Introduction Deep learning techniques are gaining momentum in medical research. Evidence shows that deep learning has advantages over humans in image identification and classification, such as facial image analysis in detecting people’s medical conditions. While positive findings are available, little is known about the state-of-the-art of deep learning-based facial image analysis in the medical context. For the consideration of patients’ welfare and the development of the practice, a timely understanding of the challenges and opportunities faced by research on deep-learning-based facial image analysis is needed. To address this gap, we aim to conduct a systematic review to identify the characteristics and effects of deep learning-based facial image analysis in medical research. Insights gained from this systematic review will provide a much-needed understanding of the characteristics, challenges, as well as opportunities in deep learning-based facial image analysis applied in the contexts of disease detection, diagnosis and prognosis. Methods Databases including PubMed, PsycINFO, CINAHL, IEEEXplore and Scopus will be searched for relevant studies published in English in September, 2021. Titles, abstracts and full-text articles will be screened to identify eligible articles. A manual search of the reference lists of the included articles will also be conducted. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework was adopted to guide the systematic review process. Two reviewers will independently examine the citations and select studies for inclusion. Discrepancies will be resolved by group discussions till a consensus is reached. Data will be extracted based on the research objective and selection criteria adopted in this study. Ethics and dissemination As the study is a protocol for a systematic review, ethical approval is not required. The study findings will be disseminated via peer-reviewed publications and conference presentations. PROSPERO registration number CRD42020196473.

Although COVID-19 vaccines are becoming increasingly available, their ability to effectively control and contain the spread of the COVID-19 pandemic is highly contingent on an array of factors. This paper discusses how limitations to vaccine accessibility, issues associated with vaccine side effects, concerns regarding vaccine efficacy, along with the persistent prevalence of vaccine hesitancy among the public, including health care professionals, might impact the potential of COVID-19 vaccines to curb the pandemic. We draw insights from the literature to identify practical solutions that could boost people’s adoption of COVID-19 vaccines and their accessibility. We conclude with a discussion on health experts’ and government officials’ moral and ethical responsibilities to the public, even in light of the urgency to adopt and endorse “the greatest amount of good for the greatest number” utilitarian philosophy in controlling and managing the spread of COVID-19.

Introduction A growing number of technology-based interventions are used to support the health and quality of life of nursing home residents. The onset of COVID-19 and recommended social distancing policies that followed led to an increased interest in technology-based solutions to provide healthcare and promote health. Yet, there are no comprehensive resources on technology-based healthcare solutions that describe their efficacy for nursing home residents. This systematic review will identify technology-based interventions designed for nursing home residents and describe the characteristics and effects of these interventions concerning the distinctive traits of nursing home residents and nursing facilities. Additionally, this paper will present practical insights into the varying intervention approaches that can assist in the delivery of broad digital health solutions for nursing home residents amid and beyond the impact of COVID-19. Methods and analysis Databases including the PubMed, PsycINFO, CINAHL and Scopus will be used to identify articles related to technology-based interventions for nursing home residents published between 1 January 2010 to 30 September 2021. Titles, abstracts and full-text papers will be reviewed against the eligibility criteria. The Cochrane Collaboration evaluation framework will be adopted to examine the risk of bias of the included study. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses procedures will be followed for the reporting process and implications for existing interventions and research evaluated by a multidisciplinary research team. Ethics and dissemination As the study is a protocol for a systematic review, ethical approval is not required. The study findings will be disseminated via peer-reviewed publications and conference presentations. Trial registration number CRD 42020191880.

Background/Objectives: Against the background of the rapid aging of the population, the symptoms of depression are a major health problem for middle-aged and older adults. This study analyzes the relationship between social participation and the trajectory of depressive symptoms and whether this association varies by gender. Methods: The data comes from five rounds of surveys conducted by the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2020, including a total of 5796 participants aged 45 or above. The depressive symptoms of each wave are measured using the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10). Social participation was defined as the number of reported activities (0, 1, or ≥2). The development trajectory of depressive symptoms was analyzed through Group-Based Trajectory Modeling (GBTM), and their links with social participation level were subsequently quantified using multinomial logistic regression. Gender differences were assessed via interaction tests and stratified models. Results: GBTM identified four distinct depressive symptom trajectories: low (29.71%), moderate (42.72%), increasing (22.07%), and high (5.50%). Compared with no participation, engaging in one activity was linked to lower odds of falling into the moderate, increasing, and high trajectories; the association was stronger for ≥2 activities. Gender-stratified analyses revealed substantial heterogeneity (all interaction p < 0.01). Among women, single-activity participation was associated with lower odds across all three adverse trajectories. Among men, similar associations required ≥2 activities, with single-activity participation linked only to lower odds of the high trajectory. Conclusions: Higher levels of social participation have significantly reduced the depressive symptoms of middle-aged and older adults, and the gender differences are pronounced. Interventions should improve access to social participation for older women and promote activity diversity for older men.

UNSTRUCTURED Although COVID-19 vaccines are becoming increasingly available, their ability to effectively control and contain the spread of the COVID-19 pandemic is highly contingent on an array of factors. This paper discusses how limitations to vaccine accessibility, issues associated with vaccine side effects, concerns regarding vaccine efficacy, along with the persistent prevalence of vaccine hesitancy among the public, including health care professionals, might impact the potential of COVID-19 vaccines to curb the pandemic. We draw insights from the literature to identify practical solutions that could boost people’s adoption of COVID-19 vaccines and their accessibility. We conclude with a discussion on health experts’ and government officials’ moral and ethical responsibilities to the public, even in light of the urgency to adopt and endorse “the greatest amount of good for the greatest number” utilitarian philosophy in controlling and managing the spread of COVID-19.