Causal Statements Research Articles

Multiteam Semantics for Interventionist Counterfactuals: Probabilities and Causation

AbstractIn (Barbero and Sandu 2020 Journal of Philosophical Logic, 50, 471-521), we showed that languages encompassing interventionist counterfactuals and causal notions based on them (as e.g. in Pearl’s and Woodward’s manipulationist approaches to causation) as well as information-theoretic notions (such as learning and dependence) can be interpreted in a semantic framework which combines the traditions of structural equation modeling and of team semantics. We now present a further extension of this framework (causal multiteams) which allows us to talk about probabilistic causal statements. We analyze the expressivity resources of two causal-probabilistic languages, one finitary and one infinitary. We show that many causal-probabilistic notions from the literature on causal inference can already be expressed in the finitary language, and we prove a normal form theorem that throws a new light on Pearl’s “ladder of causation”. In addition, we provide an exact semantic characterization of the infinitary language, which shows that this language captures precisely those causal-probabilistic statements that do not commit us to any specific interpretation of probability; and we prove that no usual, countable language is apt for this task.

Investigating the link between students’ learning intentions and their learning outcomes: A clustered randomised controlled trial

We investigate the impact of repeated contextual nudging on task com- pletion and performance within the setting of traditional face-to-face education, adding to a literature which has focused on non-contextual nudges, provided contextual nudges in online learning settings, or used one-time nudges. We undertake a clustered randomised controlled trial on first-year Business School students at Heriot-Watt University, employing weekly nudges during tutorials to encourage students to establish learning intentions for the upcoming week. We rule out significant treatment effects from the nudging intervention on tutorial attendance, the most important predictor of final marks of all intermediate outcomes that we consider. We are unable to make causal statements on the effects of the intervention on final marks. Nonetheless, this experiment yields valuable insights into the dynamics of repeated contextual nudging within traditional educational settings as well as shedding light on aspects of student behaviour.

On Validity of Causal Statements

On Validity of Causal Statements

Socioeconomic and sociodemographic correlations to COVID-19 variability in the United States in 2020.

The COVID-19 pandemic provided an additional spotlight on the longstanding socioeconomic/health impacts of redlining and has added to the myriad of environmental justice issues, which has caused significant loss of life, health, and productive work. The Centers for Disease Control and Prevention (CDC) reports that a person with any selected underlying health conditions is more likely to experience severe COVID-19 symptoms, with more than 81% of COVID-19-related deaths among people aged 65 years and older. The effects of COVID-19 are not homogeneous across populations, varying by socioeconomic status, PM2.5 exposure, and geographic location. This variability is supported by analysis of existing data as a function of the number of cases and deaths per capita/1,00,000 persons. We investigate the degree of correlation between these parameters, excluding health conditions and age. We found that socioeconomic variables alone contribute to ~40% of COVID-19 variability, while socioeconomic parameters, combined with political affiliation, geographic location, and PM2.5 exposure levels, can explain ~60% of COVID-19 variability per capita when using an OLS regression model; socioeconomic factors contribute ~28% to COVID-19-related deaths. Using spatial coordinates in a Random Forest (RF) regressor model significantly improves prediction accuracy by ~120%. Data visualization products reinforce the fact that the number of COVID-19 deaths represents 1% of COVID-19 cases in the US and globally. A larger number of democratic voters, larger per-capita income, and age >65 years is negatively correlated (associated with a decrease) with the number of COVID cases per capita. Several distinct regions of negative and positive correlations are apparent, which are dominated by two major regions of anticorrelation: (1) the West Coast, which exhibits high PM2.5 concentrations and fewer COVID-19 cases; and (2) the middle portion of the US, showing mostly high number of COVID-19 cases and low PM2.5 concentrations. This paper underscores the importance of exercising caution and prudence when making definitive causal statements about the contribution of air quality constituents (such as PM2.5) and socioeconomic factors to COVID-19 mortality rates. It also highlights the importance of implementing better health/lifestyle practices and examines the impact of COVID-19 on vulnerable populations, particularly regarding preexisting health conditions and age. Although PM2.5 contributes comparable deaths (~7M) per year, globally as smoking cigarettes (~8.5M), quantifying any causal contribution toward COVID-19 is non-trivial, given the primary causes of COVID-19 death and confounding factors. This becomes more complicated as air pollution was reduced significantly during the lockdowns, especially during 2020. This statistical analysis provides a modular framework, that can be further expanded with the context of multilevel analysis (MLA). This study highlights the need to address socioeconomic and environmental disparities to better prepare for future pandemics. By understanding how factors such as socioeconomic status, political affiliation, geographic location, and PM2.5 exposure contribute to the variability in COVID-19 outcomes, policymakers and public health officials can develop targeted strategies to protect vulnerable populations. Implementing improved health and lifestyle practices and mitigating environmental hazards will be essential in reducing the impact of future public health crises on marginalized communities. These insights can guide the development of more resilient and equitable health systems capable of responding effectively to similar future scenarios.

Quality of life of families and siblings of children with cerebral palsy treated at a reference neurorehabilitation center in Brazil

ObjectivesTo investigate the associations between caregivers’ burden, family quality of life (QoL), and siblings’ QoL in Brazilian families of children with cerebral palsy, and to analyze siblings’ QoL using as a parameter the QoL of typically developed Brazilian children. MethodsIt was a cross-sectional study. The 212 families, 212 caregivers and 131 siblings completed the Family Quality of Life Scale, Burden Interview, and KIDSCREEN-27 Child and Adolescent Version and Parents Version questionnaires at a neurorehabilitation center in southeast Brazil. Univariable and multivariable models were used. ResultsFamily QoL significantly worsened as caregivers’ burden increased (95 % CI -0.66 to -0.38). Caregivers’ burden was significantly lower with increasing family QoL scores (95 % CI -0.52 to -0.30). Self-reported siblings’ QoL was significantly worse than that of their typically developed peers (95 % CI -7.6 to -3.6). Self-reported siblings’ QoL was significantly lower as siblings’ age (95 % CI -2.52 to -0.59) and caregivers’ burden (95 % CI -0.35 to -0.05) increased. Parent-reported siblings’ QoL was significantly lower with increasing caregivers’ burden (95 % CI -0.45 to -0.16) and higher as family QoL increased (95 % CI 0.09 to 0.37). ConclusionsThe cross-sectional nature of these data precludes any statement of causality. Family QoL worsened with higher caregivers’ burden levels. Lower caregivers’ burden scores were associated with a higher family QoL. Siblings’ QoL was impaired as compared to typically developed peers, worse among older siblings, and as caregivers’ burden increased and better with higher family QoL levels. Future multicenter studies may validate the generalizability of the present findings.

Quality of life of families and siblings of children and adolescents with meningomyelocele.

Children with meningomyelocele may require continuous care. Consequently, there is a risk for caregiver burden and impact on family quality of life (QoL), including siblings' QoL. Some studies analysed caregivers' burden and family QoL separately. However, none of these studies evaluated siblings' QoL and the associations between these three dimensions. This study investigated the associations between caregivers' burden, family QoL and siblings' QoL in Brazilian families of children with meningomyelocele and its correlations with sociodemographic, functional and clinical variables. Siblings' QoL was specifically assessed using as a parameter the QoL of typically developed Brazilian children. One hundred and fifty families, 150 caregivers and 68 siblings completed the Family Quality of Life Scale, Burden Interview, KIDSCREEN-27 Child and Adolescent Version and Parents Version questionnaires. Most families and caregivers reported a high family QoL and a low caregiver burden. Family QoL was significantly lower as caregivers' burden increased. Caregiver's burden was significantly lower with increasing family QoL levels. Self-reported siblings' QoL was significantly worse than that of typically developed peers. There were no significant differences between self and parent-reported siblings' QoL. Self-reported siblings' QoL was significantly worse as their age increased and better with increasing family QoL levels. Parent-reported siblings' QoL was significantly worse with increasing levels of caregiver's burden and significantly better as family QoL increased. There were no significant associations with functional and clinical variables. Despite the cross-sectional nature of the available data precludes any statements of causality, our results reinforce the relevance of knowing the factors that influence the QoL of families and siblings of children and adolescents with meningomyelocele and the relevance of actions aimed at reducing caregivers' burden, improving family QoL and meeting siblings' individual needs. Future multicenter studies may validate the generalizability of our findings.

On Different Operationalizations and Conceptualizations of the Tendency to Believe in Conspiracy Theories

Abstract: This commentary in response to Nera (2024, this issue) offers an overview of different operationalizations and conceptualizations of the tendency to believe in conspiracy theories. It distinguishes Conspiracy Mentality (the disposition to believe in any kind of conspiracy theory) from the Belief in Conspiracy Theories (described as latent variable or monological network underlying the belief in many popular and scientifically unwarranted conspiracy theories, sometimes also called conspiracy ideation or generalized conspiracy belief) and the belief in a specific conspiracy theory (for example surrounding the Apollo moonlanding or COVID-19). It emphasizes the need for researchers to be clear about their operationalization and conceptualization of the tendency to believe in conspiracy theories, especially when making causal statements about its impact on the belief in specific conspiracy theories.

Sevelamer Use and Mortality in People with Chronic Kidney Disease Stages 4 and 5 Not on Dialysis.

Rationale and objective: Data suggest that non-calcium-based binders, and specifically sevelamer, may lead to lower rates of death when compared with calcium-based binders in end-stage renal disease (ESRD) patients. However, the association between sevelamer use and mortality for those with non-dialysis-dependent chronic kidney disease (NDD-CKD) patients has been uncertain. Study design: Our research is presented in a prospective cohort study. Setting and participants: A total of 966 participants with NDD-CKD stages 4-5 were enrolled in the PECERA study from 12 centers in Spain. Exposure: The participants were treated with sevelamer. Outcome: This study yielded all-cause and cardiovascular mortality outcomes. Analytical approach: We conducted an association analysis between mortality and sevelamer use with time-dependent Cox proportional hazards models. Results: After a median follow-up of 29 months (IQR: 13-36 months), death occurred in 181 participants (19%), with cardiovascular (n = 95, 53%) being the leading cause of death. In a multivariable model, the adjusted hazard ratios (HRs) for patients under sevelamer treatment were 0.44 (95% CI, 0.22 to 0.88) and 0.37 (95% CI, 0.18 to 0.75) for all-cause and cardiovascular mortality, respectively, compared with those of untreated patients. Limitations: Some limitations include potential confusion via indication bias; causal statements about these associations cannot be made due to the observational nature of this study. Conclusions: In this prospective NDD-CKD cohort study, the administration of sevelamer was independently associated with lower all-cause and cardiovascular mortality, suggesting that non-calcium-based phosphate binders might be the first-line therapy for phosphate lowering in this population. Further interventional studies clarifying the risks and benefits of phosphate binders in NDD-CKD are warranted.

An Analysis of Studies Pertaining to Masks in Morbidity and Mortality Weekly Report: Characteristics and Quality of Studies through 2023

BackgroundThe purpose of this study was to describe and evaluate the nature and methodology of reports and appropriateness of conclusions in The Morbidity and Mortality Weekly Report (MMWR) pertaining to masks. Because MMWR has substantial influence on United States health policy and is not externally peer-reviewed, it is critical to understand the scientific process within the journal. Mask policies have been highly influenced by data published in the MMWR. MethodsRetrospective cross-sectional study of MMWR publications pertaining to masks through 2023. Outcomes included study design, whether the study was able to assess mask effectiveness, if results were statistically significant, if masks were concluded to be effective, if randomized evidence or conflicting data were mentioned or cited, and appropriateness of causal statements. ResultsThere were 77 studies, all published after 2019, that met our inclusion criteria. The most common study design was observational without a comparator group: 22/77 (28.6%); 0/77 were randomized; 23/77 (29.9%) assessed mask effectiveness; 11/77 (14.3%) were statistically significant, but 58/77 (75.3%) stated that masks were effective. Of these, 41/58 (70.7%) used causal language. One mannequin study used causal language appropriately (1.3%). None cited randomized data; 1/77 (1.3%) cited conflicting evidence. ConclusionsMMWR publications pertaining to masks drew positive conclusions about mask effectiveness >75% of the time despite only 30% testing masks and <15% having statistically significant results. No studies were randomized, yet over half drew causal conclusions. The level of evidence generated was low and the conclusions were most often unsupported by the data. Our findings raise concern about the reliability of the journal for informing health policy.

The use of causal language and inferences in observational shoulder arthroplasty database studies.

Over the last few decades, several databases and clinical registries have been used to generate studies for orthopedic surgery research including shoulder arthroplasty. Observational database studies present data that are best used to provide information regarding associations between variables but is unable to prove causation. Yet, there remains a tendency for authors to use causal language and conclusive statements in published shoulder arthroplasty literature using such databases. We systematically identified administrative database and registry studies on shoulder arthroplasty in 5 orthopedic journals from January 2020 to December 2021. Papers were independently graded by 2 reviewers for the presence, absence, or inconsistent use of causal language throughout the publication. χ2 analyses were conducted to determine the relationship between causality language and article characteristics including the journal of publication. There were 65 eligible articles. According to the reviewers, 67.7% of titles and abstracts were either consistently causal or inconsistently causal in language and inference. On reviewing the full text, 69.2% were found to contain some degree of causal language (38.5% consistently causal, 30.8% inconsistently causal). There were no statistically significant associations between the journal and title and abstract final grading (P=.863) or the journal and full-text grading (P=.726). The use of causal language remains highly prevalent in observational database studies related to shoulder arthroplasty. Understanding the limitations of observational database studies is paramount for accurate interpretation of these publications.

Propensity score methods to analyse attitudinal change during the early stages of the Covid-19 pandemic within the African Country of Malawi

The objective of this study is to determine attitudinal changes within the African country of Malawi during the early stages of the COVID-19 pandemic between the months of May and June 2020. This study is relevant and will serve as a baseline that will allow for tracking attitudinal change throughout the COVID-19 pandemic. This will give insight to areas where extra resources, information, healthcare workers, and information can be applied to the Malawi population should a similar event occur. Propensity score methods are used for this study as it is a methodology that allows for making causal statements about treatment effects, known here as the participants attitudes to COVID-19. Both single level and multilevel propensity score modelling methods are undertaken as there is an identified need for multilevel modelling which was undertaken using a fixed effects approach. This study highlights that the multilevel modeling methodology used for any study be carefully assessed and not just be granted in using a random effects methodology. This study identifies the utility of propensity score methods in highlighting methodological issues of a survey study. Propensity score methods highlighted a large, unbalanced dataset that shows possible bias in the undertaking of the survey. Further, Featured Indicator Variables are created in aiding contextual effect modelling and the interpretation of the results. This study although limited to the early stages of the COVID-19 pandemic within Malawi, serves as a baseline for longitudinal studies and interrupted time–series modelling. This study highlights determining attitudinal change, not only for Malawi but the methodology can be used for other countries in prediction, directing resources, information, health care workers, and services should a similar event occur.

Recent findings on organizational unlearning and intentional forgetting research (2019-2022).

This mini review aims at summarizing the current state-of-the-art of empirical unlearning and intentional forgetting (U/IF) research at the individual, team, and organizational level. It adds to an earlier review and incorporates 31 recent studies from 2019 to 2022. The review reveals that predictors based on the organization's adaptation context (e.g., competitive intensity), organization level (e.g., leadership exploration activities), individual task-related (e.g., features of the routines changed), and person-related level (e.g., cognitive control strategies) variables relate to process variables, such as the type of U/IF, the U/IF content (e.g., success beliefs or failure beliefs), and information processing variables (e.g., team information processing). The outcome variables are at the organizational level (e.g., cross-boundary innovation), team level performance level, the individual task performance level (e.g., errors), and person-related level (e.g., self-esteem). The analyzed studies at the team and organizational levels preferred cross-sectional study designs or in-depth qualitative methods, which severely limits the possibility of making causal statements. In contrast, at the individual-level studies use longitudinal designs as well to make temporal aspects of U/IF visible. But these individual level results are limited in terms of their generalizability to other levels. Even though all studies make valuable contribution to the understanding of antecedents and outcomes of U/IF, the temporal and process-related aspects of how U/IF unfolds at the different levels and subsequent options for its deliberate facilitation remain empirically little elaborated. It is proposed that in addition to studying the antecedents and consequences of U/IF in cross sectional designs, the topic needs more longitudinal designs to capture the nature of the U/IF processes in organizations.

Text to Causal Knowledge Graph: A Framework to Synthesize Knowledge from Unstructured Business Texts into Causal Graphs

This article presents a state-of-the-art system to extract and synthesize causal statements from company reports into a directed causal graph. The extracted information is organized by its relevance to different stakeholder group benefits (customers, employees, investors, and the community/environment). The presented method of synthesizing extracted data into a knowledge graph comprises a framework that can be used for similar tasks in other domains, e.g., medical information. The current work addresses the problem of finding, organizing, and synthesizing a view of the cause-and-effect relationships based on textual data in order to inform and even prescribe the best actions that may affect target business outcomes related to the benefits for different stakeholders (customers, employees, investors, and the community/environment).

Health Equity Implications of Missing Data among Youths with Childhood-onset Systemic Lupus Erythematosus: A Proof-of-Concept Study in the Childhood Arthritis and Rheumatology Research Alliance (CARRA) Registry.

Health disparities in childhood-onset systemic lupus erythematosus (cSLE) disproportionally impact marginalized populations. Socioeconomically-patterned missing data can magnify existing health inequities by supporting inferences that may misrepresent populations of interest. We assessed missing data and subsequent health equity implications among participants with cSLE enrolled in a large pediatric rheumatology registry. We evaluated co-missingness of 12 variables representing demographics, socioeconomic position, and clinical factors (e.g., disease-related indices) using Childhood Arthritis and Rheumatology Research Alliance (CARRA) Registry cSLE enrollment data (2015-2022; N=766). We performed logistic regression to calculate odds ratios (OR) and 95% confidence intervals (95%CI) for missing disease-related indices at enrollment (SLE Disease Activity Index, [SLEDAI-2K] and/or SLICC/ACR Damage Index [SDI]) associated with data missingness and linear regression to assess the association between socioeconomic factors and SLEDAI-2K at enrollment utilizing three analytic methods for missing data: 1) complete case analysis, 2) multiple imputation, and 3) non-probabilistic bias analyses-missing values imputed to represent extreme low or high disadvantage. On average, participants were missing 6.1% of data with over 50% of participants missing at least one variable. Missing data correlated most closely with variables within data categories (i.e., demographic). Government-assisted health insurance was associated with missing SLEDAI-2K and/or SDI compared to private health insurance (OR=2.04; 95%CI: 1.22,3.41). The different analytic approaches resulted in varying analytic sample sizes and fundamentally conflicting estimated associations. Our results support intentional evaluation of missing data to inform effect estimate interpretation and critical assessment of causal statements that might otherwise misrepresent health inequities. This article is protected by copyright. All rights reserved.

Project Evaluation and Performance of Roads Construction in Rwanda: A Case of Nyarutarama Property Developers COTRACO Projects

The general objective of this study was to determine the degree to which Rwandan road building performance is influenced by the evaluation of road projects. The specific goals were to examine the road construction project evaluation process and its effect on Rwanda's road construction performance, to assess the impact of formative project evaluation on Rwanda's road construction performance, and to evaluate the impact of summative project evaluation on Rwanda's road construction performance. Descriptive research design was adopted for this study as it assessed a sample at one specific point in time without trying to make inferences or causal statements; the target population is composed of sixty-six (66) fulltime workers of NPD – COTRACO Ltd in Rwanda who spends their working hours of the day in road construction activities in this company. The sampling technique was census. In this research work, questionnaires, and documentation data collection techniques were used. The collected data were analyzed using SPSS (version 23.0) software. It was first edited, categorized, or coded and computerized. Mean and standard deviation were utilized in descriptive statistics, while regression analysis was employed in inferential statistics to identify and demonstrate the strength of the link between the variables. The findings show that process evaluation relates positively with performance of road construction projects and cannot be concluded that this variable affects the dependent variable since (β=0.063, p˃0.05; p=0.360); There is a positive relationship between formative evaluation and performance of road construction of NPD-COTRACO as results are statistically significant since (β=0.875, p&lt;0.5; p=0.000); and summative evaluation relates positively with performance of road construction of NPD-COTRACO and cannot be concluded that this variable affects the dependent variable since (β=0.59, p˃0.5; p=0.265). The recommendation that construction companies need to have a budget covering the whole of the project as the budget affects the performance of road construction implementation was provided. Keywords: Project Evaluation, Performance of Roads Construction, Nyarutarama Property Developers COTRACO, Rwanda

Commentary: Establishing Causality in Quality Improvement Studies.

Commentary: Establishing Causality in Quality Improvement Studies.

Vertical pleiotropy explains the heritability of social science traits.

We contend that social science variables are the product of multiple partly heritable traits. Genetic associations with socioeconomic status (SES) may differ across populations, but this is a consequence of the intermediary traits associated with SES differences also varying. Furthermore, genetic data allow social scientists to make causal statements regarding the aetiology and consequences of SES.

An inventory tool to assess displacement data in the context of weather and climate-related events

Weather and climate-related events have already altered human mobility patterns and led to displacement. While the evidence base is low due to data gaps and scarcity, climate change is expected to reinforce disaster-related displacement. Here we systematically analyze how components of internal displacement data are related to disaster outcomes in Somalia, Afghanistan, the Marshall Islands and Bangladesh using a data inventory tool. We contribute the first programmatic approach to evaluate the evidence of extreme weather impacts on internal displacement in four distinct case studies. We find that the data evidence differs considerably from the disaster displacement process recorded qualitatively in reports. We provide a straightforward, bottom-up application guide that ultimately improves the understanding of changing disaster displacement risks for researchers and practitioners alike. We thereby show nuances in data availability and granularity for potential causal statements between climate change and internal displacement. We conclude that the implementation of data-focused climate policy and action could address obstacles to averting and minimizing disaster displacement.

Anthropogenic Contributions to the 2021 Pacific Northwest Heatwave

AbstractDaily maximum temperatures during the 2021 heatwave in the Pacific Northwest United States and Canada shattered century old records. Multiple causal factors, including anthropogenic climate change, contributed to these high temperatures, challenging traditional methods of attributing human influence. We demonstrate that the observed 2021 daily maximum temperatures are far above the bounds of Generalized Extreme Value distributions fitted from historical data. Hence, confidence in Granger causal inference statements about the human influence on this heatwave is low. Alternatively, we present a more conditional hindcast attribution study using two regional models. We performed ensembles of simulations of the heatwave to investigate how the event would have changed if it had occurred without anthropogenic climate change and with future warming. We found that global warming caused a ∼0.8°C–1°C increase in heatwave temperatures. Future warming would lead to a ∼5°C increase in heatwave temperature by the end of the 21st century.

The Peer Education Project to improve mental health literacy in secondary school students in England: a qualitative realist evaluation

BackgroundWorsening of adolescent mental health and exacerbated health inequalities after the COVID-19 pandemic calls for universal preventative strategies. The Mental Health Foundation's school-based Peer Education Project seeks to improve students' mental health literacy through peer educators (aged 14–18 years) teaching peer learners (aged 11–13 years) to recognise good and bad mental health, identify risk and protective factors, and seek help accordingly. Although previous before and after quantitative assessments have found the intervention to be effective, this realist evaluation aimed to qualitatively develop the theory of change, exploring how the mechanisms played out in different contexts to achieve the desired outcomes. MethodsOur initial programme theory was developed following expert stakeholder consultation and reviewing the literature. We divided mechanisms into resources and reasoning to explain how the intervention components (ie, resources), experienced within specific contexts, engendered responses in the participants (ie, reasoning), to produce observable outcomes. Data collected from six purposively recruited schools in England comprised staff interviews (n=11), student focus groups (n=15), and observations (n=5). Deductive and inductive analysis was undertaken, using NVivo-informed multiple causal statements represented as context-mechanism-outcome configurations (CMOcs), to test and refine the programme theory. FindingsWe created several distinct CMOcs. For example, in learners accustomed to didactic teaching methods (context), conversing with educators having similar life experience (mechanism resource) endorsed and destigmatised help-seeking behaviour (mechanism reasoning) and facilitated a realisation that seeking help was appropriate and acceptable (outcome). Other mechanisms included the following: learners perceiving the information as tailored and relevant, educators feeling empowered, and a cultural shift percolating across the school. InterpretationOur findings show how peer education can work to improve mental health literacy, which will inform changes to the intervention to maximise its effectiveness in different operational contexts. Future research could test our theory of change in a randomised controlled trial, and examine impacts on inequalities in a more diverse sample. FundingNational Institute for Health and Care Research School for Public Health Research.