Who Follows eHealth Interventions as Recommended? A Study of Participants' Personal Characteristics From the Experimental Arm of a Randomized Controlled Trial

Exploring online health information seeking and sharing among older adults: a mini-review about acceptance, potentials, and barriers

Online health information seeking (OHIS) is understood by health care, health promotion, and disease prevention experts as a resource for healthy aging. It is particularly relevant for older adults since this population can benefit significantly from the accessibility and convenience of online health platforms and health information. Nevertheless, empirical findings regarding the acceptance, potentials, and barriers of OHIS among older adults are limited. This mini-review aims to explore the level of acceptance of OHIS, including passive reading of information and active interactions with peers, among the older population. Furthermore, it examines the potentials and barriers associated with such practices. The findings ultimately emphasize the evolving landscape of internet health information exploration among older adults and the potential advantages and challenges that may arise, especially in the context of active interactions with peers.

Efficacy of a web-based healthcare innovation to advance the quality of life and care of patients with an implantable cardioverter defibrillator (ACQUIRE-ICD): a randomized controlled trial

AIMS

Modern clinical management of patients with an implantable cardioverter defibrillator (ICD) largely consists of remote device monitoring, although a subset is at risk of mental health issues post-implantation. We compared a 12-month web-based intervention consisting of goal setting, monitoring of patients' mental health-with a psychological intervention if needed-psychoeducational support from a nurse, and an online patient forum, with usual care on participants' device acceptance 12 months after implantation.

METHODS AND RESULTS

This national, multi-site, two-arm, non-blinded, randomized, controlled, superiority trial enrolled 478 first-time ICD recipients from all 6 implantation centres in Denmark. The primary endpoint was patient device acceptance measured by the Florida Patient Acceptance Survey (FPAS; general score range = 0-100, with higher scores indicating higher device acceptance) 12 months after implantation. Secondary endpoints included symptoms of depression and anxiety. The primary endpoint of device acceptance was not different between groups at 12 months [B = -2.67, 95% confidence interval (CI) (-5.62, 0.29), P = 0.08]. Furthermore, the secondary endpoint analyses showed no significant treatment effect on either depressive [B = -0.49, 95% CI (-1.19; 0.21), P = 0.17] or anxiety symptoms [B = -0.39, 95% CI (-0.96; 0.18), P = 0.18].

CONCLUSION

The web-based intervention as supplement to usual care did not improve patient device acceptance nor symptoms of anxiety and depression compared with usual care. This specific web-based intervention thus cannot be recommended as a standardized intervention in ICD patients.

Mobile Digital Health Intervention to Promote Nutrition and Physical Activity Behaviors Among Long-term Unemployed in Rural Areas: Protocol for a Randomized Controlled Trial

Background

Long-term unemployed have poor nutritional and physical activity statuses, and, therefore, special health promotion needs. Particularly in rural areas, however, they often do not have access to health promotion service. Thus, new promising strategies to improve the health of long-term unemployed are needed. Hence, a digital health intervention to promote nutritional and physical health behaviors was conceived, and the effectiveness of the intervention in combination with face-to-face sessions will be evaluated in a randomized controlled trial.

Objective

The aim of this study is to elucidate the effectiveness of a mobile digital health intervention to promote the nutritional and physical activity behaviors of long-term unemployed in the rural areas of Germany.

Methods

The 9-week intervention aims to promote nutritional or physical activity behavior by improving drinking habits, increasing the consumption of fruits, vegetables, and whole grains, increasing daily step count, strengthening muscles, and improving endurance. The intervention design is based on the transtheoretical model and is implemented in a mobile app using the MobileCoach open-source platform. The effectiveness of the intervention will be elucidated by a 9-week, 2-armed, parallel-designed trial. Therefore, long-term unemployed will be recruited by employees of the German social sector institutions and randomized either to receive information brochures; the digital intervention in the form of a mobile app; and 3 face-to-face sessions regarding technical support, healthy eating, and physical activity (n=100) or to receive a control treatment consisting of solely the hand over of information brochures (n=100). The effectiveness of the intervention will be assessed using questionnaires at baseline, after 9 weeks in face-to-face appointments, and after a 3-month follow-up period by postal contact. The use of the mobile app will be monitored, and qualitative interviews or focus groups with the participants will be conducted. Incentives of €50 (US $49.7) will be paid to the participants and are tied to the completion of the questionnaires and not to the use of the mobile app or progress in the intervention.

Results

The effectiveness of the intervention in promoting the nutritional and physical activity behaviors of long-term unemployed participants will be elucidated. The adherence of the participants to and the acceptance and usability of the mobile device app will be evaluated. Recruitment started in March 2022, and the final publication of the results is expected in the first half of 2023.

Conclusions

Positive health-related changes made by the intervention would display the potency of digital health interventions to promote nutritional and physical activity behaviors among long-term unemployed in the rural areas of Germany, which would also contribute to an improved health status of the German population in general.

Trial Registration

German Clinical Trials Register DRKS00024805; https://www.drks.de/DRKS00024805

International Registered Report Identifier (IRRID)

PRR1-10.2196/40321

Predictors of Adherence to Cancer-Related mHealth Apps in Cancer Patients Undergoing Oncological or Follow-Up Treatment-A Scoping Review

mHealth interventions in cancer care are being increasingly applied in various settings. Nevertheless, there is a phenomenon wherein individuals show different usage patterns, which could affect the effectiveness of the intervention. In general, it is important to know the predictors of app adherence and usage patterns to improve the design and content (i.e., tailoring). The aim of this scoping review was to provide an overview of predictors of adherence to cancer-related mHealth apps in cancer patients. A systematic literature search was conducted in March 2021 in the electronic databases PubMed, CINAHL, and PsychINFO without limitation in year, focusing on cancer patients undergoing oncological or follow-up treatment using mHealth apps. The initial database search yielded a total of N = 8035 records. After title, abstract, and full-text screening, 10 articles met inclusion criteria. Studies were published between 2013 and 2020. Studies focused on children and adolescents (2/10) as well as adults (8/10). The predictors identified could be categorized into sociodemographic variables, cancer-related factors and others. This study provides an initial insight into relevant predictors of app adherence in cancer patients. However, no clear predictor of increased app adherence was found. Further research of usage patterns is therefore needed so that mHealth interventions can be tailored during development.

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.

Preventing and treating childhood overweight and obesity in children up to 5 years old: A systematic review by intervention setting

The prevalence of childhood obesity is increasing worldwide with long-term health consequences. Effective strategies to stem the rising childhood obesity rates are needed but systematic reviews of interventions have reported inconsistent effects. Evaluation of interventions could provide more practically relevant information when considered in the context of the setting in which the intervention was delivered. This systematic review has evaluated diet and physical activity interventions aimed at reducing obesity in children, from birth to 5 years old, by intervention setting. A systematic review of the literature, consistent with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, was performed. Three electronic databases were searched from 2010 up to December 2020 for randomised controlled trials aiming to prevent or treat childhood obesity in children up to 5 years old. The studies were stratified according to the setting in which the intervention was conducted. Twenty-eight studies were identified and included interventions in childcare/school (n = 11), home (n = 5), community (n = 5), hospital (n = 4), e-health (n = 2) and mixed (n = 1) settings. Thirteen (46%) interventions led to improvements in childhood obesity measures, including body mass index z-score and body fat percentage, 12 of which included both parental/family-based interventions in conjunction with modifying the child's diet and physical activity behaviours. Home-based interventions were identified as the most effective setting as four out of five studies reported significant changes in the child's weight outcomes. Interventions conducted in the home setting and those which included parents/families were effective in preventing childhood obesity. These findings should be considered when developing optimal strategies for the prevention of childhood obesity.

The Effects of a Digital Well-Being Intervention in Older Adults: An Analysis of Real-World User Data (Preprint)

Background

Digital interventions have been shown to be effective for a variety of mental health disorders and problems. However, few studies have examined the effects of digital interventions in older adults; therefore, little is known about how older adults engage with or benefit from these interventions. Given that adoption rates for technology among people aged ≥65 years remain substantially lower than in the general population and that approximately 20% of older adults are affected by mental health disorders, research exploring whether older adults will use and benefit from digital interventions is needed.

Objective

This study aimed to examine the extent to which older adults engaged with a digital well-being intervention (Happify) and whether engaging with this program led to improvements in both subjective well-being and anxiety symptoms.

Methods

In this retrospective analysis, we analyzed data from 375 real-world Happify users aged ≥65 years who signed up for the platform between January 1, 2019, and December 23, 2021. Changes in well-being and anxiety symptoms across 42 to 182 days were assessed using responses to the in-app assessment, which users were prompted to take every 2 weeks, and were compared among users who engaged with the program at the recommended level (ie, 2 or more activities per week) or below the recommended level.

Results

In all, 30% (113/375) of the sample engaged with the platform at the recommended level (ie, completed an average of 2 or more activities per week), and overall, users completed an average of 43.35 (SD 87.80) activities, ranging from 1 to 786, between their first and last assessment. Users were also active on the platform for an average of 19.36 (SD 27.16) days, ranging from 1 to 152 days. Moreover, older adults who engaged at the recommended level experienced significantly greater improvements in subjective well-being (P=.002) and anxiety symptoms (P<.001) relative to those who completed fewer activities.

Conclusions

These data provide preliminary evidence that older adults engage with and benefit from digital well-being interventions. We believe that these findings highlight the importance of considering older adult populations in digital health research. More research is needed to understand potential barriers to using digital interventions among older adults and whether digital interventions should be modified to account for this population’s particular needs (eg, ensuring that the intervention is accessible using a variety of devices). However, these results are an important step in demonstrating the feasibility of such interventions in a population that is assumed to be less inclined toward digital approaches.

Comparing Reminders Sent via SMS Text Messaging and Email for Improving Adherence to an Electronic Health Program: Randomized Controlled Trial

Background

eHealth interventions can help people change behavior (eg, quit smoking). Reminders sent via SMS text messaging or email may improve the adherence to web-based programs and increase the probability of successful behavior change; however, it is unclear whether their efficiency is affected by the modality of the communication channel.

Objective

A 2-armed randomized control trial was conducted to compare the effect of providing reminders via SMS text messaging versus email on the adherence to an eHealth program for smoking cessation and on the probability to initiate a quit attempt.

Methods

Smokers were recruited via an internet-based advertisement. A total of 591 participants who diverted from intended use of the program (ie, failed to log on to a session) were automatically randomized to the experimental (SMS text messaging reminder, n=304) or the active comparator (email reminder, n=287) group.

Results

Unexpectedly, we found that the mode of reminder delivery did not significantly affect either the adherence, namely the number of completed program sessions, with the SMS text messaging reminder group showing a mean of 4.30 (SD 3.24) and the email reminder group showing a mean of 4.36 (SD 3.27) (t586=0.197, P=.84, and Cohen d=0.016), or the outcome, namely the quit smoking attempt rate (34.2% in the SMS text messaging group vs 31.7% in the email group; χ21=0.4, P=.52). Secondary analyses showed that age, gender, and education had significant effects on program adherence and education on the outcome. Moreover, we found a significant interaction effect between the mode of reminder delivery and gender on program adherence, suggesting that the effectiveness of SMS text message reminders might be different for females and males. However, this particular finding should be treated with care as it was based on post hoc subgroup analysis.

Conclusions

This study indicates that the modality of user reminders to log on increased neither the program adherence nor the probability of quitting smoking. This suggests that program developers may save costs using emails instead of SMS text messaging reminders.

Trial Registration

ClinicalTrials.gov NCT03276767; https://clinicaltrials.gov/ct2/show/ NCT03276767

Digital health to reduce the burden of atherosclerotic cardiovascular disease. Solutions proposed by the CARRIER consortium (Preprint)

Digital health is a promising tool to support people with an elevated risk for atherosclerotic cardiovascular disease (ASCVD) and patients with an established disease to improve cardiovascular outcomes. Many digital health initiatives have been developed and employed. However, barriers to their large-scale implementation have remained. This paper focuses on these barriers and presents solutions as proposed by the Dutch CARRIER (ie, Coronary ARtery disease: Risk estimations and Interventions for prevention and EaRly detection) consortium. We will focus in 4 sections on the following: (1) the development process of an eHealth solution that will include design thinking and cocreation with relevant stakeholders; (2) the modeling approach for two clinical prediction models (CPMs) to identify people at risk of developing ASCVD and to guide interventions; (3) description of a federated data infrastructure to train the CPMs and to provide the eHealth solution with relevant data; and (4) discussion of an ethical and legal framework for responsible data handling in health care. The Dutch CARRIER consortium consists of a collaboration between experts in the fields of eHealth development, ASCVD, public health, big data, as well as ethics and law. The consortium focuses on reducing the burden of ASCVD. We believe the future of health care is data driven and supported by digital health. Therefore, we hope that our research will not only facilitate CARRIER consortium but may also facilitate other future health care initiatives.

Investigating When, Which, and Why Users Stop Using a Digital Health Intervention to Promote an Active Lifestyle: Secondary Analysis With A Focus on Health Action Process Approach–Based Psychological Determinants

Background

Digital health interventions have gained momentum to change health behaviors such as physical activity (PA) and sedentary behavior (SB). Although these interventions show promising results in terms of behavior change, they still suffer from high attrition rates, resulting in a lower potential and accessibility. To reduce attrition rates in the future, there is a need to investigate the reasons why individuals stop using the interventions. Certain demographic variables have already been related to attrition; however, the role of psychological determinants of behavior change as predictors of attrition has not yet been fully explored.

Objective

The aim of this study was to examine when, which, and why users stopped using a digital health intervention. In particular, we aimed to investigate whether psychological determinants of behavior change were predictors for attrition.

Methods

The sample consisted of 473 healthy adults who participated in the intervention MyPlan 2.0 to promote PA or reduce SB. The intervention was developed using the health action process approach (HAPA) model, which describes psychological determinants that guide individuals in changing their behavior. If participants stopped with the intervention, a questionnaire with 8 question concerning attrition was sent by email. To analyze when users stopped using the intervention, descriptive statistics were used per part of the intervention (including pre- and posttest measurements and the 5 website sessions). To analyze which users stopped using the intervention, demographic variables, behavioral status, and HAPA-based psychological determinants at pretest measurement were investigated as potential predictors of attrition using logistic regression models. To analyze why users stopped using the intervention, descriptive statistics of scores to the attrition-related questionnaire were used.

Results

The study demonstrated that 47.9% (227/473) of participants stopped using the intervention, and drop out occurred mainly in the beginning of the intervention. The results seem to indicate that gender and participant scores on the psychological determinants action planning, coping planning, and self-monitoring were predictors of first session, third session, or whole intervention completion. The most endorsed reasons to stop using the intervention were the time-consuming nature of questionnaires (55%), not having time (50%), dissatisfaction with the content of the intervention (41%), technical problems (39%), already meeting the guidelines for PA/SB (31%), and, to a lesser extent, the experience of medical/emotional problems (16%).

Conclusions

This study provides some directions for future studies. To decrease attrition, it will be important to personalize interventions on different levels, questionnaires (either for research purposes or tailoring) should be kept to a minimum especially in the beginning of interventions by, for example, using objective monitoring devices, and technical aspects of digital health interventions should be thoroughly tested in advance.

Trial Registration

ClinicalTrials.gov NCT03274271; https://clinicaltrials.gov/ct2/show/NCT03274271

International Registered Report Identifier (IRRID)

RR2-10.1186/s13063-019-3456-7

Use and Appreciation of a Web-Based, Computer-Tailored Diet and Physical Activity Intervention Based on the Self-determination Theory: Evaluation Study of Process and Predictors

Background

eHealth is a promising tool for promoting lifestyle behaviors such as a healthy diet and physical activity (PA). However, making people use interventions is a crucial and challenging problem in eHealth. More insight into use patterns and predicting factors is needed to improve future interventions.

Objective

This study aims to examine the use, predictors of use, and appreciation of a web-based, computer-tailored, dietary and PA promotion intervention, MyLifestyleCoach, which is based on the self-determination theory. First, we depict the participants’ flow in the intervention and identify moments when they are likely to discontinue use. Second, we investigate whether demographic, motivational, and program-related characteristics predict the use of several intervention elements. Finally, we report the appreciation scores for the intervention and the participant and program characteristics associated with these scores.

Methods

This study was based on data from web-based self-report questionnaires. Here, objectively assessed intervention use data were analyzed from participants randomized to the intervention condition. Multiple stepwise (logistic) regression analyses were conducted to examine the predictors of intervention use and evaluation scores.

Results

Our findings indicate a low full completion rate for the intervention among those who chose and completed the diet module (49/146, 33.6%), the PA module (2/12, 17%), and both modules (58/273, 21.2%). Several points in the intervention where participants were likely to stop using the intervention were identified. Autonomous and intrinsic motivation toward diet were related to the completion of the initial sessions of the intervention (ie, the opening session in which participants could choose which module to follow and the first session of the diet module). In contrast, controlled motivation was linked to the completion of both modules (initial and follow-up sessions). Appreciation scores were somewhat positive. Appreciation was predicted by several motivational constructs, such as amotivation and basic psychological needs (eg, competence) and program-related features (eg, number of completed sessions).

Conclusions

This study adds meaningful information on the use and appreciation of a web-based, computer-tailored dietary and PA intervention, MyLifestyleCoach. The results indicate that different types of motivations, such as extrinsic and intrinsic motivation, are at play at the points when people are likely to stop using the intervention. The intervention was appreciated fairly well, and several motivational constructs and fulfillment of basic psychological needs were associated with appreciation. Practical implications of these findings have been provided in this study.

The Acceptance and Use of the e-Health Instrument 'The Personal Health Check' in Four Dutch Municipalities: Lessons Learned

This pilot study assessed the acceptance and use of the e-Health instrument “the Personal Health Check” (PHC) among clients and professionals in primary care settings. By filling in the online PHC instrument, participants were provided insights into their health and lifestyle. When results revealed an increased health risk, participants were advised to undertake additional lab tests measuring blood pressure and haemaglobin levels. Based on the online questionnaire and optional lab tests, participants then received a report that included individually-tailored feedback from the e-Health application about personal health risks and suggestions for health interventions. The PHC was implemented in 2016 in four Dutch municipalities that determined which neighbourhood(s) the PHC targeted and how participants were invited. The Unified Theory of Acceptance and Use of Technology was used as a theoretical framework to address our research questions. Methods used to assess acceptance were: PHC instrument data, data from additional questionnaires completed by PHC participants, focus groups with PHC participants and professionals in primary care, and telephone interviews with non-responders to the invitation to participate in the online PHC. Of the 21,735 invited, 12% participated. Our results showed that participants and professionals in this pilot were predominantly positive about the PHC. Participants reported that they made an effort to apply the PHC lifestyle advice they received. Almost all had the knowledge and resources needed to use the PHC online instrument. Invitations from general practitioners almost doubled participation relative to invitations from the sponsoring municipalities. The overall low response rate, however, suggests that the PHC is unsuitable as a foundation on which to develop local public health policy.

An observation of the impact of tailored messages on participant non-compliance during Desire2Move

We assessed the impact of tailored versus targeted messages on program non-compliance during Desire2Move (D2M), an 8-week eHealth program that promotes physical activity (PA). Participants recorded minutes of PA using MapMyFitness, which counted toward their departments' PA total. Departments were randomized into the targeted messaging (TM) or tailored messaging (TM+) group based on participant-reported goals. Participants who did not provide a goal were assigned to the control group (CG). Eligible participants were employees from invited departments who were non-compliant for at least 1 week of D2M. Upon initial non-compliance, participants across groups received a targeted email message prompting program resumption. For subsequent non-compliance, the TM group continued to receive the same targeted message. The TM+ group received a message tailored to the participant's program goal. The CG group did not receive additional messages. Participants (n = 149) were mostly female (68.5%), staff (44.3%), with an average age of 43.7 (SD = 11.1). Analyses revealed significant group differences in non-compliance between TM+ (M = 2.6, SD = 1.9) and TM (M = 4.0, SD = 2.1), F(16,88) = 3.4, p < .01; d = .64, and between TM+ (M = 2.6, SD = 1.9) and CG (M = 3.8, SD = 2.1), F(1,74) = 13.3, p < .01; d = .56. There was no significant group difference between TM and CG, F(1,80) = 0.1, p = .75; d = .02. Tailored messages improved individual program compliance. More research is needed to assess the relationship between program compliance and PA behavior change.

Who seeks Internet-based interventions for depression in Brazil?

Abstract Specific psychological treatments for depressive disorders delivered on the Internet have shown effectiveness and presented advantages over face-to-face treatments (potentially less expensive, flexible schedules, available in remote areas). This paper aims to describe the characteristics of those who sought help from an online self-guided intervention for depression and to explore hypotheses about predictors of enrollment to the program. Based on a sample of 282 of individuals who filled in screening questionnaires, we verified that the respondents were mainly female, were on average 34.36 years old, were primarily recruited through Facebook, had been previously diagnosed by mental health professionals, presented moderate self-efficacy perception, and had moderately severe symptoms of depression. Respondents who reported comorbid conditions were more likely to attend enrollment interviews, and being in treatment or not did not influence attendance. Such characterization may provide strategies to reach more people and to optimize the design of interventions targeting help-seeking depressed individuals in Brazil.

Co-Design to Support the Development of Inclusive eHealth Tools for Caregivers of Functionally Dependent Older Persons: Social Justice Design

BACKGROUND

eHealth can help reduce social health inequalities (SHIs) as much as it can exacerbate them. Taking a co-design approach to the development of eHealth tools has the potential to ensure that these tools are inclusive. Although the importance of involving future users in the development of eHealth tools to reduce SHIs is highlighted in the scientific literature, the challenges associated with their participation question the benefits of this involvement as co-designers in a real-world context.

OBJECTIVE

On the basis of Amartya Sen's theoretical framework of social justice, the aim of this study is to explore how co-design can support the development of an inclusive eHealth tool for caregivers of functionally dependent older persons.

METHODS

This study is based on a social justice design and participant observation as part of a large-scale research project funded by the Ministry of Families as part of the Age-Friendly Quebec Program (Québec Ami des Aînés). The analysis was based on the method developed by Miles and Huberman and on Paillé's analytical questioning method.

RESULTS

A total of 78 people participated in 11 co-design sessions in 11 Quebec regions. A total of 24 preparatory meetings and 11 debriefing sessions were required to complete this process. Co-designers participated in the creation of a prototype to support the search for formal services for caregivers. The majority of participants (except for 2) significantly contributed to the tool's designing. They also incorporated conversion factors to ensure the inclusiveness of the eHealth tool, such as an adequate level of digital literacy and respect for the caregiver's help-seeking process. In the course of the experiment, the research team's position regarding its role in co-design evolved from a neutral posture and promoting co-designer participation to one that was more pragmatic.

CONCLUSIONS

The use of co-design involving participants at risk of SHIs does not guarantee innovation, but it does guarantee that the tool developed will comply with their process of help-seeking and their literacy level. Time issues interfere with efforts to carry out a democratic process in its ideal form. It would be useful to single out some key issues to guide researchers on what should be addressed in co-design discussions and what can be left out to make optimal use of this approach in a real-world context.

Mobile Breast Cancer e-Support Program for Chinese Women With Breast Cancer Undergoing Chemotherapy (Part 3): Secondary Data Analysis

Background

Many app-based interventions targeting women with breast cancer have been developed and tested for effectiveness. However, information regarding the evaluation of the usage of these interventions is scarce. A better understanding of usage data is important to determine how women use apps and how these interventions affect health outcomes.

Objective

This study aimed to examine the usage duration and login frequency of an app-based intervention, the Breast Cancer e-Support (BCS) program, and to investigate the association between usage data and participants’ demographic and medical characteristics.

Methods

This study is a secondary data analysis of a randomized controlled trial assessing the effectiveness of the BCS program. The BCS program contains four modules: Learning Forum, Discussion Forum, Ask-the-Expert Forum, and Your Story Forum. A total of 57 women in the intervention group accessed the BCS program during their 12-week chemotherapy. The app’s background system tracked the usage duration and login frequency for each forum and the entire BCS program.

Results

The total usage duration per participant ranged from 0 to 9371 minutes, and the login frequency per participant ranged from 0 to 774 times. The Discussion Forum and the Learning Forum were the most frequently used modules. The general linear model showed that age, education, family monthly income, and employment were associated with BCS usage duration and/or login frequency. Age (F_1,45=10.09, P=.003, B=115.34, 95% CI 42.22-188.47) and education level (F_1,45=7.22, P=.01, B=1949.63, 95% CI 487.76-3411.50) were positively associated with the usage duration of the entire BCS program. Family monthly income was positively associated with the usage duration of the Learning Forum (F_1,45=11.85, P=.001, B=1488.55, 95% CI 617.58-2359.51) and the login frequency of the entire BCS program (F_1,45=4.47, P=.04, B=113.68, 95% CI 5.33-222.03). Employment was negatively associated with the usage duration of the Ask-the-expert Forum (F_1,45=4.50, P=.04, B=–971.87, 95% CI –1894.66 to –49.07) and the Your Story Forum (F_1,45=5.36, P=.03, B=–640.71, 95% CI –1198.30 to –83.11) and positively associated with the login frequency of the entire BCS program (F_1,45=10.86, P=.002, B=192.88, 95% CI 75.01-310.74). No statistical differences were found between BCS usage data and cancer stage, BMI, comorbidity, types of surgery, or cycles of chemotherapy.

Conclusions

Overall, this study found considerable variability in the usage of app-based interventions. When health care professionals incorporate app-based interventions into their routine care for women with breast cancer, the learning and discussion functions of apps should be strengthened to promote engagement. Additionally, characteristics of women with breast cancer, such as age, level of education, income, and employment status, should be taken in consideration to develop tailored apps that address their particular needs and therefore improve their engagement with the app.

Trial Registration

Australian New Zealand Clinical Trials Registry ACTRN12616000639426; http://www.ANZCTR.org.au/ACTRN12616000639426.aspx

Integration of Conversion Factors for the Development of an Inclusive eHealth Tool With Caregivers of Functionally Dependent Older Persons: Social Justice Design

BACKGROUND

eHealth can help reduce social health inequalities (SHIs); at the same time, it also has the potential to increase them. Several conversion factors can be integrated into the development of an eHealth tool to make it inclusive: (1) providing physical, technical, and financial access to eHealth; (2) enabling the integration of people at risk of SHIs into the research and development of digital projects targeting such populations (co-design or participatory research); (3) promoting consistency between the digital health literacy level of future users (FUs) and the eHealth tool; (4) developing an eHealth tool that is consistent with the technological skills of FUs; (5) ensuring that the eHealth tool is consistent with the help-seeking process of FUs; (6) respecting the learning capacities of FUs; and (7) being sensitive to FUs' cultural context. However, only little empirical evidence pointing out how these conversion factors can be integrated into an effective eHealth tool is available.

OBJECTIVE

On the basis of Amartya Sen's theoretical framework of social justice, the objective of this study was to explore how these 7 conversion factors can be integrated into an eHealth tool for caregivers of functionally dependent older persons.

METHODS

This study was based on a social justice design and participant observation as part of a large-scale research project funded by the Ministère de la Famille through the Quebec Ami des Aînés Program. Data were collected by recording the preparation sessions, the co-design and advisory committee sessions, as well as the debriefing sessions. The results were analyzed using Miles and Huberman's method.

RESULTS

A total of 78 co-designers participated in 11 co-design sessions, 24 preparation sessions, and 11 debriefing sessions. Of the 7 conversion factors, 5 could be explored in this experiment. The integration of conversion factors has been uneven. The participation of FUs in the development of the tool supports other conversion factors. Respecting the eHealth literacy level of FUs means that their learning abilities and technological skills are also respected because they are closely related to one another and are therefore practically difficult to be distinguished.

CONCLUSIONS

Conversion factors can be integrated into the development of eHealth tools that are intended to be inclusive and contribute to curbing SHIs by integrating FU participation into the tool design process.

Effectiveness trial of an online self-help intervention for sexual problems after cancer

Sexual dysfunction affects over 60% of cancer survivors. Internet interventions have improved sexual function, but with considerable clinician guidance, restricting scalability. This pragmatic trial evaluated an online, self-help intervention. As with many unguided digital interventions, attrition was high. Given low numbers in other groups, this paper focuses on 30% of female patient participants who completed 3-month questionnaires and visited the intervention site (N = 60). Benefits included increased sexually active individuals at follow-up (p < 0.001, Effect size = 0.54), improved sexual function (p < 0.001, Effect size = -0.76, N = 41), and increased use of sexual aids (p = 0.01, Effect size=-0.14, N = 58). The intervention has been revised to improve patient engagement.

Personalized eHealth Program for Life-style Change: Results From the "Do Cardiac Health Advanced New Generated Ecosystem (Do CHANGE 2)" Randomized Controlled Trial

OBJECTIVE

Unhealthy life-style factors have adverse outcomes in cardiac patients. However, only a minority of patients succeed to change unhealthy habits. Personalization of interventions may result in critical improvements. The current randomized controlled trial provides a proof of concept of the personalized Do Cardiac Health Advanced New Generation Ecosystem (Do CHANGE) 2 intervention and evaluates effects on a) life-style and b) quality of life over time.

METHODS

Cardiac patients (n = 150; mean age = 61.97 ± 11.61 years; 28.7% women; heart failure, n = 33; coronary artery disease, n = 50; hypertension, n = 67) recruited from Spain and the Netherlands were randomized to either the "Do CHANGE 2" or "care as usual" group. The Do CHANGE 2 group received ambulatory health-behavior assessment technologies for 6 months combined with a 3-month behavioral intervention program. Linear mixed-model analysis was used to evaluate the intervention effects, and latent class analysis was used for secondary subgroup analysis.

RESULTS

Linear mixed-model analysis showed significant intervention effects for life-style behavior (Finteraction(2,138.5) = 5.97, p = .003), with improvement of life-style behavior in the intervention group. For quality of life, no significant main effect (F(1,138.18) = .58, p = .447) or interaction effect (F(2,133.1) = 0.41, p = .67) was found. Secondary latent class analysis revealed different subgroups of patients per outcome measure. The intervention was experienced as useful and feasible.

CONCLUSIONS

The personalized eHealth intervention resulted in significant improvements in life-style. Cardiac patients and health care providers were also willing to engage in this personalized digital behavioral intervention program. Incorporating eHealth life-style programs as part of secondary prevention would be particularly useful when taking into account which patients are most likely to benefit.

TRIAL REGISTRATION

https://clinicaltrials.gov/ct2/show/NCT03178305.

The effectiveness of online interventions for patients with gynecological cancer: An integrative review

OBJECTIVE

With advantages of easy accessibility and various multimedia interactivity formats, online interventions have been developed to improve health outcomes for patients with a variety of gynecological cancers, but evidence regarding their effectiveness for such patients is not well-understood. This review aimed to synthesize study findings that were published in English or Chinese regarding the effectiveness of online interventions on the quality of life, symptom distress, social support, psychological distress, sexual well-being, and body image in patients with gynecological cancer.

METHODS

This integrative review adhered to five steps, including problem identification, literature search, quality appraisal, data analysis, and presentation. Ten electronic databases (MEDLINE, ScienceDirect, SpringerLink, PubMed, Wiley Online Journals, Web of Science, OVID, CINAHL Plus with Full Text, China National Knowledge Infrastructure, and Cochrane Library) were searched from the inception of each database to April 2019 in accordance with the rigid and explicit inclusion and exclusion criteria. Version 2018 of the Mixed Methods Appraisal Tool was used for the quality appraisal of the articles.

RESULTS

Out of 276 articles, 24 potentially eligible articles were initially identified. A manual search retrieved an additional eligible three articles. After nine articles were excluded, ten quantitative, six qualitative, and two mixed-methods articles were finally included. Online interventions improved quality of life and body images in patients with gynecological cancer, but there were inconclusive effects on symptom distress, social support, psychological distress, and sexual well-being.

CONCLUSIONS

Online interventions have been increasingly used as clinically promising interventions to promote health outcomes among patients with gynecological cancer. Studies with more rigorous designs and sufficient sample sizes are needed to elucidate the effectiveness of such online interventions. Healthcare workers can incorporate existing or new online interventions into their routine care to improve health outcomes for patients with gynecological cancer.

Engagement with a Web-Based Health Promotion Intervention among Vocational School Students: A Secondary User and Usage Analysis

Engagement with web-based interventions is both generally low and typically declining. Visits and revisits remain a challenge. Based on log data of a web-based cluster randomized controlled trial conducted in vocational schools, the present secondary analysis aimed to identify influencing factors on initially logging in to a health promotion platform among young adults and to examine the engagement over the course of an eight-week intervention. Data of 336 students (62.2% female, age span 18–25) from two intervention arms (web-based intervention and web-based intervention with an additional initial face-to-face contact) was included. Binary logistic regression and log-data visualization were performed. An additional initial face-to-face contact (odds ratio (OR) = 2.971, p = 0.005), female sex (OR = 2.237, p = 0.046) and the health-related skill “dealing with health information” (OR = 2.179, p = 0.030) significantly increased the likelihood of initially logging in. Other variables showed no influence. 16.6% of all potential users logged in at least once, of which 57.4% revisited the platform. Most logins were tracked at the beginning of the intervention and repeated engagement was low. To increase the engagement with web-based interventions, health-related skills should be fostered. In addition, a strategy could be to interlink comparable interventions in vocational schools more regularly with everyday teaching through multi-component interventions.

An Electronic Health Tool to Prepare for the First Orthopedic Consultation: Use and Usability Study

Background

The use of electronic health (eHealth) technology to prepare patients with hip or knee osteoarthritis (OA) for their first orthopedic consultation seems promising. Exploration of the use and usability of an educational eHealth tool may highlight potential modifications that could increase patient engagement and effectiveness.

Objective

This study aimed to (1) identify the use and usability of a stand-alone educational eHealth tool for patients with suspected hip or knee OA, (2) explore whether the recorded questions in the eHealth tool were in line with an existing widely used question prompt list, and (3) investigate whether user characteristics are related to use and usability.

Methods

We used data from 144 participants in the intervention group of a randomized controlled trial, who were asked to use the educational eHealth tool to prepare for their upcoming first orthopedic consultation. We defined users and nonusers based on whether they had opened the tool at least once. Users were characterized as active or superficial depending on the extent of their use of the tool. The recorded questions for the consultation preparation were categorized into themes fitting 3 predefined questions or in a remaining category. Usability was measured using the System Usability Scale (SUS, 0-100). Data were collected including the patient demographic and clinical characteristics, knowledge of OA, and internet and smartphone usage in daily life. The characteristics associated with users and nonusers were analyzed using a multivariable logistic regression analysis.

Results

A total of 116/144 (80.6%) participants used the educational eHealth tool, of whom 87/116 (75.0%) were active users. Of the three components of the tool (information, my consultation, and medication), medication was the least used (34%). On the basis of recorded questions of the users, the fourth predefined question could be proposed. The mean (SD) SUS score was 64.8 (16.0). No difference was found between the SUS scores of superficial and active users (mean difference 0.04, 95% CI −7.69 to 7.77). Participants with a higher baseline knowledge of OA (odds ratio [OR] 1.2, 95% CI 1.0 to 1.4) and who used the internet less frequently in their daily life (OR 0.6, 95% CI 0.5 to 0.9) were more likely to use the educational eHealth tool. We found no differences between the demographics and clinical characteristics of the superficial and active users.

Conclusions

Based on the results of this study, it can be concluded that the use of an educational eHealth tool to prepare patients with hip and knee OA for the first orthopedic consultation is feasible. Our results suggest some improvements that should be made to the content of the tool to improve its usability. No clear practical implications were found to support the implementation of the educational eHealth tool in specific subgroups.

Trial Registration

Netherlands Trial Register NTR6262; https://www.trialregister.nl/trial/6262

A Web-Based and Print-Delivered Computer-Tailored Physical Activity Intervention for Older Adults: Pretest-Posttest Intervention Study Comparing Delivery Mode Preference and Attrition

BACKGROUND

Web-based interventions can play an important role in promoting physical activity (PA) behavior among older adults. Although the effectiveness of these interventions is promising, they are often characterized by low reach and high attrition, which considerably hampers their potential impact on public health.

OBJECTIVE

The aim of this study was to identify the participant characteristics associated with the preference for a Web-based or a printed delivery mode and to determine whether an association exists between delivery modes or participant characteristics and attrition in an intervention. This knowledge may enhance implementation, sustainability of participation, and effectiveness of future interventions for older adults.

METHODS

A real-life pretest-posttest intervention study was performed (N=409) among community-living single adults who were older than 65 years, with physical impairments caused by chronic diseases. Measurements were taken at baseline and 3 months after the start of the intervention. Hierarchical logistic regression was used to assess demographic and behavioral characteristics (age, gender, body mass index, educational attainment, degree of loneliness, and PA level), as well as psychosocial characteristics (social support for PA, modeling, self-efficacy, attitude, and intention) related to delivery mode preference at baseline and attrition after 3 months.

RESULTS

The printed delivery mode achieved higher participation (58.9%, 241/409) than the Web-based delivery mode (41.1%, 168/409). Participation in the Web-based delivery mode was associated with younger age (B=-0.10; SE 0.02; Exp (B)=0.91; P<.001) and higher levels of social support for PA (B=0.38; SE 0.14; Exp (B)=1.46; P=.01); attrition was associated with participation in the Web-based delivery mode (B=1.28; SE 0.28; Exp (B)=3.58; P<.001) and low educational attainment (B=-0.53; SE 0.28; Exp (B)=0.59; P=.049).

CONCLUSIONS

A total of 41% of the participants chose the Web-based delivery mode, thus demonstrating a potential interest of single older adults with physical impairments in Web-based delivered interventions. However, attrition was demonstrated to be higher in the Web-based delivery mode, and lower educational attainment was found to be a predictor for attrition. Characteristics predicting a preference for the printed delivery mode included being older and receiving less social support. Although Web-based delivery modes are generally less expensive and easier to distribute, it may be advisable to offer a printed delivery mode alongside a Web-based delivery mode to prevent exclusion of a large part of the target population.

TRIAL REGISTRATION

Netherlands Trial Register NTR2297; https://www.trialregister.nl/trial/2173.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-DOI: 10.2196/resprot.8093.

How recommender systems could support and enhance computer-tailored digital health programs: A scoping review

Objective

Tailored digital health programs can promote positive health-related lifestyle changes and have been shown to be (cost) effective in trials. However, such programs are used suboptimally. New approaches are needed to optimise the use of these programs. This paper illustrates the potential of recommender systems to support and enhance computer-tailored digital health interventions. The aim is threefold, to explore: (1) how recommender systems provide health recommendations, (2) to what extent recommender systems incorporate theoretical models and (3) how the use of recommender systems may enhance the usage of computer-tailored interventions.

Methods

A scoping review was conducted, using MEDLINE and ScienceDirect, to identify health recommender systems reported in studies between January 2007 and December 2017. Information was subsequently extracted to understand the potential benefits of recommender systems for computer-tailored digital health programs. Titles and abstracts of 1184 studies were screened for the full-text screening, in which two reviewers independently selected articles and systematically extracted data using a predefined extraction form.

Results

A total of 26 articles were included for data extraction. General characteristics were reported, with eight studies reporting hybrid filtering. A description of how each recommender system provides a recommendation is described; the majority of recommender systems used messages as recommendation. We identified the potential effects of recommender systems on efficiency, effectiveness, trustworthiness and enjoyment of the digital health program.

Conclusions

Incorporating a collaborative method with demographic filtering as a second step to knowledge-based filtering could potentially add value to traditional tailoring with regard to enhancing the user experience. This study illustrates how recommender systems, especially hybrid programs, may have the potential to bring tailored digital health forward.

eHealth versus equity: Using a feminist poststructural framework to explore the influence of perinatal eHealth resources on health equity

AIMS AND OBJECTIVES

To explore whether and how eHealth resources targeted to families during the perinatal period effectively reach a diverse population or further oppress marginalised groups.

BACKGROUND

eHealth is often intended to reach a broad population, thus health content must be relatively generalised which limits the ability to tailor health education and interventions to individual needs. Generalisation of health information has historically represented a hegemonic depiction of the health consumer, especially within the perinatal period, often disregarding the diversity that exists in the world and perpetuating heteronormative constructs within healthcare systems as a result.

DESIGN

A critical review of the literature regarding perinatal eHealth resources was conducted using a feminist poststructuralist approach for analysis. Included literature addresses the development, implementation and/or evaluation of perinatal eHealth resources.

DISCUSSION

This approach uncovered hegemonic discourses related to the current state of perinatal eHealth resources. Nurses and midwives have the unique advantage of interacting and understanding diverse populations. Thus, nurses and midwives are integral to the development, implementation and evaluation of eHealth resources to reduce social health inequity.

RELEVANCE TO CLINICAL PRACTICE

This paper acts as an exemplar on how to apply feminist poststructuralism to highlight inequities that exist and identifies strategies for nurses and midwives to become involved in the development of eHealth resources or advocate for greater visibility within current resources.

Understanding the Positive Associations of Sleep, Physical Activity, Fruit and Vegetable Intake as Predictors of Quality of Life and Subjective Health Across Age Groups: A Theory Based, Cross-Sectional Web-Based Study

Background: Due to the increase in unhealthy lifestyles and associated health risks, the promotion of healthy lifestyles to improve the prevention of non-communicable diseases is imperative. Thus, research aiming to identify strategies to modify health behaviors has been encouraged. Little is known about addressing multiple health behaviors across age groups (i.e., young, middle-aged, and older adults) and the underlying mechanisms. The theoretical framework of this study is Compensatory Carry-Over Action Model which postulates that different health behaviors (i.e., physical activity and fruit and vegetable intake) are interrelated, and they are driven by underlying mechanisms (more details in the main text). Additionally, restful sleep as one of the main indicators of good sleep quality has been suggested as a mechanism that relates to other health behaviors and well-being, and should therefore also be investigated within this study. The present study aims to identify the interrelations of restful sleep, physical activity, fruit and vegetable intake, and their associations with sleep quality as well as overall quality of life and subjective health in different age groups.

Methods: A web-based cross-sectional study was conducted in Germany and the Netherlands. 790 participants aged 20–85 years filled in the web-based baseline questionnaire about their restful sleep, physical activity, fruit and vegetable intake, sleep quality, quality of life, and subjective health. Descriptive analysis, multivariate analysis of covariance, path analysis, and multi-group analysis were conducted.

Results: Restful sleep, physical activity, and fruit and vegetable intake were associated with increased sleep quality, which in turn was associated with increased overall quality of life and subjective health. The path analysis model fitted the data well, and there were age-group differences regarding multiple health behaviors and sleep quality, quality of life, and subjective health. Compared to young and older adults, middle-aged adults showed poorest sleep quality and overall quality of life and subjective health, which were associated with less engagement in multiple health behaviors.

Conclusion: A better understanding of age-group differences in clustering of health behaviors may set the stage for designing effective customized age-specific interventions to improve health and well-being in general and clinical settings.

Trial Registration: A clinical trial registration was conducted with ClinicalTrials.gov (NCT01909349) https://clinicaltrials.gov/ct2/show/NCT01909349.

Randomized Controlled Trial of a Brief Versus Extended Internet Intervention for Problem Drinkers

Purpose

Brief Internet interventions have been shown to reduce alcohol consumption. This trial intended to compare the effects of one such brief intervention to an extended Internet intervention for problem drinkers.

Method

Using online advertising, 490 participants, 18 years or older, were recruited and randomized to receive a brief (CheckYourDrinking.net) versus an extended (AlcoholHelpCentre.net) Internet intervention and were followed up at 6, 12, and 24 months. The per protocol primary analysis assessed difference between condition at the 12-month follow-up.

Results

The follow-up rate at 12 months was 83.3 %. ANCOVAs of the primary (Alcohol Use Disorder Identification Test (AUDIT)-C) and secondary outcome variables (drinks in a typical week, highest number of drinks on one occasion—baseline drinking as covariate) revealed no significant (p > 0.05) differences between the interventions. Similarly, combined analyses of the 6-, 12-, and 24-month follow-up revealed no significant differences between interventions at all time points.

Conclusion

The present study does not provide support for the added benefit of an extended Internet intervention for problem drinkers over a brief Internet intervention.

Integration of eHealth Tools in the Process of Workplace Health Promotion: Proposal for Design and Implementation

BACKGROUND

Electronic health (eHealth) and mobile health (mHealth) tools can support and improve the whole process of workplace health promotion (WHP) projects. However, several challenges and opportunities have to be considered while integrating these tools in WHP projects. Currently, a large number of eHealth tools are developed for changing health behavior, but these tools can support the whole WHP process, including group administration, information flow, assessment, intervention development process, or evaluation.

OBJECTIVE

To support a successful implementation of eHealth tools in the whole WHP processes, we introduce a concept of WHP (life cycle model of WHP) with 7 steps and present critical and success factors for the implementation of eHealth tools in each step.

METHODS

We developed a life cycle model of WHP based on the World Health Organization (WHO) model of healthy workplace continual improvement process. We suggest adaptations to the WHO model to demonstrate the large number of possibilities to implement eHealth tools in WHP as well as possible critical points in the implementation process.

RESULTS

eHealth tools can enhance the efficiency of WHP in each of the 7 steps of the presented life cycle model of WHP. Specifically, eHealth tools can support by offering easier administration, providing an information and communication platform, supporting assessments, presenting and discussing assessment results in a dashboard, and offering interventions to change individual health behavior. Important success factors include the possibility to give automatic feedback about health parameters, create incentive systems, or bring together a large number of health experts in one place. Critical factors such as data security, anonymity, or lack of management involvement have to be addressed carefully to prevent nonparticipation and dropouts.

CONCLUSIONS

Using eHealth tools can support WHP, but clear regulations for the usage and implementation of these tools at the workplace are needed to secure quality and reach sustainable results.

Clarifying the Concept of Adherence to eHealth Technology: Systematic Review on When Usage Becomes Adherence

BACKGROUND

In electronic health (eHealth) evaluations, there is increasing attention for studying the actual usage of a technology in relation to the outcomes found, often by studying the adherence to the technology. On the basis of the definition of adherence, we suggest that the following three elements are necessary to determine adherence to eHealth technology: (1) the ability to measure the usage behavior of individuals; (2) an operationalization of intended use; and (3) an empirical, theoretical, or rational justification of the intended use. However, to date, little is known on how to operationalize the intended usage of and the adherence to different types of eHealth technology.

OBJECTIVE

The study aimed to improve eHealth evaluations by gaining insight into when, how, and by whom the concept of adherence has been used in previous eHealth evaluations and finding a concise way to operationalize adherence to and intended use of different eHealth technologies.

METHODS

A systematic review of eHealth evaluations was conducted to gain insight into how the use of the technology was measured, how adherence to different types of technologies was operationalized, and if and how the intended use of the technology was justified. Differences in variables between the use of the technology and the operationalization of adherence were calculated using a chi-square test of independence.

RESULTS

In total, 62 studies were included in this review. In 34 studies, adherence was operationalized as "the more use, the better," whereas 28 studies described a threshold for intended use of the technology as well. Out of these 28, only 6 reported a justification for the intended use. The proportion of evaluations of mental health technologies reporting a justified operationalization of intended use is lagging behind compared with evaluations of lifestyle and chronic care technologies. The results indicated that a justification of intended use does not require extra measurements to determine adherence to the technology.

CONCLUSIONS

The results of this review showed that to date, justifications for intended use are often missing in evaluations of adherence. Evidently, it is not always possible to estimate the intended use of a technology. However, such measures do not meet the definition of adherence and should therefore be referred to as the actual usage of the technology. Therefore, it can be concluded that adherence to eHealth technology is an underdeveloped and often improperly used concept in the existing body of literature. When defining the intended use of a technology and selecting valid measures for adherence, the goal or the assumed working mechanisms should be leading. Adherence can then be standardized, which will improve the comparison of adherence rates to different technologies with the same goal and will provide insight into how adherence to different elements contributed to the outcomes.

Who uses apps in health promotion? A target group analysis of leaders

User characteristics should be considered when designing features for e-health or m-health applications, as the developed solution should aim to support this specific target group. This study explores the effect of user characteristics (personality, health state, stress/recovery state, leadership behavior) on the interest and likelihood of using an app for health promotion activities at the workplace. Leaders are a key factor for the success of workplace health promotion; therefore, the target group of this study are leaders. The data of 412 leaders were collected in an online study. Hierarchical multiple linear regression analyses were conducted for four outcome criteria ("personal health," "contacting," "leadership feedback" and "corporate key figures"). The findings showed that neuroticism, physical health and health-promoting leadership were important predictors for using an app for monitoring personal health and getting in social contact about health issues. The stress/recovery state was significantly related to the feature of getting in social contact.

Effectiveness of a Video-Versus Text-Based Computer-Tailored Intervention for Obesity Prevention after One Year: A Randomized Controlled Trial

Computer-tailored programs may help to prevent overweight and obesity, which are worldwide public health problems. This study investigated (1) the 12-month effectiveness of a video- and text-based computer-tailored intervention on energy intake, physical activity, and body mass index (BMI), and (2) the role of educational level in intervention effects. A randomized controlled trial in The Netherlands was conducted, in which adults were allocated to a video-based condition, text-based condition, or control condition, with baseline, 6 months, and 12 months follow-up. Outcome variables were self-reported BMI, physical activity, and energy intake. Mixed-effects modelling was used to investigate intervention effects and potential interaction effects. Compared to the control group, the video intervention group was effective regarding energy intake after 6 months (least squares means (LSM) difference = -205.40, p = 0.00) and 12 months (LSM difference = -128.14, p = 0.03). Only video intervention resulted in lower average daily energy intake after one year (d = 0.12). Educational role and BMI did not seem to interact with this effect. No intervention effects on BMI and physical activity were found. The video computer-tailored intervention was effective on energy intake after one year. This effect was not dependent on educational levels or BMI categories, suggesting that video tailoring can be effective for a broad range of risk groups and may be preferred over text tailoring.

A Self-Regulation-Based eHealth Intervention to Promote a Healthy Lifestyle: Investigating User and Website Characteristics Related to Attrition

BACKGROUND

eHealth interventions can reach large populations and are effective in increasing physical activity (PA) and fruit and vegetable intake. Nevertheless, the effects of eHealth interventions are overshadowed by high attrition rates. Examining more closely when users decide to leave the intervention can help eHealth developers to make informed decisions about which intervention components should be reshaped or simply removed. Investigating which users are more likely to quit an intervention can inform developers about whether and how their intervention should be adapted to specific subgroups of users.

OBJECTIVE

This study investigated the pattern of attrition in a Web-based intervention to increase PA, fruit, and vegetable intake. The first aim was to describe attrition rates according to different self-regulation components. A second aim was to investigate whether certain user characteristics are predictors for start session completion, returning to a follow-up session and intervention completion.

METHODS

The sample consisted of 549 adults who participated in an online intervention, based on self-regulation theory, to promote PA and fruit and vegetable intake, called "MyPlan 1.0." Using descriptive analysis, attrition was explored per self-regulation component (eg, action planning and coping planning). To identify which user characteristics predict completion, logistic regression analyses were conducted.

RESULTS

At the end of the intervention program, there was an attrition rate of 78.2% (330/422). Attrition rates were very similar for the different self-regulation components. However, attrition levels were higher for the fulfillment of questionnaires (eg, to generate tailored feedback) than for the more interactive components. The highest amount of attrition could be observed when people were asked to make their own action plan. There were no significant predictors for first session completion. Yet, two subgroups had a lower chance to complete the intervention, namely male users (OR: 2.24, 95% CI=1.23-4.08) and younger adults (OR: 1.02, 95% CI=1.00-1.04). Furthermore, younger adults were less likely to return to the website for the first follow-up after one week (OR: 1.03, 95% CI=1.01-1.04).

CONCLUSIONS

This study informs us that eHealth interventions should avoid the use of extensive questionnaires and that users should be provided with a rationale for several components (eg, making an action plan and completing questions). Furthermore, future interventions should focus first on motivating users for the behavior change before guiding them through action planning. Though, this study provides no evidence for removal of one of the self-regulation techniques based on attrition rates. Finally, strong efforts are needed to motivate male users and younger adults to complete eHealth interventions.

A Review of the Theoretical Basis, Effects, and Cost Effectiveness of Online Smoking Cessation Interventions in the Netherlands: A Mixed-Methods Approach

BACKGROUND

Tobacco smoking is a worldwide public health problem. In 2015, 26.3% of the Dutch population aged 18 years and older smoked, 74.4% of them daily. More and more people have access to the Internet worldwide; approximately 94% of the Dutch population have online access. Internet-based smoking cessation interventions (online cessation interventions) provide an opportunity to tackle the scourge of tobacco.

OBJECTIVE

The goal of this paper was to provide an overview of online cessation interventions in the Netherlands, while exploring their effectivity, cost effectiveness, and theoretical basis.

METHODS

A mixed-methods approach was used to identify Dutch online cessation interventions, using (1) a scientific literature search, (2) a grey literature search, and (3) expert input. For the scientific literature, the Cochrane review was used and updated by two independent researchers (n=651 identified studies), screening titles, abstracts, and then full-text studies between 2013 and 2016 (CENTRAL, MEDLINE, and EMBASE). For the grey literature, the researchers conducted a Google search (n=100 websites), screening for titles and first pages. Including expert input, this resulted in six interventions identified in the scientific literature and 39 interventions via the grey literature. Extracted data included effectiveness, cost effectiveness, theoretical factors, and behavior change techniques used.

RESULTS

Overall, many interventions (45 identified) were offered. Of the 45 that we identified, only six that were included in trials provided data on effectiveness. Four of these were shown to be effective and cost effective. In the scientific literature, 83% (5/6) of these interventions included changing attitudes, providing social support, increasing self-efficacy, motivating smokers to make concrete action plans to prepare their attempts to quit and to cope with challenges, supporting identity change and advising on changing routines, coping, and medication use. In all, 50% (3/6) of the interventions included a reward for abstinence. Interventions identified in the grey literature were less consistent, with inclusion of each theoretical factor ranging from 31% to 67% and of each behavior change technique ranging from 28% to 54%.

CONCLUSIONS

Although the Internet may provide the opportunity to offer various smoking cessation programs, the user is left bewildered as far as efficacy is concerned, as most of these data are not available nor offered to the smokers. Clear regulations about the effectiveness of these interventions need to be devised to avoid disappointment and failed quitting attempts. Thus, there is a need for policy regulations to regulate the proliferation of these interventions and to foster their quality in the Netherlands.

Social Health Inequalities and eHealth: A Literature Review With Qualitative Synthesis of Theoretical and Empirical Studies

Background

eHealth is developing rapidly and brings with it a promise to reduce social health inequalities (SHIs). Yet, it appears that it also has the potential to increase them.

Objectives

The general objective of this review was to set out how to ensure that eHealth contributes to reducing SHIs rather than exacerbating them. This review has three objectives: (1) identifying characteristics of people at risk of experiencing social inequality in health; (2) determining the possibilities of developing eHealth tools that avoid increasing SHI; and (3) modeling the process of using an eHealth tool by people vulnerable to SHI.

Methods

Following the EPPI approach (Evidence for Policy and Practice of Information of the Institute of Education at the University of London), two databases were searched for the terms SHIs and eHealth and their derivatives in titles and abstracts. Qualitative, quantitative, and mixed articles were included and evaluated. The software NVivo (QSR International) was employed to extract the data and allow for a metasynthesis of the data.

Results

Of the 73 articles retained, 10 were theoretical, 7 were from reviews, and 56 were based on empirical studies. Of the latter, 40 used a quantitative approach, 8 used a qualitative approach, 4 used mixed methods approach, and only 4 were based on participatory research-action approach. The digital divide in eHealth is a serious barrier and contributes greatly to SHI. Ethnicity and low income are the most commonly used characteristics to identify people at risk of SHI. The most promising actions for reducing SHI via eHealth are to aim for universal access to the tool of eHealth, become aware of users’ literacy level, create eHealth tools that respect the cultural attributes of future users, and encourage the participation of people at risk of SHI.

Conclusions

eHealth has the potential to widen the gulf between those at risk of SHI and the rest of the population. The widespread expansion of eHealth technologies calls for rigorous consideration of interventions, which are not likely to exacerbate SHI.

The conceptualization of a Just-In-Time Adaptive Intervention (JITAI) for the reduction of sedentary behavior in older adults

Low physical activity and high sedentary behavior in older adults can be addressed with interventions that are delivered through modern technology. Just-In-Time Adaptive Interventions (JITAIs) are an emerging technology-driven behavior-change intervention type and capitalize on data that is collected via mobile sensing technology (e.g., smartphones) to trigger appropriate support in real-life. In this paper we integrated behavior change and aging theory and research as well as knowledge around older adult's technology use to conceptualize a JITAI targeting the reduction of sedentary behavior in older adults. The JITAIs ultimate goal is to encourage older adults to take regular activity breaks from prolonged sitting. As a proximal outcome, we suggest the number of daily activity breaks from sitting. Support provided to interrupt sitting time can be based on tailoring variables: (I) the current accumulated sitting time; (II) the location of the individual; (III) the time of the day; (IV) the frequency of daily support prompts; and (V) the response to previous support prompts. Data on these variables can be collected using sensors that are commonly inbuilt into smartphones (e.g., accelerometer, GPS). Support prompts might be best delivered via traditional text messages as older adults are usually familiar and comfortable with this function. The content of the prompts should encourage breaks from prolonged sitting by highlighting immediate benefits of sitting time interruptions. Additionally, light physical activities that could be done during the breaks should also be presented (e.g., walking into the kitchen to prepare a cup of tea). Although the conceptualized JITAI can be developed and implemented to test its efficacy, more work is required to identify ways to collect, aggregate, organize and immediately use dense data on the proposed and other potentially important tailoring variables. Machine learning and other computational modelling techniques commonly used by computer scientists and engineers appear promising. With this, to develop powerful JITAIs and to actualize the full potential of modern sensing technologies transdisciplinary approaches are required.

Effectiveness of the self-regulation eHealth intervention 'MyPlan1.0.' on physical activity levels of recently retired Belgian adults: a randomized controlled trial

The study purpose was to test the effectiveness of the self-regulation eHealth intervention 'MyPlan1.0.' to increase physical activity (PA) in recently retired Belgian adults. This study was a randomized controlled trial with three points of follow-up/modules (baseline to 1-week to 1-month follow-up). In total, 240 recently retired adults (intervention group [IG]: n = 89; control group [CG]: n = 151) completed all three modules. The IG filled in evaluation questionnaires and received 'MyPlan1.0.', an intervention focusing on both pre- and post-intentional processes for behavioural change. The CG only filled in evaluation questionnaires. Self-reported PA was assessed using the long International Physical Activity Questionnaire, usual week version. Repeated-measures multivariate analysis of variances were conducted in SPSS 22.0. On the short-term (baseline to 1 week), the intervention significantly increased walking for transport (IG: +11 min/week, CG: -6 min/week; P < 0.01). On the intermediate-term (baseline to 1 month), the intervention increased transport-related walking (IG: +14 min/week, CG: +6 min/week; P < 0.01), leisure-time walking (IG: +26 min/week, CG: -14 min/week; P < 0.10), leisure-time vigorous PA (IG: +16 min/week, CG: -4 min/week; P < 0.01), moderate-intensity gardening (IG: +4 min/week, CG: -34 min/week; P < 0.10) and voluntary work-related vigorous PA (IG: +28 min/week, CG: +13 min/week; P < 0.10). Results show that our eHealth intervention is effective in recently retired adults. Future studies should include long-term follow-up to examine whether the effects persist over a longer period.

Impact of a randomized possible selves experiment on new retirees' physical activity and identity

BACKGROUND

Retirement is not always associated with greater engagement in physical activity. Previous interventions informed by possible selves, a type of future-oriented self-representation, proved useful to increase physical activity in young adults. We thus wanted to explore if a similar intervention would yield favorable outcomes in new retirees. We also examined whether possible selves could help increase identity relative to the physical activity context. Identity circumscribes the meanings which help individuals define who they are in a given role (i.e., what it means to be a physically active person). The strength of identification as a physically active person increases when individuals endorse these meanings more strongly. Possible selves may be tied to identity as they allow individuals to imagine themselves as physically active, which has been argued to incite changes to one's sense of self. Hence, the overall aim of this study was to determine whether a possible selves intervention would increase physical activity behaviour and physical activity identity in a group of newly-retired individuals.

METHODS

A total of 294 participants were randomized into one of three groups: (a) a repeated group with three possible selves image generation exposures, (b) a one-time group with one possible selves image generation exposure, or (c) a control group. Participants completed self-report measures at baseline and follow-up assessments were taken at weeks 4, 8, and 12 of the study. The measures for the outcomes of interest were the Godin Leisure Time Exercise Questionnaire and the modified Exercise Identity Scale.

RESULTS

Repeated measures mixed-effects models analyses with maximum likelihood estimation revealed no significant differences between groups on physical activity behaviour (p = 0.34) or physical activity identity (p = 0.97) at follow-up time points. However, a time effect was found for physical activity (p <.01) and physical activity identity (p <.01), which increased across time (baseline-to-12-week follow-up) in all three groups. Such a time effect (inconsequential to group assignment) suggests that the observed increases in physical activity and identity cannot be attributed to an exposure to a possible selves intervention.

CONCLUSIONS

While the intervention failed to significantly increase physical activity identity and physical activity in newly retired individuals, we suggest future research directions for interventions targeting new retired individuals.

Use and Appreciation of a Tailored Self-Management eHealth Intervention for Early Cancer Survivors: Process Evaluation of a Randomized Controlled Trial

BACKGROUND

A fully automated computer-tailored Web-based self-management intervention, Kanker Nazorg Wijzer (KNW [Cancer Aftercare Guide]), was developed to support early cancer survivors to adequately cope with psychosocial complaints and to promote a healthy lifestyle. The KNW self-management training modules target the following topics: return to work, fatigue, anxiety and depression, relationships, physical activity, diet, and smoking cessation. Participants were guided to relevant modules by personalized module referral advice that was based on participants’ current complaints and identified needs.

OBJECTIVE

The aim of this study was to evaluate the adherence to the module referral advice, examine the KNW module use and its predictors, and describe the appreciation of the KNW and its predictors. Additionally, we explored predictors of personal relevance.

METHODS

This process evaluation was conducted as part of a randomized controlled trial. Early cancer survivors with various types of cancer were recruited from 21 Dutch hospitals. Data from online self-report questionnaires and logging data were analyzed from participants allocated to the intervention condition. Chi-square tests were applied to assess the adherence to the module referral advice, negative binominal regression analysis was used to identify predictors of module use, multiple linear regression analysis was applied to identify predictors of the appreciation, and ordered logistic regression analysis was conducted to explore possible predictors of perceived personal relevance.

RESULTS

From the respondents (N=231; mean age 55.6, SD 11.5; 79.2% female [183/231]), 98.3% (227/231) were referred to one or more KNW modules (mean 2.9, SD 1.5), and 85.7% (198/231) of participants visited at least one module (mean 2.1, SD 1.6). Significant positive associations were found between the referral to specific modules (range 1-7) and the use of corresponding modules. The likelihoods of visiting modules were higher when respondents were referred to those modules by the module referral advice. Predictors of visiting a higher number of modules were a higher number of referrals by the module referral advice (β=.136, P=.009), and having a partner was significantly related with a lower number of modules used (β=-.256, P=.044). Overall appreciation was high (mean 7.5, SD 1.2; scale 1-10) and was significantly predicted by a higher perceived personal relevance (β=.623, P=.000). None of the demographic and cancer-related characteristics significantly predicted the perceived personal relevance.

CONCLUSIONS

The KNW in general and more specifically the KNW modules were well used and highly appreciated by early cancer survivors. Indications were found that the module referral advice might be a meaningful intervention component to guide the users in following a preferred selection of modules. These results indicate that the fully automated Web-based KNW provides personal relevant and valuable information and support for early cancer survivors. Therefore, this intervention can complement usual cancer aftercare and may serve as a first step in a stepped-care approach.

TRIAL REGISTRATION

Nederlands Trial Register: NTR3375; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=3375 (Archived by WebCite at http://www.webcitation.org/6jo4jO7kb).

Online smoking cessation program for Korean Americans: Randomized trial to test effects of incentives for program completion and interim surveys

INTRODUCTION

Smoking is prevalent among Korean American men. Quitting is Winning, an Internet-based, cognitive-behavioral smoking cessation program, was developed using community-based participatory research principles.

METHODS

A randomized controlled trial was used to evaluate whether participants were more likely to complete the program and quit smoking at 6-months of follow-up with additional reinforcement. The main outcomes were the proportion of participants who completed the online program and the proportion who quit smoking for at least 30days, 26weeks after enrollment, among those randomized into the high-reinforcement (HR) condition compared with those in the low-reinforcement (LR) condition.

RESULTS

The study achieved a final enrollment of 403 participants including 56 women. Program completion was greater for the HR as compared to the LR condition (17% vs. 10%, p=.035). There was no significant difference in 30-day smoking cessation (intent-to-treat [ITT]) between the HR and LR conditions (9% vs. 8%, ns). Smoking cessation was greater among program completers as compared to those who did not complete the program (28% vs. 5%, p<.001).

CONCLUSIONS

The addition of interim surveys and financial incentives for interim survey completion and program completion significantly increased the likelihood of program completion. Moreover, program completers were significantly more likely to quit smoking. Although smoking cessation rates did not significantly differ between the HR and LR conditions, the results suggest that future studies should explore the efficacy of larger financial incentives for program completion (Clinical Trial #NCT02584127).

Investigating paternal preconception risk factors for adverse pregnancy outcomes in a population of internet users

BACKGROUND

Paternal preconception risk factors such as smoking, exposure to environmental substances, medication use, overweight and advanced age correlate with the occurrence of malformations and birth defects in the offspring. Nonetheless, the prevalence of risk factors for adverse pregnancy outcomes in the male population has been scarcely investigated and no report on preconception interventions targeting prospective fathers is available. We conducted a web-based survey to measure the prevalence of paternal preconception risk factors for adverse pregnancy outcomes in an Italian population of Internet users.

METHODS

Prospective or expectant fathers were enrolled during a four-week period through two of the main Italian web-sites dedicated to preconception, pregnancy, childhood and family care. Participants filled in a web questionnaire regarding preconception risk factors for adverse pregnancy outcomes. Logistic regression analysis was used to explore the predictors of paternal preconception risk factors.

RESULTS

We enrolled 131 prospective and 205 expectant fathers. More than half of the total participants used medications during the preconception period, 35% were smokers and 8% were obese. Exposure to environmental substances was declared by almost 20% of the participants, with the group including pesticides/herbicides/professional paints being the most prevalent. More than a half of the study sample included men aged over 35 years. According to the multivariate analysis, smoking and exposure to environmental toxics were less frequent among individuals with a university degree (respectively: OR = 0.52; 95% CI 0.32-0.84; OR = 0.52; 95% CI 0.29-0.93). Paternal obesity and medication use in the preconception period were not associated with any of the independent variables.

CONCLUSIONS

The prevalence of preconception risk factors among male population should not be neglected when planning preconception interventions, confirming that preconception health must be focused on the couple, rather than on women only.

Generating and predicting high quality action plans to facilitate physical activity and fruit and vegetable consumption: results from an experimental arm of a randomised controlled trial

Background

In order to improve the transition from an intention to a change in health behaviour, action planning is a frequently used behavioural change method. The quality of action plans in terms of instrumentality and specificity is important in terms of supporting a successful change in health behaviour. Until now, little has been known about the predictors of action plan generation and the predictors of high quality action plans and, therefore, the current study investigates these predictors.

Method

A randomised controlled trial was conducted to improve physical activity (PA) and fruit and vegetable (FV) consumption using a web-based computer tailored intervention. During the 8-week intervention period, participants in the intervention arm (n = 346) were guided (step-by-step) to generate their own action plans to improve their health behaviours. Demographic characteristics, social cognitions, and health behaviour were assessed at baseline by means of self-reporting. Whether participants generated action plans was tracked by means of server registrations within two modules of the intervention.

Results

The action planning component of the intervention regarding physical activity and fruit and vegetable consumption was used by 40.9 and 20.7 % of the participants, respectively. We found that participants who were physically active at baseline were less likely to generate action plans concerning physical activity. With regards to generating fruit and vegetable action plans, participants with a high risk perception and a strong intention to eat fruit and vegetables on a daily basis made more use of the action planning component for this behaviour. Finally, the large majority of the action plans for physical activity (96.6 %) and fruit and vegetable consumption (100 %) were instrumental and about half of the action plans were found to be highly specific (PA = 69.6 %/FV = 59.7 %). The specificity of the action plans is associated with having a relationship and low levels of negative outcome expectancies.

Conclusion

Risk perception and intention are predictors of using the application of action planning. Increasing the motivation to change behaviour should be prioritised in interventions concerning changes in health behaviour before participants are asked to generate action plans. This would also make the intervention suitable for unmotivated people. For those participants who already perform the desired health behaviour prior to the intervention, action plans might be less relevant. Nevertheless, using a guided step-by-step approach to generate action plans resulted in highly instrumental and specific action plans and might be integrated into other interventions concerning changes in health behaviour.

Trial Registration

Netherlands Trial Register: NTR 3706, ClinicalTrials.gov: NCT01909349.