論文アブストラクト： Insomnia can drastically affect individuals' overall well-being and work performance, with substantial costs to society and industry. Cognitive behavioral therapy for insomnia (CBT-I) is a psychotherapeutic treatment, which requires patients to track sleep and share the data with CBT-I clinicians. However, the number of specialists who can provide CBT-I limits the number of patients who can receive it. In this paper, we aim to identify opportunities to leverage technology to assist clinicians in delivering quality and effective CBT-I services to broader populations. Toward this goal, we conducted formative studies, including 11 CBT-I clinic observations and 17 semi-structured interviews, to understand the current workflow of CBT-I and associated challenges. We discuss how technology can assist clinicians and patients throughout the various steps of CBT-I workflow while addressing some of the identified challenges, and more broadly, how technology can make space for clinicians and patients to build quality therapeutic relationships.
論文アブストラクト： Due to the prevalence of personal health tracking, cases of self-logged data being utilized in the clinic are gradually increasing. However, obstacles to clinicians' ability to further adopt such data-driven medical consultations in the existing workflow remain, such as lack of time and poor interoperability. In this paper, we conducted a workshop to design a clinician interface supporting the integration of data-driven consultation into the existing workflow and investigate the role of the interface in situ. After implementing the clinician interface designed based on the workshop results, we observed 32 cases of actual use within the clinical context. We found that our interface, DataMD, helped the clinician construct a new workflow, enhanced the clinician's counseling skills, and facilitated more in-depth conversation. This paper contributes to empirically identifying the role of a clinician interface through a user-centered design approach.
論文アブストラクト： When self-tracking encounters clinical practices, the data is reshaped by goals and expertise that exist within a healthcare framework. To uncover these shaping practices, we provided a Fitbit Zip step-count sensor to nine patients with Parkinson's disease. Each patient wore the sensor for four weeks and then returned for a clinical visit with their neurologist. Our analysis focuses on this first clinical visit after four weeks of data had been collected. Our use of conversation analysis of both talk and action makes visible the practices engaged in by both collaborative members to 'craft a view' of the data toward shared decision making. Our findings reveal the deliberate guiding of attention to specific interpretations of the data through both talk and actions and we explain how our systematic analysis has uncovered tools for the mutually beneficial crafting practices of the clinician and patient.
パーキンソン病患者9人にFitbit Zipステップカウントセンサを提供した。 4週間着用し、その後、神経科医との臨床訪問のために戻った。会話と行動の両方の会話分析を使用することで, 共有された意思決定に向けたデータの「見解を作る」
論文アブストラクト： In this paper we report on a four-month long field trial of ThoughtCloud, a feedback collection platform that allows people to leave ratings and audio or video responses to simple prompts. ThoughtCloud was trialled with four organisations providing care services for people with disabilities. We conducted interviews with staff and volunteers that used ThoughtCloud before, during and after its deployment, and workshops with service users and staff. While the collection of feedback was high, only one organisation regularly reviewed and responded to collected opinions. Furthermore, tensions arose around data access and sharing, and the mismatch of values between "giving voice" and the capacity for staff to engage in feedback practices. We contribute insights into the challenges faced in using novel technologies in resource constrained organisations, and discuss opportunities for designs that give greater agency to service users to engage those that care for them in reflecting and responding to their opinions.
ThoughtCloud: 人々が評価や音声やビデオの応答を簡単に残すことを可能にするフィードバック収集プラットフォームである。 ThoughtCloudは、障害を持つ人々にケアサービスを提供する4つの団体で試用した。