The Macroscope: A tool for examining the historical structure of language.

The recent rise in digitized historical text has made it possible to quantitatively study our psychological past. This involves understanding changes in what words meant, how words were used, and how these changes may have responded to changes in the environment, such as in healthcare, wealth disparity, and war. Here we make available a tool, the Macroscope, for studying historical changes in language over the last two centuries. The Macroscope uses over 155 billion words of historical text, which will grow as we include new historical corpora, and derives word properties from frequency-of-usage and co-occurrence patterns over time. Using co-occurrence patterns, the Macroscope can track changes in semantics, allowing researchers to identify semantically stable and unstable words in historical text and providing quantitative information about changes in a word's valence, arousal, and concreteness, as well as information about new properties, such as semantic drift. The Macroscope provides information about both the local and global properties of words, as well as information about how these properties change over time, allowing researchers to visualize and download data in order to make inferences about historical psychology. Although quantitative historical psychology represents a largely new field of study, we see this work as complementing a wealth of other historical investigations, offering new insights and new approaches to understanding existing theory. The Macroscope is available online at http://www.macroscope.tech .

Humor norms for 4,997 English words.

Humor ratings are provided for 4,997 English words collected from 821 participants using an online crowd-sourcing platform. Each participant rated 211 words on a scale from 1 (humorless) to 5 (humorous). To provide for comparisons across norms, words were chosen from a set common to a number of previously collected norms (e.g., arousal, valence, dominance, concreteness, age of acquisition, and reaction time). The complete dataset provides researchers with a list of humor ratings and includes information on gender, age, and educational differences. Results of analyses show that the ratings have reliability on a par with previous ratings and are not well predicted by existing norms.

Treatment resistant depression: A comparative study of access, pathways, and outcomes between Caucasian and ethnic minority individuals.

BACKGROUND: Treatment resistant depression (TRD) is considered when an individual fails to respond to two or more different antidepressants in adequate doses, duration and with adequate adherence within the same major depressive episode. AIM: To examine the clinical profiles of TRD patients through data from electronic healthcare records and compare characteristics and treatment pathways of ethnic minority and non-minority patients in UK. METHODS: A retrospective, longitudinal, observational cohort study of patients with TRD was carried out in 10 Mental Health NHS Foundation Trusts in the Akrivia Health/UK Clinical Record Interactive Search (CRIS) system network. The CRIS system was used as a means of analysing de-identified data across 3.2 million anonymised patients' records. RESULTS: 10,048 patient records were deemed eligible for this study, of which 20.2 % of patients identified as BAME, and 79.8 % patients identified as White. Overall, around half of the patients were likely to be prescribed an antidepressant within 2 months of the MDD diagnosis. White patients were prescribed more antidepressants than the BAME group (p < 0.001), with a significant effect size for comorbidities. LIMITATIONS: The nature of the data source limited the ability to filter for short treatment durations as clinicians did not often record concrete medication end-dates in clinical note fields. CONCLUSION: There are significant differences in care pathways between ethnic groups in relation to TRD patients. It is vital to understand factors causing these potential clinical biases and increase awareness and education to deliver the most effective treatments for TRD in ethnic minority patients.

Nymph piss and gravy orgies: Local and global contrast effects in relational humor.

How does the relation between two words create humor? In this article, we investigated the effect of global and local contrast on the humor of word pairs. We capitalized on the existence of psycholinguistic lexical norms by examining violations of expectations set up by typical patterns of English usage (global contrast) and within the local context of the words within the word pairs (local contrast). Global contrast was operationalized as lexical-semantic norms for single-words and local contrast was operationalized as the orthographic, phonological, and semantic distance between the two words in the pair. Through crowd-sourced (Study 1) and best-worst (Study 2) ratings of the humor of a large set of word pairs (i.e., compounds), we find evidence of both global and local contrast on compound-word humor. Specifically, we find that humor arises when there is a violation of expectations at the local level, between the individual words that make up the word pair, even after accounting for violations at the global level relative to the entire language. Semantic variables (arousal, dominance, and concreteness) were stronger predictors of word pair humor whereas form-related variables (number of letters, phonemes, and letter frequency) were stronger predictors of single-word humor. Moreover, we also find that semantic dissimilarity increases humor, by defusing the impact of low-valence words-making them seem more amusing-and by enhancing the incongruence of highly imageable pairs of concrete words. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Associated mortality risk of atypical antipsychotic medication in individuals with dementia.

BACKGROUND: Antipsychotic medications such as risperidone, olanzapine and aripiprazole are used to treat psychological and behavioural symptoms among dementia patients. Current evidence indicate prescription rates for antipsychotics vary and wider consensus to evaluate clinical epidemiological outcomes is limited. AIM: To investigate the potential impact of atypical antipsychotics on the mortality of patients with dementia. METHODS: A retrospective clinical cohort study was developed to review United Kingdom Clinical Record Interactive Search system based data between January 1, 2013 to December 31, 2017. A descriptive statistical method was used to analyse the data. Mini Mental State Examination (MMSE) scores were used to assess the severity and stage of disease progression. A cox proportional hazards model was developed to evaluate the relationship between survival following diagnosis and other variables. RESULTS: A total of 1692 patients were identified using natural language processing of which, 587 were prescribed olanzapine, quetiapine or risperidone (common group) whilst 893 (control group) were not prescribed any antipsychotics. Patients prescribed olanzapine showed an increased risk of death [hazard ratio (HR) = 1.32; 95% confidence interval (CI): 1.08-1.60; P < 0.01], as did those with risperidone (HR = 1.35; 95%CI: 1.18-1.54; P < 0.001). Patients prescribed quetiapine showed no significant association (HR = 1.09; 95%CI: 0.90-1.34; P = 0.38). Factors associated with a lower risk of death were: High MMSE score at diagnosis (HR = 0.72; 95%CI: 0.62-0.83; P < 0.001), identifying as female (HR = 0.73; 95%CI: 0.64-0.82; P < 0.001), and being of a White-British ethnic group (HR = 0.82; 95%CI: 0.72-0.94; P < 0.01). CONCLUSION: A significant mortality risk was identified among those prescribed olanzapine and risperidone which contradicts previous findings although the study designs used were different. Comprehensive research should be conducted to better assess clinical epidemiological outcomes associated with diagnosis and therapies to improve clinical management of these patients.

The burden associated with, and management of, difficult-to-treat depression in patients under specialist psychiatric care in the United Kingdom.

BACKGROUND: Major depressive disorder (MDD) is common and often has sub-optimal response to treatment. Difficult-to-treat depression (DTD) is a new concept that describes 'depression that continues to cause significant burden despite usual treatment efforts'. AIMS: To identify patients with likely DTD in UK secondary care and examine demographic, disease and treatment data as compared with 'non-DTD' MDD patients. METHODS: Anonymised electronic health records (EHRs) of five specialist mental health National Health Service (NHS) Trusts in the United Kingdom were analysed using a natural language processing model. Data on disease characteristics, comorbidities and treatment histories were extracted from structured fields and using natural language algorithms from unstructured fields. Patients with MDD aged ⩾18 years were included in the analysis; those with presumed DTD were identified on the basis of MDD history (duration and recurrence) and number of treatments prescribed. RESULTS: In a sample of 28,184 patients with MDD, 19% met criteria for DTD. Compared to the non-DTD group, patients with DTD were more likely to have severe depression, suicidal ideation, and comorbid psychiatric and/or physical illness, as well as higher rates of hospitalisation. They were also more likely to be in receipt of unemployment and sickness/disability benefits. More intensive treatment strategies were used in the DTD group, including higher rates of combination therapy, augmentation, psychotherapy and electroconvulsive therapy. CONCLUSION: This study demonstrates the feasibility of identifying patients with probable DTD from EHRs and highlights the increased burden associated with MDD in these patients.

Impact of COVID-19 on telepsychiatry at the service and individual patient level across two UK NHS mental health Trusts.

BACKGROUND: The effects of COVID-19 on the shift to remote consultations remain to be properly investigated. OBJECTIVE: To quantify the extent, nature and clinical impact of the use of telepsychiatry during the COVID-19 pandemic and compare it with the data in the same period of the 2 years before the outbreak. METHODS: We used deidentified electronic health records routinely collected from two UK mental health Foundation Trusts (Oxford Health (OHFT) and Southern Health (SHFT)) between January and September in 2018, 2019 and 2020. We considered three outcomes: (1) service activity, (2) in-person versus remote modalities of consultation and (3) clinical outcomes using Health of the Nation Outcome Scales (HoNOS) data. HoNOS data were collected from two cohorts of patients (cohort 1: patients with ≥1 HoNOS assessment each year in 2018, 2019 and 2020; cohort 2: patients with ≥1 HoNOS assessment each year in 2019 and 2020), and analysed in clusters using superclasses (namely, psychotic, non-psychotic and organic), which are used to assess overall healthcare complexity in the National Health Service. All statistical analyses were done in Python. FINDINGS: Mental health service activity in 2020 increased in all scheduled community appointments (by 15.4% and 5.6% in OHFT and SHFT, respectively). Remote consultations registered a 3.5-fold to 6-fold increase from February to June 2020 (from 4685 to a peak of 26 245 appointments in OHFT and from 7117 to 24 987 appointments in SHFT), with post-lockdown monthly averages of 23 030 and 22 977 remote appointments/month in OHFT and SHFT, respectively. Video consultations comprised up to one-third of total telepsychiatric services per month from April to September 2020. For patients with dementia, non-attendance rates at in-person appointments were higher than remote appointments (17.2% vs 3.9%). The overall HoNOS cluster value increased only in the organic superclass (clusters 18-21, n=174; p<0.001) from 2019 to 2020, suggesting a specific impact of the COVID-19 pandemic on this population of patients. CONCLUSIONS AND CLINICAL IMPLICATIONS: The rapid shift to remote service delivery has not reached some groups of patients who may require more tailored management with telepsychiatry.

Feature Biases in Early Word Learning: Network Distinctiveness Predicts Age of Acquisition.

Do properties of a word's features influence the order of its acquisition in early word learning? Combining the principles of mutual exclusivity and shape bias, the present work takes a network analysis approach to understanding how feature distinctiveness predicts the order of early word learning. Distance networks were built from nouns with edge lengths computed using various distance measures. Feature distinctiveness was computed as a distance measure, showing how far an object in a network is from other objects based on shared and non-shared features. Feature distinctiveness predicted order of acquisition across all measures: Words that were further away from other words in the network space were learned earlier. The best distance measures were based only on non-shared features (object dissimilarity) and did not include shared features (object similarity). This indicates that shared features may play less of a role in early word learning than non-shared features. In addition, the strongest effects were found for visual form and surface features. Cluster analysis further revealed that this effect is a localized effect in the object feature space, where objects' distances from their cluster centroid were inversely correlated with their age of acquisition. Together, these results suggest a role for feature distinctiveness in early word learning.