Do social media campaigns foster vaccination adherence? A systematic review of prior intervention-based campaigns on social media

Integrating Digital Health Innovations to Achieve Universal Health Coverage: Promoting Health Outcomes and Quality Through Global Public Health Equity

Digital health innovations are reshaping global healthcare systems by enhancing access, efficiency, and quality of care. Technologies such as artificial intelligence, telemedicine, mobile health applications, and big data analytics have been widely applied to support disease surveillance, enable remote care, and improve clinical decision making. This review critically identifies persistent implementation challenges that hinder the equitable adoption of digital health solutions, such as the digital divide, limited infrastructure, and weak data governance, particularly in low- and middle-income countries (LMICs). It aims to propose strategic pathways for integrating digital innovations to strengthen universal health coverage (UHC) and bridge health disparities in the region. By analyzing the best global practices and emerging innovations, this study contributes to the ongoing dialogue on leveraging digital health for inclusive, scalable, and sustainable healthcare delivery in underserved regions.

Relationship between influenza-related experience and current vaccination outcome

BACKGROUND

This study investigated how a person's influenza-related experience, together with demographic, socioeconomic, and health-related factors, was associated with their current vaccination decisions.

METHODS

The analysis used ten panels of the Medical Expenditure Panel Survey (MEPS) from 2006 to 2016. Linear and logistic probability models were estimated to predict influenza vaccination using a person's vaccination status in the previous year and history of influenza infection, adjusting for demographics, socioeconomic variables, general health status, and healthcare access. The models used two-way and three-way interactions with race/ethnicity, income, education, health status, and elderly status to examine changing relationships of flu-related experience across these variables.

RESULTS

Previous vaccination was the most important predictor, with an increase of 63.0-71.8% probability of vaccination in the next year. Infection history could either increase or decrease the impact of past vaccination depending on race/ethnicity, income, education level, health status, and age. There were significant disparities across demographic, socioeconomic, and health-related variables.

CONCLUSION

Vaccination promotion efforts could focus on those who have not been vaccinated in the past and on specific sub-populations, such as people who are Hispanic, people with lower education levels, the population aged 65 and above, and families with low-income levels. Although past infection is a predictor for some population groups, its magnitude is small and is often not a significant determinant.

A game theoretic complex network model to estimate the epidemic threshold under individual vaccination behaviour and adaptive social connections

In today's interconnected world, the spread of information is closely linked to infectious disease dynamics. Public awareness plays a crucial role, as individual vaccination decisions significantly impact collective efforts to combat emerging health threats. This study explores disease transmission within a framework integrating social connections, information sharing, and individual vaccination decisions. We introduce a behaviour-prevalence model on an adaptive multiplex network, where the physical layer (Layer-II) captures disease transmission under vaccination. In contrast, the virtual layer (Layer-I) represents adaptive social contacts and the flow of information, shaping vaccination decisions within a socially influenced environment. We derive analytical expressions for the epidemic threshold using the microscopic Markov Chain Method (MMCM). Simulation results highlight that adaptive social contacts lead to a higher epidemic threshold than non-adaptive networks. Additionally, network characteristics, such as the power-law exponent in scale-free networks, significantly impact infection spread within populations. Our results reveal that changes in perceived infection risk and an individual's sensitivity to non-vaccinated neighbour's status strongly influence vaccine uptake across populations. These insights can guide public health officials in developing targeted vaccination programs that address the evolving dynamics of social connections, information dissemination, and vaccination choice in the digital era.

Examining the Effectiveness of a Digital Media Campaign at Reducing the Duration of Untreated Psychosis in New York State: Results From a Stepped-wedge Randomized Controlled Trial

BACKGROUND AND HYPOTHESIS

Longer duration of untreated psychosis (DUP) predicts worse outcomes in First Episode Psychosis (FEP). Searching online represents one of the first proactive step toward treatment initiation for many, yet few studies have informed how best to support FEP youth as they engage in early online help-seeking steps to care.

STUDY DESIGN

Using a stepped-wedge randomized design, this project evaluated the effectiveness of a digital marketing campaign at reducing DUP and raising rates of referrals to FEP services by proactively targeting and engaging prospective patients and their adult allies online.

STUDY RESULTS

Throughout the 18-month campaign, 41 372 individuals visited our website, and 371 advanced to remote clinical assessment (median age = 24.4), including 53 allies and 318 youth. Among those assessed (n = 371), 53 individuals (14.3%) reported symptoms consistent with psychotic spectrum disorders (62.2% female, mean age 20.7 years) including 39 (10.5%) reporting symptoms consistent with either Clinical High Risk (ie, attenuated psychotic symptoms; n = 26) or FEP (n = 13). Among those with either suspected CHR or FEP (n = 39), 20 (51.3%) successfully connected with care. The campaign did not result in significant differences in DUP.

CONCLUSION

This study highlights the potential to leverage digital media to help identify and engage youth with early psychosis online. However, despite its potential, online education and professional support alone are not yet sufficient to expedite treatment initiation and reduce DUP.

Exploring the Evolution of Social Media in Mental Health Interventions: A Mapping Review

BACKGROUND

With the rise of social media, social media use for delivering mental health interventions has become increasingly popular. However, there is no comprehensive overview available on how this field developed over time.

OBJECTIVES

The objective of this paper is to provide an overview over time of the use of social media for delivering mental health interventions. Specifically, we examine which mental health conditions and target groups have been targeted, and which social media channels or tools have been used since this topic first appeared in research.

METHODS

To provide an overview of the use of social media for mental health interventions, we conducted a search for studies in four databases (PubMed; ACM Digital Library; PsycInfo; and CINAHL) and two trial registries (Clinicaltrials.gov; and Cochranelibrary.com). A sample of representative keywords related to mental health and social media was used for that search. Automatic text analysis methods (e.g., BERTopic analysis, word clouds) were applied to identify topics, and to extract target groups and types of social media.

RESULTS

A total of 458 studies were included in this review (n=228 articles, and n=230 registries). Anxiety and depression were the most frequently mentioned conditions in titles of both articles and registries. BERTopic analysis identified depression and anxiety as the main topics, as well as several addictions (including gambling, alcohol, and smoking). Mental health and women's research were highlighted as the main targeted topics of these studies. The most frequently targeted groups were "adults" (39.5%) and "parents" (33.4%). Facebook, WhatsApp, messenger platforms in general, Instagram, and forums were the most frequently mentioned tools in these interventions.

CONCLUSIONS

We learned that research interest in social media-based interventions in mental health is increasing, particularly in the last two years. A variety of tools have been studied, and trends towards forums and Facebook show that tools allowing for more content are preferred for mental health interventions. Future research should assess which social media tools are best suited in terms of clinical outcomes. Additionally, we conclude that natural language processing tools can help in studying trends in research on a particular topic.

Factors Associated with College Students' Human Papillomavirus (HPV) Vaccination and Preferred Strategies for Catch-Up Vaccine Promotion: A Mixed-Methods Study

Human papillomavirus (HPV) vaccination protects against six types of cancer-cervical, anal, oropharyngeal, penile, vulvar, and vaginal. In the United States (U.S.), HPV vaccination coverage in college students remains low, especially in the Mid-South region, despite the highest risk of HPV infections and disease burden. However, few studies have assessed HPV vaccination among college students here. This study examined factors associated with HPV vaccination among college students in the Mid-South and explored preferred strategies for promoting vaccination. A mixed-methods design comprising a cross-sectional, self-report online survey and dyadic virtual interviews was conducted. Simple random sampling was performed to recruit a total of 417 undergraduate students aged 18-26 from March to May 2021; convenience sampling was performed to recruit three sex-matched dyads of a total of six (four female and two male) undergraduates from survey respondents who had not completed the HPV vaccine series in May 2021. Binary logistic regression analyses showed HPV vaccine knowledge and perceived barriers to vaccination were factors contributing to coverage for both female and male students, while perceived risks of HPV and vaccine hesitancy were factors only among female students. Findings from the qualitative content analysis identified college students' perceived barriers to the vaccination at multiple levels and preferred strategies for vaccination promotion, corroborating the findings from the survey study. The findings provide implications that benefit the development of tailored interventions aimed at facilitating catch-up vaccination among college students in the Mid-South region. There is an urgent need for further research and the implementation of effective strategies that address the identified barriers and improve HPV vaccine uptake in this population.

Investigation and Modeling of the Variables of the Decision to Vaccinate as the Foundation of an Algorithm for Reducing Vaccination Reluctance

The purpose of this study is to examine the factors that influence vaccination options, including vaccination against COVID-19, in order to develop a management algorithm for decision-makers to reduce vaccination reluctance. This paper’s primary objective is to empirically determine the relationships between different variables that correlate to non-vaccination behavior of the target population, as well as the implications for public health and situational management strategies for future vaccination intentions. We created a questionnaire to investigate the personal approach to disease prevention measures in general and vaccination in particular. Using SmartPLS, load factors for developing an algorithm to manage vaccination reluctance were calculated. The results shows that the vaccination status of an individual is determined by their vaccine knowledge. The evaluation of the vaccine itself influences the choice not to vaccinate. There is a connection between external factors influencing the decision not to vaccinate and the clients’ motives. This plays a substantial part in the decision of individuals not to protect themselves by vaccination. External variables on the decision not to vaccinate correlate with agreement/disagreement on COVID-19 immunization, but there is no correlation between online activity and outside influences on vaccination refusal or on vaccine opinion in general.

Understanding COVID: Collaborative Government Campaign for Citizen Digital Health Literacy in the COVID-19 Pandemic

The strategy "Understanding COVID" was a Public Health campaign designed in 2020 and launched in 2021 in Asturias-Spain to provide reliable and comprehensive information oriented to vulnerable populations. The campaign involved groups considered socially vulnerable and/or highly exposed to COVID-19 infection: shopkeepers and hoteliers, worship and religious event participants, school children and their families, and scattered rural populations exposed to the digital divide. The purpose of this article was to describe the design of the "Understanding COVID" strategy and the evaluation of the implementation process. The strategy included the design and use of several educational resources and communication strategies, including some hundred online training sessions based on the published studies and adapted to the language and dissemination approaches, that reached 1056 people of different ages and target groups, an accessible website, an informative video channel, posters and other pedagogical actions in education centers. It required a great coordination effort involving different public and third-sector entities to provide the intended pandemic protection and prevention information at that difficult time. A communication strategy was implemented to achieve different goals: reaching a diverse population and adapting the published studies to different ages and groups, focusing on making it comprehensible and accessible for them. In conclusion, given there is a common and sufficiently important goal, it is possible to achieve effective collaboration between different governmental bodies to develop a coordinated strategy to reach the most vulnerable populations while taking into consideration their different interests and needs.