To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure firstname.lastname@example.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
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.
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.
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.
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.
Email your librarian or administrator to recommend adding this to your organisation's collection.