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A data set was developed for research on word recognition and comprehension as well as for vocabulary knowledge estimation of Arabic–English bilingual speakers (i.e., an understudied population). Subjective frequency (i.e., familiarity) ratings, which reflect language exposure, were collected from 1000 Arabic–English speakers (age range: 18–25) for the printed words of the Peabody Picture Vocabulary Test (PPVT). They were obtained from speakers who had received at least a score of 6 (i.e., competent user of the English language) on the International English Language Testing System (i.e., IELTS). Reading comprehension scores were also obtained from 61 speakers from the same population. In the developed data set, printed words are displayed with their subjective frequency ratings and comprehension scores alongside objective word properties.

The present study investigated the subjective lexical characteristics of words stemming from a medical context by comparing estimations of the target population (age range = 46–89) and of doctors. A total of 58 members of the target population and 22 oncologists completed measures of subjective frequency and emotional valence for words previously collected in interviews of announcement of cancer diagnosis. The members of the target population also completed tests of word definitions, without and within context. As expected, most of the words were rated less familiar, more negative and as generating more intense emotions to the target population than to the doctors. Moreover, only a few words were correctly defined by the target population. Adding a context helped the participants to define most of the words correctly. Importantly, we identified words that were rated familiar by the patients although they did not know their exact meaning. Overall, these results highlight the importance of taking into account the subjective lexical characteristics of words used in specific contexts. [ABSTRACT FROM AUTHOR]

Experimental tasks comparing participants' performance for categorising, remembering, and recognising positive and negative words are widely used in the emotional cognitive domain. Such tasks are commonly used in experimental psychology and psychiatry research, and have been shown to be sensitive biomarkers of depression and antidepressant drug action [1,2]. In addition, several of these tasks investigate self-referential processing i.e., the processing of information relevant to oneself; this has been shown to modify the way emotional words are encoded and remembered and may be a target that is amenable to treatment [3,4]. In practice, the development of such tasks for implementation in research studies often depends on the selection and matching of words according to characteristics such as valence or arousal, imageability, word frequency and word length to investigate differences in a chosen domain of interest whilst keeping important confounds constant. This introduces a need for ratings covering a range of word attributes that have been shown to affect processing. In particular, ratings of self-referential valence (how positively or negatively subjects feel about a word when this is used to describe themselves/their circumstances) have been seldom included in databases, despite the frequent investigation of the concept in research [1,5]. Other important attributes often considered in the process of matching and selection are word imageability and subjective frequency [6,7]. To facilitate the word selection and matching process required in cognitive-emotional task development, the present dataset provides subjective ratings for 150 positive and 150 negative adjectives describing personality characteristics. Across four online surveys, the 300 words were rated on self-referential valence, imageability and subjective frequency by representative samples of 200 UK-based, English-speaking adults. Basic demographics and data on depressive symptoms and state anxiety were collected from all participants. Comprehensive descriptive statistics and word length were calculated for each of the 300 words. All data cleaning and statistical analysis was performed in R. Our work is based on years of experience using the Oxford Emotional Task Battery [1,5] and may be particularly relevant for researchers using self-referential cognitive tasks with UK-based samples., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships which have or could be perceived to have influenced the work reported in this article., (© 2022 Published by Elsevier Inc.)