Ecological momentary facial emotion recognition in psychotic disorders. Issue 13 (12th October 2022)

• Record Type: Journal Article
• Authors: Depp, Colin A.; Kamarsu, Snigdha; Filip, Tess F.; Parrish, Emma M.; Harvey, Philip D.; Granholm, Eric L.; Chalker, Samantha; Moore, Raeanne C.; Pinkham, Amy
• Is Part Of: Psychological medicine. Volume 52:Issue 13(2022)
• Page Start: 2531
• Page End: 2539
• Publication Date: 2022-10-12
• Subjects: Mobile technology -- psychometric assessment -- psychosis -- social cognition -- time series analysis; Psychiatry -- Periodicals; Medicine and psychology -- Periodicals; Clinical psychology -- Periodicals; 616.89
• DOI: 10.1017/S0033291720004419
• Languages: English
• ISSNs: 0033-2917

Abstract

Abstract: Background: Cognitive tasks delivered during ecological momentary assessment (EMA) may elucidate the short-term dynamics and contextual influences on cognition and judgements of performance. This paper provides initial validation of a smartphone task of facial emotion recognition in serious mental illness. Methods: A total of 86 participants with psychotic disorders (non-affective and affective psychosis), aged 19–65, were administered in-lab 'gold standard' affect recognition, neurocognition, and symptom assessments. They subsequently completed 10 days of the mobile facial emotion recognition task, assessing both accuracy and self-assessed performance, along with concurrent EMA of psychotic symptoms and mood. Validation focused on task adherence and predictors of adherence, gold standard convergent validity, and symptom and diagnostic group variation. Results: The mean rate of adherence to the task was 79%; no demographic or clinical variables predicted adherence. Convergent validity was observed with in-lab measures of facial emotion recognition, and no practice effects were observed on the mobile facial emotion recognition task. EMA reports of more severe voices, sadness, and paranoia were associated with worse performance, whereas mood more strongly associated with self-assessed performance. Conclusion: The mobile facial emotion recognition task was tolerated and demonstrated convergent validity with in-lab measures of the same construct. Social cognitive performance, and biased judgements previously shown to predict function, can be evaluated in real-time in naturalistic environments.