There is a lack of research in forensic settings examining therapeutic relationships. A structured communication approach, placing patients’ perspectives at the heart of discussions about their care, was used to improve patients’ quality of life in secure settings.The objectives were to:• Establish the feasibility of the trial design• Determine the variability of the outcomes of interest• Estimate the costs of the intervention• If necessary, refine the interventionA pilot cluster randomised controlled trial was conducted. Data was collected from July 2012 to January 2015 from participants in 6 medium secure in–patient services in London and Southern England. 55 patients and 47 nurses were in the intervention group with 57 patients and 45 nurses in the control group. The intervention comprised 6 nurse-patient meetings over a 6 month period. Patients rated their satisfaction with a range of domains followed by discussions on improving patient identified problems. Assessments took place at baseline, 6 months, and 12 months. Participants were not blind to their allocated group. The primary outcome was self-reported quality of life collected by a researcher blind to participants’ allocation status.The randomisation procedures and intervention approach functioned well. The measures used were understood by the participants and gave relevant outcome information. The response rates were good with low patient withdrawal rates. The quality of life estimated treatment effect was 0.2 (95 % CI: −0.4 to 0.8) at 6 months and 0.4 (95 % CI: −0.3 to 1.1) indicating the likely extreme boundaries of effect in the main trial. The estimated treatment effect of the primary outcome is clinically important, and a positive effect of the intervention is not ruled out. The estimate of the ICC for the primary outcome at 6 and 12 months was 0.04 (0.00 to 0.17) and 0.05 (0.00 to 0.18). The cost of the intervention was £529 per patient.The trial design was viable as the basis for a full-scale trial. A full trial is justified to estimate the effect of the intervention with greater certainty. The variability of the outcomes could be used to calculate numbers needed for a full-scale trial. Ratings of need for therapeutic security may be useful in any future study.ISRCTN34145189. Retrospectively registered 22 June 2012.Current Controlled Trials  Forensic mental health care is the provision of mental health services for people with mental disorders who are offenders or at risk of offending. Services are provided in secure, community, NHS and criminal justice settings . Many ofThe Best Practice Guidelines in Medium Secure Units state the therapeutic alliance between staff and patients is at the centre of high-quality care and treatment in secure settings. This has been most often noted when discussing the importance of the term relational security which has been described as the therapeutic alliance between staff and patients in continuing risk assessment and detailed knowledge of the patient . The RoyHowever, a review of forensic mental health services noted a lack of a patient perspective and involvement in the service . The repResearch undertaken in primary mental health care settings has indicated a patient-centred approach, including active participation of patients in the treatment process, is associated with better quality of life, increased adherence to treatment regimens and reduced misunderstanding between clinicians and patients , 10. A pThe underlying rationale of this structured communication approach is that it facilitates explicit negotiations about what each individual patient wants and what the clinician can do about it. The hypothesis presented is that this focus on the individual concerns of the patient will, in turn, lead to an improvement in subsequent care and the patient’s quality of life. It was proposed that using a structured patient-clinician communication approach using a computer-mediated approach (DIALOG) in conjunction with non-directive counselling based on the principles of Solution Focused Brief Therapy (SFBT) within a forensic mental health setting would improve patients’ quality of life, levels of satisfaction, engagement with services and reduce disturbance. There was, however, a need to pilot the intervention in this setting since DIALOG had not been tested in a forensic environment before and there was some uncertainty whether the main trial would be feasible. The specific objectives of this pilot study were to: establish the feasibility of the trial design as the basis for determining the viability of a large full-scale trial; determine the variability of the outcomes of interest; estimate the costs of the intervention; and refine the intervention following the outcome of the study based upon the experiences of the clinicians and patients.A pragmatic cluster randomised trial was designed avoiding any potential contamination between the intervention and control groups in clinical practice. The eligibility criteria for a cluster were that they were secure mental health units with at least two medium secure wards as part of the unit. All NHS units meeting this criteria within a 50 mile radius of London were informed of the trial via email by members of the research team  and invited to participate. The first six secure units who responded were randomised. Far fewer women than men are resident in secure units. To enable the study to examine the intervention with both men and women in the forensic mental health service, the units were stratified. The first stratum included four medium secure units with two male wards in each unit participating in the study. The second stratum consisted of two medium secure units with one male ward and one female ward in each unit participating in the study. Within both groups there was a balanced design resulting in the same number of units in each of the intervention and control groups Fig. . A six-mEthical Approval was obtained from the London Surrey Borders Research Ethics Committee (reference number 11/LO/0104).The participants were mental health nurses and in-patients at six medium secure units in Southern England and London. The first six units that expressed an interest in being included in the study were then visited by members of the research team to discuss potential involvement in the study. This involved presentations to clinical staff detailing the aims and objectives of the study and clarifying what inclusion the study would entail for the unit team. All six units agreed to participate in the study. Agreement was undertaken through email correspondence between the senior member of the unit’s management team and the Chief Investigator. This was then followed up by a formal agreement with the relevant Research and Development manager.The allocation was performed by the randomisation service of the registered Pragmatic Clinical Trials Unit (PCTU) at Bart’s and the London School of Medicine and Dentistry. Nurses were initially approached in two wards in each of the participating units . The inclusion criterion for the clinicians was they were registered mental health nurses working with in-patients within those wards. After nurses had been recruited to provide the intervention to a sufficient number of patients in the unit, the patients were approached. Each patient residing in participating wards was eligible to participate as long as the following inclusion criteria were met; they had a history of least 3 months of current in-patient treatment in the service and were capable of giving informed consent. Informed consent from both nurses and patients was obtained before inclusion into the study by the Research Assistant. Once recruitment in a unit had been completed, the Research Assistant emailed the PCTU with the site ID number (known only to the Research Assistant) and requested an allocation for the unit. The allocation was generated by a statistician independent of the study using the statistical software randomisation.com. An email was then sent back to the Research Assistant indicating whether the unit was allocated to the intervention or control group. To avoid bias, the random allocation of a unit into either the intervention or control arm of the study was only undertaken following the identification and recruitment of a sufficient number of nurses and patients from each unit  meaning Participants allocated to the intervention group received the structured communication approach; the DIALOG approach combined with counselling guided by SFBT. This involved monthly meetings between the patient and nurse for a period of six months and arranged as part of routine care. The intervention consisted of two elements: a computer-mediated approach in conjunction with non-directive counselling which has been found to be an effective practical method of developing patients’ involvement in their treatment. DIALOG was used by nurses to facilitate structured communication sessions, in addition to continuing with standard treatment with their participating patients, to enable individualised therapeutic discussions. During the meeting the patients completed a simple rating checklist, recording the degree of satisfaction with eleven life and treatment domains. The domains were; mental health, physical health, accommodation, job situation, leisure activities, friendships, relationship with family/partner, personal safety, practical help, meetings and medication. Each domain was rated on a scale of 1–7 (from ‘couldn’t be worse’ to ‘couldn’t be better’), and followed by a question on whether the patient wanted any additional or different help in the given domain. If the patient answered yes, the type of the requested additional or different support was discussed and recorded. The eleven domains were presented in a fixed order and an explicit response was required for each item before proceeding to the next item. Participants’ answers to all questions were entered directly onto the iPad tablet using specifically developed software. The tablet allowed patients and nurses to view screen displays detailing the current rating of a domain as well as the rating from any previous month. The procedure was designed to ensure the patient’s views on their situation and needs for care were the central point of treatment discussions and the patient’s view on what kind of help would improve their current situation was explicit.The counselling approach offered was Solution Focused Brief Therapy. It is a structured conversational approach that promotes movement towards positive change in individuals, families, and other systems. The approach is characterised by a focus on the future, more specifically, exploring what will be different when things are better.A.Each nurse in the intervention group was individually trained to use the software and provided with written instructions on how the ratings should be used to facilitate a dialogue.B.Solution Focused Brief Therapy training was delivered by an experienced solution-focused therapist who runs a Masters course in solution focused therapy and a founder member of the UK Association of Solution Focused Practice.A three day training programme was offered to all nurses in the intervention group to help ensure the DIALOG approach was consistently administered.nd and 3rd training sessions for review by and the SFBT trainer. The nurse facilitating the sessions recorded the main topics of each session on a record sheet at the end of each session. Additionally, up to two sessions, out of the six session intervention, were audio recorded. The record sheets and recordings were reviewed by the Research Assistant (JM) who had attended the training sessions and was aware of the main principles of the SFBT approach. Monthly meetings were also held between the Research Assistant and each nurse to examine the intervention.Each nurse also received a practical handbook explaining how to conduct the solution focused approach to help ensure a similar approach was used in all sessions. The fidelity of the intervention was assessed and ensured through a number of procedures. The nurses brought their notes and thoughts from the initial sessions to the 2Nurses in the control arm were encouraged to meet patients with the same frequency as in the intervention group. These meetings were used to plan and evaluate care as well as to discuss any specific difficulties but without using the formalised structured communication approach.To assess the feasibility the following areas were considered; the recruitment process for clusters, nurses and patients, rates of completion of training, completion of outcomes, loss to follow-up, withdrawal and the number and timing of monitored sessions in each arm, and patterns of missing information.Outcome data was used to assess the potential for effectiveness and the variability in outcome measures in readiness for a sample size calculation for the main trial. The primary outcome was Quality of Life and assessed by the Manchester Short Assessment of Quality of Life scale (MANSA) . It has The primary endpoint was measured at three time points. To ensure results were not affected by a secular trend, each intervention group unit was paired with a control unit group and the assessments for each paired intervention-control group unit carried out within a month of each other at each time point.Time Point 1 - baseline assessment of patients; for the intervention group this was prior to their first structured communication session while for the control group this was at the same time as noted above;Time Point 2 – within the two weeks following the intervention; the last structured communication approach meeting (after six months);Time Point 3 – six months post intervention (twelve months after time point one).The first five secondary outcomes noted below were also assessed prior to the intervention (baseline), at 6 months (post intervention) and 12 months.Engagement with Services - Helping Alliances Scale (HAS) Ward Climate - Essen Climate Evaluation Schema (EssenCES) Patient Satisfaction - Forensic Satisfaction Scale (FSS) Recovery - Process of Recovery Questionnaire (QPR) Nurse Stress - Maslach Burnout Inventory (MBI) Disturbed behaviour was recorded from the ward untoward incident forms and patient progress notes on a monthly basis from three months prior to the baseline assessment till the six-month post intervention follow up (15 time points).DIALOG Satisfaction Checklist (completed in monthly session)Focus groups with patients (one in each intervention unit following completion of intervention)Monthly interviews with nurses (completed after each session)For the intervention groups only, the following outcomes were also documented:The patients’ demographic details, the completeness of outcomes, recruitment rates, and withdrawal rates were also recorded.Following the final session, three focus groups were convened, one in each intervention unit, to explore service user perspectives and experiences of the study . ParticiMonthly interviews were held nurses and a member of the research team (JM) from their first meeting to their final session to look at any identified concerns surrounding the intervention and to examine the acceptability of the approach from the nurse’s perspective and were also digitally audio-recorded and transcribed.The research team coded and themed the transcriptions in line with Braun and Clarke’s thematic analysis approach . MultiplTo establish the feasibility of a full-scale cluster randomised trial the estimated treatment effect and corresponding confidence intervals for all outcomes measured at 6 and 12 months was calculated. Firstly, a mean value of the outcome for each unit was calculated, and then the treatment effects  as the mean difference of these means in the intervention and control groups. This was viewed as an acceptable method of analysing data from cluster randomised trials when the number of clusters is small. To assess the likely size required for a full scale trial some estimate of the variability of the primary outcome was needed and, in particular for a cluster randomised trial, an estimate of the intra-cluster correlation coefficient (ICC). Relying on pilot studies or even single previous trials for reliable estimates of the ICC is problematic because sampling errors are very large. Nevertheless, the randomisation units in this study are unusual and ICCs from a number of other similar studies  were not available. Therefore, an ICC from this study was calculated, using standard analysis of variance techniques. The ICC was calculated for all primary and secondary outcomes, at 6 months and 12 months, except for disturbance monitoring and the DIALOG satisfaction checklist. Some measure of variability was also given for all primary and secondary outcomes .In general, where there were missing data for the primary and secondary outcomes, individuals who were missing more than 20 % of the items for mean scores were excluded. For sum scores, where an individual was missing less than some pre-specified number of items, their missing item(s) were replaced with the average of the other items given, or the individual was excluded if they were missing more than the pre-specified number of items for that particular outcome.The health economics evaluation adopted an NHS/Personal Social Services and police services perspective. Economic evaluation methods followed the NICE Guide to the Methods of Technology Appraisal 2013 . A microThe cost of training per nurse was estimated using the number of nurses enrolled on the DIALOG-SFBT course and the number of nurses who completed the course. Sensitivity analyses considered the minimum and maximum number of nurses per session as observed in the study. The cost of the intervention per patient was estimated with and without the costs of additional staff time. Sensitivity analyses were conducted using different durations of meetings between the nurse and the patient .A micro-costing of incidents was conducted based on informed clinical opinion. The data were collected using an Incidents Resource Use Questionnaire which was designed for the study. Clinicians were asked to specify resources associated with incidents and to indicate the probability of their use. These included A&E admissions, inpatient stay, outpatient appointments, investigations, medication, staff time associated with managing incidents, NHS transport and police. The cost of an incident was calculated by multiplying the probabilities of using services (taken from the Incidents Resource Use Questionnaire) by unit costs. The total cost of incidents was derived by multiplying the number of incidents extracted from medical records by incident costs.Costs and outcomes are presented in a disaggregated form. The cost of the intervention was calculated as per trial and presented as a total cost for the intervention and as a cost per patient. Outcomes for the cost-consequences analyses are presented per group (intervention and control) for the period from baseline assessment until the six-month post-intervention follow-up (12 months). As a pilot study, the outcomes for the intervention and control groups were not compared statistically.The research team contacted nine units about the possibility of participating. The first six who responded were contacted to discuss their involvement. All six agreed to participate. 112 patients were recruited to the study out of 182 approached in the six units (62 % recruitment rate) as shown on the flow diagram  randomised to the intervention group completed the training programme. The rates for the three units varied: unit one: 18 out of 27 (67 %); unit three: 13 out of 15 (87 %); unit six: 4 out of 5 (80 %). The higher dropout rates for unit one can be partly explained by the time delays between recruitment and the start of the intervention. Some nurses had moved wards so could not pair up with patients in the wards where the intervention was being carried out. Some nurses did not attend the sessions as the patients who they had been paired with for the intervention had withdrawn from the study. In addition, some nurses from all three units decided that they did not wish to undertake the training and be part of the intervention after initially agreeing to participate. Qualitative data from the monthly meetings between the nurses and the research team as well informal discussions with the SFBT trainer indicate the nurses found the training programme stimulating and enjoyable.The baseline demographic characteristics of the participants are shown in Table 5 patients in the intervention group (9 %) and 11 (19 %) in the control group were lost to follow up at 6 or 12 months. The majority (11) of these patients reported they were no longer interest in being involved. However, one participant in the intervention group had been deported and another had been sent back to prison and unable to be located in the prison system, while three participants in the control group had been sent back to prison. The probability of being lost to follow up at 6 months/12 months appears to be potentially related to some of the baseline characteristics and in particular gender; with the odds of being lost to follow up for women estimated to be 2.2 times the odds of men . Therefore, for gender, the between intervention and control group differences in those lost to follow up at 6 months/12 months tend to be larger than the chance differences observed at baseline. However, the differential attrition did not appear to lead to imbalance in gender amongst those patients remaining in the trial (i.e. not lost to follow up) compared with all patients at baseline. Both age and mental health act status seem more or less balanced both at baseline and amongst those lost to follow up at 6 months/12 months. For length of stay and clinical diagnosis, the between intervention and control group differences in those lost to follow up at 6 months/12 months tend to be larger than the chance differences observed at baseline. However, the differential attrition does not appear to lead to imbalance amongst those patients not lost to follow up compared with all patients at baseline.The number of patients from those randomised completing the primary outcome (MANSA) scale at 6 months was 48 (87 %) of the intervention group and 42 (74 %) of the control group. At 12 months, the numbers were 47 (85 %) of the intervention group and 42 (74 %) control group. The rate for the other patient outcomes ranged from 46 (84 %) to 48 (87 %) for the intervention group at 6 months and between 41 (72 %) and 42 (74 %) for the control group. At 12 months, the numbers completing the outcomes in the intervention group were 47 (85 %) for all of the assessments and between 39 (68 %) and 42 (72 %) in the control group. It appears the majority of patients completed the primary and secondary outcomes at 6 and 12 months. The number of nurses included in the analysis was much lower with 60 % of both the intervention group and control group completing the assessment at 6 months and 24 (51 %) of the intervention group and only 18 (40 %) of the control group completing the assessment at 12 months.The number of patients giving any data at 6 months, and the number of patients giving any data at 12 months, is similar for each of the outcomes/subscales. Similarly, the number of nurses giving any data at 6 and 12 months is similar for each of the outcomes/subscales. This suggests that there is not an outcome/subscale that participants did not want to complete at all more than others. Amongst those who completed an outcome measure at all, the mean proportion of the measure completed was high for all outcomes, mostly being between 90 % and 100 %. This suggests that completeness of outcomes would not be a significant issue for the main trial.The mean number of 1:1 monitored sessions between nurses and patients per month was 2 for each month for those on the intervention, but was 3 each month for those on the control. Considering the DIALOG sessions are included in the count towards the 1:1 sessions for those on the intervention as well, this suggests that patients on the intervention received on average fewer 1:1 sessions with the nurse than the control patients and that the DIALOG intervention does not create an increased workload for the service. The duration of the sessions were not recorded.Both patient and nurses involved in the intervention expressed broadly positive views about the approach.“You got used to it after one or two sessions you know. It was easier to communicate and talk about things and that”.A numbers of patient comments centred on the fact that the approach gave a structure to their meetings with nurses, was focussed on goals, and was an opportunity to reflect on issues in their lives and to think about making changes such as in the quote underneath:Some patients were also able to identify specific changes which were beneficial for them from the intervention . They also liked using iPads and how the process eased communication with the person doing the intervention. The financial reward for undertaking outcome assessments was also a strong incentive.In terms limitations of the intervention, some felt that concerns raised during the sessions were not taken seriously by staff. This linked to the theme most often brought up by participants – the importance of the relationship to the staff member doing the study.Nurses identified some challenges relating to the initial difficulties encountered in arranging some sessions with their patients due to difficulties such as unsettled ward environments or low staffing levels. Having protected time for the delivery of the session was seen as beneficial to the smooth running of the sessions as was arranging meetings to fit into daily running of the ward. For some nurses, working with new technology and software was difficult and there was some uncertainty in the initial sessions as to whether they had used the iPads correctly. However, the majority of nurses were knowledgeable about using iPads, and found using these tablets and software was straight forward and easy to use while those who were initially anxious about using the software became more confident in its use as more sessions took place.“Solution Focused Approach isn’t a hat I put on when I do my sessions. The process is happening naturally and in my every day interactions with patients”.The use of a structured approach and SFBT was viewed positively as noted below and using the structured communication approach was viewed as beneficial from both a practical and professional perspective.p-value.Data was collected from July 2012 to January 2015. The outcomes at baseline, 6 months and 12 months are shown in Table For the primary outcome at 6 months, the difference in the overall summary mean MANSA score is estimated to be as much as 0.8 higher in the intervention group to as much as 0.4 lower, and at 12 months is estimated to be as much as 1.1 higher in the intervention group to as much as 0.3 lower. This indicates the likely extreme boundaries of effect in the main trial, and that a positive effect of the intervention is not ruled out. A full trial would be justified to estimate the effect with greater certainty.Similar conclusions can be drawn for each of the secondary outcomes with only one outcome excluding a null effect . However, it should be noted that it would expected to see the null effect ruled out in 5 % of cases just by chance due to the multiple outcomes that are being examined.For the primary outcome, the standardised effect size (treatment effect divided by standard deviation) and confidence interval at 6 and 12 months are 0.7 (−0.9 to 2.4) and 1.4 (−0.4 to 3.1), respectively. The confidence intervals do contain 0.3, where 0.3 is the sort of standardised effect size that might be expected for an effective complex intervention and the sort of standardised effect size that investigators often power their trials on. The estimate of the ICC for the primary outcome at 6 and 12 months is 0.04 (0.00 to 0.17) and 0.05 (0.00 to 0.18). The standard deviation is 0.3 at both time points.The results of the cost-consequences analysis for the intervention and control groups are presented in Table The levels of disturbance are shown in Table Recruitment to studies involving forensic mental health care is extremely difficult  resultinIt is important that the intervention is reproducible in a large scale trial. The training programme, SFBT manual and monthly meetings between research team and nurses provided a strong base for ensuring a consistent approach was adopted by all the nurses involved in the intervention. The training programme was designed with the perception that the nurses would not have prior experience of the DIALOG approach or Solution Focused Brief Therapy. The evidence from the taped sessions and session records suggests the nurses were able to deliver the intervention as instructed allaying concerns about the quality of the intervention provided by clinicians untrained in SFBT.n = 7, 13 %) and nurses  withdrew from the intervention. The qualitative evidence suggests both the nurses and patients viewed the intervention as valuable and able to be understood and followed by nurses and patients. The structure of the approach also allowed discussions to be structured and centred on areas considered important by patients. Approximately a quarter of nurses recruited to the study did not attend the training sessions. As noted earlier, part of the reason for the non-attendance was due to delays in the period between recruitment and undertaking the training, particularly for the first cohort. The subsequent cohort of nurses had a much shorter time span between recruitment and training with the result that the proportion of recruited nurses attending the training was much higher. Those nurses in the 2nd and 3rd intervention were also given a clearer explanation as to what involvement in the study would entail which may have also helped nurses be more confident about their role and commitment. This policy will be maintained in the proposal for a full scale trial. However, some delay between recruitment and the delivery of the training is inevitable as the service can only organise their work roster for staff to attend the training sessions once randomisation has taken place. It was also noted that nurses became more proficient in their use of DIALOG and SFBT as they undertook more sessions. It may be preferable to allow nurses some space to practice their skills before commencing the interventions.The majority of nurses randomised to the intervention group attended the training session (35 out of 47 (74 %). These were well received by the nurses as noted in the qualitative interviews. Few patients  as well as a number of practical considerations underpinning the scheduling of sessions. There were a number of competing pressures from nursing related issues , patient related issues , as well as the availability of rooms at a convenient time to undertake the session. These pressures were acknowledged in discussions between some nurses and the Research Assistant. If more frequent/intensive interventions were to be considered, it is likely that other practitioners such as occupational therapists, social workers, psychologists and doctors as well as health care assistants should be considered as facilitators of the sessions as long as they were able to attend the training sessions and to commit to undertake the sessions for the agreed frequency and duration of the interventionIn terms of the acceptability of the intervention to the patients, although there were many positive comments about the strengths of the intervention, some limitations were also noted. Some patients complained that nurses did not do anything about the patients' concerns. Two main reasons seemed to be underpinning this view. Firstly, some of the problems were unable to be changed whilst being in a forensic unit. The two most common areas where help was requested were in relation to medication and their job situation. There are limitations to the amount of change that could take place in these areas in the inpatient environment. However, the most frequent view from the patients was that they felt that it was the attitude of the nurse doing the intervention which determined whether they found it helpful or unhelpful. The centrality of staff-patient relationships to quality of life on the forensic units and a sense of fairness, safety, humanity and trust was also reported as important. In a definitive trial, it may be helpful to formally present this feature of the therapeutic relationship as part of the training programme before commencing the intervention.The study demonstrated that a full scale cluster randomised trial to examine the effectiveness of a structured communication approach using DIALOG supported by Solution Focused Brief Therapy was feasible. For the primary outcome at 6 months, the difference in the overall summary mean MANSA score is estimated to be up to 0.8 higher in the intervention group or 0.4 lower and as much as 1.1 higher in the intervention group or 0.3 lower at 12 months. The estimated treatment effect of the primary outcome is clinically important and the estimated overall summary mean MANSA scores indicate a positive effect of the intervention is not ruled out. Similar conclusions can be drawn for each of the secondary outcomes. However, as expected given the small sample size, particularly the number of clusters, there are no firm conclusions to be drawn from these estimates about the effectiveness of the intervention. The intervention is promising but there is a large degree of uncertainty which makes a larger trial essential.The estimate of the ICC for the primary outcome at 6 and 12 months is 0.04 (0.00 to 0.17) and 0.05 (0.00 to 0.18). The standard deviation is 0.3 at both time points. It is difficult to triangulate these with similar studies to form an estimate of the ICC that could be used in the main trial sample size calculation due to a lack of studies examining quality of life in medium secure units. A more conservative estimate of 0.07 or 0.08 would be employed for a main trial.The pilot study also provided estimates of intervention costs, the cost of incidents and the cost of stays in a medium secure mental healthcare facility to inform the future study. The study identified resources which are likely to be affected by the intervention, and the major sources of uncertainty associated with use of these resources. Health economics analysis showed that incidents are costly, since they are associated with significant use of NHS resources and police. Due to resource constraints, a micro-costing of incidents based on informed clinical opinion was collected and analysed rather than collecting patient-level data on resource use by patients. A number of incidents in the same category (i.e. violent acts against others) are likely to result in markedly different resource use therefore it would be helpful for the resources required for each individual incident to be recorded separately in a definitive trial.This pilot cluster randomised trial was designed to test the feasibility of a full trial and to optimise the intervention and trial approach. It has provided an initial indication that the intervention has the potential to be effective but the small sample size means it did not have the power to detect significant clinical differences. The health economic data gave a clear overview of the costs involved in the study. However, it was acknowledged that collecting individual patient data may be beneficial in a full trial particularly in relation to the costs associated with disturbed behaviour. Looking at what individual costs are associated with each episode of disturbance would give a clearer indication of the costs accrued following a disturbed event. Examining the incident costs for longer than 12 months following the start of the intervention may also give a better indication of on-going costs.There were proportionally more women patients who withdrew from the study than men. This may be associated with the specific sample of patients recruited for the pilot study. However, it would be beneficial to look more closely at any reasons for higher dropout rates for women and also whether it may be helpful to offer some ongoing support during the intervention. The number of nurses lost to follow up indicates some uncertainty of the value of the findings of the Maslach Burnout Inventory. It is worth noting that only 6 (13 %) nurses actively withdrew from providing the intervention. However, the number who did not complete the outcome assessments at 6 and 12 months was much higher. This questions the value of including nursing outcomes in a full trial. Alternatively, procedures may need to be put in place during the trial to try to reduce missing data.No information was collected on the ratings of need for therapeutic security for the patients. As this was a pragmatic trial, the team determined that clinicians would be making judgements on the relevance of the need for medium secure mental health care based on the admission criteria for these units enshrined in the standardised specifications which accompany contracts. All patients recruited to the study would have had an HoNOS-Secure  and usinThe collection of qualitative data was viewed as a positive addition to the quantitative data. It helped gain a greater understanding of the intervention’s feasibility and acceptability and also provided an opportunity for improvements in the intervention and conduct of the trial. One recommendation would be that any qualitative/focus group data be collected within 2 months of the trial finishing in a full trial. In addition, the centrality of staff-patient relationships to quality of life on the forensic units and the importance of a sense of fairness, safety, humanity and trust as important factors in this relationship could be made more central to the intervention and factored in to any measurement of quality of life on forensic wards similarly to how prison research has focused on these factors with regards to staff-prisoner relations, the quality of prison life and levels of distress .The trial design appears viable as the basis for a large full-scale trial. The procedures seem to function well; randomisation procedures, intervention approach (training and application) while the measures used were understood by the participants and gave relevant outcome information. The response rates were good with low patient withdrawal rates. The qualitative responses also suggest general satisfaction with the approach.The variability of the outcomes from this pilot study provides a starting point for considering the inputs for a sample size calculation for a main trial. Further data are needed to ensure the robustness of the estimate of the variation. The estimated treatment effect of the primary outcome is clinically important, and a positive effect of the intervention is not ruled out so a full trial is justified to estimate the effect with greater certainty.Health economics analysis showed that incidents are costly, since they are associated with significant use of NHS and police resources. The real cost of incidents may be even higher when analysed using patient-level data. Examining the incident costs for longer may give a better indication of on-going costs. There is also a need to look at the reasons for higher dropout rates for women and whether to offer ongoing support. An examination of ratings of need for therapeutic security may be useful in any future study as well the possibility of other practitioners being involved in facilitating the intervention. Finally, the number of nurses withdrawing from the study and not undertaking the outcome assessments indicates some uncertainty of the value of including nursing outcomes in a full trial.


Wireless power transfer is a nonradiative type of transmission that is performed in the near-field region. In this region, the electromagnetic fields that are produced by both the transmitting and receiving coils are evanescent fields, which should not transmit energy. This then raises the question of how the energy can be transferred. Here we describe a theoretical study of the two evanescent field distributions at different terminal loads. It is shown that the essential principle of wireless energy transfer is the superposition of the two evanescent fields, and the resulting superimposed field is mediated through the terminal load. If the terminal load is either capacitive or inductive, then the superimposed field cannot transfer the energy because its Poynting vector is zero; in contrast, if the load is resistive, energy can then be conveyed from the transmitting coil to the receiving coil. The simulation results for the magnetic field distributions and the time-domain current waveforms agree very well with the results of the theoretical analysis. This work thus provides a comprehensive understanding of the energy transfer mechanism involved in the magnetic resonant coupling system. The method used in these studies is based on the principle of resonant evanescent field (either near-field or nonradiative field) coupling, which allows the energy to be coupled efficiently between two resonant objects, i.e., between the transmitting and receiving coils6 of the WPT system. Additionally, the coupling mechanism is mediated through overlapping of the evanescent fields4. However, in the evanescent electromagnetic field that is generated by a current-carrying coil, the phase difference between the magnetic field H and the electric field E is 90°; therefore, the average value of the energy flow density in a single cycle is zero, because the energy is exchanged back and forth in the near field. This means that there is no net energy flow from the transmitting coil to the receiving coil. If this is correct, then no energy transmission should be observed. It is therefore necessary to clarify how the energy is transferred and how the superposition of the evanescent fields mediates the coupling mechanism. While the WPT mechanism has been studied extensively in previous works based on coupled-mode theory9 and equivalent circuit theory12, little attention has been paid to the issue of superposition of the evanescent fields, which is related to the essence of the energy transmission process.The feasibility of efficient wireless power transfer (WPT) via coupled magnetic resonances has previously been demonstrated both experimentallyIn this work, we first establish a simple model of the magnetic resonance-coupled WPT system. Then, the distributions of the incident and reflected fields that are produced by the transmitting and receiving coils, respectively, are depicted under the approximate working conditions, and the effects of the nature  of the terminal load on the two evanescent electromagnetic fields and the superposition of these fields are discussed. Finally, through analysis of the Poynting vector of the superimposed field at the different types of terminal load, the energy transmission mechanism is clarified.13 is shown in Fig. d that is wound into one loop of radius a. The wire is assumed to be a perfect electric conductor (PEC), and thus ohmic loss can be disregarded. A capacitor (C0) is connected to the coil to achieve resonance. A power source with an electromotive force US and an internal resistance RS is connected to the transmitting coil. A terminal load, for which the impedance ZL may be inductive, capacitive or resistive, is connected to the receiving coil. The distance between two coils is designated h, and represents the transmission distance.The circuit model used for the WPT systemI1 that is excited in the transmitting coil by the power source US with time-harmonic excitations will induce a time-varying current I2 in the receiving coil. The two resonant coils are approximated as two current loops and are thus theoretically equivalent to two magnetic dipoles, and this allows the field distributions between them to be calculated. In reality, the effects of the electric dipole that arises from the accumulation of macroscopic charges in the field distributions (mainly in the electric field distribution) should be considered. However, these effects can be negligible because almost the entire electric field is inside the capacitor C0. In the case where the magnetic coupling only is considered, the near magnetic and electric fields that are generated by either magnetic dipole, using the spherical coordinates shown in Fig. A (A = πa2) is the coil area, k = 2πλ (where λ is the wavelength at the operating frequency in free space) is the wave number, m = 1 and m = 2 denote the incident and reflected fields, respectively. Note that the magnetic and electric fields that are expressed in equations . Note that equation  is equal to the circuit resonant frequency, the impedances of the coil inductance and the capacitance C0 are offset. Therefore, the current I2 in the receiving coil is entirely determined by the terminal load, and is given byZL = j2πf0L, ZL = 1/(j2πf0C) or ZL = R when the terminal load is an inductor (L), capacitor (C) or resistor (R), respectively. In equation  between the two magnetic dipoles shown in Fig. p in the two spherical coordinates has been marked. Based on equations  × (H1 + H2)*]/2 of the superimposed field at an inductive or capacitive load at any point in the yoz plane between the two coils is zero. For any point in any other plane passing through the z-axis between the two coils, the result is obviously identical. Therefore, the net energy does not flow from the transmitting coil to the receiving coil, although the two coils are continuously involved in the process of charging and discharging of the electrical and magnetic energy. This conclusion meets our requirements because the capacitor and the inductor are energy storage elements that operate without consuming power.In terms of equation , the Poyy direction, and the other is the z direction. In Fig. p in the yoz plane, there is always another point q that is symmetrical with it about the centre plane 10), the quations  and (10)quations  and (10)z direction in equation  and θ2 ∈ ; therefore, the energy flow density in the z direction at any point in the yoz plane between the two coils is nonzero. Additionally, we note that the energy flow density in the z direction has no relationship with the azimuth φ. The energy flow from the transmitting coil to the receiving coil can then be calculated using the surface integral of the Poynting vector over the centre plane , and it can be simplified asA = 2πxdx is the differential area of the centre plane. Clearly, the result of equation z directid = 1 mm is a = 100 mm. An 80 pF chip capacitor is inserted into the coil to achieve resonance. An input port with power of 1 W and resistance of 10 Ω is set in the transmitting coil. The properties of the output port in the receiving coil and the transmission distance between the two coils can be set arbitrarily according to the transfer requirements. Our study results show that, irrespective of the magnitude of the transmission distance, the relationship between the reflected and incident fields is consistent with that of the theoretical analysis. This again indicates that the superposition principle of the evanescent fields is not confined to the condition where a ≪ h. For example, if the space between the two coils is 100 mm, then the simulation results at a given time are as shown in Figs To validate the above conclusions, a physical model of the WPT system is set up using the commercial full-wave electromagnetic solver. In this model, the radius of the PEC coil with the cross-sectional radius 4L = μ0a[ln(8a/d)−2]. The chip capacitance C0 is 80 pF, and thus the resonant frequency of both coils is 23.2 MHz. The mutual inductance between the two coils, which represents the transmission distance, is calculated from the formula13In contrast, we analysed the time-domain current waveforms of the equivalent circuit of the above physical model. The coil inductance of 590 nH is calculated from the formulaS11 and the transmission coefficient S21 to describe its performance. The results of the circuit and electromagnetic simulations are consistent  in the presence of a resistive load, which is the appeal of the nonradiative WPT when compared with microwave power transmission16, and the radiated energy in the far field has been concentrated in a narrow cone for directive emission17. Therefore, for nonradiative near-field energy transfer, the evanescent field should also be mediated to improve both transmission power and efficiency18 and to reduce the overall system size. In the process of understanding the essence of the WPT process and the characteristics of the evanescent field distributions, these problems will also be solved gradually.In addition, the electromagnetic field (wave) must be modulated to achieve certain specific goals. For example, magnetostatic energy has been harvested and distributed as desired in space to increase the sensitivity of magnetic sensorsIn our theoretical analysis, we used the point magnetic dipole model to discuss the incident and reflected evanescent field distributions. Through analysis of the Poynting vector of the superimposed field at the different terminal loads, the essence of the energy transmission process is clarified. The electromagnetic software was used to build a two-coil WPT system that was loaded with chip capacitances and contained an input/output port. The port characteristics and the WPT system size can be adjusted, and we can thus simulate a real physical WPT system model. From the physical model, equivalent circuit parameters are extracted. The electromagnetic simulation results and the time-domain current waveforms agree very well with the results of the theoretical analysis. These analyses have thus combined to prove that the essence of the WPT process is the superposition of the evanescent fields.


SNP collection to compare diverse accessions, they also show that the Watkins Collection contains a substantial amount of novel genetic diversity which has either not been captured in current breeding programmes or which has been lost through previous selection pressures. As a consequence of our analysis, we have identified a number of accessions which carry an array of novel alleles along with a number of interesting chromosome rearrangements which confirm the variable nature of the wheat genome.The importance of wheat as a food crop makes it a major target for agricultural improvements. As one of the most widely grown cereal grains, together with maize and rice, wheat is the leading provider of calories in the global diet, constituting 29% of global cereal production in 2015. In the last few decades, however, yields have plateaued, suggesting that the green revolution, at least for wheat, might have run its course and that new sources of genetic variation are urgently required. The overall aim of our work was to identify novel variation that may then be used to enable the breeding process. As landraces are a potential source of such diversity, here we have characterized the A.E. Watkins Collection alongside a collection of elite accessions using two complementary high‐density and high‐throughput genotyping platforms. While our results show the importance of using the appropriate  Triticum aestivum), with production of more than 730 million tonnes in 2015 constituting 29% of global cereal production, is the main provider of calories in the diet globally  such that elite lines experienced a bottle neck that reduced genetic diversity  are most similar to those from Eastern Europe; accessions from the Caucasus are most similar to those from the Middle East and Asia. Of the 26 lines from the former USSR that fell into group Q1, 22 were from Transcaucasia . Of the 19 that fell into group Q3, eleven were from the Ukraine and Siberia. Thus, the lines from the former USSR fall into two groups geographically and are related to either lines in Eastern Europe (group 3) or lines from the Middle East (group 1). Interestingly, along the corridor of land between the Black and Caspian Seas, there is a shift in assignment from predominantly group 3 (the Ukraine) to predominantly group 2  via predominantly group 1 (Transcaucasian countries).The geographic distribution of the three STRUCTURE groups was investigated by analysing Q scores  for each country and projecting these onto a world map Fig. . This reet al., To determine whether there is novel variability in the Watkins Collection with respect to modern elite varieties, Watkins accessions were genotyped alongside a large number of elite varieties. An analysis was carried out of 1795 accessions  on the 35 k Wheat Breeders’ Array  were polymorphic across the two collections taken together; 32 443 (92.32%) and 32 992 (93.88%) were polymorphic markers in the Watkins Collections and elites, respectively. Thus, the majority of markers (32 115) were polymorphic in both collections, and very few polymorphic markers were exclusive to either group Fig. a; 328 .To further investigate the relationship between modern accessions and the Watkins Collection, we characterized the core collection of 120 Watkins accessions and 145 elite cultivars using the wheat high‐density 820 K Axiom Array, which contains 819 571 markers  that, with respect to the 145 modern elite accessions used in this study, the Watkins Core Collection contains a considerable number of novel polymorphisms, we wished to determine which of the Watkins accessions were particularly polymorphic and whether there was any geographic bias in this regard. That is, are accessions from some regions more polymorphic than accessions from other regions? To determine this, the genotype scores for each Watkins accession in turn were added to the genotype scores for the 145 elites and the number of additional polymorphisms was determined. The cumulative addition of the Watkins accessions of the Core Collection shows that each contains novel polymorphisms Fig. a. The avet al., et al., et al., Lists of collection specific, polymorphic SNP markers and their chromosome positions). Of the polymorphic markers unique to the two collections, 42 492 (Watkins) and 25 764 (elites) could be provisionally mapped based by BLASTN to the Chapman assembly  clustered with accessions from the Middle East and Asia, while those from north of the Black Sea (Crimea and the Ukraine) clustered with accessions from Eastern Europe. The accessions from Siberia were not distinctly clustered by PCO plot. This highlights an interesting pattern of diversity around the Black Sea: accessions collected from this relatively small geographic area, that is the two regions from the former USSR (Transcaucasia and the Ukraine) and Turkey, are genetically quite distinct and derived from the three main ancestral groups indicated by the STRUCTURE analysis Fig. b. The reet al., n = 804) together with modern elites (n = 1002) accessions indicates that the former are different from the latter as there was little overlap between their respective clusters. This lack of co‐localization is, in part, explained by the fact that there is not complete geographical concordance between the countries of origin of the accessions analysed: the elite varieties are principally from the Americas, Australia and Europe while the accessions from the Watkins Collection come from Asia, the Middle East and North Africa as well as from Europe and Australia. However, Watkins accessions of European origin form a cluster distinct from the elite European accessions. Interestingly, the Australian Watkins accessions do not cluster with the elite Australian accessions which might reflect the fact that modern Australian lines are not derived from their local landraces. It has been reported that 98 per cent of the Australian wheat belt is sown with varieties derived from genetic materials from the CIMMYT gene bank and breeding programmes . The countries with the largest number, apart from Italy with its two very diverse accessions, were Palestine, Turkestan, Iran and Egypt. It is perhaps no surprise that these SNP rich accessions occupy the ancestral home of bread wheat in the fertile crescent.The SNPs unique to the landraces might indicate the presence of a valuable genetic variability that is not being incorporated in modern breeding programmes. All 120 accessions of the Watkins Core Collection possessed novel alleles, but there was great variability in the number of these (range 127–12 828) and the accessions from some regions and countries housed more variability than others. At a regional level, the landrace accessions from Australia and Eastern Europe were the least rich with regard to the number of novel polymorphisms. By contrast, it would appear that breeders should turn to landraces in the Middle East and North Africa if they are looking for novel alleles as these, on average, carry the largest number of novel polymorphic alleles. On a country‐by‐country basis, these patterns become a little clearer. The Eastern European landraces did have relatively low numbers of novel SNPs. The landrace accessions from France, however, had by far the smallest number of novel SNPs .Thus, the Watkins Collection would appear to be a valuable reservoir of variability that might be drawn from in future breeding programmes. This array‐based study has provided a clear picture of the level of genetic diversity and its geographic distribution in the Watkins Collection and, in so doing, we hope provides breeders with a useful map to guide them in the choice of material in breeding programmes. In general, it would appear that breeders should turn to landraces in the Middle East and North Africa if they are looking for novel alleles as these, on average, carry the largest number of novel polymorphic alleles. However, there are accessions from all six regions that carry a large number of novel polymorphisms. Thus, array‐based genotyping studies of landraces collections, such as the Watkins Collection, could prove to be highly valuable to breeders allowing them to precisely target the regional alleles they wish to include in their breeding programmes. The diversity present within the Watkins Collection has been captured in an elite background through the large‐scale development of bi‐parental populations and near isogenic lines (NILs) undertaken in the Landrace Pillar of the Wheat Improvement Strategic Programme (WISP). This material has been developed and is free to access in the form of a breeder's toolkit  the Axiom® Wheat HD Genotyping Array, which contains 820 k features . Samples were genotyped using the Affymetrix GeneTitan® system according to the procedure described by Affymetrix . Allele calling was carried out using the Affymetrix proprietary software package GTC, following the Axiom® Best Practices Genotyping Workflow .Two different Axiomcmdscale’. The first two principal co‐ordinates were plotted.The relationship between the lines was determined by calculating a pairwise similarity matrix for all lines using a custom python script. Similarity was calculated as the number of calls in common between two lines divided by total number of markers scored for the two lines; markers that had missing calls for either of the lines being compared were not used to estimate similarity. The matrix was imported into the R statistical software package version 3.3.1 , the Bayesian model‐based clustering method implemented in the program STRUCTURE version 2.3.4 (Pritchard et al., et al., et al., To investigate population structure for the Watkins Collection (File S1 Accessions used in this study.Click here for additional data file.File S2 Principal co‐ordinate plots of Watkins accessions coloured by country of origin.Click here for additional data file.File S3 Markers that are polymorphic only among Watkins accessions or elite accessions.Click here for additional data file.File S4 Number of novel SNP polymorphisms in each Watkins accession.Click here for additional data file.File S5 Principal co‐ordinate plot of Watkins accessions coloured by sowing season.Click here for additional data file.


EP 16461554.4) is related to a method of analysing a solid substrate by means of Secondary Ion Mass Spectrometry (SIMS). It comprises the steps of providing a graphene layer over the substrate surface and analysing ejected secondary anions through mass spectrometry analysis. The graphene layer acts as a kind of filament that emits a lot of secondary electrons during the experiment which significantly increases the negative ionization probability and thus the intensity of the SIMS signal can be more than two orders of magnitude higher than that of a similar sample without graphene. The method is particularly useful for the analysis of surfaces, 2D materials and ultra-thin films. The intensity of dopants and contamination signals can be enhanced up to 35 times, which approaches the detection limit of ~10 The sample is bombarded with a primary ion beam that leads to the sputtering of the surface. Small parts of the sputtered particles are ionized (secondary ions) and the sample composition can be determined by means of mass spectral analysis. During the sputtering subsequent layers of the sample are removed and thus it is possible to obtain information about changes in the composition as a function of depth, thus creating a depth profile.SIMS is a very precise analytical technique for determining the elemental composition of a sample12. For most materials it is reported to be in the range of 1015–1016atoms/cm311, sometimes even as good as 1012atoms/cm312. These optimum detection limits, however, are achieved during the dynamic SIMS (dSIMS) mode. In this mode a very dense ion beam is used and a substantial amount of material is sputtered simultaneously, allowing more ions to be detected. Drawbacks include very poor depth resolution and limitation to thick materials.SIMS is well known for its excellent detection limits of trace elements15, in which a low density ion beam ensures that ions are emitted only from monolayers 1 to 3. This mode, however, has physical limitations. Because a relatively small amount of matter is sputtered, and even less ionized, there are not enough secondary ions extracted from the sample to achieve as optimum detection limit as the dynamic mode does. In most cases it is difficult to exceed a limit of 1 ppm (5 * 1016atoms/cm3 or 109atoms/cm2).Surfaces, 2D materials and ultra-thin films are analysed ideally in a special mode called static SIMS (sSIMS)19, whereas cesium enhances the formation of negative ions20. For some elements the difference can be up to four orders of magnitude. Although most elements can be detected as both positive and negative ions, each element usually gives better results in terms of detection limit in either positive or negative mode. In some experiments, oxygen flooding can further enhance the secondary ion yields of some negative ions23. Using these techniques yields acceptable results, but in the cases of surfaces, 2D materials and ultra-thin films, it is often not enough to reach the desired detection limit, particularly in the case of trace elements.There are many ways to enhance the ionization probability and thus the detection limit. It has been noted that using oxygen as primary ions significantly enhances the formation of positive ions31. More specifically, SIMS has been used to map the surface of the graphene layer25, to analyse the mass spectra of graphene27, and to create a depth profile of single-layer graphene grown on substrates that do not contain carbon29. Furthermore, SIMS has been used for the depth profiling of multilayer graphene of a thickness of more than 3 nm on SiC30 and, recently, of hydrogen-intercalated graphene on SiC having a theoretical thickness of 0.69 nm31. All these methods employed SIMS for characterising the graphene layer, while the composition of support material underneath was not analysed.Several SIMS measurements on graphene (Gr) have already been reportedIn this work we present Graphene Enhanced Secondary Ion Mass Spectrometry (GESIMS) - a new technique for enhancing the detection limit in the analysis of thin materials. It has been found that providing a graphene layer on a substrate significantly reduces the emission of matter from the substrate but at the same time increases the negative ionization probability. Destruction of a small part of the graphene layer in a dynamic SIMS mode significantly reduces the initial strong blocking effect of graphene, while the enhancement of the ionization probability of the sputtered material is still observed. Under these conditions the ionization probability greatly prevails, resulting in an SIMS signal with an intensity that is unexpectedly high compared with a sample without graphene and thus able to to reach better detection limits.A−/A+  per incident ion. In turn, secondary ion yield is defined as the product of the partial sputter yield (number of emitted species A per incident ion) and ionization probability. The presence of graphene on a substrate surface clearly reduces the partial sputter yield of a material from the substrate, since for given conditions it is expected that sputtered species are emitted from the ~3 top monolayers of material and graphene acts as a barrier to emission. If despite this fact a significant increase in the SIMS signal intensity is still observed, the only possible explanation is that the presence of graphene drastically increases the negative ionization probability. Fig. The basic concept of GESIMS method is presented on Fig. YGr and Y denote partial sputter yield for a sample with and without graphene, respectively, while αGr and α denote ionization probabilities . Under optimum conditions YGr < Y and αGr > α, whereby the latter effect is much stronger, so that GF > 1 and thus the intensity of the SIMS signal can be enhanced.To quantify the effect, a gain factor can be defined as follows:Although increasing the intensity of the matrix element signal is of interest from a scientific viewpoint, it does not seem to have much practical application in SIMS-based surface analysis. As already mentioned above, the actual benefit is the enhancement of the detection limit of trace elements and thus new sets of samples have been considered and tested. Each of the sets consisted of a pair of samples, one having graphene transferred onto its surface, and the other - without graphene - serving as a reference. Signal enhancement was observed for all of them and the maximum gain that was reached during the experiments has been presented in Table GF = 1).As already mentioned, the effect was not observed at the beginning of the experiment, when a fresh graphene layer was transferred on a sample. This is not surprising since graphene is a strong material and the blocking effect was expected to be high. Thus the reduction in the partial sputter yield was higher than the increase of the ionization probability. To overcome it, the primary beam intensity had to be increased to several hundred pA for a short time. Under such conditions dynamic SIMS mode was achieved and the entire surface was slowly eroded. When only a small part of the graphene sheet was destroyed, the blocking effect was significantly reduced while the enhancement of the ionization probability was still observed. Figure It was essential in these experiments for the uniformity and the intensity of the beam to be well defined and reproducible and thus it was not surprising that the shape of all curves and the position of the maximum were similar for all measured samples as they depended on the partial destruction of the graphene layer and not to the type of the dopant and the substrate. Only the actual enhancement was material related (both the substrate and the type of dopant) and thus each sample had a different maximal gain factor.−8 mbar for two hours. Figure The result is fully reproducible - Fig. The best results, as presented in Table 18 atoms/cm3) and low (1 * 1016 atoms/cm3) dopant concentration . As can be clearly seen for Sample A, the intensity of the SIMS signal was significantly increased and thus a better detection limit was achieved (3.02 * 1015 instead of 4.86 * 1016 atoms/cm3). In the case of Sample B, the concentration was too low to be measured using a standard sSIMS condition, whereas it was possible for the GESIMS method. As can be seen, the enhancing effect does not depend on the dopant concentration and thus GESIMS method is quantifiable.When the optimal conditions are reached, the beam intensity should be decreased and sSIMS measurement can be performed. Figure 2+ primary beam with positive ion detection. As shown on Fig. YGr/Y ratio.The same procedure was used for a O+ ions and the gain factor change was obtained just like it was shown on Fig. + beam was switched off and a very brief sSIMS measurement with O2+ beam was performed so that the YGr/Y ratio could be determined as shown on Fig. YGr/Y ratio increased rapidly from ~0.27 to ~0.43 close to the optimal condition which apparently led to a significant increase of the gain factor.A new experiment was devised for AlGaAs substrate with Si dopant: the sample was sputtered in dSIMS mode with Cs2 which normally required an electron flood gun for charge compensation. The intensity of the Cs+ primary beam was once again set to 200 pA and it turned out that a thin layer of the amorphous carbon did not alter the experiment significantly: the charging effect was visible from the very beginning and the flood gun was needed to perform the analysis. However, in case of the graphene layer we were able to sputter the sample without the flood gun up to four an a half minutes before the charging effect occurred. It corresponded well with the time frame of the enhancement effect  and yet it was still able to provide enough electrons for charge compensation. We assumed that in a similar way the GESIMS effect could be explained: during the SIMS experiment a high voltage was applied to the sample holder (up to 5 kV) and thus the graphene layer acted as a kind of filament which emitted an excess of electrons during the ion bombardment leading to the enhanced ionization probability.From Fig. applying a graphene layer over the substrate surface;annealing the graphene-coated substrate at elevated temperature and reduced pressure;sputtering of the graphene-coated substrate in dSIMS mode, which leads to the partial destruction of the graphene layer;detecting and analysing ejected secondary anions by mass spectrometry analysis in sSIMS mode.GESIMS is a process for measuring and analysing thin substrates that involves the following steps:This method cannot be used for depth profiling of thick materials because the graphene layer will be destroyed within the first moments of the measurement and the enhancing property will be lost. Furthermore, the dSIMS analysis itself offers a high detection limit. It cannot be used for a high resolution imagining neither, since the presence of the partially destroyed graphene layer will reduce the spatial resolution. However, in the case of very thin materials, sSIMS reaches its physical limit and any enhancement is beneficial. GESIMS requires more preparation and optimization than the standard sSIMS analysis but improves by one order of magnitude the detection limits of trace elements, which may prove to be invaluable for the further development of 2D materials.The effect does not take place for samples covered with a thin layer of amorphous carbon. It has been noted that the graphene layer has different electric properties during the SIMS experiment - even a significantly destroyed layer can provide enough electrons to compensate the charging effect which is typically present for insulating materials. This behaviour can suggest the explanation of the GESIMS effect: since a high voltage is applied to the sample holder the graphene layer acts as a kind of filament and emits a lot of secondary electrons during the ion bombardment and thus the negative ionization probability is increased.A pair of samples was created for every experiment described in this work, one having graphene grown or transferred onto its surface, and the other - without graphene - serving as a reference.et al.33. As a substrate, (100)-oriented Ge layers deposited on Si (100) wafers were used. Methane gas in the mixture of Ar and H2 in the ratio of 200:1 was used as a carbon precursor. Growth was preceded by the substrate’s annealing in a pure hydrogen atmosphere in order to reduce native oxides in-situ. During the growth process, 800 mbar of pressure were sustained.In the case of germanium substrate, graphene films were synthesized in a commercially available system by the CVD method as described by Paternak μm thick copper foils by the CVD method using a Black Magic Pro system (Aixtron). To grow graphene on copper foils the following procedure was used: copper samples were first pretreated at 960 °C under an Ar gas flow and then a H2 gas flow at 20 mbar of pressure. The purpose of this step was to improve the quality and enlarge the grain size of Cu substrates as well as to remove oxides from the copper surface. Next, methane was introduced into the reactor at an adequate flow rate for a few minutes. During this step, the synthesis of graphene was observed. Finally, the copper substrates covering the graphene films were cooled to room temperature in an Ar atmosphere. To transfer graphene onto target substrates, we used the high-speed electrochemical delamination method34.In other samples, graphene films were synthesized on 35 As described in aforementioned procedures, the presence of the graphene layer was confirmed by Raman spectroscopy measurements performed in back-scattering geometry, using a Renishaw inVia Raman Microscope, with a ×100 objective and a 532 nm Nd:YAG laser as an excitation source.−10 mbar. A Cs+ primary beam with negative ion detection was used for most measurements. Impact energy was varied between 1 keV and 13 keV but the highest energy was used for the most of the experiments. The intensity of the primary beam was 100–2000 pA and 0.5–10 pA for the dynamic and static SIMS mode, respectively. An O2+ primary beam with positive ion detection was used for a few experiments to show that graphene do not enhance the positive ionization probability. Impact energy was varied between 2 keV and 5 keV and the intensity of the primary beam was 300–3000 pA and 3–10 pA for the dynamic and static SIMS mode, respectively. Primary beams were rastered over 250 × 250 μm2 and the analysis area was limited to (200 × 200) μm2. Mass interferences were verified prior to analysis and adequate mass resolving power was used for each experiment.In this work all SIMS measurements were performed employing the CAMECA SC Ultra instrument under ultra-high vacuum (UHV), usually of 4 × 1037.Beam on the sample in the SC Ultra tool has a square shape and owning to the “variable rectangular shape concept” forms a homogeneous spot. The primary beam at the working point in the SC Ultra is formed by two stencils - well-shaped apertures. While the first one is used to choose the most intense and homogeneous part of the ion beam, the second one changes the size of the spot. This innovation provides high sensitivity for all measured elements and a high dynamic range with a very low sputter rate12 ions/cm2). This ensures that with a high probability every ion will impact on undamaged surface and not on an area that has already received ion impacts. In this mode, the emission is essentially limited to a few topmost monolayers and thus it is very surface-sensitive. It makes it an ideal mode for the analysis of surfaces, 2D materials and ultra-thin films because there is no interference with the lower layers. In dynamic SIMS mode the emission is theoretically still limited to the topmost monolayers but for higher ion doses it is expected that the whole surface will erode in time and thus the lower layer will be gradually exposed. In this way it is possible to obtain information on the variation of the composition of material below the initial surface, thereby creating so-called depth profiles. In this work, however, the dynamic SIMS mode was used to destroy only partially the graphene layer in order to expose the underlying substrate, which was subjected for further analysis. It was a critical step to ensure good reproducibility of the results and therefore a very homogeneous ion beam was required to perform GESIMS analysis.Secondary ions that are detected in SIMS analysis usually originate from the top three monolayers of the bombarded sample. For static SIMS analysis, very low ion doses are used (typically in range of 10