Deceptive Patterns (also known as Dark Patterns) are manipulative interface elements that can cause users to experience financial, temporal, and privacy-related losses. While Deceptive Patterns have been extensively studied in Android applications, their prevalence in iOS apps remains largely unexplored, despite significant ecosystem differences and iOS's growing popularity among younger users. Notably, Apple's tight control over its ecosystem has fostered public perception of iOS being the safer platform and as a byproduct, iOS users may be less vigilant towards app-related risks. To investigate how the prevalence of Deceptive Patterns on iOS compares to Android, we conducted a review of the same 143 mobile apps across both platforms. Our analysis reveals statistically significant differences between Deceptive Patterns on iOS and Android, with iOS apps exhibiting more instances overall (1477 vs. 1398). The findings suggest that iOS users may be more vulnerable to the risks posed by Deceptive Patterns. Furthermore, our analysis identified four specific types of Deceptive Patterns with notable discrepancies between the mobile platforms, indicating potential influences by app store guidelines and developer tools, and the rise of A/B testing Deceptive Patterns. These findings highlight the need to further explore different digital platforms and user protections on mobile devices.

Mobile device users frequently experience Situational Visual Impairments (SVIs) when viewing screen content in bright outdoor environments. Designers could help alleviate SVIs if they had design tools that illustrated the effects that bright outdoor environments have on screen content. However, the exact nature of the underlying factors that lead to bright environment SVIs is poorly understood. To address this, we build on previous work by exploring the effects of bright environmental lighting on display content visibility using in-lab studies. In particular, we measured the differentiability of achromatic colours under a variety of realistic screen content and environmental brightnesses. Surprisingly, we found that environmental brightness makes a significant but relatively small contribution to reducing screen content visibility, with screen content brightness having a larger effect. As such, we conclude that non-glare ambient light reflecting off a screen has little influence on the visibility of that screen’s content, and make recommendations for future research to help map the true factors underlying SVIs.

By far the most available assistive tool to assist people with Colour Vision Deficiency (CVD) is recolouring. However, despite over three decades of research designing and developing recolouring tools, no work yet has looked to understand how these tools are actually used or perceived by people with CVD. To address this, we first analyzed posts and comments from the r/colorblind subreddit in order to get an unconstrained understanding of the perspectives people with CVD have on recolouring tools. We then conducted an observation study with follow-on interview to further understand how people with CVD use and perceive these tools in a more controlled setting. Our findings suggest that recolouring tools are rarely used how their designers intended and that a better future solution is to design with true inclusivity by solving the actual problems people with CVD have, rather than attempting to ‘fix’ CVD.

Identification of and discrimination between colours is an important task in everyday life, but for the 5% of the population who have Colour Vision Deficiency (CVD), correctly identifying or discriminating between colours can be difficult or impossible. Colour Identification (or CVD) Aids have been developed to assist people with CVD, however, the methods used to evaluate them are often limited and many use CVD simulations instead of participants with CVD. To address this, we propose two new CVD Aid evaluation tasks and show that they can assist in providing a more thorough evaluation of potential CVD aids. In addition, we evaluate the effectiveness of CVD simulations used by non-CVD people in providing results similar to those for people with CVD, and found that both the results and participant behaviour often differed. Our results indicate that greater care is needed when evaluating CVD Aids.

Many daily tasks rely on accurately identifying and distinguishing between different colours. However, these tasks can be frustrating and potentially dangerous for people with Colour Vision Deficiency (CVD). Despite prior work exploring how pattern overlays on top of colours can support people with CVD, the solutions were often unintuitive or required significant training to become proficient. We address this problem by creating two new colour patterns (ColourIconizer, ColourMix). We evaluated these patterns against a previously published colour pattern (ColourMeters) using an online evaluation with three new colour identification tasks (Selection Task, Transition Task, Sorting Task). ColourMeters helped with the Transition Task, but struggled with the Selection and Sorting Tasks. Conversely, ColourIconizer helped with the Selection and Sorting Tasks but struggled to help on the Transition Task. ColourMix provided general assistance on all tasks. Our combined results help inform and improve the design of future colour patterns.

DHH (d/Deaf and hard of hearing) employees report unique challenges in their workplaces, especially under hearing supervisors. Although a technical intervention might help address these challenges, any intervention first requires a clearer understanding of DHH employees’ reality. To learn more, we conducted an autoethnographic study and an online survey of 19 DHH employees and three hearing supervisors. Through thematic analysis, we identified DHH Status, Timing and Implications of Disclosure, Accommodations, Disability Confidence, and Audism and Hearing Privileges as central factors that influence DHH employee success under hearing supervisors. By identifying these factors, this work provides the contextual knowledge necessary for proposing appropriate future technical and design interventions.

It can be difficult for parents to understand how their children perceive the world, especially when they have different sensory capabilities (e.g., hearing loss). Personalized simulations of other sensory impairments have been shown to improve understanding, so digital personalized simulations of hearing loss might improve understanding for hearing parents of d/Deaf and hard of hearing (DHH) children, but only if there is demand for it. We surveyed six hearing parents of DHH children to assess factors that might influence this demand, as well as the base demand itself. We found that there is indeed demand, even in the presence of two potentially confounding factors (parent hope for regained hearing and high parent empathy).

It is arguable that academics working in accessibility want to improve lives. Last year marked 30 years since the first accessible computing publication [46] on supporting people with Color Vision Deficiency (CVD - commonly called colorblindness), making it a great time to review the CVD academic research that has been completed since then and assess its broad availability to the general population. In this paper, we identify seven central themes in the CVD academic literature, and employ a novel technique (PDI - Persona Driven Inquiry) to explore if and how that literature is available to the general public. Subject to some limitations, we found that this research is indeed available.

Mobile devices are a substantial part of our lives, supporting communication, work, and play. However, situational visual impairments (SVIs) can make completing tasks a challenge (e.g., browsing online in bright sunlight) and poorly designed content can cause or exacerbate SVIs. We surveyed 43 mobile content designers and ran four follow-on interviews to understand what designers currently do regarding SVIs, what resources they know of, and what is required to best support them in designing to reduce SVIs. Our findings highlight key similarities and differences between accessibility and designing to reduce SVIs. Our participants requested improved guidelines, education, and digital design tools for SVIs. To accommodate the growing number of people affected by SVIs and improve the inclusion of accessibility in design, we introduce recommendations that leverage the overlap between accessibility and SVIs to minimise the effort required in extending current design processes.

With the growing popularity of mobile devices, Situational Visual Impairments (SVIs) can cause accessibility challenges. When addressing SVIs, interface and content designers are lacking guidelines based on empirically-determined SVI contrast sensitivities. To address this, we developed BrightLights -- a game that collects screen-content-contrast data in-the-wild that will enable new SVI-pertinent contrast ratio recommendations. In our evaluation with 15 participants, we found significantly worse performance with low screen brightness versus medium or high screen brightness, showing that BrightLights is sensitive to at least one factor that contributes to SVI (screen brightness). Once validated for in-the-wild deployment, BrightLights data will finally help designers address SVIs through their designs.

Many people around the world have difficulties in day-to-day conversation due to hearing loss. Hearing aids often fail to offer enough benefits and have low adoption rates. However, people with hearing loss find that speechreading can improve their understanding during conversation, but speechreading is a challenging skill to learn. Speechreading classes can improve acquisition, however there are a limited number of classes available and students can only practice effectively when attending class. To address this, we conducted a postal survey with 59 speechreading students to understand students' perspectives on practicing. Using our findings, we developed an Android application called MirrorMirror - a new Speechreading Acquisition Tool (SAT) that allows students to practice their speechreading by recording and watching videos of people they frequently speak with. We evaluated MirrorMirror through three case studies with speechreading students and found that they could effectively target their speechreading practice on people, words and situations they encounter during daily conversations.

At least 360 million people worldwide have disabling hearing loss that frequently causes difficulties in day-to-day conversations. Traditional technology (e.g., hearing aids) often fails to offer enough value, has low adoption rates, and can result in social stigma. Speechreading can dramatically improve conversational understanding, but speechreading is a skill that can be challenging to learn. To address this, we developed a novel speechreading acquisition framework that can be used to design Speechreading Acquisition Tools (SATs) - a new type of technology to improve speechreading acquisition. We interviewed seven speechreading tutors and used thematic analysis to identify and organise the key elements of our framework. We then evaluated our framework by using it to: 1) categorise every tutor-identified speechreading teaching technique, 2) critically evaluate existing conversational aids, and 3) design three new SATs. Through the use of SATs designed using our framework, the speechreading abilities of people with hearing loss around the world should be enhanced, thereby improving the conversational foundation of their day-to-day lives.

A myoelectric prosthesis (myo) is a dexterous artificial limb controlled by muscle contractions. Learning to use a myo can be challenging, so extensive training is often required to use a myo prosthesis effectively. Signal visualizations and simple muscle-controlled games are currently used to help patients train their muscles, but are boring and frustrating. Furthermore, current training systems require expensive medical equipment and clinician oversight, restricting training to infrequent clinical visits. To address these limitations, we developed a new game that promotes fun and success, and shows the viability of a low-cost myoelectric input device. We adapted a user-centered design (UCD) process to receive feedback from patients, clinicians, and family members as we iteratively addressed challenges to improve our game. Through this work, we introduce a free and open myo training game, provide new information about the design of myo training games, and reflect on an adapted UCD process for the practical iterative development of therapeutic games.

Colour forms an essential element of day-to-day life for most people, but at least 5% of the world have Impaired Colour Vision (ICV) - seeing fewer colours than everyone else. Those with typical colour vision find it difficult to understand how people with ICV perceive colour, leading to misunderstanding and challenges for people with ICV. To help improve understanding, personalized simulations of ICV have been developed, but are computationally demanding (so limited to static images), which limits the value of these simulations. To address this, we extended personalized ICV simulations to work in real time on a mobile device to allow people with typical colour vision greater freedom in exploring ICV. To validate our approach, we compared our real-time simulation technique to an existing adjustable simulation technique and found general agreement between the two. We then deployed three real-time personalized ICV simulations to nine people with typical colour vision, encouraging them to take photos of interesting colour situations. In just over one week, participants recorded over 450 real-world images of situations where their simulation presented a distinct challenge for their respective ICV participant. Through a questionnaire and discussion of photos with participants, we found that our solution provides a valuable mechanism for building understanding of ICV for people with typical colour vision.

Using real time eye tracking, gaze-contingent displays can modify their content to represent depth (e.g., through additional depth cues) or to increase rendering performance (e.g., by omitting peripheral detail). However, there has been no research to date exploring how gaze-contingent displays can be leveraged for manipulating perceived color. To address this, we conducted two experiments (color matching and sorting) that manipulated peripheral background and object colors to influence the user's color perception. Findings from our color matching experiment suggest that we can use gaze-contingent simultaneous contrast to affect color appearance and that existing color appearance models might not fully predict perceived colors with gaze-contingent presentation. Through our color sorting experiment we demonstrate how gaze-contingent adjustments can be used to enhance color discrimination. Gaze-contingent color holds the promise of expanding the perceived color gamut of existing display technology and enabling people to discriminate color with greater precision.

Users frequently experience situations in which their ability to differentiate screen colors is affected by a diversity of situations, such as when bright sunlight causes glare, or when monitors are dimly lit. However, designers currently have no way of choosing colors that will be differentiable by users of various demographic backgrounds and abilities and in the wide range of situations where their designs may be viewed. Our goal is to provide designers with insight into the effect of real-world situational lighting conditions on people's ability to differentiate colors in applications and imagery. We therefore developed an online color differentiation test that includes a survey of situational lighting conditions, verified our test in a lab study, and deployed it in an online environment where we collected data from around 30,000 participants. We then created ColorCheck, an image-processing tool that shows designers the proportion of the population they include (or exclude) by their color choices.

Being able to identify colours is a fundamental human activity; colour identification helps us work, get dressed, prepare food, and keep safe. But for the 5% of the world with impaired colour vision (ICV), colour identification is often a challenge, resulting in frustration and confusion with sometimes dangerous consequences. Colour namer tools have been proposed as a solution, however these are often slow to use and imprecise. To address these shortcomings, we developed three new colour identification techniques (ColourNames, ColourMeters, ColourPopper) using a new colour name dictionary based on the largest colour naming experiment to date. We compared our techniques to colour namers using participants with ICV in desktop and mobile conditions, and found that ColourNames and ColourPopper resulted in ~99% colour identification accuracy (10% higher than the colour namer), ColourMeters and ColourPopper were three times faster, and ColourPopper had lower perceived effort and was ranked significantly higher. With the benefits provided by our new colour identification techniques, people with ICV are one step closer to seeing the world like everyone else.

Colours are an important part of user experiences on the Web. Colour schemes influence the aesthetics, first impressions and long-term engagement with websites. However, five percent of people perceive a subset of all colours because they have colour vision deficiency (CVD), resulting in an unequal and less-rich user experience on the Web. Traditionally, people with CVD have been supported by recolouring tools that improve colour differentiability, but do not consider the subjective properties of colour schemes while recolouring. To address this, we developed SPRWeb, a tool that recolours websites to preserve subjective responses and improve colour differentiability - thus enabling users with CVD to have similar online experiences. To develop SPRWeb, we extended existing models of non-CVD subjective responses to CVD, then used this extended model to steer the recolouring process. In a lab study, we found that SPRWeb did significantly better than a standard recolouring tool at preserving the temperature and naturalness of websites, while achieving similar weight and differentiability preservation. We also found that recolouring did not preserve activity, and hypothesize that visual complexity influences activity more than colour. SPRWeb is the first tool to automatically preserve the subjective and perceptual properties of website colour schemes thereby equalizing the colour-based web experience for people with CVD.

Object handoff - that is, passing an object or tool to another person - is an extremely common activity in collaborative tabletop work. On digital tables, object handoff is typically accomplished by sliding them on the table surface - but surface-only interactions can be slow and error-prone, particularly when there are multiple people carrying out multiple handoffs. An alternative approach is to use the space above the table for object handoff; this provides more room to move, but requires above-surface tracking. We have developed two above-the-surface handoff techniques that use simple and inexpensive tracking: a force-field technique that uses a depth camera to determine hand proximity, and an electromagnetic-field technique called ElectroTouch that provides positive indication when people touch hands over the table. We compared the new techniques to three kinds of surface-only handoff (sliding, flicking, and surface-only Force-Fields). The study showed that the above-surface techniques significantly improved both speed and accuracy, and that ElectroTouch was the best technique overall. This work provides designers with practical new techniques for substantially increasing performance and interaction richness on digital tables.

In optical see-through displays, light coming from background objects mixes with the light originating from the display, causing what is known as the color blending problem. Color blending negatively affects the usability of such displays as it impacts the legibility and color encodings of digital content. Color correction aims at reducing the impact of color blending by finding an alternative display color which, once mixed with the background, results in the color originally intended.

Colour vision deficiencies (CVD) affect the everyday lives of a large number of people, but it is difficult for others - even friends and family members - to understand the experience of having CVD. Simulation tools can help provide this experience; however, current simulations are based on general models that have several limitations, and therefore cannot accurately reflect the perceptual capabilities of most individuals with reduced colour vision. To address this problem, we have developed a new simulation approach that is based on a specific empirical model of the actual colour perception abilities of a person with CVD. The resulting simulation is therefore a more exact representation of what a particular person with CVD actually sees. We tested the new approach in two ways. First, we compared its accuracy with that of the existing models, and found that the personalized simulations were significantly more accurate than the old method. Second, we asked pairs of participants (one with CVD, and one close friend or family member without CVD) to discuss images of everyday scenes that had been simulated with the CVD person's particular model. We found that the personalized simulations provided new insights into the details of the CVD person's experience. The personalized-simulation approach shows great promise for improving understanding of CVD (and potentially other conditions) for people with ordinary perceptual abilities.

Color is commonly used to convey information in digital environments, but colors can be difficult to distinguish for many users -- either because of a congenital color vision deficiency (CVD), or because of situation-induced CVDs such as wearing colored glasses or working in sunlight. Tools intended to improve color differentiability (recoloring tools) exist, but these all use abstract models of only a few types of congenital CVD; if the user's color problems have a different cause, existing recolorers can perform poorly. We have developed a recoloring tool (SSMRecolor) based on the idea of situation-specific modeling -- in which we build a performance-based model of a particular user in their specific environment, and use that model to drive the recoloring process. SSMRecolor covers a much wider range of CVDs, including acquired and situational deficiencies. We evaluated SSMRecolor and two existing tools in a controlled study of people's color-matching performance in several environmental conditions. The study included participants with and without congenital CVD. Our results show both accuracy and response time in color-matching tasks were significantly better with SSMRecolor. This work demonstrates the value of a situation-specific approach to recoloring, and shows that this technique can substantially improve the usability of color displays for users of all types.

Color vision deficiencies (CVDs) cause problems in situations where people need to differentiate the colors used in digital displays. Recoloring tools exist to reduce the problem, but these tools need a model of the user's color-differentiation ability in order to work. Situation-specific models are a recent approach that accounts for all of the factors affecting a person's CVD (including genetic, acquired, and environmental causes) by using calibration data to form the model. This approach works well, but requires repeated calibration - and the best available calibration procedure takes more than 30 minutes. To address this limitation, we have developed a new situation-specific model of human color differentiation (called ICD-2) that needs far fewer calibration trials. The new model uses a color space that better matches human color vision compared to the RGB space of the old model, and can therefore extract more meaning from each calibration test. In an empirical comparison, we found that ICD-2 is 24 times faster than the old approach, and had small but significant gains in accuracy. The efficiency of ICD-2 makes it feasible for situation-specific models of individual color differentiation to be used in the real world.

Interactive systems often require calibration to ensure that input and output are optimally configured. Without calibration, user performance can degrade (e.g., if an input device is not adjusted for the user's abilities), errors can increase (e.g., if color spaces are not matched), and some interactions may not be possible (e.g., use of an eye tracker). The value of calibration is often lost, however, because many calibration processes are tedious and unenjoyable, and many users avoid them altogether. To address this problem, we propose calibration games that gather calibration data in an engaging and entertaining manner. To facilitate the creation of calibration games, we present design guidelines that map common types of calibration to core tasks, and then to well-known game mechanics. To evaluate the approach, we developed three calibration games and compared them to standard procedures. Users found the game versions significantly more enjoyable than regular calibration procedures, without compromising the quality of the data. Calibration games are a novel way to motivate users to carry out calibrations, thereby improving the performance and accuracy of many human-computer systems.

Color is commonly used to represent categories and values in many computer applications, but differentiating these colors can be difficult in many situations (e.g., for users with color vision deficiency (CVD), or in bright light). Current solutions to this problem can adapt colors based on standard simulations of CVD, but these models cover only a fraction of the ways in which color perception can vary. To improve the specificity and accuracy of these approaches, we have developed the first ever individualized model of color differentiation (ICD). The model is based on a short calibration performed by a particular user for a particular display, and so automatically covers all aspects of the user's ability to see and differentiate colors in an environment. In this paper we introduce the new model and the manner in which differentiability limits are predicted. We gathered empirical data from 16 users to assess the model's accuracy and robustness. We found that the model is highly effective at capturing individual differentiation abilities, works for users with and without CVD, can be tuned to balance accuracy and color availability, and can serve as the basis for improved color adaptation schemes.