionnaires including variables from the following categories: demographics, pain outcomes, pain beliefs, impact of the COVID-19 pandemic, stress/anxiety and self-efficacy. Twenty-eight variables were considered in a cross-sectional network analysis to examine bidirectional associations between biopsychosocial factors and pain outcomes. Subgroup analyses were conducted to estimate differences according to gender and symptom duration. The greatest associations were observed between pain duration and pain evolution during lockdown. Participants' age, pain symptoms' evolution during lockdown, and generalized anxiety were the variables with the strongest influence over the whole network. Negative emotions evoked by the pandemic were indirectly associated with pain outcomes, possibly via pain catastrophizing. The network structure of patients reporting acute pain showed important differences when compared to patients with chronic pain. These findings will contribute to identify which factors explain the deleterious effects of both the pandemic and the restrictions on patients living with pain.

Understanding the Psychophysiological and Sensitization Mechanisms Behind Fibromyalgia Syndrome: A Network Analysis Approach

OBJECTIVE

Current evidence suggests that fibromyalgia syndrome (FMS) involves complex underlying mechanisms. This study aimed to quantify the multivariate relationships between clinical, psychophysical, and psychological outcomes in women with FMS by using network analysis to understand the psychobiological mechanisms driving FMS and generating new research questions for improving treatment strategies.

METHODS

Demographic (age, height, weight), clinical (pain history, pain intensity at rest and during daily living activities), psychophysical (widespread pressure pain thresholds [PPT]), sensory-related (PainDETECT, S-LANSS, Central Sensitization Inventory [CSI]) and psychological (depressive and anxiety levels) variables were collected in 126 women with FMS. Network analysis was conducted to quantify the adjusted correlations between the modeled variables and to assess their centrality indices (i.e., the connectivity with other symptoms in the network and the importance in the system modelled as network).

RESULTS

The network showed several local associations between psychophysical and clinical sensory-related variables. Multiple positive correlations between PPTs were observed, being the strongest weight between PPTs on the knee and tibialis anterior muscle (ρ: 0.33). PainDETECT was associated with LANSS (ρ: 0.45) and CSI (ρ: 0.24), whereas CSI was associated with HADS-A (ρ: 0.28). The most central variables were PPTs over the tibialis anterior (the highest Strength centrality) and CSI (the highest Closeness and Betweenness centrality).

CONCLUSION

Our findings support a model where clinical sensory-related, psychological, and psycho-physical variables are connected, albeit in separate clusters, reflecting a nociplastic condition with a relevant role of sensitization. Clinical implications of the findings, such as developing treatments targeting these mechanisms, are discussed.

A network analysis reveals the interaction between fear and physical features in people with neck pain

Although neck pain is known to be a complex and multifactorial condition characterised by the interplay between physical and psychological domains, a comprehensive investigation examining the interactions across multiple features is still lacking. In this study, we aimed to unravel the structure of associations between physical measures of neuromuscular function and fear of movement in people with a history of neck pain. One hundred participants (mean age 33.3 ± 9.4) were assessed for this cross-sectional study, and the neuromuscular and kinematic features investigated were the range of motion, velocity of neck movement, smoothness of neck movement, neck proprioception (measured as the joint reposition error), and neck flexion and extension strength. The Tampa Scale for Kinesiophobia was used to assess fear of movement. A network analysis was conducted to estimate the associations across features, as well as the role of each feature in the network. The estimated network revealed that fear of movement and neuromuscular/kinematic features were conditionally dependent. Higher fear of movement was associated with a lower range of motion, velocity, smoothness of neck movement, neck muscle strength, and proprioception (partial correlations between − 0.05 and − 0.12). Strong interactions were also found between kinematics features, with partial correlations of 0.39 and 0.58 between the range of motion and velocity, and between velocity and smoothness, respectively. The velocity of neck movement was the most important feature in the network since it showed the highest strength value. Using a novel approach to analysis, this study revealed that fear of movement can be associated with a spectrum of neuromuscular/kinematic adaptations in people with a history of neck pain.

Maternal pain during pregnancy dose-dependently predicts postpartum depression: The Japan Environment and Children's Study

BACKGROUND

Postpartum depression (PPD) affects women during the first year after delivery. This study investigated the association between prenatal pain (maternal pain during pregnancy) and PPD.

METHODS

Data were analyzed from the Japan Environment and Children's Study (JECS), a nationwide prospective birth cohort study. Information on prenatal pain was collected twice during pregnancy through self-administered questionnaires. PPD symptoms were assessed using the Edinburgh Postnatal Depression Scale at one month postpartum. Poisson regression analyses were performed to investigate the association between prenatal pain and PPD, with other putative risk factors adjusted in the model.

RESULTS

Among 84,801 study subjects, 11,535 (13.6%) were screened as positive for PPD. In the present study, the occurrence of prenatal pain was 69.6 and 84.0% at the first trimester and the second/third trimester, respectively. A positive relationship between any degree of pain and PPD in both the first and the second/third trimester was observed. A significant linear dose-dependent association was also found (Ptrend < 0.001) when the subjects were divided by the severity of pain. Using participants without any pain at either point as a reference, those with persistent pain both at the first and the second/third trimesters showed the highest risk for PPD: aRR = 1.95 (95%CI: 1.76-2.15; p < 0.001).

LIMITATIONS

No detailed information regarding the type or site of prenatal pain was available in the JECS questionnaires, neither did data concerning delivery and postpartum pain.

CONCLUSIONS

The study results suggest that prenatal pain is a dose-dependent risk factor for the development of PPD.

The network structure of depressive symptomatology in Peruvian adults with arterial hypertension

Background: Globally, arterial hypertension (AH) has increased by 90% over the last four decades, and has increased by 1.6% in Peru over the previous four years. Scientific evidence indicates the prevalence of depressive symptoms in patients with AH and its importance in the comprehensive evaluation of the adult for adherence to clinical treatment. Previous studies carried out in the Peruvian population with AH mostly report the prevalence and associations, but do not indicate which depressive symptoms are more relevant in patients with AH. This study involved a network analysis of depressive symptomatology in Peruvian patients with AH using network estimation. Network analysis is used in this study for analysis, control, and monitoring purposes.

Method: A representative cross-sectional study at the national level, using secondary data from 2019 Demographic and Family Health Survey (ENDES) was performed. The sample used included men and women of age over 17 years diagnosed with AH and was able to respond to Patient Health Questionnaire-9 (PHQ-9).

Results: The symptoms of depressive mood (bridging force and centrality) and energy fatigue or loss (bridge centrality) play an essential role in the network structure, as does the feeling of uselessness in terms of closeness and intermediation.

Conclusion: The study highlighted the symptoms related to depressive mood and energy fatigue or loss as bridging symptoms, which could trigger a depressive episode in patients diagnosed with AH. The results will contribute to developing personalized treatments aimed at patients with specific depressive symptoms who have also been diagnosed with AH. The study analysis presents statistical coefficients of effect size (≤ 0,1 = small; > 0,1 to < 0,5 = moderate; ≥ 0,5 = large) to determine network connections.

Understanding how individualised physiotherapy or advice altered different elements of disability for people with low back pain using network analysis

Purpose

The Oswestry Disability Index (ODI) is a common aggregate measure of disability for people with Low Back Pain (LBP). Scores on individual items and the relationship between items of the ODI may help understand the complexity of low back disorders and their response to treatment. In this study, we present a network analysis to explore how individualised physiotherapy or advice might influence individual items of the ODI, and the relationship between those items, at different time points for people with LBP.

Methods

Data from a randomised controlled trial (n = 300) comparing individualised physiotherapy versus advice for low back pain were used. A network analysis was performed at baseline, 5, 10, 26 and 52 weeks, with the 10 items of the Oswestry Disability Index modelled as continuous variables and treatment group (Individualised Physiotherapy or Advice) modelled as a dichotomous variable. A Mixed Graphical Model was used to estimate associations between variables in the network, while centrality indices (Strength, Closeness and Betweenness) were calculated to determine the importance of each variable.

Results

Individualised Physiotherapy was directly related to lower Sleep and Pain scores at all follow-up time points relative to advice, as well as a lower Standing score at 10-weeks, and higher Lifting and Travelling scores at 5-weeks. The strongest associations in the network were between Sitting and Travelling at weeks 5 and 26, between Walking and Standing at week 10, and between Sitting and Standing scores at week 52. ODI items with the highest centrality measures were consistently found to be Pain, Work and Social Life.

Conclusion

This study represents the first to understand how individualised physiotherapy or advice differentially altered disability in people with LBP. Individualised Physiotherapy directly reduced Pain and Sleep more effectively than advice, which in turn may have facilitated improvements in other disability items. Through their high centrality measures, Pain may be considered as a candidate therapeutic target for optimising LBP management, while Work and Socialising may need to be addressed via intermediary improvements in lifting, standing, walking, travelling or sleep. Slower (5-week follow-up) improvements in Lifting and Travelling as an intended element of the Individualised Physiotherapy approach did not negatively impact any longer-term outcomes.

Trials registration

ACTRN12609000834257.

Depressive Symptomatology and Functional Status Among Stroke Survivors: A Network Analysis

OBJECTIVE

To (1) characterize poststroke depressive symptom network and identify the symptoms most central to depression, and (2) examine the symptoms that bridge depression and functional status.

DESIGN

Secondary data analysis of the Stroke Recovery in Underserved Population database. Networks were estimated using regularized partial correlation models. Topology, network stability and accuracy, node centrality and predictability, and bridge statistics were investigated.

SETTING

Eleven inpatient rehabilitation facilities across 9 states of the United States.

PARTICIPANTS

Stroke patients (N=1215) who received inpatient rehabilitation.

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURE

The Center for Epidemiologic Studies Depression Scale and Functional Independence Measure were administered at discharge from inpatient rehabilitation.

RESULTS

Depressive symptoms were positively intercorrelated within the network, with stronger connections between symptoms within the same domain. "Sadness" (expected influence=1.94), "blues" (expected influence=1.14), and "depressed" (expected influence=0.97) were the most central depressive symptoms, whereas "talked less than normal" (bridge expected influence=-1.66) emerged as the bridge symptom between depression and functional status. Appetite (R²=0.23) and sleep disturbance (R²=0.28) were among the least predictable symptoms, whose variance was less likely explained by other symptoms in the network.

CONCLUSION

Findings illustrate the potential of network analysis for discerning the complexity of poststroke depressive symptomology and its interplay with functional status, uncovering priority treatment targets and promoting more precise clinical practice. This study contributes to the need for expansion in the understanding of post-stroke psychopathology and challenges clinicians to use targeted intervention strategies to address depression in stroke rehabilitation.

Network analysis of anxiety and depressive symptoms among quarantined individuals: cross-sectional study

BACKGROUND

The mental health burden of COVID-19 has been examined in different settings. Existing research has relied on the latent variable model in assessing COVID-19-related distress. Network theory provides an alternative framework wherein symptoms are conceptualised as causal, interconnected constituents rather than outcomes of mental disorders.

AIMS

To assess networks of self-reported anxiety and depressive symptoms among quarantined individuals.

METHOD

Consenting individuals in different quarantine centres in Qatar completed the Patient Health Questionnaire Anxiety and Depression Scale. We used partial correlation network methods to illustrate interactions of self-reported psychopathology.

RESULTS

Participants with COVID-19 were significantly older and had a significantly higher proportion of males. The most central node was COVID-19, followed by thoughts of self-harm. COVID-19 status was strongly positively connected to thoughts of self-harm, which was positively connected to psychomotor changes, which were connected to decreased concentration. COVID-19 status was also positively connected to feeling anxious, which was strongly connected to inability to concentrate, which was connected to feeling afraid.

CONCLUSIONS

COVID-19 was the most influential factor, with the highest number and strength of connections to psychopathology in a network of anxiety and depressive symptoms in a quarantine setting. Beyond the resolution of the infection, therapeutic interventions targeting psychomotor changes might prove beneficial in reducing suicidality among quarantined individuals with COVID-19. Follow-up with mental health services after COVID-19 infection is needed to restore psychological well-being. Further research is needed to understand the short- and long-term psychological effects of COVID-19, and the outcomes of different therapeutic interventions.

How does individualised physiotherapy work for people with low back pain? A Bayesian Network analysis using randomised controlled trial data

PURPOSE

Individualised physiotherapy is an effective treatment for low back pain. We sought to determine how this treatment works by using randomised controlled trial data to develop a Bayesian Network model.

METHODS

300 randomised controlled trial participants (153 male, 147 female, mean age 44.1) with low back pain (of duration 6-26 weeks) received either individualised physiotherapy or advice. Variables with potential to explain how individualised physiotherapy works were included in a multivariate Bayesian Network model. Modelling incorporated the intervention period (0-10 weeks after study commencement-"early" changes) and the follow-up period (10-52 weeks after study commencement-"late" changes). Sequences of variables in the Bayesian Network showed the most common direct and indirect recovery pathways followed by participants with low back pain receiving individualised physiotherapy versus advice.

RESULTS

Individualised physiotherapy directly reduced early disability in people with low back pain. Individualised physiotherapy exerted indirect effects on pain intensity, recovery expectations, sleep, fear, anxiety, and depression via its ability to facilitate early improvement in disability. Early improvement in disability, led to an early reduction in depression both directly and via more complex pathways involving fear, recovery expectations, anxiety, and pain intensity. Individualised physiotherapy had its greatest influence on early change variables (during the intervention period).

CONCLUSION

Individualised physiotherapy for low back pain appears to work predominately by facilitating an early reduction in disability, which in turn leads to improvements in other biopsychosocial outcomes. The current study cannot rule out that unmeasured mechanisms (such as tissue healing or reduced inflammation) may mediate the relationship between individualised physiotherapy treatment and improvement in disability. Further data-driven analyses involving a broad range of plausible biopsychosocial variables are recommended to fully understand how treatments work for people with low back pain.

TRIALS REGISTRATION

ACTRN12609000834257.

Refractory Chronic Pain and Obesity: Promising Implications for Multidisciplinary Pain Rehabilitation

OBJECTIVE

Individuals with obesity frequently contend with chronic pain, but few studies address the clinical impact of coordinated pain services on this population. The current study addresses this topic by comparing the effectiveness of a comprehensive pain rehabilitation program for patients with and without obesity.

METHODS

A retrospective analysis of registry data was conducted. Obesity was considered as one of three weight groups, based on the following body mass index cutoffs: normal weight (18.5 to < 25 kg/m2), overweight (25 to < 30 kg/m2), and obese (> 30 kg/m2). These groups were compared on the Pain Severity Ratings (PSR) Scale, the Pain Disability Index (PDI), and the Depression, Anxiety, Stress Scales-Short Form (DASS-SF).

RESULTS

Groups differed on baseline pain disability and depression. Patients with obesity had higher scores on both the PDI (P = .028) and the DASS-SF depression subscale (P = .006). Contrary to the hypothesis, after controlling for baseline score and sex there were no significant differences between weight groups with regards to PSR, PDI, or any DASS-SF subscale at discharge. At 1-year follow-up, individuals who were overweight and obese had significantly more anxiety compared to individuals whose weight was in the normal range.

CONCLUSIONS

Multidisciplinary pain rehabilitation programs appear to be an effective treatment intervention for patients who have concomitant chronic pain and obesity, to a degree comparable to patients who have chronic pain but do not contend with obesity. Implications for program development, clinical interventions, and future research are discussed.

Early Treatment Improvements in Depression Are Associated With Overall Improvements in Fatigue Impact and Pain Interference in Adults With Multiple Sclerosis

BACKGROUND

Depression, fatigue, and pain commonly co-occur in multiple sclerosis (MS) and are positively associated with one another. However, it is unclear whether treatment-related improvement in one of these symptoms is associated with improvements in the other two symptoms.

PURPOSE

This study examined whether early improvements in depressive symptoms, fatigue impact, and pain interference during a multisymptom intervention in persons with MS were associated with overall improvements in the other two symptoms.

METHODS

Secondary analysis of a randomized controlled trial in which both treatments improved depressive symptoms, fatigue, and pain interference. Adults with MS experiencing chronic pain, chronic fatigue, and/or moderate depressive symptoms (N = 154, 86% women) participated in an 8-week, telephone-delivered intervention: self-management (n = 69) or education (n = 85); intervention groups were combined for the current study. Outcome measures were depressive symptoms (PHQ-9), fatigue impact (Modified Fatigue Impact Scale), and pain interference (Brief Pain Inventory). Path analysis examined associations between pre-to-mid intervention improvement in one symptom (i.e., depression, fatigue, pain interference) and pre-to-post (overall) improvement in the other two symptoms.

RESULTS

Early reduction in depressive symptoms was associated with an overall reduction in pain interference and fatigue impact (p's < .01). Early reduction in fatigue impact was associated with an overall reduction in depressive symptom severity (p = .04) but not pain interference. Early reduction in pain interference was not associated with reductions in fatigue impact or depressive symptoms.

CONCLUSIONS

These findings suggest the potential importance of reducing depressive symptoms to overall improvement in fatigue and pain interference in persons with MS.

CLINICAL TRIAL REGISTRATIONS

NCT00944190.

Understanding the Psychophysiological Mechanisms Related to Widespread Pressure Pain Hyperalgesia Underpinning Carpal Tunnel Syndrome: A Network Analysis Approach

OBJECTIVE

Current evidence suggests that carpal tunnel syndrome (CTS) involves widespread pressure pain sensitivity as manifestion of central sensitization. This study aimed to quantify mechanisms driving widespread pressure pain hyperalgesia in CTS by using network analysis.

DESIGN

Cross-sectional.

SETTING

Urban hospital.

SUBJECTS

120 women with CTS who participated in a previous randomized clinical trial.

METHODS

Pain intensity, related-function, symptom's severity, depressive levels, and pressure pain threshold (PPTs) over median, radial and ulnar nerves, the cervical spine, the carpal tunnel, and the tibialis anterior were collected. Network analysis was used to quantify the adjusted correlations between the modelled variables, and to determine the centrality indices of each variable (i.e., the degree of connection with other symptoms in the network).

RESULTS

The estimated network showed several local associations between clinical variables and the psychophysical outcomes separately. The edges with the strongest weights were between PPT over the median and radial nerves (ρ: 0.34), function and depressive levels (ρ: 0.30), and PPT over the carpal tunnel and tibialis anterior (ρ: 0.29). The most central variables were PPT over the tibialis anterior (the highest Strength centrality), and PPT over the carpal tunnel (the highest Closeness and Betweenness centrality).

CONCLUSIONS

This is the first study to apply network analysis to understand the multivariate mechanisms of individuals with CTS. Our findings support a model where clinical, depression, and widespread pressure pain sensitivity are connected, albeit within separate clusters. Clinical implications of current findings, such as developing treatments targeting these mechanisms, are also discussed.

A Network Analysis of Clinical Variables in Chronic Pain: A Study from the Swedish Quality Registry for Pain Rehabilitation (SQRP)

BACKGROUND

Efforts to identify specific variables that impact most on outcomes from interdisciplinary pain rehabilitation are challenged by the complexity of chronic pain. Methods to manage this complexity are needed. The purpose of the study was to determine the network structure entailed in a set of self-reported variables, examine change, and look at potential predictors of outcome, from a network perspective.

METHODS

In this study we apply network analysis to a large sample of people seeking interdisciplinary pain treatment (N = 2,241). Variables analyzed include pain intensity, pain interference, extent of pain, depression, anxiety, insomnia, and psychological variables from cognitive behavioral models of chronic pain.

RESULTS

We found that Acceptance, Pain Interference, and Depression were key, "central," variables in the pretreatment network. Interestingly, there were few changes in the overall network configuration following treatment, specifically with respect to which variables appear most central relative to each other. On the other hand, Catastrophizing, Depression, Anxiety, and Pain Interference each became less central over time. Changes in Life Control, Acceptance, and Anxiety were most strongly related to changes in the remainder of the network as a whole. Finally, no network differences were found between treatment responders and non-responders.

CONCLUSIONS

This study highlights potential future targets for pain treatment. Further application of a network approach to interdisciplinary pain rehabilitation data is recommended. Going forward, it may be better to next do this in a more comprehensive theoretically guided fashion, and ideographically, to detect unique individual differences in potential treatment processes.

Using latent profile analysis to evaluate the utility of a DSM-5 symptom checklist in screening children for autism spectrum disorder

Objective: Currently available screening measures for Autism Spectrum Disorder (ASD) typically do not reflect DSM-5 diagnostic criteria and generally have weak positive predictive values. These factors result in missed opportunities for early intervention, delays in diagnosis, and contribute to inefficient usage of healthcare resources by inadequately discerning those in need of comprehensive assessment. This study examined a DSM-5 ASD symptom checklist to determine whether parent-report response patterns could accurately identify which children received an ASD diagnosis. Method: Data were examined from 376 ASD evaluations in a three-year period. Latent profile analysis was used to determine if subgroups could be identified according to parent response patterns, and network analysis was implemented to examine the relationship among DSM-5 ASD criteria within each latent profile. Results: A four-profile model was best supported based on fit indices and high probability classifications. The model was largely a product of how parents responded regarding their child's sensory behavior and minimally reflected other symptomatology. Subsequent network analyses by profile indicated weak coherence among DSM-5 symptoms within all profiles. Overall, direct assessment of DSM-5 criteria based on parent report did not add diagnostic value beyond that reflected in base rates. Conclusions: Although continued refinement of ASD screening tools is needed to improve accuracy of referrals for evaluations and reduce wait time for diagnosis, this study continues to support the need for behavioral observation and formal assessment by trained clinicians. Continued development of sensitive and specific screening tools, likely with embedded behavioral and/or objective observation, is needed.

A Network Analysis of Major Depressive Disorder Symptoms and Age- and Gender-Related Differences in People over 65 in a Madrid Community Sample (Spain)

Major depressive disorder (MDD) is one of the most prevalent conditions among mental disorders in individuals over 65 years. People over 65 who suffer from MDD are often functionally impaired, chronically physically ill, and express cognitive problems. The concordance between a clinician-assessed MDD diagnosis in a primary care setting and MDD assessed with a structured clinical interview in older adults is only approximately 18%. Network analysis may provide an alternative statistical technique to better understand MDD in this population by a dimensional approach to symptomatology. The aim of this study was to carry out a network analysis of major depressive disorder (MDD) in people over 65 years old. A symptom network analysis was conducted according to age and gender in 555 people over 65, using a sample from the MentDis_ICF65+ Study. The results revealed different networks for men and women, and for the age groups 65–74 and 75–84. While depressive mood stood out in women, in men the network was more dispersed with fatigue or loss of energy and sleep disturbances as the main symptoms. In the 65–74 age group, the network was complex; however, in the 75–84 age group, the network was simpler with sleep disturbances as the central symptom. The gaps between the networks indicate the different characteristics of MDD in the elderly, with variations by gender and age, supporting the idea that MDD is a complex dynamic system that has unique characteristics in each person, rather than a prototypical classification with an underlying mental disorder. These unique characteristics can be taken into account in the clinical practice for detection and intervention of MDD.

Network Structure of Physical, Cognitive, and Emotional Symptoms at Preseason Baseline in Student Athletes with Attention-Deficit/ Hyperactivity Disorder

OBJECTIVE

Preexisting attention-deficit/hyperactivity disorder (ADHD) may be a risk factor for worse outcome following sport-related concussion. We used a statistical and psychometric approach known as network analysis to examine the architecture of physical, cognitive, and emotional symptoms at preseason baseline among student athletes with ADHD.

METHOD

A cohort of 44,527 adolescent student athletes completed baseline preseason testing with ImPACT® between 2009 and 2015. A subsample of athletes reporting a diagnosis of ADHD and at least one symptom were included in this study (N = 3,074; 14-18 years old, 32.7% girls). All participants completed the 22-item Post-Concussion Symptom Scale at preseason baseline.

RESULTS

Student athletes reported high frequencies of difficulty concentrating (boys/girls = 50.7%/59.4%), emotional symptoms (nervousness: boys/girls = 30.2%/51.0%; irritability: boys/girls = 23.6%/34.8%; sadness: boys/girls = 21.4%/39.7%), sleep/arousal-related symptoms (trouble falling asleep: boys/girls = 39.5%/49.4%; sleeping less than usual: boys/girls = 36.2%/43.4%; and fatigue: boys/girls = 29.8%/36.4%), and headaches (boys/girls = 27.6%/39.0%) during preseason baseline testing. The most central symptoms included dizziness, which was related to multiple somatic symptoms, and increased emotionality, which was related to a cluster of emotional symptoms. Girls reported symptoms at a greater frequency than boys, and there was evidence for variance in the global strength of the symptom network across gender, but not specific intersymptom relationships.

CONCLUSION

In the absence of injury, symptoms that commonly occur after concussion interact and potentially reinforce each other among student athletes with ADHD at preseason. Symptoms common in ADHD (i.e., difficulty concentrating) are not necessarily the most central within the symptom network. These findings may inform more precise interventions for athletes with ADHD and prolonged recovery following concussion.

Exploring the interconnectedness of fatigue, depression, anxiety and potential risk and protective factors in cancer patients: a network approach

Researchers have extensively studied fatigue, depression and anxiety in cancer patients. Several risk and protective factors have been identified for these symptoms. As most studies address these constructs, independently from other symptoms and potential risk and protective factors, more insight into the complex relationships among these constructs is needed. This study used the multivariate network approach to gain a better understanding of how patients' symptoms and risk and protective factors (i.e. physical symptoms, social withdrawal, illness cognitions, goal adjustment and partner support) are interconnected. We used cross-sectional data from a sample of cancer patients seeking psychological care (n = 342). Using network modelling, the relationships among symptoms of fatigue, depression and anxiety, and potential risk and protective factors were explored. Additionally, centrality (i.e. the number and strength of connections of a construct) and stability of the network were explored. Among risk factors, the relationship of helplessness and physical symptoms with fatigue stood out as they were stronger than most other connections in the network. Among protective factors, illness acceptance was most centrally embedded within the network, indicating it had more and stronger connections than most other variables in the network. The network identified key connections with risk factors (helplessness, physical symptoms) and a key protective factor (acceptance) at the group level. Longitudinal studies should explore these risk and protective factors in individual dynamic networks to further investigate their causal role and the extent to which such networks can inform us on what treatment would be most suitable for the individual cancer patient.

Diagnostic Issues of Depressive Disorders from Kraepelinian Dualism to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition

Because the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) was mainly influenced by the neo-Kraepelinian approach, its categorical approach to defining mental disorders has been criticized from the viewpoint of etiological neutrality. In the context of bridging the gap between "presumed etiologies-based symptomatology" and "identifiable pathophysiological etiologies," the content in 5th edition, the DSM-5, has been revised to incorporate a combination of categorical and dimensional approaches. The most remarkable change of note regarding the diagnostic classification of depressive disorders in the DSM-5 is the splitting of mood disorders into bipolar disorders and depressive disorders, which is in accordance with the deconstruction of the Kraepelinian dualism for psychoses. The transdiagnostic specifiers "with mixed features," "with psychotic features," and "with anxious distress" are introduced to describe the relationships of depressive disorders with bipolar disorders, schizophrenia, and generalized anxiety disorder, respectively, in a dimensional manner. The lowering of the diagnostic threshold for major depressive disorder (MDD) may be caused by the addition of "hopelessness" to the subjective descriptors of depressive mood and the elimination of "bereavement exclusion" from the definition of MDD. Since the heterogeneity of MDD is equivalent to the Wittgensteinian "games" analogy, the different types of MDD are related not by a single essential feature but rather by "family resemblance." Network analyses of MDD symptoms may therefore need further review to elucidate the connections among interrelated symptoms and other clinical elements.

Does mindfulness change the mind? A novel psychonectome perspective based on Network Analysis

If the brain is a complex network of functionally specialized areas, it might be expected that mental representations could also behave in a similar way. We propose the concept of ‘psychonectome’ to formalize the idea of psychological constructs forming a dynamic network of mutually dependent elements. As a proof-of-concept of the psychonectome, networks analysis (NA) was used to explore structural changes in the network of constructs resulting from a psychological intervention. NA was applied to explore the effects of an 8-week Mindfulness-Based Stress Reduction (MBSR) program in healthy participants (N = 182). Psychological functioning was measured by questionnaires assessing five key domains related to MBSR: mindfulness, compassion, psychological well-being, psychological distress and emotional-cognitive control. A total of 25 variables, covering the five constructs, were considered as nodes in the NA. Participants significantly improved in most of the psychological questionnaires. More interesting from a network perspective, there were also significant changes in the topological relationships among the elements. Expected influence and strength centrality indexes revealed that mindfulness and well-being measures were the most central nodes in the networks. The nodes with highest topological change after the MBSR were attentional control, compassion measures, depression and thought suppression. Also, cognitive appraisal, an adaptive emotion regulation strategy, was associated to rumination before the MBSR program but became related to mindfulness and well-being measures after the program. Community analysis revealed a strong topological association between mindfulness, compassion, and emotional regulation, which supports the key role of compassion in mindfulness training. These results highlight the importance of exploring psychological changes from a network perspective and support the conceptual advantage of considering the interconnectedness of psychological constructs in terms of a ‘psychonectome’ as it may reveal ways of functioning that cannot be analyzed through conventional analytic methods.

The Study of Psychopathology from the Network Analysis Perspective: A Systematic Review

BACKGROUND

Network analysis (NA) is an analytical tool that allows one to explore the map of connections and eventual dynamic influences among symptoms and other elements of mental disorders. In recent years, the use of NA in psychopathology has rapidly grown, which calls for a systematic and critical analysis of its clinical utility.

METHODS

Following PRISMA guidelines, a systematic review of published empirical studies applying NA in psychopathology, between 2010 and 2017, was conducted. We included the literature published in PubMed and PsycINFO using as keywords any combination of "network analysis" with the terms "anxiety," "affective disorders," "depression," "schizophrenia," "psychosis," "personality disorders," "substance abuse" and "psychopathology."

RESULTS

The review showed that NA has been applied in a plethora of mental disorders in adults (i.e., 13 studies on anxiety disorders; 19 on mood disorders; 7 on psychosis; 1 on substance abuse; 1 on borderline personality disorder; 18 on the association of symptoms between disorders), and 6 on childhood and adolescence.

CONCLUSIONS

A critical examination of the results of each study suggests that NA helps to identify, in an innovative way, important aspects of psychopathology like the centrality of the symptoms in a given disorder as well as the mutual dynamics among symptoms. Yet, despite these promising results, the clinical utility of NA is still uncertain as there are important limitations on the analytic procedures (e.g., reliability of indices), the type of data included (e.g., typically restricted to secondary analysis of already published data), and ultimately, the psychometric and clinical validity of the results.

Network Analysis and Precision Rehabilitation for the Post-concussion Syndrome

Some people experience persistent symptoms following a mild traumatic brain injury (MTBI), and the etiology of those symptoms has been debated for generations. Post-concussion-like symptoms are caused by many factors both before and after MTBI, and this non-specificity is the bedrock of the conundrum regarding the existence of the post-concussion syndrome. A latent model or common cause theory for the syndrome is inconsistent with the prevailing biopsychosocial conceptualization. It is the thesis of this paper that adopting a network perspective for persistent symptoms following MTBI, including the post-concussion syndrome, could lead to new insights and targeted treatment and rehabilitation strategies. The network perspective posits that symptoms co-occur because they are strongly inter-related, activating, amplifying, and mutually reinforcing, not because they arise from a common latent disease entity. This approach requires a conceptual shift away from thinking that symptoms reflect an underlying disease or disorder toward viewing inter-related symptoms as constituting the syndrome or disorder. The symptoms do not arise from an underlying syndrome—the symptoms are the syndrome. A network analysis approach allows us to embrace heterogeneity and comorbidity, and it might lead to the identification of new approaches to sequenced care. The promise of precision rehabilitation requires us to better understand the interconnections among symptoms and problems so that we can produce more individualized and effective treatment and rehabilitation.