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OBJECTIVE: Communicating risk information and offering lifestyle advice are important goals in cardiac rehabilitation. However, the most effective way and the most effective source to communicate this information are not yet known. Therefore, we examined the effect of source (cardiologist, physiotherapist) and framing (gain, loss) of brief lifestyle advice on patients' intention-to-change-lifestyle. METHODS: In an online experimental study, 636 cardiac patients (40% female, 67 (10) yrs.) were randomly assigned to one of four textual vignettes. Effect of source and framing on intention-to-change-lifestyle (assessed using a 5-point Likert scale) was analysed using analysis of covariance (ANCOVA). RESULTS: Patients expressed positive intention-to-change-lifestyle after receiving advice from the cardiologist (Mâ¯= 4.1) and physiotherapist (Mâ¯= 3.9). However, patients showed significantly higher intention-to-change-lifestyle after receiving advice from the cardiologist (0.58 [0.54-0.61]) when compared with the physiotherapist (0.52 [0.48-0.56]), (F[1,609]â¯= 7.06, Pâ¯= 0.01). Gain-framed and loss-framed advice appeared equally effective. However, communicating risks (loss) was remembered by only 9% of patients, whereas 89% remembered benefits (gain). CONCLUSIONS: Our study shows the value of cardiologists and physiotherapists communicating brief lifestyle advice, as cardiac patients expressed positive intention for lifestyle change after receiving advice, irrespective of framing. Lifestyle advice should include benefits due to better recall.
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OBJECTIVE: eHealth is a useful tool to deliver lifestyle interventions for patients with cardiometabolic diseases. However, there are inconsistent findings about whether these eHealth interventions should be supported by a human professional, or whether self-help interventions are equally effective. METHODS: Databases were searched between January 1995 and October 2021 for randomized controlled trials on cardiometabolic diseases (cardiovascular disease, chronic kidney disease, type 1 and 2 diabetes mellitus) and eHealth lifestyle interventions. A multilevel meta-analysis was used to pool clinical and behavioral health outcomes. Moderator analyses assessed the effect of intervention type (self-help versus human-supported), dose of human support (minor versus major part of intervention), and delivery mode of human support (remote versus blended). One hundred seven articles fulfilled eligibility criteria and 102 unique ( N = 20,781) studies were included. RESULTS: The analysis showed a positive effect of eHealth lifestyle interventions on clinical and behavioral health outcomes ( p < .001). However, these effects were not moderated by intervention type ( p = .169), dose ( p = .698), or delivery mode of human support ( p = .557). CONCLUSIONS: This shows that self-help eHealth interventions are equally effective as human-supported ones in improving health outcomes among patients with cardiometabolic disease. Future studies could investigate whether higher-quality eHealth interventions compensate for a lack of human support.Meta-analysis registration: PROSPERO CRD42021269263 .
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Enfermedades Cardiovasculares , Diabetes Mellitus Tipo 1 , Diabetes Mellitus Tipo 2 , Telemedicina , Humanos , Diabetes Mellitus Tipo 2/prevención & control , Estilo de Vida , Enfermedades Cardiovasculares/prevención & controlRESUMEN
BACKGROUND AND AIMS: Diet is important in prevention and management of non-communicable disease and in particular, cardiovascular disease. Recently, more hospitals gear towards healthier dietary policies, however, a tool to assess the effect of these interventions in patient populations is currently lacking. The Theory of Planned Behavior (TPB) is generally used to assess health-related behavior and offers a framework for development of questionnaires. In this study, we aim to evaluate the reliability, internal consistency and preliminary construct validity of the newly developed Dietary Intention Evaluation Tool for In-hospital patients (DIETI) which is based on the TPB. METHODS AND RESULTS: An expert panel constructed the item list of the DIETI. A total of 312 patients admitted to the cardiology ward filled out the DIETI. Explanatory- and confirmatory factor analysis showed that our tool adequately discerns five TPB-consistent factors regarding a healthy diet in hospitalized patients. (N = 312, for the CFA model χ2 = 313.072 (df = 160, p < 0.001, CFI = 0.939, RMSEA = 0.058). Subsequent analysis of reliability showed satisfactory to strong internal consistency of the questionnaire as a whole and all subscales (Cronbach's alpha for the subscales ranging between 0.65 and 0.88). CONCLUSIONS: We conclude that the DIETI is an internally reliable tool to assess behavioral intentions regarding a healthy diet of in-hospital patients. Thus, this questionnaire can be used to evaluate the effect of dietary interventions aimed at hospitalized patients.
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Dieta , Intención , Humanos , Reproducibilidad de los Resultados , Encuestas y Cuestionarios , Conductas Relacionadas con la SaludRESUMEN
BACKGROUND: The number of complex eHealth interventions has increased considerably. Despite available implementation theory outlining well-designed strategies, implementing complex interventions within practice proves challenging and often does not lead to sustainable use. To improve sustainability, theory and practice should be addressed during the development of an implementation strategy. By subsequently transparently reporting the executed theory-based steps and their corresponding practice findings, others can learn from these valuable lessons learned. This study outlines the iterative approach by which a multifaceted implementation strategy for a complex eHealth intervention in clinical practice was developed, tested and refined. METHODS: We implemented the BENEFIT program, an advanced eHealth platform with Personal Health Portal facilitating healthy living in cardiac patients. In six iterative phases alternating between theory and practice, the implementation strategy was developed, tested and refined. The initial implementation strategy (phase 1) was drawn up using the Implementation model and RE-AIM. Subsequently, this strategy was further updated in brainstorming sessions and group discussions with twenty key stakeholders from three cardiac care centres and then evaluated in a pilot (phases 2 and 3). RESULTS: The pilot of the program led to the identification of (context-specific) key challenges in practice (phase 4), which were subsequently connected back to broader theory (phase 5) using the Consolidated Framework of Implementation Research (CFIR). In the final phase, practice recommendations tackling the key challenges were formulated (phase 6) based on CFIR theory, the CFIR-ERIC Matching Tool, and stakeholders' input and feedback. These recommendations were then added to the refined strategy. Thus, executing this approach led to the realisation and use of a multifaceted theory-informed practice-based implementation strategy. CONCLUSION: This case study gives an in-depth description of an iterative approach to developing an evidence-based, practice-tailored strategy for implementing a complex eHealth intervention in cardiac care. As such, this study may serve as a blueprint for other researchers aspiring to implement complex eHealth interventions within clinical practice sustainably.
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Telemedicina , Humanos , Práctica Clínica Basada en la EvidenciaRESUMEN
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.
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Telemedicina , Voz , Humanos , Disparidades en el Estado de SaludRESUMEN
BACKGROUND: 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.
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Promoción de la Salud , Estilo de Vida Saludable , Clase Social , Telemedicina , Humanos , Internet , Estilo de Vida , Telemedicina/métodos , TeléfonoRESUMEN
BACKGROUND: Financial incentive interventions for improving physical activity have proven to be effective but costly. Deposit contracts (in which participants pledge their own money) could be an affordable alternative. In addition, deposit contracts may have superior effects by exploiting the power of loss aversion. Previous research has often operationalized deposit contracts through loss framing a financial reward (without requiring a deposit) to mimic the feelings of loss involved in a deposit contract. OBJECTIVE: This study aimed to disentangle the effects of incurring actual losses (through self-funding a deposit contract) and loss framing. We investigated whether incentive conditions are more effective than a no-incentive control condition, whether deposit contracts have a lower uptake than financial rewards, whether deposit contracts are more effective than financial rewards, and whether loss frames are more effective than gain frames. METHODS: Healthy participants (N=126) with an average age of 22.7 (SD 2.84) years participated in a 20-day physical activity intervention. They downloaded a smartphone app that provided them with a personalized physical activity goal and either required a 10 (at the time of writing: 1=US $0.98) deposit up front (which could be lost) or provided 10 as a reward, contingent on performance. Daily feedback on incentive earnings was provided and framed as either a loss or gain. We used a 2 (incentive type: deposit or reward) × 2 (feedback frame: gain or loss) between-subjects factorial design with a no-incentive control condition. Our primary outcome was the number of days participants achieved their goals. The uptake of the intervention was a secondary outcome. RESULTS: Overall, financial incentive conditions (mean 13.10, SD 6.33 days goal achieved) had higher effectiveness than the control condition (mean 8.00, SD 5.65 days goal achieved; P=.002; ηp2=0.147). Deposit contracts had lower uptake (29/47, 62%) than rewards (50/50, 100%; P<.001; Cramer V=0.492). Furthermore, 2-way analysis of covariance showed that deposit contracts (mean 14.88, SD 6.40 days goal achieved) were not significantly more effective than rewards (mean 12.13, SD 6.17 days goal achieved; P=.17). Unexpectedly, loss frames (mean 10.50, SD 6.22 days goal achieved) were significantly less effective than gain frames (mean 14.67, SD 5.95 days goal achieved; P=.007; ηp2=0.155). CONCLUSIONS: Financial incentives help increase physical activity, but deposit contracts were not more effective than rewards. Although self-funded deposit contracts can be offered at low cost, low uptake is an important obstacle to large-scale implementation. Unexpectedly, loss framing was less effective than gain framing. Therefore, we urge further research on their boundary conditions before using loss-framed incentives in practice. Because of limited statistical power regarding some research questions, the results of this study should be interpreted with caution, and future work should be done to confirm these findings. TRIAL REGISTRATION: Open Science Framework Registries osf.io/34ygt; https://osf.io/34ygt.
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Aplicaciones Móviles , Adulto , Ejercicio Físico , Humanos , Motivación , Actividad Motora , Recompensa , Adulto JovenRESUMEN
BACKGROUND: Cardiovascular diseases (CVDs) pose a significant health threat and reduce both people's life expectancy and quality of life. Healthy living is a key component in the effective prevention and treatment of CVD. However, health care professionals (HCPs) experience difficulties in supporting lifestyle changes among their patients. eHealth can provide a solution to these barriers. OBJECTIVE: This study aims to provide insights into the factors HCPs find important in the support of patients with CVD in the uptake of and adherence to a healthy lifestyle and the perceived facilitators of and barriers to using eHealth to provide lifestyle support to patients with CVD. METHODS: In-depth interviews were conducted with 16 Dutch HCPs specializing in lifestyle support in cardiac care. RESULTS: We identified 13 themes, of which the first 12 concerned lifestyle support in general and were related to intervention, patient, or health care. Throughout these themes, the use of eHealth reoccurred as a potential facilitator of or solution to barriers to lifestyle support. Our final theme specifically concerned barriers to the adoption and usability of eHealth. CONCLUSIONS: HCPs do recognize the potential advantages of eHealth while experiencing barriers to using digital tools. Incorporating their needs and values in the development of lifestyle support programs, especially eHealth, could increase their use and lead to a more widespread adoption of eHealth into health care.
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Calidad de Vida , Telemedicina , Atención a la Salud , Personal de Salud , Estilo de Vida Saludable , HumanosRESUMEN
BACKGROUND: Self-help eHealth interventions provide automated support to change health behaviors without any further human assistance. The main advantage of self-help eHealth interventions is that they have the potential to lower the workload of health care professionals. However, one disadvantage is that they generally have a lower uptake. Possibly, the absence of a relationship with a health care professional (referred to as the working alliance) could lead to negative expectations that hinder the uptake of self-help interventions. The Unified Theory of Acceptance and Use of Technology (UTAUT) identifies which expectations predict use intention. As there has been no previous research exploring how expectations affect the adoption of both self-help and human-supported eHealth interventions, this study is the first to investigate the impact of expectations on the uptake of both kinds of eHealth interventions. OBJECTIVE: This study investigated the intention to use a self-help eHealth intervention compared to a human-supported eHealth intervention and the expectations that moderate this relationship. METHODS: A total of 146 participants were randomly assigned to 1 of 2 conditions (human-supported or self-help eHealth interventions). Participants evaluated screenshots of a human-supported or self-help app-based stress intervention. We measured intention to use the intervention-expected working alliance and the UTAUT constructs: performance expectancy, effort expectancy, and social influence. RESULTS: Use intention did not differ significantly between the 2 conditions (t142=-1.133; P=.26). Performance expectancy (F1,140=69.269; P<.001), effort expectancy (F1,140=3.961; P=.049), social influence (F1,140=90.025; P<.001), and expected working alliance (F1,140=26.435; P<.001) were positively related to use intention regardless of condition. The interaction analysis showed that performance expectancy (F1,140=4.363; P=.04) and effort expectancy (F1,140=4.102; P=.045) more strongly influenced use intention in the self-help condition compared to the human-supported condition. CONCLUSIONS: As we found no difference in use intention, our results suggest that we could expect an equal uptake of self-help eHealth interventions and human-supported ones. However, attention should be paid to people who have doubts about the intervention's helpfulness or ease of use. For those people, providing additional human support would be beneficial to ensure uptake. Screening user expectations could help health care professionals optimize self-help eHealth intervention uptake in practice. TRIAL REGISTRATION: OSF Registries osf.io/n47cz; https://osf.io/n47cz.
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BACKGROUND: Type 2 diabetes (T2D) tremendously affects patient health and health care globally. Changing lifestyle behaviors can help curb the burden of T2D. However, health behavior change is a complex interplay of medical, behavioral, and psychological factors. Personalized lifestyle advice and promotion of self-management can help patients change their health behavior and improve glucose regulation. Digital tools are effective in areas of self-management and have great potential to support patient self-management due to low costs, 24/7 availability, and the option of dynamic automated feedback. To develop successful eHealth solutions, it is important to include stakeholders throughout the development and use a structured approach to guide the development team in planning, coordinating, and executing the development process. OBJECTIVE: The aim of this study is to develop an integrated, eHealth-supported, educational care pathway for patients with T2D. METHODS: The educational care pathway was developed using the first 3 phases of the Center for eHealth and Wellbeing Research roadmap: the contextual inquiry, the value specification, and the design phase. Following this roadmap, we used a scoping review about diabetes self-management education and eHealth, past experiences of eHealth practices in our hospital, focus groups with health care professionals (HCPs), and a patient panel to develop a prototype of an educational care pathway. This care pathway is called the Diabetes Box (Leiden University Medical Center) and consists of personalized education, digital educational material, self-measurements of glucose, blood pressure, activity, and sleep, and a smartphone app to bring it all together. RESULTS: The scoping review highlights the importance of self-management education and the potential of telemonitoring and mobile apps for blood glucose regulation in patients with T2D. Focus groups with HCPs revealed the importance of including all relevant lifestyle factors, using a tailored approach, and using digital consultations. The contextual inquiry led to a set of values that stakeholders found important to include in the educational care pathway. All values were specified in biweekly meetings with key stakeholders, and a prototype was designed. This prototype was evaluated in a patient panel that revealed an overall positive impression of the care pathway but stressed that the number of apps should be restricted to one, that there should be no delay in glucose value visualization, and that insulin use should be incorporated into the app. Both patients and HCPs stressed the importance of direct automated feedback in the Diabetes Box. CONCLUSIONS: After developing the Diabetes Box prototype using the Center for eHealth and Wellbeing Research roadmap, all stakeholders believe that the concept of the Diabetes Box is useful and feasible and that direct automated feedback and education on stress and sleep are essential. A pilot study is planned to assess feasibility, acceptability, and usefulness in more detail.
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Diabetes Mellitus Tipo 2 , Telemedicina , Humanos , Diabetes Mellitus Tipo 2/terapia , Masculino , Femenino , Educación del Paciente como Asunto/métodos , Persona de Mediana Edad , Automanejo/educación , Automanejo/métodos , AutocuidadoRESUMEN
BACKGROUND: Financial incentives are a promising tool to help people increase their physical activity, but they are expensive to provide. Deposit contracts are a type of financial incentive in which participants pledge their own money. However, low uptake is a crucial obstacle to the large-scale implementation of deposit contracts. Therefore, we investigated whether (1) matching the deposit 1:1 (doubling what is deposited) and (2) allowing for customizable deposit amounts increased the uptake and short term effectiveness of a deposit contract for physical activity. METHODS: In this randomized controlled trial, 137 healthy students (age M = 21.6 years) downloaded a smartphone app that provided them with a tailored step goal and then randomized them to one of four experimental conditions. The deposit contract required either a 10 fixed deposit or a customizable deposit with any amount between 1 and 20 upfront. Furthermore, the deposit was either not matched or 1:1 matched (doubled) with a reward provided by the experiment. During 20 intervention days, daily feedback on goal progress and incentive earnings was provided by the app. We investigated effects on the uptake (measured as agreeing to participate and paying the deposit) and effectiveness of behavioral adoption (measured as participant days goal achieved). FINDINGS: Overall, the uptake of deposit contracts was 83.2%, and participants (n = 113) achieved 14.9 out of 20 daily step goals. A binary logistic regression showed that uptake odds were 4.08 times higher when a deposit was matched (p = .010) compared to when it was not matched. Furthermore, uptake odds were 3.53 times higher when a deposit was customizable (p = .022) compared to when it was fixed. Two-way ANCOVA showed that matching (p = .752) and customization (p = .143) did not impact intervention effectiveness. However, we did find a marginally significant interaction effect of deposit matching X deposit customization (p = .063, ηp2 = 0.032). Customization decreased effectiveness when deposits were not matched (p = .033, ηp2 = 0.089), but had no effect when deposits were matched (p = .776, ηp2 = 0.001). CONCLUSIONS: We provide the first experimental evidence that both matching and customization increase the uptake of a deposit contract for physical activity. We recommend considering both matching and customization to overcome lack of uptake, with a preference for customization since matching a deposit imposes significant additional costs. However, since we found indications that customizable deposits might reduce effectiveness (when the deposits are not matched), we urge for more research on the effectiveness of customizable deposit contracts. Finally, future research should investigate which participant characteristics are predictive of deposit contract uptake and effectiveness. PRE-REGISTRATION: OSF Registries, https://osf.io/cgq48.
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Daucus carota , Motivación , Humanos , Adulto Joven , Ejercicio Físico , Renta , RecompensaRESUMEN
eHealth lifestyle interventions without human support (self-help interventions) are generally less effective, as they suffer from lower adherence levels. To solve this, we investigated whether (1) using a text-based conversational agent (TCA) and applying human cues contribute to a working alliance with the TCA, and whether (2) adding human cues and establishing a positive working alliance increase intervention adherence. Participants (N = 121) followed a TCA-supported app-based physical activity intervention. We manipulated two types of human cues: visual (ie, message appearance) and relational (ie, message content). We employed a 2 (visual cues: yes, no) x 2 (relational cues: yes, no) between-subjects design, resulting in four experimental groups: (1) visual and relational cues, (2) visual cues only, (3) relational cues only, or (4) no human cues. We measured the working alliance with the Working Alliance Inventory Short Revised form and intervention adherence as the number of days participants responded to the TCA's messages. Contrary to expectations, the working alliance was unaffected by using human cues. Working alliance was positively related to adherence (t(78) = 3.606, p = .001). Furthermore, groups who received visual cues showed lower adherence levels compared to those who received relational cues only or no cues (U = 1140.5, z = -3.520, p < .001). We replicated the finding that establishing a working alliance contributes to intervention adherence, independently of the use of human cues in a TCA. However, we were unable to show that adding human cues impacted the working alliance and increased adherence. The results indicate that adding visual cues to a TCA may even negatively affect adherence, possibly because it may create confusion concerning the true nature of the coach, which may prompt unrealistic expectations.
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BACKGROUND: eHealth technology can help patients with cardiovascular disease adopt and maintain a healthy lifestyle by supporting self-management and offering guidance, coaching, and tailored information. However, to support patients over time, eHealth needs to blend in with their needs, treatment, and daily lives. Just as needs can differ between patients, needs can change within patients over time. To better adapt technology features to patients' needs, it is necessary to account for these changes in needs and contexts of use. OBJECTIVE: This study aimed to identify and monitor patients' needs for support from a web-based health management platform and how these needs change over time. It aimed to answer the following research questions: "How do novice and more advanced users experience an online health management platform?" "What user expectations support or hinder the adoption of an online health management platform, from a user perspective?" and "How does actual usage relate to user experiences and adoption?" METHODS: A mixed methods design was adopted. The first method involved 2 rounds of usability testing, followed by interviews, with 10 patients at 0 months (round 1) and 12 patients at 6 months (round 2). In the second method, log data were collected to describe the actual platform use. RESULTS: After starting cardiac rehabilitation, the platform was used frequently. The patients mentioned that they need to have an incentive, set goals, self-monitor their health data, and feel empowered by the platform. However, soon after the rehabilitation program stopped, use of the platform declined or patients even quit because of the lack of continued tailored or personalized advice. The reward system motivated them to log data, but most participants indicated that being healthy should be the main focus, not receiving gifts. A web-based platform is flexible, accessible, and does not have any obligations; however, it should be implemented as an addition to regular care. CONCLUSIONS: Although use of the platform declined in the longer term, patients quitting the technology did not directly indicate that the technology was not functioning well or that patients no longer focused on achieving their values. The key to success should not be user adherence to a platform but adherence to healthy lifestyle habits. Therefore, the implementation of eHealth should include the transition to a stage where patients might no longer need support from a technology platform to be independently and sustainably adherent to their healthy lifestyle habits. This emphasizes the importance of conducting multi-iterative evaluations to continuously monitor whether and how patients' needs and contexts of use change over time. Future research should focus on how this transition can be identified and monitored and how these insights can inform the design and implementation of the technology.
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Background and aims: Adopting healthier diets can drastically improve societal health. Our environment plays a crucial role in daily dietary choices and hospitals in particular can stimulate patients to adopt healthier eating habits. Unfortunately, no robust clinically applicable cuing tools exist to help guide in-hospital dietary interventions. The purpose of this study was to identify patient-related barriers and facilitators to adopting healthier dietary choices. Methods and results: This cross-sectional observational study was conducted on the cardiology ward of a university medical center between June 2020 and January 2021. Of the 594 patients asked and the 312 completed surveys on healthy eating intentions, 285 responses were considered for analysis. Notably, the majority of respondents were male (68.8%), with an average hospital stay of 3.3 days. The results indicate that cardiac patients attribute significantly greater influence on their dietary behavior to doctors compared to other caregivers, including dieticians (X2 = 37.09, df = 9, p < 0.001). Also, younger patients (below 70 years of age) were more inclined to plan changing dietary behavior than older patients. Most mentioned facilitators for adopting a healthier diet were more information/counseling, help in preparing food, support from family and friends, and more emphasis from a doctor. Conclusion: The study highlights the importance of involving doctors in formulating dietary policies and patient-directed interventions within hospital settings. It also sheds light on the barriers and facilitators for promoting healthier dietary behaviors among patients during their hospitalization.
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Suboptimal diet is a major modifiable risk factor in cardiovascular disease. Governments, individuals, educational institutes, healthcare facilities and the industry all share the responsibility to improve dietary habits. Healthcare facilities in particular present a unique opportunity to convey the importance of healthy nutrition to patients, visitors and staff. Guidelines on cardiovascular disease do include policy suggestions for population-based approaches to diet in a broad list of settings. Regrettably, healthcare facilities are not explicitly included in this list. The authors propose to explicitly include healthcare facilities as a setting for policy suggestions in the current and future ESC Guidelines for cardiovascular disease prevention in clinical practice.
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Enfermedades Cardiovasculares , Humanos , Enfermedades Cardiovasculares/prevención & control , Dieta , Factores de Riesgo , Políticas , Atención a la SaludRESUMEN
Background: Gamification and deposit contracts (a financial incentive in which participants pledge their own money) can enhance effectiveness of mobile behavior change interventions. However, to assess their potential for improving population health, research should investigate implementation of gamified deposit contracts outside the research setting. Therefore, we analyzed data from StepBet, a smartphone application originally developed by WayBetter, Inc. Objective: To perform a naturalistic evaluation of StepBet gamified deposit contracts, for whom they work best, and under which conditions they are most effective to help increase physical activity. Methods: WayBetter provided data of StepBet participants that participated in a stepcount challenge between 2015 and 2020 (N = 72,974). StepBet challenges were offered on the StepBet smartphone application. The modal challenge consisted of a $40 deposit made prior to a 6-week challenge period during which participants needed to reach daily and weekly step goals in order to regain their deposit. Participants who met their goals also received additional earnings which were paid out from the money lost by those who failed their challenge. Challenge step goals were tailored on a 90-day historic step count retrieval that was also used as the baseline comparison for this study. Primary outcomes were increase in step count (continuous) and challenge success (dichotomous). Results: Overall, average daily step counts increased by 31.2 % (2423 steps, SD = 3462) from 7774 steps (SD = 3112) at baseline to 10,197 steps (SD = 4162) during the challenge. The average challenge success rate was 73 %. Those who succeeded in their challenge (n = 53,281) increased their step count by 44.0 % (3465 steps, SD = 3013), while those who failed their challenge (n = 19,693) decreased their step count by -5.3 % (-398 steps, SD = 3013). Challenges started as a New Year's resolution were slightly more successful (77.7 %) than those started during the rest of the year (72.6 %). Discussion: In a real-world setting, and among a large and diverse sample, participating in a gamified deposit contract challenge was associated with a large increase in step counts. A majority of challenges were successful and succeeding in a challenge was associated with a large and clinically relevant increase in step counts. Based on these findings, we recommend implementing gamified deposit contracts for physical activity where possible. An interesting avenue for future research is to explore possible setback effects among people who fail a challenge, and how setbacks can be mitigated. Pre-registration: Open Science Framework (doi:10.17605/OSF.IO/D237C).
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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.
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Telemedicina , Humanos , Técnica Delphi , Encuestas y Cuestionarios , Telemedicina/métodos , Consenso , Factores SocioeconómicosRESUMEN
[This corrects the article DOI: 10.1016/j.invent.2023.100610.].
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Background: Healthcare professionals (HPs) can play a substantial role in smoking cessation counseling (SCC) but in practice often skip this task due to time constraints. This study evaluates the implementation of the rapid Ask-Advise-Connect (AAC) method in a University hospital setting. Methods: This mixed methods pre-post interventional study was performed at the Cardiology department of a University hospital and consisted of (1) a quantitative assessment of patient smoking registration and HP connection rates to external SCC from the Electronic Medical Record, (2) semi-structured interviews with 10 HPs to assess their attitudes toward AAC, and (3) a blended intervention aimed to implement AAC. The blended intervention consisted of face-to-face and online AAC psychoeducation for HPs followed-up with motivational messages on their smart pagers over a period of 6 weeks. Results: In total, 48,321 patient registrations and 67 HPs were included. Before AAC implementation, HPs assessed smoking status in 74.0% of patients and connected 9.3% of identified smokers with SCC. Post intervention, these percentages did not increase (73.2%, p = 0.20; and 10.9%, p = 0.18, respectively). Nonetheless, the vast majority (90%) of HPs feel it is important to discuss patient smoking, and view it as their duty to do so. Main barriers to AAC reported by HPs were forgetfulness and time pressure. Conclusion: This study shows that this AAC intervention does not increase Asking after smoking status or Connection of patients to SCC in a University Hospital. However, HPs hold positive attitudes toward AAC. A better understanding of the mechanisms required for optimizing HPs practice behavior is needed.
RESUMEN
Background: Lifestyle support is essential in preventing and treating cardiovascular diseases (CVD), and eHealth may be an easy and affordable solution to provide this support. However, CVD patients vary in their ability and interest to use eHealth. This study investigates demographic characteristics determining CVD patients' online and offline lifestyle support preferences. Methods: We used a cross-sectional study design. 659 CVD patients (Harteraad panel) completed our questionnaire. We assessed demographic characteristics and preferred lifestyle support type (coach, eHealth, family/friends, self-supportive). Results: Respondents mostly preferred being self-supportive (n = 179, 27.2%), and a coach in a group or individually (n = 145, 22.0%; n = 139, 21.1%). An app/internet to work independently (n = 89, 13.5%) or being in touch with other CVD patients (n = 44, 6.7%) was least preferred. Men were more likely to prefer being supported by family/friends (p = .016) or self-supportive (p < .001), while women preferred a coach individually or via an app/internet (p < .001). Older patients mostly preferred self-support (p = .001). Patients with low social support were more likely to prefer being coached individually (p < .001), but not support from family/friends (p = .002). Conclusion: Men and older patients are more interested in being self-supportive, and patients with lower levels of social support could need extra support outside their social network. eHealth could provide a solution, but attention should be paid to spike interest for digital interventions among certain groups.