Publications
302 results found
Kirby P, Lai H, Horrocks S, et al., 2024, Patient and public involvement in technology-related dementia research: a scoping review, JMIR Aging, Vol: 7, ISSN: 2561-7605
Background:Technology-related research for people with dementia and their carers often aims to enable people to remain living at home for longer and to prevent unnecessary hospital admissions. To develop research that is person-centred, effective and ethical, patient and public involvement (PPI) is necessary, though may be perceived as more difficult with this cohort. With recent and rapid expansions in health and care related technology, this review explores how, and with what impact, collaborations between researchers and stakeholders such as people with dementia have taken place.Objective:To describe approaches to PPI used to date in technology-related dementia research, along with the barriers and facilitators and impact of PPI in this area.Methods:A scoping review of literature relating to dementia, technology and patient and public involvement was conducted using Medline, PsycINFO, EMBASE and CINAHL. Papers were screened for inclusion by two authors. Data was then extracted using a pre-designed data extraction table by the same two authors; a third author supported resolution of any conflicts at each stage. Barriers and facilitators of undertaking PPI were then examined and themed.Results:Thirty-one papers were included for analysis. The majority (21/31) did not make clear distinctions between activities undertaken as PPI and activities undertaken by research participants, and as such their involvement did not fit easily into the NIHR definition of PPI. Most of this mixed involvement focused on the reviewing or evaluating of technology prototypes. A range of approaches was described, most typically using focus groups or co-design workshops. Nine studies described involvement at multiple stages through the research cycle, sometimes with evidence of sharing of decision-making power. Some studies commented on barriers or facilitators to effective PPI. Challenges identified were often around issues of working with people with significant cognitive impairments, and
Sadek M, Calvo R, Mougenot C, 2023, Co-designing conversational agents: a comprehensive review and recommendations for best practices, Design Studies, Vol: 89, ISSN: 0142-694X
This paper presents a comprehensive review of fifty-two studies co-designing conversational agents (CAs). Its objectives are to synthesise prior CA co-design efforts and provide actionable recommendations for future endeavours in CA co-design. The review systematically evaluates studies' methodological and contextual aspects, revealing trends and limitations. These insights converge into practical recommendations for co-designing CAs, including (1) selecting the most suitable design technique aligned with desired CA outcomes, (2) advocating continuous stakeholder involvement throughout the design process, and (3) emphasising the elicitation and embodiment of stakeholder values to ensure CA designs align with their perspectives. This paper contributes to standardising and enhancing co-design practices, promising to improve the quality of outcomes in the case of CAs while benefiting stakeholders and users.
Sadek M, Calvo R, Mougenot C, 2023, Designing value-sensitive AI: a critical review and recommendations for socio-technical design processes, AI and Ethics, ISSN: 2730-5961
This paper presents a critical review of how different socio-technical design processes for AI-based systems, from scholarly works and industry, support the creation of value-sensitive AI (VSAI). The review contributes to the emerging field of human-centred AI, and the even more embryonic space of VSAI in four ways: (i) it introduces three criteria for the review of VSAI based on their contribution to design processes’ overall value-sensitivity, and as a response to criticisms that current interventions are lacking in these aspects: comprehensiveness, level of guidance offered, and methodological value-sensitivity, (ii) it provides a novel review of socio-technical design processes for AI-based systems, (iii) it assesses each process based on the mentioned criteria and synthesises the results into broader trends, and (iv) it offers a resulting set of recommendations for the design of VSAI. The objective of the paper is to help creators and followers of design processes—whether scholarly or industry-based—to understand the level of value-sensitivity offered by different socio-technical design processes and act accordingly based on their needs: to adopt or adapt existing processes or to create new ones.
Kallis C, Calvo R, Schuller B, et al., 2023, Development of an asthma exacerbation risk prediction model for conversational use by adults in England, Pragmatic and Observational Research, Vol: 14, Pages: 111-125, ISSN: 1179-7266
Background: Improving accurate risk assessment of asthma exacerbations, and reduction via relevant behaviour change among people with asthma could save lives and reduce health care costs. We developed a simple personalised risk prediction model for asthma exacerbations using factors collected in routine healthcare data for use in a risk modelling feature for automated conversational systems.Methods: We used pseudonymised primary care electronic healthcare records from the Clinical Practice Research Datalink (CPRD) Aurum database in England. We combined variables for prediction of asthma exacerbations using logistic regression including age, gender, ethnicity, Index of Multiple Deprivation, geographical region and clinical variables related to asthma events.Results: We included 1,203,741 patients divided into three cohorts to implement temporal validation: 898,763 (74.7%) in the training sample, 226,754 (18.8%) in the testing sample and 78,224 (6.5%) in the validation sample. The Area under the ROC curve (AUC) for the full model was 0.72 and for the restricted model was 0.71. Using a cut-off point of 0.1, approximately 27 asthma reviews by clinicians per 100 patients would be prevented compared with a strategy that all patients are regarded as high risk. Compared with patients without an exacerbation, patients who exacerbated were older, more likely to be female, prescribed more SABA and ICS in the preceding 12 months, have history of GORD, COPD, anxiety, depression, live in very deprived areas and have more severe disease.Conclusion: Using information available from routinely collected electronic healthcare record data, we developed a model that has moderate ability to separate patients who had an asthma exacerbation within 3 months from their index date from patients who did not. When comparing this model with a simplified model with variables that can easily be self-reported through a WhatsApp chatbot, we have shown that the predictive performance of the model is
Espinoza Lau-Choleon F, Cook D, Butler C, et al., 2023, Supporting dementia caregivers in Peru through chatbots: generative AI vs structured conversations, 36th International BCS Human-Computer Interaction Conference 36th International BCS Human-Computer Interaction Conference Human-Computer Interaction Conference, Publisher: Association for Computing Machinery (ACM)
In Peru, dementia caregivers face burnout, depression, stress, and financial strain. Addressing their needs involves tackling the intricacies of caregiving and managing emotional burdens. Chatbots can serve as a viable support mechanism in regions with limited resources. This study delves into the perceptions of dementia caregivers in Peru regarding a chatbot tailored to offer care navigation andemotional support. We divided the study into three phases: the initial stage encompassed engaging stakeholders to define design requirements for the chatbot; the second stage focused on the creation of ‘Ana’, a chatbot for dementia caregivers; and the final stage assessed the chatbot through interviews and a caregiver satisfaction survey. ‘Ana’ was tested in two configurations - oneemployed pre-defined conversation patterns, while the other harnessed generative AI for more dynamic responses. The findings reveal that caregivers seek immediate access to information on handling behavioural symptoms and a platform for emotional release. Moreover, participantspreferred the generative AI alternative of Ana, as it was perceived to be more empathic and human-like. The participants valued the generative approach despite knowing the potential risk of receiving inaccurate information.
Widjaya MA, Bermudez J, Moradbakhti L, et al., 2023, Drivers of trust in generative AI-powered voice assistants: the role of references, 36th International BCS Human-Computer Interaction Conference
The boom in generative artificial intelligence (AI) and continuing growth of Voice Assistants (VAs) suggests their trajectories will converge. This conjecture aligns with the development of AI-driven conversational agents, aiming to utilise advance natural language processing (NLP) methods to enhance the capabilities of voice assistants. However, design guidelines for VAs prioritise maximum efficiency by advocating for the use of concise answers. This poses a conflict with the challenges around generative AI, such as inaccuracies and misinterpretation, as shorter responses may not adequately provide users with meaningful information. AI-VA systems can adapt drivers of trust formation, such as references and authorship, to improve credibility. A better understanding of user behaviour when using the system is needed to develop revised design recommendations for AI-powered VA systems. This paper reports an online survey of 256 participants residing in the U.K. and nine follow-up interviews, where user behaviour is investigated to identify drivers of trust in the context of obtaining digital information from a generative AI-based VA system. Adding references is promising as a tool for increasing trust in systems producing text, yet we found no evidence that the inclusion of references in a VA response contributed towards the perceived reliability or trust towards the system. We examine further variables driving user trust in AI-powered VA systems.
Sadek M, Calvo RA, Mougenot C, 2023, Trends, challenges and processes in conversational agent design: exploring practitioners’ views through semi-structured interviews, CUI '23: ACM conference on Conversational User Interfaces, Publisher: ACM, Pages: 1-10
The aim of this study is to explore the challenges and experiences of conversational agent (CA) practitioners in order to highlight their practical needs and bring them into consideration within the scholarly sphere. A range of data scientists, conversational designers, executive managers and researchers shared their opinions and experiences through semi-structured interviews. They were asked about emerging trends, the challenges they face, and the design processes they follow when creating CAs. In terms of trends, findings included mixed feelings regarding no-code solutions and a desire for a separation of roles. The challenges mentioned included a lack of socio-technical tools and conversational archetypes. Finally, practitioners followed different design processes and did not use the design processes described in the academic literature. These findings were analyzed to establish links between practitioners’ insights and discussions in related literature. The goal of this analysis is to highlight research-practice gaps by synthesising five practitioner needs that are not currently being met. By highlighting these research-practice gaps and foregrounding the challenges and experiences of CA practitioners, we can begin to understand the extent to which emerging literature is influencing industrial settings and where more research is needed to better support CA practitioners in their work.
Bermudez J, Nyrup R, Deterding S, et al., 2023, What is a subliminal technique? An ethical perspective on AI-driven influence, 2023 IEEE International Symposium on Ethics in Science, Technology and Engineering, Publisher: IEEE, Pages: 1-10
Concerns about threats to human autonomy feature prominently in the field of AI ethics. One aspect of this concern relates to the use of AI systems for problematically manipulative influence. In response to this, the European Union's draft AI Act (AIA) includes a prohibition on AI systems deploying subliminal techniques that alter people's behavior in ways that are reasonably likely to cause harm (Article 5(1)(a)). Critics have argued that the term ‘subliminal techniques’ is too narrow to capture the target cases of AI-based manipulation. We propose a definition of ‘subliminal techniques’ that (a) is grounded on a plausible interpretation of the legal text; (b) addresses all or most of the underlying ethical concerns motivating the prohibition; (c) is defensible from a scientific and philosophical perspective; and (d) does not over-reach in ways that impose excessive administrative and regulatory burdens. The definition provides guidance for design teams seeking to pursue responsible and ethically aligned AI innovation.
Alibasa MJ, Calvo RA, Yacef K, 2023, Predicting mood from digital footprints using frequent sequential context patterns features, International Journal of Human-Computer Interaction, Vol: 39, Pages: 2061-2075, ISSN: 1044-7318
Understanding the relationship between technology and wellbeing is important in order to raise awareness and to improve interaction designs with digital technologies. Most studies used the time spent and frequency information of digital technology usage, very few explored the sequences and the patterns of how the activity occurs. We introduce the concept of “digital context,” a representation of activity data occurring in a short time-window. Using data from our study, we determined whether: (1) there are digital context patterns that are more frequent in a particular mood compared to other moods; and (2) in the case such patterns exist, whether they can be used to improve the performance of mood prediction models. Our results showed that a mood prediction model that include digital context features yielded an accuracy of 77.8%, which is an improvement compared with the models proposed in past studies.
Burnell R, Peters D, Ryan RM, et al., 2023, Technology evaluations are associated with psychological need satisfaction across different levels of experience: An application of the METUX Scales, Frontiers in Psychology, Vol: 14, Pages: 1-12, ISSN: 1664-1078
Digital technologies have the capacity to impact psychological wellbeing in both positive and negative ways. Improving technologies with respect to wellbeing requires nuanced understanding of this impact and reliable ways to measure it. Across two experiments with 1,521 participants, we investigated the relations between psychological needs and people’s evaluations of technologies (with respect to satisfaction, usability, and measures of value). To do so, we improved and validated four scales, first put forward as part of the METUX model of technology interaction, that measure psychological needs at the life, behavior, task,and interface levels. Each of these scales had good psychometric properties when applied to four separate technologies (Facebook, TikTok, Blackboard, and Moodle). At each of the four levels, psychological need satisfaction and frustration were associated with standard measures of usability and user satisfaction, and correlation patterns supported the METUX model and its approach to differentiating spheres of technology experience
Su T, Calvo RA, Jouaiti M, et al., 2023, Assessing a sleep interviewing chatbot to improve subjective and objective sleep: protocol for an observational feasibility study, JMIR Research Protocols, Vol: 12, Pages: 1-10, ISSN: 1929-0748
BACKGROUND: Sleep disorders are common among the aging population and people with neurodegenerative diseases. Sleep disorders have a strong bidirectional relationship with neurodegenerative diseases, where they accelerate and worsen one another. Although one-to-one individual cognitive behavioral interventions (conducted in-person or on the internet) have shown promise for significant improvements in sleep efficiency among adults, many may experience difficulties accessing interventions with sleep specialists, psychiatrists, or psychologists. Therefore, delivering sleep intervention through an automated chatbot platform may be an effective strategy to increase the accessibility and reach of sleep disorder intervention among the aging population and people with neurodegenerative diseases. OBJECTIVE: This work aims to (1) determine the feasibility and usability of an automated chatbot (named MotivSleep) that conducts sleep interviews to encourage the aging population to report behaviors that may affect their sleep, followed by providing personalized recommendations for better sleep based on participants' self-reported behaviors; (2) assess the self-reported sleep assessment changes before, during, and after using our automated sleep disturbance intervention chatbot; (3) assess the changes in objective sleep assessment recorded by a sleep tracking device before, during, and after using the automated chatbot MotivSleep. METHODS: We will recruit 30 older adult participants from West London for this pilot study. Each participant will have a sleep analyzer installed under their mattress. This contactless sleep monitoring device passively records movements, heart rate, and breathing rate while participants are in bed. In addition, each participant will use our proposed chatbot MotivSleep, accessible on WhatsApp, to describe their sleep and behaviors related to their sleep and receive personalized recommendations for better sleep tailored to their specific reasons for disrup
Calvo RA, Peters D, Moradbakhti L, et al., 2023, Assessing the feasibility of a text-based conversational agent for asthma support: protocol for a mixed methods observational study, JMIR Research Protocols, Vol: 12, Pages: 9-9, ISSN: 1929-0748
BACKGROUND: Despite efforts, the UK death rate from asthma is the highest in Europe, and 65% of people with asthma in the United Kingdom do not receive the professional care they are entitled to. Experts have recommended the use of digital innovations to help address the issues of poor outcomes and lack of care access. An automated SMS text messaging-based conversational agent (ie, chatbot) created to provide access to asthma support in a familiar format via a mobile phone has the potential to help people with asthma across demographics and at scale. Such a chatbot could help improve the accuracy of self-assessed risk, improve asthma self-management, increase access to professional care, and ultimately reduce asthma attacks and emergencies. OBJECTIVE: The aims of this study are to determine the feasibility and usability of a text-based conversational agent that processes a patient's text responses and short sample voice recordings to calculate an estimate of their risk for an asthma exacerbation and then offers follow-up information for lowering risk and improving asthma control; assess the levels of engagement for different groups of users, particularly those who do not access professional services and those with poor asthma control; and assess the extent to which users of the chatbot perceive it as helpful for improving their understanding and self-management of their condition. METHODS: We will recruit 300 adults through four channels for broad reach: Facebook, YouGov, Asthma + Lung UK social media, and the website Healthily (a health self-management app). Participants will be screened, and those who meet inclusion criteria (adults diagnosed with asthma and who use WhatsApp) will be provided with a link to access the conversational agent through WhatsApp on their mobile phones. Participants will be sent scheduled and randomly timed messages to invite them to engage in dialogue about their asthma risk during the period of study. After a data collection period (28
Peters D, Calvo RA, 2023, Self-Determination Theory and Technology Design, The Oxford Handbook of Self-Determination Theory, Editors: Ryan, Publisher: Oxford University Press, ISBN: 9780197600047
Rizos G, Calvo RA, Schuller BW, 2023, Positive-Pair Redundancy Reduction Regularisation for Speech-Based Asthma Diagnosis Prediction, ISSN: 1520-6149
Asthma affects an estimated 334 million people worldwide, causing over 461 000 deaths. Exacerbations or asthma attacks can be predicted with new sensor technologies. We explore how recordings of human voice, and machine learning can provide better diagnostics for pulmonary diseases like asthma, as well as tools for helping patients better manage it. Past studies have focused on data collection processes that either mimic traditional auscultation, or make multi-sensor measurements, where the application of specialised recording hardware is required, possibly by expert personnel. This is costly and places limits on the size of the studies (e.g., number of study participants, and recording devices). In this paper, we consider another avenue, that of modelling self-recorded voice samples made using regular smartphones, along with self-reported clinical diagnosis annotations; specifically of asthma. We propose the usage of self-supervised learning that aims to reduce within-class representation redundancy among heterogeneous samples as an auxiliary task to promote robust, bias-free learning. The application of our method achieves an absolute increase of 1.80% in area under the Precision-Recall curve, compared to not using it, and a total of 3.54% compared to our baseline.
Sun S, Zhang Z, Tian M, et al., 2022, Preferences for a Mental Health Support Technology Among Chinese Employees: Mixed Methods Approach, JMIR HUMAN FACTORS, Vol: 9, ISSN: 2292-9495
Seah CEL, Zhang Z, Sun S, et al., 2022, Designing mindfulness conversational agents for people with early-stage dementia and their caregivers: thematic analysis of expert and user perspectives, JMIR Aging, Vol: 5, Pages: e40360-e40360, ISSN: 2561-7605
BACKGROUND: The number of people with dementia is expected to grow worldwide. Among the ways to support both persons with early-stage dementia and their caregivers (dyads), researchers are studying mindfulness interventions. However, few studies have explored technology-enhanced mindfulness interventions for dyads and the needs of persons with dementia and their caregivers. OBJECTIVE: The main aim of this study was to elicit essential needs from people with dementia, their caregivers, dementia experts, and mindfulness experts to identify themes that can be used in the design of mindfulness conversational agents for dyads. METHODS: Semistructured interviews were conducted with 5 dementia experts, 5 mindfulness experts, 5 people with early-stage dementia, and 5 dementia caregivers. Interviews were transcribed and coded on NVivo (QSR International) before themes were identified through a bottom-up inductive approach. RESULTS: The results revealed that dyadic mindfulness is preferred and that implementation formats such as conversational agents have potential. A total of 5 common themes were also identified from expert and user feedback, which should be used to design mindfulness conversational agents for persons with dementia and their caregivers. The 5 themes included enhancing accessibility, cultivating positivity, providing simplified tangible and thought-based activities, encouraging a mindful mindset shift, and enhancing relationships. CONCLUSIONS: In essence, this research concluded with 5 themes that mindfulness conversational agents could be designed based on to meet the needs of persons with dementia and their caregivers.
Serban A-I, Soreq E, Barnaghi P, et al., 2022, The effect of COVID-19 on the home behaviours of people affected by dementia, npj Digital Medicine, Vol: 5, ISSN: 2398-6352
The COVID-19 pandemic has dramatically altered the behaviour of most of the world’s population, particularly affecting the elderly, including people living with dementia (PLwD). Here we use remote home monitoring technology deployed into 31 homes of PLwD living in the UK to investigate the effects of COVID-19 on behaviour within the home, including social isolation. The home activity was monitored continuously using unobtrusive sensors for 498 days from 1 December 2019 to 12 April 2021. This period included six distinct pandemic phases with differing public health measures, including three periods of home ‘lockdown’. Linear mixed-effects modelling is used to examine changes in the home activity of PLwD who lived alone or with others. An algorithm is developed to quantify time spent outside the home. Increased home activity is observed from very early in the pandemic, with a significant decrease in the time spent outside produced by the first lockdown. The study demonstrates the effects of COVID-19 lockdown on home behaviours in PLwD and shows how unobtrusive home monitoring can be used to track behaviours relevant to social isolation.
Stratton E, Lampit A, Choi I, et al., 2022, Trends in Effectiveness of Organizational eHealth Interventions in Addressing Employee Mental Health: Systematic Review and Meta-analysis, JOURNAL OF MEDICAL INTERNET RESEARCH, Vol: 24, ISSN: 1438-8871
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Calvo R, Peters D, Cook D, et al., 2022, Assessing the design of Conversational Agents for Asthma support: Protocol for an Observational Pilot Study (Preprint)
<sec> <title>BACKGROUND</title> <p>A significant number of people have poorly controlled asthma – 60% according to some estimates. One likely reason is poor self-assessment of risk by those with asthma, an issue that could be addressed with a conversational agent that assesses and communicates risk accurately. Such a system could further improve outcomes by providing follow-up recommendations to address other common obstacles to asthma control such as poor inhaler technique and insufficient understanding of asthma triggers and management strategies.</p> </sec> <sec> <title>OBJECTIVE</title> <p>The aims of this study are to: 1) Determine the feasibility and usability of a text-based conversational agent (i.e. chatbot) that processes a patient’s text responses and short sample voice recordings to calculate an estimate of their risk for an asthma exacerbation and then offers follow-up information for improving asthma control; 2) Assess the level of engagement of different types of users, particularly those who do not control their asthma well; 3) Assess self-reported level of asthma control and symptoms and 4) explores associations between asthma control and engagement with the conversational agent.</p> </sec> <sec> <title>METHODS</title> <p>For this pilot study we will recruit 90 adults with asthma through NHS outpatient clinics across primary and secondary care. Participants will have access to the conversational agent through WhatsApp on their mobile phone. Participants will be sent scheduled and randomly timed messages to invite them to engage in a dialogue about their asthma management during the period of the study. After a data collection pe
Seah CEL, Sun S, Zhang Z, et al., 2022, Using a User Centered Design Approach to Design Mindfulness Conversational Agent for Persons with Dementia and their Caregivers, Pages: 207-210
Caring for people with dementia is itself a difficult task affecting the wellbeing and relationship of the patient and carer. Conversational agents (CA), like Alexa, can support mindfulness training for these dyads of persons with early-stage dementia and their caregivers. But so far, no study has utilised a user centered design (UCD) approach for such interventions. We address this, using an iterative UCD approach where experts in dementia and mindfulness (N=4) and end-users (carers and patients, N=20) were interviewed. Four design iterations resulted in the creation of a working prototype. From this expert and user feedback, general user needs were identified and integrated into future designs. By addressing the needs of dyads, the prototype CA could be well received and may be used to support mindfulness practices using CA, that could be helpful for dyads.
Ijaz K, Tran TTM, Kocaballi AB, et al., 2022, Design considerations for immersive virtual reality applications for older adults: a scoping review, Multimodal Technologies and Interaction, Vol: 6, Pages: 1-26, ISSN: 2414-4088
Immersive virtual reality (iVR) has gained considerable attention recently with increasing affordability and accessibility of the hardware. iVR applications for older adults present tremendous potential for diverse interventions and innovations. The iVR literature, however, provides a limited understanding of guiding design considerations and evaluations pertaining to user experience (UX). To address this gap, we present a state-of-the-art scoping review of literature on iVR applications developed for older adults over 65 years. We performed a search in ACM Digital Library, IEEE Xplore, Scopus, and PubMed (1 January 2010–15 December 2019) and found 36 out of 3874 papers met the inclusion criteria. We identified 10 distinct sets of design considerations that guided target users and physical configuration, hardware use, and software design. Most studies carried episodic UX where only 2 captured anticipated UX and 7 measured longitudinal experiences. We discuss the interplay between our findings and future directions to design effective, safe, and engaging iVR applications for older adults.
Jedwab RM, Hutchinson AM, Manias E, et al., 2022, <p>Change in nurses' psychosocial characteristics pre- and post-electronic medical record system implementation coinciding with the SARS-CoV-2 pandemic: pre- and post-cross-sectional surveys</p>, INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, Vol: 163, ISSN: 1386-5056
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Alibasa MJ, Purwanto RW, Yacef K, et al., 2022, Doing and feeling: relationships between moods, productivity and task-switching, IEEE Transactions on Affective Computing, Vol: 13, Pages: 1140-1154, ISSN: 1949-3045
Digital technology influences behaviours, moods and wellbeing. The relationships are complex, but users are increasingly interested in finding how to balance a digital life with psychological wellbeing. We present an approach for investigating the relationship between lifestyle aspects and digital technology usage patterns that combines MindGauge, a mobile app enabling users collect and analyse their moods and behaviours, with a productivity tool (RescueTime). We then report a 16-month study in which we collected computer and smartphone usage and self-reports from 72 participants. We present methods for analysing the relationship between productivity, task-switching, mood and lifestyle, and more specifically how digital technology usage associates with productivity and task-switching. Our study also investigates how lifestyle aspects (sleep quality, physical activity, workload, social interaction and alcoholic drink consumption) relate to mood, task-switching and productivity. Results show that more frequent task-switching is associated with negative moods. A few lifestyle aspects, such as sleep quality and physical activity, had a significant relationship with positive moods. We also contribute a mood detection model that utilise both digital footprints and lifestyle contexts, yielding an accuracy of 87%. The study provides evidence that such methods can be used to understand the impact of technology on wellbeing.
Aji M, Glozier N, Bartlett DJ, et al., 2022, The effectiveness of digital insomnia treatment with adjunctive wearable technology: a pilot randomized controlled trial, Behavioral Sleep Medicine, Vol: 20, Pages: 570-583, ISSN: 1540-2002
OBJECTIVE: This pilot trial aimed to provide evidence for whether the integration of a wearable device with digital behavioral therapy for insomnia (dBTi) improves treatment outcomes and engagement. PARTICIPANTS AND METHODS: One hundred and twenty-eight participants with insomnia symptoms were randomized to a 3-week dBTi program (SleepFix®) with a wearable device enabling sleep data synchronization (dBTi+wearable group; n = 62) or dBTi alone (n = 66). Participants completed the Insomnia Severity Index (ISI) and modified Pittsburgh Sleep Quality Index (PSQI) parameters: wake-after-sleep-onset (WASO), sleep-onset-latency (SOL), and total sleep time (TST) at baseline and weeks 1, 2, 3, and primary endpoint of week 6 and follow-up at 12 weeks. Engagement was measured by the number of daily sleep diaries logged in the app. RESULTS: There was no difference in ISI change scores between the groups from pre- to post-treatment (Cohen's d= 0.7, p= .061). The dBTi+wearable group showed greater improvements in WASO (d= 0.8, p = .005) and TST (d= 0.3, p= .049) compared to the dBTi group. Significantly greater engagement (sleep diary entries) was observed in the dBTi+wearable group (mean = 22.4, SD = 10.0) compared to the dBTi group (mean = 14.1, SD = 14.2) (p = .010). CONCLUSIONS: This pilot trial found that integration of wearable device with a digital insomnia therapy enhanced user engagement and led to improvements in sleep parameters compared to dBTi alone. These findings suggest that adjunctive wearable technologies may improve digital insomnia therapy effectiveness.
Ballou N, Deterding S, Tyack A, et al., 2022, Self-determination theory in HCI: shaping a research agenda, New York, CHI Conference on Human Factors in Computing Systems (CHI ’22), Publisher: ACM, Pages: 1-6
Self-determination theory (SDT) has become one of the most frequently used and well-validated theories used in HCI research, modelling the relation of basic psychological needs, intrinsic motivation, positive experience and wellbeing. This makes it a prime candidate for a ‘motor theme’ driving more integrated, systematic, theory-guided research. However, its use in HCI has remained superficial and disjointed across various application domains like games, health and wellbeing, or learning. This workshop therefore convenes researchers across HCI to co-create a research agenda on how SDT-informed HCI research can maximise its progress in the coming years.
Hänsel K, Sobolev M, Kowatsch T, et al., 2022, HEALTHI: Workshop on Intelligent Healthy Interfaces, Pages: 7-9
The second workshop on intelligent healthy interfaces (HEALTHI), collocated with the 2022 ACM Intelligent User Interfaces (IUI) conference, offers a forum that brings academics and industry researchers together and seeks submissions broadly related to the design of healthy user interfaces. The workshop will discuss intelligent user interfaces such as screens, wearables, voices assistants, and chatbots in the context of accessibly supporting health, health behavior, and wellbeing.
Stratton E, Lampit A, Choi I, et al., 2022, Are Organizational EHealth Interventions Becoming More Effective at Addressing Employee Mental Health; A Systematic Review and Meta-Analysis (Preprint)
<sec> <title>BACKGROUND</title> <p>Mental health conditions are considered the leading cause of disability, sickness absence, and long-term work incapacity in most developed countries. EHealth interventions provide employees with access to psychological assistance. There has been widespread implementation and provision of eHealth interventions in the workplace as an inexpensive and anonymous way of addressing common mental disorders</p> </sec> <sec> <title>OBJECTIVE</title> <p>The aims of this updated review were to synthesize the literature of the efficacy of eHealth interventions for anxiety, depression, and stress outcomes in employee samples in organisational settings, and evaluate whether their effectiveness has improved over time.</p> </sec> <sec> <title>METHODS</title> <p>Systematic searches in relevant articles published from 2004 - July 2020 of trials of eHealth interventions (App or web-based) focused on the mental health of employees. The quality and bias of all studies was assessed. We extracted means and standard deviations from publications, comparing the difference in effect sizes (Hedge’s g) in standardized mental health outcomes. We meta-analyzed these using a random effects model.</p> </sec> <sec> <title>RESULTS</title> <p>We identified a tripling of the body of evidence, with 75 trials available for meta-analysis, with a combined sample of n=14,747. EHealth interventions showed small positive effects for anxiety (g=0.26), depression (g=0.26), and stress (g=0.25) in employees’ post-intervention, with simila
Deady M, Glozier N, Calvo R, et al., 2022, Preventing depression using a smartphone app: a randomized controlled trial, Psychological Medicine, Vol: 52, Pages: 457-466, ISSN: 0033-2917
BackgroundThere is evidence that depression can be prevented; however, traditional approaches face significant scalability issues. Digital technologies provide a potential solution, although this has not been adequately tested. The aim of this study was to evaluate the effectiveness of a new smartphone app designed to reduce depression symptoms and subsequent incident depression amongst a large group of Australian workers.MethodsA randomized controlled trial was conducted with follow-up assessments at 5 weeks and 3 and 12 months post-baseline. Participants were employed Australians reporting no clinically significant depression. The intervention group (N = 1128) was allocated to use HeadGear, a smartphone app which included a 30-day behavioural activation and mindfulness intervention. The attention-control group (N = 1143) used an app which included a 30-day mood monitoring component. The primary outcome was the level of depressive symptomatology (PHQ-9) at 3-month follow-up. Analyses were conducted within an intention-to-treat framework using mixed modelling.ResultsThose assigned to the HeadGear arm had fewer depressive symptoms over the course of the trial compared to those assigned to the control (F3,734.7 = 2.98, p = 0.031). Prevalence of depression over the 12-month period was 8.0% and 3.5% for controls and HeadGear recipients, respectively, with odds of depression caseness amongst the intervention group of 0.43 (p = 0.001, 95% CI 0.26–0.70).ConclusionsThis trial demonstrates that a smartphone app can reduce depression symptoms and potentially prevent incident depression caseness and such interventions may have a role in improving working population mental health. Some caution in interpretation is needed regarding the clinical significance due to small effect size and trial attrition.Trial Registration Australian and New Zealand Clinical Trials Registry (www.anzctr.org.au/) ACTRN12617000548336
Deady M, Collins DAJ, Johnston DA, et al., 2022, The impact of depression, anxiety and comorbidity on occupational outcomes., Occup Med (Lond), Vol: 72, Pages: 17-24
BACKGROUND: Anxiety and depression account for considerable cost to organizations, driven by both presenteeism (reduced performance due to attending work while ill) and absenteeism. Most research has focused on the impact of depression, with less attention given to anxiety and comorbid presentations. AIMS: To explore the cross-sectional relationship between depression and anxiety (individually and comorbidly) on workplace performance and sickness absence. METHODS: As part of a larger study to evaluate a mental health app, 4953 working Australians were recruited. Participants completed in-app assessment including demographic questions, the Patient Health Questionnaire-9, two-item Generalized Anxiety Disorder and questions from the World Health Organization Health and Work Performance Questionnaire. Cut-off scores were used to establish probable cases of depression alone, anxiety alone and comorbidity. RESULTS: Of the total sample, 7% met cut-off for depression only, 13% anxiety only, while 16% were comorbid. Those with comorbidity reported greater symptom severity, poorer work performance and more sickness absence compared to all other groups. Presenteeism and absenteeism were significantly worse in those with depression only and anxiety only compared to those with non-clinical symptom levels. Although those with depression alone tended to have poorer outcomes than the anxiety-only group, when sample prevalence rates were considered, the impact on presenteeism was comparable. CONCLUSIONS: Workplace functioning is heavily impacted by depression and anxiety both independently and where they co-occur. While comorbidity and more severe depression presentations stand out as impairing, workplace interventions should also prioritize targeting of anxiety disorders (and associated presenteeism) given their high population prevalence.
Kim JY, Liu C, Calvo RA, et al., 2022, Comparison of Automatic Speech Recognition Systems, International Workshop on Spoken Dialog System Technology, Publisher: Springer Nature Singapore, Pages: 123-131, ISSN: 1876-1100
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