Approximately 69 million people worldwide are annually affected by traumatic brain injury (TBI). In Malaysia, the traumatic injury was the leading cause of hospital admission and death, accounting for one in three emergency visits. Among the most recognised complication of TBI is post-traumatic epilepsy (PTE), which is an essential contributor to morbidity and mortality. However, there is a lack of local epidemiological data on PTE in Malaysia. This study aims to describe the incidence and predictors of PTE among TBI patients admitted to a tertiary healthcare centre in Kuala Lumpur, Malaysia. We hypothesised that increases in age, race, and severity of brain injury are among the main potential predictors of PTE. It will also provide evidence that patients with epilepsy following TBI are associated with significant impairment in cognitive performance than TBI patients without epilepsy. An analysis of a two years retrospective cohort will be employed, of which adults with a history of admission for TBI in 2019 and 2020 will be contacted, and the development of epilepsy will be ascertained using a validated tool and confirmed by our neurologists during visits. The patients will then be grouped into two, with PTE and without PTE, and assessed their cognitive performance by clinical psychologists. Given that the management of TBI and PTE patients involves a multidisciplinary team, the findings might be significant to many healthcare providers in determining policy and strategise a better treatment.
The COVID-19 pandemic has brought substantial attention to the systems used to communicate biomedical research. In particular, the need to rapidly and credibly communicate research findings has led many stakeholders to encourage researchers to adopt open science practices such as posting preprints and sharing data. To examine the degree to which this has led to the adoption of such practices, we examined the “openness” of a sample of 539 published papers describing the results of randomized controlled trials testing interventions to prevent or treat COVID-19. The majority (56%) of the papers in this sample were free to read at the time of our investigation and 23.56% were preceded by preprints. However, there is no guarantee that the papers without an open license will be available without a subscription in the future, and only 49.61% of the preprints we identified were linked to the subsequent peer-reviewed version. Of the 331 papers in our sample with statements identifying if (and how) related datasets were available, only a paucity indicated that data was available in a repository that facilitates rapid verification and reuse. Our results demonstrate that, while progress has been made, there is still a significant mismatch between aspiration and the practice of open science in an important area of the COVID-19 literature.
Sadism represents a predisposition towards enjoying the suffering that we cause others. However, this conceptualization of Sadism closely abuts that of schadenfreude—the tendency to find pleasure in others’ suffering. The relationship between trait Sadism and trait schadenfreude has gone understudied. Using latent construct modeling with a cross-sectional and diverse sample of 322 undergraduate participants, we found that the bi-factor model of Sadism and schadenfreude that best fit the data articulated Sadism as a sub-facet of schadenfreude. Sadism was more strongly related to physical aggressiveness, anger, and antagonism than schadenfreude, suggesting a distinct nomological profile. Future research should seek to identify the mechanisms that translate a passive, schadenfreudic disposition into actual acts of Sadistic aggression.
Humans are influenced by the presence of other social agents, sometimes performing better, sometimes performing worse than alone. Humans are also affected by how they perceive the social agent. The present study investigat-ed whether individual differences in the attitude toward robots can predict human behavior in Human-Robot Interaction (HRI). Therefore, adult partic-ipants played a game with the Cozmo robot (Anki Inc., San Francisco), in which their task was to stop a balloon from exploding. In individual trials, only the participants could stop the balloon inflating, while in joint trials al-so Cozmo could stop it. Results showed that in joint trials, the balloon ex-ploded less often than in individual trials. However participants stopped the balloon earlier in joint than in individual trials, although this was less bene-ficial for them. This effect of Cozmo joining the game, nevertheless, was in-fluenced by the negative attitude of the participants toward robots. The more negative they were, the less their behavior was influenced by the presence of the robot. This suggests that robots can influence human behavior, although this influence is modulated by the attitude toward the robot.
Successful emotion regulation is essential for promoting psychological and physical health (DeSteno et al., 2013; Sheppes et al., 2015). However, people often experience difficulties regulating their emotions. Even with optimal self-regulation capacity, people have problems managing their feelings when fatigued or stressed (Grillon et al., 2015; Raio et al., 2013). Therefore, it is essential to find ways to make self-regulation less difficult. Placebo effects, which are brain-body responses to an inert treatment and the psychosocial context in which it is delivered (Ashar et al., 2017), offer an avenue to address these issues since they may regulate emotions automatically (Braunstein et al., 2017). In this review, we focus on placebo effects that use a placebo object or procedure to regulate emotions. This chapter has four goals. First, we discuss placebo effects and their mechanisms. Second, we review evidence of placebos regulating emotions. Third, we discuss the ethical dilemma in using placebos to regulate emotions and highlight work on placebos without deception. Lastly, we discuss basic science and translational application questions and suggest directions for future research.
Background Social isolation is strongly associated with poor mental health. The COVID-19 pandemic and ensuing social restrictions disrupted young people’s social interactions and resulted in several periods during which school closures necessitated online learning. We hypothesise that digitally excluded young people would demonstrate greater deterioration in their mental health than their digitally connected peers during this time. Methods We analysed representative mental health data from a sample of UK 10–15-year-olds (N = 1387); Understanding Society collected the Strengths and Difficulties Questionnaire in 2017-19 and thrice during the pandemic (July 2020, November 2020 and March 2021). We employed cross-sectional methods and longitudinal latent growth curve modelling to describe trajectories of adolescent mental health for participants with and without access to a computer or a good internet connection for schoolwork. Outcomes Adolescent mental health had a quadratic trajectory during the COVID-19 pandemic, with the highest mean Total Difficulties score around December 2020. The worsening and recovery of mental health during the pandemic was greatly pronounced among those without access to a computer, although we did not find evidence for a similar effect among those without a good internet connection. Interpretation Digital exclusion, as indicated by lack of access to a computer, is a tractable risk factor that likely compounds other adversities facing children and young people during periods of social isolation. Funding British Psychological Society; School of the Biological Sciences, University of Cambridge; NIHR Applied Research Centre; Medical Research Council; Economic and Social Research Council; and Emmanuel College, University of Cambridge. Competing Interest Statement The authors have declared no competing interest. Funding Statement This study was funded by the British Psychological Society; the School of the Biological Sciences, University of Cambridge; the NIHR Applied Research Centre; the Medical Research Council; the Economic and Social Research Council; and Emmanuel College, University of Cambridge.