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

Digital Interventions for Treating Post-COVID or Long-COVID Symptoms: Scoping Review

BackgroundPatients with post-COVID/long-COVID symptoms need support, and health care professionals need to be able to provide evidence-based patient care. Digital interventions can meet these requirements, especially if personal contact is limited. ObjectiveWe reviewed evidence-based digital interventions that are currently available to help manage physical and mental health in patients with post-COVID/long-COVID symptoms. MethodsA scoping review was carried out summarizing novel digital health interventions for treating post-COVID/long-COVID patients. Using the PICO (population, intervention, comparison, outcome) scheme, original studies were summarized, in which patients with post-COVID/long-COVID symptoms used digital interventions to help aid recovery. ResultsFrom all scanned articles, 8 original studies matched the inclusion criteria. Of the 8 studies, 3 were “pretest” studies, 3 described the implementation of a telerehabilitation program, 1 was a post-COVID/long-COVID program, and 1 described the results of qualitative interviews with patients who used an online peer-support group. Following the PICO scheme, we summarized previous studies. Studies varied in terms of participants (P), ranging from adults in different countries, such as former hospitalized patients with COVID-19, to individuals in disadvantaged communities in the United Kingdom, as well as health care workers. In addition, the studies included patients who had previously been infected with COVID-19 and who had ongoing symptoms. Some studies focused on individuals with specific symptoms, including those with either post–COVID-19 or long-term symptoms, while other studies included patients based on participation in online peer-support groups. The interventions (I) also varied. Most interventions used a combination of psychological and physical exercises, but they varied in duration, frequency, and social dimensions. The reviewed studies investigated the physical and mental health conditions of patients with post-COVID/long-COVID symptoms. Most studies had no control (C) group, and most studies reported outcomes (O) or improvements in physiological health perception, some physical conditions, fatigue, and some psychological aspects such as depression. However, some studies found no improvements in bowel or bladder problems, concentration, short-term memory, unpleasant dreams, physical ailments, perceived bodily pain, emotional ailments, and perceived mental health. ConclusionsMore systematic research with larger sample sizes is required to overcome sampling bias and include health care professionals’ perspectives, as well as help patients mobilize support from health care professionals and social network partners. The evidence so far suggests that patients should be provided with digital interventions to manage symptoms and reintegrate into everyday life, including work

T-REX17 is a transiently expressed non-coding RNA essential for human endoderm formation

Long non-coding RNAs (lncRNAs) have emerged as fundamental regulators in various biological processes, including embryonic development and cellular differentiation. Despite much progress over the past decade, the genome-wide annotation of lncRNAs remains incomplete and many known non-coding loci are still poorly characterized. Here, we report the discovery of a previously unannotated lncRNA that is transcribed 230 kb upstream of the SOX17 gene and located within the same topologically associating domain. We termed it T-REX17 (Transcript Regulating Endoderm and activated by soX17) and show that it is induced following SOX17 activation but its expression is more tightly restricted to early definitive endoderm. Loss of T-REX17 affects crucial functions independent of SOX17 and leads to an aberrant endodermal transcriptome, signaling pathway deregulation and epithelial to mesenchymal transition defects. Consequently, cells lacking the lncRNA cannot further differentiate into more mature endodermal cell types. Taken together, our study identified and characterized T-REX17 as a transiently expressed and essential non-coding regulator in early human endoderm differentiation