It is easy to see that technology, especially in the most technologically developed societies, is present in many areas of our lives. Just think of the equipment we use every day, such as mobile phones, remote controls, home alarms, microwaves, computers, among others. The technological development has been very fast and its applications broad spectrum. Today, through a mobile phone, we can manage the heating system of the house, make purchases and have appointments online. This spectacular technological development, aimed at the general population, is called McCreadie (2010) as conventional technology (mainstream technology).
The development of conventional technology has been accompanied by the development of technology aimed at people with special needs (including the elderly), which McCreadie (2010) calls "special needs technology". This technology is further divided into "assistive technology "1, robotics and telecare (McCreadie, 2010).
Assistive technology consists of "products and services designed with the aim of promoting independence for older people and people with disabilities" (McCreadie, 2010: 608). According to Lansley and his collaborators (2004), this technology is divided into three main types: (a) portable (e.g. wheelchairs and walkers); (b) stationary (devices installed in accommodations, such as lifts and ramps); (c) electronic (devices requiring electrical power or energy stored in batteries, such as alarms and door openers).
Robotics is "an electromechanical system under some form of computerized control that gives the illusion that it has some agency or intent of its own" (McCreadie, 2010: 608). Robotics has expanded into several fields of activity, developing robots to mow the lawn, to vacuum the house, to help people get out and into bathtubs or showers, to provide information and news, etc. (McCreadie, 2010).
Finally, tele-assistance refers to "application of information and communication technology to promote and enable independent care in the community and home setting" (Emery et al., 2002: 29). Barlow et al. (Barlow et al., 2003 in Barlow et al., 2005: 443) distinguish two types of telecare devices: a) those designed for information recording; b) and those designed for risk management. The first type of device is used, for example, in health care, where information about a person's health status is sent to health professionals, allowing remote monitoring of their health status. The second type of device has risk management as its central objective, although the first type of device may also have risk management as its objective (Barlow et al, 2005).
Sixsmith and Sixsmith (2008) give the example of alarms, in which an individual presses a button or pulls a string, thus activating a warning that will be identified and managed in a call center. This is, according to Sixsmith and Sixsmith (2008), an example of the first generation of telecare devices. However, according to these authors, a second generation of these devices was developed with the aim of being useful also for individuals who cannot activate the alarm for physical or cognitive reasons. These devices are intended to capture "abnormal" patterns of activity, such as sensors that detect immobility of the body over a long period of time or sensors that detect sudden movements or changes in body position, which can indicate a fall (Sixsmith and Sixsmith, 2008).
The expansion of the supply of special needs technology, particularly for older people, is the result of a market opportunity created by the mismatch between "ageing in place" policies, which aim to keep older people in their communities/households as long as possible, and the support that actually exists to enable this goal to be achieved.
Ageing in place" policies are considered more economically advantageous than policies that focus on institutional care (Mostashari, 2011), and are in line with the preferences and aspirations of most older people, who prefer to continue living in their own homes (Bettio and Verashchagina, 2010; DeJonge et al., 2009). It is true that there has been a deinstitutionalization of health care and long-term care, especially for the elderly and chronically ill (Marin et al., 2009; Vassli and Farshchian, 2017), a deinstitutionalization that began even before the formulation of policies to "age in place". However, it is also true that support/services in the community, both formal (e.g. support provided by health centres, so-called third sector or social sector institutions) and informal (e.g. support provided by family, friends and neighbours) have been under strong pressure.
If, on the one hand, the demand for health care and long-term care has increased and will continue to increase due to population ageing and the increased prevalence of some disabilities and disabling diseases (Lafortune and Balestat, 2007; OECD, 2011), on the other hand, this care has faced severe constraints. With regard to formal care, there have been strong budgetary pressures, particularly in the area of health and long-term care, and difficulties in recruiting and retaining professionals, especially in the long-term care sector (Fujisawa and Colombo, 2009). In informal care, pressures have not been reduced, mainly due to several changes in family structures and dynamics. Among these changes, there has been an increase in women's participation in the labour market (traditional carers), which in most countries is full-time, posing problems in reconciling work and family care. In this regard, in most OECD countries the number of informal carers, particularly adult children, is expected to decline in the future (Colombo et al., 2011).
Faced with this mismatch, there are several supporters of the idea that the solution involves focusing on special needs technology (Khosravia and Ghapanchi, 2016; Pinto-Bruno et al., 2017; Vassli and Farshchian, 2017). They argue that this technology, in addition to contributing to "ageing in place", also facilitates the fight against social isolation, promotes the quality of life of older people, reduces health and long-term care costs, and reduces readmissions to hospitals and the length of hospital stays (Khosravia and Ghapanchi, 2016; Vassli and Farshchian, 2017).
Indeed, in recent decades, several special needs technologies have been developed to support older people (Azimi et al., 2016; Khosravia and Ghapanchi, 2016; Padilla, 2008), including the internet of things. The "Internet of things" refers to "(...) pervasive presence around us of a variety of things or objects - such as Radio-Frequency IDentification (RFID) tags, sensors, actuators, mobile phones, etc. - which, through unique addressing schemes, are able to interact with each other and cooperate with their neighbors to reach common goals" (Giusto et al., 2010, in Azimi et al., 2016: 2787). Azimi and its partners (2016) organize the various applications and services based on the "Internet of Things" into five categories: a) health monitoring (e.g., monitoring of medication intake); b) nutritional monitoring (e.g., weight monitoring); c) safety monitoring (e.g., fall detection); d) location and navigation (e.g., indoor location and route planning); e) and social networks (e.g., online shopping).
The following pages provide an overview of the literature on the subject of technologies in the most advanced stages of life. First, the theories and conceptual models used in empirical research are reviewed. Second, the available empirical evidence is reviewed. Finally, the main contributions and limitations of the revised literature are systematized.
Research on the theme of technologies in the most advanced stages of life: Theory and conceptual models
The literature review identified the main theories and conceptual models mobilized in empirical research on the subject of technologies in the most advanced stages of life, that is: a) The Unified Theory of Acceptance and Use of Technology (UTAUT); b) A theoretical model to explain the smart technology adoption behaviors of elder consumers (Elderadopt); c) Theoretical Model of Assistive Technology Adoption and Use by Older People; d) A New Framework for Theorizing and Evaluating Nonadoption, Abandonment, and Challenges to the Scale-Up, Spread, and Sustainability of Health and Care Technologies (NASSS).
The Unified Theory of Acceptance and Use of Technology (Venkatesh et al., 2003), subsequently expanded and designated with the acronym UTAUT2 (Venkatesh et al., 2012), is one of the most widely used and known theories in the field of research on technologies in the most advanced stages of life (Tan & Chan, 2018). This theory has as a dependent variable the effective use of a certain technology (use behavior) and as an intervening variable the behavioral intention, that is, the intention to use a certain technology.
The independent variables are: a) performance expectancy; b) effort expectancy; c) social influence; d) facilitating conditions; e) hedonic motivation; f) price value; g) habit (Venkatesh et al., 2012).
Following Venkatesh and collaborators (2012), the first construct (performance expectation) refers to the perception of the benefits that the use of a technology will bring to the performance of certain activities. The second construct (effort expectation) aims to account for the level of effort required for the use of a technology. On the other hand, the third construct (social influence) refers to situations in which other people (e.g., family and friends) influence the consumer to use a particular technology. The fourth construct (enabling conditions) includes the resources and supports available to use a given technology. The fifth construct (hedonistic motivation) consists of the potential pleasure or satisfaction that is withdrawn from the use of a technology. The sixth construct (price value) is defined as the compensation between the perceived benefits and the monetary cost of using a particular technology. The price value is positive when the benefits derived from the use of a technology are perceived as higher than the costs of use. Finally, the last construct (habit) refers mainly to past uses of technologies. In addition, this theory also includes three moderating variables: a) age; b) gender; c) experience.
The Unified Theory of Acceptance and Use of Technology proposes that the effective use of a given technology depends on behavioral intent, facilitation conditions, and habit. In turn, behavioral intent depends on performance expectation, effort expectation, social influence, facilitating conditions, hedonistic motivation, price value, and habit. Finally, the relationships between independent variables and the intervening variable (behavioral intention) are moderated by age, gender, and experience. Experience also moderates the relationship between behavioral intent and the effective use of technology.
Despite its popularity, this theory has been the subject of several criticisms, including the fact that it neglects the contextual aspects of both the micro, meso and macro nature that can shape the use of technologies (Tan & Chan, 2018). Examples of these contextual aspects are the level of education and income, the family support network, and the political and economic contexts. According to Tan and Chan (2018), this suggests that studies on the acceptance and use of technologies should include a more structural perspective in the development of conceptual models.
In accordance with the limitations of the Unified Theory of Acceptance and Use of Technology, Golant (2017) proposes a theoretical model to explain the adoption of technological or non-technological coping solutions by older people, which it calls "Elderadopt". This model proposes that older people's assessment of support solutions depends on four factors: a) the perceived stressfulness of individual's unmet needs, i.e. the severity of unsatisfied needs, the temporary imminence of unsatisfied needs and the duration of unsatisfied needs; b) individual resilience, i.e. perceived self-efficacy, openness to new experiences and flexibility of adaptation; c) the level of persuasion of internal (resulting from past experiences) and external (transmitted by the media, family, professionals, etc.) information.); d) the attributes of the supporting solutions, namely perceived efficaciousness, perceived usability and perceived collarteral damages. According to this model, the more positively older people evaluate support solutions, the more likely they are to adopt them. Older people's decisions may include: (a) adopting one or more technology support solutions; (b) adopting one or more non-technological/traditional support solutions; (c) adopting technology support solutions and non-technology support solutions; (d) not adopting any of the support solutions (see Figure 1).
Tan y Chan (2018) sostienen que UTAUT2 y Elderadopt se centran, sobre todo, en el "qué" (what), es decir, en los factores/variables que influyen en la adopción de tecnologías. Sin quitar valor a estas
theoretical perspectives, these authors argue, however, that it is also necessary to analyse the "how", that is, the processes or, in other words, the way in which consumers use technologies. In this sense, Tan and Chan (2018) propose the mobilization of the Theory of Practice of the French sociologist Pierre Bourdieu (1977), which seeks to overcome the dualism between agency and structure.
In the field of health and long-term care, Greenhalgh and his collaborators (2013) proposed a Theoretical Model of Assistive Technology Adoption and Use by Older People. This model is based on the following notion introduced by Sayer: "what matters to people" in the course of their daily lives, i.e. in terms of networks of relationships, support, material aspects, etc. (Sayer, 2001 in Greenhalgh et al 2013: 88). In addition to this notion, Greenhalgh and collaborators (2013) mobilize the phenomenology of Merleau-Ponty, in particular the notions of "body schema" (capacity of physical and psychological commitment with the world to make action possible) and "motor intentionality" (pre-reflexive awareness of oneself and the environment). It is this capacity and this consciousness, in combination with more reflexive forms of intentionality, that allows the participation of older people, once sick or incapacitated, in the world. As for technology, Greenhalgh and his collaborators (2013) conceive it as a mediator of the relationship between the individual and the world. However, in the opinion of these authors, technology can be "disabling" or "enabling", as well as "dis-empowering" or "empowering".
To resolve the criticism directed at phenomenology that neglects the role of social structures in individual action, Greenhalgh and collaborators (2013) also mobilize the Strong Structuration Theory developed by sociologist Rob Stones, adapted to incorporate the technological dimension (Greenhalgh & Stones, 2010). Within the framework of this adaptation, Greenhalgh and Stones (2010) highlight one of the central aspects of the Strong Structuring Theory, namely the recursive relationship between structure and action, in the sense that structure is not only a condition of action but also a result of action. In addition, they distinguish between external and internal structures. External structures include historical and social forces, which are macro in nature, and networks of position practices (networks of positions occupied by individuals and technologies, and relationships between positions), which are meso 2 in nature. In turn, internal structures are those that "inhabit" individuals and technologies. The internal structures of individuals include the general dispositions (mental and corporal) and the embedded knowledge, which corresponds to the notion of "habitus" developed by the sociologist Pierre Bourdieu. Conjuncture-specific knowledge refers to the knowledge of the structures of meaning (interpretative schemes), the structures of legitimization (social norms and expectations) and the structures of domination (distribution of power) in force in each situation/context of social interaction, as well as to the knowledge of the material properties of the technologies and of the socio-cultural structures inculcated in them, and of their functionalities. The internal structures of technologies include their inculcated material properties and socio-cultural structures (e.g. decision models and privileged access), and their specific conjunctural functionalities (functionalities relevant to each situation). Finally, there is the action of both individuals and technologies, although Greenhalgh and Stones (2010) argue that individuals and technologies do not act in the same way. Figure 2 outlines the Theoretical Model of Adoption and Use of Assistive Technology by Older People.
Based on the adaptation of the Strong Structuring Theory from Greenhalgh and Stones (2010), Greenhalgh and colleagues (2013: 89) propose five questions to guide the analysis of older people's adoption and use of assistive technologies:
"1. What is the social, cultural and historical context in which this participant is experiencing ageing and chronic illness?
2. What is their experience of illness, ageing and (if appropriate) decline and impending death? In particular, what can we say about their existence in the world and their body schema and motor intentionality?
3. What matters to this participant? What are their key relationships and who or what do they care most about?
4. What are the key technologies in their home and life? To what extent, and in what way, are these technologies materially ‘ready-to-hand’ (hence enabling and empowering)? If they are ‘not working’, why?
5. What happens in particular, real-life situations when the participant contemplates (or might be expected to contemplate) the use of an assistive technology and what are the consequences of this for them and for the people they care about? In such situations, how do they draw on their culturally shaped dispositions and body schemas (‘habitus’) and on the materiality of available technologies to achieve what matters to them? If they choose not to use an assistive technology, how is this explained with reference to habitus and materiality?".
More recently, Greenhalgh and his collaborators (2017) developed a conceptual model to predict and evaluate the success of the implementation of assistive technologies in health and long-term care, which they called "A New Framework for Theorizing and Evaluating Nonadoption, Abandonment, and Challenges to the Scale-Up, Spread, and Sustainability of Health and Care Technologies" (NASSS). This model defines seven areas and 19 questions:
Domain 1 - The condition or disease 1A - What is the nature of the condition or disease? 1B - What are the relevant sociocultural factors and co-morbidities?
Domain 2 - Technology 2A - What are the key characteristics of technology? 2B - What type of knowledge does technology put into action? 2C - What knowledge and/or support is required to use the technology? 2D - What is the technology delivery model?
Domain 3 - Value proposition 3A - What is the advantage for the business developer of the developed technology (value on the supply side)? 3B - What is its convenience, efficiency, security and profitability (value on the demand side)?
Domain 4 - The adopter of the 4A system - What changes are involved in the team's functions, practices and identities? 4B - What is expected of the patient (and/or immediate caregiver) - and is this achievable by him and acceptable to him? 4C - What is assumed about the extensive network of lay caregivers?
Domain 5 - Organization 5A - What is the organization's ability to innovate? 5B - How prepared is the organization for technology-supported change? 5C - How easy will the adoption and funding decision be? 5D - What changes will be necessary in team interactions and routines? 5E - What work is involved in implementation and who will do it?
Domain 6 - The broader context 6A - What is the political, economic, regulatory, professional (e.g. medical-legal) and socio-cultural context for the launch of the programme?
Domain 7 - Incorporation and adaptation in time 7A - How much space is there to adapt and develop technology and service in time? 7B - How resilient is the organization to cope with critical events and adapt to unforeseen events?
Research on the topic of technologies in the most advanced stages of life: empirical evidence
Empirical evidence on the topic of technologies in advanced life stages can be grouped into three main themes: (a) access to technology and the digital divide; (b) acceptance and use of technology; (c) efficiency of technology.
Access to technology and the digital divide
Several studies have focused on the issue of access to technology for older people and associated social inequalities. For example, a recent qualitative study in Singapore on how older people perceive and use information and communication technologies (ICTs) revealed that the use of these technologies depends on the capital they possess, particularly social and cultural capital (Tan & Chan, 2018). This study highlights that, despite advances in terms of usability and accessibility from an economic point of view, many older people in Singapore still lack sufficient educational and language skills and social support networks to facilitate their access to these technologies. In this regard, McCreadie (2010) also emphasises the role of older people's socio-economic profiles (e.g. income, level of education, career and level of dependency) in older people's access to technologies.
Other studies have drawn attention to the existence of a "digital divide" that opposes those who access ICTs and those who do not (e.g. Gilleard & Higgs, 2008; Olphert & Damodaran, 2013). A longitudinal study of older people's use of the Internet in England notes that: "Those born near the end of the first half of the twentieth century are more likely to use the Internet than those born near its beginning" (Gilleard & Higgs, 2008: 238). However, this study argues that this digital divide is not explained by age itself, that is, by age-related structural inequalities or by such intrinsic age-related factors (e.g., mental and/or physical disabilities), but above all by the differentiated diffusion of ICTs among preWorld War II and post-World War II cohorts. In other words, this study concludes that the digital divide in Internet use in later life is the result of a "generational" rather than a "structural" or "life stage" effect.
Acceptance and use of technology
A systematic review of the qualitative literature on the acceptance of health-oriented ICTs by older people living in the community (Vassli and Farshchian, 2017) concluded that they generally show a positive attitude towards ICTs. However, the level of acceptance of these technologies by older people depends on a number of factors. They agree to use these technologies as long as: a) they promote independence; b) they promote security and safety; c) they allow socialization and health status management; d) they allow access to online information; e) they help in daily activities; f) help is given in case of problems with use; g) access to adequate training is guaranteed.
This literature review also identified barriers to the acceptance of ICTs, including the following: a) violation of privacy; b) loss of protection (security); c) cognitive difficulties (e.g. memory loss); d) stigmatization (association of these technologies with dependency, old age, illness and institutionalization). On the issue of stigma, Greenhalgh and colleagues (2013) suggest that older people's acceptance and use of technologies depends on the cultural importance of each technology. For example, while some technologies (e.g. iPads) symbolize social status, independence, modernity and joviality, others (e.g. alarms or incontinence detectors) symbolize precisely the opposite, i.e. stigma, dependence, decadence and loss of joviality.
It should be noted that the violation of privacy, as well as informed consent for the collection of information and the confidentiality of this information are ethical aspects to consider in the use of technologies by older people, especially technologies with special needs (McCreadie, 2010).
According to Selwyn (2004), older people's acceptance/non-acceptance of technology also depends on their level of participation in the technology design process, as effective participation makes technologies more attractive and useful. In this sense, there is increasing talk of "inclusive design" (McCreadie, 2010), that is, technologies designed in such a way that they are friendly for all ages, and not just for the more advanced ones.
Charness (2003) identifies five conditions for successful use of technologies by older people: a) design; b) access; c) motivation/attitude; d) ability; e) training.
When it comes to the first condition (design), it is important that the design is friendly to older people. As mentioned above, the current trend is for design to be inclusive, i.e. friendly to all ages. As for the second condition (access), the price of the product, the income of consumers, the availability of substitute products and the preferences of consumers are determining factors in access to the so-called conventional technology. Consumers' incomes are also determinants of access to special needs technology, as are the provision of information and health and long-term care (Wright et al., 2005). With regard to the third condition (motivation), there is empirical evidence (e.g. McCreadie, 2004) that older people's purchase and use of different technologies depends on the relationship between the need for support and the attributes of the technologies, namely efficiency, reliability, simplicity, safety and aesthetics. Empirical evidence shows that motivation also depends on a number of sociodemographic variables related to older people, such as age, income, gender, education, ethnicity, social networks and pressure groups (McCreadie, 2010). For example, the children and grandchildren of older people, who often use mobile phones and computers, can play an important role in encouraging their parents/grandparents to use a variety of technologies. On the other hand, with regard to the fourth condition (ability), it is important to draw attention to the fact that certain technologies pose challenges to some older people, especially those with problems of memory, vision and dexterity (McCreadie, 2010). As for the last condition (training), the purchase and use of technologies depends on the level of training offered to older people (McCreadie, 2010).
With specific reference to solutions based on the "Internet of things", the acceptance and use of these solutions depend on their limitations, which remain significant. According to Azimi et al. (2016), these solutions are not yet: a) miniaturized; b) light; c) low power; d) easy to use; e) suitable for the user to use for 24 hours and 7 days (Azimi et al., 2016). In addition, the same authors emphasize that inaccurate results (e.g., in health status monitoring) and false alarms have contributed to reducing the confidence of users and their families in the use of these solutions (Azimi et al., 2016).
A systematic review of the literature by Khosravia and Ghapanchi (2016) analysed the level of effectiveness of each category of technologies supporting older people for each problem they show. General ICTs are mainly effective in combating depression and are also (albeit to a lesser extent) effective in cases of dementia, social isolation and low well-being. In turn, robotics is effective in combating depression, promoting independent living and promoting well-being. Telemedicine is effective in combating chronic diseases and also in promoting independent living. Sensors are effective in promoting independent living, preventing falls and helping in cases of dementia. Applications for the management of medications, on the other hand, show a low efficiency in the taking of medications and, finally, video games are very effective in preventing falls. In this sense, a study conducted in the United States of America concluded that the use of iPads contributes to reducing the social isolation of elderly people, since it facilitates online contact with friends and family (Delello & McWhorter, 2017).
A study in England (Greenhalgh et al., 2013) concluded that assistive technologies met a limited set of needs of older people receiving health and long-term care, and that some devices had been abandoned and others deliberately disabled. This study also concluded that success in the use of assistive technologies depended on a "do-it-yourself" using these technologies, i.e., a pragmatic personalization resulting from an articulation between several devices, by older people or others. This shows, according to the authors of the study, that the standardisation of technological solutions often clashes with the specificities and singularities of the needs of the elderly. In this line of thought, the authors of the study leave the following recommendation to the creators of assistive technologies for the elderly: "technology providers need to move beyond the goal of representing technology users informationally (e.g. as biometric data) to providing flexible components from which individuals and their carers can 'think with things' to improve the situated, lived experience of multimorbidity". (Greenhalgh et al., 2013: 86).
In addition to the study just described, several literature reviews (e.g., Brandt et al., 2011; Cruz et al., 2014; McLean et al., 2013; Ward et al., 2012) have shown, on the one hand, that empirical evidence on the effectiveness of assistive technologies in promoting the well-being of their consumers is inconclusive. On the other hand, they have drawn attention to the following: assuming that certain technologies are potentially effective, their introduction into the daily routine of health care and long-term care poses numerous challenges in economic, technical, operational and ethical terms. With this in mind, in a study on the quality of assistive technologies for older people, Greenhalgh and his collaborators (2015b: 13-14) developed a set of guidelines and principles for the development of these technologies, which they called "ARCHIE framework": "First, both technology designers and assistive technology services need to shift their focus from developing, installing and monitoring a particular technology to a more dynamic focus on performance (supporting technologies- in-use). Second, those who commission telehealth and telecare services need to shift from standardized care packages (the one-size-fits-all 'home care contract') to personalised solutions (that is, they should require providers to adapt products and services to the patient's needs and preferences). Thirdly, industry (perhaps supported by relevant incentives by government) must drive a shift in the design model from 'walled garden' branded solutions (packages that are designed to interface only with a particular manufacturer's products) to components that are designed to be combined creatively by people making their own ad hoc solutions to one-off challenges, and which must, therefore, be inter-operable across multiple devices and platforms. Technological advances are important, but they must be underpinned by a robustly user-centred approach to technology design and service delivery by industry and service providers."
3. Research on technologies in the most advanced stages of life: contributions and limitations
This section analyses the main inputs and limitations of Assisted Living Technology studies, studies on the effectiveness of technologies and studies on solutions based on the "Internet of Things".
Beginning with studies on assisted living technologies, Greenhalgh and colleagues (2016) suggest that these can be divided into three overlapping generations: a) generation of technical design studies, in which researchers, especially in the area of informatics, tried to demonstrate that the technologies work under controlled conditions; b) generation of experimental studies, mainly randomised controlled trials, which were designed and carried out mainly by doctors, in which the impact of the technologies on the health conditions of the patients was measured; c) generation of qualitative studies on the experiences and perspectives of the users, which were carried out mainly by social scientists and health professionals. These latter studies highlighted the uniqueness of individual needs and aspirations, the importance of assessing the social and material contexts into which technologies are introduced, the problems posed by the standardization of technologies, the possible negative effects of technologies, and the crucial role played by family members and formal caregivers in the adaptation and support of installed technologies.
Greenhalgh et al (2016) argue that despite the contributions of these studies, they have several limitations. Among the various constraints identified, they highlight the fact that these studies neglect the socio-technical system, which is complex and in which technologies and their users are embedded. From this point of view, they argue that it is necessary to initiate a fourth generation of studies on assisted living technologies, which should have five essential characteristics: a) unlike the previous three generations of studies, which were predominantly monodisciplinary, the fourth generation should be interdisciplinary; b) it should encompass complexity, i.e. it should conceive of people and technologies "(...) as linked in dynamic, networked and potentially unstable systems made up of multiple interacting stakeholders" (p.). 2); c) should adopt recursion, which translates into the idea that human (micro) action is simultaneously influenced by, and influences the family and organizational context (meso), as well as society as a whole (macro); d) should take into account the ecological paradigm, which questions the notion that specific solutions are easily transferable to other contexts, as well as the idea of a linear link between research and the application of conclusions; e) it must be critical (in the sociological sense of the term), in the sense that the complex systems in which assisted living technologies are inserted are potentially spaces of power struggle.
As for studies on the efficacy of technologies, Khosravia and Ghapanchi (2016) stress that these studies are poor in theory and based on small samples. Finally, studies on 'internet of things' solutions for older people do not sufficiently address the everyday needs of older people (Azimi et al., 2016). In other words, these studies do not yet focus sufficiently on the user/consumer (user-centered research).
1 Also known as assisted living technology.
2 The proposal of the notion of network of practice positions was inspired by the Actor Network Theory of Bruno Latour (1992).
Azimi, I., Rahmani, A.M., Liljeberg, P. and Tenhunen, H. (2016). Internet of things for remote elderly monitoring: a study from user-centered perspective. Journal of Ambient Intelligence and Humanized Computing, 8(2): 273–289.
Barlow, J., Bayer, S. and Curry, R. (2005). Flexible Homes, Flexible Care, Inflexible Organisations? The Role of Telecare in Supporting Independence. Housing Studies, 20(3): 441-456. DOI: 10.1080/02673030500062467
Bettio, F. and Verashchagina, A. (2010). Long-Term Care for the elderly. Provisions and providers in 33 European countries, EU Expert Group on Gender and Employment, Roma: Fondazione G. Brodolini.
Bourdieu, P. (1977). Outline of a theory of practice. Cambridge, UK: Cambridge University Press.
Brandt, A., Samuelsson, K., Töytäri, O. and Salminen, A.L. (2011). Activity and participation, quality of life and user satisfaction outcomes of environmental control systems and smart home technology: a systematic review. Disability and Rehabilitation Assistive Technology, 6(3):189–206.
Charness, N. (2003). Commentary: access, motivation, ability, design, and training: necessary conditions for older adults success with technology. In Charness, N. and Schaie, K. W. (eds.), Impact of Technology on Successful Aging. New York: Springer, pp. 15-27.
Colombo, F. et al. (2011). Help Wanted? Providing and Paying for Long-Term Care, OECD Health Policy Studies, OECD Publishing. http://dx.doi.org/10.1787/9789264097759-en
Cruz, J., Brooks, D., Marques, A. (2014). Home telemonitoring effectiveness in COPD: a systematic review. International Journal of Clinical Practice, 68(3): 369–78.
DeJonge, K., Taler, G. and Boling, P. (2009). Independence at home: Community-based care for older adults with severe chronic illness. Clinics in Geriatric Medicine, 25 (1): 155–169.
Delello, J.A., McWhorter, R.R. (2017). Reducing the Digital Divide: Connecting Older Adults to iPad Technology. Journal of Applied Gerontology, 36(1): 3-28.
Emery, D., Hayes, B.J and Cowan, A.M. (2002). Telecare delivery of health and social care information. Health Informatics Journal, 8: 29-33.
Fujisawa, R. and F. Colombo (2009). The Long-Term Care Workforce: Overview and Strategies to Adapt Supply to a Growing Demand, OECD Health Working Papers, No. 44, OECD Publishing. http://dx.doi.org/10.1787/225350638472
Gilleard, C., Higgs, P. (2008). Internet use and the digital divide in the English longitudinal study of ageing. European Journal of Ageing, 5(3): 233. doi: 10.1007/s10433-008-0083-7.
Golant, S.M. (2017). A theoretical model to explain the smart technology adoption behaviors of elder consumers (Elderadopt). Journal of Aging Studies, 42: 56-73. doi: 10.1016/j.jaging.2017.07.003.
Greenhalgh, T. and Stones, R. (2010). Theorising big IT programmes in healthcare: strong structuration theory meets actor-network theory. Social Science & Medicine, 70(9): 1285-94. doi: 10.1016/j.socscimed.2009.12.034.
Greenhalgh, T., Procter, R., Wherton, J., Sugarhood, P., Hinder, S., Rouncefield, M. (2015). BMC Medicine, 23; 13:91. doi: 10.1186/s12916-015- 0279-6.
Greenhalgh, T., Shaw, S., Wherton, J., Hughes, G., Lynch, J., A'Court, C., Hinder, S., Fahy, N., Byrne, E., Finlayson, A., Sorell, T., Procter, R., Stones, R. (2016). SCALS: a fourth-generation study of assisted living technologies in their organisational, social, political and policy context. BMJ Open, 15;6(2): e010208. doi: 10.1136/bmjopen-2015-010208.
Greenhalgh, T., Wherton, J., Papoutsi, C., Lynch, J., Hughes, G., A'Court, C., Hinder, S., Fahy, N., Procter, R., Shaw, S. (2017). Beyond Adoption: A New Framework for Theorizing and Evaluating Nonadoption, Abandonment, and Challenges to the Scale-Up, Spread, and Sustainability of Health and Care Technologies. Journal of Medical Internet Research, 19(11): e367. doi: 10.2196/jmir.8775
Greenhalgh, T., Wherton, J., Sugarhood, P., Hinder, S., Procter, R., Stones. R. (2013). What matters to older people with assisted living needs? A phenomenological analysis of the use and non-use of telehealth and telecare. Social Science & Medicine, 93: 86-94. doi: 10.1016/j.socscimed.
Khosravi, P., Ghapanchi, A.H. (2016). Investigating the effectiveness of technologies applied to assistseniors: A systematic literature review. International Journal of Medical Informatics, 85(1): 17-26. doi: 10.1016/j.ijmedinf.2015.05.014
Lafortune, G. and G. Balestat (2007). Trends in Severe Disability Among Elderly People: Assessing the Evidence in 12 OECD Countries and the Future Implications, OECD Health Working Papers, No. 26, OECD Publishing, Paris, http://dx.doi.org/10.1787/217072070078.
Lansley, P., McCreadie, C. and Tinker, A. (2004). Can adapting the homes of older people and providing Assistive Technology py its way? Age and Ageing, 33(6): 571-6.
Latour, B. (1992). Reassembling the social: An introduction to actor-network- theory. Oxford: Oxford University Press.
Marin, B., Leichsenring, K., Rodrigues, R. and Huber, M. (2009). Who cares? Care coordination and cooperation to enhance quality in elderly care in the European Union, Conference on Healthy and Dignified Ageing, Stockholm, 15- 16 September 2009. http://www.se2009.eu/polopoly_fs/1.13915!menu/standard/file/Discussion%20 Paper-Who%20Cares.pdf
McCreadie, C. (2004). Devices and desires: identifying the acceptability of assistive technology to older people. In keates, S., Clarkson, J., Langdon, P. and Robinson, P. (eds.), Designing a More Inclusive World. London: Springer, pp. 91-100.
McCreadie, C. (2010). Technology and Older People. In Dannefer, D. and Phillipson, C. (Eds.), The Sage Handbook of Social Gerontology. Los Angeles: Sage, pp.607-617.
McLean, S., Sheikh, A., Cresswell, K., Nurmatov, U., Mukherjee, M., Hemmi, A., Pagliari, C. (2013). The impact of telehealthcare on the quality and safety of care: a systematic overview. PLoS ONE, 8: e71238.
Mostashari, F. (2011). Aging in place: The national broadband plan and bringing health care technology home. Technical report. Statement to the Senate Special Committee on Aging and the United States House of Representatives by the Senior Advisor to the Office of the National Coordinator for Health IT. Retrieved from http://www.hhs.gov/asl/testify/2010/04/t20100422e.html
OECD (2011). Health at a Glance 2011: OECD Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/health_glance-2011-en.
Olphert, W. and Damodaran, L. (2013). Older people and digital disengagement: a fourth digital divide? Gerontology, 59(6): 564-70. doi: 10.1159/000353630.
Padilla, D. (2008). Tecnologías para mayores. [Tecnologies for the Elderly], Universitas Psychologica [online]. 7(3): 883–894.
Pinto-Bruno, A.C, García-Casal, J.A., Csipke, E., Jenaro-Río, C. and Franco- Martín, M. (2017). ICT-based applications to improve social health and social participation in older adults with dementia. A systematic literature review. Aging & Mental Health, 21(1):58-65. DOI: 10.1080/13607863.2016.1262818
Selwyn, N. (2004). The information aged: a qualitative study of older adults’ use of information and communications technology. Journal of Aging Studies, 18: 369-84.
Sixsmith, A. and Sixsmith, J. (2008). Ageing in place in the United Kingdom. Ageing International, 32(3): 219-35.
Tan, K.S.Y. and Chan, C.M.L. (2018). Unequal access: Applying Bourdieu's practice theory to illuminate the challenges of ICT use among senior citizens in Singapore. Journal of Aging Studies, 47: 123-131. doi: 10.1016/j.jaging.2018.04.002.
Vassli, L.T and Farshchian, B.A. (2017). Acceptance of Health-Related ICT among Elderly People Living in the Community: A Systematic Review of Qualitative Evidence, International Journal of Human–Computer Interaction. DOI: 10.1080/10447318.2017.1328024
Venkatesh, V., Morris, M.G., Davis, G.B. and Davis, F.D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3): 425–478.
Venkatesh, V., Thong, J.Y.L. and Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1): 157–178.
Ward, G., Holliday, N., Fielden, S. and Williams, S. (2012). Fall detectors: a review of the literature. Journal of Assistive Technologies, 6: 202–15.
Wright, F., McCreadie, C. and Tinker, A. (2005). Improving the Provision of Information about Assistive Technology for Older People. London: Institute of Gerontology, King’s College London.