IMPORTANCEDepression is a debilitating and highly prevalent mental health disorder. There is a need for new, effective, and scalable treatments for depression, and cognitive bias modification (CBM) of negative emotional processing biases has been suggested as one possibility. Such treatments may form the basis of 'digital therapeutics', that could be administered remotely and at low cost, should they prove to be effective.
OBJECTIVESStudy one was designed to determine neural correlates of a recently developed CBM technique for emotion recognition training; specifically, our aim was to compare the effects of training vs placebo on pre-specified regions of interest involved in emotion processing that are known to be sensitive to antidepressant treatment. Study two aimed to investigate efficacy of training on mood measures at 2 and 6-week follow-up and was powered to replicate and extend earlier findings.
DESIGN, SETTING, AND PARTICIPANTSBoth studies were double blind RCTs, in which participants completed five sessions of emotion recognition training or sham training, in the laboratory, over a one-week period. In study one (N=37), following this training, participants completed a novel emotion recognition task whilst undergoing fMRI. In study two (N=190), measures of mood were assessed post training, and at 2-week and 6-week follow-up. Both studies recruited analogue samples of healthy volunteers with high levels of depressive symptoms (BDI-ii > 14).
MAIN OUTCOMES AND MEASURESIn study one, our primary outcome was neural activation in the following pre-specified regions of interest: the bilateral amygdala, the mPFC, bilateral dlPFC, and the occipital cortex. In study two, our primary outcome was depressive symptoms over the last 2 weeks assessed using the BDI-ii at 6-week follow-up. Secondary outcomes included depressive to work? A cognitive neuropsychological model of antidepressant drug action. . Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage, 17(2), 825-841.
Introduction. There are growing concerns about the impact of the COVID-19 pandemic on mental health. With government-imposed restrictions as well as a general burden on healthcare systems, the pandemic has the potential to disrupt the access to, and delivery of, mental healthcare. Ultimately, this could potentially lead to unmet needs of individuals requiring mental health support.
Methods. Electronic healthcare records from primary care psychological therapy services (Improving Access to Psychological Therapy) in England were used to examine changes in access to mental health services and service delivery during early stages of the COVID-19 pandemic. A cross-sectional, descriptive timeseries was conducted using data from 1st January 2019 to 24th May 2020 across five NHS trusts to examine patterns in referrals to services (n = 171,823) and appointments taking place (n = 865,902).
Results. The number of patients accessing mental health services dropped by an average of 55% in the 9 weeks after lockdown was announced, reaching a maximum reduction of 74% in the initial 3 weeks after lockdown in the UK. As referrals began to increase again, there was a relatively faster increase in referrals from Black, Asian, and ethnic minority groups as well an increase in referrals from more densely populated areas. Despite a reduction in access, service providers adapted to infection control guidance by rapidly shifting to remote delivery of care.
Interpretation. Services were able to rapidly adapt to provide continuity of care in mental healthcare. However, patients accessing services reduced dramatically, potentially placing a future burden on service providers to treat a likely backlog of patients in addition to a possible excess of patients as the long-term consequences of the pandemic become more apparent. Despite the observational nature of the data, which should be noted, the present study can inform the planning of service provision and policy.
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