BC Mental Health & Substance Use Services

ABSTRACT Background Metamemory is the awareness of and ability to evaluate one’s own cognitive abilities. This study examined impaired metamemory as a possible mechanism contributing to persistent cognitive symptoms after COVID-19. Methods Individuals with previous COVID-19 illness were recruited. Participants completed questionnaires regarding physical health, mental health, and their COVID-19 illness. To assess memory and metamemory performance, participants were presented with 50 words and then completed a two-alternative forced choice recognition memory task with a confidence rating after each trial. This was repeated for 3 blocks of 50 trials each. A signal detection theory framework was applied to derive metrics of memory performance (d’), metamemory performance (meta-d’), and metamemory efficiency (M-ratio). We compared participants who self-reported persistent cognitive symptoms at the time of their metamemory assessment (n = 47) to participants who denied persistent cognitive symptoms (n = 87). We used a general linear model to compare groups, covarying for age and days between COVID-19 and metamemory assessment. Results Participants with and without self-reported persistent cognitive symptoms did not differ on memory performance (d’: p = .24, β = 0.22 95% CI [−0.1, 0.6]), metamemory performance (meta-d’: p = .28, β = 0.20 95% CI [−0.2, 0.6]), or metamemory efficiency (M-ratio: p = .85, β = −0.04 95% CI [−0.4, 0.3]). Those with persistent cognitive symptoms reported a higher degree of depression (p < 0.001, β = 0.83 95% CI [0.5, 1.2]), anxiety (p = 0.016, β = 0.50 95% CI [0.2, 0.9]), and somatic symptom scores (p < 0.001, β = 0.92 95% CI [0.5, 1.3]). Conclusions Patients with and without self-reported persistent cognitive symptoms had similar memory accuracy and both demonstrated good (synchronous) awareness of their memory test performance. While both cognitive and metacognitive impairment appear unlikely to drive cognitive symptoms after COVID-19, psychological distress (particularly anxiety) remains a compelling candidate perpetuating factor. Future mechanistic research is necessary to understand if and how psychological distress contributes to cognitive symptoms, and vice versa.

In the Article by Tara Gomes and colleagues,1 it was concluded that initiation of safer opioid supply (SOS) programmes was associated with improvements in the rate of opioid toxicities, all-cause emergency department visits, all-cause inpatient hospitalisations, incident infections, and non-primary care-related health-care costs. The benefits in these factors were attributed to the initiation of SOS, similar to what was seen in the matched methadone initiation cohort, with the exception that the SOS group had significantly higher rates of opioid toxicity.

ABSTRACT Introduction Despite the recognized importance of social cognition in predicting functional outcomes in schizophrenia, there is a lack of widely accepted measures that assess this broad domain while possessing psychometric validity and predictive utility. This study aimed to address this gap by providing incremental validity data for a promising social cognitive measure assessing facial affect recognition in patients presenting with treatment-resistant psychosis. Method Using a clinical archival dataset comprising 59 consecutive admissions to an inpatient treatment-resistant psychosis unit, this study examined facial affect naming performance from the Advanced Clinical Solutions-Social Perception (ACS-SP) affect naming subtest, and the association with neuropsychological functioning and symptom severity. Hierarchical regression models were used to assess whether facial affect recognition predicted daily functioning, including measures of functional capacity and functional performance. Results The ACS-SP affect naming measure showed limited sensitivity for impairment relative to other cognitive domains. Affect naming showed weak to moderate correlations with a broad range of non-memory cognitive functions, and no association with symptom severity. After controlling for cognitive functioning and symptoms, the ACS-SP affect naming task predicted poorer functioning with regard to functional performance but not functional capacity. Conclusions The ACS-SP affect naming task associates weakly to moderately with other measures of cognition, but also likely taps into social cognitive skills not measured by typical neuropsychological tests. This measure was predictive of some aspects of functional outcomes in patients with treatment-resistant psychosis, and therefore may be a useful tool to incorporate into routine neuropsychological assessments in such treatment settings.

Social determinants are known to impact stroke risk and poststroke outcomes. Using complexity science, we examined interrelations between county- and individual-level social and clinical determinants influencing stroke functional outcomes. We examined a retrospective cohort of 2 961 664 patients diagnosed with acute ischemic or hemorrhagic stroke from 2218 US hospitals participating in the Get With The Guidelines-Stroke Registry from 2013 to 2019, linked by ZIP code with the county-level institute for health metrics and evaluation data. We constructed multilayer networks, estimating mixed graphical models of 32 nodes representing social and clinical factors. Networks included 4 layers of factors: (1) county-level social, (2) individual-level social, (3) clinical comorbidities, and (4) hospital encounters. Networks were estimated for patients with less favorable (modified Rankin Scale score 3-6) versus favorable (modified Rankin Scale score 0-2) outcomes. We compared network structure and node centrality measures between groups using bootstrap permutation analyses, identifying influential (hub) nodes. The overall influence of social determinants (global connectivity) was greater in patients with less favorable outcomes (P<0.001). Homelessness and Black race were hub nodes, indicating their role in mediating relationships between social and downstream clinical factors in patients with less favorable outcomes. Being uninsured had greater influence (closeness centrality; P<0.001) in patients with less favorable outcomes, indicating its role in amplifying the effects of social determinants. Greater county-level high school completion (P<0.001) and a lower proportion of the population living below the US poverty line (P=0.030) were directly associated with faster onset-to-arrival time in patients with less favorable functional outcomes. The clinical-social determinant network explained 34% of the variance of modified Rankin Scale scores. Social determinants have a substantial influence on functional outcomes after stroke. County-level poverty directly affected onset-to-arrival time and quality of care. Health insurance status and homelessness were influential and modifiable patient-level factors that may serve as critical leverage points for future interventions aimed at improving outcomes.

Context: Calls to collect patients’ race/ethnicity (RE) data as a measure to promote equitable health care among vulnerable patient groups are increasing. The COVID-19 pandemic has highlighted how a public health crisis disproportionately affects racialized patient groups. However, less is known about the uptake of RE data collection in the context of mental health care services. Methodology: A qualitative case study used surveys with mental health patients (n = 47) and providers (n = 12), a retrospective chart review, and a focus group to explore healthcare providers’ and patients’ perspectives on collecting RE data in Canada. Results: The patient survey data and focus groups show that patients avoid providing identifying information due to perceived stigma and discrimination and a lack of trust. Providers did not feel comfortable asking patients about RE, leading to chart review data where RE information was not systematically collected. Conclusions: The uptake and implementation of RE data collection in mental health care contexts require increased training and support, systematic implementation, and further evaluation and measurement of how the collection of RE data will be used to mitigate systemic racism and improve mental health outcomes.

Our recent improved understanding of traumatic brain injury (TBI) comes largely from cohort studies of TBI patients with indication for computed tomography (CT). Using CT head as an inclusion criterion may overestimate poor outcomes after TBI with Glasgow Coma Scale (GCS) 13-15. We aimed to compare outcomes after TBI in adults who had a head CT scan (with negative findings) versus those who had no CT when presenting to an emergency department. This was a secondary analysis of a trial that recruited adults with GCS = 13-15 after TBI in Vancouver, Canada. We included 493 participants (18-69 years, 54% female), after removing n = 19 with traumatic abnormalities on CT (intracranial and/or skull fracture). Outcomes were Glasgow Outcome Scale Extended (GOSE), Rivermead Post-Concussion Symptoms Questionnaire (RPQ), Patient Health Questionnaire (PHQ)-9, and generalized anxiety disorder (GAD)-7 at 6 months post-injury. Over half (55%) of participants received a CT. At 6 months, 55% of participants with CT and 49% without CT had functional limitations on GOSE; 32% with CT and 33% without CT reported severe post-concussion symptoms (RPQ ≥16); 26% (with CT) and 28% (without CT) screened positive for depression (PHQ-9 ≥ 10), and 25% (with CT) and 28% (without CT) screened positive for anxiety (GAD-7 ≥ 8). In regression adjusted for personal variables, participants with CT had somewhat higher odds of worse functioning (ordinal GOSE; 1.4, 95% CI 1.0-2.0) but similar odds of severe post-concussion symptoms (1.1, 95% CI: 0.7-1.7), and depression (1.1, 95% CI: 0.7-1.7) and anxiety (1.0, 95% CI: 0.6-1.5) symptoms. Adults with and without head CT have mostly comparable outcomes from TBI with GCS = 13-15. Requiring CT by clinical indication for study entry may not create problematic selection bias for outcome research.

INTRODUCTIONIn the aging brain, cognitive abilities emerge from the coordination of complex pathways arising from a balance between protective lifestyle and environmental factors and accumulation of neuropathologies.METHODSAs part of the Rush Memory and Aging Project (n = 440), we measured accelerometer‐based actigraphy, cognitive performance, and after brain autopsy, selected reaction monitoring mass spectrometry. Multilevel network analysis was used to examine the relationships among the molecular machinery of vesicular neurotransmission, Alzheimer's disease (AD) neuropathology, cognition, and late‐life physical activity.RESULTSSynaptic peptides involved in neuronal secretory function were the most influential contributors to the multilayer network, reflecting the complex interdependencies among AD pathology, synaptic processes, and late‐life cognition. Older adults with lower physical activity evidenced stronger adverse relationships among phosphorylated tau peptides, markers of synaptic integrity, and tangle pathology.DISCUSSIONNetwork‐based approaches simultaneously model interdependent biological processes and advance understanding of the role of physical activity in age‐associated cognitive impairment.HighlightsNetwork‐based approaches simultaneously model interdependent biological processes.Secretory synaptic peptides were influential contributors to the multilayer network.Older adults with lower physical activity had adverse relationships among pathology.There was interdependence among phosphorylated tau, synaptic integrity, and tangles.Network methods elucidate the role of physical activity in cognitive impairment.

BACKGROUND Cognitive impairments are a key aspect of schizophrenia spectrum disorders (SSDs), significantly affecting clinical and functional outcomes. The COVID-19 pandemic has heightened concerns about mental health services and cognitive stimulation opportunities. Despite evidence-based interventions like action-based cognitive remediation (ABCR) and metacognitive training (MCT), a research-to-practice gap exists in their application across mental health settings. OBJECTIVE The iCogCA study aims to address this gap by implementing digital ABCR and MCT through a national Canadian collaborative effort using digital psychological interventions to enhance cognitive health in SSDs. METHODS The study involves 5 Canadian sites, with mental health care practitioners trained digitally through the E-Cog platform, which was developed by our research group. Over 2.5 years, participants with SSDs will undergo pre- and postintervention assessments for clinical symptoms, cognition, and functioning. Each site will run groups annually for both ABCR and MCT, totaling ~390 participants. A nonrandomized concurrent controlled design will assess effectiveness design, in which one intervention (eg, ABCR) acts as the active control for the other (eg, MCT) and vice versa, comparing cognitive and clinical outcomes between the interventions using generalized linear mixed effect modeling. Implementation strategy evaluation will consider the digital platform’s efficacy for mental health care practitioners’ training, contextual factors influencing implementation, and sustainability, using descriptive statistics for quantitative data and thematic analysis for qualitative data. RESULTS A pilot pragmatic trial has been conducted previously at the Montreal site, evaluating 3 early implementation outcomes: acceptability, feasibility, and engagement. Patient and therapist acceptability was deemed as high and feasible (21/28, 75% of recruited service users completed therapy, rated feasible by therapists). Technology did not appear to significantly impede program participation. Therapist-rated levels of engagement were also satisfactory. In the ongoing study, recruitment is underway (114 participants recruited as of winter 2024), and intervention groups have been conducted at all sites, with therapists receiving training via the E-Cog learning platform (32 enrolled as of winter 2024). CONCLUSIONS At least 3 significant innovations will stem from this project. First, this national effort represents a catalyst for the use of digital technologies to increase the adoption of evidence-based interventions and will provide important results on the effectiveness of digitally delivered ABCR and MCT. Second, the results of the implementation component of this study will generate the expertise needed to inform the implementation of similar initiatives. Third, the proposed study will introduce and validate our platform to train and supervise mental health care practitioners to deliver these interventions, which will then be made accessible to the broader mental health community. CLINICALTRIAL ClinicalTrials.gov NCT05661448; https://clinicaltrials.gov/study/NCT05661448 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/63269