Chapter 6: Conclusions, Limitations and Recommendations
3.3 Data Collection Technique and Research Instruments
3.3.5 Psychological Capital Questionnaire
The Psychological Capital Questionnaire (PCQ) was developed by Luthans, Youssef and Avolio (2007) and is used to assess various domains of psychological capital in participants who complete the questionnaire. In answering the questionnaire, participants rate their responses on a 6-point Likert scale (1 = strongly disagree, 2= disagree, 3 = somewhat disagree, 4 = somewhat agree, 5 = agree and 6 = strongly agree) for each of the 24-items. These 24-items are further divided into four subscales (each of which has 6 items) of psychological capital, namely; efficacy, hope, optimism and resilience (Luthans, Youssef & Avolio, 2007).
Therefore, the division of the PCQ into 4 underlying constructs, allows for the gathering of information that provides an overall inclusive measure of the higher order construct of psychological capital.
Various studies (Luthans et al., 2007; Avey et al., 2009, Toor & Ofori, 2010; Appollis, 2010;
Roberts et al., 2011; Simons & Buitendach, 2013) have found that the PCQ has good internal consistency with the Cronbach alpha coefficients for the overall scale exceeding 0.87. Luthans et al. (2007) established that the full PCQ scale had a Cronbach alpha coefficient of 0.91, whereas research conducted by Avey et al. (2010) found that the Cronbach alpha coefficient of 0.93. An alpha value of 0.88 was discovered by Toor and Ofori (2010) and an alpha value of 0.89 was found by Roberts et al. (2011). Within the South African context, a Cronbach alpha coefficient of 0.93 was discovered by Appolis (2010) for the overall scale, which was indicative of a high level of internal consistency for this instrument and thus suitable for use in South
Africa. Furthermore, within in the South African context, Pillay (2012) and Kesari (2012) both found alpha values of 0.88 and 0.82 respectively for the overall PCQ scale.
More recently, Simons and Buitendach (2013) confirmed an alpha value of 0.91 for the overall PCQ scale in South Africa, which is consistent with the original findings of Luthans, Youssef and Avolio (2007). Therefore, the multicultural applicability of the PCQ, especially in South Africa (Appolis, 2010; Simons & Buitendach, 2013), justifies the selection of this instrument in the present study as it has been proven to be both reliable and valid within the South African context. According to Avey et al. (2010), the subscales of the PCQ are drawn from previously established scales, they are as follows:
3.3.5.1 Self-Efficacy
The incorporation of Parker’s (1998) 6-item Self-Efficacy scale into the PCQ provides a measure of the participant’s self-efficacy through their responses to statements such as “I feel confident presenting information to a group of colleagues” and “I feel confident helping to set goals/targets in my work area”. According to Axtell and Parker (1998), the Cronbach coefficient alpha for this measure is 0.96; whereas research by Luthans, Avey and Patera (2008) reported an alpha value of 0.92 for this self-efficacy scale. Studies conducted in South Africa by Herbert (2011) found that the self-efficacy scale computed a Cronbach alpha coefficient of 0.83, which is indicative of good internal consistency.
3.3.5.2 Hope
Developed by Snyder (1996), the 6-item Hope scale was incorporated into the PCQ as it provides a measure of the participant’s hope through their responses to statements such as “At
the present time, I am energetically pursuing my goals” and “If I should find myself in a jam, I could think of many ways to get out of it”. Formative research by Luthans and Youssef (2004) computed a Cronbach alpha coefficient of 0.64 for this subscale; however, Roberts et al. (2011) discovered an alpha value of 0.80. The findings by Robert et al. (2011) were mirrored in South Africa by Herbert (2011) who discovered a Cronbach coefficient alpha value of 0.81 which is indicative of relatively good internal consistency for this subscale.
3.3.5.3. Hopeful Confidence
An exploratory factor analysis conducted by Pillay (2012) indicated a two factor model of the PCQ with items representing self-efficacy and hope loading onto one factor, and items that represented resilience and optimism loading on factor two (Pillay, 2012). This finding is in contrast to Du Plessis and Barkhuizen’s (2011) study that suggested a three factor model being most representative of a South African sample from which data was gathered. Both Du Plessis and Barkhuizen (2011), and Pillay (2012) further postulate that items relating to self-efficacy and hope can be renamed the hopeful-confidence subscale, which looks at having the self- confidence in one’s ability to pursue challenging tasks and persevere in order to reach such goals (Pillay, 2012). A similar finding was advanced by Setar, Buitendach and Kanengoni (2015) within their study. The PCA in their study indicated multiple correlation coefficients above 0.30 in the correlation matrix, inferring the suitability of the data for factor analysis (Setar, Buitendach & Kanengoni, 2015). The Kaiser-Meyer-Olkin and Bartlett’s Test of Sphericity values for were 0.778 and 0.000 respectively, indicating that their data was suitable for analysis (Setar, Buitendach & Kanengoni, 2015). Further analysis indicated that items relating to self-efficacy (items 1-6) as well as hope (items 7-12) loaded onto one factor, which was also consequently named the hopeful-confidence subscale which contributed 27.664% of
present study, both the self-efficacy and hope subscales will be referred to from here on out, as the hopeful-confidence subscale.
3.3.5.4 Resilience
Developed by Block and Kremen (1996), the 6-item Resilience scale (known as the Ego- Resiliency Scale) was incorporated into the PCQ as it provides a measure of the participant’s resiliency through their responses to statements such as “When I have a setback at work, I have trouble recovering from it, moving on” which is reversed scored; and “I usually manage difficulties one way or another at work”. Formative research conducted by Luthans et al.
(2008), indicated a Cronbach alpha value of 0.83 for the sub-construct of resilience; this finding is slightly higher than the alpha value of 0.81 computed by Roberts et al. (2011). The findings by Robert et al. (2011) were mirrored in South Africa by Du Plessis and Barkhuizen (2012) who discovered a Cronbach coefficient alpha value of 0.81 which is indicative of relatively good internal consistency for this subscale.
3.3.5.5 Optimism
The incorporation of Scheier and Carver’s (1985) 6-item Optimism scale (LOT-R) into the PCQ provides a measure of the participant's optimism through their responses to statements such as "In this job, things never work out the way I want them to" and "There are lots of ways around any problems that I am facing now". Recent research conducted by Du Plessis and Barkhuizen (2012) in South Africa computed a Cronbach alpha value of 0.77 which is indicative of matrix internal consistency for this measure.
3.3.5.6 Positive Outlook
An exploratory factor analysis conducted by Pillay (2012) indicated a two factor model of the PCQ with items representing self-efficacy and hope loading onto one factor whereas items that representing resilience and optimism loading on factor two (Pillay, 2012). The resilience subscale (items 13-18) as well as the optimism subscale (items 19-24) successfully loaded onto one factor, which according to Pillay (2012) can be renamed the positive outlook subscale, as it refers to being capable of bouncing back in the face of adversity and being optimistic about future success (Pillay, 2012). Similarly, Setar, Buitendach and Kanengoni’s (2015) study also produced a two factor structure of which resilience and optimism loaded onto one factor that contributed 9.564% of the total variance (37.228%). It is important to note the results of Du Plessis and Barkhuizen (2011), Pillay (2012) and Setar, Buitendach and Kanengoni (2015) present a departure from Luthans’ et al. (2007), Larson and Luthans’ (2006) and Avey et al.’s (2006) findings of a four factor model that is indicative of each subscale of the PCQ loading onto separate factors. The four factor model, as indicated by Luthans et al. (2007) explains 51.4% of total variance, whereas the two structure model explains 37.6% of the total variance (Pillay, 2012).