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Across the lifespan, individuals often face choices to stay with a familiar option or explore new alternatives. For example, do you go to your favourite café for lunch, or do you try out the new pizzeria that has opened across the road? Deciding whether to try a new option or stick with an option that is already known to you, known as the “explore/exploit” dilemma, is an important feature of cognition and is present across decision-making domains, including social interactions (Gabay et al., 2021, Soc Cog Affec Neurosci), economic decision-making (Addicott et al., 2017, Neuropsychopharmacology), and romantic partner selection (van de Wouw et al., 2022, Judgement and Decision-Making). Explore/exploit decision-making is worthy of investigation as a transdiagnostic target for depression, anxiety, and psychosis, as it relies on cognitive faculties implicated in the onset and maintenance of these disorders, such as motivational drives and executive functions (Addicott et al., 2017). In this project, we will synthesise evidence on explore/exploit decision-making as a potential transdiagnostic mechanism (Aylward et al., 2019, Nat Hum Behav) for anxiety, depression and psychosis.

Adolescence is a critical developmental period when most mental health problems start to emerge (Blakemore, 2019). Globally, around 14% of adolescents aged 10-19 experience mental health problems (WHO, 2021). The rate for diagnosis among US adolescents in 2016 for anxiety, depression, and ADHD were found to be 11%, 13%, and 13%, respectively (Ghandour et al., 2019; US Department of Health and Human Services, 2017). These prevalence rates are likely to be even higher in the future, as mental health problems among children and adolescents have been on the rise over past decades (Collishaw, 2014; Deighton et al., 2019). One factor closely associated with adolescent mental health is peer relationships (e.g. Bernasco et al., 2021; Snyder et al., 2004). Adolescence is a period during which relationships with peers become particularly salient and the importance of parents decreases (Andrews et al., 2020). Children increase the time spent with friends as they transition into adolescence (Perry, Kelder, & Komro, 1993), and peer support at this age is especially important (Cornwell, 2003). However, adolescents with mental health problems are more likely to have difficulties with friendships (Van Zalk et al., 2010). It is, therefore, important to examine how mental health problems and peer relationship quality reciprocally influence each other during adolescence, in order to better understand the transactional nature between mental health problems and social relationships.

During adolescence (ages 10-24; Sawyer et al., 2018), there are significant changes to the individual’s social and physical environment. This period has been associated with changes to social behaviour and peer associations as the individual becomes independent of caregivers (e.g. Blakemore & Mills, 2014; Ellis et al., 2012), but also coincides with lifestyle changes, such as educational milestones (Eccles et al., 1993). The ability to adapt to such changes is necessary to ensure these transitions are successful and experimental evidence has demonstrated that adolescents are adept at adjusting their behaviour to navigate changeable environments (Crone & Dahl, 2012). However, this adaptive ability is threatened (Browning et al., 2015) by the heightened risk for psychopathology that also comes with adolescence (Rapee et al., 2019). The present study aims to examine these harmful effects of anxiety on adolescents’ and adults’ adaptive abilities. This study’s results could have implications for interventions that aim to support adolescents during periods of transition. Previous research has demonstrated that adolescents can calibrate the degree to which they weigh recent information according to the structure of their environment (e.g. Eckstein et al., 2020; Davidow et al., 2016). However, to our knowledge, no studies to date have experimentally manipulated the stability/volatility of the task within a single study to test whether adolescents can adjust their behaviour to the structure of the environment. This is important as it has been suggested that developmental effects on learning can be explained by task differences, rather than age (Nussenbaum & Hartley, 2019). To examine this, the present study will compare adolescents’ and adults’ decision-making between stable and volatile environments to examine whether individuals in these age groups adjust their behaviour to the structure of their surroundings. As adults can successfully adjust the degree to which they weigh recent information between stable and volatile environments (Behrens et al., 2007) we propose that adolescents will show even greater adjustment compared to their older counterparts. However, the ability to adjust behaviour to one’s surroundings is disrupted by psychopathology, such as anxiety. Anxiety disorder can lead to poorer instrumental learning (Alvares et al., 2014) and a poorer ability for adults to adapt to stable and volatile environments (Browning et al., 2015). As such, we expect anxiety to disrupt decision making for both adolescents and adults. Examining anxiety in the context of adolescence is important to identify difficulties this age group may have in adjusting to novel environments after significant periods of transition, such as beginning a university programme.

When the first UK national lockdown was announced, large numbers of the population began purchasing non-perishable foods and hygiene items in quantities that exceeded their usual weekly shop. This so called ‘over-purchasing’ was featured in news outlets and led to total stockouts of items including canned food and toilet paper in several UK supermarkets. To understand the psychological characteristics that were associated with the tendency to panic buy, several studies have considered the psychological and demographic predictors of this behaviour (e.g., Bentall et al., 2021; Garbe et al., 2020). The former of these studies found that participants who reported having a higher income were more likely to engage in panic buying, as these individuals had greater means of stockpiling resources relative to members of the population with a lower income. Far from being an irrational strategy, for those with access to the means to hoard, this may be a rational behaviour to avoid resource scarcity and is observed in several animal species during periods of uncertainty (Anselme & Güntürkün, 2020; Dickins & Schalz, 2020). As the response of the virus has become increasingly protracted, the economic impacts of the pandemic have grown. Current estimates of the cost of the pandemic to the UK Government have been estimated at 317 billion pounds as of September 2020. In the private sector, this has led to the closing of a number of businesses either temporarily or permanently. As such, some members of the population have experienced a fall in income due to job loss or being placed on the Government’s furlough scheme. However, other groups in the population have experienced the opposite effect: with fewer leisure activities to spend their disposable income on, some individuals have reported increases in wealth due to the pandemic (Institute for Fiscal Studies, 2020). As income predicted over purchasing during the first wave of the pandemic, the current study will examine how changes to income during the COVID-19 pandemic affect this behaviour. Specifically, we will examine whether those who experience a reduction to their income report a decline in over-purchasing, and whether those who experience an increase in their income report an increase in over purchasing behaviour. We also examine whether psychological variables contribute to longitudinal changes in over purchasing behaviour.

Across animal species, an organism’s survival is dependent on its ability to adapt to the conditions of its environment (McNamara & Houston, 1985). However, not all organisms experience parity in the resources afforded to them in an environment; some may experience relative environmental stability where resources are guaranteed, whereas others may experience relative resource instability. Human beings are able to adapt their decision-making to suit environments of different qualities (Grove, 2009; Sutton & Barto, 2018) and it has been suggested that early experiences of stability or instability determine these decision-making strategies across the lifespan (Humphreys et al., 2015). Different decision-making trajectories resulting from early life experiences have been used to explain why some individuals engage in potentially harmful risk-taking behaviours, such as substance misuse or risky sexual practices, whilst others abstain from these behaviours (Ellis et al., 2012). The present study will examine whether early life stress determines decision-making strategies, and whether these correspond to real-world risk-taking behaviours. Early instability can be the result of a range of life events that create extreme stress for the individual. Adverse Childhood Experiences (ACEs) are events that are chronic stressors experienced by the individual during their early development (Danese & McEwen, 2012). These events can be categorized into two broad groups: maltreatment, which refers to events that are directly experienced by the individual (e.g. physical abuse), or household adversity, which refers to circumstances in the individuals’ environment that can cause chronic stress (e.g. parental divorce; Hughes et al., 2017). It is estimated that up to 47% of individuals have experienced at least one ACE in the UK while 9% have experienced four or more (Bellis et al., 2015). Notably, higher rates of ACEs experienced by an individual are associated with poorer health and social outcomes, such as substance misuse and antisocial behaviour (Baglivio, Wolff, Piquero & Epps, 2015; Mersky, Topitzes & Reynolds, 2013). The impact of early life adversity on learning strategies has been demonstrated behaviourally and computationally. Hanson et al. (2017) tested adolescents with and without experience of previous adversity (specifically physical abuse) on an associative learning task. Participants were required to learn the probability structure associated with two pairs of unknown stimuli in order to acquire rewards. The authors found that adolescents who had experienced early adversity were less likely to utilise knowledge of the environment in future decisions and therefore demonstrated poorer associative learning. Computationally, this was explained by group level differences on a parameter capturing noise in participants’ decisions, indicating participants with prior experience of adversity used knowledge from previous trials less than participants without previous adversity. However, the authors did not report analyses of group differences in the parameter capturing learning rate (; Sutton & Barto, 2018). This is important as early life stress is associated with more environmental volatility (Ellis et al., 2017), which favours a learning strategy that weights recent feedback highly (Behrens et al., 2007). To our knowledge, no research to date has examined whether early life stress is associated with differences in learning rate, which could provide insight into the differences in decision-making evidenced between individuals with and without history of early life adversity. The proposed study seeks to examine how early experiences of adversity and instability impact decision-making. Previous research has demonstrated that individuals exposed to early adversity are less likely to explore in decision-making tasks, but this can be optimal under certain conditions (Humphreys et al., 2015). Yet, the exact mechanism driving these differences in decision-making has not been examined. While previous research has demonstrated that adolescents who have experienced adversity show poorer associative learning (Hanson et al., 2017), no research to date has examined the contribution of learning rate (i.e. how much weight is given to recent feedback when updating decisions) to suboptimal performance. This is important as a learning strategy that weighs recent feedback highly can be advantageous in unstable and volatile environments (Behrens et al., 2007), which are associated with childhood adversity (Ellis et al., 2015). Therefore, this question can inform our understanding of the mechanistic differences in decision-making that result from early adversity and their relationship with high risk taking behaviours. To examine this, the present study will utilise a patch foraging paradigm to examine the influence of ACEs on decision-making strategies. Using a computational modelling approach, we aim to identify the mechanisms underlying different decision-making strategies between individuals with previous experience of childhood adversity, and those without.

This article examines e-waste management in India, identifying lessons and implications from e-waste management in the European Union and the United States which may influence or predict both strengths and obstacles to effectiveness in Indian e-waste regulation. India's new draft E-waste (Management and Handling) Rules are much more comprehensive than any US e-waste regulations and contain several similarities to the EU's current WEEE Directive. The inclusion of the EPR principle and the role of stakeholders in formulating the draft rules are both positive developments that are essential to address the e-waste problem successfully. Once in effect, however, the draft rules are likely to face many of the same obstacles to implementation and enforcement present in the EU and the US. Ultimately, until an international definition of e-waste is in place and the economic causes of illegal e-waste export and handling are addressed in all three entities, enforcing regulatory compliance and eliminating the health and environmental hazards related to e-waste dismantling in India will remain difficult., Asien, Nr. 117 (2010): ASIEN (Oktober)

The clothing fabric and skin interact continuously across the many regions of users′ bodies during wear, which can lead to both physical skin damage and discomfort. Therefore, this investigation aimed to explore the regional differences in skin friction, tactile perception, and sensitivity in both females and males during the skin-textile interaction. The static and dynamic friction coefficient and textile perception (texture, stickiness, pleasantness, and discomfort) were measured across the 36 selected testing body areas by using a friction measurement device. The results revealed there was a significant difference in skin friction, tactile perceptions, and sensitivity across the various body regions. The anterior neck had the highest skin friction in both females and males, and participants generally rated higher texture perception in their anterior aspects compared to posterior and lateral regions. There was no significant difference in skin friction, tactile perception ratings, and sensitivity between females and males. Practitioner summary: This study sought to examine regional variations in skin friction, tactile perception, and sensitivity during the skin-textile interaction. There was a significant difference in skin friction, tactile perceptions, and sensitivity across the various body regions and no significant sex effect on skin friction, tactile perception ratings, and sensitivity.