Personalization of Visual Scene Displays: Preliminary Investigations of Adults with Aphasia, Typical Females across the Age-Span, and Young Adult Males and Females

Abstract

Visual scene displays (VSDs) are becoming an increasingly popular method of message representation within augmentative and alternative communication (AAC) supports; however, design factors can influence the effectiveness of these images as communication supports. One issue that has come to light in recent years is the fact that selecting personalized VSDs, which depict the person with complex communication needs or an individual with whom they are familiar, are preferred over generic VSDs, which depict unfamiliar individuals. Although personalization is likely an important factor in the usability of VSDs, these images may be difficult for clinicians to obtain. As such, compromises must be identified.

The purpose of this study was to explore the effects of controlling personal relevance factors (i.e., age and gender of the people depicted in generic VSDs) on the image preference patterns of adults with and without aphasia. Results from three very preliminary study summaries indicate that gender and age are both mitigating factors in image preference, as males tended to indicate preference for VSDs containing males over those containing females. In addition, females tended to indicate preference for females of a similar age depicted in VSDs.

Introduction

Visual scene displays (VSDs) are contextual images that can be used to represent events, activities, or places for people who rely on augmentative and alternative communication (AAC; Dietz et al., 2006). VSDs differ from the decontextual images often found in traditional, grid-based AAC systems, in that they depict objects and people in their natural, contextual environments. This factor is thought to be highly beneficial for people with complex communication needs who have historically struggled with grid-based AAC systems that require an individual to formulate messages in a word-by-word manner and necessitate complex system navigation (Jacobs et al., 2004). The reason for this, as Dietz and her colleagues (2006) explained, is that the contextual nature of VSDs allows for the representation of holistic messages thereby reducing the message formulation demands commonly associated with grid-based systems. Also, VSDs reduce the need for complex system navigation, as they are often designed with topical navigation rings that allow for a more simplified navigation process.

In addition to minimizing challenges associated with AAC use, VSDs are also thought to capitalize on the relatively preserved skills of people with aphasia. For example, VSDs allow for individuals to use their gist processing skills to rapidly identify the main themes depicted in these images (Thiessen et al., 2019). VSDs also capitalize on visuospatial processing capabilities of individuals with aphasia by depicting items within their natural contexts. Thus, size and other relational characteristics are preserved. This is in direct opposition to grid displays which tend to present all items within discreet cells with each object being of a relatively similar size (e.g., dog and house). Additionally, Dietz and her colleagues (2006) argued that VSDs capitalize on the relatively preserved autobiographical memory of people with aphasia by depicting important life events and people in their natural contexts.

Given their numerous benefits, it is not surprising that VSDs have been shown not only to be preferred over icons (McKelvey et al., 2010) but also to support the functional communication of people with aphasia (Brock et al., 2017; Hux et al., 2010). Although the benefits of VSDs are obvious, not all images are able to equally act in this capacity (Wilkinson & Jagaroo, 2004). Rather, clinicians must make a variety of decisions regarding VSD design when developing AAC supports for their clients. Ideally, the decisions made result in improved ease of image identification and greater accuracy in selection of target messages.

Identifying factors that improve the usability of VSDs is also critically important for the long term success of AAC system implementation. In fact, research indicates that device abandonment may occur as a result of selecting supports that are ill-matched to an individual user’s cognitive abilities (Johnson et al., 2006). Researchers have addressed these concerns by learning more about how individuals with complex communication needs cognitively process VSDs (Thiessen et al., 2016; Thiessen et al., 2014; Wilkinson & Light, 2014) and about their unique preference patterns for specific aspects of VSD design (McKelvey et al., 2010). Study methodologies range from direct questioning (e.g., McKelvey et al., 2010) to the use of eye-tracking technology to examine overt visual attention patterns (e.g., Thiessen et al., 2014). For a more information on VSD design, we encourage readers to review Light and colleagues’ (2019) state of the science paper on AAC display design. For the purposes of this paper, we focus solely on preference for image personalization.

Personalization of VSDs

Personalized VSDs typically contain either the person who relies on AAC or a close friend or family member who is engaged in a familiar, meaningful task in a familiar environment (McKelvey et al., 2010). They have been shown to be preferable to non-personalized, generic VSDs for adults with aphasia and to result in more accurate word-to-picture matching than generic visual scenes (McKelvey et al., 2010). Case study research also suggests that adults with aphasia tend to reference personalized VSDs with greater frequency than generic images during personal narrative production tasks (Dietz et al., 2014; Griffith et al., 2014).

Challenges of Personalization

Although personalized VSDs are likely more effective at supporting the communication of people with aphasia than generic photos, the acquisition of these images may be challenging. This is especially true for individuals who reside in rehabilitation, assisted living, or long-term residential care settings, as family members and close friends may not be available to supply the images required. In these instances, it becomes the responsibility of direct care staff and/or clinicians to capture, print or upload, and update personalized images for the person with aphasia. Given high turnover rates among direct care staff (Gray & Muramatsu, 2013) and the need for AAC facilitator training (Thiessen & Beukelman, 2013), clinicians, who are already facing large caseloads (Kenny & Lincoln, 2012), may find themselves unable to keep up with this demand. Therefore, appropriate, personalized photographs are often unavailable to support an individual’s communication of their life story, family or work-related concerns, community activities, or for social communication.

In those situations, clinicians must adapt and make compromises to balance therapy success with real-life time constraints to achieve optimal outcomes for their clients. One potential option is to select icons or line drawings to represent the information that the individual needs to communicate. Although this may lessen time constraints, it may not be the most effective way to support communication, as people with aphasia tend both to prefer and to more accurate identify personal photographs than line drawn icons. Another option is to consider the large resources of VSDs that can be accessed from the Internet to use in place of personalized photographs. Although this option has promise, care must be taken to ensure that the images selected are optimized for each individual client. One way to accomplish this may be to locate images that have some generic personal relevance such as age, gender, or appearance including physical features. For instance, when serving an older female client, clinicians may consider selecting images of an individual who appears to be of the same gender and of close age to that client; however, to date, this method has been unexplored. Thus, the purpose of the series of preliminary studies conducted herein, was to investigate the effects of generic personal relevance factors, specifically age and gender of people in VSDs. Thus, the images selected for these studies did not include the participants themselves. Instead, they contained people of similar age and gender to the participants.

Rationale for Three Preliminary Research Investigations

The following research projects were triggered by the authors’ experiences with adults with aphasia due to a stroke, who, following their inpatient rehabilitation, transitioned to assisted-living facilities in rural communities. During acute rehabilitation, these individuals’ communication effectiveness was enhanced by the use of VSDs to represent words and messages as compared to printed words or line-drawn images. However, photographic images of them in the assisted-living facility were not available, as they had not previously resided in those facilities. The authors collaborated with the clinical staff to search online for images of individuals of the same gender and similar age range to these individuals in settings consistent in appearance to an assisted-living residence. These images were then added to their AAC systems to support communication. Although the photographs were representative of the assisted living location, one individual expressed concern and even rejected photographs in which the person depicted in the generic, personally relevant VSD was older. This rejection of images based on perceived personal traits resulted in new insight regarding the potential to produce semi-personalized VSDs based on important personal characteristics of individuals with complex communication needs.

To further investigate the effects personal relevance in VSDs, the authors conducted a series of preliminary case studies with small samples of participants to discern whether factors involved in personalization, including the perceived age and gender of depicted people, influenced the visual attention preference patterns of adults without neurological conditions. In addition, a small sample of adults with aphasia also participated. The authors utilized research-based eye-tracking technology to systematically study the personnel relevance choices of these groups of individuals for this preliminary, exploratory investigation.

Method

The authors conducted three preliminary studies for the current paper. These studies were performed under the auspices of an investigational review board. The first focused on the differences in the visual attention preference patterns of three age ranges of females without neurological conditions (i.e., younger = 20-30 years, middle = 40-55 years, older = 60-80 years). The second focused on gender differences for a group of young adult men and women without neurological conditions, and the third focused on the visual attention preference patterns of adults with aphasia. The research methods for the three investigations presented herein were identical. To avoid redundancy, information related to stimuli, procedures, and analysis are described together in the following sections; however, given the differences in groups per study, participants are described separately for each study in the results and discussion section.

Experimental Screen Stimuli

A total of four experimental visual scene screens were utilized for each of these preliminary investigations. Each screen contained four photographs presented simultaneously on the research-based eye-tracker monitor. The four photographs found in each display were matched for a specific theme, as a different person in each of the four photographs was depicted as engaging in the same activity. Themes were selected to be reflective of common tasks in which adults would potentially engage to promote ecological validity (see Table 1). Although VSDs are often utilized to support social interactions and therefore often consist of socially relevant stimuli, the researchers opted to include images of highly recognizable, familiar tasks for this investigation to maximize the chance that all individuals would recognize the image themes. The activity was held consistent across images in each 2x2 screen; however, the people depicted in the photos differed in age and gender such that one younger male, one older male, one younger female, and one older female were presented for each themed display.

Table 1.

Experimental and Distractor Auditory Cue and Themes

Auditory Prompt: “What picture best represents for you (slight pause…”
Experimental Themes	Distractor Themes
Sleeping in bed	Your favorite pet
Listening to music	Visiting with a friend
Drinking water	An animal you could ride
Read a book	A family photo
	Working on a computer

Distractor Screen Stimuli

The researchers also dispersed five additional screens throughout the experiment to reduce the likelihood of participants discerning the purpose of the studies. Each of these screens consisted of four images, much like the experimental screens; however, they differed in that they did not depict four adults of a different ages and genders. Rather, they depicted animals, group pictures, or children and adults engaging a range of activities (see Table 1). The presentation order of the distractor screens was maintained, as they appeared at the same point in the image order for each participant.

Auditory Cues

Prior to viewing each screen, participants were presented with an auditory cue that related to the theme presented on the display. For example, the auditory cue for the visual reading stimulus items was “What picture best represents for you (slight pause) reading a book?” The auditory cues associated with the experimental and distractor stimuli are listed in Table 1.

Equipment

Tobii T60.

The researchers employed the Tobii T60 (Tobii, Danderyd, Sweden), a remote, infrared eye-tracker, to precisely and accurately measure participants’ visual fixations on target stimuli. The T60 consists of a monitor with a 43.2 cm screen and a built-in infrared camera designed to noninvasively measure oculomotor activity. This device was tethered to a computer that housed Tobii Studio 3.2 software, which was specifically designed to interface with Tobii eye-trackers. As such, the visual stimuli used for these investigations were housed within the Tobii Studio software package, and they were sent via direct connection to the T60 eye-tracker to be presented for each participant. Fixation data was then sent from the T60 back to the tethered computer loaded with Tobii Studio for later processing.

Procedures

The procedures were consistent across all three investigations presented herein. Prior to initiating the experimental task, participants completed the Tobii Studio software’s nine-point calibration procedure to ensure the eye-tracker was able to accurately track participants’ eye movements. To complete the calibration procedure, participants sat approximately 64 cm from the Tobii T60 monitor and were instructed to visually fixate on a ball that moved around the monitor, stopping at nine locations. Upon completing this task, the researchers reviewed the calibration accuracy screen provided by Tobii Studio software and the process was repeated as necessary until an effective calibration was achieved. Once this procedure was complete, participants moved on to the experimental task.

Participants viewed a total of nine screens (four experimental, five distractor) while completing the experimental task. Prior to viewing each screen, a black transition screen with a red dot in the center was presented was presented for five seconds. Participants were told to visually focus on the red dot while listening to an auditory cue (i.e., “What picture best represents for you (slight pause)…”) read by the experimenter. This cue was written to allow participants to infer that the image they visually fixated upon was their perceived choice for each stimuli set. . The purpose of the black transition screen was both to provide time for the auditory cue to be presented and to ensure participants were visually fixating on the same screen region prior to the appearance of experimental and distractor images. Immediately after five seconds had elapsed, the transition screen disappeared and was replaced with either an experimental or distractor screen on the eye-tracker monitor for five seconds (see Figure 1). This procedure repeated until all images had been viewed. The stimuli and transition screens described above were presented in the same order for each participant across all three studies.

Figure 1.

Stimulus presentation order. Photographs were unable to be provided due to copyright restrictions.

Data Analysis

As stated above, we utilized eye-tracking technology to measure the visual attention patterns of our participants. This information allowed us to infer image selection without physical access of the images presented on the eye-tracker monitor. Participant fixation data was recorded and transmitted directly to the tethered computer loaded with Tobii Studio software. The researchers set the fixation threshold at 40 ms of relative immobility of eye movement. This threshold has been used by researchers in the AAC field to account for rapid fixations placed on relatively small elements presented within visual stimuli (Thiessen et al., 2014; Wilkinson & Light, 2011). A single dependent variable was selected for these investigations, percent of time fixated. Percent of time fixated was calculated by summing the total amount of time participants fixated on each image in a stimulus screen and dividing that by the total fixation time on the images in the screen. Percent of time fixated has been shown to correlated with the importance of an element within an image (Jacob & Karn, 2003). This metric served as a proxy for selection of preferred image for this investigation. Specifically, individuals were asked which image best represented a particular action or theme and they responded by fixating upon their intended target. Thus, image preference was inferred through gaze location. Visual attention has been used in previous AAC research to indicate a selected choice and allow for investigation of the cognitive processing associated with AAC displays (Thiessen et al., 2017).

Results and Discussion

Study 1: Visual Attention Patterns of Three Age Groups of Women without Neurological Conditions

The purpose of the first study was to investigate the visual attention and preference patterns of ten younger (20 to 30 years of age), ten middle-aged (40 to 55 years of age), and ten older women (60 to 80 years of age). The participants were recruited from the personal networks of the researchers and were neither professional nor pre-professional speech-language pathologists, occupational therapists, or psychologists.

Summary data is reported in Tables 2 and 3. Results revealed that the younger group of female participants visually focused on images containing females 79.1% of the time, more specifically images of younger women 64.3% of the time and images of older women 14.8% of the time. In contrast, they focused their visual attention on VSDs containing males 20.9% of the time with 10.8% of that time visually focused on younger male images and 10.1% on older male images. The group of middle-aged female participants focused their visual attention on VSDs containing females 59.9% of the time with 30.8% of that time spent on younger female images and 29.1% on older female images. Middle-aged female participants also spent 40.1% of their time on VSDs containing males with 17.8% of that time being spent on younger male images and 22.3% on older male images. The older group of female participants visually focused on images containing containing females 71.3% of time with 40.9% of that time focused on younger female images and 30.4% on older female images. Those participants also spent 28.7% of their time visually focused on images of males with 14.2% of that time on young male images and 14.5% on older male images.

Table 2.

Percent of Time Fixated on Male and Female Images for Women in Three Age Groups

Participants	Age (Years)	Female Images	Male Images
Younger Women	20 to 30	79.1%	20.9%
Middle-aged Woman	40 to 55	59.9%	40.1%
Older Women	60 to 80	71.5%	28.7%

Table 3.

Percentage of Fixation Time for Women in Three Age Groups

VSD Images	Participants
	20-30 years	40-55 years	60+ years
Young Females	64.3%	30.8%	40.9%
Older Females	14.8%	29.1%	30.4%
Young Males	10.8%	17.8%	14.2%
Older Males	10.1%	22.3%	14.5%

These results indicated that female participants visually attended more to images depicting females than images containing males suggesting that gender may play an important role in the selection of visual scenes for women. However, that finding was not consistent across all age groups, as middle-aged females demonstrated a greater proportion of fixation time on images of males than did younger or older female participants. Specifically, participants in the middle-aged group visually focused more on images with males than did those in the other age groups. In an informal discussion with the researcher following the experimental task, some women in the middle-aged group indicated that they felt unrepresented by images of older and younger women and expressed a need for images representing ages closer to their own. This could have influenced the nature of their viewing patterns; however, further work is necessary to determine whether this finding is consistent across larger groups of participants.

Study 2. Visual Attention Patterns of Typical Young Women and Men

The purpose of the second investigation was to examine whether gender played a role in image preference for adults without neurological conditions. As such, the researchers compared the visual attention patterns of younger (20-30 years) men and women without neurological conditions to the same set of experimental displays described above. As stated above, the research methods employed for this investigation were consistent with those used in the previous study. The participants were recruited from the personal networks of the researchers and were taken from the same pool as those in the first study. They were neither professional nor pre-professional speech language pathologists, occupational therapists, or psychologists.

The summary data is reported in Table 4. Across the visual images the female group fixated on visual scenes with females 79.1% of time and on visual scenes with males 29.1% of the time. The male group fixated on visual scenes with males 78.41% of the time and on visual scenes containing females 20.9% of the time. These results support the conclusion that males and females tend to visually focus on visual scenes containing people of their own gender than the opposite gender. Perceived age also appeared to have an effect, as the young male participant group tended to focus more on visual scenes depicting younger males (63.0%) than those containing older males (15.2%).

Table 4.

Percent of Fixation Time of Young Adult Females and Males for Four Visual Scene Displays

Visual Scene Displays	Participants
	Men	Women
Young Females	13.1%	63.3%
Older Females	9.6%	14.8%
All Females	22.7%	78.1%
Young Males	63.0%	10.8%
Older Males	15.2%	10.1%
All Males	78.4%	20.9%

Study 3: Visual Attention Patterns of Women and Men with Aphasia

The purpose of the third preliminary study was to determine whether individual males and females with aphasia differed in their preference of VSDs based on the age and gender of the human figures depicted in those images. Results from a small sample of six participants (2 males, 4 females) are summarized in Table 5. Results revealed that the two male participants visually fixated on visual scenes depicting males 66% and 75% (M = 70.5) of the total viewing time, and on scenes containing females 35% and 25% (M = 30.0) of the total fixation time, respectively.

Table 5.

Percent Visual Fixation Duration for Men and Women with Stroke

Participants	Age (Years)	Aphasia Severity	Female Images	Male Images
Men
1	65	Mild	25.0%	75.0%
2	74	Mild	11.9%	88.1%
Women
1	20	Mild	53.5%	46.5%
2	54	Mild	68.0%	32.0%
3	61	Moderate	48.6%	54.0%
4	86	Moderate-Severe	50.7%	49.3%

Note. Aphasia severity rated by speech-language pathologist working with participant

The individual results for women with aphasia are also summarized in Table 5. There was some variation among female participants’ performances; however, on average, they focused their visual attention on visual scenes with females 55.20% (SD = 8.77) of the total viewing time and on visual scenes with males 45.45% (SD = 9.49) of the total viewing time. In follow-up discussions, it was noted that some of these women viewed themselves as middle-aged and were not comfortable choosing the younger or the older female images in the displays.

Clinical Implications

Although the sample sizes from the studies presented herein were small, results rendered may still serve to inform clinical practice. The most notable finding among these investigations is that perceptions of one’s age and gender appear to play a role in image preference, as those without neurological conditions selected images that more closely matched them in regards to those two features. Male participants with aphasia also demonstrated a relatively strong propensity to select images containing men; however, females with aphasia were less consistent in this result. The fact that females with aphasia were somewhat inconsistent in their selection of gender matched images could have been a result of issues with age representation, as reported above. When considering these results and the potential challenges associated with obtaining personalized photos along with the risk of device abandonment with improper feature matching (Johnson et al., 2006), clinicians may wish to explore the use of semi-personalized photos depicting human figures who closely resemble their clients when designing AAC systems.

The selection of semi-personalized photos would assist in overcoming the challenges associated with obtaining personalized photos; however, this process may not be fully effective when lead solely by clinicians. Rather individuals with aphasia should be empowered to select the images that feel are most representative of their self image. This was evidenced in the current studies as some participants felt unrepresented by the age categories presented via the study images. Perhaps a more effective way of selecting semi-personalized photos would be for clinicians and their clients to work together to co-construct an image profile that closely mirrors each client’s unique vision of themself.

The process of co-constructing a visual representation of a client may seem somewhat foreign; however, it is not unlike other aspects of the AAC assessment and treatment process. AAC is an inherently personalized method of treatment, as best practice dictates that clinicians determine their clients’ vocabulary needs based on personal interests and experiences (Renvall et al., 2013) that they identify the most appropriate method of access and message representation for each of their clients based on strengths, deficits, and preference (Beukelman & Light, 2020). Thus, selecting an ideal representation of a client would be another step in the customization process of AAC supports.

The preliminary nature of current studies does leave many questions unanswered in regard to the selection of personalized images. For instance, little is known as to whether semi-personalized photos would support communication as effectively as personalized images. In the event that personalized photos prove to be a more effective communication support, clinicians may find it necessary to weigh factors such as the importance of particular topics and the frequency with which specific communication situations occur when determining when and which contexts a fully personalized photo is necessary or if a semi-personalized photo is adequate. An additional question that remains unanswered is whether factors are critical for optimizing semi-personalized images. For instance, in these studies, only age and gender were examined; however, many other aspects of physical appearance may also require consideration such as race, ethnicity, hair color and style, body structure, and clothing style. It is possible that these factors could influence an individual’s adoption of an alternate human figure as a personal representation of themself.

Study Limitations and Future Directions

As was noted earlier, these studies were completed as very preliminary, exploratory investigations of semi-personalization of the people depicted in VSDs. Results rendered from these studies provide support for further investigations of personal relevance; however, several study limitations must be considered by future researchers. The first major limitation was the sample size of participants recruited for each study. Although larger samples are always preferrable, in the case of these investigations, the authors’ goal was to explore the possibility of semi-personalization and whether further exploration would be warranted. As such, future research with larger sample sizes should be conducted to determine the full benefits of feature personalization for individuals with acquired neurological conditions. In addition, larger sample sizes of males are essential to determine if age is an important factor to consider for these individuals, as it appears to be for females.

A second major limitation of the study was the fact that full language testing was not conducted on the participants with aphasia. Although a qualified speech-language pathologist observed the participants and provided labels ranging from mild to severe, no standardized or systematic method was utilized to determine type or severity of aphasia. Future researchers should not only conduct a larger scale investigation, but should also complete thorough language testing to ensure type and severity of aphasia are documented.

The third major issue with these investigations is the diversity of participants and people depicted in images. Specifically, all of the participants recruited for this investigation were Caucasian, and all of the stimuli contained Caucasian individuals. Therefore, the results may not be representative of the full population, as the issue of the relevance of race and ethnicity was not investigated. At the 2018 State of the Science Conference for the Rehabilitation Research and Engineering Center for AAC, the preliminary data included in this article was presented and the conference participants strongly encouraged future research to include race and ethnicity as independent variables.

When considering the diversity of the sample, one must also consider the age ranges and gender identities represented in the stimuli set. These preliminary investigations utilized only young and senior men and women and consideration was not given for potential variation in age and gender identity. Future research should take these factors into consideration to ensure representation of greater populations of individuals.

The final limitation worthy of note was that participants were not expected to physically access their image choice from the four images in the display, rather only visual fixation duration was measured. Although researchers have employed this methodology in prior research (Thiessen et al., 2017), it may not render data that completely represents the choices of participants the way that physically selection either through pointing or use of external aids (e.g., mouse click, response box selection) would. In addition to potential issues with the selection method, the methodology only captured preference at one moment in time. Thus, it is impossible to say whether participants simply preferred an image or whether they would actually use that image over the others presented when engaged in a communication task. Given these issues, it is essential that future research be undertaken to determine whether visual attention fully aligns with physical selection and to ensure that preferred images correspond to those that would be used in real communication situations.

Conclusion

Current research supports the use of personalized VSDs in AAC displays; however, this act could prove problematic for clinicians who may be unable to acquire the necessary images in a timely manner. As such, identifying alternative VSDs that contain aspects of personalization may be an effective means of supporting the communication of people with aphasia. Although further research is necessary to confirm, results from the very preliminary studies outlined herein indicate that age and gender factors may be worthy of consideration by clinicians looking to personalize AAC displays. In addition, further research is necessary to compare the use of semi-personalized and fully-personalized images on communication in functional contexts and for social interaction purposes. It is only through that type of research that we will fully understand the importance of personalization and when more generic or semi-personalized images may be utilized.

1. Which two factors appear to be important consideration when selecting semi-personalized visual scenes?

   1. Age and hair color
   2. Age and gender
   3. Body structure and age

   Pg. 12. Correct answer: B

2. Based on the study results, which of the following best describes the image preference patterns of men with aphasia?

   1. Male participants tended to select nearly equal numbers of images of men and women
   2. Male participants tended to select images of men than on images of women
   3. Male participants tended to select images of women more than images of men

   Pg. 11 Correct answer: B

3. Which statement best describes personalized visual scene displays?

   1. Portrait style photos of close family members or friends of the person who relies on AAC
   2. Line drawn images that depict important places or events for people who rely on AAC
   3. Photos depicting the person who relies on AAC or someone they know engaged in a familiar, meaningful task in a familiar environment

   Pg. 2 Correct answer: C

4. Which statement best describes semi-personalized visual scene displays?

   1. Photos depicting human figures who closely resemble the person who relies on AAC
   2. Photos that depict places and activities that are important and relevant to the person who relies on AAC
   3. Photos depicting the person who relies on AAC or someone they know engaged in a familiar, meaningful task in a familiar environment

   Pg. 12 Correct answer: A

5. Why is it important for a person who relies on AAC to take part/co-construct a visual representation of themselves?

   1. It takes the onus off of the clinician to find appropriate images.
   2. People who rely on AAC might not feel fully represented unless they are part of the process.
   3. There is no reason to work together. Either the clinician or the client should be able to find suitable images on their own.

   Pg. 12 Correct answer: B