Clinical Research Directory

Vaccine Confidence Study Among Historically Marginalized Racial and Ethnic Groups

Achieving optimal vaccination rates is vital for protecting the health and well-being of all individuals. This specific study focuses on the MMR and RSV vaccines in pregnancy and early childhood, which have been shown to reduce RSV and MMR-related illnesses, hospitalizations, and deaths. Efforts to improve vaccination rates have not been equally effective across the entire population; this has resulted in poorer outcomes from interventions for certain populations who are vaccine-hesitant. This study seeks to understand how to best increase vaccine confidence in marginalized populations. To do this, the investigators will interview parents of children who receive care at Boston Medical Center (BMC), Community Health Workers and other Clinical providers at BMC, leading experts in the fields of vaccine confidence and implementation science, and key public health stakeholders/officials.

Predicting Vaccine Hesitancy Using Machine Learning

In recent years, emerging technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), and Virtual Reality (VR) have rapidly become integrated into daily life. The widespread use of these applications has led to the accumulation of vast amounts of data, giving rise to what is commonly referred to as "Big Data." Due to the sheer volume, manual processing and analysis of these large datasets are not feasible. Therefore, software tools and libraries-such as Python and R libraries-have been developed to perform these analyses efficiently and to generate predictions for the future by leveraging historical data through Machine Learning (ML) algorithms. The primary goal of machine learning algorithms is to discover patterns within existing data and use these patterns to make accurate predictions on new data. The use of machine learning in the field of healthcare has gained significant momentum in recent years. However, a review of the literature reveals that research specifically addressing childhood vaccine hesitancy remains limited. This study aims to identify the factors contributing to vaccine hesitancy among parents of children aged 0-48 months and to develop a predictive model using machine learning techniques based on these factors. Such a model could help anticipate the likelihood of vaccine refusal among parents and thereby support the development of targeted public health strategies for at-risk populations.

Active Health Education to Increase HPV Vaccine Coverage in Youth: A Stepped-wedge, Cluster, and Randomized Trial

This study aims to evaluate the impact of active health education methodologies on increasing adherence to the HPV vaccine among schoolchildren. The project will involve 196 schools across Brazil, encompassing a total of 5,000 students. A stepped-wedge implementation design will be applied, with clusters being randomized every two months to one of four interventions. Each intervention will be implemented in 48 schools.

Improving Vaccine Acceptance Through EHR Integrated Patient- and Provider-Facing Decision Support

The goal of this project is to establish the technical feasibility of a scalable, integrated platform to improve patient informed decision-making and increase vaccine uptake and to evaluate the effectiveness of the integrated platform to improve vaccine uptake.

Vaccinations and People With Disabilities

The goal of this observational study is to learn about vaccinations hesitancy, delay or avoidance in children with chronic diseases, congenital anomalies or disabilities. The main questions it aims to answer are: • Attitudes of caregivers towards vaccinating their children, obstacles that postpone vaccinations, and the status of vaccinations of these children. Participants will fill out questionnaires and some will be included in focused groups for the qualitative part of the study. Researchers will compare the vaccinations status of the research group to their siblings' status as well as the published national records of vaccination compliance.

Evaluating the Impact of Resource Navigators to Support LTC and RH Staff During and Beyond COVID-19

The goal of this clinical trial is to test how well resource navigators help long-term care and retirement home staff access the various health and wellness resources available to them and the effects that this has on their health and wellness overall. The main questions it aims to answer are: \- How does one-on-one support from a resource navigator affect the wellness of long-term care and retirement home staff, including burnout, vaccination status, and COVID-19 infection? Researchers will compare participants in the intervention group (where participants are paired with a resource navigator) and the control group (where participants are not paired with a resource navigator) to see the impact access to a resource navigator has on wellness (primary outcome), burnout, knowledge of, access to and use of wellness resources, knowledge/alignment with provincial public health guidelines related to SARS-CoV-2 vaccine outcomes, SARS-CoV-2 infection, hospitalization, and death (secondary outcomes). Hypothesis: Researchers anticipate that those in the intervention group (have access to a resource navigator) will report a higher positive change in wellness between baseline and 6 months.

A Survey of Acceptance and Factors Associated With Hesitancy Vaccination in Northeast Brazil

The objective of this study is to investigate vaccination acceptance and identify the reasons why people are not vaccinated. People over 18 years of age who live in neighborhoods with socioeconomic vulnerability and with many cases of infectious diseases, as well as health professionals, will respond to a research questionnaire.

Supporting CHWs as Vaccine Educators: Impact of a Digital Training and Chatbot Intervention on Vaccination in Kenya

This study seeks to understand how to support community health workers (CHWs) to improve routine vaccination rates in high-need areas by testing a two-part intervention. The first part of the intervention is a digital training provided to CHWs, which includes videos and job aids on vaccine education to support patient communication. The second part of the intervention is a patient-facing chatbot that CHWs can share with their patients. The chatbot is designed to answer patient questions about routine immunization. The intervention will be implemented in two sub-counties in Migori County Kenya (Awendo and Nyatike) that Lwala Community Health Alliance has identified as high need with respect to vaccine education. We hypothesize that the intervention will increase knowledge about routine immunization among CHWs and patients, increase vaccine acceptance, intent-to-vaccinate, and vaccination rates among patients in the treatment group.