Evaluating a fatigue management training program for coach drivers

[Abstract]: A nonprescriptive fatigue management training program was developed that aimed at identifying specific factors contributing to coach driver fatigue and assisting coach drivers to develop more effective coping strategies to manage difficult or stressful work situations. The training program incorporated a strategy of presenting realistic, job related situations and multiple responses to drivers and asking them to indicate the effectiveness of each response in dealing with that situation. The advantage of using this methodology was that drivers were presented with stimulus material that was directly related to their work tasks, that is, had a high level of psychological fidelity. The evaluation of the training indicated that drivers who perceived the situational exercises as most realistic reported better training outcomes. Overall, the drivers reported positive reactions to the training, high levels of posttraining self efficacy, and strong level of transfer intentions

Predicting job satisfaction and depression at work: how important are work-related factors?

This study compared the degree to which work characteristics added to the prediction of two outcomes (job satisfaction and depression) in a sample of employed Australians after controlling for measures of personality and affectivity (both positive and negative). The main purpose was to examine the unique contribution of various work characteristics to the prediction of job satisfaction and depression. A total of 280 employed participants completed the online survey that assessed the four work characteristics (demands, control, supervisor support and co-worker support), personality (Extraversion and Neuroticism),both positive affect (PA) and negative affect (NA), job satisfaction and depressive symptoms. Several hierarchical regression analyses were conducted. The results of the analyses predicting job satisfaction showed that the four work characteristics explained a small but significant proportion of job satisfaction ( R2 = .04, p > .001) after controlling for PA and NA at step 1 (R2 = .60, p > .001) and personality variables at step 2 ( R2 = .00, ns). Control and co-worker support were significant unique predictors of job satisfaction. The results of the analyses predicting depression showed that the four work characteristics explained a nonsignificant proportion of depression ( R2 = .01, ns) after controlling for PA and NA at step 1 (R2 = .29, p > .001) and personality variables at step 2 ( R2 = .21, p > .001). These results are important in that levels of job satisfaction are mainly explained by affect (PA and NA) with a weak contribution from level of job control and co-worker support but no unique contribution from personality variables. When predicting the presence of depressive symptoms, the personality variables contributed additional variance after controlling for PA and NA but there were no unique contributions from the work characteristics. This study compared the degree to which work characteristics added to the prediction of two outcomes(job satisfaction and depression) in a sample of employed Australians after controlling for measures of personality and affectivity (both positive and negative). The main purpose was to examine the unique contribution of various work characteristics to the prediction of job satisfaction and depression. A total of 280 employed participants completed the online survey that assessed the four work characteristics (demands, control, supervisor support and co-worker support), personality (Extraversion and Neuroticism), both positive affect (PA) and negative affect (NA), job satisfaction and depressive symptoms. Several hierarchical regression analyses were conducted. The results of the analyses predicting job satisfaction showed that the four work characteristics explained a small but significant proportion of job satisfaction ( R2 = .04, p > .001) after controlling for PA and NA at step 1 (R2 = .60, p > .001) and personality variables at step 2 ( R2 = .00, ns). Control and co-worker support were significant unique predictors of job satisfaction. The results of the analyses predicting depression showed that the four work characteristics explained a nonsignificant proportion of depression ( R2 = .01, ns) after controlling for PA and NA at step 1 (R2 = .29, p > .001) and personality variables at step 2 ( R2 = .21, p > .001). These results are important in that levels of job satisfaction are mainly explained by affect (PA and NA) with a weak contribution from level of job control and co-worker support but no unique contribution from personality variables. When predicting the presence of depressive symptoms, the personality variables contributed additional variance after controlling for PA and NA but there were no unique contributions from the work characteristics. The focus of work-related interventions designed to improve satisfaction or alleviate depression should give priority to the determinants of PA and NA which have been found to include several workplace characteristics (work demands, control, supervisor support and co-worker support), personality traits, and personal resources such as mastery and efficacy beliefs, a sense of autonomy, positive relatedness with others, and self acceptanc

The importance of psychological well-being in organisational settings: moving beyond the pleasure principle

In contrast to the emphasis on affective states as components of Subjective Well-Being (SWB), the Psychological Well-Being (PWB) approach considers the role of personal resources, such as mastery and efficacy beliefs, a sense of autonomy, positive relatedness with others, and self acceptance. This study of 679 high-school teachers was based on the Organisational Health Research Framework and compared the contribution of PWB, personality and organisational climate to the prediction of SWB and organisational well-being. PWB was identified as a significant predictor of SWB even after controlling for demographic characteristics, organisational climate and personality variables with 46% of the variance in PA and 47% of the variance in NA explained. In addition, PWB contributed uniquely to the prediction of school morale and school distress with the overall set of predictors accounting for 69% of the variance in school morale and 66% of the variance in school distress. Individual interventions which promote PWB components would appear to be a most important avenue by which to improve employee SWB, while organisational interventions that focus on improving the organisational climate should have greater impact on organisational well-bein

Understanding the differential benefits of training for the unemployed

[Abstract]: This study examined the connection between background variables (such as length of unemployment and number of previous training courses), contextual variables (perceptions of training climate), dispositional variables (positive affect and negative affect), and psychological outcomes for unemployed trainees who attended either a five week occupational skills training program (control group) or the same five week program with an additional two day intervention before the start of the program (treatment group). The trainees in both the treatment and control conditions were found to reduce their levels of psychological distress over the course of a five-week training program. Trainees in the treatment condition who started with the lowest levels of general self-efficacy and the highest levels of psychological distress showed the greatest improvements at time 2 (T2). The measures of length of unemployment, number of previous training courses, and the perceptions of the training climate (with one exception) did not account for any unique variance in either of the well-being measures at time 3 (T3). Positive and negative affect (PA and NA respectively) accounted for 30% of the variance in initial levels of general self-efficacy and 43% of the variance in initial levels of psychological distress. However, PA and NA measured at T1 did not account for any unique variance in the T3 levels of general self-efficacy and psychological distress, after the initial levels of each of the variables were controlled. It was concluded that components of dispositional affect are the main influence on how individuals perceive stimuli in the environment and subsequently regulate their emotional response

Social problem-solving skills and mental health: a comparison of undergraduate cohorts

Problem Solving Skills is clearly indicated as a graduate attribute at the University of Southern Queensland (USQ) and many other Australian Universities. This study was cross-sectional in design and aimed to compare perceived social problem solving skills and mental health variables between undergraduate year levels. Previous research has shown that first year university students are more likely to indicate signs of depression than students‘ in latter years. Research has also found that groups with higher education have indicated more positive problem solving appraisal. Finally, there is considerable research that has linked poorer problem solving appraisal with higher levels of depression and anxiety. An online test battery was administered to 464 undergraduate students from the USQ. The Problem Solving Inventory, Form B (PSI-B; Heppner, 1988) measured perceived problem-solving ability, and is comprised of three subscales; Problem Solving Confidence, Approach Avoidance and Personal Control.The other measure was the shortened version of the Depression Anxiety Stress Scale (DASS-21;Lovibond & Lovibond, 1995) and measured mental health variables (Depression, Anxiety and Stress). Participants were divided into year level (i.e. first, second or third year), and a one way Analysis of Variance (ANOVA) indicated no significant difference between the groups on any of the problem solving or mental health variables. Given that the USQ has a large mature age student population, students were re-analysed with one-way ANOVA according to age (under 21, 21-29, 30-39 and 40 and over years). Significant differences were found where the two older groups had a more positive problem appraisal than the two younger groups. The two older groups also indicated less depression and anxiety symptoms than the two younger groups. It is suggested that problem solving therapy programs specifically targeting younger students may be worth considerin

Personal effectiveness training for unemployed people: where to now?

Unemployment remains a major social problem in Australia. Successive governments have attempted to address the problem, in part, by funding occupational skills based training programs for the unemployed. This paper reviews the general area of occupational skills/personal effectiveness training for unemployed people, and reports on outcomes for individuals attending 'typical' courses in Australia. Also reported, are outcomes for unemployed people who attended specially devised training, based on the cognitive behavioural (e.g., Beck, 1976) and learned optimism (Seligman, 1990) intervention approaches, that was aimed at improving well-being, confidence and coping abilities. Variables assessed include individual well-being (e.g., psychological distress), confidence (e.g., self-efficacy), attitude-to-work (e.g., work-commitment); training climate; and labour market outcomes such as return-to-work. More positive outcomes were identified for unemployed people attending the specially devised programs. The authors argue that training targeted at unemployed people must be based on sound theoretical principles to produce measurable long-term benefits. Future applications of personal development programs are discussed in relation to occupational skills based training and as stand-alone programs

Predicting employees' commitment to and support for organisational change

This study aimed to identify factors that predict employees' commitment to and support for organisational change. The three components of Herscovitch and Meyer's (2002) commitment to organisational change model were hypothesised to mediate the relationship between organisational climate and behavioural support for organisational change. Data were collected from a Queensland government department (N = 342). Analysis of correlations revealed that organisational climate, commitment to change, and behavioural support for change variables were all significantly related. Structural equation modelling demonstrated that affective, normative, and continuance commitment to change were all predictors of behavioural support for organisational change. Positive work climate also contributed directly to the prediction of behavioural support for change over and above the indirect influence through commitment to organisational change, indicating a partial mediation effect. These findings support Herscovitch and Meyer's (2002) three-component model of commitment to organisational change and extend their nomological network by showing the relevance of two types of organisational climate to the core components of the model. Affective commitment to organisational change is a positive influence on employees' behavioural support for change and also reflects healthy aspects of the organisational climate. However, continuance commitment to organisational change is detrimental influence on employees' behavioural support for change and is linked with unhealthy dimensions of the organisational climate

Motives for Facebook use in an Australian sample

A survey of 209 Australians (17-69 years) was conducted to examine the motives for Facebook use, and how these factors related to individuals' belonging, self-esteem, control, and meaning. An initial factor analysis identified four distinct factors underlying motives for Facebook use: meeting people, relationship maintenance, monitoring relationships, and seeking information. These four factors extend previous research and help clarify the key reasons for Facebook use. Further analyses found that participants' age was negatively correlated with each of the motives for Facebook use factors. Multiple regressions were performed with each of the four motives regressed on age, gender, and the individuals' belonging, self-esteem, control, and meaning. All four of these variables contributed significantly to the prediction of factor 1 (meeting people). Only belonging was a significant predictor of factor 2 (relationship maintenance) and factor 3 (monitoring relationships). Both self-esteem and belonging were significant predictors of factor 4 (seeking information). This study included general community members and not just undergraduate students and therefore has wider applicability than previous research. Facebook use seems to be closely related to individuals' belonging across a wide age range

Relations between dimensions of empowering leadership and multidimensional work motivation

Recent developments work motivation facilitate a more thorough understanding of the potential impact of constructs such as empowering leadership. Amundsen and Martinsen (2014) demonstrated that empowering leadership has two dimensions (autonomy support and development support) and that these dimensions relate positively to subordinates’ psychological empowerment and creativity. This study assessed how two dimensions of empowering leadership (autonomy support and development support) predicted six types of work motivation as part of a larger study into predictors of work performance. It was predicted that the two dimensions of empowering leadership would predict these specific types of motivation in somewhat different patterns which would not be obvious if composite forms of motivation were considered. An online survey was used to collect data from 192 employed individuals. Of the respondents, 132 (69%) were female, 173 (90%) lived in Australia, and 150 (78%) worked at least 30 hours per week. Feedback was not provided to participants. The survey included the 18-item Empowering Leadership Scale (ELS; Amundsen & Martinsen, 2014), the 19-item Multidimensional Work Motivation Scale (MWMS; Gagne et al., in press), as well as a number of other measures that contributed to a larger study into work performance. The correlations between the two dimensions of empowering leadership and the six types of work motivation were calculated. Autonomy Support and Development Support were highly correlated (r = .76, p<.001). These two dimensions of empowering leadership displayed a similar pattern of correlations with each of the six types of work motivation although the correlations for Autonomy Support were slightly stronger in nearly all cases. Given this similar pattern and the large degree of overlap between the two dimensions, the analysis proceeded by constructing a structural equation model in which the two dimensions of empowering leadership were specified as indicators of an underlying construct which then predicted each of the six types of work motivation. This model was respecified to accommodate the significant correlations between many of the specific types of motivation and the final model was a good fit to the data with χ2 = 5.818 (df = 8), p = .67, AGFI = .97, TLI = 1.01 and RMSEA = .00 (90%CI .00 to .07 with pclose = .88). Empowering Leadership was a significant negative predictor of two types of work motivation: Amotivation (β = -.39, p < .001) and Extrinsic Regulation (social) (β = -.31, p < .001). However, Empowering Leadership was not a significant predictor of either Extrinsic Regulation (material) (β = .06, NS) or Introjected Regulation (β = -.01, NS). Empowering Leadership was a significant positive predictor of the final two types of work motivation: Identified Regulation (β = .38, p < .001) and Intrinsic Motivation (β = .63, p < .001). The differences in the standardised coefficients across the six types of work motivation provide a powerful argument for a more nuanced understanding of how a construct such as empowering leadership may influence employees’ work motivation. Previous research that has focused on the second order factors of controlled and autonomous motivation may have obscured important differences in the patterns of relationships

Predicting occupational strain and job satisfaction: the role of stress, coping, personality, and affectivity variables

Four studies employed path analysis to examine how measures of occupational stressors, coping resources, and negative affectivity (NA) and positive affectivity (PA) interact to predict occupational strain. The Occupational Stress Inventory (Osipow & Spokane, 1987) was used to measure stress, strain, and coping. The Positive and Negative Affectivity Schedule (Watson, Clark, & Tellegen, 1988) was used for the affectivity variables. The hypothesised model showed NA and PA as background dispositional variables that influenced relations among stress, strain, and coping while still allowing stress and coping to have a direct influence on strain. Goodness of fit indices were acceptable with the model predicting 15 per cent of the variance in stress, 24 per cent of coping, and 70 per cent of strain. Study 2 replicated these findings. Study 3 added a positive outcome variable, job satisfaction (JSI: Brayfield & Rothe, 1951) to the model. The expanded model again fit the data well. A fourth study added a global measure of personality (NEO-FFI: Costa & McCrae, 1991) to the model tested in Study 3. Results indicated that personality measures did not add anything to the prediction of job satisfaction and strain in a model that already included measures of stressors, coping resources, NA and PA. The series of four studies yielded a reliable structural model that highlights the influence of organizational and dispositional variables on occupational strain and job satisfaction