Transition to suicide ideation and attempt among emergency room patients.

BACKGROUND: Suicidal thoughts and behaviours (STB) represent a persistent and serious public health problem, and suicide is among the leading causes of death worldwide. We focus on predictors of transition rates and time courses through the STB spectrum among psychiatric emergency room (PER) patients. AIMS: We aimed to investigate (a) whether currently suicidal patients had prior referrals to the PER, (b) for which reason they were previously referred to the PER and (c) the timing of this referral. METHOD: We performed a retrospective study spanning 20 years with 24 815 PER referrals. Descriptive statistics of patients' sociodemographic and clinical characteristics are provided and expressed as weighted proportions and means. Logistic regression was used to identify risk profiles of patients who had a higher chance of being referred for reasons of STB given their PER history. Multiple imputation and data weighting techniques were implemented. RESULTS: STB among PER patients was persistent and led to repeated referrals (up to five times more likely), often within a short period (18% <1 month). Those previously referred for ideation/plan had 66% higher risk of making the transition to suicide attempt, with 25% making this transition within a month after previous referral. This is similar to the transition from depressed mood to suicide ideation/plan. CONCLUSIONS: STBs in PER patients are persistent and lead to repeated referrals, often within a short period, including transitions to more severe forms of STB.

Convergent Validity of 2 Widely Used Methodologies for Calculating the Hospital Standardized Mortality Ratio in Flanders, Belgium.

OBJECTIVES: To assess their construct validity, we compared results from 2 models used for estimating hospital standardized mortality ratios (HSMRs) in Belgium. The method of the Flemish Hospital Network (FHN) is based on a logistic regression for each of the 64 All Patient Refined Diagnosis-Related Groups that explain 80% of mortality and uses the Elixhauser score to correct for comorbidities. (H)SMRs published on the 3M-Benchmark-Portal are calculated by a simpler indirect standardization for All Patient Refined Diagnosis-Related Groups and risk of mortality (ROM) at discharge. METHODS: We used administrative data from all eligible hospital admissions in 22 Flemish hospitals between 2016 and 2019 (FHN, n = 682,935; 3M, n = 2,122,305). We evaluated model discrimination and accuracy and assessed agreement in estimated HSMRs between methods. RESULTS: The Spearman correlation between HSMRs generated by the FHN model and the standard 3M model was 0.79. Although 2 of 22 hospitals showed opposite classification results, that is, an HSMR significantly <1 according to the FHN method but significantly >1 according to the 3M model, classification agreement between methods was significant (agreement for 59.1% of hospitals, κ = 0.45). The 3M model ( c statistic = 0.96, adjusted Brier score = 26%) outperformed the FHN model (0.87, 17%). However, using ROM at admission instead of at discharge in the 3M model significantly reduced model performance ( c statistic = 0.94, adjusted Brier score = 21%), but yielded similar HSMR estimates and eliminated part of the discrepancy with FHN results. CONCLUSIONS: Results of both models agreed relatively well, supporting convergent validity. Whereas the FHN method only adjusts for disease severity at admission, the ROM indicator of the 3M model includes diagnoses not present on admission. Although diagnosis codes generated by complications during hospitalization have the tendency to increase the predictive performance of a model, these should not be included in risk adjustment procedures.

Positive screens for mental disorders among healthcare professionals during the first covid19 wave in Belgium.

We examined the manifestation of major depressive disorder, generalized anxiety disorder, substance use disorder, post-traumatic stress disorder, and panic attacks among health care professionals during the first COVID-19 wave (n = 6409) by means of mental disorder screening instruments. Logistic regressions were used to gauge individual risk factors; population attributable risk proportions (PARP) were inferred to identify the most important risk factors at the societal level. Data were weighted to represent general profiles of Belgian health care professionals. Lifetime, pre-pandemic emotional problems and work-related factors during the first wave of COVID-19 were strongly associated (mean adjusted odds ratios of 3.79 and 1.47, respectively) with positive screens for current mental disorders (occurrence of 29.3%). Most prominently, the data suggest that disruptions of work-life balance account for more than a quarter of the observed mental health problems due to the combination of widespread occurrence and strong association.

Suicidality among healthcare professionals during the first COVID19 wave.

BACKGROUND: Prevalence estimates of suicidal thoughts and behaviours (STB) among clinically active healthcare professionals during the first wave of COVID19 pandemic are non-existing. The main aim of this study was to investigate the 30-day prevalence of STB and associated risk factors. METHODS: As part of the Recovering Emotionally from COVID study (RECOVID), 30-day STB among healthcare professionals (N = 6,409) was assessed in an e-survey in healthcare settings in Belgium. The prevalence of STB and associated risk factors were estimated in multivariable models with individual-level and society-level measures of association. We used post-stratification weights to make the data representative for the entire clinical workforce in Belgium. RESULTS: Prevalence was 3.6% death wish, 1.5% suicide ideation, 1.0% suicide plan, and 0.0% suicide attempt. Thirty-day STB was (a) increased among respondents with lifetime and current mental disorders (mostly depression) and those hospitalized for COVID19 infection, (b) decreased among respondents with social support, and (c) unrelated to work environment. LIMITATIONS: This is an explorative cross-sectional study using multivariate models that generates specific hypotheses on the prevalence of and risk factors for STB during the COVID19 pandemic rather than testing specific pathways that lead to STB onset. CONCLUSIONS: Across age, gender, professional discipline, and exposure to COVID, lifetime and current mental disorders were highly associated with STB. These factors could guide governments and healthcare organizations in taking up responsibilities in preventing emotional problems and developing resilience among healthcare professionals during, but probably beyond, the current COVID19 pandemic.

Sound-Symbolism Effects in the Absence of Awareness: A Replication Study.

People have been shown to link particular sounds with particular shapes. For instance, the round-sounding nonword bouba tends to be associated with curved shapes, whereas the sharp-sounding nonword kiki is deemed to be related to angular shapes. People's tendency to associate sounds and shapes has been observed across different languages. In the present study, we reexamined the claim by Hung, Styles, and Hsieh (2017) that such sound-shape mappings can occur before an individual becomes aware of the visual stimuli. More precisely, we replicated their first experiment, in which congruent and incongruent stimuli (e.g., bouba presented in a round shape or an angular shape, respectively) were rendered invisible through continuous flash suppression. The results showed that congruent combinations, on average, broke suppression faster than incongruent combinations, thus providing converging evidence for Hung and colleagues' assertions. Collectively, these findings now provide a solid basis from which to explore the boundary conditions of the effect.

Is jellyfish more of a fish in English than in Dutch? The effect of informative labels.

Some words are lexically suggestive about the taxonomic position of their referent (e.g., jellyfish in English), and this information can vary across languages (e.g., in Dutch the equivalent of jellyfish holds no taxonomic information: kwal). To evaluate the role of such lexical suggestions, we conducted a cross-linguistic study in which similarity judgements from two language groups (Dutch and English speakers) were compared. We paired asymmetrically informative items with items that are considered to be typical members of the referenced category (e.g., jellyfish-salmon). Our analyses revealed that items were deemed more similar by speakers of a language in which the lexical information was present (e.g., English speakers tended to give relatively higher ratings for jellyfish-salmon than Dutch participants did for the non-informative equivalent kwal-zalm). Results are discussed in light of theories of concept representation and compound processing.

Cross-cultural consistency and relativity in the enjoyment of thinking versus doing.

Which is more enjoyable: trying to think enjoyable thoughts or doing everyday solitary activities? Wilson et al. (2014) found that American participants much preferred solitary everyday activities, such as reading or watching TV, to thinking for pleasure. To see whether this preference generalized outside of the United States, we replicated the study with 2,557 participants from 12 sites in 11 countries. The results were consistent in every country: Participants randomly assigned to do something reported significantly greater enjoyment than did participants randomly assigned to think for pleasure. Although we found systematic differences by country in how much participants enjoyed thinking for pleasure, we used a series of nested structural equation models to show that these differences were fully accounted for by country-level variation in 5 individual differences, 4 of which were positively correlated with thinking for pleasure (need for cognition, openness to experience, meditation experience, and initial positive affect) and 1 of which was negatively correlated (reported phone usage). (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Sensitivity to the prototype in children with high-functioning autism spectrum disorder: An example of Bayesian cognitive psychometrics.

We present a case study of hierarchical Bayesian explanatory cognitive psychometrics, examining information processing characteristics of individuals with high-functioning autism spectrum disorder (HFASD). On the basis of previously published data, we compare the classification behavior of a group of children with HFASD with that of typically developing (TD) controls using a computational model of categorization. The parameters in the model reflect characteristics of information processing that are theoretically related to HFASD. Because we expect individual differences in the model's parameters, as well as differences between HFASD and TD children, we use a hierarchical explanatory approach. A first analysis suggests that children with HFASD are less sensitive to the prototype. A second analysis, involving a mixture component, reveals that the computational model is not appropriate for a subgroup of participants, which implies parameter estimates are not informative for these children. Focusing only on the children for whom the prototype model is appropriate, no clear difference in sensitivity between HFASD and TD children is inferred.

Depressive Symptoms and Category Learning: A Preregistered Conceptual Replication Study.

We present a fully preregistered, high-powered conceptual replication of Experiment 1 by Smith, Tracy, and Murray (1993). They observed a cognitive deficit in people with elevated depressive symptoms in a task requiring flexible analytic processing and deliberate hypothesis testing, but no deficit in a task assumed to require more automatic, holistic processing. Specifically, they found that individuals with depressive symptoms showed impaired performance on a criterial-attribute classification task, requiring flexible analysis of the attributes and deliberate hypothesis testing, but not on a family-resemblance classification task, assumed to rely on holistic processing. While deficits in tasks requiring flexible hypothesis testing are commonly observed in people diagnosed with a major depressive disorder, these deficits are much less commonly observed in people with merely elevated depressive symptoms, and therefore Smith et al.'s (1993) finding deserves further scrutiny. We observed no deficit in performance on the criterial-attribute task in people with above average depressive symptoms. Rather, we found a similar difference in performance on the criterial-attribute versus family-resemblance task between people with high and low depressive symptoms. The absence of a deficit in people with elevated depressive symptoms is consistent with previous findings focusing on different tasks.

Caveats for the spatial arrangement method: Comment on Hout, Goldinger, and Ferguson (2013).

The gold standard among proximity data collection methods for multidimensional scaling is the (dis)similarity rating of pairwise presented stimuli. A drawback of the pairwise method is its lengthy duration, which may cause participants to change their strategy over time, become fatigued, or disengage altogether. Hout, Goldinger, and Ferguson (2013) recently made a case for the Spatial Arrangement Method (SpAM) as an alternative to the pairwise method, arguing that it is faster and more engaging. SpAM invites participants to directly arrange stimuli on a computer screen such that the interstimuli distances are proportional to psychological proximity. Based on a reanalysis of the Hout et al. (2013), data we identify three caveats for SpAM. An investigation of the distributional characteristics of the SpAM proximity data reveals that the spatial nature of SpAM imposes structure on the data, invoking a bias against featural representations. Individual-differences scaling of the SpAM proximity data reveals that the two-dimensional nature of SpAM allows individuals to only communicate two dimensions of variation among stimuli properly, invoking a bias against high-dimensional scaling representations. Monte Carlo simulations indicate that in order to obtain reliable estimates of the group average, SpAM requires more individuals to be tested. We conclude with an overview of considerations that can inform the choice between SpAM and the pairwise method and offer suggestions on how to overcome their respective limitations.

How do people learn from negative evidence? Non-monotonic generalizations and sampling assumptions in inductive reasoning.

A robust finding in category-based induction tasks is for positive observations to raise the willingness to generalize to other categories while negative observations lower the willingness to generalize. This pattern is referred to as monotonic generalization. Across three experiments we find systematic non-monotonicity effects, in which negative observations raise the willingness to generalize. Experiments 1 and 2 show that this effect emerges in hierarchically structured domains when a negative observation from a different category is added to a positive observation. They also demonstrate that this is related to a specific kind of shift in the reasoner's hypothesis space. Experiment 3 shows that the effect depends on the assumptions that the reasoner makes about how inductive arguments are constructed. Non-monotonic reasoning occurs when people believe the facts were put together by a helpful communicator, but monotonicity is restored when they believe the observations were sampled randomly from the environment.

Problems of reliability and validity with similarity derived from category fluency.

This study aims to assess the reliability and the validity of exemplar similarity derived from category fluency tasks. A homogeneous sample of 21 healthy participants completed a category fluency task twice with an interval of one week. They also rated pairs comprised of the most frequently generated exemplars in terms of similarity. Similarities were derived from the fluency data by determining the average distance between generated exemplars and correcting it for repetitions and response sequence length. We calculated the correlation between the similarities derived from the two sessions of the fluency task and between the derived similarities and the directly rated similarities. Spatial representations of the similarities were constructed using multidimensional scaling to visualize the differences between both sessions of the fluency task and the pairwise rating task. We find that the derived similarities are not stable in time and show little correspondence with directly rated similarities. The differences between similarities derived from category fluency tasks in healthy participants, indicate that similar differences between healthy controls and patients with mental disorders, do not necessarily point to a semantic impairment of the latter, but rather reflect the unreliability of the data.

Can race really be erased? A pre-registered replication study.

WHEN ENCOUNTERING AN UNKNOWN INDIVIDUAL, SOCIAL CATEGORIZATION OF THE INDIVIDUAL HAS BEEN SHOWN TO AUTOMATICALLY PROCEED ON THE BASIS OF THREE FUNDAMENTAL DIMENSIONS: People seem to mandatorily encode race, sex and age. In contradiction to this general finding, Kurzban et al. (2001) showed that race encoding is not automatic and inevitable, but rather a byproduct of categorization in terms of coalitions. In particular, they argue and empirically support that when other coalitional information is present, the encoding of race is spectacularly reduced. In the present contribution, we present a replication of the race-erased effect reported by Kurzban et al. First, we give a detailed overview of the hypotheses, the experimental methodology, the derivation of the sample size required to achieve a power of 95%, and the criteria that need to be met for a successful replication. Then we present the findings of an empirical test that met the requirements of our power analyses. Our results indicate that the encoding of race is indeed reduced when another coalitional cue is available, yet this reduction is less marked than in the original study. This experiment was preregistered before data collection at Open Science Framework, osf.io/vnhrm/.

Norms of age of acquisition and concreteness for 30,000 Dutch words.

Word processing studies increasingly make use of regression analyses based on large numbers of stimuli (the so-called megastudy approach) rather than experimental designs based on small factorial designs. This requires the availability of word features for many words. Following similar studies in English, we present and validate ratings of age of acquisition and concreteness for 30,000 Dutch words. These include nearly all lemmas language researchers are likely to be interested in. The ratings are freely available for research purposes.

Deriving semantic structure from category fluency: clustering techniques and their pitfalls.

Assessing verbal output in category fluency tasks provides a sensitive indicator of cortical dysfunction. The most common metrics are the overall number of words produced and the number of errors. Two main observations have been made about the structure of the output, first that there is a temporal component to it with words being generated in spurts, and second that the clustering pattern may reflect a search for meanings such that the 'clustering' is attributable to the activation of a specific semantic field in memory. A number of sophisticated approaches to examining the structure of this clustering have been developed, and a core theme is that the similarity relations between category members will reveal the mental semantic structure of the category underlying an individual's responses, which can then be visualized by a number of algorithms, such as MDS, hierarchical clustering, ADDTREE, ADCLUS or SVD. Such approaches have been applied to a variety of neurological and psychiatric populations, and the general conclusion has been that the clinical condition systematically distorts the semantic structure in the patients, as compared to the healthy controls. In the present paper we explore this approach to understanding semantic structure using category fluency data. On the basis of a large pool of patients with schizophrenia (n = 204) and healthy control participants (n = 204), we find that the methods are problematic and unreliable to the extent that it is not possible to conclude that any putative difference reflects a systematic difference between the semantic representations in patients and controls. Moreover, taking into account the unreliability of the methods, we find that the most probable conclusion to be made is that no difference in underlying semantic representation exists. The consequences of these findings to understanding semantic structure, and the use of category fluency data, in cortical dysfunction are discussed.

Idealness and similarity in goal-derived categories: a computational examination.

The finding that the typicality gradient in goal-derived categories is mainly driven by ideals rather than by exemplar similarity has stood uncontested for nearly three decades. Due to the rather rigid earlier implementations of similarity, a key question has remained--that is, whether a more flexible approach to similarity would alter the conclusions. In the present study, we evaluated whether a similarity-based approach that allows for dimensional weighting could account for findings in goal-derived categories. To this end, we compared a computational model of exemplar similarity (the generalized context model; Nosofsky, Journal of Experimental Psychology. General 115:39-57, 1986) and a computational model of ideal representation (the ideal-dimension model; Voorspoels, Vanpaemel, & Storms, Psychonomic Bulletin & Review 18:1006-114, 2011) in their accounts of exemplar typicality in ten goal-derived categories. In terms of both goodness-of-fit and generalizability, we found strong evidence for an ideal approach in nearly all categories. We conclude that focusing on a limited set of features is necessary but not sufficient to account for the observed typicality gradient. A second aspect of ideal representations--that is, that extreme rather than common, central-tendency values drive typicality--seems to be crucial.

Contrast effects in typicality judgements: a hierarchical Bayesian approach.

We examine the influence of contrast categories on the internal graded membership structure of everyday concepts using computational models proposed in the artificial category learning tradition. In particular, the generalized context model (Nosofsky, 1986), which assumes that only members of a given category contribute to the typicality of a category member, is contrasted to the similarity-dissimilarity generalized context model (SD-GCM; Stewart & Brown, 2005), which assumes that members of other categories are also influential in determining typicality. The models are compared in a hierarchical Bayesian framework in their account of the typicality gradient of five animal categories and six artefact categories. For each target category, we consider all possible relevant contrast categories. Three separate issue are examined: (a) whether contrast effects can be found, (b) which categories are responsible for these effects, and (c) whether more than one category influences the typicality. Results indicate that the internal category structure is codetermined by dissimilarity towards potential contrast categories. In most cases, only a single contrast category contributed to the typicality. The present findings suggest that contrast effects might be more widespread than has previously been assumed. Further, they stress the importance of characteristics particular of everyday concepts, which require careful consideration when applying computational models of representation of the artificial category learning tradition to everyday concepts.

A formal ideal-based account of typicality.

Inspired by Barsalou's (Journal of Experimental Psychology: Learning, Memory, and Cognition, 11, 629-654, 1985) proposal that categories can be represented by ideals, we develop and test a computational model, the ideal dimension model (IDM). The IDM is tested in its account of the typicality gradient for 11 superordinate natural language concepts and, using Bayesian model evaluation, contrasted with a standard exemplar model and a central prototype model. The IDM is found to capture typicality better than do the exemplar model and the central tendency prototype model, in terms of both goodness of fit and generalizability. The present findings challenge the dominant view that exemplar representations are most successful and present compelling evidence that superordinate natural language categories can be represented using an abstract summary, in the form of ideal representations. Supplemental appendices for this article can be downloaded from http://mc.psychonomic-journals.org/content/supplemental.

Raising argument strength using negative evidence: a constraint on models of induction.

Both intuitively, and according to similarity-based theories of induction, relevant evidence raises argument strength when it is positive and lowers it when it is negative. In three experiments, we tested the hypothesis that argument strength can actually increase when negative evidence is introduced. Two kinds of argument were compared through forced choice or sequential evaluation: single positive arguments (e.g., "Shostakovich's music causes alpha waves in the brain; therefore, Bach's music causes alpha waves in the brain") and double mixed arguments (e.g., "Shostakovich's music causes alpha waves in the brain, X's music DOES NOT; therefore, Bach's music causes alpha waves in the brain"). Negative evidence in the second premise lowered credence when it applied to an item X from the same subcategory (e.g., Haydn) and raised it when it applied to a different subcategory (e.g., AC/DC). The results constitute a new constraint on models of induction.