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Health information technology (HIT) is a widely recognized strategy to encourage cancer patients and caregivers to participate in healthcare delivery in a sustainable and cost-effective way. In the context of autologous hematopoietic cell transplant (HSCT), HIT-enabled tools have the potential to effectively engage, educate, support, and optimize outcomes of patients and caregivers in the outpatient setting. This study sought to leverage human-centered design to develop a high-fidelity prototype of a HIT-enabled psychoeducational tool for HSCT caregivers. Phase 1 focuses on breadth and depth of information gathering through a systematic review and semi-structured interviews to determine optimal tool use. Phase 2 engages in human-centered design synthesis and visualization methods to identify key opportunities for the HIT design. Phase 3 employs human-centered design evaluation, engaging caregivers to respond to low-fidelity concepts and scenarios to help co-design an optimal tool for HSCT. This study outlines a hybrid method of healthcare delivery research and human-centered design to develop technology-enabled support for HSCT caregivers. Herein, we present a design methodology for developing a prototype of HIT-enabled psychoeducational tool which can be leveraged to develop future eHealth innovations to optimize HSCT.

We have conducted a pragmatic clinical trial aimed to assess whether an electrocardiogram (ECG)-based, artificial intelligence (AI)-powered clinical decision support tool enables early diagnosis of low ejection fraction (EF), a condition that is underdiagnosed but treatable. In this trial ( NCT04000087 ), 120 primary care teams from 45 clinics or hospitals were cluster-randomized to either the intervention arm (access to AI results; 181 clinicians) or the control arm (usual care; 177 clinicians). ECGs were obtained as part of routine care from a total of 22,641 adults (N = 11,573 intervention; N = 11,068 control) without prior heart failure. The primary outcome was a new diagnosis of low EF (≤50%) within 90 days of the ECG. The trial met the prespecified primary endpoint, demonstrating that the intervention increased the diagnosis of low EF in the overall cohort (1.6% in the control arm versus 2.1% in the intervention arm, odds ratio (OR) 1.32 (1.01–1.61), P = 0.007) and among those who were identified as having a high likelihood of low EF (that is, positive AI-ECG, 6% of the overall cohort) (14.5% in the control arm versus 19.5% in the intervention arm, OR 1.43 (1.08–1.91), P = 0.01). In the overall cohort, echocardiogram utilization was similar between the two arms (18.2% control versus 19.2% intervention, P = 0.17); for patients with positive AI-ECGs, more echocardiograms were obtained in the intervention compared to the control arm (38.1% control versus 49.6% intervention, P

The National Academies Board on Human Systems Integration (BOHSI) has organized this session exploring the state of the art and research and design frontiers relating to the application of Artificial Intelligence (AI) technologies to Healthcare. Advances in AI, machine learning, and robotics promise to revolutionize access to and quality of healthcare. At the same time lessons learned from earlier applications of AI technologies suggest a need to carefully consider the user and use context and the need for effective human-machine teaming design to avoid brittle systems that fail to be used or worse that negatively impact patient safety. The Panel brings together prominent researchers from both the Human Factors and Computer Science and AI communities to discuss promising applications, challenges and short-falls and ways forward for achieving the promise of enhanced delivery of health care through application of AI technologies.

Background A deep learning algorithm to detect low ejection fraction (EF) using routine 12-lead electrocardiogram (ECG) has recently been developed and validated. The algorithm was incorporated into the electronic health record (EHR) to automatically screen for low EF, encouraging clinicians to obtain a confirmatory transthoracic echocardiogram (TTE) for previously undiagnosed patients, thereby facilitating early diagnosis and treatment. Objectives To prospectively evaluate a novel artificial intelligence (AI) screening tool for detecting low EF in primary care practices. Design The EAGLE trial is a pragmatic two-arm cluster randomized trial ( NCT04000087 ) that will randomize >100 clinical teams (i.e., clusters) to either intervention (access to the new AI screening tool) or control (usual care) at 48 primary care practices across Minnesota and Wisconsin. The trial is expected to involve approximately 400 clinicians and 20,000 patients. The primary endpoint is newly discovered EF ≤50%. Eligible patients will include adults who undergo ECG for any reason and have not been previously diagnosed with low EF. Data will be pulled from the EHR, and no contact will be made with patients. A positive deviance qualitative study and a post-implementation survey will be conducted among select clinicians to identify facilitators and barriers to using the new screening report. Summary This trial will examine the effectiveness of the AI-enabled ECG for detection of asymptomatic low EF in routine primary care practices and will be among the first to prospectively evaluate the value of AI in real-world practice. Its findings will inform future implementation strategies for the translation of other AI-enabled algorithms.

Early drug development for cancer requires broad collaboration and skilled clinical investigators to enable enrollment of patients whose tumors have defined molecular profiles. To respond to these challenges, the National Cancer Institute (NCI) transformed its 60-year-old early-phase drug development program in 2014 into the Experimental Therapeutics Clinical Trials Network (ETCTN). The ETCTN is a consolidated, national network of 40+ academic institutions responsible for conducting more than 100 early-phase clinical trials. It promotes team science coordinated among basic, translational, and clinical investigators, emphasizing the inclusion of early career trialists. This perspective provides a brief overview of the ETCTN, summarizes its successes and challenges over its first grant funding cycle, and discusses the program's future directions. Measures indicated strong connectivity across the institutions, significant increases in investigator approval of the ETCTN scientific portfolio from years 1 to 4, and substantial research activity over 5 years, with 334 letters of intent submitted, 102 trials activated, and 3,570 patients accrued. The ETCTN's successful adoption relied heavily on the inclusion of senior investigators who have long-standing interactions with the NCI and a willingness to participate in a team science approach and to mentor early career investigators. In addition, NCI invested substantial resources in a centralized infrastructure to conduct trials and to support the inclusion of biomarkers in its studies. The ETCTN provides evidence that a collaborative national clinical trial network for early drug development is feasible and can address the demands of precision medicine approaches to oncologic clinical trials.

While there is significant enthusiasm in the medical community about the use of artificial intelligence (AI) technologies in healthcare, few research studies have sought to assess patient perspectives on these technologies. We conducted 15 focus groups examining patient views of diverse applications of AI in healthcare. Our results indicate that patients have multiple concerns, including concerns related to the safety of AI, threats to patient choice, potential increases in healthcare costs, data-source bias, and data security. We also found that patient acceptance of AI is contingent on mitigating these possible harms. Our results highlight an array of patient concerns that may limit enthusiasm for applications of AI in healthcare. Proactively addressing these concerns is critical for the flourishing of ethical innovation and ensuring the long-term success of AI applications in healthcare.

Background Smartphone mobile apps are frequently used in standalone or multimodal smoking cessation interventions. However, factors that impede or improve app usage are poorly understood. Objective This study used the supportive accountability model to investigate factors that influence app usage in the context of a trial designed to reduce maternal smoking in low-income and predominantly minority communities. Methods We conducted a secondary analysis of data (N=181) from a randomized controlled trial that included a smoking cessation app (QuitPal-m). Supportive accountability was measured by the number of times a participant was advised by their cessation counselor to use QuitPal-m. Participants reported app use helpfulness and barriers. Investigators tracked reported phone and technical problems that impeded app use. Results Most participants rated the app as very helpful (103/155, 66.5%), but daily use declined rapidly over time. App use was positively related to the level of perceived app helpfulness (P=.02) and education (P=.002) and inversely related to perceived barriers (P=.003), phone technical problems (P Conclusions Findings show the utility of supportive accountability for increasing smoking cessation app use in a predominantly low-income, minority population, particularly if quit motivation is low. Results also highlight the importance of addressing personal and phone/technical barriers in addition to adding supportive accountability. Trial Registration ClinicalTrials.gov NCT02602288; https://clinicaltrials.gov/ct2/show/NCT02602288

BACKGROUND Smartphone mobile apps are frequently used in standalone or multimodal smoking cessation interventions. However, factors that impede or improve app usage are poorly understood. OBJECTIVE This study used the supportive accountability model to investigate factors that influence app usage in the context of a trial designed to reduce maternal smoking in low-income and predominantly minority communities. METHODS We conducted a secondary analysis of data (N=181) from a randomized controlled trial that included a smoking cessation app (QuitPal-m). Supportive accountability was measured by the number of times a participant was advised by their cessation counselor to use QuitPal-m. Participants reported app use helpfulness and barriers. Investigators tracked reported phone and technical problems that impeded app use. RESULTS Most participants rated the app as very helpful (103/155, 66.5%), but daily use declined rapidly over time. App use was positively related to the level of perceived app helpfulness (P=.02) and education (P=.002) and inversely related to perceived barriers (P=.003), phone technical problems (PPPP=.03), independent of education and phone or app problems. CONCLUSIONS Findings show the utility of supportive accountability for increasing smoking cessation app use in a predominantly low-income, minority population, particularly if quit motivation is low. Results also highlight the importance of addressing personal and phone/technical barriers in addition to adding supportive accountability. CLINICALTRIAL ClinicalTrials.gov NCT02602288; https://clinicaltrials.gov/ct2/show/NCT02602288

Using a human-centered design method, our team sought to envision a new model of care for women experiencing low-risk pregnancy. This model, called OB Nest, aimed to demedicalize the experience of pregnancy by providing a supportive and empowering experience that fits within patients' daily lives. To explore this topic, we invited women to use self-monitoring tools, a text-based smartphone application to communicate with their care team, and moderated online communities to connect with other pregnant women. Through observations of tool use and patient- and care team-provided feedback, we found that self-measurement and access to a fetal heart monitor provided women with confidence and joy in the progress of their pregnancies while shifting their position to being an active participant in their care. The smartphone application gave women direct access to their care team, provided continuity, and removed hurdles in establishing communication. The online community platform was a space where women in the same obstetric clinic could share nonmedical questions and advice with one another. This created a sense of community, leveraged the knowledge of women, and provided a venue beyond the clinic visit for information exchange. These findings were integrated into the design of the Mayo Clinic OB Nest model. This model redistributes care based on the individual needs of patients by providing self-measurement tools and continuous flexible access to their care team. By enabling women to meaningfully participate in their care, there is potential for cost savings and improved patient satisfaction.

Rationale Severe acute respiratory syndrome Coronavirus 2 (SARS CoV-2), the virus that causes COVID-19, and consequent social distancing directives have been observed to negatively impact social relationships but the impact of these changes on the quality of social relationships at a population level has not been explored. Objective To evaluate changes in social relationships in a U.S. population sample during a time of social distancing. Methods We deployed a matched, longitudinal survey design of the National Institutes of Health Adult Social Relationship Scales to assess the social aspects of emotional support, instrumental support, friendship, loneliness, perceived hostility, and perceived rejection from a time without social distancing (February 2018) to a time where social distancing directives were active (May 2020). Changes in social relationships were compared using paired t-tests, and generalized linear regression models were constructed to identify subpopulations experiencing differential changes in each subdomain of social relationships during social distancing. Results Within our sample population, individuals experienced an increased sense of emotional support, instrumental support, and loneliness, and decreased feelings of friendship and perceived hostility during a period of social distancing. Individuals with low self-rated health experienced a decreased sense of emotional support, and females experienced increased feelings of loneliness compared with males. Conclusions Social distancing measurably impacts social relationships and may have a disproportionate impact on females and individuals with lower self-rated health. If novel emergent infectious diseases become more commonplace, social interventions may be needed to mitigate the potential adverse impact of social distancing on social relationships.

The article details the materials that will be used in a clinical trial - ECG AI-Guided Screening for Low Ejection Fraction (EAGLE): Rationale and design of a pragmatic cluster randomized trial [1]. It includes a clinician-facing action recommendation report that will translate an artificial intelligence algorithm to routine practice and an alert when a positive screening result is found. This report was developed using a user-centered approach via an iterative process with input from multiple physician groups. Such data can be reused and adapted to translate other artificial intelligence algorithms. This article also includes data collection forms we developed for the clinical trial aiming to evaluate the artificial intelligence algorithm. Such materials can be adapted for other clinical trials.

Stories are like searchlights and spotlights; they brighten up parts of the stage while leaving the rest in darkness.... Stories aid the seekers of comprehension by separating the relevant from the irrelevant, actions from their settings, the plot from its background, and the heroes or the villains at the centre of the plot from the hosts of supernumeraries and dummies. It is the mission of stories to select, and it is in their nature to include through exclusion and to illuminate through casting shadows. It is a grave misunderstanding, and injustice, to blame stories for favoring one part of the stage while neglecting another. Without selection there would be no story. (1) In a letter to the poet Antonio Somma on 23 April 1853, Giuseppe Verdi described the powerful impact of William Shakespeare's plays and how he had best realized their dramatic conflict and variety of expression in Rigoletto: Per l'istessa ragione preferisco Shakespeare a tutti i drammatici, senza eccettuarne i Greci. A me pare che il miglior soggetto in quanto ad effetto che io m'abbia finora posto in musica (non intendo parlare affatto sul merito letterario e poetico) sia Rigoletto. Vi sono posizioni potentissime, varieta, brio, patetico ... (2) (For the same reason [of variety] I prefer Shakespeare to all other dramatists, not excepting the Greeks. It seems to me that the best subjects I have set to music so far, from the point of view of effect (I don't mean at all to allude to its literary or poetic merit) is Rigoletto. It has very powerful situations, variety, verve, pathos ...) Verdi identified two aspects of Shakespeare's plays as central to his own dramatic vision: first, Shakespeare's variety of mood and location, such as between the interior of the castle and the exterior of the heath, telescoped the action and demanded the audience's active, imaginative participation much more than the classical unities of time, place, and action. Second, counterpointing strongly drawn characters tightened the plot's web of treachery and retribution and propelled the action to its climax. Through such vivid characterization and powerful plots, Verdi developed new techniques within existing conventions of nineteenth-century Italian opera, integrating arias and duets into larger and more cohesive units. In the same letter, Verdi proposed to Somma that they should work together on an opera on King Lear. Far from the first time Verdi had expressed interest in the subject, this was part of a succession of Lear projects that, for a variety of reasons, had either stalled or been allowed to lapse. These forays of engagement and withdrawal from Lear territory raise the question, not so much of what attracted him--that much is evident from his letters--but what prevented him from writing an opera on King Lear. Perhaps it is possible to date the beginning of his involvement with King Lear to a new translation of Shakespeare, published in Milan in January 1843 by Giulio Carcano, which brought into sharp focus the abrasive confrontation about the abuse of power between Lear and his older daughters and the touching reconciliation with Cordelia near the end of the play before her death. Envisioning the same elements of emotional confrontation and dramatic action that had contributed to the outstanding success of Nabucco the previous year, Verdi raised the possibility of a Lear opera with Count Mocenigo, director of operatic productions at the Teatro La Fenice in Venice, in a letter dated 6 June 1843. Soon afterwards, though, and even before he had found a librettist and begun work, Verdi started to voice all kinds of concerns, not so much about the plan as about the process. Could he complete the work on time to fulfill his contract to La Fenice? Where would he find suitable singers for the main roles, especially the huge title role, which demanded not only a consummate singer but a powerful actor who could convey the power of kingship and the pathos of Lear's ruined mind? …

Hydrazine-based fuels are commonly used in missiles, spacecraft and space launch vehicles. These chemicals are extremely toxic, highly energetic, and consequentially very hazardous. Currently, monomethylhydrazine (MMH) is considered to be the predominant fuel for spontaneous ignition. The current threshold limit value (TLV) is established at 10 ppb by the American Conference of Governmental Industrial Hygienists (ACGIH). Therefore, monitoring leakage of these chemicals in ambient air becomes highly important for compliance monitoring. InnoSense LLC's (ISL) all-optical leak detector can be calibrated to detect leaks in the parts-per-million to parts-per-billion range. ISL's innovative sensor device incorporates a self-referenced, fiber-optics-based sensor platform for detecting MMH from -46{degree sign}C to +71{degree sign}C. Additionally, an optical sensor system can decrease payload in space applications, and be networked to monitor multiple locations in situ and in real time. This paper discusses the use of an organically modified silicate (Ormosil) matrix to develop the optical leak detector for MMH.

Despite the emphatic, rhetorical endings of the second and eighth symphonies, many of Mahler's other movements and works avoid closure as a gesture of finality. Instead, closure is subverted in various ways, including delay, interpolation, and suspension. Such interpolations affect more than the finality of the ending: They split the succession of events into different lines of time and action streams. When a disrupted line is later resumed, our perception has nevertheless been affected by the interpolation, which requires a re-evaluation of both function and meaning in the context of the work or movement. By-passed closure can be considered from two perspectives; on the one hand, interpolation in Mahler is seen as an extension of the interrupted cadence. On the other hand, instead of a single line of compositional process and resolution, the reinterpretation of structure opens up a “garden of forking paths,” as variant viewpoints in the delineation of design. Such alternative structural reinterpretations...

This paper explores the emergence of a new paradigm we call the ‘media fabric’ — a semi-intelligent organism consisting of a vast and evolving collection of media artefacts, structures and programs that support our engagement in meaningful real-time dialogues, art making, and social interaction. Situated in and around modern communications networks, the media fabric beckons us into an evolving landscape of creative story potential that is synergistic with our imagination, integral to our everyday life, mindful of itself and our intentions, improvisationally shaped, and provides us with interactions and remaindered artefacts that are evocative and self-reflective.

In order to build software that can deeply understand people and our problems, we require computational tools that give machines the capacity to learn and reason about everyday life. We describe three commonsense knowledge bases that take unconventional approaches to representing, acquiring, and reasoning with large quantities of commonsense knowledge. Each adopts a different approach — ConceptNet is a large-scale semantic network, LifeNet is a probabilistic graphical model, and StoryNet is a database of story-scripts. We describe the evolution, architecture and operation of these three systems, and conclude with a discussion of how we might combine them into an integrated commonsense reasoning system.

Several web-based search engines have been developed to assist individuals to find clinical trials for which they may be interested in volunteering. However, these search engines may be difficult for individuals with low health and computer literacy to navigate. The authors present findings from a usability evaluation of clinical trial search tools with 41 participants across the health and computer literacy spectrum. The study consisted of 3 parts: (a) a usability study of an existing web-based clinical trial search tool; (b) a usability study of a keyword-based clinical trial search tool; and (c) an exploratory study investigating users' information needs when deciding among 2 or more candidate clinical trials. From the first 2 studies, the authors found that users with low health literacy have difficulty forming queries using keywords and have significantly more difficulty using a standard web-based clinical trial search tool compared with users with adequate health literacy. From the third study, the authors identified the search factors most important to individuals searching for clinical trials and how these varied by health literacy level.

This paper describes recent progress toward a framework and toolset for Very Distributed Storytelling. It focuses on three independent but interconnected axes of development: continuous story playout environments, story authoring systems, and scenarios for interaction, particularly those that operate in casual or formal architectural spaces. Aspects of these are explored in several systems currently under development at the Interactive Cinema Group of the MIT Media Laboratory. Agent Stories invites authors to develop story segments that know about their role in the story and agents that can use these role designations to orchestrate the playout of story parts. Happenstance, an ecologically based, context-sensitive "stage" for the performance of interactive narratives, provides an information landscape that is continuous in space and time, supports multiple viewpoints, and acts as a semiporous membrane to information and messages from the outside world. The CINEMAT and other large-scale interactive media pieces--situated in sensor-rich architectural spaces-- explore the relationships among immersion, interaction, narrative guidance, and public space.

Nutrition practice guidelines define a systematic approach for medical nutrition therapy (MNT) provided by dietitians and are derived from scientific evidence and expert opinion. Nutrition practice guidelines for persons with non-insulin-dependent diabetes mellitus (NIDDM) can be implemented for those with newly diagnosed or previously diagnosed NIDDM at the first visit to a dietitian for initial or ongoing MNT. The guidelines apply to patients treated with MNT alone, MNT and oral glucose-lowering agents, or MNT and insulin. They provide a framework to assist the dietitian in the assessment, intervention (nutrition prescription, education, goal setting), and evaluation of outcomes for MNT. Minimum referral data for clinical decision making and outcome criteria are defined. Basic nutrition care is defined as one visit with the dietitian. Nutrition practice guidelines care consists of a series of visits with the dietitian. At the second follow-up visit, the dietitian assesses what has been accomplished with the nutrition interventions. If the patient has implemented the nutrition recommendations to the best of his or her ability and has not achieved the treatment goals, the dietitian should notify the physician and recommend that changes in medical management are needed. Ongoing nutrition care is recommended at 6-month to 1-year intervals for both basic and practice guidelines care. J Am Diet Assoc. 1995; 95:999-1006.

Objective To conduct a cost analysis and cost-effectiveness study based on a randomized clinical trial of basic nutrition care (BC) and practice guidelines nutrition care (PGC) provided by dietitians in outpatient clinics. Design Subjects with non–insulin-dependent diabetes mellitus (NIDDM) from three states (Minnesota, Florida, Colorado) were randomly assigned to a group receiving BC or a group receiving PGC for a 6-month clinical trial. Along with data about medical and clinical outcomes, data about cost resources were collected. The cost-effectiveness of PGC compared with BC was calculated using per-patient costs and glycemic outcomes for the 6 months of the study. A net cost-effectiveness ratio comparing BC and PGC, including the cost savings resulting from changes in medical therapy, was also calculated. Subjects The study reports on a sample of 179 subjects with NIDDM between the ages of 38 and 76 years who completed the clinical trial. Results Patients in the PGC group experienced a mean 1.1±2.8mmol/L decrease in fasting plasma glucose level 6 months after entry to the study, for a total per-patient cost of $112. PGC costs included one glycated hemoglobin assay used by the dietitian to evaluate nutrition outcomes. Patients in the BC group experienced a mean 0.4±2.7mmol/L decrease, for a total per-patient cost of $42. In the PGC group, 17 persons had changes in therapy, which yielded an average 12-month cost savings prorated for all patients of $31.49. In contrast, in the BC group, 9 persons had changes in therapy, for an average 12-month prorated cost savings of $3.13. Each unit of change in fasting plasma glucose level from entry to the 6-month follow-up can be achieved with an investment of $5.75 by implementing BC or of $5.84 by implementing PGC. If net costs are considered (per-patient costs – cost savings due to therapy changes), the cost-effectiveness ratios become $5.32 for BC and $4.20 for PGC, assuming the medical changes in therapy were maintained for 12 months. Applications These findings suggest that individualized nutrition interventions can be delivered by experienced dietitians with a reasonable investment of resources. Cost-effectiveness is enhanced when dietitians are engaged in active decision making about intervention alternatives based on the patient's needs. J Am Diet Assoc. 1995; 95:1018-1024 .

Objective To assess the the effect of medical nutrition therapy (MNT) provided by dietitians on medical and clinical outcomes for adults with non–insulin-dependent diabetes mellitus (NIDDM), and to compare MNT administered according to practice guidelines nutrition care (PGC) to MNT administered with basic nutrition care (BC). Design A prospective, randomized, controlled clinical trial of two levels of MNT on metabolic control in persons newly diagnosed with or currently under treatment for NIDDM was conducted at diabetes centers in three states (Minnesota, Florida, and Colorado). BC consisted of a single visit with a dietitian; PGC involved an initial visit with a dietitian followed by two visits during the first 6 weeks of the study period. Data were collected at entry to the study and at 3 and 6 months. Subjects Results are reported for 179 men and women aged 38 to 76 years: 85 assigned randomly to BC and 94 to PGC. This represents 72% of the 247 subjects enrolled. An additional 62 adults with NIDDM at one site who had no contact with a dietitian were identified as a nonrandom comparison group. Outcomes Medical outcome measures included fasting plasma glucose (FPG), glycated hemoglobin (HbA 1c ), and serum lipid levels. Clinical outcomes included weight, body mass index, waist-to-hip ratio, and changes in medical therapy. Statistical analyses Initial analysis of the discrete variables was done using the χ 2 statistic with Yates' correction. Initial analysis of continuous variables was done by analysis of variance. The changes in variables between time periods were analyzed by paired t test, and comparisons between groups were analyzed using a t test for independent groups. Results At 6 months, PGC resulted in significant improvements in blood glucose control as indicated by FPG and HbA 1c levels and BC resulted in significant improvements in HbA 1c level. Participants assigned to the PGC group had a mean FPG level at 6 months that was 10.5% lower than the level at entry, and those in the BC group had a 5.3% lower value. Among subjects who had diabetes for longer than 6 months, those who received PGC had a significantly better HbA 1c level at 3 months compared with those receiving BC. The comparison group showed no improvement in glycemic control over a comparable 6 months. PGC subjects had significant improvements in cholesterol values at 6 months, and subjects in both the PGC and the BC groups had significant weight loss. Conclusions MNT provided by dietitians resulted in significant improvements in medical and clinical outcomes in both the BC and PGC groups and is beneficial to persons with NIDDM. Persons with a duration of diabetes longer than 6 months tended to do better with PGC than with BC. Because of the upward trend in glucose levels after 3 months, ongoing MNT by dietitians is important for long-term metabolic control. J Am Diet Assoc. 1995; 95:1009-1017 .

Older adults with strong social connections are at a reduced risk for health problems and mortality. We describe two field studies to inform the development of a virtual agent designed to provide long-term, continuous social support to isolated older adults. Findings include the topics that older adults would like to discuss with a companion agent, in addition to overall reactions to interacting with a remote-controlled companion agent installed in their home for a week. Results indicate a generally positive attitude towards companion agents and a rich research agenda for virtual companion agents.

Humans naturally share knowledge by telling stories. This is a form of knowledge exchange we engage in right from early childhood, and over time we learn to recall, order and organize our experiences as stories [1]. In this paper we describe the Open Mind Experiences (OMEX) system, a web-based knowledge acquisition tool that exploits our natural ability to tell and explain stories in order to build a large-scale commonsense knowledge base. We built OMEX to gather descriptions and explanations of everyday, 'common sense' experiences from volunteer contributors distributed across the Internet. We first describe the results of our previous attempt to collect commonsense knowledge from the general public, the Open Mind Common Sense (OMCS) project. The OMCS project focused on collecting largely assertional commonsense knowledge, and we describe some of its products and spin-offs. We then give several motivating reasons for why we now wish to collect more script-like knowledge. We then explain the features of the new OMEX site and give an evaluation of system based on a preliminary user study. We conclude by discussing our future directions.

This paper introduces a model for producing common sense metadata during video capture and describes how this technique can have a positive impact on content capture, representation, and presentation. Metadata entered into the system at the moment of capture is used to generate suggestions designed to help the videographer decide what to shoot, how to compose a shot and how to index their video material to best support their communication requirements. An approach and first experiments using a common sense database and reasoning techniques to support a partnership between the camera and videographer during video capture are presented.

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