Enhancing human-robot interaction (HRI) requires a deep understanding of engagement. This paper explores how to capture engagement within conversational HRI by examining multiple non-verbal communication cues. Specifically, we analyze the engagement of 16 participants in the context of a reminiscence task, which establishes a foundational dialogue between the robot and the user. Head pose and voice activation were the non-verbal communication cues used in this study. We developed a methodology that identifies and correlates these cues with engagement levels during specific epochs of interaction. By contrasting these cues against video annotations and self-reported feedback, we refine our understanding of engagement. Our results demonstrate that a multimodal approach to analysing engagement significantly outperforms unimodal analysis, where 11 out of 16 cases (68%) correlate with engagement, increasing accuracy compared to using them independently. Critically, the study reveals that objective and subjective methods to analyse engagement closely align with users' perceptions of engagement, emphasising the importance of integrated communication strategies in HRI.

This paper explores the design space for one-minute digital interventions that prompt immediate action without onboarding or sensing. By embracing Fogg's Behavior Model and four design principles informed by literature, the goal of these interventions was to provide triggers that encourage actions so simple that even people with low motivation would be willing to complete them. We examined the utility of these prompts by conducting a 14-day study with 22 participants interested in making small lifestyle improvements in at least one of three domains: physical activity, healthy eating, and mental well-being. When combined with insights drawn from participants' rewrites of our prompts, our findings suggest that intentional personalization through co-authorship could be a lightweight personalization mechanism that balances relevance with low friction.

Regular practice of gratitude has the potential to enhance psychological wellbeing and foster stronger social connections among young adults. However, there is a lack of research investigating user needs and expectations regarding gratitude-promoting applications. To address this gap, we employed a user-centered design approach to develop a mobile application that facilitates gratitude practice. Our formative study involved 20 participants who utilized an existing application, providing insights into their preferences for organizing expressions of gratitude and the significance of prompts for reflection and mood labeling after working hours. Building on these findings, we conducted a deployment study with 26 participants using our custom-designed application, which confirmed the positive impact of structured options to guide gratitude practice and highlighted the advantages of passive engagement with the application during busy periods. Our study contributes to the field by identifying key design considerations for promoting gratitude among young adults.

Background Current online interventions dedicated to assisting individuals in managing stress and negative emotions often necessitate substantial time commitments. This can be burdensome for users, leading to high dropout rates and reducing the effectiveness of these interventions. This highlights an urgent need for concise digital activities that individuals can swiftly access during instances of negative emotions or stress in their daily lives. Objective The primary aim of this study was to investigate the viability of using a brief digital exercise, specifically a reflective questioning activity (RQA), to help people reflect on their thoughts and emotions about a troubling situation. The RQA is designed to be quick, applicable to the general public, and scalable without requiring a significant support structure. Methods We conducted 3 simultaneous studies. In the first study, we recruited 48 participants who completed the RQA and provided qualitative feedback on its design through surveys and semistructured interviews. In the second study, which involved 215 participants from Amazon Mechanical Turk, we used a between-participants design to compare the RQA with a single-question activity. Our hypotheses posited that the RQA would yield greater immediate stress relief and higher perceived utility, while not significantly altering the perception of time commitment. To assess these, we measured survey completion times and gathered multiple self-reported scores. In the third study, we assessed the RQA’s real-world impact as a periodic intervention, exploring engagement via platforms such as email and SMS text messaging, complemented by follow-up interviews with participants. Results In our first study, participants appreciated the RQA for facilitating structured reflection, enabling expression through writing, and promoting problem-solving. However, some of the participants experienced confusion and frustration, particularly when they were unable to find solutions or alternative perspectives on their thoughts. In the second study, the RQA condition resulted in significantly higher ratings (P=.003) for the utility of the activity and a statistically significant decrease (P<.001) in perceived stress rating compared with the single-question activity. Although the RQA required significantly more time to be completed (P<.001), there was no statistically significant difference in participants’ subjective perceived time commitment (P=.37). Deploying the RQA over 2 weeks in the third study identified some potential challenges to consider for such activities, such as the monotony of doing the same activity several times, the limited affordances of mobile phones, and the importance of having the prompts align with the occurrence of new troubling situations. Conclusions This paper describes the design and evaluation of a brief online self-reflection activity based on cognitive behavioral therapy principles. Our findings can inform practitioners and researchers in the design and exploration of formats for brief interventions to help people with everyday struggles.

Objective: To develop and evaluate a smartphone application that accurately measures height and provides notifications when abnormalities are detected. Patients and Methods: A total of 145 (75 boys) participants with a mean age ± SD of 8.7±4.5 years (range, 1.0-17.0 years), from the Children’s Hospital at Barts Health Trust, London, United Kingdom, were enrolled in the study. “GrowthMonitor” (UCL Creatives) iPhone application (GMA) measures height using augmented reality. Using population-based (UK-WHO) references, algorithms calculated height SD score (HSDS), distance from target height (THSDSDEV), and HSDS change over time (ΔHSDS). Pre-established thresholds discriminated normal/abnormal growth. The GMA and a stadiometer (Harpenden; gold standard) measured standing heights of children at routine clinic visits. A subset of parents used GMA to measure their child’s height at home. Outcome targets were 95% of GMA measurements within ±0.5 SDS of the stadiometer and the correct identification of abnormal HSDS, THSDSDEV, and ΔHSDS. Results: Bland-Altman plots revealed no appreciable bias in differences between paired study team GMA and stadiometer height measurements, with a mean of the differences of 0.11 cm with 95% limits of agreement of −2.21 to 2.42 cm. There was no evidence of greater bias occurring for either shorter/younger children or taller/older children. The 2 methods of measurements were highly correlated (R=0.999). GrowthMonitor iPhone application measurements performed by parents in clinic and at home were slightly less accurate. The κ coefficient indicated reliable and consistent agreement of flag alerts for HSDS (κ=0.74) and THSDSDEV (κ=0.88) between 83 paired GMA and stadiometer measurements. GrowthMonitor iPhone application yielded a detection rate of 96% and 97% for HSDS-based and THSDSDEV-based red flags, respectively. Forty-two (18 boys) participants had GMA calculated ΔHSDS using an additional height measurement 6-16 months later, and no abnormal flag alerts were triggered for ΔHSDS values. Conclusion: GrowthMonitor iPhone application provides the potential for parents/carers and health care professionals to capture serial height measurements at home and without specialized equipment. Reliable interpretation and flagging of abnormal measurements indicate the potential of this technology to transform childhood growth monitoring.

The ability to resolve conflict while preserving relationships is ever more vital in our divisive, global society. Traditional conflict-resolution training is mostly delivered in one-off sessions with practice opportunities limited to a fixed number of pre-defined role play scenarios. This is insufficient for acquiring the notoriously difficult skill of communicating effectively amidst conflict. We present a new web application that teaches relationship-preserving language for conflict resolution. Our system uses artificial intelligence (AI) to provide automated feedback to open text, natural language input, alerting users to language that may sound judgmental or be otherwise ineffective for resolving conflict. Our application prompts users to respond to scenarios of workplace conflict while receiving feedback from the AI. We conducted qualitative interviews with 13 participants and explore a range of themes relevant to our users’ experiences. We discuss design implications of our results through the cognitive, active, affective and relational dimensions of experiential design.

Social Assistive Robotics are widely used in health-care to improve conventional treatments and increase patient engagement. Reminiscence Therapy (RT) is one application where social robots can be incorporated. RT is commonly used with people living with dementia, and it aims to evoke users' memories and stimulate cognitive functioning using nostalgic materials. This paper presents a feasibility study of a data-driven human-robot conversational interface for reminiscing sessions. Ten healthy participants were recruited to evaluate the usability of the interface, user engagement and interaction perception. The results showed that most of the participants followed the conversation, and half of them contributed highly (i.e., interaction/speaking time >51.54%) during the interaction with the robot. Participants perceived the system as being able to generate context-relevant dialogue.

The ubiquity of the internet holds tremendous promise for users to access interactive support for mental well-being, as evidenced by the proliferation of apps enabling experiences like peer-to-peer discussion or automated chatbots. In contrast, we investigate whether and to what extent digital interfaces as simple as questionnaire webforms can help people help themselves by reflecting on stressful situations and feelings. In this work, we experiment with a brief reflective questioning activity (RQA) that prompts people to externalize their underlying thoughts and emotions on a troubling situation. Inspired by principles of cognitive behavioral therapy, the 15-minute activity encourages self-reflection without a human or automated conversational partner. A deployment of the RQA on Amazon Mechanical Turk suggests that people perceive several benefits from the RQA, including structured awareness of their thoughts and problem-solving around managing their emotions. Quantitative evidence from a randomized experiment suggests people find that our RQA makes them feel less worried about their selected situation, and is worth the time investment. We find similar benefits in a real-world deployment of a two-week technology probe deployment with 11 participants, which also suggests people see benefits to doing this activity repeatedly as long as it does not get monotonous over time. Results from our prototype RQA provides a foundational first step in exploring the design space of digital interfaces that leverage questions for user-driven reflection, whether they be for mental well-being or other areas where psychologically-informed design can empower users to help themselves.

We investigate users' perspectives on an online reflective question activity (RQA) that prompts people to externalize their underlying emotions on a troubling situation. Inspired by principles of cognitive behavioral therapy, our 15-minute activity encourages self-reflection without a human or automated conversational partner. A deployment of our RQA on Amazon Mechanical Turk suggests that people perceive several benefits from our RQA, including structured awareness of their thoughts and problem-solving around managing their emotions. Quantitative evidence from a randomized experiment suggests people find that our RQA makes them feel less worried by their selected situation and worth the minimal time investment. A further two-week technology probe deployment with 11 participants indicates that people see benefits to doing this activity repeatedly, although the activity may get monotonous over time. In summary, this work demonstrates the promise of online reflection activities that carefully leverage principles of psychology in their design.

Objectives Healthcare staff can be prone to high levels of stress and research investigating mindfulness-based courses for this population is showing promise. Given the demands of healthcare work, shortened mindfulness courses may be more appropriate. The aim of the study was to evaluate the utility of a workplace-adapted mindfulness course (MBOE) in a hospital setting, including research on workplace-specific outcomes beyond stress reduction and data relating to home practice with a mobile app. Method The effects of assignment to a workplace-adapted, 6-week mindfulness course or a waitlist control condition on dispositional mindfulness, perceived stress and fulfilment of basic psychological needs at work were examined in a sample of 65 hospital staff. Results Compared with waitlist, staff taking the course showed significant increases in mindfulness and psychological need fulfilment and reductions in perceived stress. Mean levels of perceived stress reduced from a high level to within published norms. Reductions in stress and increases in mindfulness, autonomy and competence remained stable at follow-up. Increased mindfulness mediated improvements in need fulfilment and reductions in stress. Attendance and use of a mobile app for home practice were associated with positive outcomes. Social factors (relatedness) associated with the delivery and outcome of the course were also explored. Conclusions The results indicate that a workplace-adapted, short-format mindfulness course can achieve positive results in line with mindfulness courses for other contexts. Questions were raised regarding which distinct elements may improve outcomes, e.g. home practice and dispositional mindfulness vs. learning environment on more general improvements.

Abstract Previous researchers have emphasised the need for more student-centred approaches to online learning. This study presents and assesses the feasibility of a tailoring system, which adapts vicarious experience information to best benefit the learners’ self-efficacy (SE), based upon the model–observer similarity hypothesis. This hypothesis states that the benefit of vicarious experience information is positively correlated with the levels of similarity between the model within the information and the individual observing it. Participants took part in online learning, which included a set task. Before completing the set task, they were shown vicarious experience information in the form of a fictional testimonial from a previous individual who had completed the task. Participants were exposed to one of two types of testimonials: a testimonial chosen by the tailoring system to ensure high levels of model–observer similarity, or a generic testimonial. Overall, the results found that using a tailoring system to ensure high levels of model–observer similarity did result in the testimonial information having a more positive effect on an individual’s task-specific SE when compared to generic testimonial information. The results support the feasibility of tailoring within online learning to increase the effectiveness of testimonial information in increasing an individual’s efficacy beliefs.

An individual’s general self-efficacy affects their cognitive behaviours in a number of ways. Previous research has found general self-efficacy to influence how people interpret persuasive messages designed to encourage behavioural change. No previous work has looked into how general self-efficacy affects the interpretation of vicarious experience information and how this affects self-efficacy in being able to complete a set task within a career skills online learning environment. The study presented considers this gap in knowledge, analysing the effect of six different types of vicarious experience information on the self-efficacy of online workshop participants to complete a set task. In analysing the results, each participant’s general self-efficacy was considered. Results showed individuals with low general self-efficacy to find vicarious experience information significantly less beneficial for their self-efficacy in completing a set task when compared to others with high general self-efficacy. Those with low general self-efficacy were more likely to make negative self-comparisons to the vicarious experience information, restricting its potential to increase their self-efficacy. In contrast, participants with high general self-efficacy found many of the vicarious experience information presented to be beneficial to their self-efficacy to complete the set task as they were more likely to dismiss any information they interpreted to be negative. Results from this study highlight the importance of more research into how vicarious experience information can be designed and presented in a way that ensures benefit to the task-specific self-efficacy of all individuals, regardless of their general self-efficacy beliefs at the time.

Wearable devices play an increasingly important role in maintaining and improving the sense of connectedness between loved-ones. However, despite affording numerous novel interactions and possibilities, wearables are easily discarded. And their aesthetic and functional designs are often gadget-like, or rely on cultural clichés, underutilizing the rich history of their “ analogue ” counterpart of sentimental jewelry . In this paper, we conduct a content analysis study to understand practices associated with the use of sentimental jewelry . We uncover that in contrast to social wearables , analogue artefacts are rarely paired and are intended to be worn by female partners , friends and family members. They are seldom personalized, and either explicitly convey affection , good luck or motivation or allow users to infuse their own meaning into them, or. These findings give us insights that could increase relevance of social wearables for their users, and as a result, enhance user’s wellbeing and connectedness to their loved-ones.

Maintaining a sense of relatedness with loved-ones is one of the top human needs and predictors of wellbeing. HCI research has increasingly focused on the ways and implications of mediating relatedness through technology. However, current research is at times removed from established theories in related disciplines and it lacks consistent tools for selecting user groups and appropriate interaction strategies. Our paper identifies the characteristics of potential users of tech-mediated devices in conjunction with related disciplines. It then examines users' preferences for the six Strategies of Mediating Intimate Relationships though Technology , identified by Hassenzahl et al. in the paper "All you need is Love" , in interaction within different types of relationships (with friends, partners, siblings, etc.). Our paper proposes expanding these strategies to account for varied levels of reciprocity and for essential/unwanted strategies identified by users in different types of relationships. It concludes with implications and suggestions for future research.

Patients with low grade malignant bronchogenic neoplasms present with insidious airway symptoms as these are rare indolent tumors occurring in young to middle aged adults. There is paucity of data on the role of airway intervention in the management of low grade neoplasm of the major airway as its prevalence amongst all primary bronchogenic malignancy is low. Study inclusion criteria were: 1) low grade malignant bronchogenic neoplasm confirmed on histology and 2) tumor present in the tracheobronchial tree requiring airway intervention as part of the therapeutic management. There were 13 patients (8 females) with a mean age of 40.7 (range 30-66) years. Histological types include 8 adenoid cystic carcinomas, 4 carcinoids and 1 mucoepidermoid carcinoma. Insidious symptoms often treated for benign obstructive airway diseases and respiratory infections, over a mean of 15 (range 3-31) months. About half had normal CXR as the tumor was distributed most frequently in the trachea (46.2% of 13) followed by the main bronchi (30.8%), lobar bronchi (23%). Six (46.2%) patients, all with adenoid cystic carcinoma, underwent emergent bronchoscopic intervention to secure greater airway patency before definitive therapy with surgery or/and radiotherapy. All airway interventions were performed via the rigid bronchoscope under deep intravenous sedation with assisted ventilation. The types of intervention included: NdYAG laser resection (all 13), rigid tube or forceps resection (13), balloon dilatation (7) and silicone stenting (3). There were no procedural complications. Two patients, both with typical carcinoid, had bronchoscopic curative resection and the majority (9 out of 13) of the patients underwent surgery. External beam radiotherapy was administered to 5 (38.5%) of the patients when surgical resection was deemed not feasible (2) or with positive margins (3). None received systemic therapy. Prolonged good palliation was achieved for 4 (30.8%) patients with surgically unresectable lesions or recurrences via endoscopic therapy with or without radiation, including brachytherapy. The mean follow up duration was 64 months (range 28-100) months. Airway intervention for low grade malignant bronchogenic neoplasm is an important part of the therapeutic armamentarium. Its role may be 1) emergent for critical airway obstruction where establishment of adequate airway patency is necessary prior to definitive therapy with surgery and/or radiotherapy, or 2) curative for lesions limited to within the tracheobronchial wall, or 3) palliative to relief the suffocating distressing symptom in those with no or limited oncologic/surgical options.

The Internet has enabled learning at scale, from Massive Open Online Courses (MOOCs) to Wikipedia. But online learners may become passive, instead of actively constructing knowledge and revising their beliefs in light of new facts. Instructors cannot directly diagnose thousands of learners' misconceptions and provide remedial tutoring. This paper investigates how instructors can prompt learners to reflect on facts that are anomalies with respect to their existing misconceptions, and how to choose these anomalies and prompts to guide learners to revise incorrect beliefs without any feedback. We conducted two randomized experiments with online crowd workers learning statistics. Results show that prompts to explain why these anomalies are true drive revision towards correct beliefs. But prompts to simply articulate thoughts about anomalies have no effect on learning. Furthermore, we find that explaining multiple anomalies is more effective than explaining only one, but the anomalies should rule out multiple misconceptions simultaneously.

A classic debate in cognitive science revolves around understanding how children learn complex linguistic patterns, such as restrictions on verb alternations and contractions, without negative evidence. Recently, probabilistic models of language learning have been applied to this problem, framing it as a statistical inference from a random sample of sentences. These probabilistic models predict that learners should be sensitive to the way in which sentences are sampled. There are two main types of sampling assumptions that can operate in language learning: strong and weak sampling. Strong sampling, as assumed by probabilistic models, assumes the learning input is drawn from a distribution of grammatical samples from the underlying language and aims to learn this distribution. Thus, under strong sampling, the absence of a sentence construction from the input provides evidence that it has low or zero probability of grammaticality. Weak sampling does not make assumptions about the distribution from which the input is drawn, and thus the absence of a construction from the input as not used as evidence of its ungrammaticality. We demonstrate in a series of artificial language learning experiments that adults can produce behavior consistent with both sets of sampling assumptions, depending on how the learning problem is presented. These results suggest that people use information about the way in which linguistic input is sampled to guide their learning.

Most cognitive psychology experiments evaluate models of human cognition using a relatively small, well-controlled set of stimuli. This approach stands in contrast to current work in neuroscience, perception, and computer vision, which have begun to focus on using large databases of natural images. We argue that natural images provide a powerful tool for characterizing the statistical environment in which people operate, for better evaluating psychological theories, and for bringing the insights of cognitive science closer to real applications. We discuss how some of the challenges of using natural images as stimuli in experiments can be addressed through increased sample sizes, using representations from computer vision, and developing new experimental methods. Finally, we illustrate these points by summarizing recent work using large image databases to explore questions about human cognition in four different domains: modeling subjective randomness, defining a quantitative measure of representativeness, identifying prior knowledge used in word learning, and determining the structure of natural categories.

Identifying patterns in the world requires noticing not only unusual occurrences, but also unusual absences. We examined how people learn from absences, manipulating the extent to which an absence is expected. People can make two types of inferences from the absence of an event: either the event is possible but has not yet occurred, or the event never occurs. A rational analysis using Bayesian inference predicts that inferences from absent data should depend on how much the absence is expected to occur, with less probable absences being more salient. We tested this prediction in two experiments in which we elicited people's judgments about patterns in the data as a function of absence salience. We found that people were able to decide that absences either were mere coincidences or were indicative of a significant pattern in the data in a manner that was consistent with predictions of a simple Bayesian model.