Dataset Information

Relating Experienced To Recalled breathlessness Observational (RETRO) study: a prospective study using a mobile phone application.

ABSTRACT: Background:Breathlessness, the subjective sensation of breathing discomfort, is common and appears in the daily life of people with cardiorespiratory diseases. Physicians often rely on patient's history based on symptom recall. The relation between recalled and experienced breathlessness is still poorly understood. This paper presents the protocol for a study primarily aimed at evaluating the relationship between experienced breathlessness and (1) recalled breathlessness and (2) predicted future breathlessness. Methods:A mobile phone application will be used to collect data during daily life. Medically stable participants, ?18 years of age with mean daily breathlessness of Numerical Rating Scale (NRS) 3/10 and able to use a mobile phone with internet will rate their breathlessness intensity on a 0-10 NRS prompted the user several times daily for 1?week. Participants will recall their breathlessness each day and week. Multivariable random effects regression models will be used for statistical analyses. Results:Results of the study will be submitted for publication in peer-reviewed journals and presented at relevant conferences. Discussion:This protocol describes a study aimed at investigating previously unknown areas of the experience and recall of breathlessness using a new method of data collection. Registration details:Prospectively registered with ClinicalTrials.gov (Nr: NCT03468205). Ethics and dissemination:The study has received ethical approval from the Regional Ethical Review Board Lund (DNr 2017/149). After a general study information including that participation is entirely voluntary, participants will answer the eligibility criteria and be asked to consent to participate before entering the study questions. Written informed consent to participate will be obtained for participants in the clinical sub-cohort. Participation can be discontinued at the discretion of the participant in which case no further data will be collected.

SUBMITTER: Sandberg J

PROVIDER: S-EPMC6424247 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Relating Experienced To Recalled breathlessness Observational (RETRO) study: a prospective study using a mobile phone application.

Sandberg Jacob J Lansing Robert R Anderberg Peter P Currow David D Sundh Josefin J Ahmadi Zainab Z Palmqvist Sebastian S Ekström Magnus M

BMJ open respiratory research 20190212 1

<h4>Background</h4>Breathlessness, the subjective sensation of breathing discomfort, is common and appears in the daily life of people with cardiorespiratory diseases. Physicians often rely on patient's history based on symptom recall. The relation between recalled and experienced breathlessness is still poorly understood. This paper presents the protocol for a study primarily aimed at evaluating the relationship between experienced breathlessness and (1) recalled breathlessness and (2) predicte ...[more]

PMID: 30956800

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Project description:ImportanceThe coronavirus disease 2019 pandemic has highlighted the need to expand telemedicine solutions.ObjectiveTo beta test a secure teleophthalmology mobile app at military treatment facilities in Afghanistan.Design, setting, and participantsThis prospective case series included 16 military treatment facilities at diverse roles of care including forward operating bases in Afghanistan and 1 location outside of Afghanistan. Thirty point-of-care medics and medical professionals were included from September to November 2019.InterventionsUsers placed teleophthalmology consults on their mobile phone using the mobile eye care app, and an expeditionary ophthalmologist stationed at a military hospital in Afghanistan responded. Users graded the mobile app using a rating scale from 1 to 5, with 1 being very dissatisfied and 5 being very satisfied.Main outcomes and measuresMean initial response time, agreement between the teleophthalmology diagnosis and final diagnosis, treatment and management following recommendations outlined in the Joint Trauma System clinical practice guidelines, prevention of the need for aeromedical evacuation, user satisfaction, and security and the Health Insurance Portability and Accountability Act compliance of consult.ResultsThere were 28 consults placed over 6 weeks by 18 different users that were received by the expeditionary ophthalmologist. The mean (SD) patient age was 30.3 (9.8) years. Most patients were male (26 [93%]) and active duty US military (22 [78%]). The mean initial response time was 3 minutes 58 seconds (95% CI, 2 minutes 30 seconds to 5 minutes 26 seconds). There was agreement between the teleophthalmology diagnosis and final diagnosis in 24 consults (86%; 95% CI, 72%-100%). The treatment and management followed recommendations outlined in the Joint Trauma System Clinical Practice Guidelines for Eye Trauma: Initial Care in 28 consults (100%). Teleophthalmology consultation prevented the need for aeromedical evacuation in 4 consults (14%; 95% CI, 0.7%-28%). The patient returned to duty in 15 consults (54%; 95% CI, 34%-73%). Median overall satisfaction was 5 (minimum, 3; maximum, 5). All 28 consults (100%) were secure and compliant with the Health Insurance Portability and Accountability Act.Conclusions and relevanceWhile only a limited number of consults were evaluated, this study suggests that teleophthalmology mobile phone apps may improve and extend ophthalmic care in combat zones.

Project description:BACKGROUND:Objective behavioral markers of mental illness, often recorded through smartphones or wearable devices, have the potential to transform how mental health services are delivered and to help users monitor their own health. Linking objective markers to illness is commonly performed using population-level models, which assume that everyone is the same. The reality is that there are large levels of natural interindividual variability, both in terms of response to illness and in usual behavioral patterns, as well as intraindividual variability that these models do not consider. OBJECTIVE:The objective of this study was to demonstrate the utility of splitting the population into subsets of individuals that exhibit similar relationships between their objective markers and their mental states. Using these subsets, "group-personalized" models can be built for individuals based on other individuals to whom they are most similar. METHODS:We collected geolocation data from 59 participants who were part of the Automated Monitoring of Symptom Severity study at the University of Oxford. This was an observational data collection study. Participants were diagnosed with bipolar disorder (n=20); borderline personality disorder (n=17); or were healthy controls (n=22). Geolocation data were collected using a custom Android app installed on participants' smartphones, and participants weekly reported their symptoms of depression using the 16-item quick inventory of depressive symptomatology questionnaire. Population-level models were built to estimate levels of depression using features derived from the geolocation data recorded from participants, and it was hypothesized that results could be improved by splitting individuals into subgroups with similar relationships between their behavioral features and depressive symptoms. We developed a new model using a Dirichlet process prior for splitting individuals into groups, with a Bayesian Lasso model in each group to link behavioral features with mental illness. The result is a model for each individual that incorporates information from other similar individuals to augment the limited training data available. RESULTS:The new group-personalized regression model showed a significant improvement over population-level models in predicting mental health severity (P<.001). Analysis of subgroups showed that different groups were characterized by different features derived from raw geolocation data. CONCLUSIONS:This study demonstrates the importance of handling interindividual variability when developing models of mental illness. Population-level models do not capture nuances in how different individuals respond to illness, and the group-personalized model demonstrates a potential way to overcome these limitations when estimating mental state from objective behavioral features.

Project description:BackgroundMobile health (mHealth) interventions have the potential to transform the global health care landscape. The processing power of mobile devices continues to increase, and growth of mobile phone use has been observed worldwide. Uncertainty remains among key stakeholders and decision makers as to whether global health interventions can successfully tap into this trend. However, when correctly implemented, mHealth can reduce geographic, financial, and social barriers to quality health care.ObjectiveThe aim of this study was to design and test Beacon, a mobile phone-based tool for evaluating mHealth readiness in global health interventions. Here, we present the results of an application validation study designed to understand the mobile network landscape in and around Macha, Zambia, in 2019.MethodsBeacon was developed as an automated mobile phone app that continually collects spatiotemporal data and measures indicators of network performance. Beacon was used in and around Macha, Zambia, in 2019. Results were collected, even in the absence of network connectivity, and asynchronously uploaded to a database for further analysis.ResultsBeacon was used to evaluate three mobile phone networks around Macha. Carriers A and B completed 6820/7034 (97.0%) and 6701/7034 (95.3%) downloads and 1349/1608 (83.9%) and 1431/1608 (89.0%) uploads, respectively, while Carrier C completed only 62/1373 (4.5%) file downloads and 0/1373 (0.0%) file uploads. File downloads generally occurred within 4 to 12 seconds, and their maximum download speeds occurred between 2 AM and 5 AM. A decrease in network performance, demonstrated by increases in upload and download durations, was observed beginning at 5 PM and continued throughout the evening.ConclusionsBeacon was able to compare the performance of different cellular networks, show times of day when cellular networks experience heavy loads and slow down, and identify geographic "dead zones" with limited or no cellular service. Beacon is a ready-to-use tool that could be used by organizations that are considering implementing mHealth interventions in low- and middle-income countries but are questioning the feasibility of the interventions, including infrastructure and cost. It could also be used by organizations that are looking to optimize the delivery of an existing mHealth intervention with improved logistics management.

Project description:BackgroundStrengthening surveillance systems to collect near-real-time case-based data plays a fundamental role in achieving malaria elimination in the Greater Mekong Subregion (GMS). With the advanced and widespread use of digital technology, mHealth is increasingly taking a prominent role in malaria surveillance systems in GMS countries, including Myanmar. In Myanmar's malaria elimination program, an mHealth system called Malaria Case-based Reporting (MCBR) has been applied for case-based reporting of malaria data by integrated community malaria volunteers (ICMVs). However, the sustainability of such mHealth systems in the context of existing malaria elimination programs in Myanmar is unknown.MethodsFocus group discussions were conducted with ICMVs and semi-structured in-depth interviews were conducted with malaria program stakeholders from Myanmar's Ministry of Health and Sports and its malaria program implementing partners. Thematic (deductive followed by inductive) analysis was undertaken using a qualitative descriptive approach.ResultsTechnological and financial constraints such as inadequate internet access, software errors, and insufficient financial resources to support mobile phone-related costs have hampered users' access to MCBR. Poor system integrity, unpredictable reporting outcomes, inadequate human resources for system management, and inefficient user support undermined the perceived quality of the system and user satisfaction, and hence its sustainability. Furthermore, multiple parallel systems with functions overlapping those of MCBR were in use.ConclusionsDespite its effectiveness and efficiency in malaria surveillance, the sustainability of nationwide implementation of MCBR is uncertain. To make it sustainable, stakeholders should deploy a dedicated human workforce with the necessary technical and technological capacities; secure sustainable, long-term funding for implementation of MCBR; find an alternative cost-effective plan for ensuring sustainable system access by ICMVs, such as using volunteer-owned mobile phones for reporting rather than supporting new mobile phones to them; and find a solution to the burden of multiple parallel systems.Trial registrationNot applicable.

Dataset Information

Relating Experienced To Recalled breathlessness Observational (RETRO) study: a prospective study using a mobile phone application.

Publications

Relating Experienced To Recalled breathlessness Observational (RETRO) study: a prospective study using a mobile phone application.

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