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contain quantitative as well as qualitative data) of how human actors made it happen despite all the uncertainties, contingencies, inconsistencies, material challenges and micropolitical hiccups – and how the goals changed (perhaps quite appropriately) as the project unfolded and contextual influences changed [8]. 1.3. Domains of the NASSS framework Against this background of complexity in health systems, let us now consider the different domains of the NASSS framework, shown in Figure 1, and the different kinds of complexity that can occur. Broadly speaking, such complexity can be logistical (relating to the scale, scope and different inter-related sub-systems involved) or socio- political (relating to personal, interpersonal or inter-organisational issues such as differences in values or conflicts of interest). Domain 1 in the NASSS framework is the condition (perhaps an illness, such as diabetes, or risk state, such as increased tendency to falls). The human body is of course a complex system, as is the family and community in which the sick person is cared for. The most obvious theoretical influences on this domain are biomedical and epidemiological theories of disease (which often but not always allow prediction of how the condition and its co-morbidities will progress over time) and pharmacological theories of how drugs work and interact. In addition, a number of theories of illness (that is, disease as experienced by the patient) are relevant here. Sociological framings depict illness as a unique personal (and family) experience which may involve stigma, biographical disruption, loss of status, reduced income and a heroic struggle to retain dignity, rebuild identity and live a moral life in the face of adversity [9, 10]. Political economy framings depict illness as the result of poverty or maldistribution of power in society (for example, Julian Tudor Hart’s Inverse Care Law states that people most in need of health care are least likely to seek it or receive it) [11]. Complexity in Domain 1 may occur, for example, when the condition is metabolically volatile (e.g. sepsis), inherently unstable (e.g. alcohol dependency), poorly described or understood (e.g. a newly described syndrome), associated with multiple co- morbidities and polypharmacy (for example, in older people) or influenced by socio- economic or cultural factors (including poverty and material circumstances; limited access to healthcare; low health literacy, system literacy or digital literacy; cultural traditions and norms; social exclusion). For an overview of the kinds of complexity that affect the condition or illness, see this review [12]. Domain 2 is the technology, for which a number of underpinning theories covered in separate chapters elsewhere in this text book may be relevant, including socio-technical systems theories2, technology adoption theories3, normalisation process theory4 and user-centred design theories5. In our own empirical work applying NASSS to patient- facing technologies (e.g. designed to support self-care in the home), we have drawn particularly on Jeanette Pols’ theory interpretation of actor-network theory, which 2 See Chapter 7, “Distributed Cognition: understanding complex sociotechnical informatics” and Chapter 8, “Using Actor-Network Theory to study health information technology interventions”. 3 See Chapter 6, “Technology Acceptance Models in health informatics: TAM and UTAUT”. 4 See Chapter 15, “Implementing and embedding health informatics systems – understanding organisational behaviour change using Normalization Process Theory (NPT)”. 5 See Chapter 5, “Linking Activity Theory with User Centred Design: a human computer interaction framework for the design and evaluation of mHealth interventions”. T.GreenhalghandS.Abimbola /TheNASSSFramework–ASynthesisofMultipleTheories196