BackgroundPeople from lower and middle socioeconomic classes and vulnerable populations are among the worst affected by the COVID-19 pandemic, thus exacerbating disparities and the digital divide.ObjectiveTo draw a portrait of e-services as a digital approach to support digital health literacy in vulnerable populations amid the COVID-19 infodemic, and identify the barriers and facilitators for their implementation.MethodsA scoping review was performed to gather published literature with a broad range of study designs and grey literature without exclusions based on country of publication. A search was created in Medline (Ovid) in March 2021 and translated to Medline, PsycINFO, Scopus and CINAHL with Full Text (EBSCOhost). The combined literature search generated 819 manuscripts. To be included, manuscripts had to be written in English, and present information on digital intervention(s) (e.g. social media) used to enable or increase digital health literacy among vulnerable populations during the COVID-19 pandemic (e.g. older adults, Indigenous people living on reserve).ResultsFive articles were included in the study. Various digital health literacy-enabling e-services have been implemented in different vulnerable populations. Identified e-services aimed to increase disease knowledge, digital health literacy and social media usage, help in coping with changes in routines and practices, decrease fear and anxiety, increase digital knowledge and skills, decrease health literacy barriers and increase technology acceptance in specific groups. Many facilitators of digital health literacy-enabling e-services implementation were identified in expectant mothers and their families, older adults and people with low-income. Barriers such as low literacy limited to no knowledge about the viruses, medium of contamination, treatment options played an important role in distracting and believing in misinformation and disinformation. Poor health literacy was the only barrier found, which may hinder the understanding of individual health needs, illness processes and treatments for people with HIV/AIDS.ConclusionsThe literature on the topic is scarce, sparse and immature. We did not find any literature on digital health literacy in Indigenous people, though we targeted this vulnerable population. Although only a few papers were included, two types of health conditions were covered by the literature on digital health literacy-enabling e-services, namely chronic conditions and conditions that are new to the patients. Digital health literacy can help improve prevention and adherence to a healthy lifestyle, improve capacity building and enable users to take the best advantage of the options available, thus strengthening the patient’s involvement in health decisions and empowerment, and finally improving health outcomes. Therefore, there is an urgent need to pursue research on digital health literacy and develop digital platforms to help solve current and future COVID-19-related health needs.
Aims: Prescribing errors among junior doctors are common in clinical practice because many lack prescribing competence after graduation. This is in part due to inadequate education in clinical pharmacology and therapeutics (CP&T) in the undergraduate medical curriculum. To support CP&T education, it is important to determine which drugs medical undergraduates should be able to prescribe safely and effectively without direct supervision by the time they graduate. Currently, there is no such list with broad-based consensus. Therefore, the aim was to reach consensus on a list of essential drugs for undergraduate medical education in the Netherlands. Methods: A two-round modified Delphi study was conducted among pharmacists, medical specialists, junior doctors and pharmacotherapy teachers from all eight Dutch academic hospitals. Participants were asked to indicate whether it was essential that medical graduates could prescribe specific drugs included on a preliminary list. Drugs for which ≥80% of all respondents agreed or strongly agreed were included in the final list. Results: In all, 42 (65%) participants completed the two Delphi rounds. A total of 132 drugs (39%) from the preliminary list and two (3%) newly proposed drugs were included. Conclusions: This is the first Delphi consensus study to identify the drugs that Dutch junior doctors should be able to prescribe safely and effectively without direct supervision. This list can be used to harmonize and support the teaching and assessment of CP&T. Moreover, this study shows that a Delphi method is suitable to reach consensus on such a list, and could be used for a European list.
MULTIFILE
Background: Digital health is well-positioned in low and middle-income countries (LMICs) to revolutionize health care due, in part, to increasing mobile phone access and internet connectivity. This paper evaluates the underlying factors that can potentially facilitate or hinder the progress of digital health in Pakistan. Objective: The objective of this study is to identify the current digital health projects and studies being carried out in Pakistan, as well as the key stakeholders involved in these initiatives. We aim to follow a mixed-methods strategy and to evaluate these projects and studies through a strengths, weaknesses, opportunities, and threats (SWOT) analysis to identify the internal and external factors that can potentially facilitate or hinder the progress of digital health in Pakistan. Methods: This study aims to evaluate digital health projects carried out in the last 5 years in Pakistan with mixed methods. The qualitative and quantitative data obtained from field surveys were categorized according to the World Health Organization’s (WHO) recommended building blocks for health systems research, and the data were analyzed using a SWOT analysis strategy. Results: Of the digital health projects carried out in the last 5 years in Pakistan, 51 are studied. Of these projects, 46% (23/51) used technology for conducting research, 30% (15/51) used technology for implementation, and 12% (6/51) used technology for app development. The health domains targeted were general health (23/51, 46%), immunization (13/51, 26%), and diagnostics (5/51, 10%). Smartphones and devices were used in 55% (28/51) of the interventions, and 59% (30/51) of projects included plans for scaling up. Artificial intelligence (AI) or machine learning (ML) was used in 31% (16/51) of projects, and 74% (38/51) of interventions were being evaluated. The barriers faced by developers during the implementation phase included the populations’ inability to use the technology or mobile phones in 21% (11/51) of projects, costs in 16% (8/51) of projects, and privacy concerns in 12% (6/51) of projects.
