ORCID Profile
0000-0002-3823-8052
Current Organisations
NHS Lothian
,
The University of Edinburgh
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Publisher: Cambridge University Press (CUP)
Date: 21-09-2022
DOI: 10.1017/S0033291722002720
Abstract: Major depressive disorder (MDD) was previously associated with negative affective biases. Evidence from larger population-based studies, however, is lacking, including whether biases normalise with remission. We investigated associations between affective bias measures and depressive symptom severity across a large community-based s le, followed by examining differences between remitted in iduals and controls. Participants from Generation Scotland ( N = 1109) completed the: (i) Bristol Emotion Recognition Task (BERT), (ii) Face Affective Go/No-go (FAGN), and (iii) Cambridge Gambling Task (CGT). In iduals were classified as MDD-current ( n = 43), MDD-remitted ( n = 282), or controls ( n = 784). Analyses included using affective bias summary measures (primary analyses), followed by detailed emotion/condition analyses of BERT and FAGN (secondary analyses). For summary measures, the only significant finding was an association between greater symptoms and lower risk adjustment for CGT across the s le (in iduals with greater symptoms were less likely to bet more, despite increasingly favourable conditions). This was no longer significant when controlling for non-affective cognition. No differences were found for remitted-MDD v. controls. Detailed analysis of BERT and FAGN indicated subtle negative biases across multiple measures of affective cognition with increasing symptom severity, that were independent of non-effective cognition [e.g. greater tendency to rate faces as angry (BERT), and lower accuracy for happy/neutral conditions (FAGN)]. Results for remitted-MDD were inconsistent. This suggests the presence of subtle negative affective biases at the level of emotion/condition in association with depressive symptoms across the s le, over and above those accounted for by non-affective cognition, with no evidence for affective biases in remitted in iduals.
Publisher: Elsevier BV
Date: 09-2023
Publisher: F1000 Research Ltd
Date: 16-07-2021
DOI: 10.12688/WELLCOMEOPENRES.15538.2
Abstract: STratifying Resilience and Depression Longitudinally (STRADL) is a population-based study built on the Generation Scotland: Scottish Family Health Study (GS:SFHS) resource. The aim of STRADL is to subtype major depressive disorder (MDD) on the basis of its aetiology, using detailed clinical, cognitive, and brain imaging assessments. The GS:SFHS provides an important opportunity to study complex gene-environment interactions, incorporating linkage to existing datasets and inclusion of early-life variables for two longitudinal birth cohorts. Specifically, data collection in STRADL included: socio-economic and lifestyle variables physical measures questionnaire data that assesses resilience, early-life adversity, personality, psychological health, and lifetime history of mood disorder laboratory s les cognitive tests and brain magnetic resonance imaging. Some of the questionnaire and cognitive data were first assessed at the GS:SFHS baseline assessment between 2006-2011, thus providing longitudinal measures relevant to the study of depression, psychological resilience, and cognition. In addition, routinely collected historic NHS data and early-life variables are linked to STRADL data, further providing opportunities for longitudinal analysis. Recruitment has been completed and we consented and tested 1,188 participants.
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Liana Romaniuk.