Equipoise and role conflict have been previously identified as important factors in professionals’ engagement with trials, inducing behaviours which can impact on recruitment. We explored these phenomena as potential explanations for the low levels of involvement of teenagers and young adults (TYA) with cancer in clinical trials in oncology.We report findings from interviews with 30 purposively sampled direct-care professionals involved in delivering cancer care and/or facilitating clinical trials in Scotland. We undertook qualitative descriptive analysis, focussed on identifying key issues and themes.Interviewees largely identified as clinician–researchers and portrayed oncology as a specialty in which research was integral to care. They saw their primary responsibility as ensuring patients received the best treatment, but asserted that, in general, trials provided a vehicle for optimal care. Role conflict in its traditional form was rarely evident; however, other tensions were manifest. Professionals found the significant time costs of delivering trials difficult to reconcile with the increasing pressures on clinical services. They felt a responsibility to make prudent choices about the trials with which to engage. Guided by utilitarian principles, these choices were oriented towards benefiting the largest number of patients. This favoured trials in high volume diseases; as TYA tend to have rarer forms of cancer, professionals’ support for—and TYA’s access to—relevant trials was, by default, more limited.Neither lack of individual equipoise nor experiences of traditional forms of role conflict accounted for the low levels of involvement of TYA with cancer in clinical trials. However, prominent tensions around the management of scarce resources provided an alternative explanation for TYA’s limited access to cancer trials. The prevailing approach to decision-making about whether and which trials to support was recognised as contributing to inequalities in access and care. Professionals’ choices, however, were made in the context of scarcity, and structured by incentives and sanctions understood by them as signalling governmental priorities. A franker discussion of the extent and distribution of the costs and benefits of trials work is needed, for change to be achieved. Clinical trials have played a definitive role in medical progress, particularly in the field of cancer care . ImportaWhilst clinical trials are powerful tools for advancing knowledge and patient care, their successful delivery is difficult, with recruitment challenges affecting timely completion of a significant proportion of studies , 7. A grClinical equipoise  is consiUnderpinning these behaviours is a concern that participation would not be in patients’ best interests. The care obligations at the heart of the clinician-patient relationship are deeply felt, and whilst clinical equipoise may provide ethical justification for allocation of patients to treatment according to a trial protocol, individual uncertainty will almost inevitably leave clinicians feeling conflicted. Broader tensions between goals and responsibilities relating on the one hand to research or scientific endeavours, most particularly clinical trials, and on the other to the care of  patients, have been conceptualised as manifestations of role conflict –24. RoleAs part of a wider study of barriers (and facilitators) to TYA’s involvement in cancer trials, we interviewed health professionals involved in delivering cancer care and/or facilitating clinical trials. In keeping with the literature, we anticipated that a lack of equipoise  and/or role conflict might offer explanatory vehicles for the low levels of involvement of TYA in cancer trials. Our findings did not support this. In particular, they (our findings) did not show role conflict, as currently understood and employed in the literature, to account for limited trial participation by TYA. However, as we explain below, they revealed other new and highly significant tensions, with ultimately similar consequences for TYA’s involvement in trials.We outline our methods—and findings—broadly in accordance with the consolidated criteria for reporting qualitative studies (COREQ) . The useWe undertook a qualitative study, involving one-off semi-structured interviews with direct care and other professionals, patients and family caregivers . The study was characterised by an emergent, inductive design, purposive sampling and an iterative approach to data collection and analysis . This itWe conducted our study in Scotland. Health is a devolved matter, with legislation relevant to the National Health Service (NHS) in Scotland made by the Scottish Parliament. NHS Scotland is legally and financially independent from NHS England and has a distinct organisational framework. Fourteen regional ‘Health Boards’ plan, commission and deliver services, in line with the Scottish Government’s priorities. Major and specialist facilities are concentrated in the four largest health boards, although more than 20 hospitals in Scotland provide cancer care. Research infrastructure is provided by NHS Research Scotland (NRS), which takes its strategic direction from the Chief Scientist Office (CSO), an arm of the Scottish Government (and the funder of this research), and the four largest health boards.Our approach to sampling was purposive and focussed on construction of a sample reflecting the diversity of relevant experiences and perspectives. Hence, we set out to recruit medical and nursing staff from different sub-specialties, types of service, hospitals and health boards . In light of the issues emerging in the first phase of the interviews, which related substantially to what might be termed structural factors , we later sought to recruit professionals whose roles gave them particular insight into those matters. Initially, potential research participants were identified by clinical members of the research team. As sampling progressed, help to identify professionals with particular characteristics and/or experiences was sought from advisory group members and other clinical colleagues. We also invited interviewees to suggest colleagues with whom we might usefully speak. Interviewees were not asked to introduce us to their colleagues and were not informed whether their suggestions were followed up.Approaches to potential interviewees were made in writing, either by the Chief Investigator (AJ) or the project researcher (RH), and were followed up by the latter. All potential interviewees were given detailed participant information sheets and invited to opt-in by replying directly to the project researcher. Approximately half of those approached agreed to take part. Where reasons were given for declining participation, these typically related to pressures of work and/or the small number of TYA patients seen. We discontinued recruitment once the team was in agreement that sampling ambitions had been satisfied and data saturation had been reached .Data was collected between December 2017 and August 2018. Interviewees were given the option of either a face-to-face or telephone interview, with the former (16/30) typically taking place in the interviewee’s own office or a private meeting room. These were conducted by the project researcher (RH), a social scientist with prior experience of undertaking qualitative health research in haemato-oncology and other clinical areas.guide should be considered precisely that, and not as a script. Interviews typically lasted 45–60 min. All were audio-recorded and then transcribed verbatim. After anonymization had been fully confirmed, transcripts were imported into the specialist data management software, NVivo (Version) 11 .Interviews were semi-structured, loosely following a topic guide outlined in Table We undertook qualitative descriptive analysis, with a focus on producing rich, ‘minimally theorized’ descriptions of views and experiences , 32. AftWe interviewed 30 direct care professionals whose role(s) involved delivering cancer care and/or facilitating clinical trials in Scotland. Participant characteristics are detailed further in Table In the sections that follow, we report how (1) these professionals largely identified as clinician–researchers and offered little evidence of experiencing role conflict in its traditional form, but (2) other powerful tensions had emerged around the use of scarce resources. Quotes are attributed to participants who are distinguished using unique alphanumeric codes, the initial letters of which provide information on their role: DC-C/N/O (Direct Care-Consultant/Nursing/Other). No relevant differences in perspective by role/staff group emerged.‘it’s part of core work… you can’t do oncology without doing research, it’s just… part of our job… just about every oncologist is involved in clinical trials… and if you’re not, you’ve got the question, why not?’ (DC-C-11).‘in oncology, (research) is integral to clinical care… that’s what makes it such an interesting speciality, everyone’s involved… (and) it’s very integrated into clinical practice.’ (DC-C-12).Interviewees with direct care roles strongly identified as clinician–researchers, with accounts emphasizing the close integration between research and care in contemporary oncology. They portrayed involvement in research, particularly clinical trials, as an integral part of their work; something which was the norm, rather than the exception, for professionals within their specialism:Clinicians described being introduced to clinical trials work early in their medical career and talked of taking on more responsibilities for trials work as they gained experience and status in oncology. Current oncology trainees, they said, were being prepared to take on similar responsibilities in the future. For example, as part of the medical oncology curriculum, trainees were all expected to undertake ‘GCP’  training, and to be involved in recruiting patients to trials, as well as providing follow-up care.‘you can see the development of drugs over the course of the years… you can actually see that with, you know, with your own eyes… that’s motivational, you know, to being positive about trials, and taking part in them.’ (DC-N-10).Some nursing interviewees were in research/trials nurse roles at the time of interview; others were not, but had held such posts in the past. Several recalled involvement, as staff nurses, in the care of cancer patients treated through clinical trials. This, they said, had given them too a strong sense of the importance of trials work and its contribution to improving cancer care:‘if we don’t do clinical trials, we will make decisions… not based on the best evidence… we have to do clinical trials to actually improve outcomes, but also to protect patients from drugs or interventions that might actually not be as effective as what’s already available.’ (DC-C-26).Both clinicians’ and nurses’ accounts gave a strong impression of a trial culture, underpinned by a commitment to evidence-based medicine and with a focus on improvement, patient safety and the provision of the highest quality of care:‘Trials make people think… (be) adaptable and willing to change for the better… that’s a culture that… taking part in clinical trials develops, or encourages.’ (DC-N-10).‘we also know that… being part of research is quite good from a quality control point of view… your patient care… is being compared by the trials monitoring committee, it’s almost like… intellectual peer review… of practice.’ (DC-C-16).Significantly, clinical trials were viewed not only as delivering benefits for future patients, but also as profiting current patients. Interviewees largely shared the opinion that research-active organisations achieved better results for patients  and that patients who took part in trials had superior outcomes to those who did not. Interviewees acknowledged some uncertainty as to why patients in centres that delivered trials did better. They offered explanations concerning, inter alia, the culture or outlook developed by involvement in trials, and the value of external scrutiny of practice:‘there’s… evidence… that patients who participate in trials do better, irrespective of whether they’ve got the trial treatment.’ (DC-C-13).A significant proportion of interviewees referred to ‘evidence’ suggesting that patients enrolled in trials had better outcomes. Again, interviewees acknowledged it was not yet entirely clear why trial-enrolled patients did better. They stressed that new treatments or new ways of administering treatment did not always outperform standard care and cited ‘research’ showing that control arm patients also tended to have better outcomes than non-enrolled peers:‘there’s quite a lot of evidence to say that patients in clinical trials get better clinical care, just ‘cause they are seen more frequently, and so you’re much more likely to pick up on symptoms, and problems, at an earlier stage. So for individuals, it’s always important to stress that the benefit’s not necessarily from the drug, or the technique, because we don’t know yet if that’s going to make any difference, but we know that generally speaking, because of the more intensive care provided for people in trials for collecting all the data, that translates into sort of better clinical care.’ (DC-C-5).Interviewees suggested that the explanation was probably ‘multi-factorial’ (DC-C-11), identifying a series of factors or mechanisms for what is sometimes referred to in the literature as ‘the trial effect’ . These rWhatever the explanation, treatment through a trial was, in principle, viewed as giving patients access to the best possible care. As such, our interviewees gave little impression of being conflicted in the performance of their clinical care and research responsibilities; in contrast, they saw trials as a vehicle through which they could offer their patients optimal clinical care.in principle, such a trial might still expose patients to a new agent that was inferior to current care. However, several interviewees took pains to note that ‘new’ did not mean entirely unknown, one commenting as follows:‘in (this sort of) trial you feel you’ve come far down the road enough, for, you know, the “new” drug not to be a worse drug. It (may) not be better, but there are reasonable data to say… it shouldn’t be worse.’ (DC-C-7).Accounting further for the apparent lack of conflict between care and research, interviewees reflected on the characteristics of the trials with which they were involved, and the distinctive nature of those of most relevance to TYA patients. Although some direct care interviewees reported involvement in early phase trials, most interviewees and accounts focussed on ‘Phase 3’  trials of first-line care. These are the sorts of trials involving the largest number of patients and, archetypally, compare two quite distinct drugs, procedures or technologies, one of which is new. The trials described by our interviewees appeared notable for their complexity, comparing differences in protocols which could involve multiple treatment modalities. Interviewees acknowledged that, ‘Our process for taking on trials, and the way that our consultants work… we’re quite confident that we’re not offering things to people that wouldn’t be good for them.’ (DC-N-10).They stressed that patient safety was the prime consideration in the design of trials and that all were very carefully scrutinised before initiation. Though laborious to navigate, regulatory and review processes functioned both to minimise harm and to reassure clinicians that they were not exposing their patients to inappropriate risks:new treatment.’ (DC-C-17).‘Some of the studies… are actually looking at what other medicines we can take out, or lower the dose of, to cut down on side effects, so… trials are not necessarily about ‘Trials (can) offer an opportunity to access medicines that we otherwise wouldn’t be able to… (But) a lot of our trials… are not like that though… a lot of our trials involve making minor modifications to… standard treatments.’ (DC-O-24).Moreover, interviewees described trials in the disease areas of most relevance to TYA patients  as commonly exploring different ways of using familiar treatments, sometimes using ‘different treatment approaches using the same drug’ (DC-C-9), rather than investigating the effects of new ones:‘building on what our, our gold standard, or our best available therapy is, and we’re trying to tweak the treatment slightly to improve outcomes, or add in a new treatment, or change the doses, or change the scheduling of it… (to) further improve the treatment… to improve the outcomes.’ (DC-C-17).As the quotes above suggest, interviewees portrayed these trials, which seldom had commercial funding, as often looking at quite subtle modifications to care, for example, making adjustments to treatment combinations, order, dosage and/or frequencies. Interviewees talked of attending to ‘the finer details of the treatment… trying to clarify aspects of that treatment’ (DC-C-3). One explained how they proceeded:‘in both haematology and breast cancer… we’ve got such good outcomes really, that it’s all about trying now to look at, how little do we need to do to get the same outcomes, to keep the quality of life? So there’s quite a lot of work about how much can we pull back… and still achieve the same results… The younger population, those people are hopefully going to be cured, and then live till they’re 80, so you don’t want them to live with the side effects of the chemotherapy or radiotherapy’ (DC-C-15).Priorities varied between disease areas / tumour types, but outcomes of interest included both survival and (short and longer-term) toxicities. The latter was viewed as of particular significance to TYA patients:‘I’m fairly enthusiastic about putting my acute leukaemia patients in trials… because… they get a fairly good deal in these trials and the risk-benefits… are pretty good.’ (DC-C-7).Such trials were framed as exposing TYA patients to worthwhile benefits and quite limited risks:‘the basis for the trial is that we don’t know which one’s going to be better, or better tolerated… that’s the nature of a Phase 3 trial, we can’t run it unless we think there’s genuine uncertainly about which one is best.  that difference is much less apparent to anybody, even (those) running the trial. It’s less clear what, whether you would have been better off, if you had the other bit.’ (DC-C-3).Furthermore, the nature of these trials meant that the superiority of any particular arm was exceedingly difficult to pre-judge:‘most people in, in oncology are NHS doctors… who believe in research, who do research, but whose first commitment is to the NHS service.’ (DC-C-11).‘although they are interested in research, and involved, and want to... be involved, they have a clinical workload… real patients, and real people, that have to be dealt with.’ (DC-O-30).Whilst interviewees expressed a deep commitment to research and saw it as an integral part of their responsibilities, most were employed primarily to deliver clinical services:‘in adult solid tumour oncology, we’ve had a severe shortage of staff… across the UK. So workload has been a huge issue…’ (DC-C-25).Many talked of growing pressures on core services: clinician and nursing time, pharmacy, radiology/radiotherapy services and laboratory staff and facilities. Certain fields (solid tumour oncology), services (radiology), and health boards  were suggested as facing particular or persistent challenges:‘we… use (City) labs for a lot of things anyway… that’s standard… if there’s extra tests… that can be an issue.’ (DC-N-22).Interviewees from one health board reported longstanding difficulties with clinical staffing, with vacant consultant posts leaving them heavily reliant upon locums. Meanwhile, colleagues in another health board described their pharmacy and radiology services as struggling to deliver standard care. They relied on their larger neighbours for some work related to routine clinical services:These pressures made the costs associated with undertaking trials, in particular staff time, increasingly hard to absorb. Although trials were framed by some interviewees as a potentially useful source of income, they were more frequently construed as drawing critical resources away from routine care. This may in part be reflective of the source and levels of funding for the TYA-relevant trials around which conversations revolved. All current and recent trials of clear relevance to TYA with cancer which featured in interviews were non-commercial, i.e. funded by charities or through (European) grant programmes.Notwithstanding their commitment to participating in such research, many interviewees talked at length of the significant monetary and other (e.g. in-kind) costs associated with establishing, opening and maintaining these trials: ‘trials are demanding in time, they’re demanding in resource…’ (DC-C-16). They drew attention to the substantial time costs associated with both opening and delivering a trial. These costs included trial administration, recruitment, delivery of complex trial interventions, data collection and reporting.‘Seven or eight years ago, you would maybe see one or two protocol amendments in the lifetime of a study. Now you’re seeing two or three a year, it’s out of control, there’s more protocol amendments than patients on half our studies. And staying on top of that is extremely difficult.’ (DC-O-9).The demands associated with trial administration received particular attention and were framed both as significant and expanding. An experienced clinician remarked how, over their professional lifetime, they had ‘ballooned, absolutely ballooned’ (DC-C-25). Comments were also made that whilst non-commercial trials used to be more straightforward to administer, they were now expected to meet the same regulatory and reporting requirements as commercial trials—but without equivalent resources and infrastructure. Opening a trial was portrayed as extremely laborious and, critically, due to the requirement to maintain and update documentation to reflect (increasingly frequent) amendments, the ongoing demands on staff time were also considerable:‘if we do a trial where we’re going to recruit 10 patients, then obviously the amount of work that I have to do as a PI… and some of the nurses have to do – in terms of bureaucracy – is actually pretty much the same as if we were to do a trial where we might only recruit one.’ (DC-C-25).Interviewees emphasised that, in large part, these administrative demands bore no relationship to the scale of recruitment to the trial. Due to broadly equivalent costs of activation, set-up and maintenance, trials where recruitment might be expected to be limited (often the case with those in disease areas relevant to TYA) could prove as much a drain on resources as those with much higher levels of recruitment:which trials to engage with and fight for support for:‘as a department, we’ve got limited research resource, so we… focus on trials… (with) a chance of benefiting our patients. Focus our nursing and data management resource into that.’ (DC-C-11).Hence, in this context of high demand and scarce resources, accounts suggest that trials were in competition not only with clinical services, but also with each other. Interviewees drew attention to the ‘finite’ nature of resources, the ‘opportunity cost’ of trials work, and the consequential requirement to make prudent choices about ‘it’s about numbers, how many people do you need to get into a trial in order to make the trial… worth the resource…?’ (DC-C-3).Pressed to explain further how decisions were made whether to engage with (i.e. open) a particular trial or not, interviewees talked about assessing if a trial was ‘worthwhile’. This appeared to mean a range of different things, prominent amongst which was recruitment potential:‘Not to beat around the bush, we get very little money, until we recruit patients. You know, most of the incentivisation… bean-counting, is related to the numbers of recruits, not to the numbers of… studies. And so, you know, those are resources which, we’re putting in, where we may get nothing back, and would frankly be better directed to something where we’re gonna get something back.’ (DC-C-28).Professionals appeared to evaluate trial opportunities according to the principles of utilitarianism, which, at its simplest, is an economic philosophy oriented towards achieving the greatest good for the greatest number of people. Interviewees acknowledged that the prevailing value system privileged high volume diseases . As one interviewee put it, ‘the big tumour types… dominate’ (DC-C-11). Accounts suggest that the system of rewards and penalties for trials work established by the Scottish Government (CSO) had encouraged and embedded such an approach. Its use of recruitment figures as the central metric incentivised trials in those centres, disease types, sub-types and phases where there was greatest potential to recruit:‘number of recruits to studies… that’s a slightly lazy way of trying to appreciate the quality and quantity of patient benefits… if you run a study on relatively few patients, but actually that’s a novel, good intervention, that would be a great benefit… the health impact may be… more significant that a study that runs on 100 patients which provides relatively minor, additional health benefits… Yet the 100-patient (study) would win, in the eyes of the Government.’ (DC-C-27).Some interviewees questioned the rationale of the contemporary rewards system, musing that:‘(be)cause the numbers are small… staff are kind of dis-incentivised… A lot of people just say, I just can’t be bothered with that if I’m only gonna recruit, you know, one patient in six months or something, why the hell do I wanna do that? I’ve got other things to do.’ (DC-C-25).Ultimately, and notwithstanding ambitions to have trials available for as many different patient groups as possible, there was widespread recognition that, in reality, only a minority of patients aged 16+ had access to care through a trial. One interviewee (DC-C-20) put it very bluntly: ‘for the majority of patients, there isn’t a trial.’ Significantly, however, the prevailing logic and rewards metric led to patterned inequalities in access to trials, powerfully dis-incentivising the opening of trials relating to rarer cancers such as those with which TYA typically presented:‘There is a national trial for rhabdos, but we haven’t opened it in, the adult site, because it’s a very complicated trial, and we would probably only get one patient every two or three years… ‘cause it only goes up to (age) 21, I think’ (DC-C-3).‘there are some trials for very rare cancers… quite a few that are relevant to this group (TYA), where we have had to just make the decision, we don’t have enough resources to open this trial that we may recruit one, or zero patients (to) over the lifetime of the trial… that’s a big problem… for this group of patients.’ (DC-C-18).Some interviewees highlighted a wider lack of trials in rare tumours, framing pharmaceutical companies as having limited interest in developing and trialling new treatments for such diseases . Others questioned the extent to which smaller centres, outside London, were given an opportunity to participate where such trials were established. Many, however, explicitly acknowledged the role—and consequences—of local decision-making:‘we’ve got about 160 trials open… (but) there’s probably about half a dozen… which would include diseases which were relevant (to TYA).’ (DC-C-28).It seems TYA patients might not be deprived of trial opportunities by their age per se, but by their tendency to present with tumours uncommon in the wider adult population:A key finding of our research is that interviewees identified strongly as clinician–researchers and portrayed oncology as a specialty in which research was integral to care. Examples of role conflict in its traditional form –24 were These findings do not fit entirely easily with the existing literature. Traditionally, the roles of clinician and researcher have been understood to be fundamentally distinct and inherently conflicting. Attention has been and continues to be drawn to differences in the goals, practices, responsibilities, obligations, risks and ethical frameworks for research and care –24, 26. That said, recent years have seen the publication of a growing body of work which challenges the conceptualisation of care and research as unerringly distinct and conflicting. That work suggests a more permeable boundary between research and care, at least in some technical specialities –39. KeatInterestingly, our data showed professionals to be overwhelmingly in  equipoise. We surmise that the nature of TYA-relevant trials may be significant in this. Our data suggest that whilst TYA-relevant trials may involve new treatments, they frequently compare relatively similar regimens, involving differential delivery of familiar treatments. Where differences between treatment arms are subtle, it would seem less likely that professionals might hold strong beliefs regarding the likelihood of particular patients or patient groups benefiting more from one treatment (arm) than another. Arguably, in such cases, the potential for individual uncertainty about involving one’s patients in such a trial—and all the concerns and conflicts arising from or fuelled by this—would be reduced.Although traditional forms of role conflict were largely absent from our data, powerful tensions, or conflicts, were prominent in relation to resource management. Highlighting a backdrop of fiscal crisis, or at least constraint, our interviewees portrayed themselves as having secondary, but nonetheless significant, roles as custodians of scarce resources. They indicated acute awareness of the finite nature of NHS resources and a sense of duty to use these to maximum effect. Many talked at some length of their struggles to reconcile the significant costs associated with involvement in trials with the increasing pressures on their clinical service. Other authors have documented the considerable time and other costs associated with involvement in trials –44, withOur data highlight the significant and growing challenges for healthcare professionals of being involved in research—a product of the burgeoning pressure on clinical services and the increasing cost and complexity of clinical trials. These challenges meant that, notwithstanding a deep commitment to trials, only a minority of patients aged 16+) could be offered treatment through a trial. Scholars working in other jurisdictions have similarly noted that, whilst central to the specialty, in practice, relatively few (adult) oncology patients take part in trials 6+ could . Our intThe current system of rewards and penalties for trial activity appeared to reinforce a focus on ‘high volume’ diseases and to explicitly dis-incentivise more complex or uncertain (in terms of recruitment) trials work. Again, this finding is consistent with Lipsky , who argAlthough the consequences of this new form of role conflict may be similar to those of more traditional forms, the causes are quite different. As such, proposed solutions to traditional forms of role conflict, such as, for example, more or better training on the concepts central to trials and how best to communicate these to patients , would aQualitative research can improve understanding of the views, behaviours and decisions of health professionals (and their patients) , 52, 53.Accounts revealed growing tensions between the ethos of the clinician–researcher, who delivers the best care through the vehicle of trials, and the need to make pragmatic economic choices which inevitably diminish some patient groups’ access to such care. The utilitarian logic underpinning professionals’ decision-making about engagement in trials was recognised by some interviewees as having consequences for equality of care, in particular, placing patients such as TYA, who typically present with rare types of cancer, and/or who are served by smaller treatment centres, at a disadvantage. The consequences of inequality in access to trials were not explicitly explored in this study. However, denial of those benefits associated by interviewees with trial participation might reasonably be inferred. Moreover, prior research suggests that interviewees’ discomfort with the situation has strong foundations. For example, scrutiny of outcomes in TYA cancer patients has indicated that rates of clinical trial participation and improvements in survival (or lack of these) are closely associated , 4. In t


Grounded in interviews with 29 participants diagnosed with mental illness in Victoria, Australia between February and December 2014, we consider how people interpret pharmaceutical compounds beyond their desired or intended effects, and how such effects shape and transform subjectivity and their relationship with their bodies. This paper contributes to recent discussions of mental illness and medication effects, informed by feminist science studies. It emphasises the co-constitution of social, affective and material relations in the context of ‘taking’ psychotropic medication. This paper discusses three key themes as important to the phenomenology of the nexus of illness and psychotropic medication: movement, ambivalence, and sociality. Our analysis demonstrates how psychotropic drugs are  •Analyses accounts of mental illness using feminist science and technology studies.•Focus on experiences of taking psychotropic drugs and impact on subjectivity.•Moves beyond distinctions between ‘therapeutic’ and ‘side’ effects of drugs.•Unique contribution to understandings of experiences of taking psychotropic drugs. As technologies with discrete (intended) actions and effects, psychotropic medications, those that target health conditions attracting psychiatric diagnoses, act on bodies and subjectivities . Medicatmovement, ambivalence, and sociality in disclosing some of the key intra-actions by which this co-constitution transpires. Analysis of these key themes will help to reframe discussion of the subjective effects of medication in terms of complex entanglements. We follow Barad's  conceptualisation of entanglement as more than ‘to be intertwined with another’, instead considering how ‘individuals emerge through and as part of their entangled intra-relating’  repositions the mechanisms of psychotropic action as ‘drug-centred’ – a model which encourages a more substantial engagement with the ensemble of effects that drugs can have. Through this lens, the actions of psychotropic medications can be approached in a ‘much more ambivalent light’ and the effects not ‘be parcelled off into therapeutic or adverse effects as if these were distinct’ . Barad also considers that humans (and human actions) need to be approached in a similar manner. Therefore, how people are ‘prescribed’, take and engage with psychotropic drugs require a re-evaluation that considers the various entanglements of body, mind, discourse, institutions and wider society that inevitably shape consumption events.Such articulations of encounters with drugs, and the assemblages in which these encounters are sustained, rely upon an understanding of institutions, medication and individuals as How might this type of approach be applied in this empirical context? What are the intersections (and routine assemblages) of affect, bodies, expertise and pharmaceuticals, and what interests do these service? Extending Barad's work, Elizabeth A. Wilson reconceptualises depression as entanglements of moods and medications, describing the work of selective serotonin reuptake inhibitors (SSRIs) as sets of ‘intra-actions’. For Wilson , writing on the ‘side effect’ of suicidal ideation and SSRIs, this proposition suggests that ‘Suicidal ideation is not an isolated, delimited cognitive event; it is the disequilibrium of a neuro-pharmaco-ideo-affect system given voice’. Barad, Wilson and others e.g.,  provide productive of subjectivity through their promises and potential, their unexpected harms and the institutions from which they are inseparable. In developing these themes, we are presented with a system of entanglements from which isolated side effects cannot be excavated. Our paper will demonstrate how the work of pharmaceuticals (necessarily done in relation to other actors/actants) is inherently ambivalent and paradoxical, infused with conflicting relations between recipients and diffuse effects. Treatment in the form of psychotropic medication and their effects, produce complex affiliations between subjective hopes for recovery, potential therapeutic value and the possibility for disappointment or even harm, and the alleged promises of the drug (The three (entangled) thematic axes developed in this paper demonstrate how psychotropic drugs are the drug .3This paper focuses on the narratives of 29 people diagnosed with a mental illness in the Australian mental healthcare system .The interviews from which data for this article are drawn were collected by inviting participants to firstly provide unstructured accounts of their experiences of being diagnosed with mental illness. Participants could begin their stories at any point in time, with some choosing to start with first clinical encounters of diagnosis, and others earlier in childhood, thus recollecting early experiences of symptoms associated with mental illness. Following this initial narrative, participants were asked to further clarify encounters with health professionals, instances of voluntary and involuntary hospitalisation, relationships with friends and family, experiences of treatment  and ideas on personal recovery. This enabled us to identify congruities and divergences in how concepts such as subjectivity, agency and illness appeared in different contexts. Interviews lasted between one to 3 h and were conducted in a place comfortable for the participant. The interviews were audio or video recorded and transcribed verbatim. Transcripts were returned to participants to review and provide them with an opportunity to, upon reflection, remove sections of the interview text if they wished.4Transcripts were analysed in a series of iterative steps. Initially, they were read closely by the two first authors and discussed broadly in the light of existing literature. We used participants transcripts both ‘as a rich source of qualitative data’ and to observe how individual stories moved in and out of the trajectory of collective narrations , p. 101.As noted, our analysis was informed by feminist sciences studies , particuThis analysis and its theoretical framings point to the impossibility of isolating unwanted side effects from the totality of experience of medication and their effects situated in the context of people's lives. The experience of consuming psychotropic medication inevitably entails highly variable, complex and inter-dependent effects and outcomes. This complexity is manifest in participants' reports of movement, ambivalence and sociality, and the ways medications are generative of subjective feelings of hope, value, change and fear. We commence with a discussion of movement and its varied physical and subjective iterations.4.14.1.1One of the dominant distressing effects of psychotropic medication reported by participants pertained to alterations in the way their body feels, looks and moves. A compelling example offered by participants is the profound disorientated movements known as akathisia. Akathisia has been defined as ‘subjective’ feelings of ‘inner restlessness and the urge to move’ and ‘objective components’ such as ‘rocking while standing or sitting, lifting feet as if marching on the spot’ , p. 73. and inextricable. Beyond questions of continual movements and their role in producing subjectivity, akathisia also raises questions of how subjectivity can be approached as sets of connections to objects, bodies and motion itself.Eamon, a 35-year-old man diagnosed with schizoaffective disorder, offered an account of akathisia while on trifluoperazine: ‘I was running to places … one day I ran so far … and I thought, where am I? You know, I had to get home’. The effects Eamon experienced caused him to move incessantly, he described running and ‘[pacing] for a long time’. Eamon's descriptions of drug effects demonstrate the ‘intra-action’ of medication, effects, embodiment and subjectivity by revealing how each is co-constituted in the experience of consumption. This finding is in line with In contrast to continual movement, Nick, a 41-year-old man diagnosed with schizoaffective disorder described taking several typical antipsychotics see  that mad4.1.2I wasn't menstruating … So that was quite upsetting … I started lactating … I shouldn't be on medication that's making me lactate … being forced to be on [risperidone] which you know causes lactation … I think it was a bit cruel.All participants who were taking psychotropic medication reported experiencing a range of effects embodying the therapeutic regime, many of which were referred to as debilitating. Medication fractured the physiological order to which participants were accustomed, with significant ongoing impacts on subjectivity. For example, Alejandra, a 33-year-old woman with a diagnosis of schizophrenia, described how risperidone caused changes to her body:one of them that really kind of freaked me out … was the fact that as a male I could start lactating … I was like this … is going to like damage me big time if that's something that's going to happen from taking these tablets.Interestingly, a 40-year-old male participant with a diagnosis of bipolar affective disorder I, Vincenzo, experienced shock when he learned that he could begin to lactate. He could not recall the drug's name, but this possibility disrupted his ideas of male embodiment:Another participant, Amrick, a 32-year-old man who was diagnosed with paranoid schizophrenia, did not use the term ‘lactation’ but explained that one side effect of taking quetiapine was an increase in his prolactin levels and an enlarged breast area. Combined with impotence, these corporeal shifts caused him significant distress.expects the manifestation of menstrual periods. By the same token, her body lactating at a time when it is neither expected nor ‘needed’, caused significant concern such that she demanded a change of medication. The cultivation and disruption of gendered subjectivities are also clearly at work in Alejandra, Vincenzo and Amrick's experiences. Beyond disturbing gendered physiological form, gender is produced as problematic through the  encounter with breast milk and sexual dysfunction. It is thus not simply a question of drugs encountering gender, but one of drugs and gender being mutually constituted as the medication encounters bodies, transforming subjectivities and disrupting identities.Feeling distress because of the absence of menstrual periods reveals the troubling of gendered identities through new (and disruptive) pharmaco-physical interactions, reflecting the entanglements of medicalisation, identity, and ‘normality’. Alejandra bring the symptoms to the surface. Therapeutic regimes, in their embodied effects, function to reveal  features of the person and affliction. Or do they produce these very symtomatologies? It is here that before, during and after come into play; the symptoms follow the treatment, or does the treatment produce the symptoms? These accounts challenge the linear progression of time and therapy, that is, from emergence, treatment and recovery, to illustrate the unsettling of temporal delineations between symptom, side effect and ‘normality’.A mouth that drools, a breast suddenly lactating, a body part distended, tics in a section of one's visage, these complex effects of psychotropic medication transform embodied subjectivities, sometimes quite abruptly. The overall effects of drugs fragment and ‘re-assemble’ the body in different ways. These changes, quite paradoxically, become indicators of illness upon the body; they metaphorically and the person, rather than mere manifestation; it is induced emergence, mediated by pharmacological materials and respective expertise, rather than physiological manifestation. ‘Individuals’, ‘symptoms’, ‘afflictions’, ‘recoveries’ become collective and relational productions (with agreements and disagreements therein) rather than reflecting taken-for-granted ideas about individual diseases (symptoms) and collective responses (therapies). Such distinctions become untenable, and in doing and being so, raise questions about why one would assume such things hold together at all. This speaks to the power of an individualised logic in the collective imagination, and the need for ordering in the context of disordered being in the world. Thus, it is not that symptoms follow treatment or treatment produces symptoms, it is that there is no meaningful, coherent line between these concepts. And that the attempt to delineate is an act of power and in turn concealment of the pernicious effects of pharmacological interventions (which can become packaged with disease).The implication is that various assumed ontological splits , slip into murkier territory. The appearance of illness is thus more accurately viewed as a co-production of this particular scene 4.1.3For a few participants, the enmeshment of mental illness and distressing effects of medications caused disruptions to subjectivity (and life) to the extent that they decided to cease their medication. For instance, Florence, a 37-year-old woman diagnosed with reactive psychosis, noted that the experience of side effects, which in her narrative is enmeshed with the experience of mental illness, stood in stark contrast with what life in her thirties should be. As she said, ‘[this] is not the life’. The combination of constant fatigue and weight gain seemed to fragment Florence's understanding of who she is: ‘I was putting on weight … it was still enough for me to feel out of touch with myself’. Florence described her thoughts as ‘paranoid and conspiracy like’ but maintained she never heard voices. After being given diazepam and another medication which name she could not recall, Florence also explained that she heard ‘an audio voice [she] never heard before in [her] head saying two times, “Shut up, shut up”.’ Her symptoms were exacerbated by the medication, and she was unsure whether she had been given an additional drug. Her account reveals the ambiguous qualities of drugs, and how drugs can become continuous in accounts of mental illness. Florence's subjectivity as a person diagnosed with a mental illness, and her own understanding of her condition, are further transformed through contact with drugs.4.2inducing new symptoms, as well as, or instead of, potentially exacerbating – rather than allying – existing ones. Such epistemological uncertainty – both about how to interpret the action of drugs, and how to judge one's own medicated life in relation to an imagined life that might have not included drug-taking – was prominent in several interviews. Indeed, while clinical discourses of psychotropic medication identify the labour of drugs on specific neurons and organs  argument that ‘“subjects” and “objects” do not pre-exist as such, but are constituted within particular practices’. Molly, the ‘compliant subject’, is one example.Other participants' experiences were also marked by ambivalence, representing the ‘multiple paradoxes of lived experience’ , p. 70. and improve symptoms and quality of life. Larry, a 37-year-old man with multiple diagnoses including schizoaffective disorder and obsessive compulsive disorder, shared his thoughts on how he lives with the ambiguities of his diagnoses and psychotropic medication:it's got side effects and that's unpleasant … You have to put up with them. There's no other word for it. … unless some miracle cure comes … this is going to be my life for the rest of my life … it's like having an incurable disease. It can be managed it need'nt get in your way all the time … But it's never going to quite leave your consciousness. And I think you can run away from it every now and then. But you just have to realise that you just have to take your medication at 10–10:30 at night as usual.Psychotropic drugs can be experienced simultaneously as ‘saviours’ bringing quietude and impediments causing distress, indicating how subjectivity is transformed through the ambivalences of experiencing the asymmetrical and complex effects of the pharmacological regimen. As agents and voices of resistance and negotiation within the field of psychiatric knowledge, our participants considered trust and control paramount to their treatment. Psychotropic medication became a signifier of both medical expertise and a loss of control. Medication became symbolic of a system working to withdraw agency never quite disappear from one's consciousness – stand in stark contrast to discourses of mental illness which rely on the ‘master clinical trope’  encourages us to view it as ‘fully alive to the event at hand’ , how the effects are known and narrated and by whom, and the institutions and persons that make the ingestion of drugs possible . Beyond the object itself, and its complex entanglements in processes of treatment, care and support, our analysis revealed key links between the expressions of subjective identity in the consideration of medication effects, and the character and experience of sociality.Knowledge of the drug  is crucial to what makes it ‘work’; a drug 4.3pharmaco-affective sociality. Such sociality, deploying Barad's insights, does not distinguish between the subject that swallows the object and engages in social life. Instead, the medication enacts as it participates in forms of pharmaco-affective sociality whereby the drug can ‘lubricate’ social contact and transform subjectivity as an ‘always unfinished, interrupted, intricate and nonlinear’ project  psychotropic drugs. This opens a critical space where ‘side effects’, ‘therapeutic effects’ and subjectivity – and the object of the drug – are intimately entangled and inextricable from each other. In terms of the social science of mental healthcare, the accounts presented here suggest that experiences of psychotropic medications are in fact better articulated as intra-subjective emergences, as co-produced and inflected by power relations. Further, that these relations evade temporal simplicity  but rather a vitalistic process of becoming (rather than being) and one that operates on and through a brain-body-world axis  and necessary side effects (things to tolerate). The forms of ambivalence expressed point to the ontological instability of such ideas. Lines between symptomatic and side effects, functioning and dysfunctional, may be much murkier than often recognised. Hence, the idea of medication as entanglement – with body, person, authority, institution, power and identity – is more theoretically useful way into examining drug effects. It allows us to ask, what does this technology do in and for this person; what does the medication itself embody, perhaps a certain version of stability? A series of side effects deemed acceptable in the past by people in positions of authority to make such decisions? Other actors and subjects produce subjectivities in the present, and even future possibilities for recovery.The particular importance of this work lies in highlighting the ontological problems associated with ‘typical’ ways of knowing and thinking about medications. For example, the assumptions around pathologies  and supported by partner organisations, including the Victorian Department of Health and Human Services, Mind Australia, Neami National, Wellways, Tandem Carers, the Victorian Mental Illness Awareness Council, and Healthdirect Australia.This project was funded by an The Wellcome Trust (209513/Z/17/Z).Felicity Callard is supported by


Moonstone, a new, highly configurable rule-based clinical natural language processing system designed to automatically extract information that requires inferencing from clinical notes. Our initial use case for the tool is focused on the automatic extraction of social risk factor information — in this case, housing situation, living alone, and social support — from clinical notes. Nursing notes, social work notes, emergency room physician notes, primary care notes, hospital admission notes, and discharge summaries, all derived from the Veterans Health Administration, were used for algorithm development and evaluation.Social risk factors are important dimensions of health and are linked to access to care, quality of life, health outcomes and life expectancy. However, in the Electronic Health Record, data related to many social risk factors are primarily recorded in free-text clinical notes, rather than as more readily computable structured data, and hence cannot currently be easily incorporated into automated assessments of health. In this paper, we present housing situation, living alone, and social support). The system achieved positive predictive value (i.e. precision) scores ranging from 0.66  to 0.98 (lives at home/not homeless), accuracy scores ranging from 0.63 (lives in facility) to 0.95 , and sensitivity  scores ranging from 0.75 (lives in facility) to 0.97 .An evaluation of Moonstone demonstrated that the system is highly accurate in extracting and classifying the three variables of interest (lives in facility) to excellent  performance. Although developed with the social risk factor identification task in mind, Moonstone provides a powerful tool to address a range of clinical natural language processing tasks, especially those tasks that require nuanced linguistic processing in conjunction with inference capabilities.The Moonstone system is — to the best of our knowledge — the first freely available, open source natural language processing system designed to extract social risk factors from clinical text with good ( Moonstone, a new, highly configurable rule-based natural language processing (NLP) system designed to automatically extract information that require inferencing from clinical notes. The use case to which we applied Moonstone for this study is extraction of Social Determinants of Health (SDOH) — specifically, housing situation, living alone, and social support — from clinical notes derived from the Veterans Health Administration (VA). We chose these three variables as our focus as this information is not captured in structured fields within the VA’s administrative data, and because these domains of social risk are important to health outcomes. Building on previous rule-based clinical NLP systems [Social risk factors are important dimensions of health and are linked to access to care, quality of life, health outcomes, life expectancy and health care utilization. Some social risk factors such as alcohol and drug abuse can be captured using administrative and laboratory data. However, data related to measures such as housing, living situation and social support are primarily recorded in free-text clinical notes, rather than as computable structured data, and hence resists easy incorporation into prediction models. In this paper, we present  systems , the MooThe relationship between SDOH and health outcomes is well established . Lack ofMedical Language Extraction and Encoding System) uses a rule-based approach to extract clinically relevant information from radiology reports and discharge summaries, and has been used successfully for a number of different clinical information extraction applications  utilizes open source technologies and a highly modularized system architecture in conjunction with both machine learning and rule-based methods to perform clinical information extraction tasks. The system has been used for multiple clinical NLP application domains . , 9. Medification  and cohofication ).The NLP systems described above are designed to extract information explicitly stated in clinical text ; however, a significant proportion of information regarding social context is not explicitly stated in the clinical note, but can be inferred. For example, from the statement “patient family by bedside”, it can be indirectly inferred that the patient enjoys a degree of social support (i.e. family members who visit). This inferencing process requires a degree of semantic analysis and reasoning that existing clinical NLP systems, optimized as they are for explicit information extraction, cannot easily perform. Furthermore, existing clinical NLP systems are not necessarily well suited for tasks that require the processing of highly ambiguous “everyday” words. For example, to process the sentence “patient has to stay at the VA hospital overnight because he had no one to take him home after the procedure” requires identification of everyday words, tasks, and roles, in addition to inference capabilities to arrive at the (correct) conclusion that the patient lacks social support.housing situation, living alone, and social support — from the clinical notes using NLP.Our goal with this work is to demonstrate the effectiveness of the Moonstone system’s semantic processing and inferencing capabilities by extracting and evaluating key measures of social risk — housing and living alone variables. For example, the statement “discharged: home with wife” implies that the patient both lives in a stable home, and does not live alone. Furthermore, the identity of the person with whom the patient lives can be indicative of whether a housing situation is stable or marginal. For example, “lives with wife” and “lives in ex-wife’s basement” both indicate that the patient does not live alone, but the latter suggests a more precarious living situation. The effort to identify implicit, indirect meaning is complicated by several factors: Inference. The target variable is often several inference steps away from what is stated explicitly in the text. For instance, “family at bedside” literally means that family members are with the patient in the clinical care setting, which in turn implies that they are involved in the patient’s care, which connotes support.Ambiguity. The meaning-bearing words relevant to social support are typically “everyday” high frequency words which, in contrast to medical terminology, have a high probability of appearing in contexts irrelevant to social support. For example, the word “bedside” can be used in many ways unrelated to social support . Although potentially relevant words are relatively common in clinical text, relevant sentences appear much more sparsely, with very few documents in our corpus containing such sentences.Semantic roles. Understanding semantic roles — i.e. who is the actor and who is the recipient of an action — is vital to sentence interpretation. For example, in the sentences “the wife helps the patient with medications” and “the patient helps the wife with medications”, only the first conveys the fact that the patient receives social support, as the patient is the direct object of the verb “helps”. Similarly, word placement can affect interpretation. For example, the sentences “he needs no help with ADL” (Activities of Daily Living) and “he has no help with ADL needs”, differ in only one word (“has”), and yet have very different meanings. NLP systems that do not consider word order, and which do not analyze the meaning and placement of modifiers, cannot reliably make such distinctions.The current state of the art in automatic social risk factor analysis — as exemplified by Chen et al.  and GreeThe clinical document corpus used in this study was selected with the goal of developing information extraction methods capable of automatically extracting SDOH variables relevant to 30-day readmission predictive models, with a focus on four diseases of interest . We selected these conditions as, at the time of study initiation, they were the four medical conditions for which hospital readmission rates were publicly recorded. To create an initial cohort, we identified all VA patients aged 65 or older admitted with at least one of the four diseases of interest between January 1st 2012 and December 31st 2012. More than 21,000 patients were identifiedSocial risk factors pose a significant challenge to the creation of reliable annotated reference standards given that human annotators typically experience extreme difficulty in identifying and reliably annotating rarely documented variables. For this reason, using the corpus described above, we pre-annotated social support instances using a prototype version of Moonstone. We trained three annotators who were familiar with VA documentation practices to review a randomly selected sample of pre-annotated instances, with all disagreements between the annotators discussed until consensus was achieved. We then ran the final, trained version of Moonstone over the document set and presented disagreements between the human annotators and Moonstone to a fourth annotator  who was blinded as to whether the value was assigned by Moonstone or by the previous consensus of annotators. The fourth annotator selected the best variable value, which was then used as the final gold standard value.Moonstone is an open-source, Java-based NLP system developed by the Biomedical Language Understanding Laboratory (BLULab) at the University of Utah and derived from a lineage of clinical NLP systems  that utMoonstone’s activities are user-controlled through its graphical control tool. A function in that tool can be used to apply Moonstone to analyze a corpus of documents. For each document, Moonstone splits that document into tokens representing words, numbers, punctuation and other symbols, attaches a dictionary definition to word tokens if available, and groups the tokens into named sections (e.g. "History of Present Illness") and sentences within those sections.For each sentence in a document, the Moonstone grammatical parser applies the semantic grammar to analyze the tokens in that sentence, and gathers resulting concepts which are relevent to the current NLP task into a list for further processing. The grammatical parser also consults the Moonstone ontology to fire those grammar rules which contain references to semantic types in their patterns.After the document has been parsed at the sentence level, information can be added to task-relevant annotations using first-order inference over task-specific TSL rules. After all this takes place, the task-relevant concepts are filtered to remove duplicates, then passed to the XML generator which converts them into an XML format which is readable by the eHOST annotation tool .Typed Semantic Language). A first-order logic such as TSL consists of a set of symbols and syntactic rules for creating complex expressions from simpler ones, and semantic rules for determining the truth value of an expression based on the values of its components. Simple TSL expressions use a relation/argument format “(relation object1 object2...)”, and complex expressions use “and”, “or” and “not” operators to combine simple expressions into complex ones. For example, the TSL statement “(and (has-support ?patient) ))” indicates that a patient has support and does not live alone. TSL meaning predicates are stored within Moonstone’s type hierarchy and semantic grammar (described below) and assembled by the Moonstone sentence analyzer into a set of TSL statements describing the meaning of an English phrase or sentence. The collection of TSL predicates attached to an annotation object is called the object’s interpretation. In addition, each annotation is assigned a TSL constant representing a summary of the literal or inferred meaning of the sentence; for instance, the summary of “wife at bedside” is the task-relevant concept “:HAVE_SUPPORT:”.Moonstone includes a first-order symbolic logic called TSL ” and “< SOCIAL_SUPPORT >”), whereas constants denoting objects of a given type use colons as delimiters; for instance “:SOCIAL_SUPPORT:” represents an instance of social support within a TSL interpretation.The TSL definition statement shown in Fig. Semantic grammar. The semantic grammar consists of a set of grammar rules containing sequences of elements that may be found in a sentence, as well as tests and constraints to validate that a rule matches a sequence of text. Semantic grammars have been used in a variety of different information extraction systems, including MedLEE [g MedLEE .The pattern of the grammar rule shown in Fig. Unlike most grammatical parsers, words do not need to be in left-to-right order for a match to occur, and there may be intervening words not captured in the grammar or dictionary. Not requiring a specified word order introduces some errors but makes it possible to apply a relatively small, focused grammar to identify relevant information from a document where most words are unknown and irrelevant to the NLP task at hand.Finally, the rule listed in Fig. Lexical dictionary. Moonstone uses an optional dictionary of words and phrases, extracted from the UMLS  Metathesaurus [Systematized Nomenclature of Medicine) or RxNorm, word-level grammar rules are used in place of a dictionary in this project. For example, the word-level grammar rule shown in Fig. hesaurus  that mayTSL inference rules. TSL includes an inference engine which is invoked by the semantic grammar analysis module to assign interpretations to sentences when the semantic grammar does not provide sufficient information to do so. The TSL rule shown in Fig. The Moonstone Knowledge Base consists of four components: a hierarchy of semantic types implemented in TSL, a semantic grammar, a lexical dictionary, and a set of inference rules, also written in TSL. Moonstone’s Named Entity Recognition (NER) module is not shown in Figure 1. The NER module uses a fast, computationally efficient algorithm inspired by the IndexFinder NER tool, a widely used resource in clinical NLP . The NERThe grammar analysis module applies a semantic grammar to each sentence in a document, and outputs a set of TSL expressions representing the sentence’s interpretation. The module uses a variation of the CYK context-free grammar parsing algorithm , to perfNote that with a large or complex grammar there will often be many alternative parse trees, often with different interpretations. Moonstone selects the most likely trees based on probabilities learned during the training process, and on the prevalence of task-relevant concepts such as “:NOT_LIVING_ALONE” and “:HAVE_SUPPORT:”.forward-chaining inference , and ono Prolog )3. In adOne of the most challenging aspects in the development of any tool capable of symbolic knowledge processing is the development of supporting Knowledge Bases, including lexicons, ontologies and grammars. On the basis of our experience working with VA clinical texts, writing and debugging useful semantic grammars by hand is time consuming, frustrating and prone to error. With this in mind, we have developed a training tool to aid in expanding a set of abstract grammar rules into a larger set of rules tailored for a specific NLP task. We begin with a limited set of basic, domain-neutral rules potentially applicable to a large set of NLP projects. The training tools permit a human trainer to apply Moonstone to a corpus of training documents. For each structurally correct parse tree, the trainer selects from a menu the intended TSL summary constant for that tree. The training tool then creates a new specialized grammar rule based on the structure of the abstract rule, containing the semantic constants in the parse tree as the new pattern, and assigning the user-selected constant an interpretation.housing situation, living alone, and social support). When applied to a blind test set with a manually annotated reference standardhomeless/marginally housed) to 0.98 (lives at home/not homeless), accuracy scores ranging from 0.63 (lives in facility) to 0.95 , and sensitivity  scores ranging from 0.75 (lives in facility) to 0.97  . We suspect that performance was lower for these categories, because they require inference from the text by Moonstone, rather than being explicitly stated in the text. Consider the example of the lives alone category. It is common for clinicians to directly ask, and explicitly document this information, making Moonstone’s task easier. Another possibly salient factor is that some of the lower performing variables occur with relatively low frequency in our corpus. For example homeless/marginally housed has 79 True Positives, whereas lives at home/not homeless has 6382.For some categories performance was good but not excellent  nature of VA clinical notes , includireason that a particular classification is made is often a function of various non-pellucid numerical weights within the algorithm). Rule-based methods are typically substantially more perspicuous, given that the reasons for a particular classification decision can be clearly articulated. However, the perspicuousness of Moonstone’s rule-based inferencing capabilities is accompanied by costs, including relative computational inefficiency (i.e. Moonstone may not be suitable for processing millions of notes), and the need to manually construct complex Knowledge Bases.Moonstone uses a linguistically-oriented rule-based approach. This is in contrast to widely used approaches in the general domain NLP community, where machine learning — in particular, modern neural network based machine learning  — is freIn future work, we intend to utilize the Moonstone mention-level social support classifier described in this paper as input to a machine learning based patient-level classifier, with the resulting patient-level classification variables integrated into a 30-day readmission model, allowing us to formally evaluate the contribution of social risk factor variables to 30-day readmission algorithm performance.The Moonstone system is an open-source NLP system designed for clinical NLP tasks that require nuanced linguistic processing and inferencing capabilities. The system achieved excellent results in the challenging task of extracting SDOH variables from VA clinical notes. We are currently applying the rules developed on VA text to non-VA notes at three locations in order to determine the extent to which the system is portable between sites. Although developed with the social risk factor identification task in mind, Moonstone provides a powerful tool to address a range of clinical NLP tasks, especially those tasks that require nuanced linguistic processing in conjunction with inferencing capabilities.Project name: MoonstoneProject homepage: https://github.com/Blulab-Utah/VAReadmissionMoonstoneOS: Java/Multi-platformProgramming language: JavaOther requirements: No other requirementsLicense: Apache 2Any restrictions on use by non-academics?: No restrictions