Self-reported use of technology by orientation and mobility clients in Australia and Malaysia before the COVID-19 pandemic.

Since the 1960s, many electronic travel aids have been developed for people with low vision or blindness to improve their independent travel skills, but uptake of these specialist devices has been limited. This study investigated what technologies orientation and mobility (O&M) clients in Australia and Malaysia have, use, like, and want to support their travel, to inform technology research and development. This two-phase mixed-methods study surveyed O&M clients face-to-face in Malaysia (n = 9), and online in Australia (n = 50). Participants managed safe walking using a human guide, long cane, or guide dog when their vision was insufficient to see hazards, but a smartphone is now a standard travel aid in both Australia and Malaysia. Participants relied on smartphone accessibility features and identified 108 apps they used for travel: for planning (e.g., public transport timetables), sourcing information in transit (e.g., GPS location and directions, finding a taxi), sensory conversion (e.g., camera-to-voice, voice-to-text, video-to-live description), social connections (e.g., phone, email, Facebook), food (e.g., finding eateries, ordering online), and entertainment (e.g., music, games). They wanted to 'carry less junk', and sought better accessibility features, consistency across platforms, and fast, reliable, real-time information that supports confident, non-visual travel, especially into unfamiliar places.

Potential benefits and limitations of machine learning in the field of eating disorders: current research and future directions.

Advances in machine learning and digital data provide vast potential for mental health predictions. However, research using machine learning in the field of eating disorders is just beginning to emerge. This paper provides a narrative review of existing research and explores potential benefits, limitations, and ethical considerations of using machine learning to aid in the detection, prevention, and treatment of eating disorders. Current research primarily uses machine learning to predict eating disorder status from females' responses to validated surveys, social media posts, or neuroimaging data often with relatively high levels of accuracy. This early work provides evidence for the potential of machine learning to improve current eating disorder screening methods. However, the ability of these algorithms to generalise to other samples or be used on a mass scale is only beginning to be explored. One key benefit of machine learning over traditional statistical methods is the ability of machine learning to simultaneously examine large numbers (100s to 1000s) of multimodal predictors and their complex non-linear interactions, but few studies have explored this potential in the field of eating disorders. Machine learning is also being used to develop chatbots to provide psychoeducation and coping skills training around body image and eating disorders, with implications for early intervention. The use of machine learning to personalise treatment options, provide ecological momentary interventions, and aid the work of clinicians is also discussed. Machine learning provides vast potential for the accurate, rapid, and cost-effective detection, prevention, and treatment of eating disorders. More research is needed with large samples of diverse participants to ensure that machine learning models are accurate, unbiased, and generalisable to all people with eating disorders. There are important limitations and ethical considerations with utilising machine learning methods in practice. Thus, rather than a magical solution, machine learning should be seen as an important tool to aid the work of researchers, and eventually clinicians, in the early identification, prevention, and treatment of eating disorders.

Machine learning models are computer algorithms that learn from data to reach an optimal solution for a problem. These algorithms provide exciting potential for the accurate, accessible, and cost-effective early identification, prevention, and treatment of eating disorders, but this potential is just beginning to be explored. Research to date has mainly used machine learning to predict women's eating disorder status with relatively high levels of accuracy from responses to validated surveys, social media posts, or neuroimaging data. These studies show potential for the use of machine learning in the field, but we are far from using these methods in practice. Useful avenues for future research include the use of machine learning to personalise prevention and treatment options, provide ecological momentary interventions via smartphones, and to aid clinicians with their treatment fidelity and effectiveness. More research is needed with large samples of diverse participants to ensure that machine learning models are accurate, unbiased, and generalisable to all people with eating disorders. There are limitations and ethical considerations with using these methods in practice. If accurate and generalisable machine learning models can be created in the field of eating disorders, it could improve the way we identify, prevent, and treat these debilitating disorders.

Use of technology by orientation and mobility professionals in Australia and Malaysia before COVID-19.

PURPOSE: Orientation and Mobility (O&M) professionals teach people with low vision or blindness to use specialist assistive technologies to support confident travel, but many O&M clients now prefer a smartphone. This study aimed to investigate what technology O&M professionals in Australia and Malaysia have, use, like, and want to support their client work, to inform the development of O&M technologies and build capacity in the international O&M profession. MATERIALS AND METHODS: A technology survey was completed by professionals (n = 36) attending O&M workshops in Malaysia. A revised survey was completed online by O&M specialists (n = 31) primarily in Australia. Qualitative data about technology use came from conferences, workshops and interviews with O&M professionals. Descriptive statistics were analysed together with free-text data. RESULTS: Limited awareness of apps used by clients, unaffordability of devices, and inadequate technology training discouraged many O&M professionals from employing existing technologies in client programmes or for broader professional purposes. Professionals needed to learn smartphone accessibility features and travel-related apps, and ways to use technology during O&M client programmes, initial professional training, ongoing professional development and research. CONCLUSIONS: Smartphones are now integral to travel with low vision or blindness and early-adopter O&M clients are the travel tech-experts. O&M professionals need better initial training and then regular upskilling in mainstream O&M technologies to expand clients' travel choices. COVID-19 has created an imperative for technology laggards to upskill for O&M tele-practice. O&M technology could support comprehensive O&M specialist training and practice in Malaysia, to better serve O&M clients with complex needs.Implications for rehabilitationMost orientation and mobility (O&M) clients are travelling with a smartphone, so O&M specialists need to be abreast of mainstream technologies, accessibility features and apps used by clients for orientation, mobility, visual efficiency and social engagement.O&M specialists who are technology laggards need human-guided support to develop confidence in using travel technologies, and O&M clients are the experts. COVID-19 has created an imperative to learn skills for O&M tele-practice.Affordability is a significant barrier to O&M professionals and clients accessing specialist travel technologies in Malaysia, and to O&M professionals upgrading technology in Australia.Comprehensive training for O&M specialists is needed in Malaysia to meet the travel needs of clients with low vision or blindness who also have physical, cognitive, sensory or mental health complications.

Examining the Pro-Eating Disorders Community on Twitter Via the Hashtag #proana: Statistical Modeling Approach.

BACKGROUND: There is increasing concern around communities that promote eating disorders (Pro-ED) on social media sites through messages and images that encourage dangerous weight control behaviors. These communities share group identity formed through interactions between members and can involve the exchange of "tips," restrictive dieting plans, extreme exercise plans, and motivating imagery of thin bodies. Unlike Instagram, Facebook, or Tumblr, the absence of adequate policy to moderate Pro-ED content on Twitter presents a unique space for the Pro-ED community to freely communicate. While recent research has identified terms, themes, and common lexicon used within the Pro-ED online community, very few have been longitudinal. It is important to focus upon the engagement of Pro-ED online communities over time to further understand how members interact and stay connected, which is currently lacking. OBJECTIVE: The purpose of this study was to explore beyond the common messages of Pro-ED on Twitter to understand how Pro-ED communities get traction over time by using the hashtag considered to symbolize the Pro-ED movement, #proana. Our focus was to collect longitudinal data to gain a further understanding of the engagement of Pro-ED communities on Twitter. METHODS: Descriptive statistics were used to identify the preferred tweeting style of Twitter users (either as mentioning another user in a tweet or without) as well as their most frequently used hashtag, in addition to #proana. A series of Mann Whitney U tests were then conducted to compare preferred posting style across number of followed, followers, tweets, and favorites. This was followed by linear models using a forward step-wise approach that were applied for Pro-ED Twitter users to examine the factors associated with their number of followers. RESULTS: This study reviewed 11,620 Pro-ED Twitter accounts that posted using the hashtag #proana between September 2015 and July 2018. These profiles then underwent a 2-step screening of inclusion and exclusion criteria to reach the final sample of 967 profiles. Over 90% (10,484/11,620) of the profiles were found to have less than 6 tweets within the 34-month period. Most of the users were identified as preferring a mentioning style of tweeting (718/967, 74.3%) over not mentioning (248/967, 25.7%). Further, #proana and #thinspo were used interchangeably to propagate shared themes, and there was a reciprocal effect between followers and the followed. CONCLUSIONS: Our analysis showed that the number of accounts followed and number of Pro-ED tweets posted were significant predictors for the number of followers a user has, compared to likes. Our results could potentially be useful to social media platforms to understand which features could help or otherwise curtail the spread of ED messages and activity. Our findings also show that Pro-ED communities are transient in nature, engaging in superficial discussion threads but resilient, emulating cybersectarian behavior.

Development of a Positive Body Image Chatbot (KIT) With Young People and Parents/Carers: Qualitative Focus Group Study.

BACKGROUND: Body image and eating disorders represent a significant public health concern; however, many affected individuals never access appropriate treatment. Conversational agents or chatbots reflect a unique opportunity to target those affected online by providing psychoeducation and coping skills, thus filling the gap in service provision. OBJECTIVE: A world-first body image chatbot called "KIT" was designed. The aim of this study was to assess preliminary acceptability and feasibility via the collection of qualitative feedback from young people and parents/carers regarding the content, structure, and design of the chatbot, in accordance with an agile methodology strategy. The chatbot was developed in collaboration with Australia's national eating disorder support organization, the Butterfly Foundation. METHODS: A conversation decision tree was designed that offered psychoeducational information on body image and eating disorders, as well as evidence-based coping strategies. A version of KIT was built as a research prototype to deliver these conversations. Six focus groups were conducted using online semistructured interviews to seek feedback on the KIT prototype. This included four groups of people seeking help for themselves (n=17; age 13-18 years) and two groups of parents/carers (n=8; age 46-57 years). Participants provided feedback on the cartoon chatbot character design, as well as the content, structure, and design of the chatbot webchat. RESULTS: Thematic analyses identified the following three main themes from the six focus groups: (1) chatbot character and design, (2) content presentation, and (3) flow. Overall, the participants provided positive feedback regarding KIT, with both young people and parents/carers generally providing similar reflections. The participants approved of KIT's character and engagement. Specific suggestions were made regarding the brevity and tone to increase KIT's interactivity. CONCLUSIONS: Focus groups provided overall positive qualitative feedback regarding the content, structure, and design of the body image chatbot. Incorporating the feedback of lived experience from both individuals and parents/carers allowed the refinement of KIT in the development phase as per an iterative agile methodology. Further research is required to evaluate KIT's efficacy.

Influencing the Conversation About Masculinity and Suicide: Evaluation of the Man Up Multimedia Campaign Using Twitter Data.

BACKGROUND: It has been suggested that some dominant aspects of traditional masculinity are contributing to the high suicide rates among Australian men. We developed a three-episode documentary called Man Up, which explores the complex relationship between masculinity and suicide and encourages men to question socially imposed rules about what it means to be a man and asks them to open up, express difficult emotions, and seek help if and when needed. We ran a three-phase social media campaign alongside the documentary using 5 channels (Twitter, Facebook, Instagram, YouTube, and Tumblr). OBJECTIVE: This study aimed to examine the extent to which the Man Up Twitter campaign influenced the social media conversation about masculinity and suicide. METHODS: We used Twitter insights data to assess the reach of and engagement with the campaign (using metrics on followers, likes, retweets, and impressions) and to determine the highest and lowest performing tweets in the campaign (using an aggregated performance measure of reactions). We used original content tweets to determine whether the campaign increased the volume of relevant Twitter conversations (aggregating the number of tweets for selected campaign hashtags over time), and we used a subset of these data to gain insight into the main content themes with respect to audience engagement. RESULTS: The campaign generated a strong following that was engaged with the content of the campaign; over its whole duration, the campaign earned approximately 5000 likes and 2500 retweets and gained around 1,022,000 impressions. The highest performing tweets posted by the host included video footage and occurred during the most active period of the campaign (around the screening of the documentary). The volume of conversations in relation to commonly used hashtags (#MANUP, #ABCMANUP, #LISTENUP, and #SPEAKUP) grew in direct relation to the campaign activities, achieving strongest growth during the 3 weeks when the documentary was aired. Strongest engagement was found with content related to help-seeking, masculinity, and expressing emotions. A number of followers tweeted personal stories that revealed overwhelmingly positive perceptions of the content of the documentary and strongly endorsed its messages. CONCLUSIONS: The Man Up Twitter campaign triggered conversations about masculinity and suicide that otherwise may not have happened. For some, this may have been game-changing in terms of shifting attitudes toward expressing emotions and reaching out to others for help. The campaign was particularly effective in disseminating information and promoting conversations in real time, an advantage that it had over more traditional health promotion campaigns. This sort of approach could well be adapted to other areas of mental (and physical) health promotion campaigns to increase their reach and effectiveness.

Optimising technology to measure functional vision, mobility and service outcomes for people with low vision or blindness: protocol for a prospective cohort study in Australia and Malaysia.

INTRODUCTION: Orientation and mobility (O&M) specialists assess the functional vision and O&M skills of people with mobility problems, usually relating to low vision or blindness. There are numerous O&M assessment checklists but no measures that reduce qualitative assessment data to a single comparable score suitable for assessing any O&M client, of any age or ability, in any location. Functional measures are needed internationally to align O&M assessment practices, guide referrals, profile O&M clients, plan appropriate services and evaluate outcomes from O&M programmes (eg, long cane training), assistive technology (eg, hazard sensors) and medical interventions (eg, retinal implants). This study aims to validate two new measures of functional performance vision-related outcomes in orientation and mobility (VROOM) and orientation and mobility outcomes (OMO) in the context of ordinary O&M assessments in Australia, with cultural comparisons in Malaysia, also developing phone apps and online training to streamline professional assessment practices. METHODS AND ANALYSIS: This multiphase observational study will employ embedded mixed methods with a qualitative/quantitative priority: corating functional vision and O&M during social inquiry. Australian O&M agencies (n=15) provide the sampling frame. O&M specialists will use quota sampling to generate cross-sectional assessment data (n=400) before investigating selected cohorts in outcome studies. Cultural relevance of the VROOM and OMO tools will be investigated in Malaysia, where the tools will inform the design of assistive devices and evaluate prototypes. Exploratory and confirmatory factor analysis, Rasch modelling, cluster analysis and analysis of variance will be undertaken along with descriptive analysis of measurement data. Qualitative findings will be used to interpret VROOM and OMO scores, filter statistically significant results, warrant their generalisability and identify additional relevant constructs that could also be measured. ETHICS AND DISSEMINATION: Ethical approval has been granted by the Human Research Ethics Committee at Swinburne University (SHR Project 2016/316). Dissemination of results will be via agency reports, journal articles and conference presentations.