The design and evaluation of novel technologies for the self monitoring and management of Parkinson's symptoms

PhD ThesisThis thesis explores how digital technologies might better support people with Parkinson’s (PwP) to take control of their condition, by engaging in self monitoring and management practices. The specific focus of this thesis is around issues managed by Speech and Language Therapists (SLTs) (namely drooling and speech and voice changes). Three case studies were used to explore the ways that different technologies might be configured to aid the self monitoring and management of these speech and drooling symptoms. The first case study describes an evaluation of PDCue, a wrist worn device to assist the self management of drooling through the use of a temporal cueing method, to increase swallowing frequency. This study showed evidence that drooling can be behaviourally self managed through cueing—like other symptoms of Parkinson’s such as gait freezing—and proved a viable first step towards re-considering the use of additional medications as a first option for drooling treatment. However, whilst this study proved successful in understanding the ways in which a simple, temporal cueing technique might support drooling management, it opened up questions around the ways in which PwP might use technology to actively think about and understand their condition through self monitoring, and use this information to support self management practices further. In response, the second case study describes the design and evaluation of LApp, an application to support both the self monitoring and management of vocal loudness issues through the use of an insitu cueing approach. The Google Glass was chosen as the platform to run the cueing method on, due to its technical capabilities as a multi-sensor, wearable platform, to analyse a constant stream of audio and provide real time visual prompts to support the wearer in increasing their volume at times when it is needed in conversation. This study highlighted how participants saw value in LApp in supporting their loudness issues, but also noted a desire for participants to understand more about their speech and the SLT strategies that they were required to do in order to improve it. The third case study drew upon this desire for increased understanding by developing and evaluating Speeching, which employed crowdsourcing through a smartphone application to support the self monitoring of speech and voice changes, through the provision of human feedback, and the subsequent effect that this feedback had on self management practices. This study yielded positive responses from participants, who valued the anonymous feedback from the crowd and the support that this provided them in configuring their home based speech practice. A final discussion chapter draws the 3 case studies together and discusses the lessons learned throughout the research. It discusses the overall research questions for the thesis in detail and describes the implications of the research for the wider HCI and medical communities. A framework is presented which aims to visualise the levels of agency that the studied technologies afforded and the levels of responsiveness required by participants to make sense of, and implement the information being provided by the devices in order to facilitate a change to the self monitoring and management practices. Through the design and evaluation of the described technologies and a synthesis of the findings across the span of the research, this thesis explores the ways in which PwP, with a diverse range of symptoms and related physical, social and emotional issues, might value digital technologies and their potential to facilitate new forms of self monitoring and self management in their everyday lives.The National Institute of Health Research (NIHR): The Engineering and Physical Sciences Research Council (EPSRC): Gordon Chapman Memorial Fund

DemYouth: Co-Designing and Enacting Tools to Support Young People’s Engagement with People with Dementia

There is a growing body of research examining the role of technology in supporting the care of—and relationships surrounding—people with dementia, yet little attention has been given to how this relates to younger family members. We conducted a qualitative study based on a series of 6 codesign workshops conducted with 14 young people who had personal experience with dementia. Initially, our workshops focused on understanding the difficulties that young people face when engaging, interacting and being with people with dementia. Initial analysis of workshop data informed the design of three digital tool concepts that were used as the basis for user enactment workshops. Our findings highlight the young people's desire to be more involved in their family discussions around dementia and a need for them to find new ways to connect with their loved ones with dementia. We offer a set of design considerations for future systems that support these needs and reflect on some of the complexities we faced around engaging young people in this difficult topic of discussion

'The issue with that sort of data?':Clinicians’ accountability concerns around COPD self-monitoring tools

There is an increasing interest in CSCW to understand how technology can be used for the monitoring of chronic conditions, and how collaboration for care planning can occur between clinicians and patients through its use. Many studies in this area have focussed on the patients’experience of using such technology.We report findings from a small-scale study, where a smartphone app for monitoring Chronic Obstructive Pulmonary Disease symptoms was introduced into a community respiratory service for patients’ use. Our findings provide three key insights into the clinicians’experiences in receiving the patient reported data and supporting the patients’ use of the app as part of their service

Designing video stories around the lived experience of severe mental illness

Caregivers of people experiencing severe mental illness (SMI) report a multitude of psychosocial impacts, including feelings of loneliness and isolation, distress, societal stigma and prejudice around mental health. We describe the design of a series of video stories, performed by actors, which were based on the lived experiences of caregivers and people with SMI. We conducted a series of in-depth qualitative interviews with 11 participants, which formed the basis for the video content. We then worked alongside two caregivers (as advisors), at each stage of the production process, to develop a set of 45 video stories, using personas in our process. Through a discussion of our creative process, we offer a set of considerations for future researchers wishing to develop relatable and empathic digital content for online information provision and support tools. In addition, we offer a set of reflections around the complex ethical challenges underpinning this design space

The feasibility and acceptability of using a novel wrist worn cueing device to self-manage drooling problems in people with Parkinson’s disease: A pilot study

Introduction: Daytime drooling is experienced by around 50% of Parkinson’s patients, who fail to swallow saliva in sufficient volume or regularity, despite normal production. This research explored the feasibility and acceptability of using a cueing device, to improve drooling. Methods: During a 4-week intervention, 28 participants were asked to use a cueing device for one hour per day. During this time, the device vibrated once-per-minute, reminding the participant to swallow their saliva. A daily diary was used to collect self-report around swallowing severity, frequency and duration. This was filled out by participants for 1 week before, 4 weeks during, and for 1 week immediately after intervention. Diaries were also collected for 1 week during a follow up, carried out 4 weeks after intervention finished. Results: Participants self-reported benefits in drooling severity (p=0.031), frequency (p=<0.001), and duration (p=0.001) after using the device. Improvements were maintained at follow up. Twenty-two participants explicitly reported a positive benefit to their drooling during exit interview. All felt the intervention and device were acceptable and usable. Conclusions: Using a cueing device for 1 month had perceived benefit to drooling severity, frequency and duration in patients with Parkinson’s. Participants accepted the device and treatment protocol

Exploring Human-Data Interaction in Clinical Decision-making Using Scenarios: Co-design Study

When caring for patients with chronic conditions like Chronic Obstructive Pulmonary Disease (COPD), healthcare professionals (HCPs) rely on multiple data sources to make decisions. Collating and visualizing this data, for example on clinical dashboards, holds potential to support timely and informed decision-making. Most studies about data supported decision-making (DSDM) technologies for healthcare have focused on their technical feasibility or quantitative effectiveness. While these studies are an important contribution to the literature, they do not further our limited understanding of how HCPs engage with these technologies and how they can be designed to support specific contexts of use. To progress our knowledge of this area, we must work with HCPs to explore this space and the real-world complexities of healthcare work and service structures. This research aimed to qualitatively explore how DSDM technologies could support HCPs in their decision-making about COPD care. We created a scenario-based research tool, called Respire, that visualized HCPs’ data needs about their COPD patients and services. We used Respire with HCPs to uncover rich and nuanced findings about human-data interaction in this context, focusing on the real-world challenges that HCPs face when carrying out their work and making decisions. We engaged nine respiratory HCPs from two collaborating healthcare organizations to design Respire. We then used Respire as a tool to investigate human-data interaction in the context of decision-making about COPD care. The study followed a co-design approach that had three stages and spanned two years. The first stage involved five workshops with the HCPs to identify data-interaction scenarios which would support their work. The second stage involved creating Respire, an interactive scenario-based web application that visualized HCPs’ data needs, incorporating feedback from the HCPs. The final stage involved 11 one-to-one sessions with HCPs to use Respire, focusing on how they envisaged it could support their work and decisions about care. We found that: (1) HCPs trust data differently depending on where it came from and who recorded it; (2) sporadic and subjective data generated by patients has value but creates challenges for decision-making; and (3) HCPs require support interpreting and responding to new data and its use cases. Our study uncovers important lessons for the design of DSDM technologies to support healthcare contexts. We show that while DSDM technologies have potential to support patient care and healthcare delivery, important sociotechnical and human data interaction challenges influence how these technologies should be designed and deployed. Exploring these considerations during the design process can ensure DSDM technologies are designed with a holistic view of how decision-making and engagement with data occurs in healthcare contexts

A Web-Based Intervention for Relatives of People Experiencing Psychosis or Bipolar Disorder:Design Study Using a User-Centered Approach

Background: Relatives of people experiencing bipolar mood episodes or psychosis face a multitude of challenges (eg, social isolation, limited coping strategies, and issues with maintaining relationships). Despite this, there is limited informational and emotional support for people who find themselves in supporting or caring roles. Digital technologies provide us with an opportunity to offer accessible tools, which can be used flexibly to provide evidence-based information and support, allowing relatives to build their understanding of mental health problems and learn from others who have similar experiences. However, to design tools that are useful to relatives, we first need to understand their needs. Objective: The aim of this study was to use a user-centered design approach to develop an accessible Web-based intervention, based on the Relatives Education And Coping Toolkit (REACT) booklet, to support the informational and emotional needs of relatives of people experiencing psychosis or bipolar disorder. Methods: We engaged relatives of people with experiences of bipolar disorder or psychosis in workshops to identify their needs and design requirements for developing a Web-based version of a paper-based toolkit. We used a 2-phase qualitative approach to explore relatives’ views on content, design, and functionalities, which are considered to be engaging and useful in a Web-based intervention. In phase 1, we consulted 24 relatives in 2 workshops to better understand their existing support infrastructure, their barriers for accessing support, unmet needs, and relatives’ views on online support. On the basis of the results of these workshops, we developed a set of design considerations to be explored in a smaller workshop. Workshop 3 then involved working with 2 digitally literate relatives to design a usable and acceptable interface for our Web-based toolkit. Finally, in phase 2, we conducted a heuristic evaluation to assess the usability of the toolkit. Results: Our findings indicated that relatives require technologies that (1) they can place their trust in, particularly when discussing a highly sensitive topic, (2) enable learning from the lived experiences of others while retaining confidentiality, and (3) they can work through at their own pace in a personalized manner. Conclusions: Our study highlights the need for providing a trustworthy, supportive tool where relatives can engage with people who have similar experiences to their own. Our heuristic evaluation showed promise in terms of perceived usability of the REACT Web-based intervention. Through this work, we emphasize the need to involve stakeholders with various characteristics, including users with limited computer literacy or experience in online support

Multimodal Classification of Parkinson's Disease in Home Environments with Resiliency to Missing Modalities

Parkinson’s disease (PD) is a chronic neurodegenerative condition that affects a patient’s everyday life. Authors have proposed that a machine learning and sensor-based approach that continuously monitors patients in naturalistic settings can provide constant evaluation of PD and objectively analyse its progression. In this paper, we make progress toward such PD evaluation by presenting a multimodal deep learning approach for discriminating between people with PD and without PD. Specifically, our proposed architecture, named MCPD-Net, uses two data modalities, acquired from vision and accelerometer sensors in a home environment to train variational autoencoder (VAE) models. These are modality-specific VAEs that predict effective representations of human movements to be fused and given to a classification module. During our end-to-end training, we minimise the difference between the latent spaces corresponding to the two data modalities. This makes our method capable of dealing with missing modalities during inference. We show that our proposed multimodal method outperforms unimodal and other multimodal approaches by an average increase in F1-score of 0.25 and 0.09, respectively, on a data set with real patients. We also show that our method still outperforms other approaches by an average increase in F1-score of 0.17 when a modality is missing during inference, demonstrating the benefit of training on multiple modalities