Background No trials have tested multifaceted mental health interventions recommended by public health organisations during COVID-19. The objective of this trial was to evaluate the effect of the Scleroderma Patient-centered Intervention Network COVID-19 Home-isolation Activities Together (SPIN-CHAT) Program on anxiety symptoms and other mental health outcomes among people vulnerable during COVID-19 owing to a pre-existing medical condition. Methods The SPIN-CHAT Trial was a pragmatic, two-arm, parallel, partially nested, randomised, controlled trial (1:1 allocation to intervention or waitlist). Eligible participants with systemic sclerosis were recruited from the international SPIN COVID-19 Cohort. SPIN COVID-19 Cohort participants were eligible for the trial if they completed baseline measures and had at least mild anxiety symptoms, had not tested positive for COVID-19, and were not currently receiving mental health counselling. SPIN-CHAT is a 4-week (3 sessions per week) videoconference-based group intervention that provided education and practice with mental health coping strategies, and provided social support to reduce isolation. Groups included 6–10 participants. The primary outcome analysed in the intention-to-treat population was anxiety symptoms (PROMIS Anxiety 4a version 1.0) immediately post-intervention. This trial is registered with ClinicalTrials.gov , NCT04335279 and is complete. Findings Of participants who completed baseline measures between April 9, 2020, and April 27, 2020, 560 participants were eligible and 172 participants were randomly assigned to intervention (n=86) or waitlist (n=86). Mean age was 55·0 years (SD 11·4 years), 162 (94%) were women, and 136 (79%) identified as White. In intention-to-treat analyses, the intervention did not significantly reduce anxiety symptoms post-intervention (−1·57 points, 95% CI −3·59 to 0·45; standardised mean difference [SMD] −0·22 points) but reduced symptoms 6 weeks later (−2·36 points, 95% CI −4·56 to −0·16; SMD −0·31). Depression symptoms were significantly lower 6 weeks post-intervention (−1·64 points, 95% CI −2·91 to −0·37; SMD −0·31); no other secondary outcomes were significant. No adverse events were reported. Interpretation The intervention did not significantly improve anxiety symptoms or other mental health outcomes post-intervention. However, anxiety and depression symptoms were significantly lower 6 weeks later, potentially capturing the time it took for new skills and social support between intervention participants to affect mental health. Multi-faceted interventions such as SPIN-CHAT have potential to address mental health needs in vulnerable groups during COVID-19, yet uncertainty remains about effectiveness. Funding Canadian Institutes of Health Research (CIHR; VR4-172745, MS1-173066); McGill Interdisciplinary Initiative in Infection and Immunity Eme...

Introduction No studies have reported mental health symptom comparisons prior to and during COVID-19 in vulnerable medical populations. Objective To compare anxiety and depression symptoms among people with a pre-existing medical condition and factors associated with changes. Methods Pre-COVID-19 Scleroderma Patient-centered Intervention Network Cohort data were linked to COVID-19 data from April 2020. Multiple linear and logistic regression were used to assess factors associated with continuous change and ≥ 1 minimal clinically important difference (MCID) change for anxiety (PROMIS Anxiety 4a v1.0; MCID = 4.0) and depression (Patient Health Questionnaire-8; MCID = 3.0) symptoms, controlling for pre-COVID-19 levels. Results Mean anxiety symptoms increased 4.9 points (95% confidence interval [CI] 4.0 to 5.7). Depression symptom change was negligible (0.3 points; 95% CI -0.7 to 0.2). Compared to France ( N = 159), adjusted anxiety symptom change scores were significantly higher in the United Kingdom ( N = 50; 3.3 points, 95% CI 0.9 to 5.6), United States ( N = 128; 2.5 points, 95% CI 0.7 to 4.2), and Canada ( N = 98; 1.9 points, 95% CI 0.1 to 3.8). Odds of ≥1 MCID increase were 2.6 for the United Kingdom (95% CI 1.2 to 5.7) but not significant for the United States (1.6, 95% CI 0.9 to 2.9) or Canada (1.4, 95% CI 0.7 to 2.5). Older age and adequate financial resources were associated with less continuous anxiety increase. Employment and shorter time since diagnosis were associated with lower odds of a ≥ 1 MCID increase. Conclusions Anxiety symptoms, but not depression symptoms, increased dramatically during COVID-19 among people with a pre-existing medical condition.

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How do people learn when to allocate how much cognitive control to which task? According to the Learned Value of Control (LVOC) model, people learn to predict the value of alternative control allocations from features of a situation. This suggests that people may generalize the value of control learned in one situation to others with shared features, even when demands for control are different. This makes the intriguing prediction that what a person learned in one setting could cause them to misestimate the need for, and potentially overexert, control in another setting, even if this harms their performance. To test this prediction, we had participants perform a novel variant of the Stroop task in which, on each trial, they could choose to either name the color (more control-demanding) or read the word (more automatic). Only one of these tasks was rewarded each trial and could be predicted by one or more stimulus features (the color and/or word). Participants first learned colors and then words that predicted the rewarded task. Then, we tested how these learned feature associations transferred to novel stimuli with some overlapping features. The stimulus-task-reward associations were designed so that for certain combinations of stimuli, transfer of learned feature associations would incorrectly predict that more highly rewarded task would be color-naming, even though the actually rewarded task was word-reading and therefore did not require engaging control. Our results demonstrated that participants overexerted control for these stimuli, providing support for the feature-based learning mechanism described by the LVOC model.

How do people learn when to allocate how much cognitive control to which task? According to the Learned Value of Control (LVOC) model, people learn to predict the value of alternative control allocations from features of a given situation. This suggests that people may generalize the value of control learned in one situation to other situations with shared features, even when the demands for cognitive control are different. This makes the intriguing prediction that what a person learned in one setting could, under some circumstances, cause them to misestimate the need for, and potentially over-exert control in another setting, even if this harms their performance. To test this prediction, we had participants perform a novel variant of the Stroop task in which, on each trial, they could choose to either name the color (more control-demanding) or read the word (more automatic). However only one of these tasks was rewarded, it changed from trial to trial, and could be predicted by one or more of the stimulus features (the color and/or the word). Participants first learned colors that predicted the rewarded task. Then they learned words that predicted the rewarded task. In the third part of the experiment, we tested how these learned feature associations transferred to novel stimuli with some overlapping features. The stimulus-task-reward associations were designed so that for certain combinations of stimuli the transfer of learned feature associations would incorrectly predict that more highly rewarded task would be color naming, which would require the exertion of control, even though the actually rewarded task was word reading and therefore did not require the engagement of control. Our results demonstrated that participants over-exerted control for these stimuli, providing support for the feature-based learning mechanism described by the LVOC model.