Abstract:Purpose
The purpose of this paper is to examine the psychometric properties of the positive and negative affect schedule (PANAS) in a sample of employees working in Indian manufacturing and service sector organisations.
Design/methodology/approach
The data were collected through self-administered structured questionnaire from 53 employees for the pilot study and 383 employees for the final study. For the psychometric evaluation of the PANAS, item analysis, reliability, exploratory factor analysis, convergent… Show more
“…In line with previous studies, discriminant validity (correlation with theoretically dissimilar construct) of SWLS was measured using two scales (Dahiya and Rangnekar, 2018b;Thompson et al, 2005). One being positive and negative affect schedule (PANAS; Dahiya and Rangnekar, 2019c) with two dimensions (positive affect [PA] and negative affect [NA]), containing ten items in each. The participants responded to a seven-point scale ranging from "never" as 1 to "always" as 7.…”
Section: Instrumentsmentioning
confidence: 95%
“…Discriminant validity of the scale. Following the recommendation of Churchill and Iacobucci (2002), we examined the correlation coefficient between SWLS with two theoretical dissimilar scales, namely PANAS (Dahiya and Rangnekar, 2019c) and the HFS (Dahiya and Rangnekar, 2018b). The results of the coefficient of correlations showed that SWLS positively related with the positive affect (r 5 0.19, p < 0.01), negatively with negative affect (r 5 À0.14, p < 0.01) and positively related with forgiveness (r 5 0.18, p < 0.01).…”
Section: External Validity Analysismentioning
confidence: 99%
“…Need for validation of SWLS in Indian manufacturing sector Indeed, there has been a recognition among scholars of a need for organizations within the Indian manufacturing sector to lay emphasis on fostering positive psychological functioning among employees by studying variables such as life satisfaction (Singhal and Rastogi, 2018). These organizations are facing intense global competition, incessant technological changes and restructuring (Dahiya and Rangnekar, 2019c). On one hand, this offers career opportunities and growth to employees and, on the other, unceasing competitive pressure that leads to stress at work (Chhabra, 2018).…”
PurposeIn the modern world, life satisfaction has become a quintessential construct for large-scale organizations, and a valid measure to evaluate employee life satisfaction is required. Therefore, this study aims to evaluate the psychometric properties of the satisfaction with life scale (SWLS) in a sample of employees working in the Indian manufacturing sector.Design/methodology/approachSurvey method was used for data collection among a sample of 404 employees. Further, the psychometric properties of SWLS were evaluated with reference to reliability and validity assessment (face, content and construct validity).FindingsThe results were found to be significant for SWLS to assess the life satisfaction of employees working in manufacturing organizations in India.Originality/valueThis study attempts to validate SWLS among employees, which is a novel contribution in the field. Also, it suggests that effective application of SWLS can help in identifying and understanding the work-related factors associated with life satisfaction.
“…In line with previous studies, discriminant validity (correlation with theoretically dissimilar construct) of SWLS was measured using two scales (Dahiya and Rangnekar, 2018b;Thompson et al, 2005). One being positive and negative affect schedule (PANAS; Dahiya and Rangnekar, 2019c) with two dimensions (positive affect [PA] and negative affect [NA]), containing ten items in each. The participants responded to a seven-point scale ranging from "never" as 1 to "always" as 7.…”
Section: Instrumentsmentioning
confidence: 95%
“…Discriminant validity of the scale. Following the recommendation of Churchill and Iacobucci (2002), we examined the correlation coefficient between SWLS with two theoretical dissimilar scales, namely PANAS (Dahiya and Rangnekar, 2019c) and the HFS (Dahiya and Rangnekar, 2018b). The results of the coefficient of correlations showed that SWLS positively related with the positive affect (r 5 0.19, p < 0.01), negatively with negative affect (r 5 À0.14, p < 0.01) and positively related with forgiveness (r 5 0.18, p < 0.01).…”
Section: External Validity Analysismentioning
confidence: 99%
“…Need for validation of SWLS in Indian manufacturing sector Indeed, there has been a recognition among scholars of a need for organizations within the Indian manufacturing sector to lay emphasis on fostering positive psychological functioning among employees by studying variables such as life satisfaction (Singhal and Rastogi, 2018). These organizations are facing intense global competition, incessant technological changes and restructuring (Dahiya and Rangnekar, 2019c). On one hand, this offers career opportunities and growth to employees and, on the other, unceasing competitive pressure that leads to stress at work (Chhabra, 2018).…”
PurposeIn the modern world, life satisfaction has become a quintessential construct for large-scale organizations, and a valid measure to evaluate employee life satisfaction is required. Therefore, this study aims to evaluate the psychometric properties of the satisfaction with life scale (SWLS) in a sample of employees working in the Indian manufacturing sector.Design/methodology/approachSurvey method was used for data collection among a sample of 404 employees. Further, the psychometric properties of SWLS were evaluated with reference to reliability and validity assessment (face, content and construct validity).FindingsThe results were found to be significant for SWLS to assess the life satisfaction of employees working in manufacturing organizations in India.Originality/valueThis study attempts to validate SWLS among employees, which is a novel contribution in the field. Also, it suggests that effective application of SWLS can help in identifying and understanding the work-related factors associated with life satisfaction.
“…In order to measure affect, participants were asked to respond to Positive and Negative Affect Schedule (PANAS) developed by Watson et al (1988) and validated in Indian manufacturing organizations by Dahiya and Rangnekar (2019b). The measure has two dimensions, namely positive affect and NA.…”
Section: Negative Affectmentioning
confidence: 99%
“…Similarly, two sample items for positive affect were: "I feel interested at work" and "I feel alert at work". Researchers have reported that both the dimensions of PANAS are related to each other (Dahiya & Rangnekar, 2019b;Watsson et al, 1988) and positive affect has a high likelihood of affecting this relationship (forgiveness and NA), hence, statistically controlled for analysis. A higher score means a higher level of NA in the respondents.…”
The present study investigates the impact of forgiveness at work (self, others and situations) on negative affect (NA) using age as a moderator. Data, collected from 376 employees working in various Indian manufacturing organizations, were analysed with the help of regression analysis. The results show that forgiveness (self, others and situations) is significantly associated with lower NA and age moderates the relationship between forgiveness (self and others) and NA. The study offers a concrete insight into the complicated play of age in linking forgiveness dimensions and NA, an area that has largely been ignored in organizational research. The study shows that forgiveness significantly reduces the NA on employees and hence, organizations should make positive interventions in order to encourage forgiveness at work. Organizational psychologists and HR counsellors can similarly develop psychological tests and use theme-based interventions to foster intrapersonal and interpersonal development of forgiveness at work.
IntroductionThe factor structure of the Positive and Negative Affective Schedule (PANAS) is still a topic of debate. There are several reasons why using Exploratory Graph Analysis (EGA) for scale validation is advantageous and can help understand and resolve conflicting results in the factor analytic literature.
ObjectiveThe main objective of the present study was to advance the knowledge regarding the factor structure underlying the PA-NAS scores by utilizing the different functionalities of the EGA method. EGA was used to (1) estimate the dimensionality of the PANAS scores, (2) establish the stability of the dimensionality estimate and of the item assignments into the dimensions, and (3) assess the impact of potential redundancies across item pairs on the dimensionality and structure of the PANAS scores.
MethodThis assessment was carried out across two studies that included two large samples of participants.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
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