Exploring online health information seeking and sharing among older adults: a mini-review about acceptance, potentials, and barriers

Online health information seeking (OHIS) is understood by health care, health promotion, and disease prevention experts as a resource for healthy aging. It is particularly relevant for older adults since this population can benefit significantly from the accessibility and convenience of online health platforms and health information. Nevertheless, empirical findings regarding the acceptance, potentials, and barriers of OHIS among older adults are limited. This mini-review aims to explore the level of acceptance of OHIS, including passive reading of information and active interactions with peers, among the older population. Furthermore, it examines the potentials and barriers associated with such practices. The findings ultimately emphasize the evolving landscape of internet health information exploration among older adults and the potential advantages and challenges that may arise, especially in the context of active interactions with peers.

Improving Predictability and Effectiveness in Preventive Digital Health Interventions: Scoping Review

BACKGROUND

Lifestyle-related diseases caused by inadequate diet and physical activity cause premature death, loss of healthy life years, and increased health care costs. Randomized controlled trial (RCT) studies indicate that preventive digital health interventions (P-DHIs) can be effective in preventing these health problems, but the results of these studies are mixed. Adoption studies have identified multiple factors related to individuals and the context in which they live that complicate the transfer of positive results from RCT studies to practical use. Implementation studies have revealed barriers to the large-scale implementation of mobile health (mHealth) solutions in general. Consequently, there is no clear path to delivering predictable outcomes from P-DHIs and achieving effectiveness when scaling up interventions to reduce health problems in society.

OBJECTIVE

This research aimed to expand our understanding of how to increase the outcome predictability of P-DHIs by focusing on physical activity and diet behaviors and amplify our understanding of how to improve effectiveness in large-scale implementations.

METHODS

The research objective was pursued through a multidisciplinary scoping review. This scoping review used the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) as a guide. A comprehensive search of Web of Science and PubMed limited to English-language journal articles published before January 2022 was conducted. Google Scholar was used for hand searches. Information systems theory was used to identify key constructs influencing outcomes of IT in general. Public health and mHealth literature were used to identify factors influencing the adoption of, outcomes from, and implementation of P-DHIs. Finally, the P-DHI investment model was developed based on information systems constructs and factors from the public health and mHealth literature.

RESULTS

In total, 203 articles met the eligibility criteria. The included studies used a variety of methodologies, including literature reviews, interviews, surveys, and RCT studies. The P-DHI investment model suggests which constructs and related factors should be emphasized to increase the predictability of P-DHI outcomes and improve the effectiveness of large-scale implementations.

CONCLUSIONS

The research suggests that outcome predictability could be improved by including descriptions of the constructs and factors in the P-DHI investment model when reporting from empirical studies. Doing so would increase our understanding of when and why P-DHIs succeed or fail. The effectiveness of large-scale implementations may be improved by using the P-DHI investment model to evaluate potential difficulties and possibilities in implementing P-DHIs to create better environments for their use before investing in them and when designing and implementing them. The cost-effectiveness of large-scale implementations is unknown; implementations are far more complicated than just downloading and using apps, and there is uncertainty accompanying implementations given the lack of coordinated control over the constructs and factors that influence the outcome.

The Utilization of Mobile Phones in Health Information Seeking in Rural China

This study aims to investigate the mobile phone utilization for health information seeking among adults who are 45 years or older in rural areas in China. Using Andersen’s Behavioral Model (BM), we examine the factors that influence the target group’s behaviors of online health information seeking and contacting healthcare providers via mobile phones. By using stratified sampling method, we conducted a survey among 607 rural adults who were 45 years or older from six villages in Jiangsu Province, China. The results reveal that participants can be excluded from such services for not using a smartphone. eHealth information literacy could serve as a strong influential factor for online health information seeking and contacting healthcare providers via mobile phones. Participants with lower emotional wellbeing are more inclined to seek health information online via mobile phones. The results indicate variables such as utilization of technological devices and eHealth literacy should be included in Andersen’s model when investigating the utilization of mHealth services. This study contributes to the literature on mHealth adoption in rural areas in China and has implications for practitioners to tailor the mHealth service for socio-economically disadvantaged groups.

Behavioral Patterns of Supply and Demand Sides of Health Services for the Elderly in Sustainable Digital Transformation: A Mixed Methods Study

The aging transformation of digital health services faces issues of how to distinguish influencing factors, redesign services, and effectively promote measures and policies. In this study, in-depth interviews were conducted, and grounded theory applied to open coding, main axis coding, and selective coding to form concepts and categories. Trajectory equifinality modeling clarified the evolution logic of digital transformation. Based on the theory of service ecology, a digital health service aging model was constructed from the “macro–medium–micro” stages and includes governance, service, and technology transformation paths. The macro stage relies on organizational elements to promote the institutionalization of management and guide the transformation of governance for value realization, including the construction of three categories: mechanism, indemnification, and decision-making. The meso stage relies on service elements to promote service design and realize service transformation that is suitable for aging design, including the construction of three categories: organization, resources, and processes. The micro stage relies on technical elements to practice experiencing humanization, including the construction of three categories: target, methods, and evaluation. These results deepen the understanding of the main behaviors and roles of macro-organizational, meso-service, and micro-technical elements in digital transformation practice and have positive significance for health administrative agencies to implement action strategies.