In over 50 years since the genetic counseling (GC) profession began, a systematic study of GC communication skills and patient-reported outcomes in actual sessions across multiple clinical specialties has never been conducted. To optimize GC quality and improve efficiency of care, the field must first be able to comprehensively measure GC skills and determine which skills are most critical to achieving positive patient experiences and outcomes. This study aims to characterise GC communication skills using a novel and pragmatic measure and link variations in communication skills to patient-reported outcomes, across clinical specialties and with patients from diverse backgrounds in the USA. Our community-engagement and provider-engagement approach is crucial to develop recommendations for quality, culturally informed GC care, which are greatly needed to improve GC practice.

A mixed methods, sequential explanatory design will be used to collect and analyze: audio-recorded GC sessions in cancer, cardiac, and prenatal/reproductive genetic indications; pre-visit and post-visit quantitative surveys capturing patient experiences and outcomes and post-visit qualitative interview data. A novel, practical checklist will measure GC communication skills. Coincidence analysis will identify patterns of GC skills that are consistent with high scores on patient-reported measures. Two-level, multilevel models will be used to evaluate how GC communication skills and other session/patient characteristics predict patient-reported outcomes. Four community advisory boards (CABs) and a genetic counselor advisory board will inform the study design and analysis.

This study has been approved by the single Institutional Review Board of the University of Minnesota. This research poses no greater than minimal risk to participants. Results from this study will be shared through national and international conferences and through community-based dissemination as guided by the study’s CABs. A lay summary will also be disseminated to all participants.

Cardiovascular disease is a leading cause of global death. Prospective population-based studies have found that changes in retinal microvasculature are associated with the development of coronary artery disease. Recently, artificial intelligence deep learning (DL) algorithms have been developed for the fully automated assessment of retinal vessel calibres.

In this study, we validate the association between retinal vessel calibres measured by a DL system (Singapore I Vessel Assessment) and incident myocardial infarction (MI) and assess its incremental performance in discriminating patients with and without MI when added to risk prediction models, using a large UK Biobank cohort.

Retinal arteriolar narrowing was significantly associated with incident MI in both the age, gender and fellow calibre-adjusted (HR=1.67 (95% CI: 1.19 to 2.36)) and multivariable models (HR=1.64 (95% CI: 1.16 to 2.32)) adjusted for age, gender and other cardiovascular risk factors such as blood pressure, diabetes mellitus (DM) and cholesterol status. The area under the receiver operating characteristic curve increased from 0.738 to 0.745 (p=0.018) in the age–gender-adjusted model and from 0.782 to 0.787 (p=0.010) in the multivariable model. The continuous net reclassification improvements (NRIs) were significant in the age and gender-adjusted (NRI=21.56 (95% CI: 3.33 to 33.42)) and the multivariable models (NRI=18.35 (95% CI: 6.27 to 32.61)). In the subgroup analysis, similar associations between retinal arteriolar narrowing and incident MI were observed, particularly for men (HR=1.62 (95% CI: 1.07 to 2.46)), non-smokers (HR=1.65 (95% CI: 1.13 to 2.42)), patients without DM (HR=1.73 (95% CI: 1.19 to 2.51)) and hypertensive patients (HR=1.95 (95% CI: 1.30 to 2.93)) in the multivariable models.

Our results support DL-based retinal vessel measurements as markers of incident MI in a predominantly Caucasian population.

To determine the association between occupational factors, particularly psychosocial factors, and hypertension.

Descriptive and analytical cross-sectional study using logistic multivariate regression.

Fifteen cotton ginning plants in Benin.

Permanent and occasional workers in the cotton ginning industry.

Data on sociodemographic, occupational, behavioural and clinical history characteristics were collected using a number of standardised, interviewer-administered questionnaires. These questionnaires were based on the WHO’s non-communicable disease questionnaire, Karasek questionnaire and Siegrist questionnaire. Weight, height and blood pressure were measured. Any worker with systolic blood pressure ≥140 mm Hg and/or diastolic blood pressure ≥90 mm Hg according to the WHO criteria was considered hypertensive, as was any subject on antihypertensive treatment even if blood pressure was normal.

A total of 1883 workers were included, with a male to female ratio of 9.08. Of these, 510 suffered from hypertension (27.1%, 95% CI 25.1 to 29.2). In the multivariate analysis, the risk factors identified were occupational stress (adjusted OR (aOR)=3.96, 95% CI 1.28 to 12.2), age ≥25 years (aOR=2.77, 95% CI 1.55 to 4.96), body mass index of 25–30 kg/m² (aOR=1.71, 95% CI 1.32 to 2.2), body mass index >30 kg/m² (aOR=2.74, 95% CI 1.84 to 4.09), permanent worker status (aOR=1.66, 95% CI 1.44 to 2.41) and seniority in the textile sector >5 years (aOR=2.18, 95% CI 1.7 to 2.8). Recognition at work emerged as an effect-modifying factor subject to stratification.

Occupational factors, particularly job strain and recognition at work, are modifiable factors associated with hypertension in the ginning plants sector and deserve to be corrected through occupational health promotion and prevention.

SCALE-UP II aims to investigate the effectiveness of population health management interventions using text messaging (TM), chatbots and patient navigation (PN) in increasing the uptake of at-home COVID-19 testing among patients in historically marginalised communities, specifically, those receiving care at community health centres (CHCs).

The trial is a multisite, randomised pragmatic clinical trial. Eligible patients are >18 years old with a primary care visit in the last 3 years at one of the participating CHCs. Demographic data will be obtained from CHC electronic health records. Patients will be randomised to one of two factorial designs based on smartphone ownership. Patients who self-report replying to a text message that they have a smartphone will be randomised in a 2x2x2 factorial fashion to receive (1) chatbot or TM; (2) PN (yes or no); and (3) repeated offers to interact with the interventions every 10 or 30 days. Participants who do not self-report as having a smartphone will be randomised in a 2x2 factorial fashion to receive (1) TM with or without PN; and (2) repeated offers every 10 or 30 days. The interventions will be sent in English or Spanish, with an option to request at-home COVID-19 test kits. The primary outcome is the proportion of participants using at-home COVID-19 tests during a 90-day follow-up. The study will evaluate the main effects and interactions among interventions, implementation outcomes and predictors and moderators of study outcomes. Statistical analyses will include logistic regression, stratified subgroup analyses and adjustment for stratification factors.

The protocol was approved by the University of Utah Institutional Review Board. On completion, study data will be made available in compliance with National Institutes of Health data sharing policies. Results will be disseminated through study partners and peer-reviewed publications.

ClinicalTrials.gov: NCT05533918 and NCT05533359.

Coal-fired power plants are major sources of air pollution which impact human health. Coal combustion byproducts released into the air include particulate matter, nitrogen oxides and sulphur dioxide. Exposure to fine particulate matter is associated with increased risk of mortality. This scoping review will examine and summarise the current literature on the health risks of exposure to air pollution in areas in which coal-fired power plants exist.

This scoping review will be conducted according to the Joanna Briggs Institute methodological framework and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines. Five electronic databases (PubMed, ScienceDirect, Scopus, Web of Science and Google Scholar) will be searched for relevant articles. Studies will be included up until 31 January 2024. There will be no restriction on geographical area. The searches will be limited to studies published in English. Title, abstract, full-text screening and data extraction of relevant articles will be done by two independent reviewers. Discrepancies will be resolved by group discussion. The findings will be presented in tables with a narrative summary. This review will consider epidemiological studies and grey literature that report on the health risks of exposure to air pollution in areas where coal-fired power plants exist.

All data will be collected from published and grey literature. Ethics approval is therefore not required. We will submit our findings for publication in a peer-reviewed journal.

To compare the associations of COVID-19 preventive behaviours and depressive and anxiety symptoms with eHealth literacy and COVID-19 knowledge among Korean adults.

A cross-sectional online survey was conducted in April 2020.

Seoul metropolitan area in South Korea.

1057 Korean adults were recruited.

Associations between eHealth literacy, COVID-19 knowledge, COVID-19 preventive behaviours and psychological distress were computed using Pearson’s correlation and logistic regression analyses. eHealth literacy, COVID-19 knowledge, COVID-19 preventive behaviours and psychological distress were weighted by sex and age distribution of the general population in Seoul Metropolitan area.

68.40% (n=723) perceived high eHealth literacy level (eHEALS ≥26), while 57.43% (n=605) had high levels of COVID-19 knowledge (score ≥25). No significant association between eHealth literacy and COVID-19 knowledge was identified (r=0.05, p=0.09). eHealth literacy and COVID-19 knowledge were significantly associated with COVID-19 preventive behaviours (aOR=1.99, 95% CI 1.51 to 2.62 L; aOR=1.81, 95% CI 1.40 to 2.34, respectively). High eHealth literacy was significantly associated with anxiety symptom (aOR=1.71, 95% CI 1.18 to 2.47) and depressive symptom (aOR=1.69, 95% CI 1.24 to 2.30). COVID-19 knowledge had negative and no associations with the symptoms (aOR=0.62, 95% CI 0.46 to 0.86; aOR=0.79, 95% CI 0.60 to 1.03, respectively). High eHealth literacy with low COVID-19 knowledge was positively and significantly associated with COVID-19 preventive behaviours (aOR=2.30, 95% CI 1.52 to 3.43), and anxiety (aOR=1.81, 95% CI 1.09 to 3.01) and depressive symptoms (aOR=2.24, 95% CI 1.41 to 3.55). High eHealth literacy with high COVID-19 knowledge were significantly associated with more preventive behaviours (aOR=3.66, 95% CI 2.47 to 5.42) but no significant associations with anxiety and depressive symptoms.

We identified that eHealth literacy and COVID-19 knowledge were not associated each other, and differently associated with individuals’ COVID-19 preventive behaviours and psychological well-being. Public health strategies should pay attention to enhancing both eHealth literacy and COVID-19 knowledge levels in the public to maximise their COVID-19 preventive behaviours and mitigate their psychological distress during COVID-19 pandemic.

Over 40% of US adults meet criteria for obesity, a major risk factor for chronic disease. Obesity disproportionately impacts populations that have been historically marginalised (eg, low socioeconomic status, rural, some racial/ethnic minority groups). Evidence-based interventions (EBIs) for weight management exist but reach less than 3% of eligible individuals. The aims of this pilot randomised controlled trial are to evaluate feasibility and acceptability of dissemination strategies designed to increase reach of EBIs for weight management.

This study is a two-phase, Sequential Multiple Assignment Randomized Trial, conducted with 200 Medicaid patients. In phase 1, patients will be individually randomised to single text message (TM1) or multiple text messages (TM+). Phase 2 is based on treatment response. Patients who enrol in the EBI within 12 weeks of exposure to phase 1 (ie, responders) receive no further interventions. Patients in TM1 who do not enrol in the EBI within 12 weeks of exposure (ie, TM1 non-responders) will be randomised to either TM1-Continued (ie, no further TM) or TM1 & MAPS (ie, no further TM, up to 2 Motivation And Problem Solving (MAPS) navigation calls) over the next 12 weeks. Patients in TM+ who do not enrol in the EBI (ie, TM+ non-responders) will be randomised to either TM+Continued (ie, monthly text messages) or TM+ & MAPS (ie, monthly text messages, plus up to 2 MAPS calls) over the next 12 weeks. Descriptive statistics will be used to characterise feasibility (eg, proportion of patients eligible, contacted and enrolled in the trial) and acceptability (eg, participant opt-out, participant engagement with dissemination strategies, EBI reach (ie, the proportion of participants who enrol in EBI), adherence, effectiveness).

Study protocol was approved by the University of Utah Institutional Review Board (#00139694). Results will be disseminated through study partners and peer-reviewed publications.

clinicaltrials.gov; NCT05666323.