Implementation and evaluation of a new model of nursing practice in radiation oncology

Patients undergoing radiation therapy for cancer face a series of challenges that require support from a multidisciplinary team which includes radiation oncology nurses. However, the specific contribution of nursing, and the models of care that best support the delivery of nursing interventions in the radiotherapy setting, is not well described. In this case study, the Interaction Model of Client Health Behaviour and the associated principles of person-centred care were incorporated into a new model of care that was implemented in one radiation oncology setting in Brisbane, Australia. The new model of care was operationalised through a Primary Nursing/Collaborative Practice framework. To evaluate the impact of the new model for patients and health professionals, multiple sources of data were collected from patients and clinical staff prior to, during, and 18 months following introduction of the practice redesign. One cohort of patients and clinical staff completed surveys incorporating measures of key outcomes immediately prior to implementation of the model, while a second cohort of patients and clinical staff completed these same surveys 18 months following introduction of the model. In-depth interviews were also conducted with nursing, medical and allied health staff throughout the implementation phase to obtain a more comprehensive account of the processes and outcomes associated with implementing such a model. From the patients’ perspectives, this study demonstrated that, although adverse effects of radiotherapy continue to affect patient well-being, patients continue to be satisfied with nursing care in this specialty, and that they generally reported high levels of functioning despite undergoing a curative course of radiotherapy. From the health professionals’ perspective, there was evidence of attitudinal change by nursing staff within the radiotherapy department which reflected a greater understanding and appreciation of a more person-centred approach to care. Importantly, this case study has also confirmed that a range of factors need to be considered when redesigning nursing practice in the radiotherapy setting, as the challenges associated with changing traditional practices, ensuring multidisciplinary approaches to care, and resourcing a new model were experienced. The findings from this study suggest that the move from a relatively functional approach to a person-centred approach in the radiotherapy setting has contributed to some improvements in the provision of individualised and coordinated patient care. However, this study has also highlighted that primary nursing may be limited in its approach as a framework for patient care unless it is supported by a whole team approach, an appropriate supportive governance model, and sufficient resourcing. Introducing such a model thus requires effective education, preparation and ongoing support for the whole team. The challenges of providing care in the context of complex interdisciplinary relationships have been highlighted by this study. Aspects of this study may assist in planning further nursing interventions for patients undergoing radiotherapy for cancer, and continue to enhance the contribution of the radiation oncology nurse to improved patient outcomes.

Forecasting crashes at the planning level: Simultaneous negative binomial crash model applied in Tucson, Arizona

At least two important transportation planning activities rely on planning-level crash prediction models. One is motivated by the Transportation Equity Act for the 21st Century, which requires departments of transportation and metropolitan planning organizations to consider safety explicitly in the transportation planning process. The second could arise from a need for state agencies to establish incentive programs to reduce injuries and save lives. Both applications require a forecast of safety for a future period. Planning-level crash prediction models for the Tucson, Arizona, metropolitan region are presented to demonstrate the feasibility of such models. Data were separated into fatal, injury, and property-damage crashes. To accommodate overdispersion in the data, negative binomial regression models were applied. To accommodate the simultaneity of fatality and injury crash outcomes, simultaneous estimation of the models was conducted. All models produce crash forecasts at the traffic analysis zone level. Statistically significant (p-values < 0.05) and theoretically meaningful variables for the fatal crash model included population density, persons 17 years old or younger as a percentage of the total population, and intersection density. Significant variables for the injury and property-damage crash models were population density, number of employees, intersections density, percentage of miles of principal arterial, percentage of miles of minor arterials, and percentage of miles of urban collectors. Among several conclusions it is suggested that planning-level safety models are feasible and may play a role in future planning activities. However, caution must be exercised with such models.

Multiple indicators of ambient and personal ultraviolet radiation exposure and risk of non-Hodgkin lymphoma (United States)

Recent epidemiologic studies have suggested that ultraviolet radiation (UV) may protect against non-Hodgkin lymphoma (NHL), but few, if any, have assessed multiple indicators of ambient and personal UV exposure. Using the US Radiologic Technologists study, we examined the association between NHL and self-reported time outdoors in summer, as well as average year-round and seasonal ambient exposures based on satellite estimates for different age periods, and sun susceptibility in participants who had responded to two questionnaires (1994–1998, 2003–2005) and who were cancer-free as of the earlier questionnaire. Using unconditional logistic regression, we estimated the odds ratio (OR) and 95% confidence intervals for 64,103 participants with 137 NHL cases. Self-reported time outdoors in summer was unrelated to risk. Lower risk was somewhat related to higher average year-round and winter ambient exposure for the period closest in time, and prior to, diagnosis (ages 20–39). Relative to 1.0 for the lowest quartile of average year-round ambient UV, the estimated OR for successively higher quartiles was 0.68 (0.42–1.10); 0.82 (0.52–1.29); and 0.64 (0.40–1.03), p-trend = 0.06), for this age period. The lower NHL risk associated with higher year-round average and winter ambient UV provides modest additional support for a protective relationship between UV and NHL.

Forecasting negative effects of monotony and sensation seeking on performance during a vigilance task

The driving task requires sustained attention during prolonged periods, and can be performed in highly predictable or repetitive environments. Such conditions could create hypovigilance and impair performance towards critical events. Identifying such impairment in monotonous conditions has been a major subject of research, but no research to date has attempted to predict it in real-time. This pilot study aims to show that performance decrements due to monotonous tasks can be predicted through mathematical modelling taking into account sensation seeking levels. A short vigilance task sensitive to short periods of lapses of vigilance called Sustained Attention to Response Task is used to assess participants‟ performance. The framework for prediction developed on this task could be extended to a monotonous driving task. A Hidden Markov Model (HMM) is proposed to predict participants‟ lapses in alertness. Driver‟s vigilance evolution is modelled as a hidden state and is correlated to a surrogate measure: the participant‟s reactions time. This experiment shows that the monotony of the task can lead to an important decline in performance in less than five minutes. This impairment can be predicted four minutes in advance with an 86% accuracy using HMMs. This experiment showed that mathematical models such as HMM can efficiently predict hypovigilance through surrogate measures. The presented model could result in the development of an in-vehicle device that detects driver hypovigilance in advance and warn the driver accordingly, thus offering the potential to enhance road safety and prevent road crashes.

Availability of advance visual information constrains association-football goalkeeping performance during penalty kicks

A pressing concern within the literature on anticipatory perceptual-motor behaviour is the lack of clarity on the applicability of data, observed under video-simulation task constraints, to actual performance in which actions are coupled to perception, as captured during in-situ experimental conditions. We developed an in-situ experimental paradigm which manipulated the duration of anticipatory visual information from a penalty taker’s actions to examine experienced goalkeepers’ vulnerability to deception for the penalty kick in association football. Irrespective of the penalty taker’s kick strategy, goalkeepers initiated movement responses earlier across consecutively earlier presentation points. Overall goalkeeping performance was better in non-deception trials than in deception conditions. In deception trials, the kinematic information presented up until the penalty taker initiated his/her kicking action had a negative effect on goalkeepers’ performance. It is concluded that goalkeepers are likely to benefit from not anticipating a penalty taker’s performance outcome based on information from the run-up, in preference to later information that emerges just before the initiation of the penalty taker’s kicking action.

Empirical Bayes method in the study of traffic safety via heterogeneous negative multinomial model

In the study of traffic safety, expected crash frequencies across sites are generally estimated via the negative binomial model, assuming time invariant safety. Since the time invariant safety assumption may be invalid, Hauer (1997) proposed a modified empirical Bayes (EB) method. Despite the modification, no attempts have been made to examine the generalisable form of the marginal distribution resulting from the modified EB framework. Because the hyper-parameters needed to apply the modified EB method are not readily available, an assessment is lacking on how accurately the modified EB method estimates safety in the presence of the time variant safety and regression-to-the-mean (RTM) effects. This study derives the closed form marginal distribution, and reveals that the marginal distribution in the modified EB method is equivalent to the negative multinomial (NM) distribution, which is essentially the same as the likelihood function used in the random effects Poisson model. As a result, this study shows that the gamma posterior distribution from the multivariate Poisson-gamma mixture can be estimated using the NM model or the random effects Poisson model. This study also shows that the estimation errors from the modified EB method are systematically smaller than those from the comparison group method by simultaneously accounting for the RTM and time variant safety effects. Hence, the modified EB method via the NM model is a generalisable method for estimating safety in the presence of the time variant safety and the RTM effects.

Negative mood, implicit alcohol-related memory, and alcohol use in young adults: The moderating effect of alcohol expectancy

Objective Alcohol-related implicit (preconscious) cognitive processes are established and unique predictors of alcohol use, but most research in this area has focused on alcohol-related implicit cognition and anxiety. This study extends this work into the area of depressed mood by testing a cognitive model that combines traditional explicit (conscious and considered) beliefs, implicit alcohol-related memory associations (AMAs), and self-reported drinking behavior. Method Using a sample of 106 university students, depressed mood was manipulated using a musical mood induction procedure immediately prior to completion of implicit then explicit alcohol-related cognition measures. A bootstrapped two-group (weak/strong expectancies of negative affect and tension reduction) structural equation model was used to examine how mood changes and alcohol-related memory associations varied across groups. Results Expectancies of negative affect moderated the association of depressed mood and AMAs, but there was no such association for tension reduction expectancy. Conclusion Subtle mood changes may unconsciously trigger alcohol-related memories in vulnerable individuals. Results have implications for addressing subtle fluctuations in depressed mood among young adults at risk of alcohol problems.

Countering negative country of origin effects using imagery processing

A favorable product country of origin (e.g., an automobile made in Germany) is often considered an asset by marketers. Yet a challenge in today's competitive environment is how marketers of products from less favorably regarded countries can counter negative country of origin perceptions. Three studies investigate how mental imagery can be used to reduce the effects of negative country of origin stereotypes. Study 1 reveals that participants exposed to country of origin information exhibit automatic stereotype activation. Study 2 shows that self-focused counterstereotypical mental imagery (relative to other-focused mental imagery) significantly inhibits the automatic activation of negative country of origin stereotypes. Study 3 shows that this lessening of automatic negative associations persists when measured one day later. The results offer important implications for marketing theory and practice.

Increased traffic exposure and negative birth outcomes : a prospective cohort in Australia

Background: Pregnant women exposed to traffic pollution have an increased risk of negative birth outcomes. We aimed to investigate the size of this risk using a prospective cohort of 970 mothers and newborns in Logan, Queensland. ----- ----- Methods: We examined two measures of traffic: distance to nearest road and number of roads around the home. To examine the effect of distance we used the number of roads around the home in radii from 50 to 500 metres. We examined three road types: freeways, highways and main roads.----- ----- Results: There were no associations with distance to road. A greater number of freeways and main roads around the home were associated with a shorter gestation time. There were no negative impacts on birth weight, birth length or head circumference after adjusting for gestation. The negative effects on gestation were largely due to main roads within 400 metres of the home. For every 10 extra main roads within 400 metres of the home, gestation time was reduced by 1.1% (95% CI: -1.7, -0.5; p-value = 0.001).----- ----- Conclusions: Our results add weight to the association between exposure to traffic and reduced gestation time. This effect may be due to the chemical toxins in traffic pollutants, or because of disturbed sleep due to traffic noise.

A quasi four dimensional radiation detector

Techniques for the accurate measurement of ionising radiation have been evolving since Roentgen first discovered x-rays in 1895; until now experimental measurements of radiation fields in the three spatial dimensions plus time have not been successfully demonstrated. In this work, we embed an organic plastic scintillator in a polymer gel dosimeter to obtain the first quasi-4D experimental measurement of a radiation field.

A hybrid radiation detector for simultaneous spatial and temporal dosimetry

In this feasibility study an organic plastic scintillator is calibrated against ionisation chamber measurements and then embedded in a polymer gel dosimeter to obtain a quasi-4D experimental measurement of a radiation field. This hybrid dosimeter was irradiated with a linear accelerator, with temporal measurements of the dose rate being acquired by the scintillator and spatial measurements acquired with the gel dosimeter. The detectors employed in this work are radiologically equivalent; and we show that neither detector perturbs the intensity of the radiation field of the other. By employing these detectors in concert, spatial and temporal variations in the radiation intensity can now be detected and gel dosimeters can be calibrated for absolute dose from a single irradiation.

Mining positive and negative patterns for relevance feature discovery

It is a big challenge to guarantee the quality of discovered relevance features in text documents for describing user preferences because of the large number of terms, patterns, and noise. Most existing popular text mining and classification methods have adopted term-based approaches. However, they have all suffered from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern-based methods should perform better than term-based ones in describing user preferences, but many experiments do not support this hypothesis. The innovative technique presented in paper makes a breakthrough for this difficulty. This technique discovers both positive and negative patterns in text documents as higher level features in order to accurately weight low-level features (terms) based on their specificity and their distributions in the higher level features. Substantial experiments using this technique on Reuters Corpus Volume 1 and TREC topics show that the proposed approach significantly outperforms both the state-of-the-art term-based methods underpinned by Okapi BM25, Rocchio or Support Vector Machine and pattern based methods on precision, recall and F measures.