The operational framework has the potential to produce ICT and services with high clinical impact but requires substantial investment.

Developing technology that accounts for values has been achieved in many areas, including security, gaming, finance, engineering, and many more. The main methodological approach has been that of value sensitive design. But most of the work to date has been on the first of its three stages. The focus of this article is on advances related to its second stage, empirical investigation, and in particular the impact of contextual understanding in that stage. Although lessons can be learnt from other domains, the specific context of dementia means that there are nuances to understanding values, including justice and autonomy, that differ from other areas. The integration of value considerations in the development of assistive technology in dementia is explored in two broad categories: the traditional and ongoing need for fixed decision support, and adaptable decision support technologies. For fixed decision support the A&D Benchmark is particularly useful in design. But for adaptable technologies, that benchmark requires further development, including consideration of the values of additional stakeholders, such as the general public.

A rising elderly population and diminishing number of family and professional carers has led to calls for the intervention of care robots. This leaves the quality of robot-delivered care to be determined by designers, for profit companies, nursing codes of practice and conduct, potential user sample groups, etc. What is missing is the carer who consciously makes good ethical decisions during practice. Good care is ‘determinative in practice’. That is, a carer can make good decisions because they are making them within the carer-patient relationship. If a robot is to be capable of good care ethics on the same level as humans, it needs to be conscious and able to make dynamic decisions in practice. Moreover, a care robot must conduct patient interactions in appropriate ways, tailored to the person in its care, at run-time. This is because good care, as well as being determinative in practice, is tailored to the individual. The introduction of robotic care determined by limited stakeholders leaves customised care in danger and instead could potentially turn the quality of elderly care into ‘elderly management’. This study introduces a new care robot framework—the attentive framework—which suggests using care centred value sensitive design (CCVSD) for the design process, as well as a computationally conscious information system (IS) to make practice-determinative decisions in run-time with extrinsic care value ordering. Although VSD has been extensively researched in the IS literature, CCVSD has not. The results of this study suggest that this new care robot framework, which is inspired by CCVSD, is competent in determining good, customised patient care at run-time. The contribution of this study is in its exploration of end-user willingness to trust known AI decisions and unwillingness to trust unknown AI decisions. Moreover, this study signifies the importance of, and desire for, good, customised robot-delivered care.

Client welfare is detrimentally affected by poor communication of data between rural service providers, which in part is complicated by privacy legislation. A study of service provision involving interviews with mental health professionals, found challenges in communicative processes between agencies were exacerbated by the heavy workloads. Dependence on individual interpretations of legislation, and on manual handling, led to delays that detrimentally affected client welfare. The main recommendation arising from this article is the creation of an ehealth system that is able to negotiate differing levels of access to client data through centralised controls, where the administration of that system ensures that it stays current with changing legislative requirements. The main contribution of the proposed model is to combine two well-known concepts: data integration and generalisation. People with mental illness are amongst the most vulnerable members of society, and current ehealth systems that provide access to medical records inadequately cater to their needs.

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