Feasibility and Acceptability of a Health App Platform Providing Individuals With a Budget to Purchase Preselected Apps to Work on Their Health and Well-Being: Quantitative Evaluation Study.

BACKGROUND: The potential of health apps for health promotion and disease prevention is widely recognized. However, uptake is limited due to barriers individuals face in finding suitable and trustworthy apps, such as the overwhelming amount of available health apps. Therefore, the health app platform "FitKnip" was developed, enabling individuals to purchase preselected, trustworthy health apps with a budget of 100 euros (a currency exchange rate of EUR €1=US $1.0831 is applicable). The platform aimed to empower individuals to improve their health and vitality, ultimately supporting a more healthy society. OBJECTIVE: The primary aim of this study was to evaluate the health app platform in terms of feasibility and acceptability. Potential effects on health empowerment and health outcomes were secondarily explored. METHODS: This quantitative study was part of a mixed methods study with a prospective pre-post interventional design. We collected web-based user data, and self-reported web-based questionnaires were collected over 5 measurements over an 8-month period. Use statistics were tracked on the platform, including the number of purchased apps and euros spent per user registered within the health app platform. We measured the user-friendliness of the health app platform using the System Usability Scale (SUS) and satisfaction using the Client Satisfaction Questionnaire-8 (CSQ-8) and several 10-point Likert items. We asked participants to indicate, on a scale from 1 (not at all) to 10 (completely), how much the health app platform contributed to various areas related to health empowerment. We assessed health-related quality of life by the 12-item Short-Form Health Survey (SF-12) and one's perceived level of stress by the 10-item Perceived Stress Scale (PSS-10). RESULTS: A total of 1650 participants were included, of whom 42% (685/1650) bought at least 1 app. The majority of those purchased one app (244/685, 35.6%). The health app platform was rated as user-friendly (SUS mean 66.5, SD 20.7; range 66.5-70.0), and the acceptability of the health app platform was moderate (CSQ-8 mean 20.0, SD 1.5; range 19.6-20.0). Results furthermore showed that participants were generally satisfied to highly satisfied with the ease of the payment system to purchase apps on the platform (median 8, IQR 7-10), the look and feel of the platform (median 7, IQR 6-8), as well as the provided budget of 100 euros (median 9, IQR 7-10). Participants were less satisfied with the amount (median 6, IQR 4-7) and diversity (median 6, IQR 4-7) of apps offered on the platform. CONCLUSIONS: A health app platform is a promising initiative to enhance public health. Feasibility and acceptability are critical for success, as they ensure that such a platform is accessible, user-friendly, and meets end users' needs and preferences. This can help to increase uptake, engagement, and ultimately the platform's adoption and effectiveness.

Evaluation of completely online psychotherapy with app-support versus therapy as usual for clients with depression or anxiety disorder: A retrospective matched cohort study investigating the effectiveness, efficiency, client satisfaction, and costs.

INTRODUCTION: Depressive and anxiety disorders are common mental disorders ranking among the leading causes of global disease burden. Not all clients currently benefit from therapy and clients are looking for modern ways of therapy. Online psychotherapy is a promising option for better meeting clients' needs. Recently, a new psychotherapy concept has emerged that combines videoconferencing sessions with support through a mobile application. The latter allows for ecological momentary assessments and interventions, facilitates communication between patients and therapists in between sessions through chat, and allows for incorporating feedback-informed treatment principles. MATERIAL AND METHODS: The study was a retrospective observational matched cohort study, comparing online psychotherapy with Therapy As Usual (TAU) for clients with depressive or anxiety disorders. Data were obtained via questionnaires, which are part of standard clinical care. Primary outcomes included general mental functioning, and symptoms of depression and anxiety. Secondary outcomes were efficiency, client satisfaction, and therapy costs. Primary endpoints were analyzed using linear mixed models analysis, with an interaction term between time and group. Secondary outcomes were analyzed using linear regression. RESULTS: Larger improvements were observed in the online compared to the TAU group for general mental functioning and depressive disorder (i.e., General mental functioning: B = -8.50, 95 CI: -15.01 - -1.97, p = 0.011; Depressive disorder: B = - 3.66, 95 % CI: -5.79 - -1.54p < 0.01). No significant differences in change over time between the two groups were observed for anxiety disorder (B = -3.64, 95 % CI: (-13.10 - 5.82) p = 0.447). The total number of sessions was significantly higher in the online psychotherapy group than in TAU (B = 3.71, p < 0.01), although clients were matched on treatment time in weeks. Treatment session duration in minutes was comparable across the groups. DISCUSSION: Online psychotherapy with app support showed to be a promising alternative to TAU for depressive and anxiety disorders. More research is needed to evaluate the effectiveness, cost-effectiveness and client satisfaction of online psychotherapy compared to TAU, such as randomized controlled trials or studies multiple baseline series designs, and in-depth qualitative research.

A Health App Platform Providing a Budget to Purchase Preselected Apps as an Innovative Way to Support Public Health: Qualitative Study With End Users and Other Stakeholders.

BACKGROUND: eHealth has the potential to improve health outcomes. However, this potential is largely untapped. Individuals face an overload of apps and have difficulties choosing suitable apps for themselves. In the FitKnip experiment, individuals were given access to a health app platform, where they could purchase reliable preselected health apps with a personal budget of €100 (US $107.35). By conducting a prospective study, we aimed to scientifically evaluate the FitKnip experiment as an innovative way to improve population health. OBJECTIVE: The aim of the experiment was to scientifically evaluate the FitKnip experiment as an innovative way to improve population health. More specifically, we conducted an in-depth qualitative evaluation of the concept and acceptability of FitKnip, its perceived impact on health empowerment, as well as the roles of stakeholders for the future implementation of a health app platform through focus group interviews. METHODS: This study followed a phenomenological research design and included 7 focus group interviews with end users and 1 with stakeholders, held between July and December 2020. End users were recruited through various institutions in the Netherlands, for example, insurance companies and local governments. All focus groups were semistructured using interview guides and were held via videoconferencing due to the COVID-19 pandemic measures. Each participant received access to a health app platform where they were enabled to purchase reliable, preselected health apps with a budget of €100 (US $107.35). The budget was valid for the entire research period. The health app platform offered 38 apps. A third party, a health care coalition, selected the apps to be included in FitKnip. The analyses were conducted according to the principles of the Framework Method. RESULTS: A priori formulated themes were concept, acceptability, health empowerment, and outcomes, and the roles of stakeholders for the future implementation of a health app platform. Both end users (n=31) and stakeholders (n=5) were enthusiastic about the concept of a health app platform. End users indicated missing apps regarding physical health and lifestyle and needing more guidance toward suitable apps. End users saw health empowerment as a precondition to using a health app platform and achieving health outcomes depending on the purchased mobile apps. End users and stakeholders identified potential providers and financing parties of FitKnip. Stakeholders recommended the establishment of a reputable national or international quality guidelines or certification for health and wellbeing apps, that can demonstrate the quality and reliability of mobile health applications. CONCLUSIONS: This study showed the need for a personalized and flexible platform. Next to this, a deeper understanding of the roles of stakeholders in such initiatives is needed especially on financing and reimbursement of health promotion and digital health services. A personalized, flexible health app platform is a promising initiative to support individuals in their health.

The feasibility of using Apple's ResearchKit for recruitment and data collection: Considerations for mental health research.

In 2015, Apple launched an open-source software framework called ResearchKit. ResearchKit provides an infrastructure for conducting remote, smartphone-based research trials through the means of Apple's App Store. Such trials may have several advantages over conventional trial methods including the removal of geographic barriers, frequent assessments of participants in real-life settings, and increased inclusion of seldom-heard communities. The aim of the current study was to explore the feasibility of participant recruitment and the potential for data collection in the non-clinical population in a smartphone-based trial using ResearchKit. As a case example, an app called eMovit, a behavioural activation (BA) app with the aim of helping users to build healthy habits was used. The study was conducted over a 9-month period. Any iPhone user with access to the App Stores of The Netherlands, Belgium, and Germany could download the app and participate in the study. During the study period, the eMovit app was disseminated amongst potential users via social media posts (Twitter, Facebook, LinkedIn), paid social media advertisements (Facebook), digital newsletters and newspaper articles, blogposts and other websites. In total, 1,788 individuals visited the eMovit landing page. A total of 144 visitors subsequently entered Apple's App Store through that landing page. The eMovit product page was viewed 10,327 times on the App Store. With 79 installs, eMovit showed a conversion rate of 0.76% from product view to install of the app. Of those 79 installs, 53 users indicated that they were interested to participate in the research study and 36 subsequently consented and completed the demographics and the participants quiz. Fifteen participants completed the first PHQ-8 assessment and one participant completed the second PHQ-8 assessment. We conclude that from a technological point of view, the means provided by ResearchKit are well suited to be integrated into the app process and thus facilitate conducting smartphone-based studies. However, this study shows that although participant recruitment is technically straightforward, only low recruitment rates were achieved with the dissemination strategies applied. We argue that smartphone-based trials (using ResearchKit) require a well-designed app dissemination process to attain a sufficient sample size. Guidelines for smartphone-based trial designs and recommendations on how to work with challenges of mHealth research will ensure the quality of these trials, facilitate researchers to do more testing of mental health apps and with that enlarge the evidence-base for mHealth.

Development and implementation of guidelines for the management of depression: a systematic review.

OBJECTIVE: To evaluate the development and implementation of clinical practice guidelines for the management of depression globally. METHODS: We conducted a systematic review of existing guidelines for the management of depression in adults with major depressive or bipolar disorder. For each identified guideline, we assessed compliance with measures of guideline development quality (such as transparency in guideline development processes and funding, multidisciplinary author group composition, systematic review of comparative efficacy research) and implementation (such as quality indicators). We compared guidelines from low- and middle-income countries with those from high-income countries. FINDINGS: We identified 82 national and 13 international clinical practice guidelines from 83 countries in 27 languages. Guideline development processes and funding sources were explicitly specified in a smaller proportion of guidelines from low- and middle-income countries (8/29; 28%) relative to high-income countries (35/58; 60%). Fewer guidelines (2/29; 7%) from low- and middle-income countries, relative to high-income countries (22/58; 38%), were authored by a multidisciplinary development group. A systematic review of comparative effectiveness was conducted in 31% (9/29) of low- and middle-income country guidelines versus 71% (41/58) of high-income country guidelines. Only 10% (3/29) of low- and middle-income country and 19% (11/58) of high-income country guidelines described plans to assess quality indicators or recommendation adherence. CONCLUSION: Globally, guideline implementation is inadequately planned, reported and measured. Narrowing disparities in the development and implementation of guidelines in low- and middle-income countries is a priority. Future guidelines should present strategies to implement recommendations and measure feasibility, cost-effectiveness and impact on health outcomes.

Effectiveness of eHealth Interventions in Improving Treatment Adherence for Adults With Obstructive Sleep Apnea: Meta-Analytic Review.

BACKGROUND: Poor adherence to continuous positive airway pressure (CPAP) treatment by adults with obstructive sleep apnea (OSA) is a common issue. Strategies delivered by means of information and communication technologies (ie, eHealth) can address treatment adherence through patient education, real-time monitoring of apnea symptoms and CPAP adherence in daily life, self-management, and early identification and subsequent intervention when device or treatment problems arise. However, the effectiveness of available eHealth technologies in improving CPAP adherence has not yet been systematically studied. OBJECTIVE: This meta-analytic review was designed to investigate the effectiveness of a broad range of eHealth interventions in improving CPAP treatment adherence. METHODS: We conducted a systematic literature search of the databases of Cochrane Library, PsycINFO, PubMed, and Embase to identify relevant randomized controlled trials in adult OSA populations. The risk of bias in included studies was examined using seven items of the Cochrane Collaboration risk-of-bias tool. The meta-analysis was conducted with comprehensive meta-analysis software that computed differences in mean postintervention adherence (MD), which was defined as the average number of nightly hours of CPAP use. RESULTS: The meta-analysis ultimately included 18 studies (N=5429 adults with OSA) comprising 22 comparisons between experimental and control conditions. Postintervention data were assessed at 1 to 6 months after baseline, depending on the length of the experimental intervention. eHealth interventions increased the average nightly use of CPAP in hours as compared with care as usual (MD=0.54, 95% CI 0.29-0.79). Subgroup analyses did not reveal significant differences in effects between studies that used eHealth as an add-on or as a replacement to care as usual (P=.95), between studies that assessed stand-alone eHealth and blended strategies combining eHealth with face-to-face care (P=.23), or between studies of fully automated interventions and guided eHealth interventions (P=.83). Evidence for the long-term follow-up effectiveness of eHealth adherence interventions remains undecided owing to a scarcity of available studies and their mixed results. CONCLUSIONS: eHealth interventions for adults with OSA can improve adherence to CPAP in the initial months after the start of treatment, increasing the mean nightly duration of use by about half an hour. Uncertainty still exists regarding the timing, duration, intensity, and specific types of eHealth interventions that could be most effectively implemented by health care providers.