Brief lifestyle advice in cardiac care: an experimental study on message source and framing.

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 (M = 4.1) and physiotherapist (M = 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] = 7.06, P = 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.

Effectiveness of Human-Supported and Self-Help eHealth Lifestyle Interventions for Patients With Cardiometabolic Risk Factors: A Meta-Analysis.

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 .

An iterative approach to developing a multifaceted implementation strategy for a complex eHealth intervention within clinical practice.

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.

Guide Development for eHealth Interventions Targeting People With a Low Socioeconomic Position: Participatory Design Approach.

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.

The Barriers and Facilitators of eHealth-Based Lifestyle Intervention Programs for People With a Low Socioeconomic Status: Scoping Review.

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.

Investigating Rewards and Deposit Contract Financial Incentives for Physical Activity Behavior Change Using a Smartphone App: Randomized Controlled Trial.

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.

Cost-effectiveness of a stepwise cardiometabolic disease prevention program: results of a randomized controlled trial in primary care.

BACKGROUND: Cardiometabolic diseases (CMD) are the major cause of death worldwide and are associated with a lower quality of life and high healthcare costs. To prevent a further rise in CMD and related healthcare costs, early detection and adequate management of individuals at risk could be an effective preventive strategy. The objective of this study was to determine long-term cost-effectiveness of stepwise CMD risk assessment followed by individualized treatment if indicated compared to care as usual. A computer-based simulation model was used to project long-term health benefits and cost-effectiveness, assuming the prevention program was implemented in Dutch primary care. METHODS: A randomized controlled trial in a primary care setting in which 1934 participants aged 45-70 years without recorded CMD or CMD risk factors participated. The intervention group was invited for stepwise CMD risk assessment through a risk score (step 1), additional risk assessment at the practice in case of increased risk (step 2) and individualized follow-up treatment if indicated (step 3). The control group was not invited for risk assessment, but completed a health questionnaire. Results of the effectiveness analysis on systolic blood pressure (- 2.26 mmHg; 95% CI - 4.01: - 0.51) and total cholesterol (- 0.15 mmol/l; 95% CI - 0.23: - 0.07) were used in this analysis. Outcome measures were the costs and benefits after 1-year follow-up and long-term (60 years) cost-effectiveness of stepwise CMD risk assessment compared to no assessment. A computer-based simulation model was used that included data on disability weights associated with age and disease outcomes related to CMD. Analyses were performed taking a healthcare perspective. RESULTS: After 1 year, the average costs in the intervention group were 260 Euro higher than in the control group and differences were mainly driven by healthcare costs. No meaningful change was found in EQ 5D-based quality of life between the intervention and control groups after 1-year follow-up (- 0.0154; 95% CI - 0.029: 0.004). After 60 years, cumulative costs of the intervention were 41.4 million Euro and 135 quality-adjusted life years (QALY) were gained. Despite improvements in blood pressure and cholesterol, the intervention was not cost-effective (ICER of 306,000 Euro/QALY after 60 years). Scenario analyses did not allow for a change in conclusions with regard to cost-effectiveness of the intervention. CONCLUSIONS: Implementation of this primary care-based CMD prevention program is not cost-effective in the long term. Implementation of this program in primary care cannot be recommended. TRIAL REGISTRATION: Dutch Trial Register NTR4277 , registered on 26 November 2013.

Facilitators of and Barriers to Lifestyle Support and eHealth Solutions: Interview Study Among Health Care Professionals Working in Cardiac Care.

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.

Effectiveness of a stepwise cardiometabolic disease prevention program: Results of a randomized controlled trial in primary care.

Effective preventive strategies for cardiometabolic disease (CMD) are needed. We aim to establish the effectiveness of a stepwise CMD risk assessment followed by individualized treatment if indicated compared to care as usual. We conducted a RCT between 2014 and 2017. Individuals (45-70 years) without CMD or CMD risk factors were invited for stepwise CMD risk assessment through a risk score (step1), additional risk assessment at the practice in case of high-risk (step2) and individualized follow-up treatment if indicated (step3). We compared newly detected CMD and newly prescribed drugs during one-year follow-up, and change in CMD risk profile between baseline and one-year follow-up among participants who completed step2 to matched controls. A CMD was diagnosed almost three times more often (OR 2.90, 95% CI 2.25: 3.72) in the intervention compared to the control group, in parallel with newly prescribed antihypertensive and lipid lowering drugs (OR 2.85, 95% CI 1.96: 4.15 and 3.23, 95% CI 2.03: 5.14 respectively). Waist circumference significantly decreased between the intervention compared to the control group (mean -3.08 cm, 95% CI -3.73: -2.43). No differences were observed for changes in BMI and smoking. Systolic blood pressure (mean -2.26 mmHg, 95% CI -4.01: -0.51) and cholesterol ratio (mean -0.11, 95% CI -0.19: -0.02) significantly decreased within intervention participants between baseline and one-year follow-up. In conclusion, implementation of the CMD prevention program resulted in the detection of two- to threefold more patients with CMD. A significant drop in systolic blood pressure and cholesterol levels was found after one year of treatment. Modelling of these results should confirm the effect on long term endpoints. Trial registration: Dutch trial Register number NTR4277.

Feasibility and success rates of response enhancing strategies in a stepwise prevention program for cardiometabolic diseases in primary care.

BACKGROUND: Prevention programs for cardiometabolic diseases (CMD), including cardiovascular disease, diabetes mellitus and chronic kidney disease are feasible, but evidence for the cost-effectiveness of selective CMD prevention programs is lacking. Response rates have an important role in effectiveness, but methods to increase response rates have received insufficient attention. The aim of the current study is to determine the feasibility and the success rate of a variety of response enhancing strategies to increase the participation in a selective prevention program for CMD. METHODS: The INTEGRATE study is a Dutch randomised controlled trial to assess the effectiveness and cost-effectiveness of a stepwise program for CMD prevention. During the INTEGRATE study we developed ten different response enhancing strategies targeted at different stages of non-response and different patient populations and evaluated these in 29 general practices. RESULTS: A face-to-face reminder by the GP increased the response significantly. Digital reminders targeted at patients with an increased CMD risk showed a positive trend towards participation. Sending invitations and reminders by e-mail generated similar response rates, but at lower costs and time investment than the standard way of dissemination. Translated materials, information gatherings at the practice, self-management toolkits, reminders by telephone, information letters, local media attention and SMS text reminders did not increase the response to our program. CONCLUSIONS: Inviting or reminding patients by e-mail or during GPs consultation may enhance response rates in a selective prevention program for CMD. Different response-enhancing strategies have different patient target populations and implementation issues, therefore practice characteristics need to be taken into account when implementing such strategies. TRIAL REGISTRATION: Dutch trial Register number NTR4277 . Registered 26 November 2013.

Effectiveness of the blended-care lifestyle intervention 'PerfectFit': a cluster randomised trial in employees at risk for cardiovascular diseases.

BACKGROUND: Web-based lifestyle interventions at the workplace have the potential to promote health and work productivity. However, the sustainability of effects is often small, which could be enhanced by adding face-to-face contacts, so-called 'blended care'. Therefore, this study evaluates the effects of a blended workplace health promotion intervention on health and work outcomes among employees with increased cardiovascular risk. METHODS: In this multicentre cluster-randomised controlled trial (PerfectFit), 491 workers in 18 work units from military, police, and a hospital with increased cardiovascular risk were randomised into two intervention groups. The limited intervention (n = 213; 9 clusters) consisted of a web-based Health Risk Assessment with advice. In the extensive intervention (n = 271; 8 clusters), coaching sessions by occupational health physicians using motivational interviewing were added. One cluster dropped out after randomisation but before any inclusion of subjects. Primary outcome was self-rated health. Secondary outcomes were body weight, body mass index (BMI), work productivity, and health behaviours. Follow-up measurements were collected at 6 and 12 months. Effect sizes were determined in mixed effects models. RESULTS: At 12 months, the extensive intervention was not statistically different from the limited intervention for self-rated health (4.3%; 95%CI -5.3-12.8), BMI (- 0.81; 95%CI -1.87-0.26) and body weight (- 2.16; 95%CI -5.49-1.17). The within-group analysis showed that in the extensive intervention group body weight (- 3.1 kg; 95% CI -2.0 to - 4.3) was statistically significantly reduced, whereas body weight remained stable in the limited intervention group (+ 0.2 kg; 95% CI -1.4 to 1.8). In both randomised groups productivity loss and physical activity increased and excessive alcohol use decreased significantly at 12 months. CONCLUSIONS: There were no effects on self-rated health, body weight, and BMI. However, within the group with web-based tailored Health Risk Assessment including personalized advice body weight reduced significantly. Adding motivational coaching is promising to reduce body weight. TRIAL REGISTRATION: Retrospectively registered at the Netherlands Trial Registry with number NTR4894 , at Nov 14 2014.

Cardiac rehabilitation and survival in a large representative community cohort of Dutch patients.

AIMS: To assess the effects of multi-disciplinary cardiac rehabilitation (CR) on survival in the full population of patients with an acute coronary syndrome (ACS) and patients that underwent coronary revascularization and/or heart valve surgery. METHODS AND RESULTS: Population-based cohort study in the Netherlands using insurance claims database covering ∼22% of the Dutch population (3.3 million persons). All patients with an ACS with or without ST elevation, and patients who underwent coronary revascularization and/or valve surgery in the period 2007-10 were included. Patients were categorized as having received CR when an insurance claim for CR was made within the first 180 days after the cardiac event or revascularization. The primary outcome was survival time from the inclusion date, limited to a total follow-up period of 4 years, with a minimum of 180 days. Propensity score weighting was used to control for confounding by indication. Among 35 919 patients with an ACS and/or coronary revascularization or valve surgery, 11 014 (30.7%) received CR. After propensity score weighting, the adjusted hazard ratio (HR) associated with receiving CR was 0.65 (95% CI 0.56-0.77). The largest benefit was observed for patients who underwent coronary artery bypass grafting (CABG) and/or valve surgery (HR = 0.55, 95% CI 0.42-0.74). CONCLUSION: In a large and representative community cohort of Dutch patients with an ACS and/or intervention, CR was associated with a substantial survival benefit up to 4 years. This survival benefit was present regardless of age, type of diagnosis, and type of intervention.

A six question screen to facilitate primary cardiovascular disease prevention.

BACKGROUND: European guidelines on primary prevention of cardiovascular disease (CVD) recommend the SCORE risk charts for determining CVD risk, which include blood pressure and serum cholesterol as risk parameters. To facilitate cost-effective large-scale screening, we aimed to construct a risk score with 'non-invasive' parameters as a first screening step to identify persons at increased CVD risk requiring further risk assessment. METHODS: We used data of Dutch employees from 25 organisations participating in a health risk assessment between August 2007 and January 2013. Backward multivariate logistic regression analysis was employed to select non-invasive, independent predictors of high CVD risk, defined as the 10-year risk of fatal CVD of ≥5 % based on the SCORE formula. The total CVD risk score was calculated as the summed coefficients of the retained variables. RESULTS: Data of 6189 male participants was used for the development and validation of the risk score. Age, tobacco use, history of hypertension, alcohol consumption, BMI, and waist circumference were independent predictors of high CVD risk. Ten-fold cross-validation resulted in an area under the curve of 0.95 (SE 0.01, 95 % confidence interval 0.94-0.96). A cut-off score ≥45 on the CVD risk score yielded a sensitivity of 0.93, and a specificity of 0.85. CONCLUSIONS: We developed a simple, non-invasive risk score that accurately identifies persons at increased CVD risk according to the SCORE formula in a population of working men. The risk score enables a stepwise approach in large screening programmes, strongly reducing the number of persons that require full risk estimation including blood pressure and cholesterol measures.

Combining risk factors with faecal immunochemical test outcome for selecting CRC screenees for colonoscopy.

OBJECTIVE: Faecal immunochemical testing (FIT) is increasingly used in colorectal cancer (CRC) screening but has a less than perfect sensitivity. Combining risk stratification, based on established risk factors for advanced neoplasia, with the FIT result for allocating screenees to colonoscopy could increase the sensitivity and diagnostic yield of FIT-based screening. We explored the use of a risk prediction model in CRC screening. DESIGN: We collected data in the colonoscopy arm of the Colonoscopy or Colonography for Screening study, a multicentre screening trial. For this study 6600 randomly selected, asymptomatic men and women between 50 years and 75 years of age were invited to undergo colonoscopy. Screening participants were asked for one sample FIT (OC-sensor) and to complete a risk questionnaire prior to colonoscopy. Based on the questionnaire data and the FIT results, we developed a multivariable risk model with the following factors: total calcium intake, family history, age and FIT result. We evaluated goodness-of-fit, calibration and discrimination, and compared it with a model based on primary screening with FIT only. RESULTS: Of the 1426 screening participants, 1112 (78%) completed the questionnaire and FIT. Of these, 101 (9.1%) had advanced neoplasia. The risk based model significantly increased the goodness-of-fit compared with a model based on FIT only (p<0.001). Discrimination improved significantly with the risk-based model (area under the receiver operating characteristic (ROC) curve: from 0.69 to 0.76, (p=0.02)). Calibration was good (Hosmer-Lemeshow test; p=0.94). By offering colonoscopy to the 102 patients at highest risk, rather than to the 102 cases with a FIT result >50 ng/mL, 5 more cases of advanced neoplasia would be detected (net reclassification improvement 0.054, p=0.073). CONCLUSIONS: Adding risk based stratification increases the accuracy FIT-based CRC screening and could be used in preselection for colonoscopy in CRC screening programmes.

Home blood pressure measurement as a screening tool for hypertension in a web-based worksite health promotion programme.

BACKGROUND: Guidelines on home blood pressure measurement (HBPM) recommend taking at least 12 measurements. For screening purposes, however, it is preferred to reduce this number. We therefore derived and validated cut-off values to determine hypertension status after the first duplicate reading of a HBPM series in a web-based worksite health promotion programme. METHOD: Nine hundred forty-five employees were included in the derivation and 528 in the validation cohort, which was divided into a normal (n = 297) and increased cardiometabolic risk subgroup (n = 231), and a subgroup with a history of hypertension (n = 98). Six duplicate home measurements were collected during three consecutive days. Systolic and diastolic readings at the first duplicate measurement were used as predictors for hypertension in a multivariate logistic model. Cut-off values were determined using receiver operating characteristics analysis. RESULTS: Upper (≥ 150 or ≥ 95 mmHg) and lower limit (<135 and <80 mmHg) cut-off values were derived to confirm or reject presence of hypertension after one duplicate reading. The area under the curve was 0.94 (standard error 0.01, 95% confidence interval 0.93-0.95). In 62.5% of participants, hypertension status was determined, with 1.1% false positive and 4.7% false negatives. Performance was similar in participants with high and low cardiometabolic risk, but worse in participants with a history of hypertension (10.4% false negatives). CONCLUSION: One duplicate home reading is sufficient to accurately assess hypertension status in 62.5% of participants, leaving 37.5% in which the whole HBPM series needs to be completed. HBPM can thus be reliably used as screening tool for hypertension in a working population.

Design of the INTEGRATE study: effectiveness and cost-effectiveness of a cardiometabolic risk assessment and treatment program integrated in primary care.

BACKGROUND: The increasing prevalence of cardiometabolic disease (CMD) in combination with an ageing population is a major public health problem. Early detection and management of individuals at risk for CMD is required to prevent future health problems with associated costs. General practice is the optimal health care setting to accomplish this goal. Prevention programs for identification and treatment of patients with an increased risk for CMD in primary care have been proven feasible. However, the effectiveness and cost-effectiveness have yet to be demonstrated. The 'Personalized Prevention Approach for CardioMetabolic Risk' (PPA CMR) is such a prevention program. The objective of the INTEGRATE study is to investigate the effectiveness and cost-effectiveness of PPA CMR, as well as to establish determinants for participation and compliance. METHODS: The INTEGRATE study is designed as a stepped-wedge randomized controlled trial with a waiting list control group. In approximately 40 general practices, all enlisted patients without CMD aged 45-70 years, are invited to participate in PPA CMR. After an online risk estimation, patients with a score above risk threshold are invited to the GP for additional measurements, detailed risk profiling and tailored treatment of risk factors through medication and/or lifestyle counseling. At baseline and after twelve months of follow-up lifestyle, health and work status of all participants are established with online questionnaires. Additionally after twelve months, we will determine health care utilization, costs of PPA CMR and compliance. Primary endpoints are the number of newly detected patients with CMD and changes in individual risk factors between the intervention and waiting list control group. Medical data will be extracted from the GPs' electronic medical records. In order to assess factors related to participation, we will send questionnaires to non-participants and assess characteristics of participating practices. For all participants, additional demographic characteristics will be available through Statistics Netherlands. DISCUSSION: The INTEGRATE study will provide insight into the effectiveness and cost-effectiveness of PPA CMR as well as determinants for participation and compliance, which represents essential information to guide further large-scale implementation of primary prevention programs for CMD. TRIAL REGISTRATION NUMBER: NTR4277, The Netherlands National Trial Register, 26-11-2013.

Evaluating a web-based health risk assessment with tailored feedback: what does an expert focus group yield compared to a web-based end-user survey?

BACKGROUND: Increasingly, Web-based health applications are developed for the prevention and management of chronic diseases. However, their reach and utilization is often disappointing. Qualitative evaluations post-implementation can be used to inform the optimization process and ultimately enhance their adoption. In current practice, such evaluations are mainly performed with end-user surveys. However, a review approach by experts in a focus group may be easier to administer and might provide similar results. OBJECTIVE: The aim of this study was to assess whether industrial design engineers in a focus group would address the same issues as end users in a Web-based survey when evaluating a commercial Web-based health risk assessment (HRA) with tailored feedback. METHODS: Seven Dutch companies used the HRA as part of their corporate health management strategy. Employees using the HRA (N=2289) and 10 independent industrial designers were invited to participate in the study. The HRA consisted of four components: (1) an electronic health questionnaire, (2) biometric measurements, (3) laboratory evaluation, and (4) individually tailored feedback generated by decision support software. After participating in the HRA as end users, both end users and designers evaluated the program. End users completed an evaluation questionnaire that included a free-text field. Designers participated in a focus group discussion. Constructs from user satisfaction and technology acceptance theories were used to categorize and compare the remarks from both evaluations. RESULTS: We assessed and qualitatively analyzed 294 remarks of 189 end users and 337 remarks of 6 industrial designers, pertaining to 295 issues in total. Of those, 137 issues were addressed in the end-user survey and 148 issues in the designer focus group. Only 7.3% (10/137) of the issues addressed in the survey were also addressed in the focus group. End users made more remarks about the usefulness of the HRA and prior expectations that were not met. Designers made more remarks about how the information was presented to end users, quality of the feedback provided by the HRA, recommendations on the marketing and on how to create more unity in the design of the HRA, and on how to improve the HRA based on these issues. CONCLUSIONS: End-user surveys should not be substituted for expert focus groups. Issues identified by end users in the survey and designers in the focus group differed considerably, and the focus group produced a lot of new issues. The issues addressed in the focus group often focused on different aspects of user satisfaction and technology acceptance than those addressed by the survey participants; when they did focus on the same aspects, then the nature of issues differed considerably in content.

Use Intention and User Expectations of Human-Supported and Self-Help eHealth Interventions: Internet-Based Randomized Controlled Trial.

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.

Less stick more carrot? Increasing the uptake of deposit contract financial incentives for physical activity: A randomized controlled trial.

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.

Human cues in eHealth to promote lifestyle change: An experimental field study to examine adherence to self-help interventions.

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.