Online prostate cancer screening decision aid for at-risk men: A randomized trial

Objective: This study examines the efficacy of an online decision aid (DA) for men with a family history of prostate cancer. Methods: Unaffected Australian men (40 - 79 years) with at least one affected relative completed the first online questionnaire, were randomized to read either the tailored DA (intervention) or nontailored information about prostate cancer screening (control), then completed a questionnaire postreading and 12 months later. The primary outcome was decisional conflict regarding prostate specific antigen (PSA) testing. The impact of the DA on longitudinal outcomes was analyzed by using random intercept mixed effects models. Logistic and linear regressions were used to analyze the impact of the DA on screening behavior and decision regret. Stage of decision-making was tested as a moderator for decisional conflict and decision regret. The frequency of online material access was recorded. Results: the DA had no effect on decisional conflict, knowledge, inclination toward PSA testing, accuracy of perceived risk, or screening behavior. However, among men considering PSA testing, those who read the DA had lower decision regret compared with men who read the control materials, β=.34 , p \u3c.001, 95% confidence interval (CI) = [.22, .53]. Conclusions: This is the first study to our knowledge to evaluate the uptake and efficacy of an online screening DA among men with a family history of prostate cancer. Men who were undecided about screening at baseline benefitted from the DA, experiencing less regret 12 months later. In relation to decisional conflict, the control materials may have operated as a less complex and equally informative DA

Just good enough data: Figuring data citizenships through air pollution sensing and data stories

Citizen sensing, or the use of low-cost and accessible digital technologies to monitor environments, has contributed to new types of environmental data and data practices. Through a discussion of participatory research into air pollution sensing with residents of northeastern Pennsylvania concerned about the effects of hydraulic fracturing, we examine how new technologies for generating environmental data also give rise to new problems for analysing and making sense of citizen-gathered data. After first outlining the citizen data practices we collaboratively developed with residents for monitoring air quality, we then describe the data stories that we created along with citizens as a method and technique for composing data. We further mobilise the concept of ‘just good enough data’ to discuss the ways in which citizen data gives rise to alternative ways of creating, valuing and interpreting datasets. We specifically consider how environmental data raises different concerns and possibilities in relation to Big Data, which can be distinct from security or social media studies. We then suggest ways in which citizen datasets could generate different practices and interpretive insights that go beyond the usual uses of environmental data for regulation, compliance and modelling to generate expanded data citizenships

Patient experiences of swallowing exercises after head and neck cancer:A qualitative study examining barriers and facilitators using behaviour change theory

Poor patient adherence to swallowing exercises is commonly reported in the dysphagia literature on patients treated for head and neck cancer. Establishing the effectiveness of exercise interventions for this population may be undermined by patient non-adherence. The purpose of this study was to explore the barriers and facilitators to exercise adherence from a patient perspective, and to determine the best strategies to reduce the barriers and enhance the facilitators. In-depth interviews were conducted on thirteen patients. We used a behaviour change framework and model [Theoretical domains framework and COM-B (Capability-opportunity-motivation-behaviour) model] to inform our interview schedule and structure our results, using a content analysis approach. The most frequent barrier identified was psychological capability. This was highlighted by patient reports of not clearly understanding reasons for the exercises, forgetting to do the exercises and not having a system to keep track. Other barriers included feeling overwhelmed by information at a difficult time (lack of automatic motivation) and pain and fatigue (lack of physical capability). Main facilitators included having social support from family and friends, the desire to prevent negative consequences such as long-term tube feeding (reflective motivation), having the skills to do the exercises (physical capability), having a routine or trigger and receiving feedback on the outcome of doing exercises (automatic motivation). Linking these findings back to the theoretical model allows for a more systematic selection of theory-based strategies that may enhance the design of future swallowing exercise interventions for patients with head and neck cancer

Patient experiences of swallowing exercises after head and neck cancer:A qualitative study examining barriers and facilitators using behaviour change theory

Poor patient adherence to swallowing exercises is commonly reported in the dysphagia literature on patients treated for head and neck cancer. Establishing the effectiveness of exercise interventions for this population may be undermined by patient non-adherence. The purpose of this study was to explore the barriers and facilitators to exercise adherence from a patient perspective, and to determine the best strategies to reduce the barriers and enhance the facilitators. In-depth interviews were conducted on thirteen patients. We used a behaviour change framework and model [Theoretical domains framework and COM-B (Capability-opportunity-motivation-behaviour) model] to inform our interview schedule and structure our results, using a content analysis approach. The most frequent barrier identified was psychological capability. This was highlighted by patient reports of not clearly understanding reasons for the exercises, forgetting to do the exercises and not having a system to keep track. Other barriers included feeling overwhelmed by information at a difficult time (lack of automatic motivation) and pain and fatigue (lack of physical capability). Main facilitators included having social support from family and friends, the desire to prevent negative consequences such as long-term tube feeding (reflective motivation), having the skills to do the exercises (physical capability), having a routine or trigger and receiving feedback on the outcome of doing exercises (automatic motivation). Linking these findings back to the theoretical model allows for a more systematic selection of theory-based strategies that may enhance the design of future swallowing exercise interventions for patients with head and neck cancer

Measuring electrophysiological connectivity by power envelope correlation: a technical review on MEG methods

The human brain can be divided into multiple areas, each responsible for different aspects of behaviour. Healthy brain function relies upon efficient connectivity between these areas and, in recent years, neuroimaging has been revolutionised by an ability to estimate this connectivity. In this paper we discuss measurement of network connectivity using magnetoencephalography (MEG), a technique capable of imaging electrophysiological brain activity with good (~5mm) spatial resolution and excellent (~1ms) temporal resolution. The rich information content of MEG facilitates many disparate measures of connectivity between spatially separate regions and in this paper we discuss a single metric known as power envelope correlation. We review in detail the methodology required to measure power envelope correlation including i) projection of MEG data into source space, ii) removing confounds introduced by the MEG inverse problem and iii) estimation of connectivity itself. In this way, we aim to provide researchers with a description of the key steps required to assess envelope based functional networks, which are thought to represent an intrinsic mode of coupling in the human brain. We highlight the principal findings of the techniques discussed, and furthermore, we show evidence that this method can probe how the brain forms and dissolves multiple transient networks on a rapid timescale in order to support current processing demand. Overall, power envelope correlation offers a unique and verifiable means to gain novel insights into network coordination and is proving to be of significant value in elucidating the neural dynamics of the human connectome in health and disease

Engaging primary students with the issue of air pollution through citizen science: lessons to be learnt

This paper shares insights from an air quality research project that involved 258 primary school children aged between 5 and 11. The children attended a dedicated session led by scientists explaining the nature of air pollution. They then wore specially designed backpacks with built‐in air quality sensors during their commute to school for one week to measure air pollution. The generated data were used by scientists to determine children’s exposure to air pollution in and around their schools. To examine the children’s understanding of both air pollution and ways to reduce exposure, participating children completed surveys (pre‐ and post‐ the monitoring week). Interviews with ten teachers were conducted to help contextualise the survey findings. Our findings indicate that contributory citizen science projects constitute a valuable approach to engaging children in environmental education. We also note the importance of ensuring the active participation of teachers, particularly so that misconceptions are rapidly identified and thereafter addressed

Unexpectedly high concentrations of monoterpenes in a study of UK homes

The abundance of volatile organic compounds (VOCs) found in homes depends on many factors such as emissions, ventilation and the oxidative environment and these are evolving over time, reflecting changes in chemical use, behaviour and building design/materials. The concentrations of VOCs in 25 UK homes of varying ages, design and occupancy were quantified using continuous indoor air sampling over five days. Air was collected through low flow (1 mL min-1) constant flow restrictors into evacuated 6 L internally silica-treated canisters until the canisters reached atmospheric pressure. This was followed by thermal desorption-gas chromatography and high mass accuracy time-of-flight mass spectrometry (TD-GC-TOF/MS). A fully quantitative analysis was performed on the eight most abundant hydrocarbon-based VOCs found. Despite differences in building characteristics and occupant numbers 94% of the homes had d-limonene or α-pinene as the most abundant VOCs. The variability seen across the 25 homes in concentrations of monoterpenes indoors was considerably greater than that of species such as isoprene, benzene, toluene and xylenes. The variance in VOCs indoors appeared to be strongly influenced by occupant activities such as cleaning with 5-day average concentrations of d-limonene ranging from 18 μg m-3 to over 1400 μg m-3, a peak domestic value that is possibly the highest yet reported in the literature

Linking e-health records, patient-reported symptoms and environmental exposure data to characterise and model COPD exacerbations: protocol for the COPE study.

INTRODUCTION: Relationships between exacerbations of chronic obstructive pulmonary disease (COPD) and environmental factors such as temperature, humidity and air pollution are not well characterised, due in part to oversimplification in the assignment of exposure estimates to individuals and populations. New developments in miniature environmental sensors mean that patients can now carry a personal air quality monitor for long periods of time as they go about their daily lives. This creates the potential for capturing a direct link between individual activities, environmental exposures and the health of patients with COPD. Direct associations then have the potential to be scaled up to population levels and tested using advanced human exposure models linked to electronic health records. METHODS AND ANALYSIS: This study has 5 stages: (1) development and deployment of personal air monitors; (2) recruitment and monitoring of a cohort of 160 patients with COPD for up to 6 months with recruitment of participants through the Clinical Practice Research Datalink (CPRD); (3) statistical associations between personal exposure with COPD-related health outcomes; (4) validation of a time-activity exposure model and (5) development of a COPD prediction model for London. ETHICS AND DISSEMINATION: The Research Ethics Committee for Camden and Islington has provided ethical approval for the conduct of the study. Approval has also been granted by National Health Service (NHS) Research and Development and the Independent Scientific Advisory Committee. The results of the study will be disseminated through appropriate conference presentations and peer-reviewed journals.This work is funded by the Medical Research Council (MR/L019744/1). MRC-PHE funding has been obtained for a pilot study to collect blood and sputum samples on a subset of 20 participants. Enrolment will take place at The Royal Brompton and Harefield (RBH) and Guy's and St Thomas' (GSTT) NHS Foundation Trusts. Support will be provided by the Respiratory Clinical Research Facility at RBH and the Lane Fox Unit at GSTT. The project is a portfolio adopted by the National Institute for Health Research (NIHR) UK Clinical Research Network (CRN). Additional support was provided by the NIHR Biomedical Research Centre based at GSTT and King's College London.This is the final version of the article. It first appeared from the BMJ Publishing Group via http://dx.doi.org/10.1136/bmjopen-2016-01133

Methods to estimate acclimatization to urban heat island effects on heat- and cold-related mortality

Background: Investigators have examined whether heat mortality risk is increased in neighborhoods subject to the urban heat island (UHI) effect but have not identified degrees of difference in susceptibility to heat and cold between cool and hot areas, which we call acclimatization to the UHI. Objectives: We developed methods to examine and quantify the degree of acclimatization to heat- and cold-related mortality in relation to UHI anomalies and applied these methods to London, UK. Methods: Case–crossover analyses were undertaken on 1993–2006 mortality data from London UHI decile groups defined by anomalies from the London average of modeled air temperature at a 1-km grid resolution. We estimated how UHI anomalies modified excess mortality on cold and hot days for London overall and displaced a fixed-shape temperature-mortality function (“shifted spline” model). We also compared the observed associations with those expected under no or full acclimatization to the UHI. Results: The relative risk of death on hot versus normal days differed very little across UHI decile groups. A 1°C UHI anomaly multiplied the risk of heat death by 1.004 (95% CI: 0.950, 1.061) (interaction rate ratio) compared with the expected value of 1.070 (1.057, 1.082) if there were no acclimatization. The corresponding UHI interaction for cold was 1.020 (0.979, 1.063) versus 1.030 (1.026, 1.034) (actual versus expected under no acclimatization, respectively). Fitted splines for heat shifted little across UHI decile groups, again suggesting acclimatization. For cold, the splines shifted somewhat in the direction of no acclimatization, but did not exclude acclimatization. Conclusions: We have proposed two analytical methods for estimating the degree of acclimatization to the heat- and cold-related mortality burdens associated with UHIs. The results for London suggest relatively complete acclimatization to the UHI effect on summer heat–related mortality, but less clear evidence for cold–related mortality

Measurement error in a multi-level analysis of air pollution and health: a simulation study.

BACKGROUND: Spatio-temporal models are increasingly being used to predict exposure to ambient outdoor air pollution at high spatial resolution for inclusion in epidemiological analyses of air pollution and health. Measurement error in these predictions can nevertheless have impacts on health effect estimation. Using statistical simulation we aim to investigate the effects of such error within a multi-level model analysis of long and short-term pollutant exposure and health. METHODS: Our study was based on a theoretical sample of 1000 geographical sites within Greater London. Simulations of "true" site-specific daily mean and 5-year mean NO2 and PM10 concentrations, incorporating both temporal variation and spatial covariance, were informed by an analysis of daily measurements over the period 2009-2013 from fixed location urban background monitors in the London area. In the context of a multi-level single-pollutant Poisson regression analysis of mortality, we investigated scenarios in which we specified: the Pearson correlation between modelled and "true" data and the ratio of their variances (model versus "true") and assumed these parameters were the same spatially and temporally. RESULTS: In general, health effect estimates associated with both long and short-term exposure were biased towards the null with the level of bias increasing to over 60% as the correlation coefficient decreased from 0.9 to 0.5 and the variance ratio increased from 0.5 to 2. However, for a combination of high correlation (0.9) and small variance ratio (0.5) non-trivial bias (> 25%) away from the null was observed. Standard errors of health effect estimates, though unaffected by changes in the correlation coefficient, appeared to be attenuated for variance ratios > 1 but inflated for variance ratios < 1. CONCLUSION: While our findings suggest that in most cases modelling errors result in attenuation of the effect estimate towards the null, in some situations a non-trivial bias away from the null may occur. The magnitude and direction of bias appears to depend on the relationship between modelled and "true" data in terms of their correlation and the ratio of their variances. These factors should be taken into account when assessing the validity of modelled air pollution predictions for use in complex epidemiological models