scholarly journals Conversations that Count: Lessons From Evaluating a Men’s Digital Mental Health Response During COVID-19

2021 ◽  
pp. 1035719X2110530
Author(s):  
Kathryn Erskine ◽  
Matt Healey
Keyword(s):  
Mental Health ◽  
Data Collection ◽  
Real Time ◽  
Digital Health ◽  
Evaluation Design ◽  
Evaluation Practice ◽  
Health Response ◽  
Digital Evaluation ◽  
Support Evaluation ◽  
Evaluation Space

This paper details disruption and innovation in digital evaluation practice at Movember, as a result of the COVID-19 pandemic. The paper examines a men’s digital health intervention (DHI) – Movember Conversations – and the product pivot that was necessary to ensure it could respond to the pandemic. The paper focuses on the implications of the pivot for the evaluation and how the evaluation was adapted to the COVID-19 exigencies. It details the redesign of the evaluation to ensure methods wrapped around the modified product and could deliver real-time, practical insights. The paper seeks to fill knowledge gaps in the DHI evaluation space and outlines four key principles that support evaluation re-design in an agile setting. These include a user-centred approach to evaluation design, proportionate data collection, mixed (and flexible) methodologies, and agile evaluation reporting. The paper concludes with key lessons and reflections from the evaluators about what worked at Movember, to support other evaluators planning digital evaluations.

Protocol for Remote Assessment of Lung Disease and Impact on Physical and Mental Health (RALPMH) (Preprint)

2021 ◽  
Author(s):  
Yatharth Ranjan ◽  
Malik Althobiani ◽  
Joseph Jacob ◽  
Michele Orini ◽  
Richard Dobson ◽  
...  
Keyword(s):  
Mental Health ◽  
Data Collection ◽  
Real Time ◽  
Remote Monitoring ◽  
Wearable Devices ◽  
Physical And Mental Health ◽  
Disease Trajectory ◽  
Passive Data ◽  
Active Data ◽  
Finger Pulse

BACKGROUND Chronic Lung disorders like COPD and IPF are characterised by exacerbations which are a significant problem: unpleasant for patients, and sometimes severe enough to cause hospital admission (and therefore NHS pressures) and death. Reducing the impact of exacerbations is very important. Moreover, due to the COVID-19 pandemic, the vulnerable populations with these disorders are at high risk and hence their routine care cannot be done properly. Remote monitoring offers a low cost and safe solution of gaining visibility into the health of people in their daily life. Thus, remote monitoring of patients in their daily lives using mobile and wearable devices could be useful especially in high vulnerability groups. A scenario we consider here is to monitor patients and detect disease exacerbation and progression and investigate the opportunity of detecting exacerbations in real-time with a future goal of real-time intervention. OBJECTIVE The primary objective is to assess the feasibility and acceptability of remote monitoring using wearable and mobile phones in patients with pulmonary diseases. The aims will be evaluated over these areas: Participant acceptability, drop-out rates and interpretation of data, Detection of clinically important events such as exacerbations and disease progression, Quantification of symptoms (physical and mental health), Impact of disease on mood and wellbeing/QoL and The trajectory-tracking of main outcome variables, symptom fluctuations and order. The secondary objective of this study is to provide power calculations for a larger longitudinal follow-up study. METHODS Participants will be recruited from 2 NHS sites in 3 different cohorts - COPD, IPF and Post hospitalised Covid. A total of 60 participants will be recruited, 20 in each cohort. Data collection will be done remotely using the RADAR-Base mHealth platform for different devices - Garmin wearable devices, smart spirometers, mobile app questionnaires, surveys and finger pulse oximeters. Passive data collected includes wearable derived continuous heart rate, SpO2, respiration rate, activity, and sleep. Active data collected includes disease-specific PROMs, mental health questionnaires and symptoms tracking to track disease trajectory in addition to speech sampling, spirometry and finger Pulse Oximetry. Analyses are intended to assess the feasibility of RADAR-Base for lung disorder remote monitoring (include quality of data, a cross-section of passive and active data, data completeness, the usability of the system, acceptability of the system). Where adequate data is collected, we will attempt to explore disease trajectory, patient stratification and identification of acute clinically interesting events such as exacerbations. A key part of this study is understanding the potential of real-time data collection, here we will simulate an intervention using the Exacerbation Rating Scale (ERS) to acquire responses at-time-of-event to assess the performance of a model for exacerbation identification from passive data collected. RESULTS RALPMH study provides a unique opportunity to assess the use of remote monitoring in the study of lung disorders. The study is set to be started in mid-May 2021. The data collection apparatus, questionnaires and wearable integrations have been set up and tested by clinical teams. While waiting for ethics approval, real-time detection models are currently being constructed. CONCLUSIONS RALPMH will provide a reference infrastructure for the use of wearable data for monitoring lung diseases. Specifically information regarding the feasibility and acceptability of remote monitoring and the potential of real-time remote data collection and analysis in the context of chronic lung disorders. Moreover, it provides a unique standpoint to look into the specifics of novel coronavirus without burdensome interventions. It will help plan and inform decisions in any future studies that make use of remote monitoring in the area of Respiratory health. CLINICALTRIAL https://www.isrctn.com/ISRCTN16275601

scholarly journals Data Collection and Labeling of Real-Time IoT-Enabled Bio-Signals in Everyday Settings for Mental Health Improvement

2021 ◽  
Author(s):  
Ali Tazarv ◽  
Sina Labbaf ◽  
Amir M. Rahmani ◽  
Nikil Dutt ◽  
Marco Levorato
Keyword(s):  
Mental Health ◽  
Data Collection ◽  
Real Time ◽  
Health Improvement

Digital Health Entrepreneurship

2021 ◽  
pp. 375-388
Author(s):  
Wendy Charles ◽  
Sharon Wulfovich ◽  
Arlen Meyers
Keyword(s):  
Mental Health ◽  
Quality Of Care ◽  
Data Collection ◽  
Digital Health ◽  
Mental Healthcare ◽  
Electronic Data Collection ◽  
Health Technologies ◽  
Reducing Costs ◽  
Workforce Engagement

Digital health technologies can promote advancements in mental healthcare using methods of electronic data collection and high-powered computing. There is a growing recognition that implementation of these technologies can address the quadruple aim in healthcare by improving health of populations, increasing quality of care, reducing costs, and increasing workforce engagement. The convergence drivers of innovation in digital health are described in a discipline referred to as digital health entrepreneurship. This chapter introduces digital health entrepreneurship, and its relationship to convergence science, and describes the strategies to advance digital health entrepreneurship in mental health.

scholarly journals Digitization of Measurement Based Care Pathways in Mental Health through REDCap and Electronic Health Record Integration (Preprint)

2020 ◽  
Author(s):  
Steve Hawley ◽  
David Rotenberg ◽  
Joanna Yu ◽  
Nikola Bogetic ◽  
Natalia Potapova ◽  
...  
Keyword(s):  
Mental Health ◽  
Data Collection ◽  
Data Quality ◽  
Real Time ◽  
Fold Increase ◽  
Self Report ◽  
Care Pathways ◽  
Health Record ◽  
Measurement Based Care ◽  
Clinician Attitudes

BACKGROUND The delivery of standardized self-report assessments is essential for measurement-based care (MBC) in mental health. Paper-based methods of MBC data collection may result in transcription errors, missing data, and other data quality issues when entered into the patient electronic health record (EHR). OBJECTIVE To address these issues, a dedicated instance of REDCap, a free, widely used electronic data capture platform, was established to enable the deployment of digitized self-assessments in clinical care pathways to inform clinical decision making. METHODS REDCap was integrated with the primary clinical information system to facilitate real-time transfer of discrete data and descriptive reports from REDCap into the EHR. Both technical and administrative components were required for complete implementation. A technology acceptance survey was also administered to capture physician and clinician attitudes towards the new system. RESULTS Integration of REDCap with the EHR transitioned clinical workflows from paper-based to electronic data collection. This resulted in significant time-savings, improved data quality and valuable real-time information delivery. Digitization of self-report assessments at each appointment contributed to clinic-wide implementation of the Major Depressive Disorder Integrated Care Pathway (MDD-ICP). This digital transformation facilitated a 4-fold increase in physician adoption of this ICP workflow and a 3-fold increase in patient enrollment resulting in an overall significant increase in MDD-ICP capacity. Physician and Clinician attitudes were overall positive with almost all respondents agreeing that the system was useful to their work. CONCLUSIONS REDCap provided an intuitive patient interface for collection of self-report measures, real-time access to results to inform clinical decisions, and an extensible backend for systems integration. The approach scaled effectively and expanded to high-impact clinics throughout the hospital, allowing for broad deployment of complex workflows and standardized assessments leading to accumulation of harmonized data across clinics and care pathways. REDCap is a flexible tool that can be effectively leveraged to facilitate automatic transfer of self-report data to the EHR. However, thoughtful governance is required to complement the technical implementation to ensure that data standardization, data quality, patient safety, and privacy are maintained.

Enhancing Clinical Supervision Using High-Definition Real-Time Digital Recording, Annotation, and Bluetooth Technology

2019 ◽  
Vol 4 (2) ◽  
pp. 356-362
Author(s):  
Jennifer W. Means ◽  
Casey McCaffrey
Keyword(s):  
Graduate Students ◽  
Data Collection ◽  
Real Time ◽  
Clinical Supervision ◽  
Video Recording ◽  
Advanced Technology ◽  
High Definition ◽  
Recording Technology ◽  
Self Confidence ◽  
Additional Data Collection

Purpose The use of real-time recording technology for clinical instruction allows student clinicians to more easily collect data, self-reflect, and move toward independence as supervisors continue to provide continuation of supportive methods. This article discusses how the use of high-definition real-time recording, Bluetooth technology, and embedded annotation may enhance the supervisory process. It also reports results of graduate students' perception of the benefits and satisfaction with the types of technology used. Method Survey data were collected from graduate students about their use and perceived benefits of advanced technology to support supervision during their 1st clinical experience. Results Survey results indicate that students found the use of their video recordings useful for self-evaluation, data collection, and therapy preparation. The students also perceived an increase in self-confidence through the use of the Bluetooth headsets as their supervisors could provide guidance and encouragement without interrupting the flow of their therapy sessions by entering the room to redirect them. Conclusions The use of video recording technology can provide opportunities for students to review: videos of prospective clients they will be treating, their treatment videos for self-assessment purposes, and for additional data collection. Bluetooth technology provides immediate communication between the clinical educator and the student. Students reported that the result of that communication can improve their self-confidence, perceived performance, and subsequent shift toward independence.

Developing a sustainable Digital Health Innovation Ecosystem in a rural and resource-poor region: A monitored networking approach (Preprint)

2020 ◽  
Author(s):  
Arunangsu Chatterjee ◽  
Sebastian Stevens ◽  
Sheena Asthana ◽  
Ray B Jones
Keyword(s):  
Social Network ◽  
Network Analysis ◽  
Data Collection ◽  
Digital Health ◽  
Resource Poor Setting ◽  
Quadruple Helix ◽  
Innovation Ecosystem ◽  
Resource Poor ◽  
Quadruple Helix Model ◽  
Over Time

BACKGROUND Digital health (DH) innovation ecosystems (IE) are key to the development of new e-health products and services. Within an IE, third parties can help promote innovation by acting as knowledge brokers and the conduits for developing inter-organisational and interpersonal relations, particularly for smaller organisations. Kolehmainen’s quadruple helix model suggests who the critical IE actors are, and their roles. Within an affluent and largely urban setting, such ecosystems evolve and thrive organically with minimal intervention due to favourable economic and geographical conditions. Facilitating and sustaining a thriving DH IE within a resource-poor setting can be far more challenging even though far more important for such peripheral economics and the health and well-being of those communities. OBJECTIVE Taking a rural and remote region in the UK, as an instance of an IE in a peripheral economy, we adapt the quadruple helix model of innovation, apply a monitored social networking approach using McKinsey’s Three Horizons of growth to explore: • What patterns of connectivity between stakeholders develop within an emerging digital health IE? • How do networks develop over time in the DH IE? • In what ways could such networks be nurtured in order to build the capacity, capability and sustainability of the DH IE? METHODS Using an exploratory single case study design for a developing digital health IE, this study adopts a longitudinal social network analysis approach, enabling the authors to observe the development of the innovation ecosystem over time and evaluate the impact of targeted networking interventions on connectivity between stakeholders. Data collection was by an online survey and by a novel method, connection cards. RESULTS Self-reported connections between IE organisations increased between the two waves of data collection, with Small and Medium-sized Enterprises (SMEs) and academic institutions the most connected stakeholder groups. Patients involvement improved over time but still remains rather peripheral to the DH IE network. Connection cards as a monitoring tool worked really well during large events but required significant administrative overheads. Monitored networking information categorised using McKinsey’s Three Horizons proved to be an effective way to organise networking interventions ensuring sustained engagement. CONCLUSIONS The study reinforces the difficulty of developing and sustaining a DH IE in a resource-poor setting. It demonstrates the effective monitored networking approach supported by Social Network Analysis allows to map the networks and provide valuable information to plan future networking interventions (e.g. involving patients or service users). McKinsey’s Three Horizons of growth-based categorisation of the networking assets help ensure continued engagement in the DH IE contributing towards its long-term sustainability. Collecting ongoing data using survey or connection card method will become more labour intensive and ubiquitous ethically driven data collection methods can be used in future to make the process more agile and responsive.

scholarly journals IoT-Based Patient Movement Monitoring: The Post-Operative Hip Fracture Rehabilitation Model

2021 ◽  
Vol 13 (8) ◽  
pp. 195
Author(s):  
Akash Gupta ◽  
Adnan Al-Anbuky
Keyword(s):  
Hip Fracture ◽  
Real Time ◽  
System Performance ◽  
Digital Health ◽  
Time Behavior ◽  
Functional Requirements ◽  
Rehabilitation Process ◽  
Rehabilitation Model ◽  
The Impact ◽  
Movement Monitoring

Hip fracture incidence is life-threatening and has an impact on the person’s physical functionality and their ability to live independently. Proper rehabilitation with a set program can play a significant role in recovering the person’s physical mobility, boosting their quality of life, reducing adverse clinical outcomes, and shortening hospital stays. The Internet of Things (IoT), with advancements in digital health, could be leveraged to enhance the backup intelligence used in the rehabilitation process and provide transparent coordination and information about movement during activities among relevant parties. This paper presents a post-operative hip fracture rehabilitation model that clarifies the involved rehabilitation process, its associated events, and the main physical movements of interest across all stages of care. To support this model, the paper proposes an IoT-enabled movement monitoring system architecture. The architecture reflects the key operational functionalities required to monitor patients in real time and throughout the rehabilitation process. The approach was tested incrementally on ten healthy subjects, particularly for factors relevant to the recognition and tracking of movements of interest. The analysis reflects the significance of personalization and the significance of a one-minute history of data in monitoring the real-time behavior. This paper also looks at the impact of edge computing at the gateway and a wearable sensor edge on system performance. The approach provides a solution for an architecture that balances system performance with remote monitoring functional requirements.

scholarly journals A qualitative evaluation of Southwark Council’s public health response to mitigating the mental health impact of the 2017 London bridge and borough market terror attack

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sandra Jumbe ◽  
Adrienne Milner ◽  
Megan Clinch ◽  
Jonathan Kennedy ◽  
Richard J. Pinder ◽  
...  
Keyword(s):  
Mental Health ◽  
Qualitative Evaluation ◽  
Health Impact ◽  
Health Needs ◽  
Health Impacts ◽  
Terror Attack ◽  
Terror Attacks ◽  
Physical Injuries ◽  
Community Stakeholders ◽  
Health Response

Abstract Background Over recent years there have been several major terror attacks in cities across Europe. These attacks result in deaths, physical injuries, and pose long-term threats to mental health and wellbeing of large populations. Although psychologists have completed important work on mental health responses to disaster exposure including terrorist attacks, the mental health impacts of such attacks have been comparatively less examined in academic literature than the acute health response to physical injuries. This paper reflects on Southwark Council’s pioneering public mental health response to the June 2017 terror attack at London Bridge and Borough Market. It aims to explore perceptions of the mental health impact of the incident by those living and working in the borough. Methods A rapid qualitative evaluation informed by the logic underpinning Southwark Council’s response was conducted. Seven formative interviews were undertaken with individuals involved in the response planning and/or delivery, enabling the evaluation team to establish the response’s theoretical basis. Subsequently, nineteen semi-structured interviews with consenting Council employees, residents, business owners, and workers from the Borough were conducted to understand perceived mental health impacts of the attack and the success of the Council response. Thematic analysis of transcribed interviews was undertaken to evaluate the extent to which the response was implemented successfully. Results Participants reported feeling the attack had a wide-reaching negative impact on the mental health of residents, those working in the borough and visitors who witnessed the attack. Delivering the response was a challenge and response visibility within the community was limited. Participants suggested a comprehensive systematic approach to health needs assessment informed by knowledge and relationships of key Council workers and community stakeholders is imperative when responding to terrorist incidents. Improved communication and working relationships between statutory organisations and community stakeholders would ensure community groups are better supported. Prioritising mental health needs of terror attack responders to mitigate persisting negative impacts was highlighted. Conclusions This article highlights a potential public health approach and need for developing robust practical guidance in the aftermath of terror attacks. This approach has already influenced the response to the Christchurch mosque shooting in 2019.

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