A self-regulation-based intervention to increase physical activity in cancer patients

The study examined whether a behavior-change intervention focusing on self-regulatory strategies and emphasizing role model support increases physical activity (PA) among insufficiently active (not meeting PA guidelines of 150 min/week) cancer patients. Ambulatory cancer patients [N = 72; 54% female; M = 56 years, SD = 12.34; most with breast or colon cancer (34, 15%)] were enrolled in the MOTIVACTION-study, a 4-week intervention (1-hr counseling, followed by weekly phone calls), with pretest (T1), posttest (T2) and a 10-week follow-up (T3). Participants were randomized to either an exercise or to a stress management intervention (active control). The exercise intervention emphasized self-regulatory strategies (e.g. action- and coping planning and self-monitoring); patients were also encouraged to contact a physically active same-sex role model as a potential exercise partner. The active control condition consisted of coping and relaxation techniques. Sixty-seven patients remained in the study and completed the SQUASH assessment of PA and a measure of perceived stress. PA was validated by Actigraph accelerometry. At T2, 46% of the patients in the exercise group and 19% of stress management patients increased their activity levels to meet PA guidelines (>150 min/week; χ²(1) = 5.51, p = .019). At T3, participants in the exercise intervention maintained their exercise level (46%), but also 31% of the stress management patients met the guidelines. All patients reported reductions in perceived stress. Additional analyses comparing patients in the exercise group by role model contact (63% realized contact) revealed that those who had contact with their role model were significantly more likely to adhere to the recommended guidelines (T2:50%; T3:64%) compared to those who did not have contact with a role model (T2:39%; T3:15%), suggesting the potential of mobilizing role model support to facilitate PA. In sum, cancer patients may not only benefit from an exercise intervention emphasizing self-regulation, but also from stress management, regarding both reducing stress and increasing PA.     

On-call work and physicians’ turnover intention: the moderating effect of job strain

Physician shortage and turnover are major problems worldwide. On-call duties may be among the risk factors of high turnover rates among physicians. We investigated whether having on-call duties is associated with physicians’ turnover intention and whether job strain variables moderate this association. The present study was a cross-sectional questionnaire study among 3324 (61.6% women) Finnish physicians. The analyses were conducted using analyses of covariance adjusted for age, gender, response format, specialization status and employment sector. The results showed that job strain moderated the association between being on-call and turnover intention. The highest levels of turnover intention were among those who had on-call duties and high level of job strain characterized by high demands and low control opportunities. The lowest levels of turnover intention were among those who were not on-call and who had low strain involving low demands and high control. Also, job demands moderated the association between being on-call and turnover intention; turnover intention levels were higher among those with on-call duties and high demands than those being on-call and low demands. To conclude, working on-call was related to physicians’ turnover intention particularly in those with high job strain. Health care organizations should focus more attention on working arrangements and scheduling of on-call work, provide a suitable working pace and implement means to increase physicians’ participation and control over their job.     

A field investigation of red-light-running in Shanghai,China

Red-Light-Running (RLR) is the major cause of severe injury crashes at signalized intersections for both China and the US. As several studies have been conducted to identify the influencing factors of RLR behavior in the US, no similar studies exist in China. To fill this gap, this study was conducted to identify the key factors that affect RLR and compare the contributing factors between US and China. Data were collected through field observations and video recordings; four intersections in Shanghai were selected as the study sites. Both RLR drivers and comparison drivers, who had the opportunity to run the light but did not, were identified. Based on the collected data, preliminary analyses were firstly conducted to identify the features of the RLR and comparison groups. It was determined that: around 57% of RLR crossed the stop line during the 0–0.4 second time interval after red-light onset, and the numbers of red light violators decreased as the time increased; among the RLR vehicles, 38% turned left and 62% went straight; and at the onset of red, about 88% of RLR vehicles were in the middle of a vehicle platoon. Furthermore, in order to compare the RLR group and non-RLR group, two types of logistic regression models were developed. The ordinary logistic regression model was developed to identify the significant variables from the aspects of driver characteristics, driving conditions, and vehicle types. It was concluded that RLR drivers are more likely to be male, have local license plates, and are driving passenger vehicles but without passengers. Large traffic volume also increased the likelihood of RLR. However, the ordinary logistic regression model only considers influencing factors at the vehicle level: different intersection design and signal settings may also have impact on RLR behaviors. Therefore, in order to account for unobserved heterogeneity among different types of intersections, a random effects logistic regression model was adopted. Through the model comparisons, it has been identified that the model goodness-of-fit was substantially improved through considering the heterogeneity effects at intersections. Finally, benefits of this study and the analysis results were discussed.     

Socio-economic and driving experience factors affecting drivers’ perceptions of traffic crash risk

Drivers are estimated to contribute an overwhelming proportion to the burden of traffic crashes, as factors that increase crash risk are frequently due to unsafe driving behaviours. The relationship between risk perceptions and people’s risky driving behaviours is still not well understood. This paper aims to further analyse the potential effect of risky driving behaviours on drivers’ perceptions of crash risk and differences in perceptions among drivers.Crash risk perceptions in an inter-city, two-way road context of 492 drivers were measured by using a Stated Preference (SP) ranking survey. Rank-ordered logit models were used to evaluate the impact on risk perception of five unsafe driving behaviours and to identify differences in drivers’ risk perceptions. The five unsafe driving behaviours considered in the analysis were respectively related to whether or not the driver follows the speed limits, the rules of passing another car and the safe distance, whether or not the driver is distracted, and whether or not she/he is driving under optimal personal conditions.All risky driving behaviours showed a significant potential effect (p < 0.001) on crash risk perceptions, and model’s results allowed to differentiate more important from less important unsafe driving behaviours based on their weight on perceived crash risk. Additionally, this paper further analyses the potential differences in risk perception of these traffic violations between drivers of different characteristics, such as driving experience, household size, income and gender.The SP technique could be applied to further analyse differences in perceptions of risky driving behaviours among drivers. Future research should consider the potential effect of driving skill on perceptions of risky driving behaviours.     

Accounting for the Theory of Planned Behaviour in departure time choice

Motivating people to change their departure time could play a key role in reducing peak-hour congestion, which remains one of the most prevalent transport problems in large urban areas. To achieve this behavioural change, it is necessary to better understand the factors that influence departure time choice. So far departure time choice modelling focussed mainly on objective factors, such as time and costs as main behavioural determinants. In this study, we derived psychological factors based on the Theory of Planned Behaviour, estimated them based on structural equation modelling, and included them into a discrete choice model. The psychological factors were measured based on an online questionnaire addressed to car commuters to the city centre of Copenhagen (N = 286). The questionnaire additionally included a travel diary and a stated preference experiment with nine departure time choice scenarios. All psychological factors had a significant effect on departure time choice and could improve the model as compared to a basic discrete choice model without latent constructs. As expected, the effects of the psychological factors were different depending on framework conditions: for people with fixed starting times at work, the intention to arrive at work on time (as estimated by subjective norm, attitude, perceived behavioural control) had the strongest effect; for people with flexible working hours, the attitude towards short travel time was most relevant. Limitations, the inclusion of additional psychological factors and their possible interactions are discussed.     

Escapism motive for sport consumption as a predictor of meaning in life

The objective of this study was to examine whether spectator escapism motive for sport consumption could predict meaning in life, and to explore the role of psychological ownership in this relationship. A sample of 806 football spectators (African = 85%, male = 67.4%, Sesotho = 26.2%) completed the Motivation Scale for Sport Consumption (MSSC), the South African Psychological Ownership Questionnaire (SAPOS) and the Meaning in Life Questionnaire (MLQ). Structural equation modelling was utilised to investigate the postulated paths of the structural model. Escapism motive for sport consumption predicted meaning in life among spectators through psychological ownership. The sports escapism motive can yield positive psychological outcomes for sports fans.     

Perfectionism and changes in athlete burnout over three months: Interactive effects of personal standards and evaluative concerns perfectionism

ObjectivesA recent longitudinal study with junior athletes (Madigan, Stoeber, & Passfield, 2015) found perfectionism to predict changes in athlete burnout: evaluative concerns perfectionism predicted increases in burnout over a 3-month period, whereas personal standards perfectionism predicted decreases. The present study sought to expand on these findings by using the framework of the 2 × 2 model of perfectionism (Gaudreau & Thompson, 2010) to examine whether evaluative concerns perfectionism and personal standards perfectionism show interactions in predicting changes in athlete burnout.DesignTwo-wave longitudinal design.MethodThe present study examined self-reported evaluative concerns perfectionism, personal standards perfectionism, and athlete burnout in 111 athletes (mean age 24.8 years) over 3 months of active training.Results and conclusionWhen moderated regression analyses were employed, interactive effects of evaluative concerns perfectionism × personal standards perfectionism were found indicating that personal standards perfectionism buffered the effects of evaluative concerns perfectionism on total burnout and physical/emotional exhaustion. To interpret these effects, the 2 × 2 model of perfectionism provides a useful theoretical framework.     

Evaluating the temporal structure and correlates of daily self-esteem using a trait state error framework (TSE)

This study evaluates the temporal structure of daily self-esteem and the relative contribution of a range of theoretically motivated predictors of daily self-esteem. To assess self-esteem stability, a daily version of the Rosenberg Self-Esteem scale (RSE, Rosenberg, 1965) was administered to 278 undergraduates for five consecutive days. These short-term longitudinal data were analysed using the Trait State Error (TSE) modelling framework. The TSE decomposes multi-wave data into three components: (1) a stable trait component, (2) a state component, and (3) an error component. Significant predictors of the trait component of self-esteem observed across five days were: (1) emotional stability, and (2) the congruence between implicit and explicit self-esteem. Significant predictors of the state components of self-esteem were daily positive and negative events. We discuss the implications of these results for future research concerning self-esteem stability.     

Grain Size and Parameter Recovery with TIMSS and the General Diagnostic Model

The purpose of this study was to explore the degree of grain size of the attributes and the sample sizes that can support accurate parameter recovery with the General Diagnostic Model (GDM) for a large-scale international assessment. In this resampling study, bootstrap samples were obtained from the 2003 Grade 8 TIMSS in Mathematics at varying sample sizes from 500 to 4000 and grain sizes of the attributes from a unidimensional model to one with ten attributes. The results showed that the eight-attribute model was the one most consistently identified as best fitting. Parameter estimation for more than ten attributes and samples less than 500 failed. Furthermore, the precision of item parameter recovery decreased as the number of attributes measured by an item increased and sample size decreased. On the other hand, the distributions of latent classes were relatively stable across all models and sample sizes.