Brief Emergency Department Patient Satisfaction Scale (BEPSS); Development of a New Practical Instrument

Introduction: Methodologically correct assessment of patient satisfaction (PS) plays a crucial role for quality-improvement purposes. Evaluation of Iranian literature on emergency department’s PS resulted in an emerging need for developing a new instrument with satisfactory psychometric properties. The present study, aimed to develop and initially validate a scale to measure PS in emergency departments. Methods: A sample of 301 patients was selected in 2014 from two hospitals in Tehran. A pool of 24 items was prepared for administering. An item analysis was conducted to evaluate the quality of each item. Validity and reliability of the scale were evaluated. The data were analyzed using SPSS. Results: Item analysis and exploratory factor analysis yielded in a 20-item scale in five domains named emergency department staff, emergency department environment, physician care satisfaction, general patient satisfaction, and patient’s family’s satisfaction. Validity and factor structure of the scale were reported satisfactory. Reliability coefficients of the domains ranged between 0.75 and 0.88. Conclusion: The findings of the present study provided evidence for psychometric properties of a newly developed scale for PS assessment in emergency departments. Five underlying components of PS were found in the item pool. In sum, this scale may be used in research and emergency departments to measure PS

Surveying the Dead Minds: Historical-Psychological Text Analysis with Contextualized Construct Representation (CCR) for Classical Chinese

In this work, we develop a pipeline for historical-psychological text analysis in classical Chinese. Humans have produced texts in various languages for thousands of years; however, most of the computational literature is focused on contemporary languages and corpora. The emerging field of historical psychology relies on computational techniques to extract aspects of psychology from historical corpora using new methods developed in natural language processing (NLP). The present pipeline, called Contextualized Construct Representations (CCR), combines expert knowledge in psychometrics (i.e., psychological surveys) with text representations generated via transformer-based language models to measure psychological constructs such as traditionalism, norm strength, and collectivism in classical Chinese corpora. Considering the scarcity of available data, we propose an indirect supervised contrastive learning approach and build the first Chinese historical psychology corpus (C-HI-PSY) to fine-tune pre-trained models. We evaluate the pipeline to demonstrate its superior performance compared with other approaches. The CCR method outperforms word-embedding-based approaches across all of our tasks and exceeds prompting with GPT-4 in most tasks. Finally, we benchmark the pipeline against objective, external data to further verify its validity

Psychometric Assessments of Persian Translations of Three Measures of Conspiracist Beliefs

Several self-report measures of conspiracist beliefs have been developed in Western populations, but examination of their psychometric properties outside Europe and North America is limited. This study aimed to examine the psychometric properties of three widely-used measures of conspiracist beliefs in Iran. We translated the Belief in Conspiracy Theory Inventory (BCTI), Conspiracy Mentality Questionnaire (CMQ), and Generic Conspiracist Belief Scale (GCBS) into Persian. Factorial validity was examined using principal-axis factor analysis in a community sample from Tehran, Iran (N = 544). Further, the relationships between scores on these measures and hypothesized antecedents (i.e., education, schizotypal personality, information processing style, superstitious beliefs, religiosity, and political orientation) were examined. Overall, we failed to find support for the parent factor structures of two of the three scales (BCTI and GCBS) and evidence of construct validity for all three scales was limited. These results highlight the necessity of further psychometric work on existing measures of conspiracy theories in diverse culturo-linguistic groups and the development of context-specific measures of conspiracist beliefs

Hate Speech Classifiers Learn Normative Social Stereotypes

AbstractSocial stereotypes negatively impact individuals’ judgments about different groups and may have a critical role in understanding language directed toward marginalized groups. Here, we assess the role of social stereotypes in the automated detection of hate speech in the English language by examining the impact of social stereotypes on annotation behaviors, annotated datasets, and hate speech classifiers. Specifically, we first investigate the impact of novice annotators’ stereotypes on their hate-speech-annotation behavior. Then, we examine the effect of normative stereotypes in language on the aggregated annotators’ judgments in a large annotated corpus. Finally, we demonstrate how normative stereotypes embedded in language resources are associated with systematic prediction errors in a hate-speech classifier. The results demonstrate that hate-speech classifiers reflect social stereotypes against marginalized groups, which can perpetuate social inequalities when propagated at scale. This framework, combining social-psychological and computational-linguistic methods, provides insights into sources of bias in hate-speech moderation, informing ongoing debates regarding machine learning fairness

Antidepressants: New Hypothetical Interactions to Increase Their Efficiency

Depression is a prevalent disorder that stems from an imbalance in brain chemistry, particularly involving neurotransmitters. It is commonly treated with antidepressants, such as Selective Serotonin Reuptake Inhibitors (SSRIs), which work by inhibiting the reuptake of serotonin. Paroxetine is one of the most commonly used SSRIs; however, it is associated with side effects on both thyroid and sex hormones. The objective of this study is to identify an alternative compound or drug to paroxetine that offers fewer side effects

In COVID-19 Health Messaging, Loss Framing Increases Anxiety with Little-to-No Concomitant Benefits: Experimental Evidence from 84 Countries

The COVID-19 pandemic (and its aftermath) highlights a critical need to communicate health information effectively to the global public. Given that subtle differences in information framing can have meaningful effects on behavior, behavioral science research highlights a pressing question: Is it more effective to frame COVID-19 health messages in terms of potential losses (e.g., "If you do not practice these steps, you can endanger yourself and others") or potential gains (e.g., "If you practice these steps, you can protect yourself and others")? Collecting data in 48 languages from 15,929 participants in 84 countries, we experimentally tested the effects of message framing on COVID-19-related judgments, intentions, and feelings. Loss- (vs. gain-) framed messages increased self-reported anxiety among participants cross-nationally with little-to-no impact on policy attitudes, behavioral intentions, or information seeking relevant to pandemic risks. These results were consistent across 84 countries, three variations of the message framing wording, and 560 data processing and analytic choices. Thus, results provide an empirical answer to a global communication question and highlight the emotional toll of loss-framed messages. Critically, this work demonstrates the importance of considering unintended affective consequences when evaluating nudge-style interventions

A global experiment on motivating social distancing during the COVID-19 pandemic

Finding communication strategies that effectively motivate social distancing continues to be a global public health priority during the COVID-19 pandemic. This cross-country, preregistered experiment (n = 25,718 from 89 countries) tested hypotheses concerning generalizable positive and negative outcomes of social distancing messages that promoted personal agency and reflective choices (i.e., an autonomy-supportive message) or were restrictive and shaming (i.e., a controlling message) compared with no message at all. Results partially supported experimental hypotheses in that the controlling message increased controlled motivation (a poorly internalized form of motivation relying on shame, guilt, and fear of social consequences) relative to no message. On the other hand, the autonomy-supportive message lowered feelings of defiance compared with the controlling message, but the controlling message did not differ from receiving no message at all. Unexpectedly, messages did not influence autonomous motivation (a highly internalized form of motivation relying on one’s core values) or behavioral intentions. Results supported hypothesized associations between people’s existing autonomous and controlled motivations and self-reported behavioral intentions to engage in social distancing. Controlled motivation was associated with more defiance and less long-term behavioral intention to engage in social distancing, whereas autonomous motivation was associated with less defiance and more short- and long-term intentions to social distance. Overall, this work highlights the potential harm of using shaming and pressuring language in public health communication, with implications for the current and future global health challenges

Moral Foundations Questionnaire

Psychometric and theoretical refinement of the Moral Foundations Questionnaire