The ubiquity of social media has increased exposure to idealised beauty standards, often unrealistic and harmful. Repeated exposure has been linked to body dissatisfaction, harmful behaviours, and potentially the development of eating disorders (ED). Given the volume of content produced daily, effective harm mitigation strategies (automated or user-driven) are essential, requiring an informed understanding of the contexts and nuances surrounding harmful content. The study has two key aims: (1) to understand the perspectives of experts by profession and people with lived experience of ED, on what makes social media content harmful in the context of body image and ED, including why and how this harm occurs; and (2) to explore how technology might help mitigate these effects. We engaged n = 30 participants, including 12 interviews with experts by profession (n = 2 ED support service providers and n = 10 body image and ED experts), and five focus groups with experts by lived experience (n = 18 people with lived experience of ED). Using the Framework Method guided by inductive thematic analysis, we developed six prominent themes: (1) Spectrum of harmful and ambiguous content on social media, (2) The “echo chamber” of harmful content amplified by social media algorithms, (3) Balancing safety, freedom and responsibility in social media moderation, (4) Shared responsibility and collaboration for safer social media environments, (5) The role of representation and diversity in social media recovery and support, and (6) Harnessing digital innovation to reduce harm on social media. We developed an eight-category framework of harmful social media content, offering an underlying contextual understanding of harmful content and guidance for harm-reducing technologies. Manual safeguards place significant responsibility on users. This work supports informed distinctions between harmful, ambiguous and safe content and provides design insights for classification systems and adaptable automated moderation. Constant exposure to idealised beauty standards online can lead to negative body image, unhealthy behaviours and eating disorders (ED). To reduce these harms, we need effective ways to identify and moderate harmful content. However, first, we must understand why and how this content causes harm. We consulted n = 30 participants, including interviews with n = 12 professionals in ED support and research, and five focus groups with n = 18 individuals with lived experience of ED. Six major themes were developed using the Framework Method guided by inductive thematic analysis: the range of harmful and ambiguous content, social media’s contribution to an ED “echo chamber,” challenges in content moderation, the need for shared responsibility in creating safer spaces, the importance of diverse representation and the potential for technology to help mitigate harm. From this analysis, we developed eight categories of harmful social media content related to body image and ED, clarifying how individuals may be negatively affected and providing structure for future interventions. Participants highlighted the powerful influence of algorithms in promoting harmful content and called for shared responsibility among users, content creators, platforms, and policymakers. The findings offer guidance for designing technologies that mitigate social media harm.

Suicidal ideation and behaviours are common among adolescents. Parents play a fundamental protective role in the prevention of adolescent suicide, but many describe feeling ill-equipped in their caretaking role. This is despite prior research indicating that it is important for these parents to feel empowered to emotionally support their adolescent if they are experiencing suicidality. An online parenting program could offer parents flexible access to evidence-based parenting strategies. However, there are limited digital resources for these parents and, further, very little is known about how an intervention could be designed to support the empowerment of these parents. Therefore, the aim of the current study is to explore how an existing evidence-based, digital parenting intervention, Partners in Parenting (PiP+), could be adapted through co-design to empower parents. Four parents who have lived experience of caring for a suicidal adolescent, four young people who experienced suicidality during adolescence, and four experts in youth mental health/suicide prevention participated in four sets of co-design workshops to innovate adaptations to PiP+ to empower parents of suicidal adolescents. Affinity mapping was used to analyse and interpret findings. Three key themes highlight how a digital intervention could be innovated and adapted to empower parents caring for a suicidal adolescent. Specifically, for parents to feel empowered to parent a suicidal adolescent, a digital intervention should support them to (1) “deal with the now”; (2) “acknowledge needs and understand their role”, and (3) “hold hope for the future”. Further, ten sub-themes were developed illustrating different concepts related to these themes. Findings highlight how technological features could support parents to feel more empowered when caring for a suicidal adolescent. In conclusion, the proposed technological features illustrate how digital interventions can be adapted to empower parents in their role of emotionally supporting and managing the suicide risk of their adolescent.

Modern commercial smart speakers are increasingly sophisticated offering hands-free, conversational access to information and services. This has propelled their adoption in health and care research across diverse user groups The aim of our study was to systematically synthesize how commercial smart speakers have been used in health and care settings and characterize studied populations and application areas. We also wanted to discover any benefits and limitations, and identify implications for design, deployment, and future research. We conducted a systematic literature review, following PRISMA guidelines, across Scopus, PubMed, and ACM Digital Library from 2014–mid-2025. Inclusion criteria included English, peer-reviewed, empirical studies where a commercial smart speaker was the primary device. We excluded smartphone-only assistants, bespoke/noncommercial hardware and add-on sensors. Our screening yielded 57 articles that we thematically analyzed to extract the overall themes of each paper relevant to how the smart speaker had been used, the populations and healthcare conditions that had been studied and the challenges and benefits that had been observed. The 57 articles addressed one of three objectives including understanding user-needs (n=21), prototype development and evaluation (n=30), and performance (n=6). Although the studies predominantly targeted the general public and older adults, they also included people with health conditions, underserved user groups, clinicians, and caregivers. Amazon devices dominated the smart speaker landscape, followed by Google and Apple. We identified several application areas spanning medication management; diet and physical activity; mental health and sleep; documentation/EHR access; screening; daily-living support; and patient–provider communication. We observed reported benefits including convenience, hands-free interaction, perceived companionship, and, in some trials, clinically meaningful outcomes. We also identified challenges clustering around (1) wake-word and turn-taking breakdowns, (2) difficulty handling complex/multi-part queries, (3) limitations of voice-only input/output, (4) learning burden and digital literacy, (5) infrastructure and setup issues (e.g., WiFi reliability, device management), (6) variable response quality across devices, and (7) privacy and data-governance concerns. In longer deployments, enthusiasm typically lessened over time though multi-modal speakers (with screens) and user training mitigated some issues. We also found reporting was often inconsistent (smart speaker vs embedded assistant), complicating cross-study comparisons. Commercial smart speakers show promise for providing health information, behavior change support, and light-touch monitoring, but reliability, safety, inclusivity, and integration barriers remain. We recommend standardized reporting of device and assistant, multi-modal interaction to reduce cognitive load, inclusive design for diverse speech and dialects, privacy-preserving data practices, and more in-the-wild and longer-term evaluations. Emerging generative-AI capabilities may enhance personalization and error recovery but require more thorough evaluation in clinical workflows. N/A

Early treatment is critical to improve eating disorder prognosis. Single session interventions have been proposed as a strategy to provide short term support to people on waitlists for eating disorder treatment, however, it is not always possible to access this early intervention. Conversational artificial intelligence agents or “chatbots” reflect a unique opportunity to attempt to fill this gap in service provision. The aim of this research was to co-design a novel chatbot capable of delivering a single session intervention for adults on the waitlist for eating disorder treatment across the diagnostic spectrum and ascertain its preliminary acceptability and feasibility. A Double Diamond co-design approach was employed which included four phases: discover, define, develop, and deliver. There were 17 participants in total in Australia; ten adults with a lived experience of an eating disorder and seven registered psychologists working in the field of eating disorders, who participated in online interviews and workshops. Thematic and content analyses were undertaken with interview/workshop transcriptions with findings from the previous phase informing the ideas and development of the next phase. A final prototype of a single session intervention chatbot was presented to the participants in the deliver phase. Thematic and content analyses identified four main themes that were present across the four phases of interviews/workshops: conversational tone, safety and risk management, user journey and session structure, and content. Overall, the feedback on the single session intervention chatbot was positive throughout the Double Diamond process from both people with a lived experience of an eating disorder and psychologists. Incorporating the feedback across the four themes and four co-design phases allowed for refinement of the chatbot. Further research is required to evaluate the chatbot’s efficacy in early treatment settings.

Deaf communities worldwide face systemic barriers in accessing mental health care because of social exclusion and marginalisation. In Bangladesh, these challenges are compounded by a historical neglect of mental health among the Deaf. This study explored mental health understanding and experiences within the Bangladeshi Deaf community, aiming to co-develop culturally and linguistically appropriate digital mental health tools. Two exploratory workshops facilitated by sign language interpreters (n=4) were conducted with Deaf individuals (n=12) and their caregivers (n=4), revealing a substantial gap in Bangla Sign Language vocabulary related to mental health. To address this, the research team developed the first digital Bangla Mental Health Sign Language Bank using an adapted Delphi and workshop approach. The three-phase Delphi process involved mental health professionals (n=9), Deaf individuals (n=5), and interpreters (n=3), who identified and prioritised key mental health terms. This was followed by three consensus workshops with Deaf participants (n=6) and interpreters (n=4) to collaboratively develop the final sign language bank. Qualitative findings revealed six key themes: stigmatisation, isolation, denial of care, difficulty expressing emotions, inadequate mental health support, and the positive role of family awareness. This participatory process led to the creation of an inclusive digital resource to support mental health communication among Deaf individuals in Bangladesh and similar contexts.

Background In Australia, with the recent introduction of electronic health records (EHRs) into hospitals, the use of hospital-based EHRs for research is a relatively new concept. The aim of this study was to explore the attitudes of older healthcare consumers on sharing their health data with an emerging EHR-based Research Data Platform within the National Centre for Healthy Ageing.Methods This was a qualitative study. Two workshops were conducted in March 2022 with consumer representatives across Peninsula Health, Victoria, Australia. The workshops comprised three parts: (1) an ice-breaker (2) an introduction to EHR-based research through the presentation of ‘use case’ scenarios and (3) focus group discussions. Qualitative data were analysed using reflexive thematic analysis.Results Consumer participants (n=16) were aged between 62 and 83 years and were of mixed gender. The overarching theme was related to trust in the use of EHR data for research; themes included: (1) benefits of sharing data, (2) uncertainty around data collection processes and (3) data sharing fears. The three themes within the overarching theme all reflect participants’ levels of trust.Conclusion Our study identified fundamental issues related to trust in the use of EHR data for research, with both healthcare and broader societal factors contributing to consumer attitudes. Processes to support transparent and clear communication with consumers are essential to support the responsible use of EHR data for research.

BackgroundApproximately 39% of young people (aged 16-24 y) experience mental ill health, but only 23% seek professional help. Early intervention is essential for reducing the impacts of mental illness, but young people, particularly those from culturally diverse communities, report experiencing shame and stigma, which can deter them from engaging with face-to-face services. Digital mental health (DMH) tools promise to increase access, but there is a lack of literature exploring the suitability of DMH tools for culturally diverse populations. ObjectiveThe project was conducted in partnership with a large-scale national DMH organization that promotes evidence-based early intervention, treatment, and support of mental health in young people and their families. The organization wanted to develop a self-directed web-based platform for parents and young people that integrates psychological assessments and intervention pathways via a web-based “check-in” tool. Our project explored the views of culturally diverse parents and young people on the opportunities and barriers to engagement with a web-based DMH screening tool. MethodsWe conducted a 2-phase qualitative study aiming to identify potential issues faced by culturally diverse communities when engaging with DMH tools designed for the Australian public. We worked with 18 culturally diverse participants (parents: n=8, 44%; young people: n=10, 56%) in a series of design-led workshops drawing on methods from speculative design and user experience to understand the opportunities and barriers that organizations might face when implementing population-level DMH tools with culturally diverse communities. NVivo was used to conduct thematic analyses of the audio-recorded and transcribed workshop data. ResultsFive themes were constructed from the workshops: (1) trust in the use and application of a DMH tool, (2) data management and sharing, (3) sociocultural influences on mental health, (4) generational differences in mental health and digital literacy, and (5) stigma and culturally based discrimination in mental health support. ConclusionsThe emergent themes have important considerations for researchers wishing to develop more inclusive DMH tools. The study found that healthy parent-child relationships will increase engagement in mental health support for young persons from culturally diverse backgrounds. Barriers to engagement with DMH tools included culturally based discrimination, the influence of culture on mental health support, and the potential impact of a diagnostic label on help seeking. The study’s findings suggest a need for culturally safe psychoeducation for culturally diverse end users that fosters self-determination with tailored resources. They also highlight important key challenges when working with culturally diverse populations.

In today’s age of data-driven healthcare, the growing utilization of health data to inform critical aspects of patient care and medical research places an ever increasing significance on its governance. This study aims to explore the perspectives of individuals living with Parkinson’s Disease regarding their needs and preferences in relation to data governance. We first conducted a survey (n=52) to explore the types of data people with Parkinson’s generate through their self-care practices, and then conducted 3 workshops with 9 participants to understand their perspectives on the governance of this type of data. Through this work, we highlight the factors that motivate them to collect self-care data, and present their requirements for its governance, which could inform the design of future infrastructure to support these needs. We also showcase how speculative approaches can be used to engage communities in discussions around data collection and governance.

Traditionally, body dissatisfaction interventions have been designed with a focus on females from Western cultures. However, with growing research indicating that body dissatisfaction is experienced across society, regardless of gender and cultural background, it is increasingly important that future interventions incorporate a broader range of socio-cultural experiences. We conducted a two-phase co-design study with thirteen participants (seven females, six males), aged 18-24, from diverse cultural backgrounds. Phase 1 aimed to understand the influencing factors that frame the development of body image perceptions. Drawing on insights from Phase 1, Phase 2, then explicitly focused on gathering design insights for digital tools for body dissatisfaction interventions. Four narrative design concepts were used to provoke discussions and ideate around potential digital interventions. Through this paper, we contribute unique insights into the experiences and digital intervention preferences of underrepresented people in body image research and highlight future directions to create more inclusive digital interventions.

As mental health (MH) disorders become increasingly prevalent, their multifaceted symptoms and comorbidities with other conditions introduce complexity to diagnosis, posing a risk of underdiagnosis. While machine learning (ML) has been explored to mitigate these challenges, we hypothesized that multiple data modalities support more comprehensive detection and that non-intrusive collection approaches better capture natural behaviors. To understand the current trends, we systematically reviewed 184 studies to assess feature extraction, feature fusion, and ML methodologies applied to detect MH disorders from passively sensed multimodal data, including audio and video recordings, social media, smartphones, and wearable devices. Our findings revealed varying correlations of modality-specific features in individualized contexts, potentially influenced by demographics and personalities. We also observed the growing adoption of neural network architectures for model-level fusion and as ML algorithms, which have demonstrated promising efficacy in handling high-dimensional features while modeling within and cross-modality relationships. This work provides future researchers with a clear taxonomy of methodological approaches to multimodal detection of MH disorders to inspire future methodological advancements. The comprehensive analysis also guides and supports future researchers in making informed decisions to select an optimal data source that aligns with specific use cases based on the MH disorder of interest.

While online parenting interventions have been shown to improve youth mental health, parents find it challenging to engage with and implement strategies from self-directed interventions. Our study purposefully designed a parent peer-support community for parents seeking support. Our two-phased qualitative study included parent interviews and design workshops. Our findings show that while parents need others’ lived experiences to learn about parenting, perceived judgment and self-doubt can stop them from actively contributing to the peer support group. To address this design challenge, we operationalised parents’ needs and challenges gained in the interviews and workshops into design implications. We demonstrate a parent-centered design approach where we formulate design implications that integrate parents’ needs and expectations with multidisciplinary theoretical and empirical evidence to deepen and concretise the design for an online parent peer-support community that cultivates empathy, encourages confidence and self-efficacy, and motivates change and growth.

Mental health issues affect approximately 13% of people aged 10-24 years old worldwide. In Western countries (e.g. USA, UK, Australia), mental health issues are particularly prominent in Culturally and Linguistically Diverse (CALD) individuals, yet they are disproportionately affected in relation to service provision. Despite demand, there is a significant lack of literature explicitly exploring the design of digital mental health tools for CALD populations. Our study engaged five professionals working in CALD mental health, to gain insights into challenges for service access and provision, and then engaged 41 CALD young people to explore their experiences. We contribute a set of unique insights into the barriers that CALD young people face when seeking help, and their needs for future digital mental health tools. We also provide design recommendations for future researchers on how they might better support the inclusion of CALD communities in the design of digital health tools.

School refusal is a complex issue which typically develops in adolescence, often in the context of anxiety and depressive disorders. While parents and educators play a critical role in supporting these adolescents, they need guidance to work together to overcome the problem. Our study explores how technology can be designed to help parents and educators work together in supporting adolescents who refuse school. We first conducted 14 interviews with parents which highlighted that empathic understanding and communication between parents and the educators is key to supporting adolescents with school refusal. Subsequently, we conducted co-design workshops with three parents, three adolescents and five educators. Our workshop findings show that reactive and problem-focused communication can undermine trust-building and progress towards supporting the adolescent. Drawing on these findings, we formulate design implications that can enable empathic parent-adolescent-educator partnerships, provide holistic support for parents, and facilitate individual tailoring for diverse parent-adolescent journeys.

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Limited examples exist of successful Patient Reported Outcome Measure (PROM) implementation across an entire healthcare organisation. The aim of this study was to use a multi-stakeholder co-design process to develop a PROM collection system, which will inform implementation of routine collection of PROMs across an entire healthcare organisation. Co-design comprised semi-structured interviews with clinicians (n = 11) and workshops/surveys with consumers (n = 320). The interview guide with clinicians focused on their experience using PROMs, preferences for using PROMs, and facilitators/barriers to using PROMs. Co-design activities specific to consumers focused on: (1) how PROMs will be administered (mode), (2) when PROMs will be administered (timing), (3) who will assist with PROMs collection, and (4) how long a PROM will take to complete. Data were analysed using a manifest qualitative content analysis approach. Core elements identified during the co-design process included: PROMs collection should be consumer-led and administered by someone other than a clinician; collection at discharge from the healthcare organisation and at 3–6 months post discharge would be most suitable for supporting comprehensive assessment; PROMs should be administered using a variety of modes to accommodate the diversity of consumer preferences, with electronic as the default; and the time taken to complete PROMs should be no longer than 5–10 min. This study provides new information on the co-design of a healthcare organisation-wide PROM collection system. Implementing a clinician and patient informed strategy for PROMs collection, that meets their preferences across multiple domains, should address known barriers to routine collection.

BACKGROUND:Speech and language therapy involves the identification, assessment, and treatment of children and adults who have difficulties with communication, eating, drinking, and swallowing. Globally, pressing needs outstrip the availability of qualified practitioners who, of necessity, focus on individuals with advanced needs. The potential of voice-assisted technology (VAT) to assist people with speech impairments is an emerging area of research but empirical work exploring its professional adoption is limited.OBJECTIVE:This study aims to explore the professional experiences of speech and language therapists (SaLTs) using VAT with their clients to identify the potential applications and barriers to VAT adoption and thereby inform future directions of research.METHODS:A 23-question survey was distributed to the SaLTs from the United Kingdom using a web-based platform, eliciting both checkbox and free-text responses, to questions on perceptions and any use experiences of VAT. Data were analyzed descriptively with content analysis of free text, providing context to their specific experiences of using VAT in practice, including barriers and opportunities for future use.RESULTS:A total of 230 UK-based professionals fully completed the survey; most were technologically competent and were aware of commercial VATs (such as Alexa and Google Assistant). However, only 49 (21.3%) SaLTs had used VAT with their clients and described 57 use cases. They reported using VAT with 10 different client groups, such as people with dysarthria and users of augmentative and alternative communication technologies. Of these, almost half (28/57, 49%) used the technology to assist their clients with day-to-day tasks, such as web browsing, setting up reminders, sending messages, and playing music. Many respondents (21/57, 37%) also reported using the technology to improve client speech, to facilitate speech practice at home, and to enhance articulation and volume. Most reported a positive impact of VAT use, stating improved independence (22/57, 39%), accessibility (6/57, 10%), and confidence (5/57, 8%). Some respondents reported increased client communication (5/57, 9%) and sociability (3/57, 5%). Reasons given for not using VAT in practice included lack of opportunity (131/181, 72.4%) and training (63/181, 34.8%). Most respondents (154/181, 85.1%) indicated that they would like to try VAT in the future, stating that it could have a positive impact on their clients' speech, independence, and confidence.CONCLUSIONS:VAT is used by some UK-based SaLTs to enable communication tasks at home with their clients. However, its wider adoption may be limited by a lack of professional opportunity. Looking forward, additional benefits are promised, as the data show a level of engagement, empowerment, and the possibility of achieving therapeutic outcomes in communication impairment. The disparate responses suggest that this area is ripe for the development of evidence-based clinical practice, starting with a clear definition, outcome measurement, and professional standardization.

Background: When caring for patients with chronic conditions such as chronic obstructive pulmonary disease (COPD), health care professionals (HCPs) rely on multiple data sources to make decisions. Collating and visualizing these data, for example, on clinical dashboards, holds the potential to support timely and informed decision-making. Most studies on data-supported decision-making (DSDM) technologies for health care have focused on their technical feasibility or quantitative effectiveness. Although these studies are an important contribution to the literature, they do not further our limited understanding of how HCPs engage with these technologies and how they can be designed to support specific contexts of use. To advance our knowledge in this area, we must work with HCPs to explore this space and the real-world complexities of health care work and service structures. Objective: This study aimed to qualitatively explore how DSDM technologies could support HCPs in their decision-making regarding COPD care. We created a scenario-based research tool called Respire, which visualizes HCPs' data needs about their patients with COPD and services. We used Respire with HCPs to uncover rich and nuanced findings about human-data interaction in this context, focusing on the real-world challenges that HCPs face when carrying out their work and making decisions. Methods: We engaged 9 respiratory HCPs from 2 collaborating health care organizations to design Respire. We then used Respire as a tool to investigate human-data interaction in the context of decision-making about COPD care. The study followed a co-design approach that had 3 stages and spanned 2 years. The first stage involved 5 workshops with HCPs to identify data interaction scenarios that would support their work. The second stage involved creating Respire, an interactive scenario-based web app that visualizes HCPs' data needs, incorporating feedback from HCPs. The final stage involved 11 one-to-one sessions with HCPs to use Respire, focusing on how they envisaged that it could support their work and decisions about care. Results: We found that HCPs trust data differently depending on where it came from and who recorded it, sporadic and subjective data generated by patients have value but create challenges for decision-making, and HCPs require support in interpreting and responding to new data and its use cases. Conclusions: Our study uncovered important lessons for the design of DSDM technologies to support health care contexts. We show that although DSDM technologies have the potential to support patient care and health care delivery, important sociotechnical and human-data interaction challenges influence the design and deployment of these technologies. Exploring these considerations during the design process can ensure that DSDM technologies are designed with a holistic view of how decision-making and engagement with data occur in health care contexts.

Mothers of preschool children with cerebral palsy are often responsible for delivering multiple home therapy programs. Technology could be a way to bridge some of the challenges of home therapy delivery, such as lack of regular contact with professionals and the need for support continuity. We interviewed seven mothers and four speech therapists to explore their challenges, and the types of support they currently receive (or give). Key issues included limitations of existing communication channels between mothers and professionals, the mothers’ social support needs, and the level of commitment required to self-deliver home therapy. Based on findings indicating video sharing as an existing practice among mothers, we conducted three workshops to further investigate how a video-based platform could support home therapy delivery. We conclude with a number of design considerations for such technologies, to improve communication and collaboration between professional therapists, mothers and members of their wider social network.

In interdisciplinary spaces such as digital health, datasets that are complex to collect, require specialist facilities, and/or are collected with specific populations have value in a range of different sectors. In this study we collected a simulated free-living dataset, in a smart home, with 12 participants (six people with Parkinson's, six carers). We explored their initial perceptions of the sensors through interviews and then conducted two data exploration workshops, wherein we showed participants the collected data and discussed their views on how this data, and other data relating to their Parkinson's symptoms, might be shared across different sectors. We provide recommendations around how participants might be better engaged in considering data sharing in the early stages of research, and guidance for how research might be configured to allow for more informed data sharing practices in the future.