Though research on male body image has advanced significantly since the 1980s (Grogan, 2016), most contemporary research on male body image has included younger male samples, with little attention paid to the body image of middle-aged and older-aged men (Drummond, 2003; Leichty, Ribeiro, Svienson and Dahlstrom, 2014; McCabe and Ricciardelli, 2004; Slevin and Linneman, 2010). Accordingly, it has been difficult for researchers to draw conclusions about how male body image develops beyond the young adult phase (McCabe and Ricciardelli, 2004). Given that body dissatisfaction has been linked with adverse psychological and behavioural consequences (Grogan, 2016), it is imperative that knowledge regarding male body image across the lifespan is sought, and that age-appropriate interventions are developed for boys and men across different ages (if required). The overall aim of the current PhD was to gain insights into the way men think, feel and behave regarding their bodies at various points in their lives. To achieve this aim, the current study employed a range of data gathering methods, including in-depth interviews, online-questionnaires and focus groups. From an examination of the findings of the overall thesis, body image unawareness in preadolescence, awareness in adolescence, body appreciation across the lifespan and body function across the lifespan appeared to be the strongest themes across the different studies. Additionally, adolescence was established as the most vulnerable developmental stage for which a hypothetical positive body image promotion programme was also developed. A key strength of this PhD is that it generated important knowledge regarding the body image of middle-aged and older men, as well as provided a lifespan perspective of men's body image which in the past has only extended as far as reporting the body image of young adult men.

Humans are adept at constructing causal models of the world that can support prediction, explanation, simulation-based reasoning, planning and control. In this thesis I explore how people learn about the causal world interacting with it, and how they represent and modify their causal knowledge as they gather evidence. Over 10 experiments and modelling, I show that interventional and temporal cues, along with top-down hierarchical constraints, inform the gradual evolution and adaptation of increasingly rich causal representations. Chapters 1 and 2 develop a rational analysis of the problems of learning and representing causal structure, and choosing interventions, that perturb the world in ways that reveal its structure. Chapters 3--5 focus on structure learning over sequences of discrete trials, in which learners can intervene by setting variables within a causal system and observe the consequences. The second half of the thesis generalises beyond the discrete trial learning case, exploring interventional causal learning in situations where events occur in continuous time (Chapters 6 and 7); and in spatiotemporally rich physical "microworlds" (Chapter 8). Throughout the experiments, I find that both children and adults are robust active causal learners, able to deal with noise and complexity even as normative judgment and intervention selection become radically intractable. To explain their success, I develop scalable process level accounts of both causal structure learning and intervention selection inspired by approximation algorithms in machine learning. I show that my models can better explain patterns of behaviour than a range of alternatives as well as shedding light on the source of common biases including confirmatory testing, anchoring effects and probability matching. Finally, I propose a close relationship between active learning and active aspects of cognition including thinking, decision making and executive control.

It is well established that testing of studied information, by comparison with restudying or doing nothing, enhances long-term retention of studied information – the backward testing effect. An accumulating body of more recent research has shown that interim testing of studied information has another important consequence: it enhances learning and retrieval of new information – the forward testing effect. This thesis aims to further explore the forward beneficial effects of interim testing. The research described here employs the most-widely used procedure – a multi-list method – to investigate the forward testing effect on self-regulated study time allocation (Experiments 1 and 2), metamemory monitoring (Experiments 3 and 4), inductive learning (Experiments 5 and 6), and transfer effect (Experiments 7-9). Finally, it explores whether interim tests can be used as a remedial technique to mitigate older adults’ learning and memory deficits (Experiments 10-12). Experiments 1 and 2 reveal that, in the absence of interim tests, learners systematically decrease their study times across a study phase; however, this decreasing trend is prevented (or attenuated) by interim tests. These two experiments also show that the forward benefits of interim tests generalize to self-paced learning situations. Experiments 3 and 4 show that people tend to be aware of the forward benefits of interim tests. Experiments 5 and 6 demonstrate that frequent interim tests facilitate the learning of abstract concepts, indicating that interim testing enhances inductive learning. Experiments 7-9 explore the transferability of the forward effect, in which material types (and test formats) were varied across blocks. The results confirm that the effect transfers broadly. Experiments 10-12 reveal that interim tests significantly improve older adults’ learning and memory of new information. Overall, the findings shed light on the mechanisms of the forward testing effect and provide strong encouragement for learners and instructors to administer interim tests in educational contexts.

Autism Spectrum Disorder (ASD) is characterised by difficulties with social communication and interaction. A great deal of experimental work has examined the performance of people with ASD on social cognition tasks in laboratory settings, and a number of cognitive models have been postulated to account for observed differences in those with ASD. Meanwhile, clinical reports indicate that people with ASD face a range of difficulties in everyday functioning. However, very little experimental work has tried to elucidate how the postulated cognitive deficits in ASD might translate into difficulties in real-life-type settings, especially in adult populations. A range of novel scenario-based tasks were developed for the present thesis which aimed to provide more sensitive tools than traditional social cognition tasks for identifying the nature and severity of impairments in everyday social functioning. These systematically examined different aspects of social performance, in particular pro-social behaviour, moral judgment and reasoning. The present thesis adopted a trait-based approach to investigate how high versus low levels of autistic traits influenced everyday social functioning. This is in line with the continuum conceptualisation of an autistic spectrum, whereby those with clinical levels of impairment (i.e. diagnosed with ASD) are thought to lie at the extreme end of a normal distribution of autistic traits. Overall, two key findings emerged; firstly, people with high levels of autistic traits tended to be less behaviourally and emotionally responsive to others’ needs. Secondly, people with high levels of autistic traits displayed relatively intact awareness of social and moral norms that underpin everyday situations, but their understanding of these appeared to be more limited. These findings are consistent with the conceptualisation of a continuum of trait severity, whereby those with high levels of autistic traits showed similar difficulties to those seen in people with ASD, although perhaps to a lesser extent. The body of work presented in this thesis has potential clinical implications for the assessment and management of adults with ASD.

This thesis investigates human probabilistic judgment in complex real-world settings to identify processes underpinning biases across groups which relate to numerical frames and formats. Experiments are conducted replicating real-world environments and data to test judgment performance based on framing and format. Regardless of background skills and experience, people in professional and consumer contexts show a strong tendency to perceive the world from a linear perspective, interpreting information in concrete, absolute terms and making judgments based on seeking and applying linear functions. Whether predicting sales, selecting between financial products, or forecasting refugee camp data, people use minimal cues and systematically apply additive methods amidst non-linear trends and percentage points to yield linear estimates in both rich and sparse informational contexts. Depending on data variability and temporality, human rationality and choice may be significantly helped or hindered by informational framing and format. The findings deliver both theoretical and practical contributions. Across groups and individual differences, the effects of informational format and the tendency to linearly extrapolate are connected by the bias to perceive values in concrete terms and make sense of data by seeking simple referent points. People compare and combine referents using additive methods when inappropriate and adhere strongly to defaults when applied in complex numeric environments. The practical contribution involves a framing manipulation which shows that format biases (i.e., additive processing) and optimism (i.e., associated with intertemporal effects) can be counteracted in judgments involving percentages and exponential growth rates by using absolute formats and positioning defaults in future event context information. This framing manipulation was highly effective in improving loan choice and repayment judgments compared to information in standard finance industry formats. There is a strong potential to increase rationality using this data format manipulation in other financial settings and domains such as health behaviour change in which peoples’ erroneous interpretation of percentages and non-linear relations negatively impact choice and behaviours in both the short and long-term.

How do humans generalize from observed to unobserved data? How does generalization support inference, prediction, and decision making? I propose that a big part of human generalization can be explained by a powerful mechanism of function learning. I put forward and assess Gaussian Process regression as a model of human function learning that can unify several psychological theories of generalization. Across 14 experiments and using extensive computational modeling, I show that this model generates testable predictions about human preferences over different levels of complexity, provides a window into compositional inductive biases, and --combined with an optimistic yet efficient sampling strategy-- guides human decision making through complex spaces. Chapters 1 and 2 propose that, from a psychological and mathematical perspective, function learning and generalization are close kin. Chapter 3 derives and tests theoretical predictions of participants' preferences over differently complex functions. Chapter 4 develops a compositional theory of generalization and extensively probes this theory using 8 experimental paradigms. During the second half of the thesis, I investigate how function learning guides decision making in complex decision making tasks. In particular, Chapter 5 will look at how people search for rewards in various grid worlds where a spatial correlation of rewards provides a context supporting generalization and decision making. Chapter 6 gauges human behavior in contextual multi-armed bandit problems where a function maps features onto expected rewards. In both Chapter 5 and Chapter 6, I find that the vast majority of subjects are best predicted by a Gaussian Process function learning model combined with an upper confidence bound sampling strategy. Chapter 7 will formally assess the adaptiveness of human generalization in complex decision making tasks using mismatched Bayesian optimization simulations and finds that the empirically observed phenomenon of undergeneralization might rather be a feature than a bug of human behavior. Finally, I summarize the empirical and theoretical lessons learned and lay out a road-map for future research on generalization in Chapter 8.

Most decision-making studies will focus on the value and uncertainty of each choice option but do not focus on the importance of the representation of the choice option itself. This thesis presents the effects that task goals have on creating the appropriate cognitive representation to achieve those goals and how these representations are dependent on the informational input within a given task. The overall hypothesis for this work is that cognitive representations reveal a trade-off between accommodating task goals and the format of the information sampled from the environment of the task. For example, ordering books in a stand in alphabetical order, to facilitate the task of retrieving a relevant one when necessary, reveals a material implication of such cognitive representations. As in many situations, the internal representations constructed by the agent embody the remaining degrees of freedom that map the input to successful task completion. The first two chapters in this work present how uncertain beliefs about ourselves and our preferences are either integrated or compared to fixed information about other agent’s beliefs. The third chapter presents the direct manipulation of representations of choice options by changing both the stimuli and controlling for the decision strategy used by the decision-makers. The fourth chapter presents how choice options themselves are represented in the human brain. The findings related to 1) the adaptation of personal preferences and beliefs to the (fixed) preferences and beliefs of other agents, 2) observed reduction in decision strategy compliance contingent on stimulus format, and 3) the task-contingent results for similarities between brain states of choice options, support the general trade-off hypothesis. The conclusion that can be drawn is that the study of choice option representations is underdetermined unless both informational input and task goals are accounted for.

Adults often learn new meanings for words they already know, for example due to language evolving with changes in technology (e.g., the newer internet-related meaning of "troll"). Learning new word meanings generally takes place incidentally, such as when reading for comprehension. The experiments in this thesis explore some of the different factors that impact adults' acquisition and long-term retention of novel meanings for familiar words learned incidentally from reading stories. Experiment 1 assessed the effect of number of exposures on incidental learning. The results showed reasonably good memory of new word meanings after only two exposures, and a linear, incremental increase in recall with more exposures. There was also no forgetting after one week, regardless of the number of exposures during training. Experiment 2 compared incidental to intentional learning, showing that new meanings for familiar words are harder to learn under incidental conditions, but may be less susceptible to forgetting. Experiments 3-4 explored whether a testing effect may have contributed to the good long-term retention of new word meanings in the previous experiments, and whether the method of immediate test affects this. These experiments showed that memory tests (cued recall or meaning-to-word matching) considerably enhanced retention of new word meanings. Experiments 5-6 explored whether sleep is important for active consolidation of new word meanings, as previously shown for learning new word forms. In these experiments sleep improved explicit knowledge of new meanings when it occurred in the immediate interval between learning and test. No evidence of active consolidation was found; the results are consistent with a passive benefit of sleep in protecting against interference. Together these experiments demonstrate that adult readers are proficient at learning new meanings for familiar words from a small number of encounters within naturalistic story contexts, and certain factors can have an important impact on learning.

Self-regulated learning (SRL) skills have recently attracted a lot of research interest because they have been identified as arguably the most important determinants of academic performance and achievement. Learners with good SRL skills perform better because they have a clearer awareness of the effective strategies needed for a task and when to apply and adapt them - above all, they learn more effectively. Furthermore, they are intrinsically motivated so they set higher goals, put in more effort and show greater perseverance at learning tasks. It is of crucial significance to understand how these skills are developed and why some children acquire them better than others. It has been observed that some cultural groups consistently exhibit higher achievement than others and variation in SRL skills by culture has also been observed. This research was therefore aimed at examining whether cultural differences impact on the organisation of SRL skills in a consistent and predictable fashion. A better understanding of the processes pertaining to this construct could provide some insight about how to promote SRL skills development in all children. Quantitative data was collected from three studies, two in the UK and one in Beijing, designed to test hypotheses derived from models of how culture (White British vs Chinese backgrounds; Confucian vs non-Confucian backgrounds, as defined by a novel measure of filial piety) could influence SRL variables. These models introduced a conceptual advancement by utilising constructs from the theory of planned behaviour (TPB) to capture the motivational elements of SRL. The data largely supported the overarching hypothesis that culture impacts on the nature and operation of the motivational elements of SRL, not the cognitive ones, with a consistent pattern of these being driven by external expectations among Confucian children, and by experientially derived attitudes among non-Confucian. The findings from the current research provide a huge impetus to cross-cultural research in SRL development by providing a model (SRL+TPB) that operationalises the interaction of cultural elements with SRL; and also point to ways in which classroom interventions to support SRL might take advantage of both patterns of effects to achieve optimal outcomes.

Humans have developed a complex social structure which relies heavily on communication between members. However, not all communication is honest. Distinguishing honest from deceptive information is clearly a useful skills, but individuals do not possess a strong ability to discriminate veracity. As others will not willingly admit they are lying, one must rely on different information to discern veracity. In deception detection, individuals are told to rely on behavioural indices to discriminate lies and truths. A source of such indices are the emotions displayed by another. This thesis focuses on the role that emotions have on the ability to detect deception, exploring the reasons for low judgemental accuracy when individuals focus on emotion information. I aim to demonstrate that emotion recognition does not aid the detection of deception, and can result in decreased accuracy. This is attributed to the biasing relationship of emotion recognition on veracity judgements, stemming from the inability of decoders to separate the authenticity of emotional cues. To support my claims, I will demonstrate the lack of ability of decoders to make rational judgements regarding veracity, even if allowed to pool the knowledge of multiple decoders, and disprove the notion that decoders can utilise emotional cues, both innately and through training, to detect deception. I assert, and find, that decoders are poor at discriminating between genuine and deceptive emotional displays, advocating for a new conceptualisation of emotional cues in veracity judgements. Finally, I illustrate the importance of behavioural information in detecting deception using two approaches aimed at improving the process of separating lies and truths. First, I address the role of situational factors in detecting deception, demonstrating their impact on decoding ability. Lastly, I introduce a new technique for improving accuracy, passive lie detection, utilising body postures that aid decoders in processing behavioural information. The research will conclude suggesting deception detection should focus on improving information processing and accurate classification of emotional information.