Active ageing : developing a quantitative multi-dimensional measure

With estimates that two billion of the world’s population will be 65 years or older by 2050, ensuring that older people ‘age well’ is an international priority. To date, however, there is significant disagreement and debate about how to define and measure ‘ageing well’, with no consensus on either terminology or measurement. Thus, this chapter describes the research rationale, methodology and findings of the Australian Active Ageing Study (Triple A Study), which surveyed 2620 older Australians to identify significant contributions to quality of life for older people: work, learning, social participation, spirituality, emotional wellbeing, health, and life events. Exploratory factor analyses identified eight distinct elements (grouped into four key concepts) which appear to define ‘active ageing’ and explained 55% of the variance: social and life participation (25%), emotional health (22%), physical health and functioning (4%) and security (4%). These findings highlight the importance of understanding and supporting the social and emotional dimensions of ageing, as issues of social relationships, life engagement and emotional health dominated the factor structure. Our intension is that this paper will prompt informed debate and discussion on defining and measuring active ageing, facilitating exploration and understanding of the complexity of issues that intertwine, converge and enhance the ageing experience.

Comparison of three-dimensional profiles over time

In this paper, we describe an analysis for data collected on a three-dimensional spatial lattice with treatments applied at the horizontal lattice points. Spatial correlation is accounted for using a conditional autoregressive model. Observations are defined as neighbours only if they are at the same depth. This allows the corresponding variance components to vary by depth. We use the Markov chain Monte Carlo method with block updating, together with Krylov subspace methods, for efficient estimation of the model. The method is applicable to both regular and irregular horizontal lattices and hence to data collected at any set of horizontal sites for a set of depths or heights, for example, water column or soil profile data. The model for the three-dimensional data is applied to agricultural trial data for five separate days taken roughly six months apart in order to determine possible relationships over time. The purpose of the trial is to determine a form of cropping that leads to less moist soils in the root zone and beyond.We estimate moisture for each date, depth and treatment accounting for spatial correlation and determine relationships of these and other parameters over time.

A Bayesian analysis of an agricultural field trial with three spatial dimensions

Modern technology now has the ability to generate large datasets over space and time. Such data typically exhibit high autocorrelations over all dimensions. The field trial data motivating the methods of this paper were collected to examine the behaviour of traditional cropping and to determine a cropping system which could maximise water use for grain production while minimising leakage below the crop root zone. They consist of moisture measurements made at 15 depths across 3 rows and 18 columns, in the lattice framework of an agricultural field. Bayesian conditional autoregressive (CAR) models are used to account for local site correlations. Conditional autoregressive models have not been widely used in analyses of agricultural data. This paper serves to illustrate the usefulness of these models in this field, along with the ease of implementation in WinBUGS, a freely available software package. The innovation is the fitting of separate conditional autoregressive models for each depth layer, the ‘layered CAR model’, while simultaneously estimating depth profile functions for each site treatment. Modelling interest also lay in how best to model the treatment effect depth profiles, and in the choice of neighbourhood structure for the spatial autocorrelation model. The favoured model fitted the treatment effects as splines over depth, and treated depth, the basis for the regression model, as measured with error, while fitting CAR neighbourhood models by depth layer. It is hierarchical, with separate onditional autoregressive spatial variance components at each depth, and the fixed terms which involve an errors-in-measurement model treat depth errors as interval-censored measurement error. The Bayesian framework permits transparent specification and easy comparison of the various complex models compared.

Educational stress scale for adolescents : development, validity, and reliability with Chinese students

This article describes the development and initial validation of a new instrument to measure academic stress—the Educational Stress Scale for Adolescents (ESSA). A series of cross-sectional questionnaire surveys were conducted with more than 2,000 Chinese adolescents to examine the psychometric properties. The final 16-item ESSA contains five latent variables: Pressure from study, Workload, Worry about grades, Self-expectation, and Despondency, which together explain 64% of the total item variance. Scale scores showed adequate internal consistency, 2-week test–retest reliability, and satisfactory concurrent validity. A confirmatory factor analysis suggested the proposed factor model fits well in a different sample. For researchers who have a particular interest in academic stress among adolescents, the ESSA promises to be a useful tool.

Proximity-to-goal as a constraint on patterns of behaviour in attacker–defender dyads in team games

The aim of this study was to determine whether spatiotemporal interactions between footballers and the ball in 1 vs. 1 sub-phases are influenced by their proximity to the goal area. Twelve participants (age 15.3 ± 0.5 years) performed as attackers and defenders in 1 vs. 1 dyads across three field positions: (a) attacking the goal, (b) in midfield, and (c) advancing away from the goal area. In each position, the dribbler was required to move beyond an immediate defender with the ball towards the opposition goal. Interactions of attacker-defender dyads were filmed with player and ball displacement trajectories digitized using manual tracking software. One-way repeated measures analysis of variance was used to examine differences in mean defender-to-ball distance after this value had stabilized. Maximum attacker-to-ball distance was also compared as a function of proximity-to-goal. Significant differences were observed for defender-to-ball distance between locations (a) and (c) at the moment when the defender-to-ball distance had stabilized (a: 1.69 ± 0.64 m; c: 1.15 ± 0.59 m; P < 0.05). Findings indicate that proximity-to-goal influenced the performance of players, particularly when attacking or advancing away from goal areas, providing implications for training design in football. In this study, the task constraints of football revealed subtly different player interactions than observed in previous studies of dyadic systems in basketball and rugby union.

When non-significance maybe significant: lessons learned from a study into the development, implementation and evaluation of a risk assessment tool for fleet settings

Introduction This study reports on the development of a self report assessment tool to increase the efficacy of crash prediction within Australian Fleet settings Over last 20 years an array of measures have been produced (Driver anger scale, Driving Skill Inventory, Manchester Driver Behaviour Questionnaire, Driver Attitude Questionnaire, Driver Stress Inventory, Safety Climate Questionnaire) While these tools are useful, research has demonstrated limited ability to accurately identify individuals most likely to be involved in a crash. Reasons cited include; - Crashes are relatively rare - Other competing factors may influence crash event - Ongoing questions regarding the validity of self report measures (common method variance etc) - Lack of contemporary issues relating to fleet driving performance

Investigation of barriers to entry into the design-build market in the People’s Republic of China (PRC)

Although the design-build (DB) system has been demonstrated to be an effective delivery method and has gained popularity worldwide, it has not gained the same popularity in the construction market of China. The objective of this study was, theretofore, to investigate the barriers to entry in the DB market. A total of 22 entry barriers were first identified through an open-ended questionnaire survey with 15 top construction professionals in the construction market of China. A broad questionnaire survey was further conducted to prioritize these entry barriers. Statistical analysis of responses shows that the most dominant barriers to entry into the DB market are, namely, lack of design expertise, lack of interest from owners, lack of suitable organization structure, lack of DB specialists, and lack of credit record system. Analysis of variance indicates that there is no difference of opinions among the respondent groups of academia, government departments, state-owned company, and private company, at the 5% significance level, on most of the barriers to entry. Finally, the underlying dimensions of barriers to entry in the DB market were investigated through factor analysis. The results indicate that there are six major underlying dimensions of entry barriers in DB market, which include, namely, the competence of design-builders, difficulty in project procurement, characteristics of DB projects, lack of support from public sectors, the competence of DB owners, and the immaturity of DB market. These findings are useful for both potential and incumbent design-builders to understand and analyze the DB market in China.

Importance of soil ecology in vegetation rehabilitation on a North Stradbroke Island sand mine

Sibelco Australia Limited (SAL), a mineral sand mining operation on North Stradbroke Island, undertakes progressive rehabilitation of mined areas. Initial investigations have found that some areas at SAL’s Yarraman Mine have failed to redevelop towards approved criteria. This study, undertaken in 2010, examined ground cover rehabilitation of different aged plots at the Yarraman Mine to determine if there was a relationship between key soil and vegetation attributes. Vegetation and soil data were collected from five plots rehabilitated in 2003, 2006, 2008, 2009 and 2010, and one unmined plot. Cluster (PATN) analysis revealed that vegetation species composition, species richness and ground cover differed between plots. Principal component analysis (PCA) extracted ten soil attributes that were then correlated with vegetation data. The attributes extracted by PCA, in order of most common variance, were: water content, pH, terrolas depth, elevation, slope angle, leaf litter depth, total organic carbon, and counts of macrofauna, fungi and bacteria. All extracted attributes differed between plots, and all except bacteria correlated with at least one vegetation attribute. Water content and pH correlated most strongly with vegetation cover suggesting an increase in soil moisture and a reduction in pH are required in order to improve vegetation rehabilitation at Yarraman Mine. Further study is recommended to confirm these results using controlled experiments and to test potential solutions, such as organic amendments.

Speeding by young novice drivers : what can personal characteristics and psychosocial theory add to our understanding?

Purpose: Young novice drivers continue to be overrepresented in fatalities and injuries arising from crashes even with the introduction of countermeasures such as graduated driver licensing (GDL). Enhancing countermeasures requires a better understanding of the variables influencing risky driving. One of the most common risky behaviours performed by drivers of all ages is speeding, which is particularly risky for young novice drivers who, due to their driving inexperience, have difficulty in identifying and responding appropriately to road hazards. Psychosocial theory can improve our understanding of contributors to speeding, thereby informing countermeasure development and evaluation. This paper reports an application of Akers’ social learning theory (SLT), augmented by Gerrard and Gibbons’ prototype/willingness model (PWM), in addition to personal characteristics of age, gender, car ownership, and psychological traits/states of anxiety, depression, sensation seeking propensity and reward sensitivity, to examine the influences on self-reported speeding of young novice drivers with a Provisional (intermediate) licence in Queensland, Australia. Method: Young drivers (n = 378) recruited in 2010 for longitudinal research completed two surveys containing the Behaviour of Young Novice Drivers Scale, and reported their attitudes and behaviours as pre-Licence/Learner (Survey 1) and Provisional (Survey 2) drivers and their sociodemographic characteristics. Results: An Akers’ measurement model was created. Hierarchical multiple regressions revealed that (1) personal characteristics (PC) explained 20.3%; (2) the combination of PC and SLT explained 41.1%; and (3) the combination of PC, SLT and PWM explained 53.7% of variance in self-reported speeding. Whilst there appeared to be considerable shared variance, the significant predictors in the final model included gender, car ownership, reward sensitivity, depression, personal attitudes, and Learner speeding. Conclusions: These results highlight the capacity for psychosocial theory to improve our understanding of speeding by young novice drivers, revealing relationships between previous behaviour, attitudes, psychosocial characteristics and speeding. The findings suggest multi-faceted countermeasures should target the risky behaviour of Learners, and Learner supervisors should be encouraged to monitor their Learners’ driving speed. Novice drivers should be discouraged from developing risky attitudes towards speeding.

Internal and external motivation factors in virtual and collocated project environments : a principal component investigation

In this study, we explore motivation in collocated and virtual project teams. The literature on motivation in a project set.,ting reveals that motivation is closely linked to team performance. Based on this literature, we propose a set., of variables related to the three dimensions of ‘Nature of work’, ‘Rewards’, and ‘Communication’. Thirteen original variables in a sample size of 66 collocated and 66 virtual respondents are investigated using one tail t test and principal component analysis. We find that there are minimal differences between the two groups with respect to the above mentioned three dimensions. (p= .06; t=1.71). Further, a principal component analysis of the combined sample of collocated and virtual project environments reveals two factors- ‘Internal Motivating Factor’ related to work and work environment, and ‘External Motivating Factor’ related to the financial and non-financial rewards that explain 59.8% of the variance and comprehensively characterize motivation in collocated and virtual project environments. A ‘sense check’ of our interpretation of the results shows conformity with the theory and existing practice of project organization

Information technology resources,complementaries and capabilities : towards a deeper understanding of leveraging business value from IT

Organisations devote substantial resources to acquire information technology (IT), and explaining the important issue of how IT can affect performance has posed a significant challenge to information system (IS) researchers. Owing to the importance of expanding our understanding on how and where IT and IT-related resources impact organisational performance, this study investigates the differential effects of IT resources and IT-related capabilities, in the presence of platform-related complementarities, on business process performance. We test these relationships empirically via a field survey of 216 firms. The findings suggest that IT resources and IT-related capabilities explain variance in performance. Of interest is the finding that IT resources and IT-related capabilities ability to explain variance in business process is further enhanced by the presence of the platform-related complementarities. Our findings are largely consistent with the resource-based and complementarity arguments of sources of IT-related business value.

Factors influencing speeding in school zones : the role of mindfulness

Background Excessive speed contributes to the incidence and severity of road crashes. The Theory of Planned Behaviour (TPB) has successfully explained variance in speeding intentions and behaviour. However, studies have shown that more than 40% of the variance in outcome measures of speeding remains unexplained, thus, suggesting additional constructs may help to enhance the TPB’s predictive power. Therefore, this study examined mindfulness; a promising construct which has not yet been tested as an additional TPB predictor. Aims The aims of this study were to explore drivers’ beliefs about speeding in school zones using the extended TPB as a framework and to examine the effect that mindfulness had on driver speeding behaviour in school zones. Methods Australian drivers (N = 17) participated in one of four focus group discussions. The overall sample was comprised of five males and twelve females who were aged between 17 to56 years. All participants were recruited via purposive sampling among 1st year psychology students at a large South East Queensland University. The group discussions took approximately one hour and were guided by a structured interview schedule which sought to elicit drivers’ beliefs, thoughts and opinions on speeding in school zones and the factors which motivate such behaviour. Results Overall, thematic analysis revealed some similar issues emerged across the groups. . In particular and perhaps somewhat unsurprisingly, given public concerns regarding the want to ensure the safety of school children, there was much agreement that speeding in school zones was dangerous and unacceptable. Somewhat paradoxically however, some participants also agreed that they had unintentionally or mindlessly sped in school zones. There were several factors that drivers believed influenced their speeding in school zones including their current mood (e.g., if in a bad mood, anxious, or excited they may be more likely to drive without awareness of, and being attentive to, their driving environment) and the extent to which they were familiar with the environment (i.e., more familiar contexts, more likely to drive mindlessly). Thus, although drivers expressed a belief that speeding in school zones was dangerous and acceptable, the extent to which a driver is mindful does influence whether or not a driver may actually engage in speeding in this context. Discussion and conclusions This study highlights the potential role of mindfulness in helping to explain speeding behaviour in school zones. Mindless drivers may speed unintentionally and while unintentional still be endangering the safety and lives of school children. The findings of this research suggest that unintentional speeding, especially in school zones, may be reduced by countermeasures which heighten the extent to which drivers are mindful of approaching and/or driving through a school zone, such as street markings and engineering measures (e.g.,flashing lights and speed bumps).

A practical approach for identifying expected solution performance and robustness in operations research applications

A practical approach for identifying solution robustness is proposed for situations where parameters are uncertain. The approach is based upon the interpretation of a probability density function (pdf) and the definition of three parameters that describe how significant changes in the performance of a solution are deemed to be. The pdf is constructed by interpreting the results of simulations. A minimum number of simulations are achieved by updating the mean, variance, skewness and kurtosis of the sample using computationally efficient recursive equations. When these criterions have converged then no further simulations are needed. A case study involving several no-intermediate storage flow shop scheduling problems demonstrates the effectiveness of the approach.

Quality of work life and turnover intention in primary healthcare organisations : a cross-sectional study of registered nurses in Saudi Arabia

Purpose: The purpose of this study was to improve the retention of primary healthcare (PHC) nurses through exploring and assessing their quality of work life (QWL) and turnover intention. Design and methods: A cross-sectional survey design was used in this study. Data were collected using a questionnaire comprising four sections (Brooks’ survey of Quality of Nursing Work Life [QNWL], Anticipated Turnover Intention, open-ended questions and demographic characteristics). A convenience sample was recruited from 143 PHC centres in Jazan, Saudi Arabia. A response rate of 87% (n = 508/585) was achieved. The SPSS v17 for Windows and NVivo 8 were used for analysis purposes. Procedures and tests used in this study to analyse the quantitative data were descriptive statistics, t-test, ANOVA, General Linear Model (GLM) univariate analysis, standard multiple regression, and hierarchical multiple regression. Qualitative data obtained from responses to the open-ended questions were analysed using the NVivo 8. Findings: Quantitative findings suggested that PHC nurses were dissatisfied with their work life. Respondents’ scores ranged between 45 and 218 (mean = 139.45), which is lower than the average total score on Brooks’ Survey (147). Major influencing factors were classified under four dimensions. First, work life/home life factors: unsuitable working hours, lack of facilities for nurses, inability to balance work with family needs and inadequacy of vacations’ policy. Second, work design factors: high workload, insufficient workforce numbers, lack of autonomy and undertaking many non-nursing tasks. Third, work context factors: management practices, lack of development opportunities, and inappropriate working environment in terms of the level of security, patient care supplies and unavailability of recreation room. Finally, work world factors: negative public image of nursing, and inadequate payment. More positively, nurses were notably satisfied with their co-workers. Conversely, 40.4% (n = 205) of the respondents indicated that they intended to leave their current employment. The relationships between QWL and demographic variables of gender, age, marital status, dependent children, dependent adults, nationality, ethnicity, nursing tenure, organisational tenure, positional tenure, and payment per month were significant (p < .05). The eta squared test for these demographics indicates a small to medium effect size of the variation in QWL scores. Using the GLM univariate analysis, education level was also significantly related to the QWL (p < .05). The relationships between turnover intention and demographic variables including gender, age, marital status, dependent children, education level, nursing tenure, organisational tenure, positional tenure, and payment per month were significant (p < .05). The eta squared test for these demographics indicates a small to moderate effect size of the variation in the turnover intention scores. Using the GLM univariate analysis, the dependent adults’ variable was also significantly related to turnover intention (p < .05). Turnover intention was significantly related to QWL. Using standard multiple regression, 26% of the variance in turnover intention was explained by the QWL F (4,491), 43.71, p < .001, with R² = .263. Further analysis using hierarchical multiple regression found that the total variance explained by the model as a whole (demographics and QWL) was 32.1%, F (17.433) = 12.04, p < .001. QWL explained an additional 19% of the variance in turnover intention, after controlling for demographic variables, R squared change =.19, F change (4, 433) = 30.190, p < .001. The work context variable makes the strongest unique contribution (-.387) to explain the turnover intention, followed by the work design dimension (-.112). The qualitative findings reaffirmed the quantitative findings in terms of QWL and turnover intention. However, the home life/work life and work world dimensions were of great important to both QWL and turnover intention. The qualitative findings revealed a number of new factors that were not included in the survey questionnaire. These included being away from family, lack of family support, social and cultural aspects, accommodation facilities, transportation, building and infrastructure of PHC, nature of work, job instability, privacy at work, patients and community, and distance between home and workplace. Conclusion: Creating and maintaining a healthy work life for PHC nurses is very important to improve their work satisfaction, reduce turnover, enhance productivity and improve nursing care outcomes. Improving these factors could lead to a higher QWL and increase retention rates and therefore reinforcing the stabilisation of the nursing workforce. Significance of the research: Many countries are examining strategies to attract and retain the health care workforce, particularly nurses. This study identified factors that influence the QWL of PHC nurses as well as their turnover intention. It also determined the significant relationship between QWL and turnover intention. In addition, the present study tested Brooks’ survey of QNWL on PHC nurses for the first time. The qualitative findings of this study revealed a number of new variables regarding QWL and turnover intention of PHC nurses. These variables could be used to improve current survey instruments or to develop new research surveys. The study findings could be also used to develop and appropriately implement plans to improve QWL. This may help to enhance the home and work environments of PHC nurses, improve individual and organisational performance, and increase nurses’ commitment. This study contributes to the existing body of research knowledge by presenting new data and findings from a different country and healthcare system. It is the first of its kind in Saudi Arabia, especially in the field of PHC. It has examined the relationship between QWL and turnover intention of PHC nurses for the first time using nursing instruments. The study also offers a fresh explanation (new framework) of the relationship between QWL and turnover intention among PHC nurses, which could be used or tested by researchers in other settings. Implications for further research: Review of the extant literature reveals little in-depth research on the PHC workforce, especially in terms of QWL and organisational turnover in developing countries. Further research is required to develop a QWL tool for PHC nurses, taking into consideration the findings of the current study along with the local culture. Moreover, the revised theoretical framework of the current study could be tested in further research in other regions, countries or healthcare systems in order to identify its ability to predict the level of PHC nurses’ QWL and their intention to leave. There is a need to conduct longitudinal research on PHC organisations to gain an in-depth understanding of the determents of and changes in QWL and turnover intention of PHC nurses at various points of time. An intervention study is required to improve QWL and retention among PHC nurses using the findings of the current study. This would help to assess the impact of such strategies on reducing turnover of PHC nurses. Focusing on the location of the current study, it would be valuable to conduct another study in five years’ time to examine the percentage of actual turnover among PHC nurses compared with the reported turnover intention in the current study. Further in-depth research would also be useful to assess the impact of the local culture on the perception of expatriate nurses towards their QWL and their turnover intention. A comparative study is required between PHC centres and hospitals as well as the public and private health sector agencies in terms of QWL and turnover intention of nursing personnel. Findings may differ from sector to sector according to variations in health systems, working environments and the case mix of patients.

Empirical analysis on relationship between traffic conditions and crash occurrences

This paper investigates relationship between traffic conditions and the crash occurrence likelihood (COL) using the I-880 data. To remedy the data limitations and the methodological shortcomings suffered by previous studies, a multiresolution data processing method is proposed and implemented, upon which binary logistic models were developed. The major findings of this paper are: 1) traffic conditions have significant impacts on COL at the study site; Specifically, COL in a congested (transitioning) traffic flow is about 6 (1.6) times of that in a free flow condition; 2)Speed variance alone is not sufficient to capture traffic dynamics’ impact on COL; a traffic chaos indicator that integrates speed, speed variance, and flow is proposed and shows a promising performance; 3) Models based on aggregated data shall be interpreted with caution. Generally, conclusions obtained from such models shall not be generalized to individual vehicles (drivers) without further evidences using high-resolution data and it is dubious to either claim or disclaim speed kills based on aggregated data.