What factors are associated with resilience in persons with multiple sclerosis? The role of personality traits.
Bibliographic record
Abstract
PURPOSE/OBJECTIVE: While personality traits have been well-documented to be related to resilience in several populations, they have yet to be explored in people with multiple sclerosis (PwMS). As such, this study aimed to understand how personality traits are associated with MS-related resilience after considering the independent contributions of self-efficacy, a significant component of the biopsychosocial model of resilience in MS, and demographic and disease characteristics. RESEARCH METHOD/DESIGN: = 112) were PwMS who completed a 1-time cross-sectional study. Resilience was measured using the MS Resiliency Scale, while personality traits and self-efficacy were assessed using the NEO-Five Factor Inventory-3 and University of Washington Self-Efficacy Scale, respectively. An ordinary least squares linear regression was run to examine the relationship between resilience, personality traits, self-efficacy, and demographic and disease characteristics. RESULTS: = .044) were significantly related to resilience. While extraversion, conscientiousness, and agreeableness were associated with resilience on a bivariate level, they were not significant in the multivariate model. CONCLUSIONS/IMPLICATIONS: This study highlights how neuroticism, along with self-efficacy and marital status, plays a role in MS-related resilience. While further research is needed, these findings may help inform future resilience-building interventions or identify individuals at greater risk for lower levels of resilience. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".