Características de la zona de estudio y de los cultivos

One of the main questions my research dealt with was the level of personalisation that users of cancer websites prefer. Based on the reviewed literature, some previous studies have explored introducing personalisation to health systems. For example, Myneni et al. [120] proposed an ontology-based framework for delivering personalised care information for young cancer survivors via mobile apps. Kuijpers et al. [121] proposed an interactive portal (various functions from educational to health record overviews) for breast cancer survivors, however without personalisation. And Milliken [190] developed a health-related system that employs mood to search for users or content of a matching mood.

While some of these systems are intended for cancer sufferers, none of them encompass the broad cancer-affected population studied in my research – directly and indirectly affected users and those interested in cancer information. Moreover, previous health research has either focused on systems that provide personalised messages, specifically for cancer survivors, or developing interactive system features. There is a lack of research on cancer websites that have incorporated a comprehensive set of advanced personalisation features that are available in other online domains (e.g., e-commerce or entertainment) or in more recent findings in adaptive Web-based systems. In other words, there is a lack of research on health websites for cancer-affected users, which provide not only personalised content and information, but also other types of rich personalisation. This type of personalisation has been implemented on the PORT website I designed for this research (further explained in Chapter 5).

Furthermore, the environment – language restrictions and healthcare services available – of the target users is also an important research consideration. The target users should be unbiased and unaffected by previous experience with health website personalisation. The health websites that offer certain personalisation features are US based or from developed European countries. The existing literature on online health services, as well as online personalisation, has mainly focused on the Western developed countries, in particular the US, UK, Netherlands, Finland, some other European countries, and China in a few cases. However, research is lacking for environments where the target users have not been

41

exposed to personalised eHealth, and have restricted access to cancer information due to language barriers. My research was, hence, firstly applied to people affected by cancer in B&H, an environment representative of the described issues, to which no studies in this field have so far been applied, to the best of my knowledge. Nevertheless, to ensure broader applicability of the research results, to cancer websites with global audience, efforts were made to include worldwide participants in evaluating the PORT cancer website. Target users from various countries were sampled, including those who have been exposed to personalised online services, as in the UK and the US.

Importantly, previous research has not looked into personalising online health services to user emotions. MyCounterpane [190] is a rare step in that direction, as it provides an online community for people suffering from chronic illnesses such as epilepsy, multiple sclerosis, lyme and mental health issues, to connect with others in a similar mood or obtain mood-matching information, i.e., mood-based support. Nevertheless, to the best of my knowledge, there is currently no cancer website that incorporates emotions (discrete and aggregated) into user profiles for personalisation purposes. Moreover, there are no online health systems that provide emotion-based content recommendations and emotion- based adaptation, as is proposed in this research.

Furthermore, there is a lack of studies on the user perspective about personalisation in online health services, particularly those establishing user preferences between personalised and non-personalised services. One of the rare studies was by Cortese et al. [32], who used a controlled experiment to explore adolescent user preferences for tailored or non-tailored health message elaboration. However, the website content they based their study on was not health specific, but rather focused on adolescent career goals. Moreover, no health-based study has evaluated user preferences for emotion-based personalisation. Hence, another set of open questions arises: What are cancer website user preferences for personalisation? Moreover, can we use controlled experiments to establish whether such users prefer personalised services to non-personalised ones? Furthermore, could emotion-based personalisation be the preferred type of personalisation to be provided on a cancer website?

42

Stemming from the above identified gaps is the second main question of my research. It delves into whether emotions influence user perception and use of specific personalisation features on a cancer website, and how the emotion- and personalisation- related factors reflect on the intentions to reuse a personalised cancer website.

The effect that emotions experienced after computer system use have on behavioural intentions has been researched to an extent. For example, the UTAUT2 model [169] incorporates hedonic motivation as one of the factors affecting behavioural intentions for IT. Yuan et al. [191] have applied the UTAUT2 model to the use of health and fitness apps. Pappas et al. [53] have shown that positive emotions increase purchase intentions in online shopping, while negative emotions have an opposite effect. Nevertheless, there is a

lack of research on the effect of a broader set of discrete emotions evoked post-use. Moreover, there is a lack of studies applied to cancer websites, and how post-use emotions reflect on user intentions to revisit and reuse a personalised cancer website. The effect of personalisation on user affective state has been researched to a limited extent in other online domains. Pappas et al. [53] have found that personalisation introduced to an online shopping site positively affects positive emotions, but does not reflect on negative emotions. Bourgonje [183] have also researched how dynamic pricing (personalising online prices) affects emotions. However, these were mainly applications in the e-commerce area. Furthermore, they provide a singular view of emotions, either in their aggregate states (e.g., based on valence), or focusing on very few singled out emotions. Hence, there is a lack of understanding how personalisation introduced to a cancer website reflects on the emotions of users of such systems. Moreover, there is a need to establish which discrete emotionsare affected – evoked, intensified or lessened – by cancer website personalisation services; and how these emotions connect to website reuse intentions.

Additionally, the effect of pre-use emotions on user preference for individual personalisation features was used as the foundation for proposing emotion-based personalisation for cancer websites in this research. Previous research has explored the use of emotions in tailoring system agent’s responses. Prendinger et al. [192] proposed an empathetic companion which recognises user affective state and adjusts the response of

43

an animated agent used in a virtual job interview. Conati and Maclaren [54] proposed a probabilistic model of user affect, which recognises user emotions during an e-learning based game and enables an intelligent agent to respond more effectively to the player’s affective state.

Since 2007, emotion-based recommender systems have received significant attention; however, they have only been applied to a few areas. For example, Berkovsky [50] proposed using viewer emotions, captured while watching a movie, in generating future movie recommendations. Zheng et al. [186], Gonzales et al. [48], Arapakis et al. [187] proposed incorporating emotions with other contexts in filtering techniques for generating personalised recommendations.

Others have looked into how emotions can be used in adapting system appearance. Blom et al. [179] proposed identifying a player’s affective state via facial expressions, and using these affects to tailor online game space in real-time. Kung-Keat and Ng [185] proposed a model for recognising emotions to adjust the design of an online learning system. Germanakos et al. [33] introduced a system that uses emotional processing (high, medium, low) as an implication how to adapt website aesthetics (font size and weight) and navigation support.

However, there is no research that explored the effect of cancer website users’ emotions on how they perceive individual website features and content, and which they consequently choose to use and interact with. Thereby, no current research has explored the applicability of emotion-based personalisation on cancer-related health websites. Hence, no available research proposes approaches for adoption of emotion-based personalisation on cancer websites, as the previous research has mainly focused on e- learning and online entertainment. Moreover, there is a lack of research that encompasses emotion-based tailoring of both content and system appearance. While previous researchers have either used emotions in tailoring content recommendations or in adapting the design and navigation of the system, the open question is whether the two approaches can be combined within the same system. In other words, can emotions users express at the start and during website use predict the content they would prefer – and thereby be used for personalising content recommendations? But also, can pre- and

44

during-use emotions be used for emotion-based adaptation? Whereby emotions would trigger the adaptation of website navigation and presentation to guide users to the features and content they would prefer to interact with in such an affective state. The research in this thesis addresses the identified open questions.

Finally, while some studies on context-aware recommenders have researched the six basic emotions, the majority of studies on emotion-based personalisation have, however, focused on a single discrete emotion (e.g. anxiety) or their aggregate states (e.g., feeling good or bad). Nevertheless, this thesis argues for the need to extend research to a broader set of discrete emotions, however, also not to neglect the affective states

resulting from aggregated emotions, as both can imply important personalisation patterns.