Conectar
by Julia Reddy, Kristel Black, Keia Bazemore, Kiva Jordan, Jamie B. Jackson, Andrea K. Knittel
BackgroundResearch ethics guidelines and emphasis on representation in research guide the inclusion of marginalized groups, including people with perinatal opioid use disorders (OUD) and people experiencing incarceration in the United States. However, insights from participants regarding the risks and benefits of participation are not adequately considered. The aim of this study was to examine the risks and benefits of research participation from the perspective of pregnant/postpartum people with OUD who have experienced incarceration.
DesignWe recruited people who had experience with perinatal incarceration and were either currently pregnant or postpartum, and at least 18 years old. All participants met the clinical criteria for OUD. Our study did not have exclusion criteria based on gender, race, or ethnicity.
SettingParticipants were either currently incarcerated at the North Carolina Correctional Institute for Women in Raleigh, North Carolina, United States or had previously experienced perinatal incarceration and were recruited from a perinatal substance use disorder treatment program located in North Carolina.
ParticipantsBetween 9/2021-4/2022, we completed 12 interviews with pregnant/postpartum people with OUD, approximately half who were currently incarcerated and half with a recent history of perinatal incarceration.
Intervention/measurementInterviews were conducted via Webex phone or video. The interviews followed a scripted interview guide and lasted one hour on average. Interview transcripts were analyzed using the Rigorous and Accelerated Data Reduction technique to produce an overarching thematic framework.
FindingsOur analysis identified benefits, including the personal advantage of self-expression, helping others and contributing to change, and financial incentives. Risks included stigma and breach of confidentiality, misunderstanding of the distinction between research and advocacy, and limited ability to share their whole experience.
ConclusionsParticipant-identified benefits of research mirrored those from other marginalized populations, though participant-identified risks were novel and nuanced. Recruitment and consent should move beyond normative research ethics committees protocol language to consider the perspectives of participants.
In Australia, only 22% of male and 8% of female adolescents meet the muscle-strengthening physical activity guidelines, and few school-based interventions support participation in resistance training (RT). After promising findings from our effectiveness trial, we conducted a state-wide dissemination of the ‘Resistance Training for Teens’ (RT4T) intervention from 2015 to 2020. Despite high estimated reach, we found considerable variability in programme delivery and teachers reported numerous barriers to implementation. Supporting schools when they first adopt evidence-based programmes may strengthen programme fidelity, sustainability, and by extension, programme impact. However, the most effective implementation support model for RT4T is unclear.
To compare the effects of three implementation support models on the reach (primary outcome), dose delivered, fidelity, sustainability, impact and cost of RT4T.
We will conduct a hybrid type III implementation–effectiveness trial involving grade 9 and 10 (aged 14–16 years) students from 90 secondary schools in New South Wales (NSW), Australia. Schools will be recruited across one cohort in 2023, stratified by school type, socioeconomic status and location, and randomised in a 1:1:1 ratio to receive one of the following levels of implementation support: (1) ‘low’ (training and resources), (2) ‘moderate’ (training and resources+external support) or ‘high’ (training and resources+external support+equipment). Training includes a teacher workshop related to RT4T programme content (theory and practical sessions) and the related resources. Additional support will be provided by trained project officers from five local health districts. Equipment will consist of a pack of semiportable RT equipment (ie, weighted bars, dumbbells, resistance bands and inverted pull up bar stands) valued at ~$A1000 per school. Study outcomes will be assessed at baseline (T0), 6 months (T1) and 18 months (T2). A range of quantitative (teacher logs, observations and teacher surveys) and qualitative (semistructured interviews with teachers) methods will be used to assess primary (reach) and secondary outcomes (dose delivered, fidelity, sustainability, impact and cost of RT4T). Quantitative analyses will use logistic mixed models for dichotomous outcomes, and ordinal or linear mixed effects regression models for continuous outcomes, with alpha levels set at p
Ethics approval has been obtained from the University of Newcastle (H-2021-0418), the NSW Department of Education (SERAP:2022215), Hunter New England Human Research Ethics Committee (2023/ETH00052) and the Catholic Schools Office. The design, conduct and reporting will adhere to the Consolidated Standards of Reporting Trials statement, the Standards for Reporting Implementation Studies statement and the Template for Intervention Description and Replication checklist. Findings will be published in open access peer-reviewed journals, key stakeholders will be provided with a detailed report. We will support ongoing dissemination of RT4T in Australian schools via professional learning for teachers.
ACTRN12622000861752.
Healthcare workers were recruited early in 2020 to chart effects on their health as the COVID-19 pandemic evolved. The aim was to identify modifiable workplace risk factors for infection and mental ill health.
Participants were recruited from four Canadian provinces, physicians (medical doctors, MDs) in Alberta, British Columbia, Ontario and Quebec, registered nurses (RNs), licensed practical nurses (LPNs) and healthcare aides (HCAs) in Alberta and personal support workers (PSWs) in Ontario. Volunteers gave blood for serology testing before and after vaccination. Cases with COVID-19 were matched with up to four referents in a nested case-referent study.
Overall, 4964/5130 (97%) of those recruited joined the longitudinal cohort: 1442 MDs, 3136 RNs, 71 LPNs, 235 PSWs, 80 HCAs. Overall, 3812 (77%) were from Alberta. Prepandemic risk factors for mental ill health and respiratory illness differed markedly by occupation. Participants completed questionnaires at recruitment, fall 2020, spring 2021, spring 2022. By 2022, 4837 remained in the cohort (127 had retired, moved away or died), for a response rate of 89% (4299/4837). 4567/4964 (92%) received at least one vaccine shot: 2752/4567 (60%) gave postvaccine blood samples. Ease of accessing blood collection sites was a strong determinant of participation. Among 533 cases and 1697 referents recruited to the nested case-referent study, risk of infection at work decreased with widespread vaccination.
Serology results (concentration of IgG) together with demographic data will be entered into the publicly accessible database compiled by the Canadian Immunology Task Force. Linkage with provincial administrative health databases will permit case validation, investigation of longer-term sequelae of infection and comparison with community controls. Analysis of the existing dataset will concentrate on effects on IgG of medical condition, medications and stage of pregnancy, and the role of occupational exposures and supports on mental health during the pandemic.
by Alan Cervantes-Guzmán, Kyle McPherson, Jimena Olveres, Carlos Francisco Moreno-García, Fabián Torres Robles, Eyad Elyan, Boris Escalante-Ramírez
Cardiovascular diseases related to the right side of the heart, such as Pulmonary Hypertension, are some of the leading causes of death among the Mexican (and worldwide) population. To avoid invasive techniques such as catheterizing the heart, improving the segmenting performance of medical echocardiographic systems can be an option to early detect diseases related to the right-side of the heart. While current medical imaging systems perform well segmenting automatically the left side of the heart, they typically struggle segmenting the right-side cavities. This paper presents a robust cardiac segmentation algorithm based on the popular U-NET architecture capable of accurately segmenting the four cavities with a reduced training dataset. Moreover, we propose two additional steps to improve the quality of the results in our machine learning model, 1) a segmentation algorithm capable of accurately detecting cone shapes (as it has been trained and refined with multiple data sources) and 2) a post-processing step which refines the shape and contours of the segmentation based on heuristics provided by the clinicians. Our results demonstrate that the proposed techniques achieve segmentation accuracy comparable to state-of-the-art methods in datasets commonly used for this practice, as well as in datasets compiled by our medical team. Furthermore, we tested the validity of the post-processing correction step within the same sequence of images and demonstrated its consistency with manual segmentations performed by clinicians.
FreshRSS 