Early parental causal language input predicts children’s later causal verb understanding

How does parental causal input relate to children’s later comprehension of causal verbs? Causal constructions in verbs differ across languages. Turkish has both lexical and morphological causatives. We asked whether (1) parental causal language input varied for different types of play (guided vs. free play), (2) early parental causal language input predicted children’s causal verb understanding. Twenty-nine infants participated at three timepoints. Parents used lexical causatives more than morphological ones for guided-play for both timepoints, but for free-play, the same difference was only found at Time 2. For Time 3, children were tested on a verb comprehension and a vocabulary task. Morphological causative input, but not lexical causative input, during free-play predicted children’s causal verb comprehension. For guided-play, the same relation did not hold. Findings suggest a role of specific types of causal input on children’s understanding of causal verbs that are received in certain play contexts.

The ABC of linear regression analysis: What every author and editor should know

Regression analysis is a widely used statistical technique to build a model from a set of data on two or more variables. Linear regression is based on linear correlation, and assumes that change in one variable is accompanied by a proportional change in another variable. Simple linear regression, or bivariate regression, is used for predicting the value of one variable from another variable (predictor); however, multiple linear regression, which enables us to analyse more than one predictor or variable, is more commonly used. This paper explains both simple and multiple linear regressions illustrated with an example of analysis and also discusses some common errors in presenting the results of regression, including inappropriate titles, causal language, inappropriate conclusions, and misinterpretation.

Causal and Associational Linking Language From Observational Research and Health Evaluation Literature in Practice: A systematic language evaluation

Background: Avoiding "causal" language with observational study designs is common publication practice, often justified as being a more cautious approach to interpretation. Objectives: We aimed to i) estimate the degree to which causality was implied by both the language linking exposures to outcomes and by action recommendations in the high-profile health literature ii) examine disconnects between language and recommendations, iii) identify which linking phrases were most common, and iv) generate estimates by which these phrases imply causality. Methods: We identified 18 of the most prominent general medical/public health/epidemiology journals, and searched and screened for articles published from 2010 to 2019 that investigated exposure/outcome pairs until we reached 65 non-RCT articles per journal (n=1,170). Two reviewers and an arbitrating reviewer rated the degree to which they believed causality had been implied by the language in abstracts based on written guidance. Reviewers then rated causal implications of linking words in isolation. For comparison, additional review was performed for full texts and for a secondary sample of RCTs. Results: Reviewers rated the causal implication of the sentence and phrase linking the exposure and outcome as None (i.e. makes no causal implication) in 13.8%, Weak in 34.2%, Moderate in 33.2%, and Strong in 18.7% of abstracts. Reviewers identified an action recommendation in 34.2% of abstracts. Of these action recommendations, reviewers rated the causal implications as None in 5.3%, Weak in 19.0%, Moderate in 42.8% and Strong in 33.0% of cases. The implied causality of action recommendations was often higher than the implied causality of linking sentences (44.5%) or commensurate (40.3%), with 15.3% being weaker. The most common linking word root identified in abstracts was "associate" (n=535/1,170; 45.7%) (e.g. "association," "associated," etc). There were only 16 (1.4%) abstracts using "cause" in the linking or modifying phrases. Reviewer ratings for causal implications of word roots were highly heterogeneous, including those commonly considered non-causal. Discussion: We found substantial disconnects between causal implications used to link an exposure to an outcome vs action implications made. This undercuts common assumptions about what words are often considered non-causal and that policing them eliminates causal implications. We recommend that instead of policing words; editors, researchers, and communicators should increase efforts at making research questions, as well as the potential of studies to answer them, more transparent.

Consistency of causal claims in observational studies: a review of papers published in a general medical journal

ObjectiveTo evaluate the consistency of causal statements in observational studies published in The BMJ.DesignReview of observational studies published in a general medical journal.Data sourceCohort and other longitudinal studies describing an exposure-outcome relationship published in The BMJ in 2018. We also had access to the submitted papers and reviewer reports.Main outcome measuresProportion of published research papers with ‘inconsistent’ use of causal language. Papers where language was consistently causal or non-causal were classified as ‘consistently causal’ or ‘consistently not causal’, respectively. For the ‘inconsistent’ papers, we then compared the published and submitted version.ResultsOf 151 published research papers, 60 described eligible studies. Of these 60, we classified the causal language used as ‘consistently causal’ (48%), ‘inconsistent’ (20%) and ‘consistently not causal’(32%). Eleven out of 12 (92%) of the ‘inconsistent’ papers were already inconsistent on submission. The inconsistencies found in both submitted and published versions were mainly due to mismatches between objectives and conclusions. One section might be carefully phrased in terms of association while the other presented causal language. When identifying only an association, some authors jumped to recommending acting on the findings as if motivated by the evidence presented.ConclusionFurther guidance is necessary for authors on what constitutes a causal statement and how to justify or discuss assumptions involved. Based on screening these papers, we provide a list of expressions beyond the obvious ‘cause’ word which may inspire a useful more comprehensive compendium on causal language.

Influence of causal language on causal understanding: A comparison between Swiss-German and Turkish

Young children have difficulties understanding untypical causal relations. While we know that hearing a causal description facilitates this understanding, less is known about what particular features of causal language are responsible for this facilitation. Here, we asked: (1) Do syntactic and morphological cues in the grammatical structure of sentences facilitate the extraction of causal meaning, and (2) do these different cues influence this facilitation to a different degree. We studied children learning either Swiss-German or Turkish, two languages which differ in their expression of causality. Swiss-German predominantly uses lexical causatives (e.g., schniidä (cut)), which lack a formal marker to denote causality. Turkish, alongside lexical causatives, uses morphological causatives, which formally mark causation (e.g., ye (eat) vs. yeDIr (feed)). We assessed 2.5- to 3.5-year-old children’s understanding of untypical cause-effect relations described with either non-causal language (e.g., Here is a cube and a car) or causal language using a pseudo-verb (e.g., lexical: The cube gorps the car). We tested n = 135 Turkish-learning (non-causal, lexical, and morphological conditions) and n = 90 Swiss-German-learning children (non-causal and lexical conditions). Children in both language groups performed better in the causal language condition(s) than the non-causal language condition. Further, Turkish-learning children’s performance in both the lexical and morphological conditions was similar to Swiss-German-learning children in the lexical condition, and did not differ from each other. These findings suggest that the structural cues of causal language support children’s understanding of untypical causal relations, regardless of the type of construction.

Conceptual Interplay between Elements of the Tort of Negligence

Chapter 3 examines how elements of the tort of negligence interact in critical conceptual ways and suggests that re-conceptualisation of aspects of those elements offers a more transparent and coherent framework. One argument is that a but-for concept of factual causation is inadequate and narrower than the concept evident in case law, one which can be identified by an ‘extended but-for test’. Another is that use of causal language at the analytical stage, which addresses the appropriate scope of responsibility for consequences of a specific breach (i.e. remoteness of damage), creates an obfuscating amalgam of the factual and normative. Similarly, by drawing a clear distinction between the forward-looking notion of the ‘scope of the duty’ and the backward-looking notion of the scope of responsibility for consequences the text argues that the principle that can coherently be extracted from the SAAMCO case is considerably narrower than the one being presented to courts.