Causal Hypotheses Research Articles

Androgyny and atypical sensory sensitivity associated with savant ability: a comparison between Klinefelter syndrome and sexual minorities assigned male at birth

IntroductionThe extreme male brain (EMB) theory, a major causal hypothesis of autism (ASD: autism spectrum disorder), attributes excess androgens during early development as one of the causes. While studies have generally followed the EMB theory in females at birth, the co-occurrence of ASD in males at birth has been observed in conditions that are assumed to be associated with reduced androgen action during early development, including Klinefelter syndrome (KS) and sexual minorities. ASD is also associated with atypical sensory sensitivity, synesthesia, and savant syndrome.MethodsIn the present study, we examined adult KS individuals (n = 22), sexual minorities assigned male at birth (n = 66), and control males matched for age and educational background to those with KS [Exploratory analysis (control 1st): n = 36; Reanalysis (control 2nd): n = 583]. Participants completed a self-report questionnaire assessing sensory hypersensitivity/hyposensitivity, savant tendency (developed for the present study), synesthesia, and sexual aspects, including gender identity and sexual orientation.ResultsThe results of the exploratory analysis suggested that individuals with KS exhibited a higher tendency toward sensory hypersensitivity/hyposensitivity than the tendency exhibited by the controls. In the Reanalysis, sexual minorities were more likely to be synesthetes, and in both analyses sexual minorities exhibited a higher savant tendency and sensory hypersensitivity/hyposensitivity than the controls. Moreover, the gender dysphoric state was associated with phenotypes observed in individuals with ASD, such as synesthesia, savant tendency, and sensory hypersensitivity/hyposensitivity.DiscussionThese results suggest a common physiological background among gender dysphoria, synesthesia, savant tendency, and atypical sensory sensitivity. Thus, androgynous features (reduced effects of sex steroids during early development) in males at birth may be partially related to the phenotype commonly observed in individuals with ASD. Based on the present results, we propose that the reduction of sex steroids during early development may lead to atypical neurodevelopment and be involved in the atypicality of external and internal sensory perception, and thus in the atypicality of self-concept integration, through the disruption of oxytocin and the gamma-aminobutyric acid system modulating the neural excitation/inhibition balance.

FDI Impact on China's Sectoral Performance: A Panel Cointegration and Causality Analysis

This study provides a thorough examine the influence of FDI inflows and outflows on China's economic growth across three major sectors. Using panel data from 1997 to 2022 in China, it utilizes tests for unit roots and cointegration to investigate the enduring connection between FDI and economic growth. The research results validate the existence of a long-standing cointegration relationship between FDI and economic expansion. Additionally, this research employs the Granger causality test to ascertain the direction of causality between FDI and economic growth. The study reveals a two-way causality between foreign direct investment (FDI) inflows and overall economic growth, which supports the hypothesis of feedback causality. Additionally, there exists a one-way causality originating from FDI inflows across various sectors, suggesting that growth attracts FDI. The government should encourage foreign investment to enhance the industrial structure and boost economic growth.

Quantifying convergence and consistency.

The reproducibility crisis highlights several unresolved issues in science, including the need to develop measures that gauge both the consistency and convergence of data sets. While existing meta-analytic methods quantify the consistency of evidence, they do not quantify its convergence: the extent to which different types of empirical methods have provided evidence to support a hypothesis. To address this gap in meta-analysis, we and colleagues developed a summary metric-the cumulative evidence index (CEI)-which uses Bayesian statistics to quantify the degree of both consistency and convergence of evidence regarding causal hypotheses between two phenomena. Here, we outline the CEI's underlying model, which quantifies the extent to which studies of four types-positive intervention, negative intervention, positive non-intervention and negative non-intervention-lend credence to any of three types of causal relations: excitatory, inhibitory or no-connection. Along with p-values and other measures, the CEI can provide a more holistic perspective on a set of evidence by quantitatively expressing epistemic principles that scientists regularly employ qualitatively. The CEI can thus address the reproducibility crisis by formally demonstrating how convergent evidence across multiple study types can yield progress toward scientific consensus, even when an individual type of study fails to yield reproducible results.

Protocol of Randomized Controlled Community Trial (RCCT) for obesity management in Brazilian primary health care.

Obesity is a chronic disease characterized by excess body fat and is a risk factor for other chronic non-communicable diseases. Its multifactorial and complex nature makes its management a challenge for health services. This manuscript presents an investigation protocol that aims to analyze the effectiveness of collective nutritional interventions for obesity management applicable to primary health care. Randomized Controlled Community Trial (RCCT) in a representative sample of users of the Programa Academia de Saúde (PAS), in Belo Horizonte, Minas Gerais, Brazil, with obesity. The research consists of four phases: (1) Screening to identify the participants eligible for the nutritional interventions (individuals with obesity, readiness for change to lose body weight, and willingness and interest to participate in a group activity for six months or more); (2) Baseline to characterize the participants; (3) Implementation of collective nutritional interventions; (4) Reassessment of the participants. Participants in the control group (CG) will receive the usual health service care, and participants in the intervention group (IG) will participate in collective nutritional interventions based on Therapeutic Group 1 (TG1) or Therapeutic Group 2 (TG2) of the "Instructive of Collective Approach for the obesity management in SUS". The strengths of the study include its robust RCCT design, which allows for longitudinal analyses and is suitable for investigating causal hypotheses and applying strategies to improve adherence to interventions. Furthermore, the study included a representative sample of a public health service and aims to evaluate therapeutic proposals from the Brazilian Ministry of Health, which can contribute to implementation and extension in the national territory. RBR-3vzsyqq and RBR-6pg682m.

The role of causal manipulability in the manifestation of time biases

We investigate the causal manipulability hypothesis, according to which what partly explains (a) why people tend to prefer negative events to be in their further future rather than their nearer future and positive events to be in their nearer future rather than their further future and (b) why people tend to prefer that negative events be located in their past not their future and that positive events be located in their future not their past, is that people tend to discount the value of events they are less able causally to manipulate. If people discount the value of events they are less able to causally manipulate, then since often temporally nearer future events are more causally manipulable than further ones, and since future events are manipulable whereas past ones aren’t, this could explain both (a) and (b). In turn, if the causal manipulability hypothesis is correct, this might suggest that insofar as people’s preferences are explained in this manner, those preferences are rationally permissible, since relative causal manipulability is normatively relevant. Thus, ascertaining whether the causal manipulability hypothesis is true may shed light on the normative status of such preferences. We investigate the cognitively mediated version of the causal manipulability hypothesis, according to which people’s consciously held beliefs about the relative causal manipulability of events explains (a) and (b). Contrary to expectations, we found no evidence in favour of this view. We suggest that either relative causal manipulability plays an explanatory role, but one that is not cognitively mediated, or that it does not play any role, even if it is sometimes associated with other factors, such as probability, that may play a role in explaining some time biased preferences.

A Study on the Cognitive, Normative, and Affective Factors That Enhance the Pro-Environmental Behaviors of Consumers in the Context of Drone Food Delivery Services

The current study examined consumers’ sustainable behavior in the context of eco-friendly drone food delivery services. It thus focused on the cognitive triggers, normative factors, and affective triggers in forming pro-environmental intentions. This study more specifically developed a comprehensive framework that included cognitive triggers, which included environmental awareness, ascribed responsibility, biospheric value, environmental concern, and perceived effectiveness, personal norm, and affective triggers, which included positive anticipated emotion and negative anticipated emotion, subjective norm, and pro-environmental intentions. The 312 samples were randomly extracted through an online survey company in Korea, which targeted individuals who have dined out within the last six months. A theoretical model that included mediation and causal hypotheses was proposed and tested by conducting structural equation modeling. The data analysis results indicated that the four dimensions of the cognitive triggers, such as ascribed responsibility, biospheric value, environmental concern, and perceived effectiveness, positively affect personal norm, and consequently have a positive effect on positive anticipated emotion. In addition, subjective norm aids in regards to enhancing personal norm and pro-environmental intentions. The study consequently contributes knowledge that addresses the acknowledged research gap and provides practical suggestions for green marketing strategies in regards to promoting the services.

A Weight-of-Evidence Approach for Understanding the Recovery of Okanagan Sockeye Salmon

The productivity of Pacific Sockeye salmon (Oncorhynchus nerka) in the Columbia River has been declining over the past century. Yet, the Okanagan River Sockeye salmon population, which spawns in the Okanagan River, a Canadian tributary of the Columbia River, has seen a remarkable turnaround in abundance. Different hypotheses and lines of evidence covering multiple spatial scales have been proposed to explain this recovery; but they have never been comprehensively assessed. We adopted a weight-of-evidence approach to systematically assess the relative likelihood that each of these causal hypotheses contributed to the observed recovery. Our analysis disentangles the relative consequences of a set of environmental management actions that have been implemented to augment the Sockeye salmon freshwater productivity, while accounting for changes in freshwater and marine environmental conditions. Our list of potentially explanatory causal factors (anthropogenic and natural) included: (1) changes in escapement concurrent with improving local fish passage, (2) the implementation of fish-friendly flows in the Okanagan River, (3) initiating a hatchery restocking program, (4) potential improvements to Columbia dam operations to support higher relative survival of out-migrating juvenile fish, (5) possible shifts in survival-favorable conditions in the coastal marine environment for ocean-going life stages, and (6) broader changes to multi-stock harvest regimes in the Columbia River. Our assessment leveraged comparisons with the population dynamics of another Sockeye salmon stock in the Columbia River basin to differentiate between the impacts of management actions taken within the Okanagan watershed (our focus) from those occurring over the broader basin and marine scale. The results suggest that while shifts towards survival-favorable conditions in the coastal marine environment in 2007 played an important role in the upturn of the Okanagan population, alone it cannot explain the rate at which the Okanagan River Sockeye salmon recovered. Strong evidence supports the combined effect of increased escapement in conjunction with establishing and securing fish-friendly flows during spawning, incubation, and alevin emergence. Additionally, Sockeye salmon restocking improved the resilience of the stock against density-independent mortality events. These combined basin-level management actions played a pivotal role in magnifying the recovery trajectory afforded by improved marine survivorship. The spectacular response of the Okanagan River Sockeye salmon to the holistic perspectives and management interventions of Indigenous and other caretakers provides hope that other Pacific salmon stocks can be stabilized and recovered.

Causal analyses in longitudinal observational studies in oral health: A scoping review.

Causal analysis including causal inference and causal mediation is pivotal to inform effective interventions. In modern epidemilogy, causal analysis involves four key steps: formulating causal questions, employing directed acyclic graphs (DAGs), conducting data management and selecting statistical strategies. Our objective was to conduct a scoping review to assess how longitudinal observational studies (LOSs) in dental field have integrated these four steps to contribute leverage evidence that inform oral public health interventions. LOSs focusing on determinants of dental caries published from 2012 to 2024 were systematically retrieved from five major databases. The Joanna Briggs Institute-scoping review guidance and the Covidence application were employed to identify eligible LOSs for being reviewed. Out of the 85 eligible LOSs, none formulated causal hypothesis by applying 'what if' question or investigated mediation across three levels of the determinants of oral health. A minority (18 studies, ~21.2%) employed DAGs to visualise relationships among study variables, while only one third (33 studies, ~39%) clearly defined confounders. The majority (64 studies, ~75%) incorporated a time-varying feature of their data, yet only a few (11 studies) fully leveraged this advanced aspect. Among these studies that fully utilised time-varying data, more than half encountered challenges in employing robust statistics to address confounders arising from such data dynamics. Dental LOSs have, to date, mostly focused on investigating associations over causality, often neglecting the four-step causal analysis and not fully utilising time-varying data. Researchers necessitate to shift their focus to causal inference and prioritise building capacity in causal analysis with a consistent four-step approach to advance the field. Studies exploring mechanisms linking determinants of dental caries across levels and leveraging time-varying data are strongly encouraged.

The link between sustainability initiatives at firm and supply chain levels: The mediating role of involvement of partners

AbstractThe deliberations of the COP28 in Dubai in December 2023 and the growing importance of UN Sustainable Development Goals have highlighted that sustainability initiatives have moved from being ‘nice‐to‐do’ to ‘must‐do’. The resource dependency theory suggests that a firm cannot develop green strategies in isolation, and a substantial involvement of all supply chain partners is needed for achieving larger impacts on environmental sustainability. However, the literature has yet to explore this link in detail. In this paper, we investigate the link between sustainability initiatives at a firm level and at the supply chain level in line with global green agenda. Data collected through a questionnaire survey of senior logistics and supply‐chain managers in UK companies were used to propose and statistically validate a framework combining both constructs and causal hypotheses. We further use a case of a farming company from Luxemburg to validate our research findings. Our results suggest a strong link in terms of green strategies between the firm level and supply chain level. We find that this link is mediated by the degree of involvement of supply chain partners. A case company participated in the study agreed to our research findings related to importance of technology and collaboration in food sector to share the resources among all supply chain players. We also find that green strategies result in improved business performance.

The Source of Nasal Rustle (Nasal Turbulence): An Overview of Current Evidence.

Nasal rustle (also called nasal turbulence) refers to a loud distracting sound that sometimes occurs with audible nasal emission (ANE) during the production of pressure-sensitive consonants in patients with velopharyngeal insufficiency (VPI). This article examines evidence for two hypotheses of causality: vibration of the soft palate (velar flutter) and periodic motion of mucus above the velopharyngeal port (turbulent mucus). A review of the relevant literature shows inconclusive evidence to support velar flutter as a cause of nasal rustle. In contrast, clinical observations and research involving high-speed nasopharyngoscopy suggest that nasal rustle is the result of turbulent mucus above a small velopharyngeal opening. Therefore, it is our contention that a plausible explanation for nasal rustle is one of turbulent mucus and not velar flutter.

Larger colony sizes favoured the evolution of more worker castes in ants.

The size-complexity hypothesis is a leading explanation for the evolution of complex life on earth. It predicts that in lineages that have undergone a major transition in organismality, larger numbers of lower-level subunits select for increased division of labour. Current data from multicellular organisms and social insects support a positive correlation between the number of cells and number of cell types and between colony size and the number of castes. However, the implication of these results is unclear, because colony size and number of cells are correlated with other variables which may also influence selection for division of labour, and causality could be in either direction. Here, to resolve this problem, we tested multiple causal hypotheses using data from 794 ant species. We found that larger colony sizes favoured the evolution of increased division of labour, resulting in more worker castes and greater variation in worker size. By contrast, our results did not provide consistent support for alternative hypotheses regarding either queen mating frequency or number of queens per colony explaining variation in division of labour. Overall, our results provide strong support for the size-complexity hypothesis.

The reciprocal relationships between economic status and mental health: Investigating the between-person and within-person effects in a three-wave longitudinal study

BackgroundSocial drift/selection (i.e., mental health symptoms cause low economic status) and social causation theories (i.e., low economic status causes mental health symptoms) specify reciprocal relationships between economic status and mental health. Little is known regarding the disaggregation of within-person and between-person effects in the relationship between economic status and mental health in the long run. The current study sought to examine the reciprocal relationships between economic status and mental health over 20 years of adulthood, disaggregating within-person and between-person effects. MethodsData were from three waves (7108 participants) of the Midlife Development in the United States study. Participants reported information about objective and subjective measures of economic status as well as a wide range of indicators of mental health on the positive dimension, including subjective, social, and psychological well-being, and on the negative side, depression, anxiety, panic attack, anhedonia, somatic amplification, alcohol abuse, and negative affect. Cross-lagged panel models were estimated. ResultsAt between-person levels, both social drift/selection and social causation hypotheses were confirmed when considering subjective measures of economic status. When using objective measures of economic status (i.e., income), the results showed decreased support for social drift/selection and social causation hypotheses. At within-person levels, social drift/selection and social causation hypotheses were generally not supported, with some notable exceptions. LimitationsRestriction of the sample to one country limits the generalizability of the findings. ConclusionsSocial causation and social drift/selection processes act simultaneously mainly at a population level, but much less when considering individual changes. Policy and programs should be targeted at addressing inequality in income and mental health within a nation or a community.

How Evidential Pluralism Can Help Clarify the Nature of the Relationship Between Unemployment and Entrepreneurship

In line with Shan and Williamson (2023 , Evidential pluralism in the social sciences, Routledge), this article argues that evidential pluralism used in the philosophical enquiry of causation can be employed to examine causal relationships in the business and economics disciplines. We focus on the relationship between unemployment and entrepreneurship, which has created heated and inconclusive debate in the economics of entrepreneurship field. Specifically, we suggest that discrepancies in the literature are due to: (a) the failure to fully capture the mechanism of the relationship; and (b) differences in the methodological and data analysis approaches used in existing studies. We therefore argue that if we want to explore the unemployment and entrepreneurship relationship, we need to capture the underlying pathways that bring together different forms of entrepreneurship and unemployment by considering, for example, structural and labour market factors that may alter the strength and/or direction of the relationship. The case study analysis provides strong support for the use of the evidential pluralism in establishing causal links. We argue that methodological diversity and mixed method approaches can be helpful for exploring mechanisms, but they can be somewhat problematic when examining correlation empirically. Here, the use of panel data may allow us to capture the statistical association more accurately than the use of other types of data and econometric modelling. Finally, we argue that exploring the mechanism ahead of the correlation can allow us to learn more about the underlying relationship among the variables, which can then be modelled and captured statistically. In contrast, examining correlation first can lead to misleading results. Overall, the article concludes that evidential pluralism used in the philosophy of causation can help us to understand causal links and establish causal claims for important economic relationships, allowing effective policy to be crafted. To this end, and as discussed in the evidential pluralism literature (see Russo, F., & Williamson, J. 2007 , International Studies in the Philosophy of Science,21[2], 157–170; Shan, Y., & Williamson, J. 2023 , Evidential pluralism in the social sciences, Routledge), evidence of both mechanisms and correlations should be used to support causal hypotheses made in economics and business research. However, we propose that before analysing the correlations, we should conceptually examine the mechanisms.

Testing the causal impact of amyloidosis on total Tau using a genetically informative sample of adult male twins.

The amyloid cascade hypothesis predicts that amyloid-beta (Aβ) aggregation drives tau tangle accumulation. We tested competing causal and non-causal hypotheses regarding the direction of causation between Aβ40 and Aβ42 and total Tau (t-Tau) plasma biomarkers. Plasma Aβ40, Aβ42, t-Tau, and neurofilament light chain (NFL) were measured in 1,035 men (mean = 67.0 years) using Simoa immunoassays. Genetically informative twin modeling tested the direction of causation between Aβs and t-Tau. No clear evidence that Aβ40 or Aβ42 directly causes changes in t-Tau was observed; the alternative causal hypotheses also fit the data well. In contrast, exploratory analyses suggested a causal impact of the Aβ biomarkers on NFL. Separately, reciprocal causation was observed between t-Tau and NFL. Plasma Aβ40 or Aβ42 do not appear to have a direct causal impact on t-Tau. In contrast, Aβ aggregation may causally impact NFL in cognitively unimpaired men in their late 60s.

Generalism in species interactions is more the consequence than the cause of ecological success.

Generalism in resource use is commonly considered a critical driver of population success, species distribution and extinction risk. This idea can be questioned as generalism may be a result rather than the cause of species abundance and range size. We tested these contrasting causal hypotheses focusing on host use in three databases encompassing approximately 44,000 mutualistic (hummingbird-plant), commensalistic (lichen-plant) and parasitic (flea-mammal) interactions in 617 ecological communities across the Americas and Eurasia. Across all interaction types, our analyses indicated that range size and abundance influence the probability of encountering hosts and set the arena for species to express generalism potentials or adapt to new hosts. Hence, our findings support the hypothesis that generalism is a consequence of species ecological success. This highlights the importance of ecological opportunity in driving species characteristics considered key for their survival and conservation.

Impact of the COVID-19 pandemic on antidepressant consumption in the Central region of Portugal: interrupted time series.

To evaluate the impact of the pandemic on the consumption of antidepressive agents in Central Portugal. To estimate the causal effect of the pandemic an interrupted time series analysis was conducted. Data of antidepressant drugs monthly dispensed in community pharmacies between Jan-2010 and Dec-2021 were provided by the regional Health Administration. Anti-Parkinson dopaminergic agents and statins, theoretically not influenced by COVID-19 pandemics, were used as comparator series. The number of packages was converted into defined daily doses and presented as defined daily doses/1000 inhabitants/day. A Bayesian structural time-series model with CausalImpact on R/RStudio was used to predict the counterfactual. Analyses with different geographical granularity (9 sub-regions and 78 municipalities) were performed. When compared to counterfactual, regional consumption non-significantly increased after the pandemic declaration, with a relative effect of + 1.30% [95%CI -1.6%:4.2%]. When increasing the granularity, differences appeared between sub-region with significant increases in Baixo Mondego + 6.5% [1.4%:11.0%], Guarda + 4.4% [1.1%:7.7%] or Cova da Beira + 4.1% [0.17%:8.3%], but non-significant variation in the remaining 6 sub-regions. Differences are more obvious at municipality level, ranging from increases of + 37.00% [32.00%:42.00%] to decreases of -11.00% [-17.00%:-4.20%]. Relative impact positively correlated with percentage of elderly in the municipality (r = 0.301; p = 0.007), and negatively with population density (r=-0.243; p = 0.032). No other predicting variables were found. Antidepressant consumption suffered very slight variations at regional level after the COVID-19 pandemic declaration. Analysis with higher granularity allowed identifying municipalities with higher impact (increase or decrease). The absence of clear association patterns suggests other causal hypotheses of the differences.

The evolution of evolutionary linguistics

Abstract This paper presents a scientometric study of the evolution of evolutionary linguistics, a multidisciplinary field that investigates the origin and evolution of language. We apply network science methods to analyse changes in the connections among core concepts discussed in the Causal Hypotheses in Evolutionary Linguistics Database, a searchable database of causal hypotheses in evolutionary linguistics. Our analysis includes a multipartite network of 416 papers, 742 authors, and 1,786 variables such as ‘population birth rate’ and ‘linguistic complexity’. Our findings indicate a significant increase in the size of concept networks from 1886 to 2022, providing an account of the growth and diversification of evolutionary linguistics as a field. We describe eight major clusters of concepts, and characterize the connections within and between clusters. Finally, we identify hypotheses cutting across clusters of concepts that have a high-betweenness centrality, implying that they might have a higher impact on the field if proven right (or wrong). Furthermore, we discuss the role of databases in cultural evolution and scientometrics, emphasizing the value of interdisciplinary connections and the potential for further cross-disciplinary collaboration in the field of Evolutionary Linguistics.

Corporate governance and innovation: a predictive modeling approach using machine learning

The examination of the associations between internal corporate governance (CG) mechanisms and innovation faces challenges due to nonlinear patterns and complex interactions. Consequently, existing literature rarely reaches a consensus on the directions or strengths of these relationships. Furthermore, to investigate the CG–innovation association, prior research has predominantly relied on explanatory modeling, which involves applying statistical models to data to test correlational or causal hypotheses about theoretical constructs. These are the reasons why it remains unclear whether internal CG mechanisms, when considered collectively as an extensive array of interconnected variables, offer valuable insights for accurately predicting innovation. To address this gap, we analyze a dataset of research and development (R&D) projects from the Brazilian electricity sector by employing predictive modeling, which entails using statistical models or data mining algorithms to predict new observations, particularly using supervised machine learning (ML) methods. Our study demonstrates that a comprehensive set of variables representing internal CG mechanisms significantly enhances the predictive capabilities of ML algorithms for innovation. Furthermore, we illustrate how ML can illuminate nonlinear and non‐monotonic patterns, and interactions among variables, in the CG–innovation relationship. Our contribution to the literature encompasses three key aspects: introducing a predictive modeling approach to the discourse on the role of CG in innovation attainment through R&D endeavors, which can complement and enrich existing explanatory research; investigating non‐linear and non‐monotonic relationships, as well as interactions, in innovation prediction; and affirming the emerging body of literature that recognizes supervised ML as a valuable tool accessible to management researchers.

The causal effect of mental health on labor market outcomes: The case of stress-related mental disorders following a human-made disaster

As disasters increase due to climate change, population density, epidemics, and technology, information is needed about postdisaster consequences for people's mental health and how stress-related mental disorders affect multiple spheres of life, including labor-market attachment. We tested the causal hypothesis that individuals who developed stress-related mental disorders as a consequence of their disaster exposure experienced subsequent weak labor-market attachment and poor work-related outcomes. We leveraged a natural experiment in an instrumental variables model, studying a 2004 fireworks factory explosion disaster that precipitated the onset of stress-related disorders (posttraumatic stress disorder, anxiety, and depression) among individuals in the local community (N = 86,726). We measured labor-market outcomes using longitudinal population-level administrative data: sick leave, unemployment benefits, early retirement pension, and income from wages from 2007 to 2010. We found that individuals who developed a stress-related disorder after the disaster were likely to go on sickness benefit, both in the short- and long-term, were likely to use unemployment benefits and to lose wage income in the long term. Stress-related disorders did not increase the likelihood of early retirement. The natural experiment design minimized the possibility that omitted confounders biased these effects of mental health on work outcomes. Addressing the mental health and employment needs of survivors after a traumatic experience may improve their labor-market outcomes and their nations' economic outputs.

A Scalable Quantum Gate‐Based Implementation for Causal Hypothesis Testing

AbstractIn this work, a scalable quantum gate‐based algorithm for accelerating causal inference is introduced. Specifically, the formalism of causal hypothesis testing presented in [Nat Commun 10, 1472 (2019)] is considered. Through the algorithm, the existing definition of error probability is generalized, which is a metric to distinguish between two competing causal hypotheses, to a practical scenario. The results on the Qiskit validate the predicted speedup and show that in the realistic scenario, the error probability depends on the distance between the competing hypotheses. To achieve this, the causal hypotheses are embedded as a circuit construction of the oracle. Furthermore, by assessing the complexity involved in implementing the algorithm's subcomponents, a numerical estimation of the resources required for the algorithm is offered. Finally, applications of this framework for causal inference use cases in bioinformatics and artificial general intelligence are discussed.