Karina Mostert

The psychometric properties of a translated version of the Survey Work-Home Interaction - Nijmegen (SWING) instrument

In this study we examined (1) the construct validity, construct equivalence, and reliability of two translations of the Survey Work-Home Interaction — Nijmegen (SWING); (2) the prevalence of work-home interaction; and (3) validity evidence based on relations with theoretically relevant external variables (i.e. job characteristics and indicators of well-being). The SWING questionnaire and a biographical questionnaire were translated into Afrikaans and Setswana and were administered, together with the original English version, among a cross-sectional sample of 685 members of the South African Police Service in North West Province. Structural equation modelling showed that a four-factor model, distinguishing between the direction (work-to-home vs. home-to-work) and the quality (positive vs. negative) of interaction, fitted the data best. The SWING was equivalent and reliable for the three language groups and relevant sub-groups. Participants reported more negative work-home interaction (WHI) than negative home-work interaction (HWI), and more positive HWI than positive WHI. Validity evidence was also provided based on the relations with external variables. In general, high levels of negative WHI were associated with job demands and a lack of job resources, while high levels of positive WHI were associated with lower demands and more job resources. Evidence was also provided for the relations between the SWING scales and four indicators of well-being (i.e. exhaustion, cynicism, professional efficacy and engagement). It is concluded that the SWING is a reliable and valid instrument to measure work-home interaction in South Africa.

Job characteristics, work–home interference and burnout: testing a structural model in the South African context

The aim of this study was to test a structural model that included job demands and job resources, negative work–home interference (WHI) and burnout (exhaustion, cognitive weariness and cynicism). A cross-sectional survey design was used. Random samples (n = 330) were taken of workers employed in the earthmoving industry in eight provinces of South Africa. Job characteristics (including job pressure, job control and job support) were measured by items that were adapted from the Job Content Questionnaire and a validated questionnaire on experience and evaluation of work. The Survey Work–Home Interaction – Nijmegen was used to measure negative WHI, while the Maslach Burnout Inventory-General Survey and cognitive weariness scale were administered to measure exhaustion, cognitive weariness and cynicism. Structural equation modelling with Amos showed that job demands (e.g. job pressure) and job resources (job control, supervisor support and colleague support) contributed to negative WHI. Negative WHI mediated the relationship between job demands and burnout and partially mediated between job resources and burnout.

Strengths use and deficit correction in organizations: development and validation of a questionnaire

Although the positive psychology tradition emphasizes the importance of a balanced approach regarding individual strengths and weaknesses, there is no valid instrument to measure these phenomena in organizations. The purpose of the present studies is to develop and validate an instrument that measures four dimensions, namely perceived organizational support (POS) for strengths use, POS for deficit correction, strengths use behaviour, and deficit correction behaviour. In study 1 and 2, the Strengths Use and Deficit COrrection (SUDCO) questionnaire was developed and tested for its factor structure, reliability, and convergent and criterion validity in two samples of South African employees (N = 338 and N = 361, respectively). In study 3, the convergent and criterion validity of the SUDCO were examined in a sample of Dutch engineers (N = 133). Results indicated that the intended dimensions of strengths use and deficit correction can be measured reliably with 24 items and showed convergent validity. Moreover, POS for strengths use and strengths use behaviour correlated positively with self- and manager-ratings of job performance, supporting the criterion validity of these scales. As expected, POS for deficit correction and deficit correction behaviour were unrelated to the performance ratings.

Burnout and Work Engagement for Different Age Groups: Examining Group-Level Differences and Predictors

This study examined age-related differences of burnout and engagement levels among employees in the South African financial sector, including influences of perceived job characteristics and personal sense of coherence. Data on burnout and work engagement, job characteristics and sense of coherence were collected from a convenience sample of 582 of junior managers (females = 55.50%, majority language was English, 54.1%). The results from this study reveal that young and middle-aged employees experience higher levels of exhaustion when compared to older employees, while older employees seemed to be more dedicated than their younger counterparts. Different job demands and resources seemed to predict burnout and work engagement of the three age groups. SOC was a significant predictor of burnout and work engagement across the three age groups. To conclude, the results of this study highlight the differences in the antecedents of employee well-being. These differences can therefore not be ignored in the workplace.

Organisational and individual strengths use as predictors of engagement and productivity

This study sought to determine whether Perceived Organisational Support for Strengths Use (POSSU) and Proactive Behaviour towards Strengths Use (PBSU) predict engagement and productivity in a sample of South African call centre operators. Participants were 218 call centre operators within the financial services sector (females=51%, males = 49%), representative of the South African population, and predominantly holding secondary educational qualifications. Information was gathered through a cross-sectional quantitative research design comprising self-report measures. The measures were administered on site within a call centre of one of the countrys largest financial service providers. Structural equation modelling methods were implemented to establish the model fit of the constructs in the study and to explain structural paths between the variables. Findings showed that POSSU and PBSU are significant predictors of work engagement. PBSU predicted productivity. In addition, engagement mediated the relationship between POSSU/PBSU and productivity. This supports the theoretical context of the job demands-resources (JD-R) model and provides grounds for further exploration of the strengths-based approach (on both organisational and individual levels) as a developmental approach to utilise within organisations to enhance engagement and productivity.

Predictors of student burnout and engagement among university students

This study investigated influences of core self-evaluation traits, career decision-making difficulties and social support on student burnout and engagement. A cross-sectional design was used with a non-probability quota sample. In the multiple regression analyses, self-efficacy, inconsistent information due to internal conflict and (lack of) parental support were significant predictors of exhaustion, cynicism, vigour and dedication. Self-esteem was also a significant predictor for the two engagement dimensions. In addition, lack of information about the self, lack of information about the occupations and inconsistent information due to external conflict predicted cynicism.

Strengths use and deficit improvement: The relationship with engagement and fit with study course amongst first-year students

This study sought to test a model of students’ proactive behaviour to use their strengths and improve their deficits and how this relates with their self-reported perceptions of their fit with a study course and engagement. Participants were 692 first-year students from a higher education institution in South Africa (females=60.3%; blacks=71.3%; mean age=19.71; SD=1.93). They completed measures of strengths use, deficit improvement, perceptions of fit with a study course and engagement. Structural equation modelling was utilised to examine the relationship between students’ strengths use and deficit improvement, perceptions of fit with a study course and student engagement. In addition, the bootstrapping method was used to identify possible mediating effects of fit with a study course. The results indicated that only deficit improvement showed a significant relationship with engagement. Perceptions of fit with a study course mediated the relationship between students’ strengths use and deficit improvement.

The psychometric properties of the Recovery Experiences Questionnaire of employees in a higher education institution

The objective of this study was to investigate the factorial validity and reliability of scores from the Recovery Experience Questionnaire (REQ) in a higher education institution. As part of the measure validation, the relationships of the four recovery dimensions (psychological detachment, relaxation, mastery and control) to other variables in the nomological network (work-home interference, home-work interference and ill health) were investigated. Data was collected from 366 participants (females = 65.3%; white = 80.35%). Confirmatory factor analysis was used to test competing factorial models. The results supported a four-factor structure for the REQ. Relationships with other variables in the nomological network were all theoretically consistent, as expected.

Examining significant predictors of students' intention to drop out

The objective of this study was to determine if core self-evaluation traits, burnout, disengagement, social support and career decision making difficulties are significant predictors of university students’ intention to drop out. A cross-sectional design and non-probability sample (N=782) was used. The participants were grouped as students with no intention to drop out (n=501) and students with the intention to drop out (n=280). These two groups were enclosed as the dependent variable in the logistic regression analysis. The variables included in the final model predicted between 13% and 18% of the variance in intention to drop out. In the final step of the logistic regression, significant predictors of the intention to drop out were lack of self-esteem, cynicism, lack of dedication and lack of information on ways of obtaining information (p < 0.05).