Department of Psychology.
J Appl Psychol. 2022 Oct;107(10):1678-1705. doi: 10.1037/apl0000964. Epub 2021 Oct 21.
Although biodata inventories have long been used to hire job applicants, there are limitations to current biodata knowledge and little in the way of contemporary biodata meta-analytic reviews. This study establishes a precise understanding of biodata validity by conducting an updated meta-analysis that differentiates biodata validity in terms of two important defining features: construct domain and scoring method (rational, hybrid, empirical). Evidence was established in terms of criterion-related validity with job performance and additional work outcomes, as well as convergent validity with common external hiring measures. In total, 180 independent samples of criterion correlations were examined, and 63 samples were analyzed containing correlations with convergent measures. Findings across the meta-analyses revealed that biodata inventories are one of the most predictive assessment methods available, but that the relationship with work outcomes differs by construct domain and scoring method. Empirically scored overall composite scales had superior criterion-related validity (ρ = .44) to rationally scored composite scales (ρ = .24). Scales developed to measure conscientiousness and leadership were generally the most predictive of the job performance of the narrow construct domains, and particularly when empirically keyed. However, when biodata scores were correlated with theoretically aligned performance ratings, rational scoring resulted in similar validity coefficients as empirical scoring. Finally, biodata scales exhibited expected patterns of correlations with external measures and were only modestly correlated with cognitive ability and five-factor model personality scores. Taken together, biodata inventories are highly predictive assessment methods and are likely to provide unique variance over other common predictors. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
尽管生物数据目录长期以来一直被用于招聘求职者,但目前的生物数据知识存在局限性,并且缺乏当代生物数据元分析综述。本研究通过进行更新的元分析,建立了对生物数据有效性的精确理解,该分析根据两个重要的定义特征区分了生物数据的有效性:构念领域和评分方法(理性、混合、经验)。根据与工作绩效和其他工作结果的相关标准的有效性,以及与常见外部招聘措施的收敛有效性,为证据提供了依据。总共检查了 180 个独立的标准相关系数样本,并且分析了包含与收敛措施相关的系数的 63 个样本。元分析的研究结果表明,生物数据目录是最具预测性的评估方法之一,但与工作结果的关系因构念领域和评分方法而异。经验评分的总体综合评分具有较高的相关标准有效性(ρ=.44),优于理性评分的综合评分(ρ=.24)。为衡量责任心和领导力而开发的量表通常是最能预测狭窄构念领域的工作绩效的,尤其是在经验性关键的情况下。然而,当将生物数据评分与理论上一致的绩效评分相关联时,理性评分导致与经验评分相似的有效性系数。最后,生物数据量表与外部测量具有预期的相关模式,并且与认知能力和五因素模型人格得分仅适度相关。总而言之,生物数据目录是高度预测性的评估方法,并且很可能提供其他常见预测指标所无法提供的独特差异。(PsycInfo 数据库记录(c)2022 APA,保留所有权利)。