BackgroundCollaborations are often a cornerstone of global health research. Power dynamics can shape if and how local researchers are included in manuscripts. This article investigates how international collaborations affect the representation of local authors, overall and in first and last author positions, in African health research.MethodsWe extracted papers on ‘health’ in sub-Saharan Africa indexed in PubMed and published between 2014 and 2016. The author’s affiliation was used to classify the individual as from the country of the paper’s focus, from another African country, from Europe, from the USA/Canada or from another locale. Authors classified as from the USA/Canada were further subclassified if the author was from a top US university. In primary analyses, individuals with multiple affiliations were presumed to be from a high-income country if they contained any affiliation from a high-income country. In sensitivity analyses, these individuals were presumed to be from an African country if they contained any affiliation an African country. Differences in paper characteristics and representation of local coauthors are compared by collaborative type using χ² tests.ResultsOf the 7100 articles identified, 68.3% included collaborators from the USA, Canada, Europe and/or another African country. 54.0% of all 43 429 authors and 52.9% of 7100 first authors were from the country of the paper’s focus. Representation dropped if any collaborators were from USA, Canada or Europe with the lowest representation for collaborators from top US universities—for these papers, 41.3% of all authors and 23.0% of first authors were from country of paper’s focus. Local representation was highest with collaborators from another African country. 13.5% of all papers had no local coauthors.DiscussionIndividuals, institutions and funders from high-income countries should challenge persistent power differentials in global health research. South-South collaborations can help African researchers expand technical expertise while maintaining presence on the resulting research.
Functional imaging studies of brain damaged patients offer a unique opportunity to understand how sensorimotor and cognitive tasks can be carried out when parts of the neural system that support normal performance are no longer available. In addition to knowing which regions a patient activates, we also need to know how these regions interact with one another, and how these inter-regional interactions deviate from normal. Dynamic causal modeling (DCM) offers the opportunity to assess task-dependent interactions within a set of regions. Here we review its use in patients when the question of interest concerns the characterization of abnormal connectivity for a given pathology. We describe the currently available implementations of DCM for fMRI responses, varying from the deterministic bilinear models with one-state equation to the stochastic non-linear models with two-state equations. We also highlight the importance of the new Bayesian model selection and averaging tools that allow different plausible models to be compared at the single subject and group level. These procedures allow inferences to be made at different levels of model selection, from features (model families) to connectivity parameters. Following a critical review of previous DCM studies that investigated abnormal connectivity we propose a systematic procedure that will ensure more flexibility and efficiency when using DCM in patients. Finally, some practical and methodological issues crucial for interpreting or generalizing DCM findings in patients are discussed.
IMPORTANCE Prescriptions for antipsychotic medications continue to increase across many brain disorders, including off-label use in children and elderly individuals. Concerning animal and uncontrolled human data suggest antipsychotics are associated with change in brain structure, but to our knowledge, there are no controlled human studies that have yet addressed this question.OBJECTIVE To assess the effects of antipsychotics on brain structure in humans. DESIGN, SETTING, AND PARTICIPANTSPrespecified secondary analysis of a double-blind, randomized, placebo-controlled trial over a 36-week period at 5 academic centers. All participants, aged 18 to 85 years, were recruited from the multicenter Study of the Pharmacotherapy of Psychotic Depression II (STOP-PD II). All participants had major depressive disorder with psychotic features (psychotic depression) and were prescribed olanzapine and sertraline for a period of 12 to 20 weeks, which included 8 weeks of remission of psychosis and remission/near remission of depression. Participants were then were randomized to continue receiving this regimen or to be switched to placebo and sertraline for a subsequent 36-week period. Data were analyzed between October 2018 and February 2019.INTERVENTIONS Those who consented to the imaging study completed a magnetic resonance imaging (MRI) scan at the time of randomization and a second MRI scan at the end of the 36-week period or at time of relapse. MAIN OUTCOMES AND MEASURESThe primary outcome measure was cortical thickness in gray matter and the secondary outcome measure was microstructural integrity of white matter.RESULTS Eighty-eight participants (age range, 18-85 years) completed a baseline scan; 75 completed a follow-up scan, of which 72 (32 men and 40 women) were useable for final analyses. There was a significant treatment-group by time interaction in cortical thickness (left, t = 3.3; P = .001; right, t = 3.6; P < .001) but not surface area. No significant interaction was found for fractional anisotropy, but one for mean diffusivity of the white matter skeleton was present (t = −2.6, P = .01). When the analysis was restricted to those who sustained remission, exposure to olanzapine compared with placebo was associated with significant decreases in cortical thickness in the left hemisphere (β [SE], 0.04 [0.009]; t 34.4 = 4.7; P <.001), and the right hemisphere (β [SE], 0.03 [0.009]; t 35.1 = 3.6; P <.001). Post hoc analyses showed that those who relapsed receiving placebo experienced decreases in cortical thickness compared with those who sustained remission. CONCLUSIONS AND RELEVANCEIn this secondary analysis of a randomized clinical trial, antipsychotic medication was shown to change brain structure. This information is important for prescribing in psychiatric conditions where alternatives are present. However, adverse effects of relapse on brain structure support antipsychotic treatment during active illness.
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