Why do we like the music we do? Research has shown that musical preferences and personality are linked, yet little is known about other influences on preferences such as cognitive styles. To address this gap, we investigated how individual differences in musical preferences are explained by the empathizing-systemizing (E-S) theory. Study 1 examined the links between empathy and musical preferences across four samples. By reporting their preferential reactions to musical stimuli, samples 1 and 2 (Ns = 2,178 and 891) indicated their preferences for music from 26 different genres, and samples 3 and 4 (Ns = 747 and 320) indicated their preferences for music from only a single genre (rock or jazz). Results across samples showed that empathy levels are linked to preferences even within genres and account for significant proportions of variance in preferences over and above personality traits for various music-preference dimensions. Study 2 (N = 353) replicated and extended these findings by investigating how musical preferences are differentiated by E-S cognitive styles (i.e., ‘brain types’). Those who are type E (bias towards empathizing) preferred music on the Mellow dimension (R&B/soul, adult contemporary, soft rock genres) compared to type S (bias towards systemizing) who preferred music on the Intense dimension (punk, heavy metal, and hard rock). Analyses of fine-grained psychological and sonic attributes in the music revealed that type E individuals preferred music that featured low arousal (gentle, warm, and sensual attributes), negative valence (depressing and sad), and emotional depth (poetic, relaxing, and thoughtful), while type S preferred music that featured high arousal (strong, tense, and thrilling), and aspects of positive valence (animated) and cerebral depth (complexity). The application of these findings for clinicians, interventions, and those on the autism spectrum (largely type S or extreme type S) are discussed.
Altmetric measurements derived from the social web are increasingly advocated and used as early indicators of article impact and usefulness. Nevertheless, there is a lack of systematic scientific evidence that altmetrics are valid proxies of either impact or utility although a few case studies have reported medium correlations between specific altmetrics and citation rates for individual journals or fields. To fill this gap, this study compares 11 altmetrics with Web of Science citations for 76 to 208,739 PubMed articles with at least one altmetric mention in each case and up to 1,891 journals per metric. It also introduces a simple sign test to overcome biases caused by different citation and usage windows. Statistically significant associations were found between higher metric scores and higher citations for articles with positive altmetric scores in all cases with sufficient evidence (Twitter, Facebook wall posts, research highlights, blogs, mainstream media and forums) except perhaps for Google+ posts. Evidence was insufficient for LinkedIn, Pinterest, question and answer sites, and Reddit, and no conclusions should be drawn about articles with zero altmetric scores or the strength of any correlation between altmetrics and citations. Nevertheless, comparisons between citations and metric values for articles published at different times, even within the same year, can remove or reverse this association and so publishers and scientometricians should consider the effect of time when using altmetrics to rank articles. Finally, the coverage of all the altmetrics except for Twitter seems to be low and so it is not clear if they are prevalent enough to be useful in practice.
Male mate choice might be based on both absolute and relative strategies. Cues of female attractiveness are thus likely to reflect both fitness and reproductive potential, as well as compatibility with particular male phenotypes. In humans, absolute clues of fertility and indices of favorable developmental stability are generally associated with increased women’s attractiveness. However, why men exhibit variable preferences remains less studied. Male mate choice might be influenced by uncertainty of paternity, a selective factor in species where the survival of the offspring depends on postnatal paternal care. For instance, in humans, a man might prefer a woman with recessive traits, thereby increasing the probability that his paternal traits will be visible in the child and ensuring paternity. Alternatively, attractiveness is hypothesized to be driven by self-resembling features (homogamy), which would reduce outbreeding depression. These hypotheses have been simultaneously evaluated for various facial traits using both real and artificial facial stimuli. The predicted preferences were then compared to realized mate choices using facial pictures from couples with at least 1 child. No evidence was found to support the paternity uncertainty hypothesis, as recessive features were not preferred by male raters. Conversely, preferences for self-resembling mates were found for several facial traits (hair and eye color, chin dimple, and thickness of lips and eyebrows). Moreover, realized homogamy for facial traits was also found in a sample of long-term mates. The advantages of homogamy in evolutionary terms are discussed.
Using clinical indicators to facilitate quality improvement via the accreditation process: an adaptive study into the control relationship
- International journal for quality in health care : journal of the International Society for Quality in Health Care / ISQua
- Published over 5 years ago
OBJECTIVE: /st>The aim of the study was to determine accreditation surveyors' and hospitals' use and perceived usefulness of clinical indicator reports and the potential to establish the control relationship between the accreditation and reporting systems. The control relationship refers to instructional directives, arising from appropriately designed methods and efforts towards using clinical indicators, which provide a directed moderating, balancing and best outcome for the connected systems. DESIGN: /st>Web-based questionnaire survey. SETTING: /st>Australian Council on Healthcare Standards' (ACHS) accreditation and clinical indicator programmes. RESULTS: /st>Seventy-three of 306 surveyors responded. Half used the reports always/most of the time. Five key messages were revealed: (i) report use was related to availability before on-site investigation; (ii) report use was associated with the use of non-ACHS reports; (iii) a clinical indicator set’s perceived usefulness was associated with its reporting volume across hospitals; (iv) simpler measures and visual summaries in reports were rated the most useful; (v) reports were deemed to be suitable for the quality and safety objectives of the key groups of interested parties (hospitals' senior executive and management officers, clinicians, quality managers and surveyors). CONCLUSIONS: /st>Implementing the control relationship between the reporting and accreditation systems is a promising expectation. Redesigning processes to ensure reports are available in pre-survey packages and refined education of surveyors and hospitals on how to better utilize the reports will support the relationship. Additional studies on the systems' theory-based model of the accreditation and reporting system are warranted to establish the control relationship, building integrated system-wide relationships with sustainable and improved outcomes.
Purpose . To explore the sentiment and themes of Twitter chatter that mentions both alcohol and marijuana. Design . Cross-sectional analysis of tweets mentioning both alcohol and marijuana during 1 month was performed. Setting . The study setting was Twitter. Participants . Tweets sent from February 4 to March 5, 2014, were studied. Method . A random sample (n = 5000) of tweets that mentioned alcohol and marijuana were qualitatively coded as normalizing both substances, preferring one substance over the other, or discouraging both substances. Other common themes were identified. Results . More than half (54%) of the tweets normalized marijuana and alcohol (without preferring one substance over the other), and 24% preferred marijuana over alcohol. Only 2% expressed a preference for alcohol over marijuana, 7% discouraged the use of both substances, and the sentiment was unknown for 13% of the tweets. Common themes among tweets that normalized both substances included using the substances with friends (17%) and mentioning substance use in the context of sex or romance (14%). Common themes among tweets that preferred marijuana over alcohol were the beliefs that marijuana is safer than alcohol (46%) and preferences for effects of marijuana over alcohol (40%). Conclusion . Tweets normalizing polysubstance use or encouraging marijuana use over alcohol use are common. Both online and offline prevention efforts are needed to increase awareness of the risks associated with polysubstance use and marijuana use.
- Proceedings of the National Academy of Sciences of the United States of America
- Published over 4 years ago
Risk taking is central to human activity. Consequently, it lies at the focal point of behavioral sciences such as neuroscience, economics, and finance. Many influential models from these sciences assume that financial risk preferences form a stable trait. Is this assumption justified and, if not, what causes the appetite for risk to fluctuate? We have previously found that traders experience a sustained increase in the stress hormone cortisol when the amount of uncertainty, in the form of market volatility, increases. Here we ask whether these elevated cortisol levels shift risk preferences. Using a double-blind, placebo-controlled, cross-over protocol we raised cortisol levels in volunteers over 8 d to the same extent previously observed in traders. We then tested for the utility and probability weighting functions underlying their risk taking and found that participants became more risk-averse. We also observed that the weighting of probabilities became more distorted among men relative to women. These results suggest that risk preferences are highly dynamic. Specifically, the stress response calibrates risk taking to our circumstances, reducing it in times of prolonged uncertainty, such as a financial crisis. Physiology-induced shifts in risk preferences may thus be an underappreciated cause of market instability.
We show here that computer game players can build high-quality crystal structures. Introduction of a new feature into the computer game Foldit allows players to build and real-space refine structures into electron density maps. To assess the usefulness of this feature, we held a crystallographic model-building competition between trained crystallographers, undergraduate students, Foldit players and automatic model-building algorithms. After removal of disordered residues, a team of Foldit players achieved the most accurate structure. Analysing the target protein of the competition, YPL067C, uncovered a new family of histidine triad proteins apparently involved in the prevention of amyloid toxicity. From this study, we conclude that crystallographers can utilize crowdsourcing to interpret electron density information and to produce structure solutions of the highest quality.
Pair formation, acquiring a mate to form a reproductive unit, is a complex process. Mating preferences are a step in this process. However, due to constraining factors such as availability of mates, rival competition, and mutual mate choice, preferred characteristics may not be realised in the actual partner. People value height in their partner and we investigated to what extent preferences for height are realised in actual couples. We used data from the Millennium Cohort Study (UK) and compared the distribution of height difference in actual couples to simulations of random mating to test how established mate preferences map on to actual mating patterns. In line with mate preferences, we found evidence for: (i) assortative mating (r = .18), (ii) the male-taller norm, and, for the first time, (iii) for the male-not-too-tall norm. Couples where the male partner was shorter, or over 25 cm taller than the female partner, occurred at lower frequency in actual couples than expected by chance, but the magnitude of these effects was modest. We also investigated another preference rule, namely that short women (and tall men) prefer large height differences with their partner, whereas tall women (and short men) prefer small height differences. These patterns were also observed in our population, although the strengths of these associations were weaker than previously reported strength of preferences. We conclude that while preferences for partner height generally translate into actual pairing, they do so only modestly.
People prefer to move in ways that minimize their energetic cost [1-9]. For example, people tend to walk at a speed that minimizes energy use per unit distance [5-8] and, for that speed, they select a step frequency that makes walking less costly [3, 4, 6, 10-12]. Although aspects of this preference appear to be established over both evolutionary [9, 13-15] and developmental  timescales, it remains unclear whether people can also optimize energetic cost in real time. Here we show that during walking, people readily adapt established motor programs to minimize energy use. To accomplish this, we used robotic exoskeletons to shift people’s energetically optimal step frequency to frequencies higher and lower than normally preferred. In response, we found that subjects adapted their step frequency to converge on the new energetic optima within minutes and in response to relatively small savings in cost (<5%). When transiently perturbed from their new optimal gait, subjects relied on an updated prediction to rapidly re-converge within seconds. Our collective findings indicate that energetic cost is not just an outcome of movement, but also plays a central role in continuously shaping it.
Individuals change their behavior during an epidemic in response to whether they and/or those they interact with are healthy or sick. Healthy individuals may utilize protective measures to avoid contracting a disease. Sick individuals may utilize preemptive measures to avoid spreading a disease. Yet, in practice both protective and preemptive changes in behavior come with costs. This paper proposes a stochastic network disease game model that captures the self-interests of individuals during the spread of a susceptible-infected-susceptible disease. In this model, individuals strategically modify their behavior based on current disease conditions. These reactions influence disease spread. We show that there is a critical level of concern, i.e., empathy, by the sick individuals above which disease is eradicated rapidly. Furthermore, we find that risk averse behavior by the healthy individuals cannot eradicate the disease without the preemptive measures of the sick individuals. Empathy is more effective than risk-aversion because when infectious individuals change behavior, they reduce all of their potential infections, whereas when healthy individuals change behavior, they reduce only a small portion of potential infections. This imbalance in the role played by the response of the infected versus the susceptible individuals on disease eradication affords critical policy insights.