Intertemporal choice involves deciding between smaller, sooner and larger, later rewards. People tend to prefer smaller rewards that are available earlier to larger rewards available later, a phenomenon referred to as temporal or delay discounting. Despite its ubiquity in human and non-human animals, temporal discounting is subject to considerable individual differences. Here, we provide a critical narrative review of this literature and make suggestions for future work. We conclude that temporal discounting is associated with key socio-economic and health-related variables. Regarding personality, large-scale studies have found steeper temporal discounting to be associated with higher levels of self-reported impulsivity and extraversion; however, effect sizes are small. Temporal discounting correlates negatively with future-oriented cognitive styles and inhibitory control, again with small effect sizes. There are consistent associations between steeper temporal discounting and lower intelligence, with effect sizes exceeding those of personality or cognitive variables, although socio-demographic moderator variables may play a role. Neuroimaging evidence of brain structural and functional correlates is not yet consistent, neither with regards to areas nor directions of effects. Finally, following early candidate gene studies, recent GWAS approaches have revealed the molecular genetic architecture of temporal discounting to be more complex than initially thought. Overall, the study of individual differences in temporal discounting is a maturing field that has produced some replicable findings. Effect sizes are small-to-medium, necessitating future hypothesis-driven work that prioritizes large samples with adequate power calculations. More research is also needed regarding the neural origins of individual differences in temporal discounting as well as the mediating neural mechanisms of associations of temporal discounting with personality and cognitive variables.

BACKGROUND: Reliable information on the incidence of induced abortion in India is lacking. Official statistics and national surveys provide incomplete coverage. Since the early 2000s, medication abortion has become increasingly available, improving the way women obtain abortions. The aim of this study was to estimate the national incidence of abortion and unintended pregnancy for 2015. METHODS: National abortion incidence was estimated through three separate components: abortions (medication and surgical) in facilities (including private sector, public sector, and non-governmental organisations [NGOs]); medication abortions outside facilities; and abortions outside of facilities and with methods other than medication abortion. Facility-based abortions were estimated from the 2015 Health Facilities Survey of 4001 public and private health facilities in six Indian states (Assam, Bihar, Gujarat, Madhya Pradesh, Tamil Nadu, and Uttar Pradesh) and from NGO clinic data. National medication abortion drug sales and distribution data were obtained from IMS Health and six principal NGOs (DKT International, Marie Stopes International, Population Services International, World Health Partners, Parivar Seva Santha, and Janani). We estimated the total number of abortions that are not medication abortions and are not obtained in a health facility setting through an indirect technique based on findings from community-based study findings in two states in 2009, with adjustments to account for the rapid increase in use of medication abortion since 2009. The total number of women of reproductive age and livebirth data were obtained from UN population data, and the proportion of births from unplanned pregnancies and data on contraceptive use and need were obtained from the 2015-16 National Family Health Survey-4. FINDINGS: We estimate that 15·6 million abortions (14·1 million-17·3 million) occurred in India in 2015. The abortion rate was 47·0 abortions (42·2-52·1) per 1000 women aged 15-49 years. 3·4 million abortions (22%) were obtained in health facilities, 11·5 million (73%) abortions were medication abortions done outside of health facilities, and 0·8 million (5%) abortions were done outside of health facilities using methods other than medication abortion. Overall, 12·7 million (81%) abortions were medication abortions, 2·2 million (14%) abortions were surgical, and 0·8 million (5%) abortions were done through other methods that were probably unsafe. We estimated 48·1 million pregnancies, a rate of 144·7 pregnancies per 1000 women aged 15-49 years, and a rate of 70·1 unintended pregnancies per 1000 women aged 15-49 years. Abortions accounted for one third of all pregnancies, and nearly half of pregnancies were unintended. INTERPRETATION: Health facilities can have a greater role in abortion service provision and provide quality care, including post-abortion contraception. Interventions are needed to expand access to abortion services through better equipping existing facilities, ensuring adequate and continuous supplies of medication abortion drugs, and by increasing the number of trained providers. In view of how many women rely on self-administration of medication abortion drugs, interventions are needed to provide women with accurate information on these drugs and follow-up care when needed. Research is needed to test interventions that improve knowledge and practice in providing medication abortion, and the Indian Government at the national and state level needs to prioritise improving policies and practice to increase access to comprehensive abortion care and quality contraceptive services that prevent unintended pregnancy. FUNDING: Government of UK Department for International Development (until 2015), the David and Lucile Packard Foundation, the John D. and Catherine T. MacArthur Foundation, and the Ford Foundation.

Unintended pregnancy accounts for more than 40% of the total pregnancies worldwide. An Unintended pregnancy can have serious implications on women and their families. With more than one-fourth of the children in India born out of unintended pregnancies such pregnancies are considered to be one of the major public health concerns today. The present study is aimed at determining major predictors of unintended pregnancy among currently pregnant ever-married women in India. The present study has used National Family Health Survey (NFHS) data, conducted by the International Institute for Population Sciences (IIPS), Mumbai, to show the trend, pattern and determinants of mistimed and unwanted pregnancies. Bivariate and multinomial logistic regression model have been used with the help of Stata 13 software. The results show that the likelihood of a mistimed pregnancy is more prevalent among young women whereas the prevalence of unwanted pregnancy is observed more among the women aged 35 years or more. The results also show that the risk of experiencing mistimed pregnancy decreases if the woman belongs to 'other' castes and has higher education. The likelihood of unwanted pregnancy decreases among married women aged 18 years and above, those women having higher education, some autonomy and access to any mode of mass communication. Knowledge of these predictors of mistimed and unwanted pregnancy will be helpful in identifying the most vulnerable group and prioritize the intervention strategies of the reproductive health programmes for the population in need.

BACKGROUND: In India, malaria is not uniformly distributed. Chhattisgarh is a highly malarious state where both Plasmodium falciparum and Plasmodium vivax are prevalent with a preponderance of P. falciparum. Malaria in pregnancy (MIP), especially when caused by P. falciparum, poses substantial risk to the mother and foetus by increasing the risk of foetal death, prematurity, low birth weight (LBW), and maternal anaemia. These risks vary between areas with stable and unstable transmission. The specific objectives of this study were to determine the prevalence of malaria, its association with maternal and birth outcomes, and use of anti-malarial preventive measures for development of evidence based interventions to reduce the burden of MIP. METHODS: A cross-sectional study of pregnant women presenting to antenatal clinics (ANC) or delivery units (DU), or hospitalized for non-obstetric illness was conducted over 12 months in high (Bastar) and low (Rajnandgaon) transmission districts in Chhattisgarh state. Intensity of transmission was defined on the basis of slide positivity rates with a high proportion due to P. falciparum. In each district, a rural and an urban health facility was selected. RESULTS: Prevalence of peripheral parasitaemia was low: 1.3% (35/2696) among women at ANCs and 1.9% at DUs (19/1025). Peripheral parasitaemia was significantly more common in Bastar (2.8%) than in Rajnandgaon (0.1%) (p < 0.0001). On multivariate analysis of ANC participants, residence in Bastar district (stable malaria transmission) was strongly associated with peripheral parasitaemia (adjusted OR [aOR] 43.4; 95% CI, 5.6-335.2). Additional covariates associated with parasitaemia were moderate anaemia (aOR 3.7; 95% CI 1.8-7.7), fever within the past week (aOR 3.2; 95% CI 1.2-8.6), and lack of formal education (aOR 4.6; 95% CI 2.0-10.7). Similarly, analysis of DU participants revealed that moderate anaemia (aOR 2.5; 95% CI 1.1-5.4) and fever within the past week (aOR 5.8; 95% CI 2.4-13.9) were strongly associated with peripheral and/or placental parasitaemia. Malaria-related admissions were more frequent among pregnant women in Bastar, the district with greater malaria prevalence (51% vs. 11%, p < 0.0001). CONCLUSIONS: Given the overall low prevalence of malaria, a strategy of enhanced anti-vector measures coupled with intermittent screening and targeted treatment during pregnancy should be considered for preventing malaria-associated morbidity in central India.

Up to a third of patients undergoing coronary angiography for angina-like chest pain are found to have normal coronary arteries and a substantial proportion of these individuals continue to consult and even attend emergency departments. Initially, these patients are usually seen by cardiologists but with accumulating evidence that the pain might have a gastrointestinal origin, it may be more appropriate for them to be cared for by the gastroenterologist once a cardiological cause has been excluded. This review covers the assessment and management of this challenging condition, which includes a combination of education, reassurance, and pharmacotherapy. For the more refractory cases, behavioral treatments, such as cognitive behavioral therapy or hypnotherapy, may have to be considered.

Using daily ownership data, this study documents median participation rates for retail and institutional shareholders in rights offers in Australia of 60% and 94%, respectively. At the median, the rights issue results in 0.25% (1.34%) of the value of firm market capitalization (offer size) being transferred from retail shareholders to institutional shareholders. Retail shareholder participation is higher in renounceable offers, offers with larger discount and those made by firms with larger market capitalization and lower risk. Companies with above median retail participation rates perform better in the long run. The results suggest that, on average, retail shareholders make rational participation decisions in rights offerings.

In traditional Reinforcement Learning (RL), agents learn to optimize actions in a dynamic context based on recursive estimation of expected values. We show that this form of machine learning fails when rewards (returns) are affected by tail risk, i.e., leptokurtosis. Here, we adapt a recent extension of RL, called distributional RL (disRL), and introduce estimation efficiency, while properly adjusting for differential impact of outliers on the two terms of the RL prediction error in the updating equations. We show that the resulting “efficient distributional RL” (e-disRL) learns much faster, and is robust once it settles on a policy. Our paper also provides a brief, nontechnical overview of machine learning, focusing on RL.

Our preferences are influenced by the opinions of others. The past human neuroimaging studies on social conformity have identified a network of brain regions related to social conformity that includes the posterior medial frontal cortex (pMFC), anterior insula, and striatum. Since these brain regions are also known to play important roles in reinforcement learning (i.e., processing prediction error), it was previously hypothesized that social conformity and reinforcement learning have a common neural mechanism. However, although this view is currently widely accepted, these two processes have never been directly compared; therefore, the extent to which they shared a common neural mechanism had remained unclear. This study aimed to formally test the hypothesis. The same group of participants (n = 25) performed social conformity and reinforcement learning tasks inside a functional magnetic resonance imaging (fMRI) scanner. Univariate fMRI data analyses revealed activation overlaps in the pMFC and bilateral insula between social conflict and unsigned prediction error and in the striatum between social conflict and signed prediction error. We further conducted multivoxel pattern analysis (MVPA) for more direct evidence of a shared neural mechanism. MVPA did not reveal any evidence to support the hypothesis in any of these regions but found that activation patterns between social conflict and prediction error in these regions were largely distinct. Taken together, the present study provides no clear evidence of a common neural mechanism between social conformity and reinforcement learning.

How natural selection can promote cooperative or altruistic behavior is a fundamental question in biological and social sciences. One of the persuasive mechanisms is "indirect reciprocity," working through reputation: cooperative behavior can prevail because the behavior builds the donor's good reputation and then s/he receives some reciprocal benefits from someone else in the community. However, an important piece missed in the previous studies is that the reputation-building process requires substantial cognitive abilities such as communication skills, potentially causing a loss of biological fitness. Here, by mathematical analyses and individual-based computer simulations, we show that natural selection never favors indirect reciprocal cooperation in the presence of the cost of reputation building, regardless of the cost-to-benefit ratio of cooperation or moral assessment rules (social norms). Our results highlight the importance of considering the cost of high-level cognitive abilities in studies of the evolution of humans' and animals' social behavior.

Free will is widely considered a foundational component of Western moral and legal codes, and yet current conceptions of free will are widely thought to fit uncomfortably with much research in psychology and neuroscience. Recent research investigating the consequences of laypeople’s free will beliefs (FWBs) for everyday moral behavior suggests that stronger FWBs are associated with various desirable moral characteristics (e.g., greater helpfulness, less dishonesty). These findings have sparked concern regarding the potential for moral degeneration throughout society as science promotes a view of human behavior that is widely perceived to undermine the notion of free will. We report four studies (combined N = 921) originally concerned with possible mediators and/or moderators of the abovementioned associations. Unexpectedly, we found no association between FWBs and moral behavior. Our findings suggest that the FWB–moral behavior association (and accompanying concerns regarding decreases in FWBs causing moral degeneration) may be overstated.

For making decisions in everyday life we often have first to infer the set of environmental features that are relevant for the current task. Here we investigated the computational mechanisms underlying the evolution of beliefs about the relevance of environmental features in a dynamical and noisy environment. For this purpose we designed a probabilistic Wisconsin card sorting task (WCST) with belief solicitation, in which subjects were presented with stimuli composed of multiple visual features. At each moment in time a particular feature was relevant for obtaining reward, and participants had to infer which feature was relevant and report their beliefs accordingly. To test the hypothesis that attentional focus modulates the belief update process, we derived and fitted several probabilistic and non-probabilistic behavioral models, which either incorporate a dynamical model of attentional focus, in the form of a hierarchical winner-take-all neuronal network, or a diffusive model, without attention-like features. We used Bayesian model selection to identify the most likely generative model of subjects' behavior and found that attention-like features in the behavioral model are essential for explaining subjects' responses. Furthermore, we demonstrate a method for integrating both connectionist and Bayesian models of decision making within a single framework that allowed us to infer hidden belief processes of human subjects.