Developing a smartphone app with UK migrants for UK migrants: lessons learned from focus group work

Abstract Background In 2018, 14% of people living in the UK were born abroad, yet we have a limited understanding of the broader determinants of their health. To address this knowledge gap, the Health on the MovE (HOME) smartphone application (app) study was conceived. Through app-based surveys, the study will examine how risk factors for health and well-being are distributed among migrants and how these vary over time since migration to the UK. There is a lack of research addressing the development of apps for longitudinal data collection in the general population - and we did not find any in migrant groups. Methods To better inform the design of the HOME app study, three workshops were held in 2018 and 2019, involving both migrants and App development experts. We used a semi-structured interview schedule focused on five themes: smartphones, apps and research, HOME app wireframe (screen-by-screen review of the app), types of surveys and survey schedules, resource section content, and participant engagement strategies. The participants were purposively sampled to reflect the migrant population arriving in the UK from non-EU countries. Results Migrants reported high smartphone use and were positive about the app design and app-based research. Concerns around privacy and data protection were highlighted and limits were suggested for the frequency of surveys and the number of questions used. Mental health was identified as a key topic for research. Participants requested the inclusion of resources concerning asylum claim procedures and immigrant and labour laws. Migrants advised that study recruitment material should clearly state the purpose and scope of the research and requested regular feedback on study outcomes. Conclusions The workshops provided important feedback and facilitated the co-production of the HOME app. Overall findings suggest that the study would be both acceptable to the migrant population and feasible for real-time data collection. Key messages The process identified potential barriers to the acceptability and feasibility of an app-based study for real-time data collection in the UK migrant population. Organising workshops with migrants allowed for an iterative process of co-production of the HOME app. Their critical comments resulted in subsequent changes to the app design and study methodology.

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The Study of Motor Winding Testing System for Inter-Turn with 30kV

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.278-280.831 ◽

2013 ◽

Vol 278-280 ◽

pp. 831-834 ◽

Cited By ~ 1

Author(s):

Xiao Sun ◽

Hao Zhou ◽

Xiang Jiang Lu ◽

Yong Yang

Keyword(s):

Data Collection ◽

Real Time ◽

Field Test ◽

Performance Indicators ◽

Testing System ◽

Time Data ◽

Process Data ◽

Real Time Data ◽

Long Time ◽

Factory Testing

This paper designed a motor winding testing system, it can do the dielectric withstand voltage test of inter-turn under 30kV.The system can communicate effectively between PC and machine, by using the PC's powerful capacity of process data and PLC's better stability and the Labview's convenient UI. So the system has real-time data collection, preservation, analysis and other characteristics. This system is able to achieve factory testing and type testing of the motor windings facilitating. Various performance indicators were stable and reliable by field test during a long time.

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PMH56 INNOVATIONS IN COMBINING PATIENT REPORTED OUTCOMES WITH COGNITIVE TESTING DATA TO STREAMLINE AND LEVERAGE REAL-TIME DATA COLLECTION

Value in Health ◽

10.1016/s1098-3015(11)72933-3 ◽

2010 ◽

Vol 13 (7) ◽

pp. A456

Author(s):

C Curry

Keyword(s):

Data Collection ◽

Real Time ◽

Patient Reported Outcomes ◽

Cognitive Testing ◽

Time Data ◽

Patient Reported ◽

Testing Data ◽

Real Time Data

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Flood management in reservoirs in upper river basins from real time data collection by using downstream water alert systems

Dams and Reservoirs, Societies and Environment in the 21st Century, Two Volume Set ◽

10.1201/b16818-34 ◽

2006 ◽

pp. 211-217 ◽

Cited By ~ 1

Author(s):

A de la Torre ◽

R Gordón ◽

J Gras ◽

P Rubí ◽

R Rollán

Keyword(s):

Data Collection ◽

Real Time ◽

River Basins ◽

Flood Management ◽

Time Data ◽

Real Time Data

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A quality improvement (QI) project on improving trainee confidence in conducting remote psychiatric consultations at Pennine Care National Health Service (NHS) Foundation Trust in the United Kingdom (UK)

BJPsych Open ◽

10.1192/bjo.2021.560 ◽

2021 ◽

Vol 7 (S1) ◽

pp. S209-S210

Author(s):

Rachel Moir ◽

Roshelle Ramkisson ◽

Seri Abraham ◽

Shevonne Matheiken

Keyword(s):

Real Time ◽

Response Rates ◽

Psychiatric Consultation ◽

Time Data ◽

Remote Consultation ◽

Safe Patient Care ◽

Pdsa Cycle ◽

Real Time Data ◽

The Uk ◽

Remote Consultations

AimsWhen the coronavirus disease 2019 pandemic hit the UK, clinicians within Pennine Care NHS Foundation Trust (a five-borough mental health trust) were faced with the challenge of rapidly switching to a novel way of assessing patients remotely.The idea for a QI project on trainees’ experience with remote consultations was conceived in April 2020. We present our February 2021 results here.We aimed to improve trainee confidence in conducting remote psychiatric assessments by at least 40%, to ensure effective and safe patient care during their 6 months placement.MethodOur discovery process included surveying trainees in April 2020 to explore experiences with remote psychiatric consultations, a literature search of current UK guidance and a local audit. The audit reviewed documentation of consent to remote consultations, with reference to standards as per NHS England remote consultation guidance. Key change ideas included publication of an article, ‘Remote consultations – top tips for clinical practitioners’, video-simulated remote consultations and a session on remote consultations in the trainee induction.In the first ‘plan-do-study-act’ (PDSA) cycle, we presented key findings from the article in a video presentation, which was sent trust-wide. We measured confidence in conducting remote assessments pre- and post-presentation via a feedback survey. Unfortunately, response rates were low and in the second PDSA cycle we targeted a smaller cohort of trainees at the August 2020 induction, although encountered similar difficulties. In the third PDSA cycle, we collected real-time data using an interactive app at the February 2021 trainee induction, and measured pre- and post- confidence following a presentation and a video-simulated remote consultation.Result2/34 respondents had accessed previous remote psychiatric consultation training and12/35 had some telepsychiatry experience. Pre-induction trainee confidence results revealed: extremely uncomfortable (16%), not confident (31%), neutral (47%), confident (6%) and very confident (0%) and post-induction confidence was 0%, 22%, 52%, 26% and 0%, respectively.ConclusionOur project started during the first peak of the pandemic, which may be a reason for initial limited response rates. Our results suggest that the remote psychiatric consultation trainee induction session has shown some improvement in trainee confidence; the ‘confident’ cohort improved from 6% to 26%.Our next steps include collecting similar real-time data, mid-rotation and uploading video-simulated remote consultations to the Trust Intranet. We plan to complete the local audit cycle. We also plan to incorporate patient experience (from an ongoing systematic review) to inform a potential triage process post-pandemic, choosing between face-to-face versus remote consultations.

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A Controllable Real-Time Data Collection System for Coastal Oceanography

10.1109/oceans.1976.1154239 ◽

1976 ◽

Cited By ~ 3

Author(s):

D. Dimmler ◽

D. Hus ◽

S. Rankowitz ◽

J. Scott

Keyword(s):

Data Collection ◽

Real Time ◽

Collection System ◽

Time Data ◽

Coastal Oceanography ◽

Data Collection System ◽

Real Time Data

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Communication Network of Wide Area Measurement System for Real-Time Data Collection on Smart Micro Grid

Advances in Intelligent Systems and Computing - Artificial Intelligence and Evolutionary Computations in Engineering Systems ◽

10.1007/978-81-322-2656-7_15 ◽

2016 ◽

pp. 163-172 ◽

Cited By ~ 3

Author(s):

Varna C. Prakash ◽

P. Sivraj ◽

K. K. Sasi

Keyword(s):

Communication Network ◽

Data Collection ◽

Real Time ◽

Measurement System ◽

Area Measurement ◽

Wide Area ◽

Time Data ◽

Wide Area Measurement System ◽

Real Time Data ◽

Micro Grid

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Season Cycling Gas Storage in Stogit Fields. A Real-Time Data Transmission System

10.2118/205206-ms ◽

2021 ◽

Author(s):

Graciela Eva Naveda ◽

France Dominique Louie ◽

Corinna Locatelli ◽

Julien Davard ◽

Sara Fragassi ◽

...

Keyword(s):

Natural Gas ◽

Real Time ◽

Fiber Optics ◽

Data Transmission ◽

Distribution Networks ◽

Gas Storage ◽

Transmission System ◽

Lessons Learned ◽

Time Data ◽

Real Time Data

Abstract Natural gas has become one of the major sources of energy for homes, public buildings and businesses, therefore gas storage is particularly important to ensure continuous provision compensating the differences between supply and demand. Stogit, part of Snam group, has been carrying out gas storage activities since early 1960's. Natural gas is usually stored underground, in large storage reservoirs. The gas is injected into the porous rock of depleted reservoirs bringing the reservoir nearby to its original condition. Injected gas can be withdrawn depending on the need. Gas market demands for industries and homes in Italy are mostly guaranteed from those Stogit reservoirs even in periods when imports are in crisis. Typically, from April to October, the gas is injected in these natural reservoirs that are "geologically tested"; while from November to March, gas is extracted from the same reservoirs and pumped into the distribution networks to meet the higher consumer demand. Thirty-eight (38) wells, across nine (9) depleted fields, are completed with downhole quartz gauges and some of them with fiber-optics gauges. Downhole gauges are installed to continuously measure and record temperature and pressure from multiple reservoirs. The Real Time data system installed for 29 wells is used to collect, transmit and make available downhole data to Stogit (Snam) headquarter office. Data is automatically collected from remote terminal units (RTUs) and transferred over Stogit (Snam) network. The entire system works autonomously and has the capability of being remotely managed from anywhere over the corporate Stogit (Snam) IT network. Historical trends, including fiber optics gauges ones, are visualized and data sets could be retrieved using a fast and user-friendly software that enables data import into interpretation and reservoir modeling software. The use of this data collection and transmission system, versus the traditional manual download, brought timely data delivery to multiple users, coupled with improved personnel safety since land travels were eliminated. The following pages describe the case study, lessons learned, and integrated new practices used to improve the current and future data transmission deployments.

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