Association of personality traits with physical function, cognition, and mood in multiple sclerosis

The Path from Personality to Anxiety and Depression Is Mediated by Cognition in Multiple Sclerosis

BACKGROUND

Multiple sclerosis (MS) is a neurodegenerative immunological disease causing significant impairment in all life areas. Therefore, personality changes are observed and associated with higher prevalence of depression and anxiety disorders. Considering this relationship, we hypothesized that clinical symptoms and personality disorders are more prevalent in MS and that dysfunctional psychological mechanisms mediate the path from personality disorders to clinical symptoms.

METHODS

The study sample consisted of 43 patients with MS (age M = 41.9, SD = 11.5) and 31 controls (age M = 39.8, SD = 10.3). Measures of personality, anxiety, depression, fatigue, health status, and dysfunctional psychological mechanisms were conducted.

RESULTS

The prevalence of clinical symptoms was increased in MS patients as compared to controls. Also, dependent and schizoid personality traits (PTs) were observed in the patient sample. Negative automatic thoughts (NATs) were found to mediate the association between dependent PT and clinical symptoms. Along with schizoid PT, all dysfunctional psychological mechanisms impacted clinical symptoms.

DISCUSSION

The results of our research are in line with previous studies showing that anxiety, depression, and dysfunctional personality traits are more prevalent in MS as compared to controls.

CONCLUSIONS

PTs and dysfunctional psychological mechanisms predicted depression, anxiety, fatigue, and health status in MS patients. Cognition acts as a strong mediator between PTs and psychopathology in MS. Hence, integrative personalized psychological treatment is recommended to improve the quality of care in MS.

Multiple sclerosis and personality traits: associations with depression and anxiety

BACKGROUND

Depression and anxiety are commonly observed in people with multiple sclerosis (pwMS). There is a growing body of literature supporting the hypothesis that personality traits can influence the mood disorders. This study aimed to investigate the personality traits and their relationships with depression and anxiety among pwMS.

METHODS

234 pwMS were involved in this cross-sectional study. Personality traits, depression, and anxiety were assessed using the NEO Five-Factor Inventory (NEO-FFI) and Hospital Anxiety and Depression Scale (HADS), respectively. Pearson's correlation coefficient and generalized linear model were employed to evaluate the relationships between demographic and clinical characteristics, NEO-FFI, and HADS subscales.

RESULTS

In pwMS, longer disease duration was significantly associated with lower level of conscientiousness (β = - 0.23, p = 0.008) and agreeableness (β = - 0.2, p = 0.01). Moreover, higher expanded disability status scale (EDSS) of pwMS had a significant relationship with higher level of neuroticism (β = 0.89, p = 0.01). Increased level of neuroticism was significantly correlated with lower level of extraversion (r = - 0.28, p < 0.001), openness (r = - 0.37, p < 0.001), agreeableness (r = - 0.31, p < 0.001), and conscientiousness (r = - 0.45, p < 0.001). PwMS with higher level of conscientiousness showed more extraversion (r = 0.23, p < 0.001), openness (r = 0.61, p < 0.001), and agreeableness (r = 0.41, p < 0.001). Elevated level of neuroticism was significantly associated with higher level of anxiety (β = 0.47, p < 0.001) and depression (β = 0.11, p < 0.001) among pwMS.

CONCLUSION

The co-occurrence of depression and anxiety is probably associated with neuroticism among pwMS. Additionally, the impact of personality traits extends to influencing key disease aspects such as physical disability and disease duration in MS.

Impact of the COVID-19 Pandemic on the Personal Networks and Neurological Outcomes of People With Multiple Sclerosis: Cross-Sectional and Longitudinal Case-Control Study

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic has negatively affected the social fabric.

OBJECTIVE

We evaluated the associations between personal social networks and neurological function in people with multiple sclerosis (pwMS) and controls in the prepandemic and pandemic periods.

METHODS

During the early pandemic (March-December 2020), 8 cohorts of pwMS and controls completed a questionnaire quantifying the structure and composition of their personal social networks, including the health behaviors of network members. Participants from 3 of the 8 cohorts had additionally completed the questionnaire before the pandemic (2017-2019). We assessed neurological function using 3 interrelated patient-reported outcomes: Patient Determined Disease Steps (PDDS), Multiple Sclerosis Rating Scale-Revised (MSRS-R), and Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function. We identified the network features associated with neurological function using paired 2-tailed t tests and covariate-adjusted regressions.

RESULTS

In the cross-sectional analysis of the pandemic data from 1130 pwMS and 1250 controls during the pandemic, having a higher percentage of network members with a perceived negative health influence was associated with worse disability in pwMS (MSRS-R: β=2.181, 95% CI 1.082-3.279; P<.001) and poor physical function in controls (PROMIS Physical Function: β=-5.707, 95% CI -7.405 to -4.010; P<.001). In the longitudinal analysis of 230 pwMS and 136 controls, the networks of all participants contracted, given an increase in constraint (pwMS-prepandemic: mean 52.24, SD 15.81; pwMS-pandemic: mean 56.77, SD 18.91; P=.006. Controls-prepandemic: mean 48.07, SD 13.36; controls-pandemic: mean 53.99, SD 16.31; P=.001) and a decrease in network size (pwMS-prepandemic: mean 8.02, SD 5.70; pwMS-pandemic: mean 6.63, SD 4.16; P=.003. Controls-prepandemic: mean 8.18, SD 4.05; controls-pandemic: mean 6.44, SD 3.92; P<.001), effective size (pwMS-prepandemic: mean 3.30, SD 1.59; pwMS-pandemic: mean 2.90, SD 1.50; P=.007. Controls-prepandemic: mean 3.85, SD 1.56; controls-pandemic: mean 3.40, SD 1.55; P=.01), and maximum degree (pwMS-prepandemic: mean 4.78, SD 1.86; pwMS-pandemic: mean 4.32, SD 1.92; P=.01. Controls-prepandemic: mean 5.38, SD 1.94; controls-pandemic: mean 4.55, SD 2.06; P<.001). These network changes were not associated with worsening function. The percentage of kin in the networks of pwMS increased (mean 46.06%, SD 29.34% to mean 54.36%, SD 30.16%; P=.003) during the pandemic, a change that was not seen in controls.

CONCLUSIONS

Our findings suggest that high perceived negative health influence in the network was associated with worse function in all participants during the pandemic. The networks of all participants became tighter knit, and the percentage of kin in the networks of pwMS increased during the pandemic. Despite these perturbations in social connections, network changes from the prepandemic to the pandemic period were not associated with worsening function in all participants, suggesting possible resilience.

Personality Traits and Fatigue in Multiple Sclerosis: A Narrative Review

(1) Background: Multiple sclerosis (MS) is a chronic neurodegenerative autoimmune disease. Fatigue is a prevalent and debilitating symptom that significantly impacts the quality of life of these patients. A relationship between personality traits and fatigue in MS has been hypothesized but not clearly defined. (2) Methods: A literature search was carried out from databases up to April 2023 for studies correlating personality traits and fatigue in patients suffering from MS. (3) Results: A total of ten articles was included; most of the studies depict a neuroticism-fatigue correlation; however, they were not consistent in terms of the fatigue, personality, and covariate assessments. (4) Conclusions: The clinical and methodological heterogeneity of the included studies prevented us from drawing any firm conclusion on the link between personality traits and fatigue in MS. Several models of personality and different fatigue assessments have been found. Despite this, a common pathway shows that the neuroticism trait or similar personality patterns has a role in fatigue diagnosis. This may be a useful target to improve the quality of life and enhance the modification of the disease treatment results. Further homogeneous and longitudinal studies are needed.

Impact of resilience, social support, and personality traits in patients with neuroinflammatory diseases during the COVID-19 pandemic

BACKGROUND AND OBJECTIVE

The COVID-19 pandemic negatively impacted the well-being of persons with neuroinflammatory diseases (pwNID). Identifying factors that influence the response to challenging conditions could guide supportive care.

METHODS

2185 pwNID and 1079 healthy controls (HCs) from five US centers completed an online survey regarding the effects of the COVID-19 pandemic on physical and psychological well-being. Survey instruments included resilience (Connor-Davidson Resilience Scale, CD-RISC), loneliness (UCLA Loneliness Scale), social support (modified social support survey, MSSS-5), personality traits (NEO-Five Factor Inventory, NEO-FFI), and disability (Patient-Determined Disability Steps (PDDS). Step-wise regression models and mediation analyses assessed whether the level of self-reported resilience, size of the social support, and specific personality traits (study predictors) were associated with self-reported disability and/or loneliness (study outcomes).

RESULTS

The response rate varied significantly between the questionnaires. While, all pwNID completed the demographic questionnaire, 78.8% completed the loneliness questionnaire and 49.7% completed the NEO-FFI. Based on 787 responses, greater neuroticism (standardized β = 0.312, p < 0.001), less social support (standardized β = -0.242, p < 0.001), lower extraversion (standardized β = -0.083, p=0.017), lower agreeableness (standardized β = -0.119, p < 0.001), and lower resilience (standardized β = -0.125, p = 0.002) were associated with the feeling of loneliness. Social support and resilience modestly but significantly mediated the association between personality traits and loneliness. Older age (standardized β = 0.165, p < 0.001) and lower conscientiousness (standardized β = -0.094, p = 0.007) were associated with worse disability (higher PDDS scores). There were no differences in outcomes between pwNID and HCs.

CONCLUSION

Greater social support potentially attenuates the association between neuroticism and the feeling of loneliness in pwNID during the COVID-19 pandemic. Assessment of personality traits may identify pwNID that are in greater need of social support and guide targeted interventions.

Predicting Multiple Sclerosis Outcomes During the COVID-19 Stay-at-home Period: Observational Study Using Passively Sensed Behaviors and Digital Phenotyping

BACKGROUND

The COVID-19 pandemic has broad negative impact on the physical and mental health of people with chronic neurological disorders such as multiple sclerosis (MS).

OBJECTIVE

We presented a machine learning approach leveraging passive sensor data from smartphones and fitness trackers of people with MS to predict their health outcomes in a natural experiment during a state-mandated stay-at-home period due to a global pandemic.

METHODS

First, we extracted features that capture behavior changes due to the stay-at-home order. Then, we adapted and applied an existing algorithm to these behavior-change features to predict the presence of depression, high global MS symptom burden, severe fatigue, and poor sleep quality during the stay-at-home period.

RESULTS

Using data collected between November 2019 and May 2020, the algorithm detected depression with an accuracy of 82.5% (65% improvement over baseline; F₁-score: 0.84), high global MS symptom burden with an accuracy of 90% (39% improvement over baseline; F₁-score: 0.93), severe fatigue with an accuracy of 75.5% (22% improvement over baseline; F₁-score: 0.80), and poor sleep quality with an accuracy of 84% (28% improvement over baseline; F₁-score: 0.84).

CONCLUSIONS

Our approach could help clinicians better triage patients with MS and potentially other chronic neurological disorders for interventions and aid patient self-monitoring in their own environment, particularly during extraordinarily stressful circumstances such as pandemics, which would cause drastic behavior changes.