Explaining fatigue in multiple sclerosis: cross-validation of a biopsychosocial model

被引:0
|
作者
Melloney L. M. Wijenberg
Sven Z. Stapert
Sebastian Köhler
Yvonne Bol
机构
[1] Maastricht University,Faculty of Psychology and Neuroscience
[2] Maastricht University,Faculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience
[3] Zuyderland Medical Center,Department of Medical Psychology/Academic MS Center Limburg
来源
关键词
Multiple sclerosis; Fatigue; Catastrophizing; Physical disability; Structural equation modelling; Biopsychosocial model;
D O I
暂无
中图分类号
学科分类号
摘要
Fatigue is a common and disabling symptom in patients with multiple sclerosis (MS), but its pathogenesis is still poorly understood and consequently evidence-based treatment options are limited. Bol et al. (J Behav Med 33(5):355–363, 2010) suggested a new model, which explains fatigue in MS from a biopsychosocial perspective, including cognitive-behavioral factors. For purposes of generalization to clinical practice, cross-validation of this model in another sample of 218 patients with MS was performed using structural equation modeling. Path analysis indicated a close and adequate global fit (RMSEA = 0.053 and CFI = 0.992). The cross-validated model indicates a significant role for disease severity, depression and a fear-avoidance cycle in explaining MS-related fatigue. Modifiable factors, such as depression and catastrophizing thoughts, propose targets for treatment options. Our findings are in line with recent evidence for the effectiveness of a new generation of cognitive behavioral therapy, including acceptance and mindfulness-based interventions, and provide a theoretical framework for treating fatigue in MS.
引用
收藏
页码:815 / 822
页数:7
相关论文
共 50 条
  • [21] Cross-validation for comparing multiple density estimation procedures
    Lian, Heng
    STATISTICS & PROBABILITY LETTERS, 2009, 79 (01) : 112 - 115
  • [22] PROSPECTIVE VALIDATION OF A BIOPSYCHOSOCIAL MODEL EXPLAINING PERSISTENT NCCP-RELATED DISABILITY
    Foldes-Busque, Guillaume
    Tremblay, Marie-Andree
    Turcotte, Stephane
    Fleet, Richard
    Archambault, Patrick M.
    Dionne, Clermont E.
    Denis, Isabelle
    PSYCHOSOMATIC MEDICINE, 2020, 82 (06): : A177 - A177
  • [23] Multiple sclerosis: cross-cultural adaptation and validation of the modified fatigue impact scale
    Pavan, Karina
    Schmidt, Kizi
    Marangoni, Bruna
    Mendes, Maria Fernanda
    Tilbery, Charles Peter
    Lianza, Sergio
    ARQUIVOS DE NEURO-PSIQUIATRIA, 2007, 65 (3A) : 669 - 673
  • [24] Separating model optimization and model validation in statistical cross-validation as applied to crystallography
    Kleywegt, Gerard J.
    ACTA CRYSTALLOGRAPHICA SECTION D-STRUCTURAL BIOLOGY, 2007, 63 : 939 - 940
  • [25] Cross-Validation Model Averaging for Generalized Functional Linear Model
    Zhang, Haili
    Zou, Guohua
    ECONOMETRICS, 2020, 8 (01)
  • [26] Fast Cross-Validation
    Liu, Yong
    Lin, Hailun
    Ding, Lizhong
    Wang, Weiping
    Liao, Shizhong
    PROCEEDINGS OF THE TWENTY-SEVENTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2018, : 2497 - 2503
  • [27] Cross-Validation With Confidence
    Lei, Jing
    JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2020, 115 (532) : 1978 - 1997
  • [28] Cross-validation Revisited
    Dutta, Santanu
    COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 2016, 45 (02) : 472 - 490
  • [29] Multifidelity Cross-validation
    Renganathan, Ashwin
    Carlson, Kade
    AIAA AVIATION FORUM AND ASCEND 2024, 2024,
  • [30] Targeted cross-validation
    Zhang, Jiawei
    Ding, Jie
    Yang, Yuhong
    BERNOULLI, 2023, 29 (01) : 377 - 402