A Computational and Empirical Investigation of Graphemes in Reading

It is often assumed that graphemes are a crucial level of orthographic representation above letters. Current connectionist models of reading, however, do not address how the mapping from letters to graphemes is learned. One major challenge for computational modeling is therefore developing a model that learns this mapping and can assign the graphemes to linguistically meaningful categories such as the onset, vowel, and coda of a syllable. Here, we present a model that learns to do this in English for strings of any letter length and any number of syllables. The model is evaluated on error rates and further validated on the results of a behavioral experiment designed to examine ambiguities in the processing of graphemes. The results show that the model (a) chooses graphemes from letter strings with a high level of accuracy, even when trained on only a small portion of the English lexicon; (b) chooses a similar set of graphemes as people do in situations where different graphemes can potentially be selected; (c) predicts orthographic effects on segmentation which are found in human data; and (d) can be readily integrated into a full‐blown model of multi‐syllabic reading aloud such as CDP++ (Perry, Ziegler, & Zorzi, 2010). Altogether, these results suggest that the model provides a plausible hypothesis for the kind of computations that underlie the use of graphemes in skilled reading.     

Two routes to perspective: Simulation and rule‐use as approaches to mentalizing

We review evidence relating to children's ability to acknowledge false beliefs within a simulation account according to which our focus is set by default to the world as we know it: hence, our current beliefs assume salience over beliefs that do not fall into this category. The model proposes that the ease with which we imaginatively shift from this default depends on the salience of our current belief, relative to the salience of the belief that is being simulated. However, children do use a rule‐based approach for mentalizing in some contexts, which has the advantage of protecting them from the salience of their own belief. Rule‐based mentalizing judgements might be faster, cognitively easier and less prone to error, relative to simulation‐based judgements that are much influenced by salience. We propose that although simulation is primary, rule‐based approaches develop as a shortcut; we thus grow from individuals capable of using only simulation into individuals capable of both techniques.     

Screening for Suicidal Ideation and Attempts among Emergency Department Medical Patients: Instrument and Results from the Psychiatric Emergency Research Collaboration

Joint Commission National Patient Safety Goal 15 calls for organizations “to identify patients at risk for suicide.” Overt suicidal behavior accounts for 0.6% of emergency department (ED) visits, but incidental suicidal ideation is found in 3%–11.6%. This is the first multicenter study of suicide screening in EDs. Of 2,243 patients in six diverse emergency settings, 1,068 (47.7%) were screened with a brief instrument. Depression was endorsed by 369 (34.5%); passive suicidal ideation by 79 (7.3%); and active suicidal ideation by 24 (2.3%). One hundred thirty‐seven (12.8%) reported prior attempts, including 35 (3.3%) with current suicidal ideation. Almost half of those with current ideation had a prior attempt (43.8%) versus those without current ideation, 10.3%, χ² (1) = 75.59, p < .001. Twenty cases (25%) were admitted to medical services, but only 10 (12.5%) received mental health assessment; none were admitted directly to a psychiatry service. The prevalence of suicidal ideation here is similar to previous studies but the frequency of prior attempts has not been reported. The 35 cases with current ideation and prior attempt are at risk. As they did not present psychiatrically, they would likely have gone undetected. Despite reporting these cases to clinical staff, few received risk assessment.