Design and evaluation of a personal robot playing a self-management education game with children with diabetes type 1

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Personalization, the involvement of stakeholders in the design process, is often applied in serious game design for health. It is expected to enhance the alignment of a game to the preferences and capacities of the end-user, thereby increasing the end-user’s motivation to interact with the game, which finally might enhance the aimed-for health effects of the game. However, the nature and effect of personalization have never been systematically studied, making assumptions regarding personalization ungrounded. In this literature review, we firstly provide a proposal of our Personalized Design Process-model, where personalization is defined as stakeholder involvement in the Problem Definition-, Product Design- and/or Tailoring Phase. Secondly, we conducted a systematic literature review on this model, focusing on health and its effects. In this review, 62 of the 2579 found studies were included. Analysis showed that a minority of the studies were of methodologically higher quality and some of these tested the health effect by contrasting tailored versus non-tailored games. Most studies involved stakeholders in the Tailoring Design Phase. Therefore, we conclude that involving stakeholders in the Tailoring Phase is valuable. However, to know if personalization is effective in the Product Design- and the Problem Definition Phase, more studies are needed.

Background Electronic health (eHealth) programs are often based on protocols developed for the original face-to-face therapies. However, in practice, therapists and patients may not always follow the original therapy protocols. This form of personalization may also interfere with the intended implementation and effects of eHealth interventions if designers do not take these practices into account. Objective The aim of this explorative study was to gain insights into the personalization practices of therapists and patients using cognitive behavioral therapy, one of the most commonly applied types of psychotherapy, in a youth addiction care center as a case context. Methods Focus group discussions were conducted asking therapists and patients to estimate the extent to which a therapy protocol was followed and about the type and reasons for personalization of a given therapy protocol. A total of 7 focus group sessions were organized involving therapists and patients. We used a commonly applied protocol for cognitive behavioral therapy as a therapy protocol example in youth mental health care. The first focus group discussions aimed at assessing the extent to which patients (N=5) or therapists (N=6) adapted the protocol. The second focus group discussions aimed at estimating the extent to which the therapy protocol is applied and personalized based on findings from the first focus groups to gain further qualitative insight into the reasons for personalization with groups of therapists and patients together (N=7). Qualitative data were analyzed using thematic analysis. Results Therapists used the protocol as a “toolbox” comprising different therapy tools, and personalized the protocol to enhance the therapeutic alliance and based on their therapy-provision experiences. Therapists estimated that they strictly follow 48% of the protocol, adapt 30%, and replace 22% by other nonprotocol therapeutic components. Patients personalized their own therapy to conform the assignments to their daily lives and routines, and to reduce their levels of stress and worry. Patients estimated that 29% of the provided therapy had been strictly followed by the therapist, 48% had been adjusted, and 23% had been replaced by other nonprotocol therapeutic components. Conclusions A standard cognitive behavioral therapy protocol is not strictly and fully applied but is mainly personalized. Based on these results, the following recommendations for eHealth designers are proposed to enhance alignment of eHealth to therapeutic practice and implementation: (1) study and copy at least the applied parts of a protocol, (2) co-design eHealth with therapists and patients so they can allocate the components that should be open for user customization, and (3) investigate if components of the therapy protocol that are not applied should remain part of the eHealth applied. To best generate this information, we suggest that eHealth designers should collaborate with therapists, patients, protocol developers, and mental health care managers during the development process.

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