775 resultados para sparse factor analysis


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The contribution of risky behaviour to the increased crash and fatality rates of young novice drivers is recognised in the road safety literature around the world. Exploring such risky driver behaviour has led to the development of tools like the Driver Behaviour Questionnaire (DBQ) to examine driving violations, errors, and lapses [1]. Whilst the DBQ has been utilised in young novice driver research, some items within this tool seem specifically designed for the older, more experienced driver, whilst others appear to asses both behaviour and related motives. The current study was prompted by the need for a risky behaviour measurement tool that can be utilised with young drivers with a provisional driving licence. Sixty-three items exploring young driver risky behaviour developed from the road safety literature were incorporated into an online survey. These items assessed driver, passenger, journey, car and crash-related issues. A sample of 476 drivers aged 17-25 years (M = 19, SD = 1.59 years) with a provisional driving licence and matched for age, gender, and education were drawn from a state-wide sample of 761 young drivers who completed the survey. Factor analysis based upon a principal components extraction of factors was followed by an oblique rotation to investigate the underlying dimensions to young novice driver risky behaviour. A five factor solution comprising 44 items was identified, accounting for 55% of the variance in young driver risky behaviour. Factor 1 accounted for 32.5% of the variance and appeared to measure driving violations that were transient in nature - risky behaviours that followed risky decisions that occurred during the journey (e.g., speeding). Factor 2 accounted for 10.0% of variance and appeared to measure driving violations that were fixed in nature; the risky decisions being undertaken before the journey (e.g., drink driving). Factor 3 accounted for 5.4% of variance and appeared to measure misjudgment (e.g., misjudged speed of oncoming vehicle). Factor 4 accounted for 4.3% of variance and appeared to measure risky driving exposure (e.g., driving at night with friends as passengers). Factor 5 accounted for 2.8% of variance and appeared to measure driver emotions or mood (e.g., anger). Given that the aim of the study was to create a research tool, the factors informed the development of five subscales and one composite scale. The composite scale had a very high internal consistency measure (Cronbach’s alpha) of .947. Self-reported data relating to police-detected driving offences, their crash involvement, and their intentions to break road rules within the next year were also collected. While the composite scale was only weakly correlated with self-reported crashes (r = .16, p < .001), it was moderately correlated with offences (r = .26, p < .001), and highly correlated with their intentions to break the road rules (r = .57, p < .001). Further application of the developed scale is needed to confirm the factor structure within other samples of young drivers both in Australia and in other countries. In addition, future research could explore the applicability of the scale for investigating the behaviour of other types of drivers.

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Police work tasks are diverse and require the ability to take command, demonstrate leadership, make serious decisions and be self directed (Beck, 1999; Brunetto & Farr-Wharton, 2002; Howard, Donofrio & Boles, 2002). This work is usually performed in pairs or sometimes by an officer working alone. Operational police work is seldom performed under the watchful eyes of a supervisor and a great amount of reliance is placed on the high levels of motivation and professionalism of individual officers. Research has shown that highly motivated workers produce better outcomes (Whisenand & Rush, 1998; Herzberg, 2003). It is therefore important that Queensland police officers are highly motivated to provide a quality service to the Queensland community. This research aims to identify factors which motivate Queensland police to perform quality work. Researchers acknowledge that there is a lack of research and knowledge in regard to the factors which motivate police (Beck, 1999; Bragg, 1998; Howard, Donofrio & Boles, 2002; McHugh & Verner, 1998). The motivational factors were identified in regard to the demographic variables of; age, sex, rank, tenure and education. The model for this research is Herzberg’s two-factor theory of workplace motivation (1959). Herzberg found that there are two broad types of workplace motivational factors; those driven by a need to prevent loss or harm and those driven by a need to gain personal satisfaction or achievement. His study identified 16 basic sub-factors that operate in the workplace. The research utilised a questionnaire instrument based on the sub-factors identified by Herzberg (1959). The questionnaire format consists of an initial section which sought demographic information about the participant and is followed by 51 Likert scale questions. The instrument is an expanded version of an instrument previously used in doctoral studies to identify sources of police motivation (Holden, 1980; Chiou, 2004). The questionnaire was forwarded to approximately 960 police in the Brisbane, Metropolitan North Region. The data were analysed using Factor Analysis, MANOVAs, ANOVAs and multiple regression analysis to identify the key sources of police motivation and to determine the relationships between demographic variables such as: age, rank, educational level, tenure, generation cohort and motivational factors. A total of 484 officers responded to the questionnaire from the sample population of 960. Factor analysis revealed five broad Prime Motivational Factors that motivate police in their work. The Prime Motivational Factors are: Feeling Valued, Achievement, Workplace Relationships, the Work Itself and Pay and Conditions. The factor Feeling Valued highlighted the importance of positive supportive leaders in motivating officers. Many officers commented that supervisors who only provided negative feedback diminished their sense of feeling valued and were a key source of de-motivation. Officers also frequently commented that they were motivated by operational police work itself whilst demonstrating a strong sense of identity with their team and colleagues. The study showed a general need for acceptance by peers and an idealistic motivation to assist members of the community in need and protect victims of crime. Generational cohorts were not found to exert a significant influence on police motivation. The demographic variable with the single greatest influence on police motivation was tenure. Motivation levels were found to drop dramatically during the first two years of an officer’s service and generally not improve significantly until near retirement age. The findings of this research provide the foundation of a number of recommendations in regard to police retirement, training and work allocation that are aimed to improve police motivation levels. The five Prime Motivational Factor model developed in this study is recommended for use as a planning tool by police leaders to improve motivational and job-satisfaction components of police Service policies. The findings of this study also provide a better understanding of the current sources of police motivation. They are expected to have valuable application for Queensland police human resource management when considering policies and procedures in the areas of motivation, stress reduction and attracting suitable staff to specific areas of responsibility.

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Over the past decade, there has been growth in the delivery of vocational rehabilitation services globally, as countries seek to control disability-related expenditure, yet there has been minimal research outside the United States on competencies required to work in this area. This study reports on research conducted in Australia to determine current job function and knowledge areas in terms of their importance and frequency of use in the provision of vocational rehabilitation. A survey comprising items from the Rehabilitation Skills Inventory-Amended and International Survey of Disability Management was completed by 149 rehabilitation counselors and items submitted to factor analysis. T-tests and analyses of variance were used to determine differences between scores of importance and frequency and differences in scores based on work setting and professional training. Six factors were identified as important and frequently used: (i) vocational counseling, (ii) professional practice, (iii) personal counseling, (iv) rehabilitation case management, (v) workplace disability case management, and (vi) workplace intervention and program management. Vocational counseling, professional practice and personal counseling were significantly more important and performed more frequently by respondents in vocational rehabilitation settings than those in compensation settings. These same three factors were rated significantly higher in importance and frequency by those with rehabilitation counselor training when compared with those with other training. In conclusion, although ‘traditional’ knowledge and skill areas such as vocational counseling, professional practice, and personal counseling were identified as central to vocational rehabilitation practice in Australian rehabilitation agencies, mean ratings suggest a growing emphasis on knowledge and skills associated with disability management practice.

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Advances in symptom management strategies through a better understanding of cancer symptom clusters depend on the identification of symptom clusters that are valid and reliable. The purpose of this exploratory research was to investigate alternative analytical approaches to identify symptom clusters for patients with cancer, using readily accessible statistical methods, and to justify which methods of identification may be appropriate for this context. Three studies were undertaken: (1) a systematic review of the literature, to identify analytical methods commonly used for symptom cluster identification for cancer patients; (2) a secondary data analysis to identify symptom clusters and compare alternative methods, as a guide to best practice approaches in cross-sectional studies; and (3) a secondary data analysis to investigate the stability of symptom clusters over time. The systematic literature review identified, in 10 years prior to March 2007, 13 cross-sectional studies implementing multivariate methods to identify cancer related symptom clusters. The methods commonly used to group symptoms were exploratory factor analysis, hierarchical cluster analysis and principal components analysis. Common factor analysis methods were recommended as the best practice cross-sectional methods for cancer symptom cluster identification. A comparison of alternative common factor analysis methods was conducted, in a secondary analysis of a sample of 219 ambulatory cancer patients with mixed diagnoses, assessed within one month of commencing chemotherapy treatment. Principal axis factoring, unweighted least squares and image factor analysis identified five consistent symptom clusters, based on patient self-reported distress ratings of 42 physical symptoms. Extraction of an additional cluster was necessary when using alpha factor analysis to determine clinically relevant symptom clusters. The recommended approaches for symptom cluster identification using nonmultivariate normal data were: principal axis factoring or unweighted least squares for factor extraction, followed by oblique rotation; and use of the scree plot and Minimum Average Partial procedure to determine the number of factors. In contrast to other studies which typically interpret pattern coefficients alone, in these studies symptom clusters were determined on the basis of structure coefficients. This approach was adopted for the stability of the results as structure coefficients are correlations between factors and symptoms unaffected by the correlations between factors. Symptoms could be associated with multiple clusters as a foundation for investigating potential interventions. The stability of these five symptom clusters was investigated in separate common factor analyses, 6 and 12 months after chemotherapy commenced. Five qualitatively consistent symptom clusters were identified over time (Musculoskeletal-discomforts/lethargy, Oral-discomforts, Gastrointestinaldiscomforts, Vasomotor-symptoms, Gastrointestinal-toxicities), but at 12 months two additional clusters were determined (Lethargy and Gastrointestinal/digestive symptoms). Future studies should include physical, psychological, and cognitive symptoms. Further investigation of the identified symptom clusters is required for validation, to examine causality, and potentially to suggest interventions for symptom management. Future studies should use longitudinal analyses to investigate change in symptom clusters, the influence of patient related factors, and the impact on outcomes (e.g., daily functioning) over time.

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BACKGROUND: Support and education for parents faced with managing a child with atopic dermatitis is crucial to the success of current treatments. Interventions aiming to improve parent management of this condition are promising. Unfortunately, evaluation is hampered by lack of precise research tools to measure change. OBJECTIVES: To develop a suite of valid and reliable research instruments to appraise parents' self-efficacy for performing atopic dermatitis management tasks; outcome expectations of performing management tasks; and self-reported task performance in a community sample of parents of children with atopic dermatitis. METHODS: The Parents' Eczema Management Scale (PEMS) and the Parents' Outcome Expectations of Eczema Management Scale (POEEMS) were developed from an existing self-efficacy scale, the Parental Self-Efficacy with Eczema Care Index (PASECI). Each scale was presented in a single self-administered questionnaire, to measure self-efficacy, outcome expectations, and self-reported task performance related to managing child atopic dermatitis. Each was tested with a community sample of parents of children with atopic dermatitis, and psychometric evaluation of the scales' reliability and validity was conducted. SETTING AND PARTICIPANTS: A community-based convenience sample of 120 parents of children with atopic dermatitis completed the self-administered questionnaire. Participants were recruited through schools across Australia. RESULTS: Satisfactory internal consistency and test-retest reliability was demonstrated for all three scales. Construct validity was satisfactory, with positive relationships between self-efficacy for managing atopic dermatitis and general perceived self-efficacy; self-efficacy for managing atopic dermatitis and self-reported task performance; and self-efficacy for managing atopic dermatitis and outcome expectations. Factor analyses revealed two-factor structures for PEMS and PASECI alike, with both scales containing factors related to performing routine management tasks, and managing the child's symptoms and behaviour. Factor analysis was also applied to POEEMS resulting in a three-factor structure. Factors relating to independent management of atopic dermatitis by the parent, involving healthcare professionals in management, and involving the child in the management of atopic dermatitis were found. Parents' self-efficacy and outcome expectations had a significant influence on self-reported task performance. CONCLUSIONS: Findings suggest that PEMS and POEEMS are valid and reliable instruments worthy of further psychometric evaluation. Likewise, validity and reliability of PASECI was confirmed.

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Accurate owner budget estimates are critical to the initial decision-to-build process for highway construction projects. However, transportation projects have historically experienced significant construction cost overruns from the time the decision to build has been taken by the owner. This paper addresses the problem of why highway projects overrun their predicted costs. It identifies the owner risk variables that contribute to significant cost overrun and then uses factor analysis, expert elicitation, and the nominal group technique to establish groups of importance ranked owner risks. Stepwise multivariate regression analysis is also used to investigate any correlation of the percentage of cost overrun with risks, together with attributes such as highway project type, indexed cost, geographics location, and project delivery method. The research results indicate a correlation between the reciprocal of project budgets size and percentage cost overrun. This can be useful for owners in determining more realistic decision-to-build highway budget estimates by taking into account the economies of scale associated with larger projects.

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Purpose – The purpose of this paper is to examine the role of three strategies - organisational, business and information system – in post implementation of technological innovations. The findings reported in the paper are that improvements in operational performance can only be achieved by aligning technological innovation effectiveness with operational effectiveness. Design/methodology/approach – A combination of qualitative and quantitative methods was used to apply a two-stage methodological approach. Unstructured and semi structured interviews, based on the findings of the literature, were used to identify key factors used in the survey instrument design. Confirmatory factor analysis (CFA) was used to examine structural relationships between the set of observed variables and the set of continuous latent variables. Findings – Initial findings suggest that organisations looking for improvements in operational performance through adoption of technological innovations need to align with operational strategies of the firm. Impact of operational effectiveness and technological innovation effectiveness are related directly and significantly to improved operational performance. Perception of increase of operational effectiveness is positively and significantly correlated with improved operational performance. The findings suggest that technological innovation effectiveness is also positively correlated with improved operational performance. However, the study found that there is no direct influence of strategiesorganisational, business and information systems (IS) - on improvement of operational performance. Improved operational performance is the result of interactions between the implementation of strategies and related outcomes of both technological innovation and operational effectiveness. Practical implications – Some organisations are using technological innovations such as enterprise information systems to innovate through improvements in operational performance. However, they often focus strategically only on effectiveness of technological innovation or on operational effectiveness. Such a focus will be detrimental in the long-term of the enterprise. This research demonstrated that it is not possible to achieve maximum returns through technological innovations as dimensions of operational effectiveness need to be aligned with technological innovations to improve their operational performance. Originality/value – No single technological innovation implementation can deliver a sustained competitive advantage; rather, an advantage is obtained through the capacity of an organisation to exploit technological innovations’ functionality on a continuous basis. To achieve sustainable results, technology strategy must be aligned with organisational and operational strategies. This research proposes the key performance objectives and dimensions that organisations should focus to achieve a strategic alignment. Research limitations/implications – The principal limitation of this study is that the findings are based on investigation of small sample size. There is a need to explore the appropriateness of influence of scale prior to generalizing the results of this study.

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This research uses confirmatory factor analysis and structural equation modelling to examine how organizational size - made up of four dimensions - control, resources, trust and complexity - impacts on utilization of industry-led supply chain innovation capacity in a traditional agribusiness industry, the Australian beef industry. It confirms small business rather than larger business accords greater importance to exploiting supply chain dynamic capabilities, particularly in relation to utilizing industry –led supply chain innovation capacity. For small business in Australian beef supply chains, being agile and able to adapt and align their business practices with supply chain partners is integral to ensuring these businesses remain relevant and competitive in this market. In theoretical terms this is supported by authors in the dynamic capabilities literature as they argue these types of capabilities enable organizations to innovate faster (or better), often leading to the creation of newer sources of competitive advantage.

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OBJECTIVE To examine the psychometric properties of a Chinese version of the Problem Areas In Diabetes (PAID-C) scale. RESEARCH DESIGN AND METHODS The reliability and validity of the PAID-C were evaluated in a convenience sample of 205 outpatients with type 2 diabetes. Confirmatory factor analysis, Bland-Altman analysis, and Spearman's correlations facilitated the psychometric evaluation. RESULTS Confirmatory factor analysis confirmed a one-factor structure of the PAID-C (χ2/df ratio = 1.894, goodness-of-fit index = 0.901, comparative fit index = 0.905, root mean square error of approximation = 0.066). The PAID-C was associated with A1C (rs = 0.15; P < 0.05) and diabetes self-care behaviors in general diet (rs = −0.17; P < 0.05) and exercise (rs = −0.17; P < 0.05). The 4-week test-retest reliability demonstrated satisfactory stability (rs = 0.83; P < 0.01). CONCLUSIONS The PAID-C is a reliable and valid measure to determine diabetes-related emotional distress in Chinese people with type 2 diabetes.

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This paper extends the work of Thompson, Beauvais and Lyness (1999) to develop a more comprehensive measure of work-life balance culture. Thompson et al. developed a survey based on three sub-dimensions which examine work-family culture. We have extended this to incorporate extra dimensions, and to broaden the measure to encompass life aspects beyond the family. Two studies were conducted in order to test and refine the measure. Over 700 participants in the first study completed the survey, and the Confirmatory Factor Analysis results show that the extended measure is robust. Further, a second study with a sample of 629 participants confirmed the general measure, with slight adaptations. The results are discussed in relation to the use of the measure for work-life balance research.

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Despite its widespread use, there has been limited examination of the underlying factor structure of the Psychological Sense of School Membership (PSSM) scale. The current study examined the psychometric properties of the PSSM to refine its utility for researchers and practitioners using a sample of 504 Australian high school students. Results from exploratory and confirmatory factor analyses indicated that the PSSM is a multidimensional instrument. Factor analysis procedures identified three factors representing related aspects of students’ perceptions of their school membership: caring relationships, acceptance, and rejection

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Bronfenbrenner.s Bioecological Model, expressed as the developmental equation, D f PPCT, is the theoretical framework for two studies that bring together diverse strands of psychology to study the work-life interface of working adults. Occupational and organizational psychology is focused on the demands and resources of work and family, without emphasising the individual in detail. Health and personality psychology examine the individual but without emphasis on the individual.s work and family roles. The current research used Bronfenbrenner.s theoretical framework to combine individual differences, work and family to understand how these factors influence the working adult.s psychological functioning. Competent development has been defined as high well-being (measured as life satisfaction and psychological well-being) and high work engagement (as work vigour, work dedication and absorption in work) and as the absence of mental illness (as depression, anxiety and stress) and the absence of burnout (as emotional exhaustion, cynicism and professional efficacy). Study 1 and 2 were linked, with Study 1 as a cross-sectional survey and Study 2, a prospective panel study that followed on from the data used in Study1. Participants were recruited from a university and from a large public hospital to take part in a 3-wave, online study where they completed identical surveys at 3-4 month intervals (N = 470 at Time 1 and N = 198 at Time 3). In Study 1, hierarchical multiple regressions were used to assess the effects of individual differences (Block 1, e.g. dispositional optimism, coping self-efficacy, perceived control of time, humour), work and family variables (Block 2, e.g. affective commitment, skill discretion, work hours, children, marital status, family demands) and the work-life interface (Block 3, e.g. direction and quality of spillover between roles, work-life balance) on the outcomes. There were a mosaic of predictors of the outcomes with a group of seven that were the most frequent significant predictors and which represented the individual (dispositional optimism and coping self-efficacy), the workplace (skill discretion, affective commitment and job autonomy) and the work-life interface (negative work-to-family spillover and negative family-to-work spillover). Interestingly, gender and working hours were not important predictors. The effects of job social support, generally and for work-life issues, perceived control of time and egalitarian gender roles on the outcomes were mediated by negative work-to-family spillover, particularly for emotional exhaustion. Further, the effect of negative spillover on depression, anxiety and work engagement was moderated by the individual.s personal and workplace resources. Study 2 modelled the longitudinal relationships between the group of the seven most frequent predictors and the outcomes. Using a set of non-nested models, the relative influences of concurrent functioning, stability and change over time were assessed. The modelling began with models at Time 1, which formed the basis for confirmatory factor analysis (CFA) to establish the underlying relationships between the variables and calculate the composite variables for the longitudinal models. The CFAs were well fitting with few modifications to ensure good fit. However, using burnout and work engagement together required additional analyses to resolve poor fit, with one factor (representing a continuum from burnout to work engagement) being the only acceptable solution. Five different longitudinal models were investigated as the Well-Being, Mental Distress, Well-Being-Mental Health, Work Engagement and Integrated models using differing combinations of the outcomes. The best fitting model for each was a reciprocal model that was trimmed of trivial paths. The strongest paths were the synchronous correlations and the paths within variables over time. The reciprocal paths were more variable with weak to mild effects. There was evidence of gain and loss spirals between the variables over time, with a slight net gain in resources that may provide the mechanism for the accumulation of psychological advantage over a lifetime. The longitudinal models also showed that there are leverage points at which personal, psychological and managerial interventions can be targeted to bolster the individual and provide supportive workplace conditions that also minimise negative spillover. Bronfenbrenner.s developmental equation has been a useful framework for the current research, showing the importance of the person as central to the individual.s experience of the work-life interface. By taking control of their own life, the individual can craft a life path that is most suited to their own needs. Competent developmental outcomes were most likely where the person was optimistic and had high self-efficacy, worked in a job that they were attached to and which allowed them to use their talents and without too much negative spillover between their work and family domains. In this way, individuals had greater well-being, better mental health and greater work engagement at any one time and across time.

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Since the 1970s the internationalisation process of firms has attracted wide research interest. One of the dominant explanations of firm internationalisation resulting from this research activity is the Uppsala stages model. In this paper, a pre-internationalisation phase is incorporated into the traditional Uppsala model to address the question: What are the antecedents of this model? Four concepts are proposed as the key components that define the experiential learning process underlying a firm’s pre-export phase: export stimuli, attitudinal/psychological commitment, resources and lateral rigidity. Through a survey of 290 Australian exporting and non-exporting small-medium sized firms, data relating to the four pre-internationalisation concepts is collected and an Export Readiness Index (ERI) is constructed through factor analysis. Using logistic regression, the ERI is tested as a tool for analysing export readiness among Australian SMEs.

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Expenditure on R&D in the China construction industry has been relatively low in comparison with many developed countries for a number of years – a situation considered to be a major barrier to the industry’s competitiveness in general and unsatisfactory industry development of the 31 regions involved. A major problem with this is the lack of a sufficiently sophisticated method of objectively evaluating R&D activity in what are quite complex circumstances considering the size and regional differences that exist in this part of the world. A regional construction R&D evaluation system (RCRES) is presented aimed at rectifying the situation. This is based on 12 indicators drawn from the Chinese Government’s R&D Inventory of Resources in consultation with a small group of experts in the field, and further factor analysed into three groups. From this, the required evaluation is obtained by a simple formula. Examination of the results provides a ranking list of the R&D performance of each of the 31 regions, indicating a general disproportion between coastal and inland regions and highlighting regions receiving special emphasis or currently lacking in development. The understanding on this is vital for the future of China’s construction industry.