Positive and negative personality descriptors: UK dataset of self-referential valence, imageability and subjective frequency ratings of 300 adjectives for use in cognitive-emotional tasks

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.

Relationships between social withdrawal and facial emotion recognition in neuropsychiatric disorders

BACKGROUND

Emotion recognition constitutes a pivotal process of social cognition. It involves decoding social cues (e.g., facial expressions) to maximise social adjustment. Current theoretical models posit the relationship between social withdrawal factors (social disengagement, lack of social interactions and loneliness) and emotion decoding.

OBJECTIVE

To investigate the role of social withdrawal in patients with schizophrenia (SZ) or probable Alzheimer's disease (AD), neuropsychiatric conditions associated with social dysfunction.

METHODS

A sample of 156 participants was recruited: schizophrenia patients (SZ; n = 53), Alzheimer's disease patients (AD; n = 46), and two age-matched control groups (SZc, n = 29; ADc, n = 28). All participants provided self-report measures of loneliness and social functioning, and completed a facial emotion detection task.

RESULTS

Neuropsychiatric patients (both groups) showed poorer performance in detecting both positive and negative emotions compared with their healthy counterparts (p < .01). Social withdrawal was associated with higher accuracy in negative emotion detection, across all groups. Additionally, neuropsychiatric patients with higher social withdrawal showed lower positive emotion misclassification.

CONCLUSIONS

Our findings help to detail the similarities and differences in social function and facial emotion recognition in two disorders rarely studied in parallel, AD and SZ. Transdiagnostic patterns in these results suggest that social withdrawal is associated with heightened sensitivity to negative emotion expressions, potentially reflecting hypervigilance to social threat. Across the neuropsychiatric groups specifically, this hypervigilance associated with social withdrawal extended to positive emotion expressions, an emotional-cognitive bias that may impact social functioning in people with severe mental illness.

Social dysfunction is transdiagnostically associated with default mode network dysconnectivity in schizophrenia and Alzheimer's disease

OBJECTIVES

Social dysfunction is one of the most common signs of major neuropsychiatric disorders. The Default Mode Network (DMN) is crucially implicated in both psychopathology and social dysfunction, although the transdiagnostic properties of social dysfunction remains unknown. As part of the pan-European PRISM (Psychiatric Ratings using Intermediate Stratified Markers) project, we explored cross-disorder impact of social dysfunction on DMN connectivity.

METHODS

We studied DMN intrinsic functional connectivity in relation to social dysfunction by applying Independent Component Analysis and Dual Regression on resting-state fMRI data, among schizophrenia (SZ; N = 48), Alzheimer disease (AD; N = 47) patients and healthy controls (HC; N = 55). Social dysfunction was operationalised via the Social Functioning Scale (SFS) and De Jong-Gierveld Loneliness Scale (LON).

RESULTS

Both SFS and LON were independently associated with diminished DMN connectional integrity within rostromedial prefrontal DMN subterritories (p_corrected range = 0.02-0.04). The combined effect of these indicators (Mean.SFS + LON) on diminished DMN connectivity was even more pronounced (both spatially and statistically), independent of diagnostic status, and not confounded by key clinical or sociodemographic effects, comprising large sections of rostromedial and dorsomedial prefrontal cortex (p_corrected=0.01).

CONCLUSIONS

These findings pinpoint DMN connectional alterations as putative transdiagnostic endophenotypes for social dysfunction and could aid personalised care initiatives grounded in social behaviour.

Validation of the P1vital® Faces Set for Use as Stimuli in Tests of Facial Emotion Recognition

BACKGROUND

Negative bias in facial emotion recognition is a well-established concept in mental disorders such as depression. However, existing face sets of emotion recognition tests may be of limited use in international research, which could benefit from more contemporary and diverse alternatives. Here, we developed and provide initial validation for the P1vital® Affective Faces set (PAFs) as a contemporary alternative to the widely-used Pictures of Facial Affect (PoFA).

METHODS

The PAFs was constructed of 133 color photographs of facial expressions of ethnically-diverse trained actors and compared with the PoFA, comprised of 110 black and white photographs of facial expressions of generally Caucasian actors. Sixty-one recruits were asked to classify faces from both sets over six emotions (happy, sad, fear, anger, disgust, surprise) varying in intensity in 10% increments from 0 to 100%.

RESULTS

Participants were significantly more accurate in identifying correct emotions viewing faces from the PAFs. In both sets, participants identified happy faces more accurately than fearful faces, were least likely to misclassify facial expressions as happy and most likely to misclassify all emotions at low intensity as neutral. Accuracy in identifying facial expressions improved with increasing emotion intensity for both sets, reaching peaks at 60 and 80% intensity for the PAFs and PoFA, respectively. The study was limited by small sizes and age-range of participants and ethnic diversity of actors.

CONCLUSIONS

The PAFs successfully depicted a range of emotional expressions with improved performance over the PoFA and may be used as a contemporary set in facial expression recognition tests.

Effect of disease related biases on the subjective assessment of social functioning in Alzheimer's disease and schizophrenia patients

BACKGROUND

Questionnaires are the current hallmark for quantifying social functioning in human clinical research. In this study, we compared self- and proxy-rated (caregiver and researcher) assessments of social functioning in Schizophrenia (SZ) and Alzheimer's disease (AD) patients and evaluated if the discrepancy between the two assessments is mediated by disease-related factors such as symptom severity.

METHODS

We selected five items from the WHO Disability Assessment Schedule 2.0 (WHODAS) to assess social functioning in 53 AD and 61 SZ patients. Caregiver- and researcher-rated assessments of social functioning were used to calculate the discrepancies between self-rated and proxy-rated assessments. Furthermore, we used the number of communication events via smartphones to compare the questionnaire outcomes with an objective measure of social behaviour.

RESULTS

WHODAS results revealed that both AD (p < 0.001) and SZ (p < 0.004) patients significantly overestimate their social functioning relative to the assessment of their caregivers and/or researchers. This overestimation is mediated by the severity of cognitive impairments (MMSE; p = 0.019) in AD, and negative symptoms (PANSS; p = 0.028) in SZ. Subsequently, we showed that the proxy scores correlated more strongly with the smartphone communication events of the patient when compared to the patient-rated questionnaire scores (self; p = 0.076, caregiver; p < 0.001, researcher-rated; p = 0.046).

CONCLUSION

Here we show that the observed overestimation of WHODAS social functioning scores in AD and SZ patients is partly driven by disease-related biases such as cognitive impairments and negative symptoms, respectively. Therefore, we postulate the development and implementation of objective measures of social functioning that may be less susceptible to such biases.

Optimizing Behavioral Paradigms to Facilitate Development of New Treatments for Anhedonia and Reward Processing Deficits in Schizophrenia and Major Depressive Disorder: Study Protocol

Background: Behavioral tasks focusing on different subdomains of reward processing may provide more objective and quantifiable measures of anhedonia and impaired motivation compared with clinical scales. Typically, single tasks are used in relatively small studies to compare cases and controls in one indication, but they are rarely included in larger multisite trials. This is due to limited systematic standardization as well as the challenges of deployment in international studies and stringent adherence to the high regulatory requirements for data integrity. The Reward Task Optimization Consortium (RTOC) was formed to facilitate operational implementation of reward processing tasks, making them suitable for use in future large-scale, international, multisite drug development studies across multiple indications. The RTOC clinical study aims to conduct initial optimization of a set of tasks in patients with major depressive disorder (MDD) or schizophrenia (SZ). Methods: We will conduct a multicenter study across four EU countries. Participants (MDD = 37, SZ = 37, with ≤80 age- and gender-matched healthy volunteers) will attend a study visit comprising screening, self-report and clinically rated assessments of anhedonia and symptom severity, and three reward processing tasks; specifically, the Grip Strength Effort task, the Doors task, and the Reinforcement Learning Working Memory task. The Grip Strength Effort and Doors tasks include simultaneous electroencephalography/event-related potential recordings. Outcomes will be compared using a two-way group design of MDD and SZ with matched controls, respectively. Further analyses will include anhedonia assessment scores as covariates. Planned analyses will assess whether our findings replicate previously published data, and multisite deployment will be evaluated through assessments of quality and conduct. A subset of participants will complete a second visit, to assess test-retest reliability of the task battery. Discussion: This study will evaluate the operational deployment of three reward processing tasks to the regulatory standards required for use in drug development trials. We will explore the potential of these tasks to differentiate patients from controls and to provide a quantitative marker of anhedonia and/or impaired motivation, establishing their usefulness as endpoints in multisite clinical trials. This study should demonstrate where multifaceted reward deficits are similar or divergent across patient populations. Registration: ClinicalTrials.gov (NCT04024371).