Sora Beatriz, Caballer Amparo, García-Buades Esther
Universitat Oberta de Catalunya (Spain).
Universidad de Valencia (Spain).
Span J Psychol. 2018 Nov 19;21:E51. doi: 10.1017/sjp.2018.52.
Applications of job crafting are widespread in the professional practice. In an attempt to measure this phenomenon, Tims, Bakker and Derks (2012) developed a Job Crafting Scale based on the Job Demand-Resources model (JD-R) and validated it in a Dutch sample. However, its application to other cultural contexts presented some difficulties. The present work aimed to validate a shorter version of scale by Tims et al. (2012) in a Spanish sample (n = 1,647). The data were randomly split in two independent subsamples (Sample 1: Explorative; Sample 2: Confirmative). The exploratory factor analysis showed a three-factor structure. Through a confirmatory factor analysis, the four-dimensionality structure of the original scale was replicated. In fact, the four-factor solution presented better goodness of fit indices than the alternative one-factor model, χ2(48) = 192.70, p < .01; AGFI = .94; NNFI = .93; RMR = .05; RMSEA = .06. Alpha reliabilities were acceptable for increasing structural job resources (α = .75), decreasing hindering job demands (α = .64), increasing social job resources (α = .78) and increasing challenging job demands (α = .77). Convergent validity was appropriate for three of the four dimensions, because each construct's AVE were around .50 and each construct's Composite Reliability were around .70. Decreasing hindering job demands presented more limited values (CR = .65; AVE = .40). In addition, the four job crafting dimensions presented significant correlations with job performance (range -.09 to .42) and personal growth (ranging from -.09 to .45). Finally, the squared correlations between factors were lower than the square root of AVE, which confirmed discriminant validity.
工作重塑在专业实践中的应用十分广泛。为了衡量这一现象，廷姆斯、巴克尔和德克斯（2012年）基于工作需求-资源模型（JD-R）开发了工作重塑量表，并在荷兰样本中进行了验证。然而，将其应用于其他文化背景时出现了一些困难。本研究旨在对廷姆斯等人（2012年）开发的量表的一个较短版本在西班牙样本（n = 1647）中进行验证。数据被随机分为两个独立的子样本（样本1：探索性；样本2：验证性）。探索性因素分析显示出一个三因素结构。通过验证性因素分析，原量表的四维结构得以重现。事实上，四因素解的拟合优度指标比替代的单因素模型更好，χ2(48) = 192.70，p <.01；AGFI =.94；NNFI =.93；RMR =.05；RMSEA =.06。增加结构性工作资源（α =.75）、减少阻碍性工作需求（α =.64）、增加社会性工作资源（α =.78）和增加挑战性工作需求（α =.77）的α信度是可接受的。四个维度中的三个维度的收敛效度是合适的，因为每个构念的AVE约为.50，每个构念的组合信度约为.70。减少阻碍性工作需求的相关值更有限（CR =.65；AVE =.40）。此外，工作重塑的四个维度与工作绩效（范围为-.09至.42）和个人成长（范围为-.09至.45）呈现出显著相关性。最后，各因素之间的平方相关低于AVE的平方根，这证实了区分效度。
