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

Challenge of Pigs with Classical Swine Fever Viruses after C-Strain Vaccination Reveals Remarkably Rapid Protection and Insights into Early Immunity

Pre-emptive culling is becoming increasingly questioned as a means of controlling animal diseases, including classical swine fever (CSF). This has prompted discussions on the use of emergency vaccination to control future CSF outbreaks in domestic pigs. Despite a long history of safe use in endemic areas, there is a paucity of data on aspects important to emergency strategies, such as how rapidly CSFV vaccines would protect against transmission, and if this protection is equivalent for all viral genotypes, including highly divergent genotype 3 strains. To evaluate these questions, pigs were vaccinated with the Riemser® C-strain vaccine at 1, 3 and 5 days prior to challenge with genotype 2.1 and 3.3 challenge strains. The vaccine provided equivalent protection against clinical disease caused by for the two challenge strains and, as expected, protection was complete at 5 days post-vaccination. Substantial protection was achieved after 3 days, which was sufficient to prevent transmission of the 3.3 strain to animals in direct contact. Even by one day post-vaccination approximately half the animals were partially protected, and were able to control the infection, indicating that a reduction of the infectious potential is achieved very rapidly after vaccination. There was a close temporal correlation between T cell IFN-γ responses and protection. Interestingly, compared to responses of animals challenged 5 days after vaccination, challenge of animals 3 or 1 days post-vaccination resulted in impaired vaccine-induced T cell responses. This, together with the failure to detect a T cell IFN-γ response in unprotected and unvaccinated animals, indicates that virulent CSFV can inhibit the potent antiviral host defences primed by C-strain in the early period post vaccination

Neurobeachin, a Regulator of Synaptic Protein Targeting, Is Associated with Body Fat Mass and Feeding Behavior in Mice and Body-Mass Index in Humans

Neurobeachin (Nbea) regulates neuronal membrane protein trafficking and is required for the development and functioning of central and neuromuscular synapses. In homozygous knockout (KO) mice, Nbea deficiency causes perinatal death. Here, we report that heterozygous KO mice haploinsufficient for Nbea have higher body weight due to increased adipose tissue mass. In several feeding paradigms, heterozygous KO mice consumed more food than wild-type (WT) controls, and this consumption was primarily driven by calories rather than palatability. Expression analysis of feeding-related genes in the hypothalamus and brainstem with real-time PCR showed differential expression of a subset of neuropeptide or neuropeptide receptor mRNAs between WT and Nbea+/− mice in the sated state and in response to food deprivation, but not to feeding reward. In humans, we identified two intronic NBEA single-nucleotide polymorphisms (SNPs) that are significantly associated with body-mass index (BMI) in adult and juvenile cohorts. Overall, data obtained in mice and humans suggest that variation of Nbea abundance or activity critically affects body weight, presumably by influencing the activity of feeding-related neural circuits. Our study emphasizes the importance of neural mechanisms in body weight control and points out NBEA as a potential risk gene in human obesity

Neurobeachin Regulates Glutamate- and GABA-Receptor Targeting to Synapses via Distinct Pathways

Neurotransmission and synaptic strength depend on expression of post-synaptic receptors on the cell surface. Post-translational modification of receptors, trafficking to the synapse through the secretory pathway, and subsequent insertion into the synapse involves interaction of the receptor with A-kinase anchor proteins (AKAPs) and scaffolding proteins. Neurobeachin (Nbea), a brain specific AKAP, is required for synaptic surface expression of both glutamate and GABA receptors. Here, we investigated the role of Nbea-dependent targeting of postsynaptic receptors by studying Nbea interaction with synapse-associated protein 102 (SAP102/Dlg3) and protein kinase A subunit II (PKA II). A Nbea mutant lacking the PKA binding domain showed a similar distribution as wild-type Nbea in Nbea null neurons and partially restored GABA receptor surface expression. To understand the relevance of Nbea interaction with SAP102, we analysed SAP102 null mutant mice. Nbea levels were reduced by ~80 % in SAP102 null mice, but glutamatergic receptor expression was normal. A single-point mutation in the pleckstrin homology domain of Nbea (E2218R) resulted in loss of binding with SAP102. When expressed in Nbea null neurons, this mutant fully restored GABA receptor surface expression, but not glutamate receptor expression. Our results suggest that the PKA-binding domain is not essential for Nbea’s role in receptor targeting and that Nbea targets glutamate and GABA receptors to the synapse via distinct molecular pathways by interacting with specific effector proteins

Effectiveness of eHealth interventions in improving medication adherence for patients with chronic obstructive pulmonary disease or asthma: Systematic review

Background: Poor treatment adherence in patients with chronic obstructive pulmonary disease (COPD) or asthma is a global public health concern with severe consequences in terms of patient health and societal costs. A potentially promising tool for addressing poor compliance is eHealth. Objective: This review investigates the effects of eHealth interventions on medication adherence in patients with COPD or asthma. Methods: A systematic literature search was conducted in the databases of Cochrane Library, PsycINFO, PubMed, and Embase for studies with publication dates between January 1, 2000, and October 29, 2020. We selected randomized controlled trials targeting adult patients with COPD or asthma, which evaluated the effectiveness of an eHealth intervention on medication adherence. The risk of bias in the included studies was examined using the Cochrane Collaboration's risk of bias tool. The results were narratively reviewed. Results: In total, six studies focusing on COPD and seven focusing on asthma were analyzed. Interventions were mostly internet-based or telephone-based, and could entail telemonitoring of symptoms and medication adherence, education, counseling, consultations, and self-support modules. Control groups mostly comprised usual care conditions, whereas a small number of studies used a face-to-face intervention or waiting list as the control condition. For COPD, the majority of eHealth interventions were investigated as an add-on to usual care (5/6 studies), whereas for asthma the majority of interventions were investigated as a standalone intervention (5/7 studies). Regarding eHealth interventions targeting medication adherence for COPD, two studies reported nonsignificant effects, one study found a significant effect in comparison to usual care, and three reported mixed results. Of the seven studies that investigated eHealth interventions targeting medication adherence in asthma, three studies found significant effects, two reported nonsignificant effects, and two reported mixed effects. Conclusions: The mixed results on the effectiveness of eHealth interventions in improving treatment adherence for asthma and COPD are presumably related to the type, context, and intensity of the interventions, as well as to differences in the operationalization and measurement of adherence outcomes. Much remains to be learned about the potential of eHealth to optimize treatment adherence in COPD and asthma

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

2022 Bührmann, Van Daele, Rinn, De Witte, Lehr, Aardoom, Loheide-Niesmann, Smit and Riper.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