Background
To improve lifestyle guidance within cardiac rehabilitation (CR), a comprehensive understanding of the motivation and lifestyle-supporting needs of patients with cardiovascular disease (CVD) is required.

Objectives
This study's purpose is to evaluate patients’ lifestyle and their motivation, self-efficacy and social support for change when starting CR.

Methods
1782 CVD patients (69 % male, mean age 62 years) from 7 Dutch outpatient CR centers participated between 2020 and 2022. Modifiable risk factors were assessed with a survey and interviews by healthcare professionals during CR intake.

Results
Most patients exhibited an elevated risk in 3–4 domains. Elevated risks were most prominent in domains of (1) waist circumference and BMI (2) physical exercise (3) healthy foods intake and (4) sleep duration. Most patients chose to focus on increasing physical exercise, but about 20 % also wanted to focus on a healthy diet and/or decrease stress levels. Generally, motivation, self-efficacy and social support to reach new lifestyle goals were high. However, patients with an unfavorable risk profile had lower motivation and self-efficacy to work on lifestyle changes, while patients with lower social support had a higher chance to quit the program prematurely.

Conclusions
Our results underscore the need to begin CR with a comprehensive lifestyle assessment and highlight the importance of offering lifestyle interventions tailored to patients’ specific modifiable risk factors and lifestyle-supporting needs, targeting multiple lifestyle domains. Expanding the current scope of CR programs to address diverse patient needs and strengthening support may enhance motivation and adherence and lead to significant long-term benefits for cardiovascular health.

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.

Objective: eHealth interventions can improve the health outcomes of people with a low socioeconomic position (SEP) by promoting healthy lifestyle behaviours. However, developing and implementing these interventions among the target group can be challenging for professionals. To facilitate the uptake of effective interventions, this study aimed to identify the barriers and facilitators anticipated or experienced by professionals in the development, reach, adherence, implementation and evaluation phases of eHealth interventions for people with a low SEP. Method: We used a Delphi method, consisting of two online questionnaires, to determine the consensus on barriers and facilitators anticipated or experienced during eHealth intervention phases and their importance. Participants provided open-ended responses in the first round and rated statements in the second round. The interquartile range was used to calculate consensus, and the (totally) agree ratings were used to assess importance. Results: Twenty-seven professionals participated in the first round, and 19 (70.4%) completed the second round. We found a consensus for 34.8% of the 46 items related to highly important rated barriers, such as the lack of involvement of low-SEP people in the development phase, lack of knowledge among professionals about reaching the target group, and lack of knowledge among lower-SEP groups about using eHealth interventions. Additionally, we identified a consensus for 80% of the 60 items related to highly important rated facilitators, such as rewarding people with a low SEP for their involvement in the development phase and connecting eHealth interventions to the everyday lives of lower-SEP groups to enhance reach. Conclusion: Our study provides valuable insights into the barriers and facilitators of developing eHealth interventions for people with a low SEP by examining current practices and offering recommendations for future improvements. Strengthening facilitators can help overcome these barriers. To achieve this, we recommend defining the roles of professionals and lower-SEP groups in each phase of eHealth intervention and disseminating this study's findings to professionals to optimize the impact of eHealth interventions for this group.

Background: eHealth interventions have the potential to enhance health outcomes for people with a low socioeconomic position (SEP), but lack of knowledge on how to effectively meet the specific needs of this population can limit their effectiveness and widen the digital divide. Our study aimed to address this issue by developing an online guide for professionals (e.g., researchers and health professionals) to support the development and adaptation of eHealth interventions for people with low SEP. Methods: During the initial phase, we conducted two studies: (1) a Delphi study with professionals, identifying barriers to developing, evaluating, and implementing eHealth interventions (top-down), and (2) a communitybased study with people from low SEP, exploring their perspectives on health, healthcare, and eHealth (bottom-up). In the second phase, an iterative participatory process was used to develop the online guide, involving 11 professionals in think-aloud sessions and interviews to assess content and design acceptance. The presentation focuses on outcomes of this second phase. Findings: Professionals found the online guide to be user-friendly and helpful, particularly the recommendations on barriers, facilitators, and user scenarios. However, they requested more practical examples and engaging content. Discussion: This guide is an important contribution to addressing the knowledge gap in eHealth interventions for people with a low SEP and provides valuable information for professionals, whether they are new to the field or have experience. Future research should focus on enhancing the guide's usability and flexibility for its diverse audience, including healthcare practitioners, and other eHealth professionals working with this population.

BACKGROUND: People with a low socioeconomic position (SEP) are less likely to benefit from eHealth interventions, exacerbating social health inequalities. Professionals developing eHealth interventions for this group face numerous challenges. A comprehensive guide to support these professionals in their work could mitigate these inequalities. OBJECTIVE: We aimed to develop a web-based guide to support professionals in the development, adaptation, evaluation, and implementation of eHealth interventions for people with a low SEP. METHODS: This study consisted of 2 phases. The first phase involved a secondary analysis of 2 previous qualitative and quantitative studies. In this phase, we synthesized insights from the previous studies to develop the guide's content and information structure. In the second phase, we used a participatory design process. This process included iterative development and evaluation of the guide's design with 11 professionals who had experience with both eHealth and the target group. We used test versions (prototypes) and think-aloud testing combined with semistructured interviews and a questionnaire to identify design requirements and develop and adapt the guide accordingly. RESULTS: The secondary analysis resulted in a framework of recommendations for developing the guide, which was categorized under 5 themes: development, reach, adherence, evaluation, and implementation. The participatory design process resulted in 16 requirements on system, content, and service aspects for the design of the guide. For the system category, the guide was required to have an open navigation strategy leading to more specific information and short pages with visual elements. Content requirements included providing comprehensible information, scientific evidence, a user perspective, information on practical applications, and a personal and informal tone of voice. Service requirements involved improving suitability for different professionals, ensuring long-term viability, and a focus on implementation. Based on these requirements, we developed the final version of "the inclusive eHealth guide." CONCLUSIONS: The inclusive eHealth guide provides a practical, user-centric tool for professionals aiming to develop, adapt, evaluate, and implement eHealth interventions for people with a low SEP, with the aim of reducing health disparities in this population. Future research should investigate its suitability for different end-user goals, its external validity, its applicability in specific contexts, and its real-world impact on social health inequality.

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.

Low socioeconomic status (SES) is associated with a higher prevalence of unhealthy lifestyles compared to a high SES. Health interventions that promote a healthy lifestyle, like eHealth solutions, face limited adoption in low SES groups. To improve the adoption of eHealth interventions, their alignment with the target group's attitudes is crucial. This study investigated the attitudes of people with a low SES toward health, healthcare, and eHealth. We adopted a mixed-method community-based participatory research approach with 23 members of a community center in a low SES neighborhood in the city of Rotterdam, the Netherlands. We conducted a first set of interviews and analyzed these using a grounded theory approach resulting in a group of themes. These basic themes' representative value was validated and refined by an online questionnaire involving a different sample of 43 participants from multiple community centers in the same neighborhood. We executed three focus groups to validate and contextualize the results. We identified two general attitudes based on nine profiles toward health, healthcare, and eHealth. The first general attitude, optimistically engaged, embodied approximately half our sample and involved light-heartedness toward health, loyalty toward healthcare, and eagerness to adopt eHealth. The second general attitude, doubtfully disadvantaged, represented roughly a quarter of our sample and was related to feeling encumbered toward health, feeling disadvantaged within healthcare, and hesitance toward eHealth adoption. The resulting attitudes strengthen the knowledge of the motivation and behavior of people with low SES regarding their health. Our results indicate that negative health attitudes are not as evident as often claimed. Nevertheless, intervention developers should still be mindful of differentiating life situations, motivations, healthcare needs, and eHealth expectations. Based on our findings, we recommend eHealth should fit into the person's daily life, ensure personal communication, be perceived usable and useful, adapt its communication to literacy level and life situation, allow for meaningful self-monitoring and embody self-efficacy enhancing strategies.