Objectives: eHealth interventions favor those with higher socio-economic positions (SEPs). This can widen disparities, as people with lower SEPs may lack resources and face digital or financial barriers, making tailored solutions necessary. This study evaluates professionals' perceptions of the Inclusive eHealth Guide (IeG) regarding its content. The aim was to ensure it meets the needs of professionals and the targeted lower SEP demographic, thereby enhancing the effectiveness of eHealth interventions.

Methods: This mixed-method study used qualitative research through semi-structured interviews and the think-aloud method with 13 professionals involved in eight different eHealth lifestyle interventions using the eHealth guide. Quantitative feedback was obtained through a survey with evaluative multiple-choice questions. Participants evaluated the IeG at various stages. They identified positive aspects and points for improvement, and provided recommendations for the guide's content and structure.

Results: Participants valued the IeG's practicality and comprehensiveness, noting its usefulness in developing accessible eHealth solutions for populations with lower SEP. They suggested improving content clarity, expanding informational depth, and refining the guide's structure.

Conclusions: The IeG has potential as a valuable tool for professionals developing eHealth interventions for lower SEP populations. Continuous refinement is crucial to ensure the guide remains relevant and effective, contributing to reducing health disparities.

Aims
Cardiac rehabilitation (CR) shows lower effectiveness and higher dropouts among people with a low socioeconomic position (SEP) compared to those with a high SEP. This study evaluated an eHealth intervention aimed at supporting patients with a low SEP during their waiting period preceding CR.

Methods and results
Participants with a low SEP in their waiting period before CR were randomized into an intervention group, receiving guidance videos, patient narratives, and practical tips, or into a control group. We evaluated adherence (usage metrics), acceptance (modified Usefulness, Satisfaction, and Ease of use questionnaire), and changes in feelings of certainty and guidance between the waiting period’s start and end. Semi-structured interviews provided complementary insights. The study involved 41 participants [median interquartile range (IQR) age 62 (14) years; 33 males], with 21 participants allocated to the intervention group, using the eHealth intervention for a median (IQR) duration of 16 (10) days, using it on a median (IQR) of 100% (25) of these days, and viewing 88% of the available messages. Key adherence themes were daily routine compatibility and curiosity. Acceptance rates were 86% for usability, 67% for satisfaction, and 43% for usefulness. No significant effects on certainty and guidance were observed, but qualitative data suggested that the intervention helped to inform and set expectations.

Conclusion
The study found the eHealth intervention feasible for cardiac patients with a low SEP, with good adherence, usability, and satisfaction. However, it showed no effect on feelings of certainty and guidance. Through further optimization of its content, the intervention holds promise to improve emotional resilience during the waiting period.

Registration
This trial is registered as follows: ‘Evaluation of a Preparatory eHealth Intervention to Support Cardiac Patients During Their Waiting Period (PReCARE)’ at ClinicalTrials.gov (NCT05698121).

Health disparities between socio-economic classes are growing. While eHealth has been proposed as a potential solution, it often disproportionately benefits people with a higher socio-economic position (SEP) thereby exacerbating health disparities. We aimed to develop an eHealth intervention that supports specifically people with a low SEP during their waiting period between hospital referral and start of cardiac rehabilitation (CR). We followed a participatory design process in which we used a variety of participatory and inclusive design tools and techniques to identify needs of the target group and develop the intervention. 15 cardiac patients with a low SEP participated in the development (n = 8) and evaluation (n = 7) of the intervention. We found that patients with a low SEP require certainty and guidance during their waiting period. To address this, healthcare providers guide them through this transitional phase using multimedia resources in the eHealth intervention. This includes introductions of the healthcare providers and information about their roles, peer experiences, practical tips and daily updates on the remaining waiting time. The evaluation yielded high scores on usability (4.4 out of 5), experience (4.1 out of 5) and perceived effect on certainty and guidance (4.0 out of 5). This study explored how eHealth can bridge gaps between hospitals and CR and between high and low SEP. It emphasizes the significance of utilizing participatory and inclusive approaches to develop feasible and acceptable eHealth interventions for those with low SEP. Currently, follow-up evaluative research is conducted to determine the proof-of-principle of the intervention.

Promoting health behaviors and preventing chronic diseases through a healthy lifestyle among those with a low socioeconomic status (SES) remain major challenges. eHealth interventions are a promising approach to change unhealthy behaviors in this target group. Objective: This review aims to identify key components, barriers, and facilitators in the development, reach, use, evaluation, and implementation of eHealth lifestyle interventions for people with a low SES. This review provides an overview for researchers and eHealth developers, and can assist in the development of eHealth interventions for people with a low SES. Methods: We performed a scoping review based on Arksey and O'Malley's framework. A systematic search was conducted on PubMed, MEDLINE (Ovid), Embase, Web of Science, and the Cochrane Library, using terms related to a combination of the following key constructs: eHealth, lifestyle, low SES, development, reach, use, evaluation, and implementation. There were no restrictions on the date of publication for articles retrieved upon searching the databases. Results: The search identified 1323 studies, of which 42 met our inclusion criteria. An update of the search led to the inclusion of 17 additional studies. eHealth lifestyle interventions for people with a low SES were often delivered via internet-based methods (eg, websites, email, Facebook, and smartphone apps) and offline methods, such as texting. A minority of the interventions combined eHealth lifestyle interventions with face-to-face or telephone coaching, or wearables (blended care). We identified the use of different behavioral components (eg, social support) and technological components (eg, multimedia) in eHealth lifestyle interventions. Facilitators in the development included iterative design, working with different disciplines, and resonating intervention content with users. Facilitators for intervention reach were use of a personal approach and social network, reminders, and self-monitoring. Nevertheless, barriers, such as technological challenges for developers and limited financial resources, may hinder intervention development. Furthermore, passive recruitment was a barrier to intervention reach. Technical difficulties and the use of self-monitoring devices were common barriers for users of eHealth interventions. Only limited data on barriers and facilitators for intervention implementation and evaluation were available. Conclusions: While we found large variations among studies regarding key intervention components, and barriers and facilitators, certain factors may be beneficial in building and using eHealth interventions and reaching people with a low SES. Barriers and facilitators offer promising elements that eHealth developers can use as a toolbox to connect eHealth with low SES individuals. Our findings suggest that one-size-fits-all eHealth interventions may be less suitable for people with a low SES. Future research should investigate how to customize eHealth lifestyle interventions to meet the needs of different low SES groups, and should identify the components that enhance their reach, use, and effectiveness.