Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, USA.
Dornsife Center for Self-Report Science and Center for Social & Economic Research, University of Southern California, Los Angeles, CA, USA.
Ergonomics. 2022 Jul;65(7):960-975. doi: 10.1080/00140139.2021.2006317. Epub 2021 Nov 22.
Our objective was to investigate the validity of four-item and six-item versions of the National Aeronautics and Space Administration Task Load Index (NASA-TLX, or TLX for short) for measuring workload over a in the context. We analysed data on 51 people with type 1 diabetes from whom we collected ecological momentary assessment and daily diary data over 14 days. The TLX was administered at the last survey of every day. Confirmatory factor analysis fit statistics indicated that neither the TLX-6 nor TLX-4 were a unidimensional representation of whole day workload. In exploratory analyses, another set of TLX items we refer to as TLX-4v2 was sufficiently unidimensional. Raw sum scores from the TLX-6 and TLX-4v2 had plausible relationships with other measures, as evidenced by intra-person correlations and mixed-effects models. TLX-6 appears to capture multiple factors contributing to workload, while TLX-4v2 assesses the single factor of 'mental strain'. Using within-person longitudinal data, we found evidence supporting the validity of a measure evaluating whole-day workload (i.e. workload derived from all sources, not only paid employment) derived from the NASA-TLX. This measure may be useful to assess how day-to-day variations in workload impact quality of life among adults. NASA-TLX or TLX: National Aeronautics and Space Administration Task Load Index; TLX-6: six item version of the NASA-TLX; TLX-4: four item version of the NASA-TLX, TLX-4v2: four item NASA-TLX version two; NIOSH: National Institute for Occupational Safety and Health; CFA: confirmatory factor analysis; T1D: type 1 diabetes; EMA: ecological momentary assessment; BG: blood glucose; SD: standard deviation; CV: coefficient of variation; RMSEA: root mean square error of approximation; CFI: comparative fit index; TLI: Tucker-Lewis Index; SRMR: standardized root mean square residual; AIC: Akaike information criterion; BIC: Bayesian information criterion; χ2: Chi-square statistic.
我们的目的是研究四分量和六分量版本的美国国家航空航天局任务负荷指数(NASA-TLX,简称 TLX)在[语境]下测量工作负荷的有效性。我们分析了 51 名 1 型糖尿病患者的数据,这些患者在 14 天内接受了生态瞬间评估和日常日记数据的收集。TLX 在每天的最后一次调查中进行。验证性因子分析拟合统计数据表明,TLX-6 和 TLX-4 都不是一整天工作负荷的单维表示。在探索性分析中,我们称之为 TLX-4v2 的另一组 TLX 项目具有足够的单维性。TLX-6 和 TLX-4v2 的原始总分与其他测量方法具有合理的关系,这表现在个体内相关性和混合效应模型中。TLX-6 似乎可以捕捉到导致工作负荷的多个因素,而 TLX-4v2 则评估了“心理压力”这一个单一因素。使用个体内纵向数据,我们发现了支持评估全天工作负荷(即源自所有来源的工作负荷,不仅是有偿就业)的 NASA-TLX 测量方法有效性的证据。这种测量方法可能有助于评估日常工作负荷变化如何影响成年人的生活质量。NASA-TLX 或 TLX:美国国家航空航天局任务负荷指数;TLX-6:六分量版本的 NASA-TLX;TLX-4:四分量版本的 NASA-TLX;TLX-4v2:四分量 NASA-TLX 版本 2;NIOSH:美国国家职业安全与健康研究所;CFA:验证性因子分析;T1D:1 型糖尿病;EMA:生态瞬间评估;BG:血糖;SD:标准差;CV:变异系数;RMSEA:近似均方根误差;CFI:比较拟合指数;TLI:塔克-刘易斯指数;SRMR:标准化均方根残差;AIC:赤池信息量准则;BIC:贝叶斯信息量准则;χ2:卡方统计量。