Remote Interaction Research Articles

Underwater Vibration Sensor to Enable Automated and Contactless Voice Recognition

AbstractIndividuals suffering from voice disabilities have limited access to currently available automation technologies that operate through voice commands. To address this issue, an alternative voice recognition approach is essential without directly monitoring the audio signals generated from the vocal cord. In this work, the design of a chemically reactive and conductive sponge is reported to create an underwater vibration sensor with a fast response time and high sensitivity, through orthogonal modulation of conductivity (40–2150 kΩ), water repellence (0°–154°) and mechanical properties (0.32–2.63 MPa). This class of porous sponge sensors enables the identification of subtle water waves generated at the air–water interface and extends its utility to detecting a variety of locomotion (squatting, jumping, walking, etc.), as well as automated voice recognition using a deep learning model without direct contact with the human body. Overall, this underwater vibration sensor provides a novel basis for remote interaction with automated technologies, which finds use in medical diagnostics, human‐machine interfaces, and underwater communication systems.

Impact of remote social interaction during the COVID-19 pandemic on the cognitive and psychological status of older adults with and without cognitive impairment: A randomized controlled study.

Social isolation and loneliness have both been associated with psychological health and cognitive decline in older adults. This study investigated the impact of social interaction through remote communication technologies during the COVID-19 pandemic on the cognitive and psychological status of older adults with and without cognitive impairment. Participants were recruited from Boston (USA) and Chieti (Italy). The study used a randomized single-blinded controlled crossover design with an intervention (remote social conversations with research staff over 20-minute video or telephone calls three times per week) and a passive control condition, each one of 4-weeks duration. The primary outcome was a composite cognitive score change from baseline to week 4. Secondary outcomes included scales for mood, anxiety, and loneliness. Out of 196 participants recruited from April 2020 to April 2021, 17% dropped out. Based on the blind MoCA, 52% had cognitive impairment, and 25% were at risk of social isolation according to the Lubben social network scale. We observed that larger social networks were linked to better cognitive status and lower depression and anxiety levels, while loneliness was directly associated to depression severity. Older adults with cognitive impairment exhibited higher levels of depression and anxiety and were at greater risk for social isolation. In terms of the intervention, 91% preferred telephone over video calls. The intervention did not lead to improvements in cognitive or psychological scores. More work is needed to assess the utility of this intervention for the support of a heterogenous cross-cultural sample of older adults at-risk for social isolation, including individuals with cognitive impairment. Future research should explore longer intervention periods, categorize participants by call type, and target those meeting social isolation criteria. ClinicalTrials.gov NCT04480112.

Building a community of practice around a community of inquiry: an examination of EFL students' perceptions of a virtual internship

In response to the new policy of English department, the internship program has been shifted to virtual programmes. As part of this initiative, the university has collaborated with other educational sectors to offer a virtual English as a Foreign Language (EFL) internship programme aimed at training individuals as EFL teachers. The aim of the study was to investigate student perceptions of dynamic social structures and communities of practice in technologically mediated environments, particularly in relation to virtual internships. The authors recognised a gap in research regarding how EFL students create meaningful learning experiences and how they build their practical knowledge in mediated communication environments. Quantitative and qualitative research methods were used. 50 students comprised the study subjects. The data were collected from multiple sources: interviews, students’ reflections, and community of inquiry and practice survey instruments. The findings revealed that an unprepared virtual environment led to social anxiety and challenges related to real-world work experience. The study suggests that evidence-based interventions in technologically mediated, virtual learning environments can help to resolve study findings with this goal: fostering a sense of belongingness and community that can promote effective remote interactions between learners and their teachers to ensure that internships serve students best.

Neighbourhood-based participatory action research with older adults: Facilitating participation through virtual and remote methods

Participatory action research (PAR) is an effective means of collaborating with older adults to support community change. Limited PAR literature exists in which older adults catalyse social change within neighbourhoods, particularly using virtual methods. In this paper, we discuss a virtual PAR process with older adults that occurred during the COVID-19 pandemic, and the results of inquiry into our application of PAR principles. We conducted PAR in a collective involving university researchers, older adult residents and community partners in an urban core neighbourhood in a mid-sized Canadian city and focused on enhancing daily life for older adults. The PAR project emerged through reflection on previous ethnographic findings regarding older adults’ daily life in neighbourhoods. Our PAR collective collaboratively identified a need among older adults for more accessible information about community resources. To support older adults’ participation and access to community information, the PAR collective created and distributed a free neighbourhood resource booklet, in print and digital formats, to promote equitable access. We evaluated the impact of the booklet through a survey and discussions with community partners. During our PAR process we found challenges and solutions related to using technology, engaging in discussion during virtual meetings, and making collaborative decisions. A combination of in-person, remote and online interactions seemed to facilitate relationship development amongst co-researchers and completion of the project. Future PAR projects would benefit from incorporating in-person, remote and online methods from the outset, as well as ways to support older adults in using and accessing technology. We further noted the value of a local resource booklet, in print and digital formats, in promoting neighbourhood information sharing.

Analysis of the provision of medical care using telemedicine technologies at the endocrinology research centre

In the first months after the pandemic of the COVID-19, the provision of medical care through telemedicine technologies took a leading position, in particular regarding endocrine nosologies. Meanwhile, at present, comprehensive information on telecommunications interaction between doctors of various medical organizations of the regions of the Russian Federation and employees of federal centers is insufficient, which determines the relevance of studying this topic. Analysis of the provision of medical care in remote interaction of medical workers using telemedicine technologies («doctor-doctor») between the Endocrinology Research Centre and the regions of the Russian Federation in 2019-2023. A single-center, observational, single-sample study was conducted, including completed planned and urgent telemedicine consultations in the format of «doctor-doctor « in the fields of «endocrinology» and «pedia-tric endocrinology», conducted through a telemedicine system for remote consultations at federal and regional levels between 2019 and 2023. Data on the referral rate of medical personnel from the regions of the Russian Federation to the Endocrinology Research Centre for telemedicine consultations were analyzed, including annual dynamics of treatment, frequency of referrals from each region, nosological structure of referrals, and number of patients admitted to the center based on the results of these consultations. Analysis of interdepartmental cooperation between the Endocrinology Research Centre and other federal centers was also performed. In the period from 2019-2023, 14,475 telemedicine consultations «doctor-doctor» were conducted. In 2019, medical workers from 78 regions of the Russian Federation applied to the Endocrinology Research Centre. By 2023, this figure has increased to 88 (including newly annexed territories). The Yamalo-Nenets Autonomous Okrug, Tambov Region and Astrakhan Region were the leading regions in terms of the circulation of medicines at the Endocrinology Research Centre. In the nosological structure, the largest number of consultations in adult patients were conducted for acromegaly and primary hyperparathyroidism, in children for stunting and type 1 diabetes mellitus. In the period from 2019-2023, the Endocrinology Research Centre sent a total of 300 «outgoing» requests to 17 medical organizations. Consulting with the use of telemedicine technologies has become a convenient and multifunctional way of providing medical care. Further analysis of the place of telemedicine in practical healthcare will expand its capabilities, including considering the introduction of financing by the territorial fund of compulsory medical insurance for this area of medical activity.

Remote interaction of participants in civil transactions and methods of their individualization, used in pre-revolutionary Russia

Remote interaction of participants in civil transactions and methods of their individualization, used in pre-revolutionary Russia

Exact Solutions and Bounds for the Thermal Conductivity Coefficient of a Dispersed Medium

Exact solutions for the thermal conductivity coefficient of a two-phase dispersed medium are obtained using the most general physical principles of locality and symmetry. Two solutions define the well-known Hashin–Shtrikman bounds. The third solution, invariant under the phase inversion transformation, significantly narrows the Hashin–Shtrikman boundaries; this is confirmed by comparison with numerous experiments by other authors. It has been shown that taking into account the remote interaction of dispersed particles at their increased concentration only slightly (less than 3%) affects the result.

What is the impact of demand patterns on integrated online-offline and buy-online-pickup in-store (BOPS) retail in a smart supply chain management?

Retailers aim to provide in-person and remote interactions to accelerate purchases through hybrid methods, which introduce additional delivery and emissions loads but create a seamless shopping experience. The challenges of unified inventory, customer information, pricing, demand forecasting complications, and order fulfillment are met successfully in the hybrid methods. Here, a smart supply chain management that integrates traditional physical presence with cloud-based and hybrid buy-online-pickup in-store channels is optimized to meet customer demand in different demand patterns. The demand patterns considered are linear, cubic, and normalized functions of the selling price, the advertising cost, and the product lifetime. The article incorporates sustainable supply chain and omnichannel strategies to optimize supply chain performance and profitability. The paper compares the results of the proposed models with traditional supply chain models and provides some managerial insights and suggestions for online retailers. Numerical simulation reveals that nonlinear price dependence in demand provides an opportunity for higher promotional investment with a substantial rise in optimal selling price and overall profit. The shift-to-imperfect probability is seen to be the volatile component in the solution surface. The markup of the offline channel has a greater impact than buy-online-pickup in-store markup.

Analyzing equitable access in a remote socio-enactive setting: A case study

Ubiquitous Computing as proposed by Mark Weiser in 1991 creates a huge diversity of interaction possibilities through, e.g., sensors, actuators, physiological data, wearables, to name but a few. Providing equitable access to everyone in these unpredictable interaction environments is already a challenge. Additionally, the Covid-19 pandemic brought new challenges to these scenarios by adding remote interactions. Ubiquitous computing remote environments should provide equitable access to everyone, including people with disabilities. To better understand such issues and contribute to their solution, we studied and evaluated access in the Aquarela Virtual workshop using the UbiAccess evaluation instrument. This workshop offered a remote ubiquitous computing environment within the context of a kindergarten school. We used thematic analysis to understand the interaction needs of an Autistic Spectrum Disorder (ASD) child during the workshop. This paper extends previous research with additional data and its analysis - in particular, concerning information provided by the teacher responsible for the specific classroom, and data on the ASD child contributing to: 1) Reflections about remote ubiquitous environments and equitable access; 2) Benefits of ubiquitous computing interactions as regards the ASD child; and 3) Coverage of the UbiAccess evaluation instrument.

A human visual attention analysis model for remote interaction interface of unmanned agricultural vehicles

When unmanned agricultural vehicles (UAVs) encounter unexpected failures or incidents during autonomous operations, a highly efficient remote human–machine interaction (HMI) interface is needed to assist in the manual joint control process. The highly complex cognitive mechanisms and visual characteristics of humans make it difficult to design efficient human–machine interfaces. Therefore, a human visual attention analysis model was proposed based on fully convolutional networks for the remote interaction interface of unmanned agricultural vehicles. First, visual attention experimental software combined with gaze-contingent real-time simulation methods was developed to build the dataset. Subsequently, the human visual attention analysis model (HVAAM) is constructed, and the corresponding training strategy is proposed, which is trained on the ILSVRC2012 standard and self-constructed datasets. The accuracy of the HVAAM analysis on the test dataset was validated. Ultimately, a human–machine interaction test of random failure warning for remote monitoring interface of unmanned plowing operation is performed with a self-developed unmanned electric tractor as the carrier. In the test dataset, the average analysis accuracy of HVAAM was 79.2 %, and the proposed training strategy led to a 20.7 % improvement in the model accuracy. In the unmanned electric tractor human–machine interaction test, HVAAM achieved 77.9 % accuracy in the visual attention analysis of the monitoring interface. This study can effectively facilitate the analysis, design, and optimization of remote monitoring interfaces for unmanned agricultural vehicles.

Preferences for pre-exposure prophylaxis delivery via online pharmacy among potential users in Kenya: a discrete choice experiment.

Oral pre-exposure prophylaxis (PrEP) is highly effective, but coverage remains low in high HIV prevalence settings. Initiating and continuing PrEP remotely via online pharmacies is a promising strategy to expand PrEP uptake, but little is known about potential users' preferences. We conducted a discrete choice experiment (DCE) to assess preferences for online pharmacy PrEP services. We partnered with MYDAWA, an online pharmacy in Nairobi, Kenya. Eligibility criteria were: ≥18 years, not known HIV positive, interested in PrEP. The DCE contained four attributes: PrEP eligibility assessment (online self-assessed, guided), HIV test type (provider administered, oral HIV self-test [HIVST], blood-based HIVST), clinical consultation (remote, in-person) and user support options (text messages, phone/video call, email). Additionally, participants indicated whether they were willing to uptake their selected service. The survey was advertised on MYDAWA's website; interested participants met staff in-person at a convenient location to complete the survey from 1 June to 20 November 2022. We used conditional logit modelling with an interaction by current PrEP use to estimate overall preferences and latent class analysis (LCA) to assess preference heterogeneity. Overall, 772 participants completed the DCE; the mean age was 25 years and 54% were female. Most participants indicated a willingness to acquire online PrEP services, with particularly high demand among PrEP-naive individuals. Overall, participants preferred remote clinical consultation, HIV self-testing, online self-assessment and phone call user support. The LCA identified three subgroups: the "prefer online PrEP with remote components" group (60.3% of the sample) whose preferences aligned with the main analysis, the "prefer online PrEP with in-person components" group (20.7%), who preferred in-person consultation, provider-administered HIV testing, and guided assessment, and the "prefer remote PrEP (18.9%)" group who preferred online PrEP services only if they were remote. Online pharmacy PrEP is highly acceptable and may expand PrEP coverage to those interested in PrEP but not accessing services. Most participants valued privacy and autonomy, preferring HIVST and remote provider interactions. However, when needing support for questions regarding PrEP, participants preferred phone/SMS contact with a provider. One-fifth of participants preferred online PrEP with in-person components, suggesting that providing multiple options can increase uptake.

Realizing smart scanning transmission electron microscopy using high performance computing.

Scanning Transmission Electron Microscopy (STEM) coupled with Electron Energy Loss Spectroscopy (EELS) presents a powerful platform for detailed material characterization via rich imaging and spectroscopic data. Modern electron microscopes can access multiple length scales and sampling rates far beyond human perception and reaction time. Recent advancements in machine learning (ML) offer a promising avenue to enhance these capabilities by integrating ML algorithms into the STEM-EELS framework, fostering an environment of active learning. This work enables the seamless integration of STEM with High-Performance Computing (HPC) systems. This integration is facilitated by our developed server software, written in Python, which acts as a wrapper over DigitalMicrograph (version 3.5) hardware modules to enable remote computer interactions. We present several implemented workflows that exemplify this integration. These workflows include sophisticated techniques such as object finding and deep kernel learning. Through these developments, we demonstrate how the fusion of STEM-EELS with ML and HPC enhances the efficiency and scope of material characterization for all of STEM available globally having Gatan, Inc. image filter installed on them. The codes are available on GitHub.

Aspects of application of digital solutions in primary health care

All over the world, with regard to digitalization in the provision of primary health care, issues of the principles of the cost-effective resource system for the provision of medical services covering all residents (any category of the population), ways to achieve other goals set for the health system at the territorial or regional level are being discussed. Depending on the main goals and principles set out in national legislation, including legislation in the field of health protection, approaches to achieving the Sustainable Development Goals and, accordingly, approaches to organizing the digitalization of medical care differ in different States. The issues of automating the processes of a medical organization and generating relevant information relate to the ways of using artificial intelligence to free up time for doctors, reduce the administrative burden on medical service providers. The level of digital medical literacy, combined with modern possibilities of remote interaction in the patient-medical worker format, can be decisive at the first stage of seeking medical help - with remote patient triage, which is an indispensable tool for determining both the need for assistance and the urgency of providing assistance. The experience of remote triage of patients by non-medical staff provided by the NHS Pathways clinical decision support system, used by the National Health Service of England, has freed up general practitioners (doctors and nurses) to provide other forms of medical care. In 2005, nurses and, to a lesser extent, general practitioners in England accounted for 100% of the staff handling telephone calls in the similar NHS Direct remote consultation system. The foreign experience of patient teletriage in our country will be limited by the legislation of the Russian Federation in the field of health protection, however, some existing restrictions, taking into account the assessment of risks to patients brought by innovative development, may be revised during the implementation of the «Program of experimental legal regime in the field of digital innovations in the field of medical activity, including the use of telemedicine technologies and technologies for collecting and processing information about the state of health and diagnoses of citizens», which will expire on 08/01/2026.

DCSS-UNet: UNet based on State Space Model for Polyp Segmentation

Early and accurate segmentation of medical images can provide valuable information for medical treatment. In recent years, the automatic and accurate segmentation of polyps in colonoscopy images has received extensive attention from the research community of artificial intelligence and computer vision. Many researchers have conducted in-depth research on models based on CNN and Transformer. However, CNN have limited ability to model remote dependencies, which makes it challenging to fully utilize semantic information in images. On the other hand, the complexity of the secondary computation poses a challenge to the transformer. Recently, state-space models (SSMS), such as Mamba, have been recognized as a promising approach. They not only show superior performance in remote interaction, but also maintain linear computational complexity. Inspired by Mamba, we propose DCSS-UNet, where we utilize visual state space (VSS) blocks in VMamba to capture a wide range of contextual information. In the Skip connection phase, we propose Skip Connects Feature Attention modules(SFA) to better communicate information from the encoder. In the decoder stage, we innovatively combined the Temporal Fusion Attention Module(TFAM) to effectively fuse the feature information. In addition, we introduced a custom Loss calculation method, Tversky Loss, for the model to achieve faster convergence and improve segmentation along polyp boundaries. Our model was trained on the Kvasir-SEG and CVC-ClinicDB datasets, and validated on datasets Kvasir-SEG, CVC-ColonDB, CVC-300, and ETIS. The results show that the model achieves good segmentation accuracy and generalization performance with a low number of parameters. We are 6.1% ahead in the Kavirs-SEG dataset and 3.1% ahead in the CVC-ClinicDB dataset compared to VM-UNet.

Remote Interactions between tropical cyclones: The case of Hurricane Michael and Leslie's high predictability uncertainty

The study explores Hurricane Michael's impact on Hurricane Leslie's trajectory predictability using ECMWF and NCEP ensemble systems. A clustering method focused on tropical cyclones is used to identify potential paths for Leslie: Cluster 1 accurately predicted Leslie's direction towards the Iberian Peninsula, whereas Clusters 2 and 3 indicated a southern recurve near the Canary Islands. Analysis of potential vorticity and irrotational wind at upper levels showed a significant interaction between Michael, ridge, and trough across the jet stream from +12 h after initialization. Cluster 1 showed a stronger Michael promoting upper-level wind divergence greatest, modifying the jet stream configuration around the ridge and downstream. Alterations in the jet stream's configuration, functioning as a waveguide, propagated downstream, guiding Leslie towards the Iberian Peninsula. Clusters 2 and 3 indicated the trough's failure to incorporate Leslie, resulting in a recurve of the trajectory around the Azores anticyclone. This research enhances comprehension of the interaction between two tropical cyclones via synoptic Rossby wave flow. Moreover, the conceptual framework can aid operational meteorologists in identifying the sources of uncertainty, particularly in track forecasts under synoptic conditions analogous to those examined in this study.

In-person versus remote (mHealth) delivery for a responsive parenting intervention in rural Kenya: a cluster randomized controlled trial

BackgroundAn estimated 43% of children under age 5 in low- and middle-income countries (LMICs) experience compromised development due to poverty, poor nutrition, and inadequate psychosocial stimulation. Numerous early childhood development (ECD) parenting interventions have been shown to be effective at improving ECD outcomes, at least in the short-term, but they are (a) still too expensive to implement at scale in low-resource and rural settings, and (b) their early impacts tend to fade over time. New approaches to deliver effective ECD parenting interventions that are low-cost, scalable, and sustainable are sorely needed.MethodsOur study will experimentally test a traditional in-person group-based delivery model for an evidence-based ECD parenting intervention against a hybrid-delivery model that increasingly substitutes in-person meetings with remote (mHealth) delivery via smartphones, featuring audiovisual content and WhatsApp social interactions and learning. We will assess the relative effectiveness and cost of this hybrid-delivery model compared to in-person delivery and will extend the interventions over two years to increase their ability to sustain changes in parenting behaviors and ECD outcomes longer-term. Our evaluation design is a cluster Randomized Controlled Trial (cRCT) across 90 villages and approximately 1200 households. Midline and endline surveys collected 12 and 24 months after the start of the interventions, respectively, will examine short- and sustained two-year intention-to-treat impacts on primary outcomes. We will also examine the mediating pathways using mediation analysis. We hypothesize that a hybrid-delivery ECD intervention will be lower in cost, but remote interactions among participants may be an inferior substitute for in-person visits, leaving open the question of the most cost-effective program.DiscussionOur goal is to determine the best model to maximize the intervention’s reach and sustained impacts to improve child outcomes. By integrating delivery into the ongoing operations of local Community Health Promoters (CHPs) within Kenya’s rural health care system, and utilizing new low-cost technology, our project has the potential to make important contributions towards discovering potentially scalable, sustainable solutions for resource-limited settings.Trial RegistrationNCT06140017 (02/08/2024) AEARCTR0012704.

Magnetic stirring with iron oxide nanospinners accretes neurotoxic Aβ42 oligomers into phagocytic clearable plaques for Alzheimer's disease treatment

An increasing number of medications have been explored to treat the progressive and irreversible Alzheimer's disease (AD) that stands as the predominant form of dementia among neurodegenerative ailments. However, assertions about toxic side effects of these drugs are a significant hurdle to overcome, calling for drug-free nanotherapeutics. Herein, a new therapeutic strategy devoid of conventional drugs or other cytotoxic species was developed. The constructed superparamagnetic iron oxide nanoparticles (SPIONs) nanospinners can accrete neurotoxic β-amyloid 42 oligomers (oAβ42) into aggregated magnetic plaques (mpAβ) by mechanical rotating force via remote interaction between nanoparticles and the applied magnetic field. While the cellular uptake of mpAβ attained from the magnetic stirring treatment by neuronal cells is severely limited, the facile phagocytic uptake of mpAβ by microglial cells leads to the polarization of the brain macrophages to M2 phenotype and thus the increased anti-inflammatory responses to the treatment. The SPION stirring treatment protects the AD mice from memory deterioration and maintain cognitive ability as evidenced from both nesting and Barnes maze tests. The examination of the oAβ42 injected brain tissues with the stirring treatment showed significant amelioration of functional impairment of neurons, microglia, astrocytes and oligodendrocytes alongside no obvious tissue damage caused by stirring meanwhile complete degradation of SPION was observed at day 7 after the treatment. The in vitro and animal data of this work strongly corroborate that this new modality of undruggable stirring treatment with SPIONs provides a new feasible strategy for developing novel AD treatments.

Spatial Augmented Reality for Expanding the Reach of Individuals with Tremor beyond Their Physical Limits.

Tremor is a prevalent neurological disorder characterized by involuntary shaking or trembling of body parts. This condition impairs fine motor skills and hand coordination to varying degrees and can even affect overall body mobility. As a result, tremors severely disrupt the daily lives and work of those affected, significantly limiting their physical activity space. This study developed an innovative spatial augmented reality (SAR) system aimed at assisting individuals with tremor disorders to overcome their physical limitations and expand their range of activities. The system integrates eye-tracking and Internet of Things (IoT) technologies, enabling users to smoothly control objects in the real world through eye movements. It uses a virtual stabilization algorithm for stable interaction with objects in the real environment. The study comprehensively evaluated the system's performance through three experiments: (1) assessing the effectiveness of the virtual stabilization algorithm in enhancing the system's ability to assist individuals with tremors in stable and efficient interaction with remote objects, (2) evaluating the system's fluidity and stability in performing complex interactive tasks, and (3) investigating the precision and efficiency of the system in remote interactions within complex physical environments. The results demonstrated that the system significantly improves the stability and efficiency of interactions between individuals with tremor and remote objects, reduces operational errors, and enhances the accuracy and communication efficiency of interactions.

In-person versus remote (mHealth) delivery for a responsive parenting intervention in rural Kenya: A cluster randomized controlled trial.

An estimated 43% of children under age 5 in low- and middle-income countries (LMICs) experience compromised development due to poverty, poor nutrition, and inadequate psychosocial stimulation. Numerous early childhood development (ECD) parenting interventions have been shown to be effective at improving ECD outcomes, at least in the short-term, but they are a) still too expensive to implement at scale in low-resource and rural settings, and b) their early impacts tend to fade over time. New approaches to deliver effective ECD parenting interventions that are low-cost, scalable, and sustainable are sorely needed. Our study will experimentally test a traditional in-person group-based delivery model for an evidence-based ECD parenting intervention against a hybrid-delivery model that increasingly substitutes in-person meetings for a remote (mHealth) delivery via smartphones, featuring audiovisual content and WhatsApp social interactions and learning. We will assess the relative effectiveness and cost of this hybrid-delivery model against purely in-person delivery and will extend the interventions over two years to increase their ability to sustain changes in parenting behaviors and ECD outcomes longer-term. Our evaluation design is a cluster Randomized Controlled Trial (cRCT) across 90 villages and approximately 1200 households. Midline and endline surveys collected 12 and 24 months after the start of the interventions, respectively, will examine short- and sustained two-year intention-to-treat impacts on primary outcomes. We will also examine the mediating pathways using Mediation Analysis. We hypothesize that a hybrid-delivery ECD intervention will be lower cost, but remote interactions among participants may be an inferior substitute for in-person visits, leaving open the question of the most cost-effective program. Our goal is to determine the best model to maximize the intervention's reach and sustained impacts to improve child outcomes. By integrating delivery into the ongoing operations of local Community Health Promoters (CHPs) within Kenya's rural health care system, and utilizing new low-cost technology, our project has the potential to make important contributions towards discovering potentially scalable, sustainable solutions for resource-limited settings. NCT06140017 (02/08/2024) AEARCTR0012704.

Patient safety in remote primary care encounters: multimethod qualitative study combining Safety I and Safety II analysis

BackgroundTriage and clinical consultations increasingly occur remotely. We aimed to learn why safety incidents occur in remote encounters and how to prevent them.Setting and sampleUK primary care. 95 safety incidents...