22 papers · ranked by Valyu relevance
Manuj Mishra, James J. Fox, Michael Wooldridge
Causal games are probabilistic graphical models that enable causal queries to be answered in multiagent settings. They extend causal Bayesian networks by specifying decision and utility variables to represent the agents' degrees of freedom and objectives. In multi-agent settings, whether each agent decides on their…
Helene Charlotte Wiese Rytgaard, Mark van der Laan
This work develops a flexible inferential framework for nonparametric causal inference in time-to-event settings, based on stochastic interventions defined through multiplicative scaling of the intensity governing an intermediate event process. These interventions induce a family of estimands indexed by a scalar…
Mark J Johnson, Carl R May
Objectives Translating research evidence into routine clinical practice is notoriously difficult. Behavioural interventions are often used to change practice, although their success is variable and the characteristics of more successful interventions are unclear. We aimed to establish the characteristics of successful…
Eric A. Hoffman, Diego Salazar-Barreto, Kara E. Rudolph, Iván Díaz
This tutorial discusses a recently developed methodology for causal inference based on longitudinal modified treatment policies (LMTPs). LMTPs generalize many commonly used parameters for causal inference including average treatment effects, and facilitate the mathematical formalization, identification, and estimation…
James Liley
Predictive risk scores estimating probabilities for a binary outcome on the basis of observed covariates are common across the sciences. They are frequently developed with the intent of avoiding the outcome in question by intervening in response to estimated risks. Since risk scores are usually developed in complex…
Leire Sevillano‐Garayoa, Maddi Olano‐Lizarraga, Jesús Martín‐Martín
The rising prevalence of advanced illness poses growing challenges for family caregivers, requiring healthcare professionals to address an increasing array of caregiver needs. This systematic review explores the impact of at-home interventions for caregivers supporting individuals with advanced illness, examining…
Nancy Doyle, Almuth McDowall
Although dyslexia affects 5-8% of the workforce this developmental disorder is insufficiently researched within adult psychological research. Dyslexia confers legal protections wherein employers must provide ‘accommodations’ to support work performance, including coaching activities. Implementation of accommodations…
Wai Man Cheng, Timothy B. Smith, Marshall Butler, Tina M. Taylor + 1 more
'Devan Clayton'] Children with autism spectrum disorder (ASD) have been shown to benefit from parent-implemented interventions (PIIs). This meta-analysis improved on prior reviews of PIIs by evaluating RCTs and multiple potential moderators, including indicators of research quality. Fifty-one effect sizes averaged…
Victoria Hamilton, Gina-Maree Sartore, Michelle Macvean, Elbina Avdagic + 4 more
'Elbina Avdagic' 'Zvezdana Petrovic' 'Cathryn Hunter' 'Catherine Wade' 'Paul B. Tchounwou'] Brief family support interventions may be an effective and acceptable option when demands on services and pressures on families can often mean intensive, long-term family support interventions are an inefficient and unappealing…
Mary C Conry, Niamh Humphries, Karen Morgan, Yvonne McGowan + 4 more
Background Against a backdrop of rising healthcare costs, variability in care provision and an increased emphasis on patient satisfaction, the need for effective interventions to improve quality of care has come to the fore. This is the first ten year (2000-2010) systematic review of interventions which sought to…
Sungbin Shin, Yohan Jo, Sung Soo Ahn, Namhoon Lee
Concept bottleneck models (CBMs) are a class of interpretable neural network models that predict the target response of a given input based on its high-level concepts. Unlike the standard end-to-end models, CBMs enable domain experts to intervene on the predicted concepts and rectify any mistakes at test time, so that…
Rachel K. Schuck, Daina M. Tagavi, Kaitlynn M. P. Baiden, Patrick Dwyer + 7 more
'Patrick Dwyer' 'Zachary J. Williams' 'Anthony Osuna' 'Emily F. Ferguson' 'Maria Jimenez Muñoz' 'Samantha K. Poyser' 'Joy F. Johnson' 'Ty W. Vernon'] Proponents of autism intervention and those of the neurodiversity movement often appear at odds, the former advocating for intensive treatments and the latter arguing…
Chris Felton
Randomized controlled trials (RCTs) and person-level observational studies feature prominently in debates over social media harms. I highlight some under-acknowledged limitations of such evidence. Most important is that published RCTs typically identify effects of a \textit{local}, or small-scale, intervention: a…
Grace Branjerdporn, Ferrell Erlich, Karthikeyan Ponraj, Laura K. McCosker + 2 more
'Laura K. McCosker' 'Sabine Woerwag-Mehta' 'Mary Jane Rotheram-Borus'] (1) Background: Suicide is a leading cause of death among young people. Preventing suicide in young people is a priority. Caregivers play a vital role in ensuring interventions for young people experiencing suicide ideation and/or attempts are…
Authors not listed
A steep, age‑related drop in nicotinamide adenine dinucleotide (NAD+) now ranks among the most reproducible molecular signatures of human aging, driving metabolic slowdown, mitochondrial dysfunction, DNA‑repair deficits, chronic inflammation, and stem‑cell fatigue. Boost NAD+ for Anti‑Aging: A Multidimensional Review…
Authors not listed
Conservation chemistry is an emerging discipline focused on preventing the loss of biodiversity through molecular-level insight and intervention. As the planet enters a mass extinction event – driven by pollution, habitat loss, invasive species, climate change, overharvesting, and disease – chemical sciences offer…
Frederik Hytting Jørgensen, Luigi Gresele, Sebastian Weichwald
Causal Bayesian networks are 'causal' models since they make predictions about interventional distributions. To connect such causal model predictions to real-world outcomes, we must determine which actions in the world correspond to which interventions in the model. For example, to interpret an action as an…
Authors not listed
The therapeutic potential of cannabis remains constrained by persistent physiological side effects that limit both medical applications and user tolerability. This paper presents a theo- retical framework for addressing these limitations through coordinated multi-target pharma- cological intervention. By synthesizing…
Lisa G. Smithers, Alyssa C. P. Sawyer, Catherine R. Chittleborough, Neil Davies + 2 more
Success in school and the labour market is due to more than just high intelligence. Associations between traits such as attention, self-regulation, and perseverance in childhood, and later outcomes have been investigated by psychologists, economists, and epidemiologists. Such traits have been loosely referred to as…
Hongbo Wang, Yingzhu Zeng, Siwen Zeng
Fear extinction requires exposure to the conditioned stimulus (CS), yet patients with fear- and anxiety-related disorders often avoid the CS, thereby undermining extinction learning. Implementation intention (II) is a self-regulation strategy that automates goal-directed behavior through “if–then” planning. Building on…
Authors not listed
Aging is a natural process that is also influenced by some factors like food someone eats, lifestyle decisions, and impacts on general health. Despite the recognized role of nutrition in modulating the molecular and cellular mechanisms underlying aging, there is a lack of comprehensive exploration into potential…
Authors not listed
People of color in the United States are disproportionately and unfairly exposed to air pollution. Equity-oriented scientific evaluations quantifying these disparities often use population-average exposure metrics to capture the overall inequality within a system. Utilizing these metrics involves choices about the…