The Development of Spatial–Temporal, Probability, and Covariation Information to Infer Continuous Causal Processes

This paper considers how 5- to 11-year-olds’ verbal reasoning about the causality underlying extended, dynamic natural processes links to various facets of their statistical thinking. Such continuous processes typically do not provide perceptually distinct causes and effect, and previous work suggests that spatial–temporal analysis, the ability to analyze spatial configurations that change over time, is a crucial predictor of reasoning about causal mechanism in such situations. Work in the Humean tradition to causality has long emphasized on the importance of statistical thinking for inferring causal links between distinct cause and effect events, but here we assess whether this is also viable for causal thinking about continuous processes. Controlling for verbal and non-verbal ability, two studies (N = 107; N = 124) administered a battery of covariation, probability, spatial–temporal, and causal measures. Results indicated that spatial–temporal analysis was the best predictor of causal thinking across both studies, but statistical thinking supported and informed spatial–temporal analysis: covariation assessment potentially assists with the identification of variables, while simple probability judgment potentially assists with thinking about unseen mechanisms. We conclude that the ability to find out patterns in data is even more widely important for causal analysis than commonly assumed, from childhood, having a role to play not just when causally linking already distinct events but also when analyzing the causal process underlying extended dynamic events without perceptually distinct components.

Assessing causality in epidemiology: revisiting Bradford Hill to incorporate developments in causal thinking

The nine Bradford Hill (BH) viewpoints (sometimes referred to as criteria) are commonly used to assess causality within epidemiology. However, causal thinking has since developed, with three of the most prominent approaches implicitly or explicitly building on the potential outcomes framework: directed acyclic graphs (DAGs), sufficient-component cause models (SCC models, also referred to as ‘causal pies’) and the grading of recommendations, assessment, development and evaluation (GRADE) methodology. This paper explores how these approaches relate to BH’s viewpoints and considers implications for improving causal assessment. We mapped the three approaches above against each BH viewpoint. We found overlap across the approaches and BH viewpoints, underscoring BH viewpoints’ enduring importance. Mapping the approaches helped elucidate the theoretical underpinning of each viewpoint and articulate the conditions when the viewpoint would be relevant. Our comparisons identified commonality on four viewpoints: strength of association (including analysis of plausible confounding); temporality; plausibility (encoded by DAGs or SCC models to articulate mediation and interaction, respectively); and experiments (including implications of study design on exchangeability). Consistency may be more usefully operationalised by considering an effect size’s transportability to a different population or unexplained inconsistency in effect sizes (statistical heterogeneity). Because specificity rarely occurs, falsification exposures or outcomes (i.e., negative controls) may be more useful. The presence of a dose-response relationship may be less than widely perceived as it can easily arise from confounding. We found limited utility for coherence and analogy. This study highlights a need for greater clarity on BH viewpoints to improve causal assessment.

Adaptive Causal Thinking About Mobility Challenges: Implications for Quality of Life

Weiner’s attribution theory posits that it is adaptive to ascribe challenges to controllable causes (e.g., insufficient effort, bad strategies) and maladaptive to ascribe them to uncontrollable causes (e.g., old age). This is supported by our prior research that showed a heightened risk of mortality when mobility challenges were attributed to old age. The present pilot study randomly assigned older adults (N=36) in a day hospital to either an attributional retraining (AR) intervention group that viewed a video intended to shift causal thinking regarding mobility challenges (uncontrollable→controllable causes), or to a comparison group (No-AR). Participants completed a Time1 survey, the AR intervention (one week later), and a Time2 follow-up survey two weeks later. A manipulation-check revealed that AR was effective in shifting causal thinking away from maladaptive causes; a decline in the endorsement of the old age attribution was observed in the AR group (Ms=2.61 vs. 2.06; p=.02), but not in the No-AR group (Ms=2.45 vs. 2.35, p=.30). The AR and No-AR groups were equivalent at Time 1 on two quality-of-life outcomes: helplessness and perceived control (PC) over health. However, helplessness declined (Time1-Time2) in the AR group (Ms=1.13 vs. 0.73, p=.03), whereas it was relatively stable in the No-AR group (Ms=1.42 vs. 1.26, p>.20). Moreover, PC increased marginally in the AR group (Ms=6.50 vs. 6.69; p=.06), but declined in the No-AR group (Ms=6.20 vs 5.45, p=.05). Together, these findings suggest that attributions can be shifted away from uncontrollable causes and that this shift can have a protective effect that benefits quality-of-life.

Agency, Intervention, and the Past

Although agency theories of causation are unsuccessful, they draw on two plausible contributions to the analysis of causation: a characterization of agent non-symmetry in terms of effective means and an insight into nature of the similarity weighting for counterfactuals. A development of evidential decision theory provides the most immediately plausible way of understanding agency asymmetry. However, a problem with the proposed development reveals the importance of causal thinking—captured in causal decision theory—in characterizing when an action fails to be the most effective means to a certain end. Non-reductive interventionist approaches to causation are unnecessary because the recommended similarity weighting captures the appropriate notion of intervention. The recommended approach to causal non-symmetry can explain the fact that, metaphysically necessarily, causes usually precede their effect because temporal direction is preponderant causal direction. The non-symmetry of agency is related to two de facto asymmetries relating to knowledge and intervention.

Scalar ambiguities

This article focuses on an interrelation of various scales of perception in Tom McCarthy’s Satin Island (2015). Basing itself on Timothy Clark’s delineation of scalar ambiguities, it argues that Satin Island’s main protagonist, U, embodies a process of growing awareness of the world’s infinite complexity, discovering personal authenticity by withdrawing from action. His perspective is contrasted with the all-pervading Koob-Sassen, which represents a level of complicatedness that contradicts an individual perspective and the possibility of causal thinking. Finally, U’s entire narrative is cast into doubt by an oil spil, signifying a global occurrence whose rift effects are impossible to gauge, let alone predict. As these various scales are explored, the article shows that the novel thematises different levels of what Clark terms the Anthropocene disorder, in which human action can counterintuitively bring about catastrophic consequences.

Why Cities and Health?

Urban health is concerned with understanding how features of cities influence the health of urban populations, thus pointing the way to interventions that can improve health. An understanding of urban health requires a grounding in the fundamentals of causal thinking. How do cities influence the health of populations? And what is unique or uniquely interesting about urban health? This chapter addresses these questions through providing a conceptual framework to organize and guide thinking. The authors explicate how we may think of urban living as a ubiquitous exposure influencing other factors to which urban residents are exposed and that have a profound influence on the health of these residents.

Supporting decision-making in retirement planning: Do diagrams on Pension Benefit Statements help?

This paper investigates whether exposure to explanatory diagrams can affect a major financial decision. In a controlled experiment, participants were given Pension Benefit Statements with or without one or two diagrams, before answering incentivised questions that measured recall, comprehension and choice of contribution rate. The diagrams had at best a marginal influence on recall or comprehension. Nevertheless, a diagram relating contributions to income projections prompted more participants to advocate higher contributions, while both diagrams influenced the rationale participants gave for decisions. The implication is that although pension products remain hard to understand, diagrams may alter decisions by reinforcing relevant causal thinking.

Causal thinking for embedded, integrated implementation research

Despite increasing use of implementation frameworks, research evidence indicates that the uptake of evidence-based practice is minimally realised. Reasons for the lack of up-take may be: 1) lack of fit between evidence-based interventions and local contexts; 2) lack of knowledge of how and when to adapt an evidence-based intervention to promote effective practice in local contexts; and 3) a frequently used implementation research agenda that limits new insights to achieve effective practice. In response to these concerns we propose an embedded, integrated research agenda motivated with causal thinking for knowledge of when and how to adapt interventions and implementation to achieve effective practice.

Für eine Onto-Ästhetik des Autismus

The present paper analyses synesthesia in autism (ASD) and neurotypical experience. The way synesthesia has been interpreted within the history of phenomenology and psychopathology should prepare a philosophical access to autism and its subjective condition. The paper draws on the basic assumption that synesthesia reveals the presence of sensible networks and crossmodal connections beneath the framework of objective reality. Synesthesia, it is argued, confronts us with a specific dimension of the world beneath the essential structures of a material apriori, as it is elaborated within husserlian phenomenology. Experience in autism has close connections with such an alternative ontological setting. Asa matter of fact, autistic self-advocates often describe moments of a deep immersion into sensible experience, in which different sensorial events come to ‘resonate’ with one another. Resonance is thus interpreted as a fundamental ontological connector within an experiential framework that is not subjected to abstract concepts and causal thinking