Abstract
In recent years, leadership issues related to ethics (and, most prominently, ethical failures) have been frequently drawn into the public spotlight. Concurrently, leadership research has shifted toward virtue-based theories and the consideration of leader character. Although patience has been rarely discussed in the context of leadership, the important of patience can be understood considering its role as a virtue. The virtue of patience describes a condition of tranquility while waiting for an outcome or persevering under provocation. Although patience can perhaps most clearly be exemplified in the Judeo-Christian context as the characteristic of a God that did not abandon His people despite their frequent disloyal treatment of Him, this virtue can be a powerful tool for proactive, rather than reactive, leaders. This chapter considers a biblical understanding of patience and how this characteristic can be incorporated into modern leadership contexts.
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Chapter Addendum on the Scale for Patience
Chapter Addendum on the Scale for Patience
Twelve items were developed from the exegetical study, and the expert panel rated all of the items at an average of 3 or higher, thus we kept all 12 items. In this addendum, we present the sample demographics, KMO and Bartlett’s test for sphericity results, the results of the principal component analysis, and the optimized final scale for gentleness.
Of the 81 people in our participant pool, 60 completed the survey, which is at the minimum of five participants per item recommended by DeVellis (2017). The sample consisted of 36 males, 23 females, and one that did not make a choice of gender. Two participants were aged 21–29, seven were in the age group of 30–39, 17 were 40–49 years of age, 14 were between 50 and 59, and the remaining 19 were 60 or over. One person declined to state his/her age. Fifty-seven people were from the United States, one from Malaysia, one from South Africa, and one from Thailand. Table 5.1 is a summary of the demographics.
We analyzed the data using KMO and Bartlett’s test for sphericity to see if the data were appropriate for factor analysis. The KMO score was .93, indicating that the data were appropriate for factor analysis (χ2 = 704.76; p < .001).
We conducted a principal component analysis on the 12 items suppressing scores below .40 and we found one factor that had an eigenvalue of 8.45 and explained 70.4% of the variance.
Since the 12-item scale had a Cronbach’s alpha of .96, we were comfortable with optimizing the scale by selecting the five highest loading items. We reran the principal component analysis and Cronbach’s alpha. The five-item scale had an eigenvalue of 4.03 that explained 80.50% of the variance and had a Cronbach’s alpha of .94. Table 5.2 shows the five items and the factor loadings.
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Bocarnea, M.C., Henson, J., Huizing, R.L., Mahan, M., Winston, B.E. (2018). Calm in the Storm: Leading with Patience. In: Evaluating Employee Performance through Christian Virtues. Christian Faith Perspectives in Leadership and Business. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-74344-8_5
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