The first part of this research section defines healthy behaviour in the workplace and explains the mechanisms of behavioural change through interior design. The second part discusses the available evidence on the health impact of workplace design elements, such as furniture, layout, and visual prompts. It concludes with an overview of current knowledge on promoting healthy behaviours at the office.@en

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.@en

People with a physically demanding job have an unhealthy disbalance in occupational and leisure-time physical activity (PA). We aimed to understand which contextual factors influence this disbalance, and explore opportunities for lifestyle interventions that could restore this disbalance. We applied a contextmapping study with six production workers from a Dutch coating department. Participants filled in a sensitizing booklet with PA-related activities, and were interviewed afterwards. Participants reported reasons for (not) being active in leisure-time using an experience sampling method. Our results indicate that main reasons for being inactive during leisure time were their believes that occupational PA is enough for a healthy lifestyle, and the need to rest after work. Results show that lifestyle interventions should tackle workers inadequate risk perception and over-exhaustion to empower them to shift their PA behavior in a healthier direction. This indicates the need for a holistic approach targeting both home and working environments.

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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. @en

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. @en

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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Background: Atrial fibrillation is commonly associated with obesity. Observational studies have shown that weight loss is associated with improved prognosis and a decrease in atrial fibrillation frequency and severity. However, despite these benefits, nonadherence to lifestyle programs is common. Objective: In this study, we evaluated adherence to and feasibility of a multidisciplinary lifestyle program focusing on behavior change in patients with atrial fibrillation and obesity. Methods: Patients with atrial fibrillation and obesity participated in a 1-year goal-oriented cardiac rehabilitation program. After baseline assessment, the first 3 months included a cardiac rehabilitation intervention with 4 fixed modules: lifestyle counseling (with an advanced nurse practitioner), exercise training, dietary consultation, and psychosocial therapy; relaxation sessions were an additional optional treatment module. An advanced nurse practitioner monitored the personal lifestyle of each individual patient, with assessments and consultations at 3 months (ie, immediately after the intervention) and at the end of the year (ie, 9 months after the intervention). At each timepoint, level of physical activity, personal goals and progress, atrial fibrillation symptoms and frequency (Atrial Fibrillation Severity Scale), psychosocial stress (Generalized Anxiety Disorder-7), and depression (Patient Health Questionnaire-9) were assessed. The primary endpoints were adherence (defined as the number of visits attended as percentage of the number of planned visits) and completion rates of the cardiac rehabilitation intervention (defined as performing at least of 80% of the prescribed sessions). In addition, we performed an exploratory analysis of effects of the cardiac rehabilitation program on weight and atrial fibrillation symptom frequency and severity. Results: Patients with atrial fibrillation and obesity (male: n=8; female: n=2; age: mean 57.2 years, SD 9.0; baseline weight: mean 107.2 kg, SD 11.8; baseline BMI: mean 32.4 kg/m2, SD 3.5) were recruited. Of the 10 participants, 8 participants completed the 3-month cardiac rehabilitation intervention, and 2 participants did not complete the cardiac rehabilitation intervention (both because of personal issues). Adherence to the fixed treatment modules was 95% (mean 3.8 sessions attended out of mean 4 planned) for lifestyle counseling, 86% (mean 15.2 sessions attended out of mean 17.6 planned) for physiotherapy sessions, 88% (mean 3.7 sessions attended out of mean 4.1 planned) for dietician consultations, and 60% (mean 0.6 sessions attended out of mean 1.0 planned) for psychosocial therapy; 70% of participants (7/10) were referred to the optional relaxation sessions, for which adherence was 86% (mean 2 sessions attended out of mean 2.4 planned). The frequency of atrial fibrillation symptoms was reduced immediately after the intervention (before: mean 35.6, SD 3.8; after: mean 31.2, SD 3.3), and this was sustained at 12 months (mean 24.8, SD 3.2). The severity of atrial fibrillation complaints immediately after the intervention (mean 20.0, SD 3.7) and at 12 months (mean 9.3, SD 3.6) were comparable to that at baseline (mean 16.6, SD 3.3). Conclusions: A 1-year multidisciplinary lifestyle program for obese patients with atrial fibrillation was found to be feasible, with high adherence and completion rates. Exploratory analysis revealed a sustained reduction in atrial fibrillation symptoms; however, these results remain to be confirmed in large-scale studies.@en

Changing a specific health behaviour can be highly com- plex and is often influenced by many personal, social, and environmental factors. Therefore, interventions that aim at behaviour change cannot be one-size-fits-all solutions, and no behaviour change technique is effective for everyone. One potential solution could be to support individuals in finding interventions through self-experimentation. This research explored the requirements for an explorative self- experimentation intervention and developed tools that sup- port users in the process, complementing developments in quantitative self-experimentation. Based on a research through design approach, we developed three different prototypes for supporting a change in health-related behaviour, which were used and evaluated by fourteen par- ticipants over a four-week period. A thematic analysis of interviews with participants led to seven themes, which can be used as a starting point when designing for explorative self-experimentation.@en

Importance: Cardiac telerehabilitation (CTR) has been found to be a safe and beneficial alternative to traditional center-based cardiac rehabilitation (CR) and might be associated with higher participation rates by reducing barriers to CR use. However, implementation of CTR interventions remains low, which may be owing to a lack of cost-effectiveness analyses of data from large-scale randomized clinical trials. Objective: To assess the cost-effectiveness of CTR with relapse prevention compared with center-based CR among patients with coronary artery disease. Design, Setting, and Participants: This economic evaluation performed a cost-utility analysis of data from the SmartCare-CAD (Effects of Cardiac Telerehabilitation in Patients With Coronary Artery Disease Using a Personalized Patient-Centred ICT Platform) randomized clinical trial. The cost-effectiveness and utility of 3 months of cardiac telerehabilitation followed by 9 months of relapse prevention were compared with the cost-effectiveness of traditional center-based cardiac rehabilitation. The analysis included 300 patients with stable coronary artery disease who received care at a CR center serving 2 general hospitals in the Netherlands between May 23, 2016, and July 26, 2018. All patients were entering phase 2 of outpatient CR and were followed up for 1 year (until August 14, 2019). Data were analyzed from September 21, 2020, to September 24, 2021. Intervention: After baseline measurements were obtained, participants were randomly assigned on a 1:1 ratio to receive CTR (intervention group) or center-based CR (control group) using computerized block randomization. After 6 supervised center-based training sessions, patients in the intervention group continued training at home using a heart rate monitor and accelerometer. Patients uploaded heart rate and physical activity data and discussed their progress during a weekly video consultation with their physical therapist. After 3 months, weekly coaching was concluded, and on-demand coaching was initiated for relapse prevention; patients were instructed to continue using their wearable sensors and were contacted in cases of nonadherence to the intervention or reduced exercise or physical activity volumes. Main Outcomes and Measures: Quality-adjusted life-years were assessed using the EuroQol 5-Dimension 5-Level survey (EQ-5D-5L) and the EuroQol Visual Analogue Scale (EQ-VAS), and cardiac-associated health care costs and non-health care costs were measured by health care consumption, productivity, and informal care questionnaires (the Medical Consumption Questionnaire, the Productivity Cost Questionnaire, and the Valuation of Informal Care Questionnaire) designed by the Institute for Medical Technology Assessment. Costs were converted to 2020 price levels (in euros) using the Dutch consumer price index (to convert to US dollars, euro values were multiplied by 1.142, which was the mean exchange rate in 2020). Results: Among 300 patients (266 men [88.7%]), the mean (SD) age was 60.7 (9.5) years. The quality of life among patients receiving CTR vs center-based CR was comparable during the study according to the results of both utility measures (mean difference on EQ-5D-5L: -0.004; P =.82; mean difference on EQ-VAS: -0.001; P =.92). Intervention costs were significantly higher for CTR (mean [SE], 224 [4] [$256 ($4)]) compared with center-based CR (mean [SE], 156 [5] [$178 ($6)]; P <.001); however, no difference in overall cardiac health care costs was observed between CTR (mean [SE], 4787 [503] [$5467 ($574)] and center-based CR (mean [SE], 5507 [659] [$6289 ($753)]; P =.36). From a societal perspective, CTR was associated with lower costs compared with center-based CR (mean [SE], 20 495 [ 2751] [$23 405 ($3142)] vs 24 381 [3613] [$27 843 ($4126)], respectively), although this difference was not statistically significant (-3887 [-$4439]; P =.34). Conclusions and Relevance: In this economic evaluation, a CTR intervention with relapse prevention was likely to be cost-effective compared with center-based CR, suggesting that CTR maybe used as an alternative intervention for the treatment of patients with coronary artery disease. These results add to the evidence base in favor of CTR and may increase the implementation of CTR interventions in clinical practice..

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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.@en

BackgroundMost studies failed to show superiority of cardiac telerehabilitation (CTR) over traditional, centre-based cardiac rehabilitation (CR).PurposeTo evaluate the effectiveness of a novel CTR intervention on the adherence to a physically active lifestyle in patients with coronary artery disease (CAD).MethodsWe randomised patients with CAD entering phase II outpatient CR to either CTR with relapse prevention by on-demand coaching (intervention group), or centre-based CR with supervised exercise training (control group). The primary outcome measure was objectively assessed physical activity level (PAL), secondary outcome measures included physical fitness and quality of life (QoL).ResultsA total of 300 patients (89% male, mean age 60.7 ± 9.5 years) participated in the trial. Both groups significantly improved their PAL at 12 months follow-up (p < 0.01), but without a significant between-group difference in the response over time (p = 0.73). Similarly, we observed sustained increases in physical fitness and QoL, but without significant between-group differences in responses over time.ConclusionsIn patients with CAD who had low residual cardiovascular risk, CTR with relapse prevention resulted in a sustained increase in PAL, physical fitness and QoL, but without differences in responses over time as compared to centre-based CR. For this reason, future CTR interventions should be directed specifically to patients who are at risk for relapse into unhealthy lifestyle behaviour.@en

Background: Despite proven clinical benefits, only a minority of patients complete outpatient cardiac rehabilitation (CR) after acute myocardial infarction (AMI). The main purpose of this study was to evaluate to what extent and at which time patients drop out of CR, and to assess which patient-related characteristics can predict dropout. Methods: In a retrospective cohort study, we selected patients who had been hospitalised with an AMI in our centre in 2015 or 2016. Patients were selected pseudonymously based on reimbursement codes in the electronic health record. We extracted baseline characteristics and data on CR referral, enrolment and completion for each patient. Multivariable logistic regression was used to assess which characteristics predicted referral and dropout. Results: The 666 patients included were predominantly male (66%), with a mean age of 69.0 years. Of the 640 eligible patients, 201 (31%) were not referred for CR. Enrolment after referral was 94%. Nonreferral was independently associated with older age, female sex, traveling distance, non-ST-elevation myocardial infarction (NSTEMI; as compared with STEMI), no coronary revascularisation and prior manifestations of coronary artery disease. Of the 414 enrolled patients, 24% did not complete their CR programmes (i.e. dropped out). Older age and worse exercise capacity at baseline were independently associated with dropout. The ability of the multiple regression models to predict nonreferral and noncompletion was good to fair, with an area under the receiver operating characteristic curves of 0.86 and 0.71, respectively. Conclusion: The main reason for not participating in or not completing CR after AMI was nonreferral. To optimise CR utilisation, improvement of referral rates should be prioritised.

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Background: Chronic heart failure (CHF) and chronic obstructive pulmonary disease (COPD) often coexist and are associated with a high morbidity and reduced quality of life (QoL). Although these diseases share similarities in symptoms and clinical course, and exacerbations of both diseases often overlap, care pathways for both conditions are usually not integrated. This results in frequent outpatient consultations and suboptimal treatment during exacerbations, leading to frequent hospital admissions. Therefore, we propose an integrated care pathway for both diseases, using telemonitoring to detect deterioration at an early stage and a single case manager for both diseases.

Objective: This study aims to investigate whether an integrated care pathway using telemonitoring in patients with combined CHF and COPD results in a higher general health-related QoL (HRQoL) as compared with the traditional care pathways. Secondary end points include disease-specific HRQoL, level of self-management, patient satisfaction, compliance to the program, and cost-effectiveness.

Methods: This is a monocenter, prospective study using a quasi-experimental interrupted time series design. Thirty patients with combined CHF and COPD are included. The study period of 2.5 years per patient is divided into a preintervention phase (6 months) and a postintervention phase (2 years) in which end points are assessed. The intervention consists of an on-demand treatment strategy based on monitoring symptoms related to CHF/COPD and vital parameters (weight, blood pressure, heart rate, oxygen saturation, temperature), which are uploaded on a digital platform. The monitoring frequency and the limit values of the measurements to detect abnormalities are determined individually. Monitoring is performed by a case manager, who has the opportunity for a daily multidisciplinary meeting with both the cardiologist and the pulmonologist. Routine appointments at the outpatient clinic are cancelled and replaced by telemonitoring-guided treatment.

Results: Following ethical approval of the study protocol, the first patient was included in May 2018. Inclusion is expected to be complete in May 2021.

Conclusions: This study is the first to evaluate the effects of a novel integrated care pathway using telemonitoring for patients with combined CHF and COPD. Unique to this study is the concept of remote on-demand disease management by a single case manager for both diseases, combined with multidisciplinary meetings. Moreover, modern telemonitoring technology is used instead of, rather than as an addition to, regular care.

Trial Registration: Netherlands Trial Register NL6741; https://www.trialregister.nl/trial/6741

International Registered Report Identifier (IRRID): DERR1-10.2196/20571@en

BACKGROUND:Improving physical activity (PA) is a core component of secondary prevention and cardiac (tele)rehabilitation. Commercially available activity trackers are frequently used to monitor and promote PA in cardiac patients. However, studies on the validity of these devices in cardiac patients are scarce. As cardiac patients are being advised and treated based on PA parameters measured by these devices, it is highly important to evaluate the accuracy of these parameters in this specific population. OBJECTIVE:The aim of this study was to determine the accuracy and responsiveness of 2 wrist-worn activity trackers, Fitbit Charge 2 (FC2) and Mio Slice (MS), for the assessment of energy expenditure (EE) in cardiac patients. METHODS:EE assessed by the activity trackers was compared with indirect calorimetry (Oxycon Mobile [OM]) during a laboratory activity protocol. Two groups were assessed: patients with stable coronary artery disease (CAD) with preserved left ventricular ejection fraction (LVEF) and patients with heart failure with reduced ejection fraction (HFrEF). RESULTS:A total of 38 patients were included: 19 with CAD and 19 with HFrEF (LVEF 31.8%, SD 7.6%). The CAD group showed no significant difference in total EE between FC2 and OM (47.5 kcal, SD 112 kcal; P=.09), in contrast to a significant difference between MS and OM (88 kcal, SD 108 kcal; P=.003). The HFrEF group showed significant differences in EE between FC2 and OM (38 kcal, SD 57 kcal; P=.01), as well as between MS and OM (106 kcal, SD 167 kcal; P=.02). Agreement of the activity trackers was low in both groups (CAD: intraclass correlation coefficient [ICC] FC2=0.10, ICC MS=0.12; HFrEF: ICC FC2=0.42, ICC MS=0.11). The responsiveness of FC2 was poor, whereas MS was able to detect changes in cycling loads only. CONCLUSIONS:Both activity trackers demonstrated low accuracy in estimating EE in cardiac patients and poor performance to detect within-patient changes in the low-to-moderate exercise intensity domain. Although the use of activity trackers in cardiac patients is promising and could enhance daily exercise behavior, these findings highlight the need for population-specific devices and algorithms.@en