The New Jersey Kids Study (NJKS) is a transdisciplinary statewide initiative to understand influences on child health, development, and disease. We conducted a mixed-methods study of project planning teams to investigate team effectiveness and relationships between team dynamics and quality of deliverables.

Ten theme-based working groups (WGs) (e.g., Neurodevelopment, Nutrition) informed protocol development and submitted final reports. WG members (n = 79, 75%) completed questionnaires including de-identified demographic and professional information and a modified TeamSTEPPS Team Assessment Questionnaire (TAQ). Reviewers independently evaluated final reports using a standardized tool. We analyzed questionnaire results and final report assessments using linear regression and performed constant comparative qualitative analysis to identify central themes.

WG-level factors associated with greater team effectiveness included proportion of full professors (β = 31.24, 95% CI 27.65–34.82), team size (β = 0.81, 95% CI 0.70–0.92), and percent dedicated research effort (β = 0.11, 95% CI 0.09–0.13); age distribution (β = −2.67, 95% CI –3.00 to –2.38) and diversity of school affiliations (β = –33.32, 95% CI –36.84 to –29.80) were inversely associated with team effectiveness. No factors were associated with final report assessments. Perceptions of overall initiative leadership were associated with expressed enthusiasm for future NJKS participation. Qualitative analyses of final reports yielded four themes related to team science practices: organization and process, collaboration, task delegation, and decision-making patterns.

We identified several correlates of team effectiveness in a team science initiative's early planning phase. Extra effort may be needed to bridge differences in team members' backgrounds to enhance the effectiveness of diverse teams. This work also highlights leadership as an important component in future investigator engagement.

PLWH report using cannabis for both recreational reasons and HIV symptom management (e.g., nausea, pain, depression/anxiety). Recent literature suggests that cannabis may attenuate HIV symptoms and neuroinflammation, which are strongly related to neurocognition. Additionally, older adults who are particularly vulnerable to cognitive impairment experience a decline in the endogenous cannabinoid system with age. Therefore, the aims of the present study were 1) to determine if cannabis use is associated with cognitive performance in PLWH, 2) to determine if age moderates the relationship between cannabis use and cognition in PLWH, and 3) to determine if there are differences in cognition in cannabis non-users, occasional users, and daily users among PLWH.

The sample included 225 PLWH (78% undetectable; 51% female, Mean age=49.10) who were classified as non-users (n=52), occasional users (n=53), or daily users (n=120). Cannabis use was measured via the Timeline Follow-back (TLFB). Cognition was examined using the NIH Toolbox Cognition Battery, which included measures of attention, working memory, executive function, processing speed, and episodic memory, as well as a fluid cognition composite score.

Increased frequency of cannabis use was weakly positively associated with episodic memory performance, r(224) = 0.15, p<0.05. Results of the multiple regression indicate that frequency of cannabis use was not significantly associated with any of the six cognitive domains. However, there was a significant interaction between age and cannabis use in the domains of attention (ß= 0.13, p < 0.05), working memory (ß= 0.12, p < 0.05), and episodic memory (ß= 0.15, p < 0.05), suggesting worse cognitive performance in older adults who use cannabis as compared to younger adults in this sample. When participants were grouped based on use status, there were no significant main effects of group.

After controlling for the effects of demographic factors and HIV disease severity, no significant negative associations between cannabis use and cognition were observed, suggesting that cannabis use is not related to cognitive impairment in PLWH. However, results were clarified by a significant interaction, indicating that older adults who use cannabis perform worse in the domains of attention, working memory, and episodic memory compared to younger adults, suggesting synergistic cognitive effects of age and cannabis use. We additionally found preliminary evidence for a potential positive effect of cannabis use on episodic memory in the overall sample. Future studies examining biological and behavioral mechanisms of improvement will be necessary to better examine this relationship.

Cannabis use has been linked to psychotic disorders but this association has been primarily observed in the Global North. This study investigates patterns of cannabis use and associations with psychoses in three Global South (regions within Latin America, Asia, Africa and Oceania) settings.

Case–control study within the International Programme of Research on Psychotic Disorders (INTREPID) II conducted between May 2018 and September 2020. In each setting, we recruited over 200 individuals with an untreated psychosis and individually-matched controls (Kancheepuram India; Ibadan, Nigeria; northern Trinidad). Controls, with no past or current psychotic disorder, were individually-matched to cases by 5-year age group, sex and neighbourhood. Presence of psychotic disorder assessed using the Schedules for Clinical Assessment in Neuropsychiatry and cannabis exposure measured by the World Health Organisation Alcohol, Smoking and Substance Involvement Screening Test (ASSIST).

Cases reported higher lifetime and frequent cannabis use than controls in each setting. In Trinidad, cannabis use was associated with increased odds of psychotic disorder: lifetime cannabis use (adj. OR 1.58, 95% CI 0.99–2.53); frequent cannabis use (adj. OR 1.99, 95% CI 1.10–3.60); cannabis dependency (as measured by high ASSIST score) (adj. OR 4.70, 95% CI 1.77–12.47), early age of first use (adj. OR 1.83, 95% CI 1.03–3.27). Cannabis use in the other two settings was too rare to examine associations.

In line with previous studies, we found associations between cannabis use and the occurrence and age of onset of psychoses in Trinidad. These findings have implications for strategies for prevention of psychosis.

Extensive evidence indicates that rates of psychotic disorder are elevated in more urban compared with less urban areas, but this evidence largely originates from Northern Europe. It is unclear whether the same association holds globally. This study examined the association between urban residence and rates of psychotic disorder in catchment areas in India (Kancheepuram, Tamil Nadu), Nigeria (Ibadan, Oyo), and Northern Trinidad.

Comprehensive case detection systems were developed based on extensive pilot work to identify individuals aged 18–64 with previously untreated psychotic disorders residing in each catchment area (May 2018–April/May/July 2020). Area of residence and basic demographic details were collected for eligible cases. We compared rates of psychotic disorder in the more v. less urban administrative areas within each catchment area, based on all cases detected, and repeated these analyses while restricting to recent onset cases (<2 years/<5 years).

We found evidence of higher overall rates of psychosis in more urban areas within the Trinidadian catchment area (IRR: 3.24, 95% CI 2.68–3.91), an inverse association in the Nigerian catchment area (IRR: 0.68, 95% CI 0.51–0.91) and no association in the Indian catchment area (IRR: 1.18, 95% CI 0.93–1.52). When restricting to recent onset cases, we found a modest positive association in the Indian catchment area.

This study suggests that urbanicity is associated with higher rates of psychotic disorder in some but not all contexts outside of Northern Europe. Future studies should test candidate mechanisms that may underlie the associations observed, such as exposure to violence.

There is evidence of an association between life events and psychosis in Europe, North America and Australasia, but few studies have examined this association in the rest of the world.

To test the association between exposure to life events and psychosis in catchment areas in India, Nigeria, and Trinidad and Tobago.

We conducted a population-based, matched case–control study of 194 participants in India, Nigeria, and Trinidad and Tobago. Cases were recruited through comprehensive population-based, case-finding strategies. The Harvard Trauma Questionnaire was used to measure life events. The Screening Schedule for Psychosis was used to screen for psychotic symptoms. The association between psychosis and having experienced life events (experienced or witnessed) was estimated by conditional logistic regression.

There was no overall evidence of an association between psychosis and having experienced or witnessed life events (adjusted odds ratio 1.19, 95% CI 0.62–2.28). We found evidence of effect modification by site (P = 0.002), with stronger evidence of an association in India (adjusted odds ratio 1.56, 95% CI 1.03–2.34), inconclusive evidence in Nigeria (adjusted odds ratio 1.17, 95% CI 0.95–1.45) and evidence of an inverse association in Trinidad and Tobago (adjusted odds ratio 0.66, 95% CI 0.44–0.97).

This study found no overall evidence of an association between witnessing or experiencing life events and psychotic disorder across three culturally and economically diverse countries. There was preliminary evidence that the association varies between settings.

The literature on Alzheimer’s disease (AD) provides little data about long-term cognitive course trajectories. We identify global cognitive outcome trajectories and associated predictor variables that may inform clinical research and care.

Data derived from the National Alzheimer’s Coordinating Center (NACC) Uniform Data Set were used to examine the cognitive course of persons with possible or probable AD, a Mini-Mental State Examination (MMSE) of ≥10, and complete annual assessments for 5 years.

Thirty-six Alzheimer’s Disease Research Centers.

Four hundred and fourteen persons.

We used a hybrid approach comprising qualitative analysis of MMSE trajectory graphs that were operationalized empirically and binary logistic regression analyses to assess 19 variables’ associations with each trajectory. MMSE scores of ±3 points or greater were considered clinically meaningful.

Five distinct cognitive trajectories were identified: fast decliners (32.6%), slow decliners (30.7%), zigzag stable (15.9%), stable (15.9%), and improvers (4.8%). The decliner groups had three subtypes: curvilinear, zigzag, and late decline. The fast decliners were associated with female gender, lower baseline MMSE scores, a shorter illness duration, or receiving a cognitive enhancer. An early MMSE decline of ≥3 points predicted a worse outcome. A higher rate of traumatic brain injury, the absence of an ApoE ϵ4 allele, and male gender were the strongest predictors of favorable outcomes.

Our hybrid approach revealed five distinct cognitive trajectories and a variegated pattern within the decliners and stable/improvers that was more consistent with real-world clinical experience than prior statistically modeled studies. Future investigations need to determine the consistency of the distribution of these categories across settings.

In this analysis, we argue that the ‘treatment gap’ for common mental disorders often reflects lack of demand, arising because services fail to address the needs of disadvantaged communities. We propose a route forward for global mental health, with explicit focus on action on the socioeconomic determinants of psychological suffering.

This study aimed to investigate general factors associated with prognosis regardless of the type of treatment received, for adults with depression in primary care.

We searched Medline, Embase, PsycINFO and Cochrane Central (inception to 12/01/2020) for RCTs that included the most commonly used comprehensive measure of depressive and anxiety disorder symptoms and diagnoses, in primary care depression RCTs (the Revised Clinical Interview Schedule: CIS-R). Two-stage random-effects meta-analyses were conducted.

Twelve (n = 6024) of thirteen eligible studies (n = 6175) provided individual patient data. There was a 31% (95%CI: 25 to 37) difference in depressive symptoms at 3–4 months per standard deviation increase in baseline depressive symptoms. Four additional factors: the duration of anxiety; duration of depression; comorbid panic disorder; and a history of antidepressant treatment were also independently associated with poorer prognosis. There was evidence that the difference in prognosis when these factors were combined could be of clinical importance. Adding these variables improved the amount of variance explained in 3–4 month depressive symptoms from 16% using depressive symptom severity alone to 27%. Risk of bias (assessed with QUIPS) was low in all studies and quality (assessed with GRADE) was high. Sensitivity analyses did not alter our conclusions.

When adults seek treatment for depression clinicians should routinely assess for the duration of anxiety, duration of depression, comorbid panic disorder, and a history of antidepressant treatment alongside depressive symptom severity. This could provide clinicians and patients with useful and desired information to elucidate prognosis and aid the clinical management of depression.

To characterize associations between exposures within and outside the medical workplace with healthcare personnel (HCP) SARS-CoV-2 infection, including the effect of various forms of respiratory protection.

Case–control study.

We collected data from international participants via an online survey.

In total, 1,130 HCP (244 cases with laboratory-confirmed COVID-19, and 886 controls healthy throughout the pandemic) from 67 countries not meeting prespecified exclusion (ie, healthy but not working, missing workplace exposure data, COVID symptoms without lab confirmation) were included in this study.

Respondents were queried regarding workplace exposures, respiratory protection, and extra-occupational activities. Odds ratios for HCP infection were calculated using multivariable logistic regression and sensitivity analyses controlling for confounders and known biases.

HCP infection was associated with non–aerosol-generating contact with COVID-19 patients (adjusted OR, 1.4; 95% CI, 1.04–1.9; P = .03) and extra-occupational exposures including gatherings of ≥10 people, patronizing restaurants or bars, and public transportation (adjusted OR range, 3.1–16.2). Respirator use during aerosol-generating procedures (AGPs) was associated with lower odds of HCP infection (adjusted OR, 0.4; 95% CI, 0.2–0.8, P = .005), as was exposure to intensive care and dedicated COVID units, negative pressure rooms, and personal protective equipment (PPE) observers (adjusted OR range, 0.4–0.7).

COVID-19 transmission to HCP was associated with medical exposures currently considered lower-risk and multiple extra-occupational exposures, and exposures associated with proper use of appropriate PPE were protective. Closer scrutiny of infection control measures surrounding healthcare activities and medical settings considered lower risk, and continued awareness of the risks of public congregation, may reduce the incidence of HCP infection.

Psychotherapies for depression are equally effective on average, but individual responses vary widely. Outcomes can be improved by optimizing treatment selection using multivariate prediction models. A promising approach is the Personalized Advantage Index (PAI) that predicts the optimal treatment for a given individual and the magnitude of the advantage. The current study aimed to extend the PAI to long-term depression outcomes after acute-phase psychotherapy.

Data come from a randomized trial comparing cognitive therapy (CT, n = 76) and interpersonal psychotherapy (IPT, n = 75) for major depressive disorder (MDD). Primary outcome was depression severity, as assessed by the BDI-II, during 17-month follow-up. First, predictors and moderators were selected from 38 pre-treatment variables using a two-step machine learning approach. Second, predictors and moderators were combined into a final model, from which PAI predictions were computed with cross-validation. Long-term PAI predictions were then compared to actual follow-up outcomes and post-treatment PAI predictions.

One predictor (parental alcohol abuse) and two moderators (recent life events; childhood maltreatment) were identified. Individuals assigned to their PAI-indicated treatment had lower follow-up depression severity compared to those assigned to their PAI-non-indicated treatment. This difference was significant in two subsets of the overall sample: those whose PAI score was in the upper 60%, and those whose PAI indicated CT, irrespective of magnitude. Long-term predictions did not overlap substantially with predictions for acute benefit.

If replicated, long-term PAI predictions could enhance precision medicine by selecting the optimal treatment for a given depressed individual over the long term.