London Health Sciences Center, London, Ontario, Canada.
Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, Parkwood Institute, Lawson Health Research Institute, University of Western Ontario, 550 Wellington Rd, London, ON, Canada.
Mult Scler Relat Disord. 2019 Nov;36:101411. doi: 10.1016/j.msard.2019.101411. Epub 2019 Sep 26.
Multiple Sclerosis (MS) is a common cause of neurological disability in young to middle-aged adults, resulting in physical, psychosocial, and cognitive impairments. Manifestation of these symptoms during crucial work-life years can greatly influence the ability of persons with (PwMS) to retain employment. It is unknown what factors are most important in leading to work disability, and if/how these different factors interact with each other and result in work disability.
To determine significant predictors of vocational status among PwMS using a structural equation modeling approach.
A retrospective chart review identified PwMS at an academic tertiary care hospital. The following data was collected: demographics and disease characteristics, vocational status, physical disability status (Expanded Disability Status Scale, EDSS), fine motor function (Nine Hole Peg Test, NHPT), generalized fatigue (Fatigue Severity Scale, FSS), mood and anxiety symptoms (Hospital Anxiety and Depression Scale, HADS) and cognitive function (Symbol Digit Modalities Test, SDMT). An exploratory structural equation model (SEM) was developed to examine the predictive utility of clinical and psychosocial variables on vocational status after controlling for demographic and disease characteristics. The fit of the model to the data was examined using the comparative fit index (CFI), normal fit index (NFI), root-mean-squared error of approximation (RMSEA), and standardized root mean residual (SRMR).
There were 158 PwMS included in the analysis. The final model demonstrated that SDMT (β = 0.16), EDSS (β = -0.33), and HADS-D (β = -0.23) significantly predicted vocational status (ps < 0.05). It explained 37% of the variance and provided a good fit to the data (χ(11) = 13.01, p > 0.05, SRMR = 0.055, RMSEA = 0.034, NFI = 0.94, CFI = 0.99.
Physical disability, depressive symptoms, and reduced information processing affect work-related disability and vocational status among PwMS. Interventions targeting these factors should be prioritized by clinicians.
多发性硬化症(MS)是中青年人群中常见的神经功能障碍病因,可导致身体、心理社会和认知障碍。这些症状在关键的工作生活期间出现,会极大地影响患者(PwMS)保持就业的能力。目前尚不清楚哪些因素是导致工作能力丧失的最重要因素,以及这些不同因素如何相互作用并导致工作能力丧失。
采用结构方程模型方法确定 PwMS 职业状况的显著预测因素。
回顾性病历分析确定了学术三级护理医院的 PwMS。收集了以下数据:人口统计学和疾病特征、职业状况、身体残疾状况(扩展残疾状况量表,EDSS)、精细运动功能(九孔钉测试,NHPT)、全身疲劳(疲劳严重程度量表,FSS)、情绪和焦虑症状(医院焦虑和抑郁量表,HADS)和认知功能(符号数字模态测试,SDMT)。建立探索性结构方程模型(SEM),以检查临床和心理社会变量对职业状况的预测效用,同时控制人口统计学和疾病特征。使用比较拟合指数(CFI)、正常拟合指数(NFI)、均方根误差近似值(RMSEA)和标准化根均方残差(SRMR)来检查模型对数据的拟合程度。
共有 158 名 PwMS 纳入分析。最终模型表明,SDMT(β=0.16)、EDSS(β=-0.33)和 HADS-D(β=-0.23)显著预测职业状况(p<0.05)。它解释了 37%的方差,并且与数据拟合良好(χ(11)=13.01,p>0.05,SRMR=0.055,RMSEA=0.034,NFI=0.94,CFI=0.99)。
身体残疾、抑郁症状和信息处理能力下降会影响 PwMS 的与工作相关的残疾和职业状况。临床医生应优先针对这些因素进行干预。