The goal of the Patient-Centered Outcomes Research Partnership was to prepare health care professionals and researchers to conduct patient-centered outcomes and comparative effectiveness research (CER). Substantial evidence gaps, heterogeneous health care systems, and decision-making challenges in the USA underscore the need for evidence-based strategies.

We engaged five community-based health care organizations that serve diverse and underrepresented patient populations from Hawai’i to Minnesota. Each partner nominated two in-house scholars to participate in the 2-year program. The program focused on seven competencies pertinent to patient-centered outcomes and CER. It combined in-person and experiential learning with asynchronous, online education, and created adaptive, pragmatic learning opportunities and a Summer Institute. Metrics included the Clinical Research Appraisal Inventory (CRAI), a tool designed to assess research self-efficacy and clinical research skills across 10 domains.

We trained 31 scholars in 3 cohorts. Mean scores in nine domains of the CRAI improved; greater improvement was observed from the beginning to the midpoint than from the midpoint to conclusion of the program. Across all three cohorts, mean scores on 52 items (100%) increased (p ≤ 0.01), and 91% of scholars reported the program improved their skills moderately/significantly. Satisfaction with the program was high (91%).

Investigators that conduct patient-centered outcomes and CER must know how to collaborate with regional health care systems to identify priorities; pose questions; design, conduct, and disseminate observational and experimental research; and transform knowledge into practical clinical applications. Training programs such as ours can facilitate such collaborations.

The impact of the coronavirus disease 2019 (COVID-19) pandemic on mental health is still being unravelled. It is important to identify which individuals are at greatest risk of worsening symptoms. This study aimed to examine changes in depression, anxiety and post-traumatic stress disorder (PTSD) symptoms using prospective and retrospective symptom change assessments, and to find and examine the effect of key risk factors.

Online questionnaires were administered to 34 465 individuals (aged 16 years or above) in April/May 2020 in the UK, recruited from existing cohorts or via social media. Around one-third (n = 12 718) of included participants had prior diagnoses of depression or anxiety and had completed pre-pandemic mental health assessments (between September 2018 and February 2020), allowing prospective investigation of symptom change.

Prospective symptom analyses showed small decreases in depression (PHQ-9: −0.43 points) and anxiety [generalised anxiety disorder scale – 7 items (GAD)-7: −0.33 points] and increases in PTSD (PCL-6: 0.22 points). Conversely, retrospective symptom analyses demonstrated significant large increases (PHQ-9: 2.40; GAD-7 = 1.97), with 55% reported worsening mental health since the beginning of the pandemic on a global change rating. Across both prospective and retrospective measures of symptom change, worsening depression, anxiety and PTSD symptoms were associated with prior mental health diagnoses, female gender, young age and unemployed/student status.

We highlight the effect of prior mental health diagnoses on worsening mental health during the pandemic and confirm previously reported sociodemographic risk factors. Discrepancies between prospective and retrospective measures of changes in mental health may be related to recall bias-related underestimation of prior symptom severity.

Ketamine is a rapidly-acting antidepressant treatment with robust response rates. Previous studies have reported that serial ketamine therapy modulates resting state functional connectivity in several large-scale networks, though it remains unknown whether variations in brain structure, function, and connectivity impact subsequent treatment success. We used a data-driven approach to determine whether pretreatment multimodal neuroimaging measures predict changes along symptom dimensions of depression following serial ketamine infusion.

Patients with depression (n = 60) received structural, resting state functional, and diffusion MRI scans before treatment. Depressive symptoms were assessed using the 17-item Hamilton Depression Rating Scale (HDRS-17), the Inventory of Depressive Symptomatology (IDS-C), and the Rumination Response Scale (RRS) before and 24 h after patients received four (0.5 mg/kg) infusions of racemic ketamine over 2 weeks. Nineteen unaffected controls were assessed at similar timepoints. Random forest regression models predicted symptom changes using pretreatment multimodal neuroimaging and demographic measures.

Two HDRS-17 subscales, the HDRS-6 and core mood and anhedonia (CMA) symptoms, and the RRS: reflection (RRSR) scale were predicted significantly with 19, 27, and 1% variance explained, respectively. Increased right medial prefrontal cortex/anterior cingulate and posterior insula (PoI) and lower kurtosis of the superior longitudinal fasciculus predicted reduced HDRS-6 and CMA symptoms following treatment. RRSR change was predicted by global connectivity of the left posterior cingulate, left insula, and right superior parietal lobule.

Our findings support that connectivity of the anterior default mode network and PoI may serve as potential biomarkers of antidepressant outcomes for core depressive symptoms.

The coronavirus disease 2019 (COVID-19) pandemic has led to significant strain on front-line healthcare workers.

In this multicentre study, we compared the psychological outcomes during the COVID-19 pandemic in various countries in the Asia-Pacific region and identified factors associated with adverse psychological outcomes.

From 29 April to 4 June 2020, the study recruited healthcare workers from major healthcare institutions in five countries in the Asia-Pacific region. A self-administrated survey that collected information on prior medical conditions, presence of symptoms, and scores on the Depression Anxiety Stress Scales and the Impact of Events Scale-Revised were used. The prevalence of depression, anxiety, stress and post-traumatic stress disorder (PTSD) relating to COVID-19 was compared, and multivariable logistic regression identified independent factors associated with adverse psychological outcomes within each country.

A total of 1146 participants from India, Indonesia, Singapore, Malaysia and Vietnam were studied. Despite having the lowest volume of cases, Vietnam displayed the highest prevalence of PTSD. In contrast, Singapore reported the highest case volume, but had a lower prevalence of depression and anxiety. In the multivariable analysis, we found that non-medically trained personnel, the presence of physical symptoms and presence of prior medical conditions were independent predictors across the participating countries.

This study highlights that the varied prevalence of psychological adversity among healthcare workers is independent of the burden of COVID-19 cases within each country. Early psychological interventions may be beneficial for the vulnerable groups of healthcare workers with presence of physical symptoms, prior medical conditions and those who are not medically trained.

To describe characteristics of self-identified popular diet followers and compare mean BMI across these diets, stratified by time following diet.

Cross-sectional, web-based survey administered in 2015.

Non-localised, international survey.

Self-selected followers of popular diets (n 9019) were recruited to the survey via social media and email announcements by diet community leaders, categorised into eight major diet groups.

General linear models were used to compare mean BMI among (1) short-term (<1 year) and long-term (≥1 year) followers within diet groups and (2) those identifying as ‘try to eat healthy’ (TTEH) to all other diet groups, stratified by time following the specific diet. Participants were 82 % female, 93 % White and 96 % non-Hispanic. Geometric mean BMI was lower (P < 0·05 for all) among longer-term followers (≥1 year) of whole food, plant-based (WFPB), vegan, whole food and low-carb diets compared with shorter-term followers. Among those following their diet for 1–5 years (n 4067), geometric mean BMI (kg/m2) were lower (P < 0·05 for all) for all groups compared with TTEH (26·4 kg/m2): WFPB (23·2 kg/m2), vegan (23·5 kg/m2), Paleo (24·6 kg/m2), vegetarian (25·0 kg/m2), whole food (24·6 kg/m2), Weston A. Price (23·5 kg/m2) and low-carb (24·7 kg/m2).

Our findings suggest that BMI is lower among individuals who made active decisions to adhere to a specific diet, particularly more plant-based diets and/or diets limiting highly processed foods, compared with those who simply TTEH. BMI is also lower among individuals who follow intentional eating plans for longer time periods.

Emergency Medical Services (EMS) systems have developed protocols for prehospital activation of the cardiac catheterization laboratory for patients with suspected ST-elevation myocardial infarction (STEMI) to decrease first-medical-contact-to-balloon time (FMC2B). The rate of “false positive” prehospital activations is high. In order to decrease this rate and expedite care for patients with true STEMI, the American Heart Association (AHA; Dallas, Texas USA) developed the Mission Lifeline PreAct STEMI algorithm, which was implemented in Los Angeles County (LAC; California USA) in 2015. The hypothesis of this study was that implementation of the PreAct algorithm would increase the positive predictive value (PPV) of prehospital activation.

This is an observational pre-/post-study of the effect of the implementation of the PreAct algorithm for patients with suspected STEMI transported to one of five STEMI Receiving Centers (SRCs) within the LAC Regional System. The primary outcome was the PPV of cardiac catheterization laboratory activation for percutaneous coronary intervention (PCI) or coronary artery bypass graft (CABG). The secondary outcome was FMC2B.

A total of 1,877 patients were analyzed for the primary outcome in the pre-intervention period and 405 patients in the post-intervention period. There was an overall decrease in cardiac catheterization laboratory activations, from 67% in the pre-intervention period to 49% in the post-intervention period (95% CI for the difference, -14% to -22%). The overall rate of cardiac catheterization declined in post-intervention period as compared the pre-intervention period, from 34% to 30% (95% CI, for the difference -7.6% to 0.4%), but actually increased for subjects who had activation (48% versus 58%; 95% CI, 4.6%-15.0%). Implementation of the PreAct algorithm was associated with an increase in the PPV of activation for PCI or CABG from 37.9% to 48.6%. The overall odds ratio (OR) associated with the intervention was 1.4 (95% CI, 1.1-1.8). The effect of the intervention was to decrease variability between medical centers. There was no associated change in average FMC2B.

The implementation of the PreAct algorithm in the LAC EMS system was associated with an overall increase in the PPV of cardiac catheterization laboratory activation.

To validate digitally displayed photographic portion-size estimation aids (PSEA) against a weighed meal record and compare findings with an atlas of printed photographic PSEA and actual prepared-food PSEA in a low-income country.

Participants served themselves water and five prepared foods, which were weighed separately before the meal and again after the meal to measure any leftovers. Participants returned the following day and completed a meal recall. They estimated the quantities of foods consumed three times using the different PSEA in a randomized order.

Two urban and two rural communities in southern Malawi.

Women (n 300) aged 18–45 years, equally divided by urban/rural residence and years of education (≤4 years and ≥5 years).

Responses for digital and printed PSEA were highly correlated (>91 % agreement for all foods, Cohen’s κw = 0·78–0·93). Overall, at the individual level, digital and actual-food PSEA had a similar level of agreement with the weighed meal record. At the group level, the proportion of participants who estimated within 20 % of the weighed grams of food consumed ranged by type of food from 30 to 45 % for digital PSEA and 40–56 % for actual-food PSEA. Digital PSEA consistently underestimated grams and nutrients across foods, whereas actual-food PSEA provided a mix of under- and overestimates that balanced each other to produce accurate mean energy and nutrient intake estimates. Results did not differ by urban and rural location or participant education level.

Digital PSEA require further testing in low-income settings to improve accuracy of estimations.

The Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS-ND) cohort study of the Canadian Consortium on Neurodegeneration in Aging (CCNA) is a national initiative to catalyze research on dementia, set up to support the research agendas of CCNA teams. This cross-country longitudinal cohort of 2310 deeply phenotyped subjects with various forms of dementia and mild memory loss or concerns, along with cognitively intact elderly subjects, will test hypotheses generated by these teams.

The COMPASS-ND protocol, initial grant proposal for funding, fifth semi-annual CCNA Progress Report submitted to the Canadian Institutes of Health Research December 2017, and other documents supplemented by modifications made and lessons learned after implementation were used by the authors to create the description of the study provided here.

The CCNA COMPASS-ND cohort includes participants from across Canada with various cognitive conditions associated with or at risk of neurodegenerative diseases. They will undergo a wide range of experimental, clinical, imaging, and genetic investigation to specifically address the causes, diagnosis, treatment, and prevention of these conditions in the aging population. Data derived from clinical and cognitive assessments, biospecimens, brain imaging, genetics, and brain donations will be used to test hypotheses generated by CCNA research teams and other Canadian researchers. The study is the most comprehensive and ambitious Canadian study of dementia. Initial data posting occurred in 2018, with the full cohort to be accrued by 2020.

Availability of data from the COMPASS-ND study will provide a major stimulus for dementia research in Canada in the coming years.