The association of positive psychological factors with work ability one year after myocardial infarction

Background Positive psychological factors like optimism, resilience and self-efficacy may facilitate successful adjustment after hospitalization for myocardial infarction (MI) and treatment with percutaneous coronary intervention (PCI), including return to work. Objective To examine whether positive psychological factors (optimism, resilience, and self-efficacy) predict work ability one year after PCI for MI. Methods Patients treated with PCI and with paid employment were included and completed questionnaires at 1 and 12 months post PCI discharge. Patients filled out the LOT-R optimism scale, the dispositional resilience scale (DRS-15), and the Cardiac Self-efficacy Scale (CSE) at 1-month, and the work ability index (WAI) at 1-year follow-up. Hierarchical linear regression models were used. Sensitivity analysis was performed for the acuteness of the PCI treatment. Results In total, 323 patients (14% women; mean age 59.5 ± 6.8y; 74% acute PCI) completed both surveys. At 1-year follow-up, resilience (β = 0.152, p = 0.009) and cardiac self-efficacy (β = 0.273, p < 0.001), but not optimism (β = 0.044, p = 0.432), were associated with work ability at 1 year, irrespective of cardiac history, or sex. Age (β = −0.158, p = 0.002) and comorbidity index (β = −0.104, p = 0.044) were significant covariates. Sensitivity analysis revealed that in patients receiving an elective Conclusion Resilience and cardiac self-efficacy were independently associated with work ability 1 year post PCI, whereas optimism was not. Identification and support of patients low in cardiac self-efficacy and resilience may contribute to improved restoration of work ability post PCI

Facial expressions of emotions during pharmacological and exercise stress testing:The role of myocardial ischemia and cardiac symptoms

Background  Negative emotions have been linked to ischemic heart disease, but existing research typically involves self-report methods and little is known about non-verbal facial emotion expression. The role of ischemia and anginal symptoms in emotion expression was examined.  Methods  Patients undergoing cardiac stress testing (CST) using bicycle exercise or adenosine with myocardial perfusion imaging were included (N = 256, mean age 66.8 +/- 8.7 year., 43% women). Video images and emotion expression (sadness, anxiety, anger, and happiness) were analyzed at baseline, initial CST , maximal CST, recovery. Nuclear images were evaluated using SPECT.  Results  Ischemia (N = 89; 35%) was associated with higher levels of sadness (p = .017, d = 0.34) and lower happiness (p = .015, d = 0.30). During recovery, patients with both ischemia and anginal symptoms had the highest sadness expression (F (3,254) = 3.67, p = .013, eta(2) = 0.042) and the lowest happiness expression (F (3, 254) = 4.19, p = .006, eta(2) = .048).  Conclusion  Sadness and reduced happiness were more common in patients with ischemia. Also, anginal symptoms were associated with more negative emotions

Assessment of needs, health-related quality of life, and satisfaction with care in breast cancer patients to better target supportive care

Background This study assessed whether breast cancer (BC) patients express similar levels of needs for equivalent severity of symptoms, functioning difficulties, or degrees of satisfaction with care aspects. BC patients who did (or not) report needs in spite of similar difficulties were identified among their sociodemographic or clinical characteristics. Patients and methods Three hundred and eighty-four (73% response rate) BC patients recruited in ambulatory or surgery hospital services completed the European Organisation for Research and Treatment of Cancer Quality of Life questionnaire (EORTC QLQ)-C30 quality of life [health-related quality of life (HRQOL)], the EORTC IN-PATSAT32 (in-patient) or OUT-PATSAT35 (out-patient) satisfaction with care, and the supportive care needs survey short form 34-item (SCNS-SF34) measures. Results HRQOL or satisfaction with care scale scores explained 41%, 45%, 40% and 22% of variance in, respectively, psychological, physical/daily living needs, information/health system, and care/support needs (P < 0.001). BC patients' education level, having children, hospital service attendance, and anxiety/depression levels significantly predicted differences in psychological needs relative to corresponding difficulties (adjusted R2 = 0.11). Medical history and anxiety/depression levels significantly predicted differences in information/health system needs relative to degrees of satisfaction with doctors, nurses, or radiotherapy technicians and general satisfaction (adjusted R2 = 0.12). Unmet needs were most prevalent in the psychological domains across hospital services. Conclusions Assessment of needs, HRQOL, and satisfaction with care highlights the subgroups of BC patients requiring better supportive care targetin

Researching the use of force: The background to the international project

This article provides the background to an international project on use of force by the police that was carried out in eight countries. Force is often considered to be the defining characteristic of policing and much research has been conducted on the determinants, prevalence and control of the use of force, particularly in the United States. However, little work has looked at police officers’ own views on the use of force, in particular the way in which they justify it. Using a hypothetical encounter developed for this project, researchers in each country conducted focus groups with police officers in which they were encouraged to talk about the use of force. The results show interesting similarities and differences across countries and demonstrate the value of using this kind of research focus and methodology

Angular redistribution of near-infrared emission from quantum dots in 3D photonic crystals

We study the angle-resolved spontaneous emission of near-infrared light sources in 3D photonic crystals over a wavelength range from 1200 to 1550 nm. To this end PbSe quantum dots are used as light sources inside titania inverse opal photonic crystals. Strong deviations from the Lambertian emission profile are observed. An attenuation of 60 % is observed in the angle dependent radiant flux emitted from the samples due to photonic stop bands. At angles that correspond to the edges of the stop band the emitted flux is increased by up to 34 %. This increase is explained by the redistribution of Bragg-diffracted light over the available escape angles. The results are quantitatively explained by an expanded escape-function model. This model is based on diffusion theory and adapted to photonic crystals using band structure calculations. Our results are the first angular redistributions and escape functions measured at near-infrared, including telecom, wavelengths. In addition, this is the first time for this model to be applied to describe emission from samples that are optically thick for the excitation light and relatively thin for the photoluminesence light.Comment: 24 pages, 8 figures (current format = single column, double spaced

The Utilization of Data Analysis Techniques in Predicting Student Performance in Massive Open Online Courses (MOOCs)

The growth of the Internet has enabled the popularity of open online learning platforms to increase over the years. This has led to the inception of Massive Open Online Courses (MOOCs) that enrol, millions of people, from all over the world. Such courses operate under the concept of open learning, where content does not have to be delivered via standard mechanisms that institutions employ, such as physically attending lectures. Instead learning occurs online via recorded lecture material and online tasks. This shift has allowed more people to gain access to education, regardless of their learning background. However, despite these advancements in delivering education, completion rates for MOOCs are low. In order to investigate this issue, the paper explores the impact that technology has on open learning and identifies how data about student performance can be captured to predict trend so that at risk students can be identified before they drop-out. In achieving this, subjects surrounding student engagement and performance in MOOCs and data analysis techniques are explored to investigate how technology can be used to address this issue. The paper is then concluded with our approach of predicting behaviour and a case study of the eRegister system, which has been developed to capture and analyse data. Keywords: Open Learning; Prediction; Data Mining; Educational Systems; Massive Open Online Course; Data Analysi