Saskia Marion Kelders

Persuasive System Design Does Matter: A Systematic Review of Adherence to Web-Based Interventions

Background Although web-based interventions for promoting health and health-related behavior can be effective, poor adherence is a common issue that needs to be addressed. Technology as a means to communicate the content in web-based interventions has been neglected in research. Indeed, technology is often seen as a black-box, a mere tool that has no effect or value and serves only as a vehicle to deliver intervention content. In this paper we examine technology from a holistic perspective. We see it as a vital and inseparable aspect of web-based interventions to help explain and understand adherence. Objective This study aims to review the literature on web-based health interventions to investigate whether intervention characteristics and persuasive design affect adherence to a web-based intervention. Methods We conducted a systematic review of studies into web-based health interventions. Per intervention, intervention characteristics, persuasive technology elements and adherence were coded. We performed a multiple regression analysis to investigate whether these variables could predict adherence. Results We included 101 articles on 83 interventions. The typical web-based intervention is meant to be used once a week, is modular in set-up, is updated once a week, lasts for 10 weeks, includes interaction with the system and a counselor and peers on the web, includes some persuasive technology elements, and about 50% of the participants adhere to the intervention. Regarding persuasive technology, we see that primary task support elements are most commonly employed (mean 2.9 out of a possible 7.0). Dialogue support and social support are less commonly employed (mean 1.5 and 1.2 out of a possible 7.0, respectively). When comparing the interventions of the different health care areas, we find significant differences in intended usage (p = .004), setup (p < .001), updates (p < .001), frequency of interaction with a counselor (p < .001), the system (p = .003) and peers (p = .017), duration (F = 6.068, p = .004), adherence (F = 4.833, p = .010) and the number of primary task support elements (F = 5.631, p = .005). Our final regression model explained 55% of the variance in adherence. In this model, a RCT study as opposed to an observational study, increased interaction with a counselor, more frequent intended usage, more frequent updates and more extensive employment of dialogue support significantly predicted better adherence. Conclusions Using intervention characteristics and persuasive technology elements, a substantial amount of variance in adherence can be explained. Although there are differences between health care areas on intervention characteristics, health care area per se does not predict adherence. Rather, the differences in technology and interaction predict adherence. The results of this study can be used to make an informed decision about how to design a web-based intervention to which patients are more likely to adhere.

A Holistic Framework to Improve the Uptake and Impact of eHealth Technologies

Background Many eHealth technologies are not successful in realizing sustainable innovations in health care practices. One of the reasons for this is that the current development of eHealth technology often disregards the interdependencies between technology, human characteristics, and the socioeconomic environment, resulting in technology that has a low impact in health care practices. To overcome the hurdles with eHealth design and implementation, a new, holistic approach to the development of eHealth technologies is needed, one that takes into account the complexity of health care and the rituals and habits of patients and other stakeholders. Objective The aim of this viewpoint paper is to improve the uptake and impact of eHealth technologies by advocating a holistic approach toward their development and eventual integration in the health sector. Methods To identify the potential and limitations of current eHealth frameworks (1999–2009), we carried out a literature search in the following electronic databases: PubMed, ScienceDirect, Web of Knowledge, PiCarta, and Google Scholar. Of the 60 papers that were identified, 44 were selected for full review. We excluded those papers that did not describe hands-on guidelines or quality criteria for the design, implementation, and evaluation of eHealth technologies (28 papers). From the results retrieved, we identified 16 eHealth frameworks that matched the inclusion criteria. The outcomes were used to posit strategies and principles for a holistic approach toward the development of eHealth technologies; these principles underpin our holistic eHealth framework. Results A total of 16 frameworks qualified for a final analysis, based on their theoretical backgrounds and visions on eHealth, and the strategies and conditions for the research and development of eHealth technologies. Despite their potential, the relationship between the visions on eHealth, proposed strategies, and research methods is obscure, perhaps due to a rather conceptual approach that focuses on the rationale behind the frameworks rather than on practical guidelines. In addition, the Web 2.0 technologies that call for a more stakeholder-driven approach are beyond the scope of current frameworks. To overcome these limitations, we composed a holistic framework based on a participatory development approach, persuasive design techniques, and business modeling. Conclusions To demonstrate the impact of eHealth technologies more effectively, a fresh way of thinking is required about how technology can be used to innovate health care. It also requires new concepts and instruments to develop and implement technologies in practice. The proposed framework serves as an evidence-based roadmap.

Factors Influencing the Use of a Web-Based Application for Supporting the Self-Care of Patients with Type 2 Diabetes: A Longitudinal Study

Background The take-up of eHealth applications in general is still rather low and user attrition is often high. Only limited information is available about the use of eHealth technologies among specific patient groups. Objective The aim of this study was to explore the factors that influence the initial and long-term use of a Web-based application (DiabetesCoach) for supporting the self-care of patients with type 2 diabetes. Methods A mixed-methods research design was used for a process analysis of the actual usage of the Web application over a 2-year period and to identify user profiles. Research instruments included log files, interviews, usability tests, and a survey. Results The DiabetesCoach was predominantly used for interactive features like online monitoring, personal data, and patient–nurse email contact. It was the continuous, personal feedback that particularly appealed to the patients; they felt more closely monitored by their nurse and encouraged to play a more active role in self-managing their disease. Despite the positive outcomes, usage of the Web application was hindered by low enrollment and nonusage attrition. The main barrier to enrollment had to do with a lack of access to the Internet (146/226, 65%). Although 68% (34/50) of the enrollees were continuous users, of whom 32% (16/50) could be defined as hardcore users (highly active), the remaining 32% (16/50) did not continue using the Web application for the full duration of the study period. Barriers to long-term use were primarily due to poor user-friendliness of the Web application (the absence of “push” factors or reminders) and selection of the “wrong” users; the well-regulated patients were not the ones who could benefit the most from system use because of a ceiling effect. Patients with a greater need for care seemed to be more engaged in long-term use; highly active users were significantly more often medication users than low/inactive users (P = .005) and had a longer diabetes duration (P = .03). Conclusion Innovations in health care will diffuse more rapidly when technology is employed that is simple to use and has applicable components for interactivity. This would foresee the patients’ need for continuous and personalized feedback, in particular for patients with a greater need for care. From this study several factors appear to influence increased use of eHealth technologies: (1) avoiding selective enrollment, (2) making use of participatory design methods, and (3) developing push factors for persistence. Further research should focus on the causal relationship between using the system’s features and actual usage, as such a view would provide important evidence on how specific technology features can engage and captivate users.

Effectiveness of a Web-based Intervention Aimed at Healthy Dietary and Physical Activity Behavior: A Randomized Controlled Trial About Users and Usage

Background Recent studies have shown the potential of Web-based interventions for changing dietary and physical activity (PA) behavior. However, the pathways of these changes are not clear. In addition, nonusage poses a threat to these interventions. Little is known of characteristics of participants that predict usage. Objective In this study we investigated the users and effect of the Healthy Weight Assistant (HWA), a Web-based intervention aimed at healthy dietary and PA behavior. We investigated the value of a proposed framework (including social and economic factors, condition-related factors, patient-related factors, reasons for use, and satisfaction) to predict which participants are users and which participants are nonusers. Additionally, we investigated the effectiveness of the HWA on the primary outcomes, self-reported dietary and physical activity behavior. Methods Our design was a two-armed randomized controlled trial that compared the HWA with a waiting list control condition. A total of 150 participants were allocated to the waiting list group, and 147 participants were allocated to the intervention group. Online questionnaires were filled out before the intervention period started and after the intervention period of 12 weeks. After the intervention period, respondents in the waiting list group could use the intervention. Objective usage data was obtained from the application itself. Results In the intervention group, 64% (81/147) of respondents used the HWA at least once and were categorized as “users.” Of these, 49% (40/81) used the application only once. Increased age and not having a chronic condition increased the odds of having used the HWA (age: beta = 0.04, P = .02; chronic condition: beta = 2.24, P = .003). Within the intervention group, users scored better on dietary behavior and on knowledge about healthy behavior than nonusers (self-reported diet: χ2 2 = 8.4, P = .02; knowledge: F1,125 = 4.194, P = .04). Furthermore, users underestimated their behavior more often than nonusers, and nonusers overestimated their behavior more often than users (insight into dietary behavior: χ2 2 = 8.2, P = .02). Intention-to-treat analyses showed no meaningful significant effects of the intervention. Exploratory analyses of differences between pretest and posttest scores of users, nonusers, and the control group showed that on dietary behavior only the nonusers significantly improved (effect size r = −.23, P = .03), while on physical activity behavior only the users significantly improved (effect size r = −.17, P = .03). Conclusions Respondents did not use the application as intended. From the proposed framework, a social and economic factor (age) and a condition-related factor (chronic condition) predicted usage. Moreover, users were healthier and more knowledgeable about healthy behavior than nonusers. We found no apparent effects of the intervention, although exploratory analyses showed that choosing to use or not to use the intervention led to different outcomes. Combined with the differences between groups at baseline, this seems to imply that these groups are truly different and should be treated as separate entities. Trial registration Trial ID number: ISRCTN42687923; http://www.controlled-trials.com/ISRCTN42687923/ (Archived by WebCite at http://www.webcitation.org/5xnGmvQ9Y)

How to Increase Reach and Adherence of Web-Based Interventions: A Design Research Viewpoint

Nowadays, technology is increasingly used to increase people’s well-being. For example, many mobile and Web-based apps have been developed that can support people to become mentally fit or to manage their daily diet. However, analyses of current Web-based interventions show that many systems are only used by a specific group of users (eg, women, highly educated), and that even they often do not persist and drop out as the intervention unfolds. In this paper, we assess the impact of design features of Web-based interventions on reach and adherence and conclude that the power that design can have has not been used to its full potential. We propose looking at design research as a source of inspiration for new (to the field) design approaches. The paper goes on to specify and discuss three of these approaches: personalization, ambient information, and use of metaphors. Central to our viewpoint is the role of positive affect triggered by well-designed persuasive features to boost adherence and well-being. Finally, we discuss the future of persuasive eHealth interventions and suggest avenues for follow-up research.

Development of a web-based intervention for the indicated prevention of depression

BackgroundTo reduce the large public health burden of the high prevalence of depression, preventive interventions targeted at people at risk are essential and can be cost-effective. Web-based interventions are able to provide this care, but there is no agreement on how to best develop these applications and often the technology is seen as a given. This seems to be one of the main reasons that web-based interventions do not reach their full potential. The current study describes the development of a web-based intervention for the indicated prevention of depression, employing the CeHRes (Center for eHealth Research and Disease Management) roadmap. The goals are to create a user-friendly application which fits the values of the stakeholders and to evaluate the process of development.MethodsThe employed methods are a literature scan and discussion in the contextual inquiry; interviews, rapid prototyping and a requirement session in the value specification stage; and user-based usability evaluation, expert-based usability inspection and a requirement session in the design stage.ResultsThe contextual inquiry indicated that there is a need for easily accessible interventions for the indicated prevention of depression and web-based interventions are seen as potentially meeting this need. The value specification stage yielded expected needs of potential participants, comments on the usefulness of the proposed features and comments on two proposed designs of the web-based intervention. The design stage yielded valuable comments on the system, content and service of the web-based intervention.ConclusionsOverall, we found that by developing the technology, we successfully (re)designed the system, content and service of the web-based intervention to match the values of stakeholders. This study has shown the importance of a structured development process of a web-based intervention for the indicated prevention of depression because: (1) it allows the development team to clarify the needs that have to be met for the intervention to be of use to the target audience; and (2) it yields feedback on the design of the application that is broader than color and buttons, but encompasses comments on the quality of the service that the application offers.

Understanding the Usage of Content in a Mental Health Intervention for Depression: An Analysis of Log Data

Background Web-based interventions for the early treatment of depressive symptoms can be considered effective in reducing mental complaints. However, there is a limited understanding of which elements in an intervention contribute to effectiveness. For efficiency and effectiveness of interventions, insight is needed into the use of content and persuasive features. Objective The aims of this study were (1) to illustrate how log data can be used to understand the uptake of the content of a Web-based intervention that is based on the acceptance and commitment therapy (ACT) and (2) to discover how log data can be of value for improving the incorporation of content in Web-based interventions. Methods Data from 206 participants (out of the 239) who started the first nine lessons of the Web-based intervention, Living to the Full, were used for a secondary analysis of a subset of the log data of the parent study about adherence to the intervention. The log files used in this study were per lesson: login, start mindfulness, download mindfulness, view success story, view feedback message, start multimedia, turn on text-message coach, turn off text-message coach, and view text message. Differences in usage between lessons were explored with repeated measures ANOVAs (analysis of variance). Differences between groups were explored with one-way ANOVAs. To explore the possible predictive value of the login per lesson quartiles on the outcome measures, four linear regressions were used with login quartiles as predictor and with the outcome measures (Center for Epidemiologic Studies—Depression [CES-D] and the Hospital Anxiety and Depression Scale—Anxiety [HADS-A] on post-intervention and follow-up) as dependent variables. Results A significant decrease in logins and in the use of content and persuasive features over time was observed. The usage of features varied significantly during the treatment process. The usage of persuasive features increased during the third part of the ACT (commitment to value-based living), which might indicate that at that stage motivational support was relevant. Higher logins over time (9 weeks) corresponded with a higher usage of features (in most cases significant); when predicting depressive symptoms at post-intervention, the linear regression yielded a significant model with login quartile as a significant predictor (explained variance is 2.7%). Conclusions A better integration of content and persuasive features in the design of the intervention and a better intra-usability of features within the system are needed to identify which combination of features works best for whom. Pattern recognition can be used to tailor the intervention based on usage patterns from the earlier lessons and to support the uptake of content essential for therapy. An adaptable interface for a modular composition of therapy features supposes a dynamic approach for Web-based treatment; not a predefined path for all, but a flexible way to go through all features that have to be used.

Participants, Usage, and Use Patterns of a Web-Based Intervention for the Prevention of Depression Within a Randomized Controlled Trial

Background Although Web-based interventions have been shown to be effective, they are not widely implemented in regular care. Nonadherence (ie, participants not following the intervention protocol) is an issue. By studying the way Web-based interventions are used and whether there are differences between adherers (ie, participants that started all 9 lessons) and nonadherers, more insight can be gained into the process of adherence. Objective The aims of this study were to (1) describe the characteristics of participants and investigate their relationship with adherence, (2) investigate the utilization of the different features of the intervention and possible differences between adherers and nonadherers, and (3) identify what use patterns emerge and whether there are differences between adherers and nonadherers. Methods Data were used from 206 participants that used the Web-based intervention Living to the full, a Web-based intervention for the prevention of depression employing both a fully automated and human-supported format. Demographic and baseline characteristics of participants were collected by using an online survey. Log data were collected within the Web-based intervention itself. Both quantitative and qualitative analyses were performed. Results In all, 118 participants fully adhered to the intervention (ie, started all 9 lessons). Participants with an ethnicity other than Dutch were more often adherers (χ2 1=5.5, P=.02), and nonadherers used the Internet more hours per day on average (F1,203=3.918, P=.049). A logistic regression showed that being female (OR 2.02, 95% CI 1.01-4.04; P=.046) and having a higher need for cognition (OR 1.02; 95% CI 1.00-1.05; P=.02) increased the odds of adhering to the intervention. Overall, participants logged in an average of 4 times per lesson, but adherers logged in significantly more times per lesson than nonadherers (F1,204=20.710; P<.001). For use patterns, we saw that early nonadherers seemed to use fewer sessions and spend less time than late nonadherers and adherers, and fewer sessions to complete the lesson than adherers. Furthermore, late nonadherers seemed to have a shorter total duration of sessions than adherers. Conclusions By using log data combined with baseline characteristics of participants, we extracted valuable lessons for redesign of this intervention and the design of Web-based interventions in general. First, although characteristics of respondents can significantly predict adherence, their predictive value is small. Second, it is important to design Web-based interventions to foster adherence and usage of all features in an intervention. Trial Registration Dutch Trial Register Number: NTR3007; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=3007 (Archived by WebCite at http://www.webcitation.org/6ILhI3rd8).

Evaluation of a web-based lifestyle coach designed to maintain a healthy bodyweight

We evaluated a web-based intervention, the Healthy Weight Assistant (HWA), which was designed to help people with a healthy bodyweight, or those who are slightly overweight, to achieve and maintain a healthy weight. Four evaluation methods were used: (1) pre- and post-test questionnaires; (2) real time usability-tests; (3) log-file analysis; (4) qualitative analysis of forum posts, email messages and free-text responses in the questionnaires. A total of 703 respondents received access to the HWA. Six weeks after receiving access, 431 respondents completed a second questionnaire. The enthusiastic responses showed that many people were interested in using an interactive online application to support achieving and maintaining a healthy weight. The preliminary results suggest that improvements with respect to motivation may lead to large effects, yet require only small changes in the design of the HWA. Sending automatic tailored reminders may enhance motivation to keep using the application. Motivation to change behaviour may be enhanced by emphasizing goal setting and visualizing progress.

Understanding adherence to web-based interventions

Although eHealth technologies and especially web-based interventions for the promotion of health and health related behavior have been shown to be effective, the impact is hindered by non-adherence: while many eHealth interventions reach a large group of participants, not all of these participants complete the intervention and may therefore not benefit as much from the intervention as they could. In this thesis, non-adherence is investigated by means of empirical studies into two web-based interventions: the Healthy Weight Assistant, an intervention aimed at healthy dietary and physical activity behavior; and Living to the Full, an intervention for the prevention of depression. Additionally, a systematic review was conducted to investigate the influence of intervention characteristics and persuasive design on adherence to web-based interventions. The comparison of adherers and non-adherers in the empirical studies has shown that adherers and non-adherers are different groups, but there are no universal predictors for adherence; rather it is important to create a match between participants and the intervention to improve adherence. Second, the human centered development process of Living to the Full and the investigation of the reasons for use of the Healthy Weight Assistant showed that participants expect a web-based intervention to support them in achieving their goals and to have the advantages that the Internet has to offer. Not fulfilling these expectations may well be a reason for non-adherence. Third, the systematic review showed that a persuasive design of web-based interventions, especially more use of dialogue support, increases the adherence to the intervention. The investigation of the impact of different persuasive design elements in Living to the Full showed that these persuasive design elements not always result in better adherence. Lastly, the empirical studies showed that participants do not use all features of a web-based intervention, but adherers use more features and seem to be more involved with the intervention than non-adherers. With these insights, the opportunity arises to not only hope for adherence, but to plan for adherence.