Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, Pennsylvania; Department of Biostatistics, University of Pittsburgh, Pittsburgh, Pennsylvania; Institute of Statistical Research and Training, University of Dhaka, Dhaka, Bangladesh.
Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, Pennsylvania.
Arch Phys Med Rehabil. 2020 May;101(5):797-806. doi: 10.1016/j.apmr.2019.10.189. Epub 2019 Dec 7.
To describe the interrelationship of postinjury employment and substance abuse (SA) among individuals with traumatic brain injury.
Structural equation model (SEM) and logistic regression analytic approach using a merged database of the National Trauma Data Bank (NTDB) and Traumatic Brain Injury Model Systems (TBIMS) National Database, with acute care and rehabilitation hospitalization data and 1, 2, and 5 year follow-up data.
United States Level I/II trauma centers and inpatient rehabilitation centers with telephone follow-up.
Individuals in the TBIMS National Database successfully matched to their NTDB data, aged 18-59 years, with trauma severity, age, sex, employment, and SA data at 1, 2, and/or 5 years postinjury (N=2890).
Not applicable.
Employment status (employed/unemployed) and SA (present/absent) at year 1, year 2, and year 5 postinjury.
SEM analysis showed older age at injury predicted lower likelihood of employment at all time points postinjury (β=-0.016; β=-0.006; β=-0.016; all P<.001), while higher injury severity score (ISS) predicted lower likelihood of employment (β=-0.008; P=.027) and SA (β=-0.007; P=.050) at year 1. Male sex predicted higher likelihood of SA at each follow-up (β=0.227; β=0.184; β=0.161; all P<.100). Despite associations of preinjury unemployment with higher preinjury SA, postinjury employment at year 1 predicted SA at year 2 (β=0.118; P=.028). Employment and SA during the previous follow-up period predicted subsequent employment and SA, respectively.
Employment and SA have unique longitudinal interrelationships and are additionally influenced by age, sex, and ISS. The present work suggests the need for more research on causal, confounding, and mediating factors and appropriate screening and intervention tools that minimize SA and facilitate successful employment-related outcomes.
描述创伤性脑损伤患者受伤后就业与物质滥用(SA)之间的相互关系。
使用国家创伤数据库(NTDB)和创伤性脑损伤模型系统(TBIMS)国家数据库的合并数据库,采用结构方程模型(SEM)和逻辑回归分析方法,对急性护理和康复住院数据以及 1、2 和 5 年随访数据进行分析。
美国一级/二级创伤中心和有电话随访的住院康复中心。
TBIMS 国家数据库中成功与 NTDB 数据匹配的年龄在 18-59 岁之间的个体,创伤严重程度、年龄、性别、就业和 SA 数据在 1、2 和/或 5 年受伤后(N=2890)。
不适用。
受伤后 1 年、2 年和 5 年的就业状况(就业/失业)和 SA(存在/不存在)。
SEM 分析显示,受伤时年龄较大预示着受伤后所有时间点的就业可能性较低(β=-0.016;β=-0.006;β=-0.016;均 P<.001),而较高的损伤严重程度评分(ISS)则预示着受伤后就业的可能性较低(β=-0.008;P=.027)和 SA(β=-0.007;P=.050)。男性性别预示着每个随访时 SA 的可能性更高(β=0.227;β=0.184;β=0.161;均 P<.100)。尽管受伤前失业与较高的受伤前 SA 有关,但受伤后 1 年的就业预测了 2 年的 SA(β=0.118;P=.028)。前一个随访期间的就业和 SA 分别预测了随后的就业和 SA。
就业和 SA 具有独特的纵向相互关系,并且还受到年龄、性别和 ISS 的影响。目前的研究表明,需要更多的关于因果关系、混杂因素和中介因素的研究,以及适当的筛查和干预工具,以减少 SA 并促进成功的就业相关结果。