JMIR Public Health and Surveillance

Although previous studies have investigated trends in unmet health care and dental care needs, most have focused on specific groups, such as patients with chronic conditions and older adults, and have been limited by smaller data sets.

The National Health Service (NHS) Long Term Plan, published in 2019, committed to ensuring that every patient in England has the right to digital-first primary care by 2023-2024. The COVID-19 pandemic and infection prevention and control measures accelerated work by the NHS to enable and stimulate the use of online consultation (OC) systems across all practices for improved access to primary care.

While smoking cessation has been linked to substantial weight gain, the potential influence of e-cigarettes on weight changes among individuals who use these devices to quit smoking is not fully understood.

Digital technologies have become more important in the health care sector in the past decades. This transition from conventional to digital health care has been accelerated by the impact of the COVID-19 pandemic, which poses the risk of creating a “digital divide,” inadvertently placing those who are older, economically disadvantaged, and have a lower level of education at a disadvantage.

Personality has an impact on the health-related quality of life (HRQoL) of older adults. However, the relationship and mechanisms of the two variables are controversial, and few studies have been conducted in older adults.

Traditional public health surveillance efforts are generally based on self-reported data. Although well validated, these methods may nevertheless be subjected to limitations such as biases, delays, and costs or logistical challenges. An alternative is the use of smart technologies (eg, smartphones and smartwatches) to complement self-report indicators. Having embedded sensors that provide zero-effort, passive, and continuous monitoring of health variables, these devices generate data that could be leveraged for cases in which the data are related to the same self-report metric of interest. However, some challenges must be considered when discussing the use of mobile health technologies for public health to ensure digital health equity, privacy, and best practices. This paper provides, through a review of major Canadian surveys and mobile health studies, an overview of research involving mobile data for public health, including a mapping of variables currently collected by public health surveys that could be complemented with self-report, challenges to technology adoption, and considerations on digital health equity, with a specific focus on the Canadian context. Population characteristics from major smart technology brands—Apple, Fitbit, and Samsung—and demographic barriers to the use of technology are provided. We conclude with public health implications and present our view that public health agencies and researchers should leverage mobile health data while being mindful of the current barriers and limitations to device use and access. In this manner, data ecosystems that leverage personal smart devices for public health can be put in place as appropriate, as we move toward a future in which barriers to technology adoption are decreasing.

The Coronavirus Disease 2019 (COVID-19) pandemic resulted in a massive disruption in access to care and thus passive, hospital and clinic-based surveillance programs. In 2020, the reported cases of Lyme disease were the lowest both across the United States and North Carolina in recent years. During this period, human contact patterns began to shift with higher rates of greenspace usage and outdoor activities, putting more people into contact with potential vectors and associated vector borne diseases. Lyme disease reporting relies on passive surveillance systems which was likely disrupted by changes in health care seeking behavior during the pandemic.

Understanding the factors contributing to mental well-being in youth is a public health priority. Self-reported enthusiasm for the future may be a useful indicator of well-being and has been shown to forecast social and educational success. Typically, cross-domain measures of ecological and health-related factors with relevance to public policy and programming are analyzed either in isolation or in targeted models assessing bivariate interactions. Here, we capitalize on a large provincial data set and machine learning to identify the sociodemographic, experiential, behavioral, and other health-related factors most strongly associated with levels of subjective enthusiasm for the future in a large sample of elementary and secondary school students.

Little is known about post–hospital health care resource use (HRU) of patients admitted for severe COVID-19, specifically for the care of patients with postacute COVID-19 syndrome (PACS).

With the development of science and technology and health literacy improvement, more studies have focused on frailty prevention by promoting medication adherence, emphasising the role of eHealth literacy. However, the association between eHealth literacy and medication adherence in frail older adults has not been well studied, and it is unknown whether there are urban-rural variances in their relationship.

Young men who have sex with men and young transgender women (YMSM-YTW) utilize online spaces to meet sexual partners with increasing regularity, and research shows that experiences of racism in these virtual spaces mimic the real world. Quantitative evidence to demonstrate that racial/ethnic minority YMSM-YTW utilize and meet sexual partners online and through mobile apps differently than White non-Hispanic YMSM-YTW is limited.

Drug users (DUs) are considered one of the high-risk groups for HIV infection and play a crucial role in the transmission of HIV. Under the emerging of new drugs, we aim to explore the drug using behaviors currently, HIV infections and the correlation between drug using behaviors and HIV infection risk among drug users from 2014-2021.