Content and Other Resources Recommendations for Individuals with Intellectual Disability: A Review
Abstract
:1. Introduction
2. An Overview of Content Recommendation for the General Population
2.1. Content Recommendation System Categorization
2.1.1. Collaborative Filtering
2.1.2. Content-Based Filtering
2.1.3. Alternative Recommendation Systems
2.1.4. Hybrid Systems
2.2. Challenges
- New community: Refers to the start-up of the recommendation system, when a collection of items exists yet no (or not enough) information about users and their interaction makes it very hard to provide reliable recommendations [48].
- New item: A new item is added to the system; this may be accompanied by metadata, but the lack of previous interactions between users and this item leads to the system not being able to provide recommendations for it [49].
- New user: A new user is introduced to the recommendation system; since this user has not completed any interactions yet, it is not possible for the system to provide a personalized recommendation to this user [14].
3. Intellectual Disability and Its Impact
3.1. Intellectual Disability Definition
- Difficulty understanding new information.
- Difficulties with communication and social skills.
- Slow cognitive processing time.
- Mild or severe learning difficulties.
- Difficulty in the sequential processing of information.
- Difficulties comprehending abstract concepts such as money, time, and the subtleties of interpersonal interactions.
- Mild (periodic support)—can live independently with minimum levels of support and have a good level of self-sufficiency (with some limitations in their psycho-social function), provided that the individual has the help and support of family and appropriate infrastructure and services.
- Moderate (limited support)—independent living may be achieved with moderate levels of support, for example, the support offered in group homes. The individuals are able to perform some tasks and actions related to taking care of themselves, with appropriate supervision and encouragement. They usually acquire some social skills, through a specific childhood education scheme, and are able to operate successfully in a supervised community.
- Severe (extended support)—this disorder is usually due to some neurological damage and requires daily assistance with self-care activities and safety supervision. The individuals need systematic training and structured protection in order to be able to develop some basic self-care and communication skills and operate in a basic and risk-free manner.
- Profound (ongoing support)—requires 24 h care, as these individuals cannot support themselves, while the limitations in their daily functionality and their cognitive function become immediately perceptible and the possibility of education is low.
3.2. Impact of Intellectual Disability in Everyday Life
3.3. How Digital Technologies Can Help Individuals with ID
- Inclusion international (https://inclusion-international.org/ (accessed on 15 September 2022)) is an international network of people with ID and their families. Inclusion is part of the Inclusive Futures initiative, a wider drive funded by United Kingdom Aid to create an equal world for people with disabilities in low- and middle-income countries, which is testing innovative ways to improve economic empowerment and inclusion for people with disabilities, enabling them to find employment and earn a living.
- DisabledBook (https://www.facebook.com/disabledbook/ (accessed on 15 September 2022)) is a Greek social networking platform targeted towards individuals with physical, as well as intellectual, disabilities, suggesting that the online world can change for the better the lives of such persons. Users of this platform can watch movies for free or listen to music from radio producers that are disabled. Additionally, DisabledBook offers the possibility to “like” specific content or other users. As a means of motivation to use the platform, if a user is actively social, i.e., collects many “likes” from other users, logs in to the platform every day, and has a lot of friends, then the platform recommends “secret” social events to him/her. Such a social networking platform could benefit from content recommendations, yet no effort has been taken in this direction.
- ELPIDA project (https://www.elpida-project.eu/index.php/en/ (accessed on 15 September 2022)) is an e-Learning Platform for Intellectual Disability Awareness. It is the outcome of efforts from six organizations from five European countries. The e-platform contains six interactive educational modules aiming at providing training, awareness raising, and/or attitude change in the areas of Human Rights, Communication, Stress Management, Transition to Adulthood, Sexual Health, and Aging. It claims to improve the quality of life of persons with ID by empowering family members, especially their parents, providing them with the necessary knowledge and skills on how to better support the needs of children of all ages with ID.
- ENABLE project (https://arfie.info/2017/12/08/enable-project/ (accessed on 15 September 2022)) proposes an inclusive training/learning platform regarding co-designing, co-delivering, and co-evaluating services for people with ID, along with their families, professionals in ID, and local community representatives.
- The MAS platform [106] is a software system that aims to assist and reinforce the learning capabilities of people with ID, as well as other health issues such as visual and hearing impairments and coordination and movement difficulties. The system offers various features including adaptive games and data processing and monitoring tools. These were installed in an education institution for people with special needs in Madrid, providing caregivers tools that are shown to improve students’ education processes. The MAS platform, along with the educational platforms of the two aforementioned projects (i.e., ELPIDA and ENABLE), lack the implementation of content recommendation techniques, which could significantly improve the learning procedure.
- Stomp [107] is a three-year program supported by the National Health Service (NHS) of England that resulted in an interactive platform for people with ID, offering tangible user interfaces, such as the Stomp drum kit and piano keyboard and many games, which makes use of a floor mat that acts as both input and output. Stomp is designed to provide and encourage new participatory experiences in order to support social and physical interaction.
- Healthy Mind [108] is a website that was developed in order to serve adults with ID and explore the accessibility and interaction of disabled users and their caregivers.
4. Recommendation for Individuals with ID
4.1. Education
4.2. Entertainment
4.3. Employment
4.4. Outdoor/Indoor Mobility
4.5. Online Shopping
4.6. Summary of Recommendation Methods for Individuals with ID
- Recommendation systems have been shown to be able to assist individuals with ID in a variety of ways, and in different domains, from entertainment to finding a job.
- The number of literature works on content recommendation specifically for individuals with ID indicates that very limited research has been performed on this subject.
- Taking a closer look at the fourth column, we observe that very few methods follow a pure collaborative filtering or content-based filtering approach; instead, most works follow alternative schemes such as session-based or knowledge-based recommendation or combine different types of approaches, as discussed in Section 2.
- Explicit information collection is adopted by the works in the jobs and education recommendation domain (for example the bottom four rows), since this is the only way to acquire such precise and sensitive personal data.
- Only one of the reviewed methods reported on specific provisions in the system’s design for protecting the privacy of users.
- Cold start may remain a significant challenge, yet most of the reviewed methods exploit prior knowledge (e.g., knowledge-based systems, as discussed in Section 2.1.3, or an explicitly filled initial user profile) in order to avoid taking additional measures to deal with this challenge. Consequently, this is, most probably, the reason why most methods employ a knowledge-based recommendation scheme.
- Most of the existing content recommendation works for this specific population (the first three rows) lack the ability of multimodal recommendations.
- Most works deal with individuals with mild ID, while only one method (in the third row) addresses individuals with severe ID. This makes sense, since, as discussed in Section 3, severe and profound ID require extended and ongoing support, respectively, even for everyday self-care tasks.
5. Discussion
- A recommendation system targeted to individuals with ID will most likely concern a relatively small community of people (Figure 3a. This favors the adoption of a content-based recommendation approach as its basis, instead of a collaborative filtering one, as can be ascertained from Table 1 (i.e., due to the relevant advantages of content-based recommendation, such as the independence from users and the absence of data sparsity concerns). This could be combined with introducing in the system prior knowledge about the specific characteristics of users with ID, drawing inspiration from knowledge-based recommendation systems.
- Privacy and trust, as discussed in Section 2.2, are of great importance; this applies to any recommendation system but even more so to systems used by a vulnerable population. Special attention should be paid to the exchange of information in a secure way, protecting personal data (Figure 3b). Minimizing the risk of exposing sensitive user profile data must be a priority, and this further advocates for the adoption of a content-based recommendation approach at the core of the recommendation system, due to the inherently increased privacy of such an approach, as can be ascertained by Table 1.
- The new user cold start problem, typical of content-based recommendation approaches, can be alleviated by employing interview-based techniques for the explicit collection of initial user information (Figure 3c), e.g., a questionnaire where the user (or the user’s caregiver) rates a selection of items so that his/her preferences can be inferred. However, for updating these preferences over time, implicit information collection techniques (see Section 2.2) should be employed to collect data from the user’s actions and interactions with the recommendation system. The reason for the latter design choice is twofold: explicit information acquisition from the user requires effort for a person with ID, particularly when their caregiver is not around, and such users are really happy while freely using their mobile devices, as discussed in Section 3.3. Thus, implicit information collection can effortlessly provide a wealth of information for updating the users’ profiles.
- Individuals with ID have difficulty in understanding abstract notions and cannot use complex systems, since the “feeling of difficulty” is a common characteristic in such populations [88]. Additionally, as discussed in Section 3, the verbal skills of individuals with ID are often poor. Therefore, a recommendation system targeted to them should include less text and more examples, e.g., visual aids complying with European standards for accessibility (https://en.wikipedia.org/wiki/EN_301_549 (accessed on 15 September 2022)) to guide them through every step that must be completed when using the system with a simple interface (Figure 3d), including cross-media recommendations (Figure 3e). As documented in [127], and also discussed in Section 4, pre-defined queries, verbal instructions, and a standardized environment fail to attract users with a developed intellectual ability but will suit users with ID; thus, the design principles of a system targeted to persons with ID are significantly different to what has evolved throughout the years and is now common for the general population.
- As discussed in [75,91], the mainstay of treatment and management of ID developmental delay is the utilization of special education. Thus, the recommendation of content items to users with ID should take into account, to the extent possible, the content’s educational potential in relation to the specific educational needs of each individual user (Figure 3f).
- Particularly, when it comes to content consumption patterns, people with ID have difficulty adapting to changes and often prefer watching a very specific set of similar videos. For example, in [127], the subject with ID watched a particular video in different languages over and over again, sometimes for hours. Therefore, the history of consumed items should not only be taken into consideration by the recommendation algorithm but also be easily accessible in the user interface of the system to facilitate re-consumption (Figure 3d).
- User interaction in the digital world is an opportunity for individuals with ID. As discussed in Section 3.3, when Facebook friends of people with ID actively reacted, for example, by liking or replying to posts, the latter individuals gained a sense of social presence. Additionally, people with ID gained a sense of belonging by joining Facebook Groups. Therefore, a content recommendation system for individuals with ID should highlight the similarities of a user to various user groups and open communication channels with other members of these groups in order to trigger the sense of belonging and social presence and promote interaction among its users (Figure 3g).
- In addition to being an opportunity, user interaction can also be a threat. When it comes to social media and similar means of interaction, the caregivers of individuals with ID regularly express concerns over the possibility of bullying incidents. Therefore, a content recommendation system that uses social media as sources for recommendable items, or enables the interaction between its users and/or users of other social media platforms, should ensure that its recommendations will not lead to taking part in an online conversation with other community members that engage in bullying, use profanity, racial slurs or foul language (Figure 3h).
- Individuals with ID can easily fall victim to online forms of fraud, as discussed in Section 3.2. Therefore, a recommendation system targeted to such individuals must provide security mechanisms for the prevention of fraud and the protection of its users, for example, by pre-filtering recommendations to exclude potentially harmful content items (Figure 3i). Moreover, it should empower the user’s caregiver (e.g., a parent) to supervise potentially inappropriate recommendations or interactions via suitable user interfaces and notifications about potentially threatening content or situations.
- Going beyond the core problem of content recommendation, the major challenge that content recommendation aims to help address is the need of individuals with ID for improved quality of life. This calls for a more holistic approach: seeing content recommendation as part of a complete framework that will consist of interactive systems, devices, and services for this community of users. In this direction, an integrated platform with multiple functionalities that include but are not limited to content recommendation, capable of adapting to the individual characteristics of the different ID severity levels of its users, seems to be ideal. Such a platform should support the provision of health, avocation, communication, training, information, and amusement services [3] (Figure 3e,f). All this should be implemented through an interface accessible from multiple devices, providing personalized suggestions according to the specialized users’ interests and skills.
- Finally, also considering the broader community around individuals with ID is important. Depression in the family circle of individuals with ID is a common phenomenon [96]; for this, initiatives such as the Inclusion International (see Section 3.3) urge, for example, the family circle to be involved in the activities of children with ID. A recommendation system should aim to support family members too, by giving them not only a feeling of control over the consumed material or the ability to update the profile of the user but also the ability to propose new recommendations, which can be later consumed together and promote their interaction with the family’s disabled member (Figure 3j).
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Advantages | Disadvantages | |
---|---|---|
Collaborative filtering | - No need for item representation | - New user cold start problem |
- Cross-media support | - New item cold start problem | |
- Good exploration capabilities | - Data sparsity | |
- Easy implementation | - Needs “long shelf life” items | |
- Scalability with respect to number of items | - Need for popular items | |
- Gray sheep problem | ||
Content-based filtering | - No new item cold start problem | - Need for item representation |
- Independence from users | - Poor cross-media performance | |
- Adaptability | - Poor exploration | |
- Increased privacy | - Overspecialization | |
- No data sparsity concerns | - New user cold start problem | |
- Scalability with respect to number of users | ||
- Explainability |
Literature Work | Application Domain | Recommendable Items Type | Recommender System Type | Information Collection | Specific Provisions for Privacy and Trust | Specific Provisions for Combating the Cold Start Problem | Users Target Group |
---|---|---|---|---|---|---|---|
[124] | Education | Videos | Hybrid | Explicit | None | Exploitation of prior knowledge | Children with ID |
[125] | Education | Educational material | Knowledge-based | Explicit | None | Not needed | Students with mild ID |
[126] | Entertainment | Videos | Collaborative filtering | Implicit and Explicit | None | Introduction of a “profile separation” technique | Disabled individuals or individuals with mild ID |
[127] | Entertainment | Videos | Session-based | Implicit | Case study considering privacy aspects in personalization | None | Individuals with severe ID |
[3] | Entertainment | Videos, images and text | Content-based | Implicit and Explicit | None | A first profile is constructed through an interview | Individuals with mild to severe ID |
[131] | Employment | Job instructions | Knowledge-based | Explicit | None | Not needed | Workers with cognitive disabilities |
[133] | Employment | Jobs | Knowledge-based | Explicit | None | Not needed | Disabled individuals and individuals with mild ID |
[134] | Employment | Jobs and job skills | Knowledge-based | Explicit | None | Not needed | Disabled individuals and individuals with mild ID |
[135] | Outdoor mobility | Trip arrangements | Session-based | Explicit | None | Not needed | Individuals with mild ID |
[136] | Outdoor mobility | Accessibility resources | Hybrid | Implicit and Explicit | None | Explicit initial user profile | Disabled individuals, elderly and individuals with mild ID |
[137] | Indoor mobility | Smart home functionalities | Knowledge-based | Explicit | Private home server with no access to the Web | Not needed | Disabled individuals and individuals with mild ID |
[138] | Online shopping | Technology products | Knowledge-based | Explicit | None | Not needed | Autism Spectrum Disorder |
[139] | Online shopping | Technology products | Knowledge-based | Explicit | None | None | Individuals with intellectual and developmental disabilities |
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Apostolidis, K.; Mezaris, V.; Papadogiorgaki, M.; Bei, E.S.; Livanos, G.; Zervakis, M.E. Content and Other Resources Recommendations for Individuals with Intellectual Disability: A Review. Electronics 2022, 11, 3472. https://doi.org/10.3390/electronics11213472
Apostolidis K, Mezaris V, Papadogiorgaki M, Bei ES, Livanos G, Zervakis ME. Content and Other Resources Recommendations for Individuals with Intellectual Disability: A Review. Electronics. 2022; 11(21):3472. https://doi.org/10.3390/electronics11213472
Chicago/Turabian StyleApostolidis, Konstantinos, Vasileios Mezaris, Maria Papadogiorgaki, Ekaterini S. Bei, George Livanos, and Michalis E. Zervakis. 2022. "Content and Other Resources Recommendations for Individuals with Intellectual Disability: A Review" Electronics 11, no. 21: 3472. https://doi.org/10.3390/electronics11213472
APA StyleApostolidis, K., Mezaris, V., Papadogiorgaki, M., Bei, E. S., Livanos, G., & Zervakis, M. E. (2022). Content and Other Resources Recommendations for Individuals with Intellectual Disability: A Review. Electronics, 11(21), 3472. https://doi.org/10.3390/electronics11213472