RESUMEN
BACKGROUND: The impact of COVID-19 and its mitigation measures have exacerbated the global mental health crisis. Digital mental health interventions (DMHIs) may have the potential to address health system gaps and global health inequalities in low- and middle-income countries (LMICs). AIMS: This thesis aims to map the current state of DMHIs in Nigeria and illustrate their progress, limitations, and challenges. METHODS: Twenty interviews were conducted with researchers, healthcare providers, and digital health experts. Interviews were recorded and transcribed. Then data were coded and analyzed using thematic analysis. RESULTS: The majority of DMHIs in Nigeria are private mental health service delivery platforms that connect directly to mental health professionals. The target audience encompasses all mental health conditions and ages. Advantages of DMHIs include increasing efficiency, accessibility, addressing stigma, and filling the mental health service gap. Disadvantages include skepticism, limitations of applicability, lack of accessibility to internet and technology, lack of sustainability and infrastructure, and lack of funding and policies. CONCLUSION: The lessons learned in the Nigerian context can inform the delivery of DMHIs in other low-resource settings. Future research should examine user and provider feedback of DMHIs to allow for comparative analysis, more conclusive and replicable results to inform DMHI design and implementation.
RESUMEN
PROBLEM: Limited research has examined and synthesized the adaptation of midwives and midwife-led interventions during crises. BACKGROUND: Evidence suggests that midwives are essential to respond to sexual and reproductive health care needs during disruptive times, and that they adapt to continue to provide their services during those circumstances. AIM: To map the adaptations of midwives when providing care during crises globally. Secondary objectives include identifying which midwives adapted, what services were adapted and how, and the demographic receiving care. STUDY METHODS: Scoping review using Levac's modifications of Arksey and O'Malley's methods. Publications and grey literature, in English and Spanish, with no limitations based on study design or date were included. Data was extracted and mapped using Wheaton and Maciver's Adaptation framework. FINDINGS: We identified 3329 records, of which forty-two were included. Midwives' prior training impacted adaptation. Midwives adapted to the COVID-19 pandemic, epidemics, natural disasters, and World War II. They adapted in hospital and community settings around the provision of antenatal, labor and birth, postpartum, and contraceptive care. However, no specific data identified population demographics. Midwifery adaptations related to their practice, role, and scope of practice. CONCLUSION: The limited available evidence identified the challenges, creativity, and mutual aid activities midwives have undertaken to ensure the provision of their services. Evidence is highly concentrated around maternal health services. Further high-quality research is needed to provide a deeper understanding of how midwifery-led care can adapt to guide sustainable responses to ensure access to sexual and reproductive health services during crises.
RESUMEN
The rapid adoption of online technologies to deliver postsecondary education amid the COVID-19 pandemic has highlighted the potential for online learning, as well as important equity gaps to be addressed. For over ten years, McMaster University has delivered graduate global health education through a blended-learning approach. In partnership with universities in the Netherlands, India, Thailand, Norway, Colombia, and Sudan, experts from across the Consortium deliver lectures online to students around the world. In 2020, two courses were piloted with small groups of students from Canada and Colombia using machine translation supported by bilingual tutors. Students met weekly via video conferencing software, speaking in English and Spanish and relying on machine translation software to transcribe and translate for group members. Qualitative semi-structured interviews were conducted with students, tutors, and instructors to explore how artificial intelligence can be harnessed to integrate multilingual group work into course offerings, challenging the dominant use of English as the principal language of instruction in global health education. Findings highlight the potential for machine translation to bridge language divides, while also underscoring several key limitations of currently available technology. Further research is needed to investigate the potential for machine translation in facilitating multilingual online education as a pathway to more equitable and inclusive online learning environments.