Causal Mechanisms Research Articles

Telerehabilitation of patients with stroke: Initial program theories for successful implementation.

Telerehabilitation has proven effective for stroke survivors, yet it is slowly implemented. We developed Initial Program Theories (IPTs) that focus on the telerehabilitation of stroke survivors in the United States to uncover the possible causal relationship between implementation strategies and outcomes. We created a conceptual framework to steer the development of IPTs. Then, we extracted concepts from theoretical frameworks reported in telemedicine implementation literature combined with feedback meetings with stakeholders with relevant experience. We developed a framework for implementing telerehabilitation that includes implementation levels, contextual domains, telerehabilitation technology, implementation phases, actors, targets, mechanisms, and outcomes. We created 27 IPTs that specify telerehabilitation interventions, implementation strategies, actors, targets, context, implementation mechanisms, and outcomes. The IPTs were refined and validated through feedback meetings. This study adds to the relatively scarce literature on IPT development. For each IPT, we elaborated on the implementation mechanism and how it could facilitate or hinder telerehabilitation implementation, an essential insight for researchers and professionals to plan successful implementation strategies. Understanding causal mechanisms helps identify implementation strategies that will work in the U.S. context and improve weak implementation strategies that are potentially significant or commonly used.

The Impact of Chinese Overseas Chinese Contributing to the Dissemination of Traditional Chinese Medicine on Enhancing China's Cultural Soft Power in the Southeast Asian Region

Traditional Chinese medicine culture is rooted in the excellent traditional Chinese culture, has a deep cultural heritage and unique value. It is an important part of the soft power of Chinese culture. With the recent increase in the number of overseas Chinese migrating to Southeast Asian countries, the role of overseas Chinese in the international dissemination of traditional Chinese medicine (TCM) is becoming increasingly significant. The overseas dissemination of Chinese medicine is conducive to helping Chinese medicine culture to go out and boosting China's cultural soft power in Southeast Asia. This paper applies the causal mechanism, taking Thailand as an example, to analyse the three basic ways of international communication of Chinese overseas Chinese: Chinese media, Chinese associations, and Chinese education, and analyses how the dissemination of Chinese traditional medicine has helped China to improve its cultural soft power in Southeast Asia, which is of great practical significance to China's efforts to promote the mutual understanding of civilizations and people's hearts and minds, and to promote opening up to the outside world and economic development.

RCDi: Robust Causal Direction Inference Using INUS-Inspired Asymmetry with the Solomonoff Prior

Investigating causal interactions between entities is a crucial task across various scientific domains. The traditional causal discovery methods often assume a predetermined causal direction, which is problematic when prior knowledge is insufficient. Identifying causal directions from observational data remains a key challenge. Causal discovery typically relies on two priors: the uniform prior and the Solomonoff prior. The Solomonoff prior theoretically outperforms the uniform prior in determining causal directions in bivariate scenarios by using the causal independence mechanism assumption. However, this approach has two main issues: it assumes that no unobserved variables affect the outcome, leading to method failure if violated, and it relies on the uncomputable Kolmogorov complexity (KC). In addition, we employ Kolmogorov’s structure function to analyze the use of the minimum description length (MDL) as an approximation for KC, which shows that the function class used for computing the MDL introduces prior biases, increasing the risk of misclassification. Inspired by the insufficient but necessary part of an unnecessary but sufficient condition (INUS condition), we propose an asymmetry where the expected complexity change in the cause, due to changes in the effect, is greater than the reverse. This criterion supplements the causal independence mechanism when its restrictive conditions are not met under the Solomonoff prior. To mitigate prior bias and reduce misclassification risk, we introduce a multilayer perceptron based on the universal approximation theorem as the backbone network, enhancing method stability. Our approach demonstrates a competitive performance against the SOTA methods on the TCEP real dataset. Additionally, the results on synthetic datasets show that our method maintains stability across various data generation mechanisms and noise distributions. This work advances causal direction determination research by addressing the limitations of the existing methods and offering a more robust and stable approach.

Multi-omic profiling of sarcopenia identifies disrupted branched-chain amino acid catabolism as a causal mechanism and therapeutic target

Multi-omic profiling of sarcopenia identifies disrupted branched-chain amino acid catabolism as a causal mechanism and therapeutic target

Plant-Based vs. Animal-Based Diets: Appetitive Traits and Dietary Patterns in Adults Based on Cross-Sectional Surveys

Background: Dietary patterns play a crucial role in shaping eating behaviours and influencing health outcomes, such as body weight. Understanding how appetitive traits differ between plant-based and animal-based diets can provide insights into dietary strategies for weight management and improved health. Objectives: The aim of this study was to analyse the relationships between appetitive traits, as measured by the Adult Eating Behaviour Questionnaire (AEBQ), and dietary patterns in adults consuming plant-based or animal-based diets. It examined how these dietary patterns influence body mass index (BMI) and explored the differences in appetite-related traits between groups with different levels of plant and animal product consumption. Methods: A cross-sectional survey of 553 Polish adults was conducted using validated questionnaires, including the AEBQ and a food frequency questionnaire (FFQ). The participants were categorised into four dietary groups: high intake of both plant and animal products, low intake of both, plant-based diet, and animal-based diet. The data were analysed using SPSS version 14.0 software. Results: The participants on a plant-based diet had significantly lower BMIs and slower eating rates than those on an animal-based diet. Positive correlations were observed between ’food approach’ traits (e.g., food responsiveness, emotional overeating) and BMI, particularly in individuals with higher animal product consumption. Conversely, ’food avoidance’ traits (e.g., food fussiness, slowness in eating) were more prevalent among those on a plant-based diet. Conclusions: The results suggest that plant-based diets are associated with favourable appetitive traits and a lower BMI. These findings highlight the potential of plant-based diets to support weight control and improve eating behaviours. Further research is warranted to investigate the causal mechanisms underlying these associations.

A Systems Perspective of How Community-Engaged Public Health Addresses Social Determinants of Health: A Case Study of a Population-Based COVID-19 Testing Program

Context: Despite the recognition that social determinants of health (SDOH) are key to improving the health of all communities, the causality and specific mechanisms through which SDOH impacts health behaviors and outcomes are often ambiguous. Objective: The aim of this study was to use systems thinking to document pathways through which SDOH affected health-seeking behaviors and identify how community engagement strategies intervened to address SDOH barriers. Design: We leveraged the case context of a large federal initiative (Rapid Acceleration of Diagnostics-Underserved Populations [RADx-UP]) designed to improve COVID-19 testing for underserved populations through community-engaged and participatory approaches. First, we used structured sessions with RADx-UP partners to create causal maps that documented relationships between factors relevant to SDOH, a health-seeking behavior (COVID-19 testing), and community engagement strategies. Second, we searched, reviewed, and tied evidence from RADx-UP peer-reviewed literature to contextualize the causal maps. Results: We identified 17 unique pathways that linked SDOH to COVID-19 testing. The map also highlighted 3 mechanisms through which the community engagement addressed SDOH: (1) improving access to testing, (2) addressing health and digital literacy, and (3) conducting social needs screening and assistance. Conclusions: Our findings highlighted the complexity of public health issues such as COVID-19 and how community engagement is critical to addressing SDOH and health equity. Importantly, dedicating resources to community engagement created positive reinforcing dynamics to improve the health of communities; however, as COVID-19 became better managed, funding also diminished and decreased the capacity for community-engaged efforts. Research in public health needs to focus on understanding and reshaping systems that better support community-engaged efforts.

Multi-INTACT: integrative analysis of the genome, transcriptome, and proteome identifies causal mechanisms of complex traits

We present multi-integration of transcriptome-wide association studies and colocalization (Multi-INTACT), an algorithm that models multiple “gene products” (e.g., encoded RNA transcript and protein levels) to implicate causal genes and relevant gene products. In simulations, Multi-INTACT achieves higher power than existing methods, maintains calibrated false discovery rates, and detects the true causal gene product(s). We apply Multi-INTACT to GWAS on 1408 metabolites, integrating the GTEx expression and UK Biobank protein QTL datasets. Multi-INTACT infers 52 to 109% more metabolite causal genes than protein-alone or expression-alone analyses and indicates both gene products are relevant for most gene nominations.

Golgi condensation causes intestinal lipid accumulation through HIF-1α-mediated GM130 ubiquitination by NEDD4.

The breakdown of Golgi proteins disrupts lipid trafficking, leading to lipid accumulation in the small intestine. However, the causal mechanism of the effects of Golgi protein degradation on the Golgi structure related to lipid trafficking in the small intestine remains unknown. Here we find that Golgi protein degradation occurs under hypoxic conditions in high-fat-diet-fed mice. Hypoxia-induced degradation promotes structural changes in the Golgi apparatus, termed 'Golgi condensation'. In addition, hypoxia-inducible factor 1α (HIF-1α) activation enhances Golgi condensation through the ubiquitination and degradation of Golgi matrix protein 130 (GM130), which is facilitated by neural precursor cell expressed developmentally downregulated protein 4 (NEDD4). Golgi condensation upon exposure to hypoxia promotes lipid accumulation, apolipoprotein A1 retention and decreased chylomicron secretion in the intestinal epithelium. Golgi condensation and lipid accumulation induced by GM130 depletion are reversed by exogenous GM130 induction in the intestinal epithelium. Inhibition of either HIF-1α or NEDD4 protects against GM130 degradation and, thereby, rescues cells from Golgi condensation, which further increases apolipoprotein A1 secretion and lipid accumulation both in vivo and in vitro. Furthermore, the HIF-1α inhibitor PX-478 prevents Golgi condensation, which decreases lipid accumulation and promotes high-density lipoprotein secretion in high-fat-diet-fed mice. Overall, our results suggest that Golgi condensation plays a key role in lipid trafficking in the small intestine through the HIF-1α- and NEDD4-mediated degradation of GM130, and these findings highlight the possibility that the prevention of structural modifications in the Golgi apparatus can ameliorate intestinal lipid accumulation in obese individuals.

Hydroxyurea Therapy and Sleep-Disordered Breathing in Children With Sickle Cell Disease.

Bidirectional relationships exist among sickle cell disease (SCD), sleep-disordered breathing (SDB), and hydroxyurea therapy, and this complex interplay poses challenges to research attempting to elucidate causal mechanisms and determine therapeutic targets. We therefore set out to study all three components of this clinical triad simultaneously (SCD, SDB, and hydroxyurea therapy), documenting correlations and suggesting underlying pathophysiological mechanisms. Hydroxyurea therapy was associated with improved SDB and with decreased inflammation, implicating the anti-inflammation effects of hydroxyurea as a plausible mechanism driving these correlations. These results underscore the need for longitudinal studies to elucidate causal relationships.

A critical assessment of male HIV/AIDS patients' satisfaction with antiretroviral therapy and its implications for sustainable development in Sub-Saharan Africa.

The emergence of unique and destructive viruses, such as COVID-19, has claimed lives, disrupted health systems and diverted resources from addressing the needs of male HIV/AIDS patients in the context of antiretroviral therapy and other HIV/AIDS-related issues. This study aims to assess male HIV/AIDS patients' satisfaction with antiretroviral therapy and its implications for sustainable development in Sub-Saharan Africa. Satisfaction, word-of-mouth, trust and revisit intention were the variables in the research model. A quantitative method was utilized. Data were collected from 400 male HIV/AIDS patients who received medical attention from hospitals in Gombe State, Nigeria, utilizing the convenience sampling method. SmartPLS was used for data analysis. The results show that satisfaction has a positive impact on trust, word-of-mouth and revisit intention. Furthermore, trust and word-of-mouth had a significant impact on revisit intentions. Word-of-mouth played a significant mediating role in the relationship between satisfaction and revisit intention. Trust played an insignificant mediating role between satisfaction and revisit intention. Additionally, word-of-mouth had a significant mediating effect on the relationship between trust and revisit intention. Healthcare organisations should prioritise patient satisfaction because it influences their likelihood of returning. Addressing the needs of male HIV patients can significantly enhance their overall healthcare experience, which would lead them to spread positive word of mouth. Healthcare administrators should make it a top priority to provide superior services that match or exceed patient expectations. The study used quantitative data and focused on the male gender. Also, the empirical research is carried out in public hospitals; however, there are some differences between the types of hospitals in terms of the factors that affect male HIV/AIDS patients' revisits. We employed a cross-sectional study. As a result, we recommend expanding it into a longitudinal study, as it allows the researcher to validate the causal mechanism and obtain results that are more generalizable. Healthcare managers should actively encourage positive patient reviews and recommendations. Setting up systems to record and distribute patient success stories can improve the hospital's reputation and attract new patients. Increased word-of-mouth advertising can naturally result from encouraging positive encounters and outcomes. Healthcare administrators should establish channels for sharing information regarding therapies, procedures and support services that are transparent and easy to obtain. Patients' intentions to return for follow-up appointments can be favourably influenced by education on the value of ongoing care. Male HIV/AIDS patients who are satisfied with their care have a tendency to trust medical professionals more, which promotes enhanced therapeutic outcomes and greater compliance with treatment regimens. Positive comments from those with the condition can also reduce stigma and motivate community members to seek treatment, fostering a supportive environment for those living with HIV/AIDS. The study emphasises how important it is for patients and healthcare providers to have stronger, greater empathy connections, which could contribute to decreasing health disparities. The study investigates the effect of satisfaction on the revisit intention of male HIV/AIDS patients and also highlights how trust and WOM mediate this relationship.

Teacher Turnover, Social Capital, and Improvement: How Instability Disrupts Schools

Teacher turnover is a persistent policy concern in public education. Researchers have documented negative impacts of turnover on student outcomes; yet we know little about the causal mechanisms by which turnover influences, or disrupts, schools’ efforts to improve. In our longitudinal qualitative study, we examined how turnover affects relationships, trust, and shared knowledge in organizations—that is, organizational social capital—in ways that can impede school improvement efforts. We found that teacher turnover depletes organizational social capital by disrupting networks and relationships between teachers working in teams, weakening shared meanings and goals in schools, and impeding teachers’ ability to collectively engage in problem-solving and learning. We illuminate the hidden ways in which instability undermines improvement efforts and strains organizations.

Thinking (about peace science) in time

In this Presidential Address, I lay out three research streams in which my findings were valid when published, but which may have been time-bound to a particular period in global history. I identify the period in which major shifts appear to have taken place across all three research areas and speculate as to which changes in the global system may have interfered with the causal processes and mechanisms underlying those findings. I use this exercise as a way of demonstrating the importance of study extensions, inductive practices, descriptive and observational data, and fieldwide synthesis and collaboration in describing the emerging international order in which we now do peace science.

Study on the Causes of Wellbore Leakage in Carbon Capture, Utilization, and Storage—Enhanced Oil Recovery

This study investigates wellbore leakage accidents associated with Carbon Capture, Utilization, and Storage Enhanced Oil Recovery (CCUS-EOR) to identify causal factors, clarify their degrees of influence, hierarchical structures, and substantive roles, while revealing the causal mechanisms behind these incidents to promote the safe development of CCUS-EOR. A distinctive aspect of this research is its integrated framework, which effectively combines the theory of integrated safety management with advanced methodologies such as the Decision-Making Trial and Evaluation Laboratory (DEMATEL), Interpretive Structural Models (ISM), and Cross-Impact Matrix Multiplication (MICMAC) to systematically analyze the interdependencies among risk factors. This comprehensive approach provides a nuanced understanding of the interactions among the 20 identified influencing factors across four domains, organized into a multilayered, three-stage structure. Furthermore, the study uncovers two critical causal pathways for wellbore leakage, namely F17 (lack of supervision and feedback) → F20 (inadequate safety investment) → F16 (lack of education and training) → F3 (weak safety awareness) → F9 (improper material selection) and F13 (high geological activity) → F11 (poor reservoir properties) → F6 (corrosion and aging failure), offering unique insights into risk dynamics that remain underexplored in the existing literature. This study could be enhanced in future research by taking into account a broader spectrum of causal factors, incorporating scenario simulations to facilitate a more comprehensive analysis, and involving a greater number of experts from diverse fields to enrich the insights derived.

Network analyses of brain tumor multiomic data reveal pharmacological opportunities to alter cell state transitions

Glioblastoma Multiforme (GBM) remains a particularly difficult cancer to treat, and survival outcomes remain poor. In addition to the lack of dedicated drug discovery programs for GBM, extensive intratumor heterogeneity and epigenetic plasticity related to cell-state transitions are major roadblocks to successful drug therapy in GBM. To study these phenomenon, publicly available snRNAseq and bulk RNAseq data from patient samples were used to categorize cells from patients into four cell states (i.e., phenotypes), namely: (i) neural progenitor-like (NPC-like), (ii) oligodendrocyte progenitor-like (OPC-like), (iii) astrocyte-like (AC-like), and (iv) mesenchymal-like (MES-like). Patients were subsequently grouped into subpopulations based on which cell-state was the most dominant in their respective tumor. By incorporating phosphoproteomic measurements from the same patients, a protein–protein interaction network (PPIN) was constructed for each cell state. These four-cell state PPINs were pooled to form a single Boolean network that was used for in silico protein knockout simulations to investigate mechanisms that either promote or prevent cell state transitions. Simulation results were input into a boosted tree machine learning model which predicted the cell states or phenotypes of GBM patients from an independent public data source, the Glioma Longitudinal Analysis (GLASS) Consortium. Combining the simulation results and the machine learning predictions, we generated hypotheses for clinically relevant causal mechanisms of cell state transitions. For example, the transcription factor TFAP2A can be seen to promote a transition from the NPC-like to the MES-like state. Such protein nodes and the associated signaling pathways provide potential drug targets that can be further tested in vitro and support cell state-directed (CSD) therapy.

Burning gig, rewarding risk: Effects of dual exposure to incentive structure and heat condition on risky driving among on-demand food-delivery motorcyclists in Kaohsiung, Taiwan

The gig economy, characterized by short-term, task-based work facilitated via digital platforms, has raised various occupational safety concerns, including road safety risks and heat exposure faced by on-demand food delivery (ODFD) workers. Often using open modes of transportation, such as motorcycles and bicycles, these workers have minimal physical protection and direct environmental exposure while working long hours on the road, interacting with larger vehicles. Prior research has suggested that their road risks result from prevalent risky driving incentivized by platform-established business models, but quantitative evidence is lacking. Furthermore, while prolonged heat exposure may contribute to increased risky driving, our understanding of this relationship remains limited. This study investigates the impact of dual exposures to incentive structure and heat condition on risky driving among ODFD motorcyclists in Kaohsiung, Taiwan. A wearable sensing scheme was implemented, tracking a cohort of 40 ODFD workers during their work shifts in real time, collecting data on their speed, acceleration/deceleration patterns, incentive issuances, and heat exposure. Through a case-crossover approach, generalized linear cross-level mixed-effects models were employed to demonstrate the impact of incentive issuance on increasing risky driving among ODFD workers, including faster driving speeds, higher risks of speeding, harsher acceleration and braking, and more erratic acceleration patterns. Additionally, this study reveals that heat exposure, characterized by higher temperatures and humidity levels, exacerbates speed-related risky driving. These findings advance our understanding of causal mechanisms in two key areas of literature: firstly, the road safety risks faced by ODFD gig workers, and secondly, the broader relationship between heat exposure and risky driving. This research offers insights for policymakers to mitigate risky driving among ODFD workers, which is crucial in the context of climate change, where such urban economic dynamics may amplify climate-related inequities and place disproportionate safety burdens on vulnerable workers within the rapidly evolving gig economy.

The impact of air pollution on career changes among Chinese workers

The influence exerted by air pollution on interregional workforce migration has garnered considerable attention in ecological economics over time; however, relatively scant consideration has been given to its effects on occupational transition dynamics. This study presents an empirical examination of the influence of air pollution on job changes among the working population and seeks to understand the underlying causal mechanisms. By merging detailed micro-level survey data with regional Fine particulate matter (PM2.5) data from Chinese counties spanning the years 1997 to 2015, we have constructed an extensive database to support our analysis. The study revealed that air pollution has a significant negative impact on the likelihood of career switching. Mechanistic analysis indicates that changes in wage compensation, as well as declines in health status, serve as the primary pathways through which air pollution exerts its influence. To reduce the welfare loss caused by air pollution, it is crucial to prioritize the welfare benefits and health conditions of the labor force.

Unraveling the depth-dependent causal dynamics of methanogenesis and methanotrophy in a high-latitude fen peatland

Abstract The dynamics of methane (CH4) cycling in high-latitude peatlands through different pathways of methanogenesis and methanotrophy are still poorly understood due to the spatiotemporal complexity of microbial activities and biogeochemical processes. Additionally, long-term in situ measurements within soil columns are limited and associated with large uncertainties in microbial substrates (e.g., dissolved organic carbon, acetate, hydrogen). To better understand CH4 cycling dynamics, we first applied an advanced biogeochemical model, ecosys, to explicitly simulate methanogenesis, methanotrophy, and CH4 transport in a high-latitude fen (within the Stordalen Mire, northern Sweden). Next, to explore the vertical heterogeneity in CH4 cycling, we applied the PCMCI/PCMCI+ causal detection framework with a bootstrap aggregation method to the modeling results, characterizing causal relationships among regulating factors (e.g., temperature, microbial biomass, soil substrate concentrations) through acetoclastic methanogenesis, hydrogenotrophic methanogenesis, and methanotrophy, across three depth intervals (0-10 cm, 10-20 cm, 20-30 cm). Our results indicate that temperature, microbial biomass, and methanogenesis and methanotrophy substrates exhibit significant vertical variations within the soil column. Soil temperature demonstrates strong causal relationships with both biomass and substrate concentrations at the shallower depth (0-10 cm), while these causal relationships decrease significantly at the deeper depth within the two methanogenesis pathways. In contrast, soil substrate concentrations show significantly greater causal relationships with depth, suggesting the substantial influence of substrates on CH4 cycling. CH4 production is found to peak in August, while CH4 oxidation peaks predominantly in October, showing a lag response between production and oxidation. Overall, this research provides important insights into the causal mechanisms modulating CH4 cycling across different depths, which will improve carbon cycling predictions, and guide the future field measurement strategies.

Mitochondrial Dysfunction Correlates with Brain Amyloid Binding, Memory, and Executive Function in Down Syndrome: Implications for Alzheimer’s Disease in Down Syndrome

Background/Objectives: Mitochondrial dysfunction is increasingly recognized as a central contributor to neurodegenerative diseases and age-related cognitive decline. Individuals with Down syndrome (DS) are at high risk of neurodegeneration due to Alzheimer’s disease (AD). This study aims to explore the relationship between mitochondrial dysfunction, brain amyloid-beta (Aβ) deposition, and cognitive decline in this population. Methods: We investigated mitochondrial function, brain amyloid-beta burden, and cognitive performance in a pilot study of a cohort of 10 eligible adults with DS selected from a sample of 28 individuals with DS. Phosphorus-31 magnetic resonance spectroscopy (31P-MRS) was used to assess mitochondrial function in skeletal muscle using a post-exercise paradigm, while positron emission tomography using 11C-Pittsburgh compound B (PiB-PET) measured brain Aβ deposition. Cognitive performance was evaluated using the Cambridge Cognitive Examination adapted for individuals with Down syndrome (CAMCOG-DS) and executive function batteries. Results: Significant correlations were observed between slowed phosphocreatine (PCr) recovery in muscle and increased Aβ deposition in key brain regions, particularly the striatum. Cognitive performance inversely correlated with mitochondrial function, with pronounced deficits in memory and executive function tasks. Notably, an individual carrying the APOE-ε4 allele exhibited the poorest mitochondrial function, highest Aβ burden, and most severe cognitive impairment, suggesting a potential interaction between genetic risk and mitochondrial health. Conclusions: These findings highlight the role of mitochondrial dysfunction in DS-associated AD (DSAD) and its impact on cognition in adults. The results support targeting mitochondrial pathways as a potential therapeutic strategy to mitigate AD progression in DS populations. Further research with larger cohorts and longitudinal designs is needed to clarify causative mechanisms and develop effective interventions.

The longitudinal network of peer problems and emotional symptoms among Australian adolescents: Bayesian structure learning of directed acyclic graphs.

Adolescence is a period in which peer problems and emotional symptoms markedly increase in prevalence. However, the causal mechanisms regarding how peer problems cause emotional symptoms at a behavioral level and vice versa remain unknown. To address this gap, the present study investigated the longitudinal network of peer problems and emotional symptoms among Australian adolescents aged 12-14 years. Data were from the Longitudinal Study of Australian Children. The complete case samples included adolescents who participated in the Longitudinal Study of Australian Children B (n = 2,694) or K (n = 3,144) Cohorts at two study follow-ups (ages 12 and 14). Peer problems and emotional symptoms were measured with the self-report Strengths and Difficulties Questionnaire. The analytical steps were (a) in Study 1, a causal discovery algorithm, Bayesian structure learning of directed acyclic graphs (DAGs), was used to identify the longitudinal network in the K Cohort; (b) the DAG discovered was evaluated with Bayesian structural equation modeling in an independent sample (the B Cohort) and compared against a DAG established through expert knowledge; and (c) in Study 2, the longitudinal network was again evaluated but considered contemporaneous effects. The empirically discovered DAG provided a better explanation of independent data than the expert DAG. Based on the discovered DAG, several plausible causal effects were identified such as that being bullied at age 12 negatively affected popularity at age 14. This study provides new insights into potential causal effects established between peer problems and emotional symptoms among Australian adolescents aged 12-14 years. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Causal Inference for Recommendation: Foundations, Methods and Applications

Recommender systems are important and powerful tools for various personalized services. Traditionally, these systems use data mining and machine learning techniques to make recommendations based on correlations found in the data. However, relying solely on correlation without considering the underlying causal mechanism may lead to various practical issues such as fairness, explainability, robustness, bias, echo chamber and controllability problems. Therefore, researchers in related area have begun incorporating causality into recommendation systems to address these issues. In this survey, we review the existing literature on causal inference in recommender systems. We discuss the fundamental concepts of both recommender systems and causal inference as well as their relationship, and review the existing work on causal methods for different problems in recommender systems. Finally, we discuss open problems and future directions in the field of causal inference for recommendations.