Protocol for a pilot cluster randomised controlled trial of a multicomponent sustainable return to work IGLOo intervention.

BACKGROUND: Long-term sickness costs businesses in the United Kingdom (UK) approximately £7 billion per annum. Most long-term sickness absences are attributed to common mental health conditions, which are also highly prevalent in people with acute or musculoskeletal health conditions. This study will pilot the IGLOo (Individual, Group, Leaders, Organisation, overarching context) intervention which aims to support workers in returning to and remaining in work following long-term sickness absence. The potential impact of the intervention is a timely return to work (main trial primary outcome) and prevention of a further episode of long-term sick leave. The intervention will be piloted in a randomised controlled trial (RCT) to examine the feasibility of the intervention (pilot trial primary outcome) and to inform a fully powered definitive trial to evaluate sustainable return to work (RTW) in people with primary or secondary mental ill-health who go on long-term sick leave. METHODS AND DESIGN: A two-arm feasibility randomised controlled trial (with a 30-month study period including 12-month follow-up) of the IGLOo intervention will be conducted in large organisations (≥ 600 workers) from the Yorkshire and Humberside regions, in the UK. Eight consenting organisations will be recruited and randomised to the intervention or control arms of the study (1:1 ratio), with a minimum recruitment target of 13 workers eligible to participate from each. Organisations assigned to the control group will continue with their usual practice. Feasibility data will include data collected on recruitment, retention and attrition of participants; completion of research outcome measures; and intervention compliance. Measurements of mental health, RTW, work outcomes, quality-of-life, workplace support and communication and other demographic data will be taken at baseline, 3, 6, 9 and 12 months in all participants. Qualitative interviews and survey data with all participants will explore the experiences of participants, acceptability of the intervention components and evaluation measures. Exploratory economic evaluation will be conducted to further inform a definitive trial. DISCUSSION: The findings from this pilot study will help to inform the development of a definitive cluster RCT designed to examine the efficacy of this intervention on health and work-related outcomes in UK workers on long-term sick leave. TRIAL REGISTRATION: ISRCTN11788559 (prospectively registered, date registered 6 October 2022).

Cognitive-behavioural versus cognitive-analytic guided self-help for mild-to-moderate anxiety: a pragmatic, randomised patient preference trial.

BACKGROUND: Guided self-help (GSH) for anxiety is widely implemented in primary care services because of service efficiency gains, but there is also evidence of poor acceptability, low effectiveness and relapse. AIMS: The aim was to compare preferences for, acceptability and efficacy of cognitive-behavioural guided self-help (CBT-GSH) versus cognitive-analytic guided self-help (CAT-GSH). METHOD: This was a pragmatic, randomised, patient preference trial (Clinical trials identifier: NCT03730532). The Beck Anxiety Inventory (BAI) was the primary outcome at 8- and 24-week follow-up. Interventions were delivered competently on the telephone via structured workbooks over 6-8 (30-35 min) sessions by trained practitioners. RESULTS: A total of 271 eligible participants were included, of whom 19 (7%) accepted being randomised and 252 (93%) chose their treatment. In the preference cohort, 181 (72%) chose CAT-GSH and 71 (28%) preferred CBT-GSH. BAI outcomes in the preference and randomised cohorts did not differ at 8 weeks (-0.80, 95% confidence interval (CI) -4.52 to 2.92) or 24 weeks (0.85, 95% CI -2.87 to 4.57). After controlling for allocation method and baseline covariates, there were no differences between CAT-GSH and CBT-GSH at 8 weeks (F(1, 263) = 0.22, P = 0.639) or at 24 weeks (F(1, 263) = 0.22, P = 0.639). Mean BAI change from baseline was a reduction of 9.28 for CAT-GSH and 9.78 for CBT-GSH at 8 weeks and 12.90 for CAT-GSH and 12.43 for CBT-GSH at 24 weeks. CONCLUSIONS: Patients accessing routine primary care talking treatments prefer to choose the intervention they receive. CAT-GSH expands the treatment offer in primary care for patients with anxiety seeking a brief but analytically informed GSH solution.

The role of socioeconomic deprivation in explaining neighborhood and clinic effects in the effectiveness of psychological interventions.

OBJECTIVE: Treatment outcomes are known to vary according to therapist and clinic/organization (therapist effect, clinic effect). Outcomes may also vary according to the neighborhood where a person lives (neighborhood effect), but this has not previously been formally quantified. Evidence suggests that deprivation may contribute to explaining such cluster effects. This study aimed to (a) simultaneously quantify neighborhood, clinic, and therapist effects on intervention effectiveness and (b) determine the extent to which deprivation variables explain neighborhood and clinic effects. METHOD: The study used a retrospective, observational cohort design with a high intensity psychological intervention sample (N = 617,375), and a low intensity (LI) psychological intervention sample (N = 773,675). Samples each included 55 clinics, 9,000-10,000 therapists/practitioners, and over 18,000 neighborhoods in England. Outcomes were postintervention depression and anxiety scores and clinical recovery. Deprivation variables included individual employment status, domains of neighborhood deprivation, and clinic-level mean deprivation. Data were analyzed using cross-classified multilevel models. RESULTS: Unadjusted neighborhood effects of 1%-2% and unadjusted clinic effects of 2%-5% were detected, with proportionally larger effects for LI interventions. After controlling for predictors, adjusted neighborhood effects of 0.0%-0.1% and clinic effects of 1%-2% remained. Deprivation variables were able to explain a significant proportion of the neighborhood effect (80%-90% of neighborhood variance) but not clinic effect. The majority of neighborhood variance could only be explained by a shared effect of baseline severity and socioeconomic deprivation variables. CONCLUSIONS: People in different neighborhoods respond differently to psychological intervention, and this clustering effect was mainly explained by socioeconomic factors. People also respond differently according to the clinic they access, but this could not be completely explained by deprivation in the present study. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Cost-effectiveness of feedback-informed psychological treatment: Evidence from the IAPT-FIT trial.

BACKGROUND: Feedback-informed treatment (FIT) involves using computerized routine outcome monitoring technology to alert therapists to cases that are not responding well to psychotherapy, prompting them to identify and resolve obstacles to improvement. In this study, we present the first health economic evaluation of FIT, compared to usual care, to enable decision makers to judge whether this approach represents a good investment for health systems. METHODS: This randomised controlled trial included 2233 patients clustered within 77 therapists who were randomly assigned to a FIT group (n = 1176) or a usual care control group (n = 1057). Treatment response was monitored using patient-reported depression (PHQ-9) and anxiety (GAD-7) measures. Therapists in the FIT group had access to a computerized algorithm that alerted them to cases that were "not on track", compared to normative clinical data. Health service costs included the cost of training therapists to use FIT and the cost of therapy sessions in each arm. The incremental cost-effectiveness of FIT was assessed relative to usual care, using multilevel modelling. RESULTS: FIT was associated with an increased probability of reliable symptomatic improvement by 8.09 percentage points (95% CI: 4.16%-12.03%) which was statistically significant. The incremental cost of FIT was £15.17 (95% CI: £6.95 to £37.29) per patient and was not statistically significant. The incremental cost-effectiveness ratio (ICER) per additional case of reliable improvement was £187.4 (95% CI: £126.7 to £501.5); this confidence interval shows that the relative cost-effectiveness is between FIT being a dominant strategy (i.e. more effective and also cost-saving) to FIT being more effective at a modest incremental cost to the health system. CONCLUSIONS: The FIT strategy increases the probability of reliable improvement in routine clinical practice and may be associated with a small (but uncertain) incremental cost. FIT is likely to be a cost-effective strategy for mental health services.

Towards personalized allocation of patients to therapists.

OBJECTIVE: Psychotherapy outcomes vary between therapists, but it is unclear how such information can be used for treatment planning or practice development. This proof-of-concept study aimed to develop a data-driven method to match patients to therapists. METHOD: We analyzed data from N = 4,849 patients who accessed cognitive-behavioral therapy in U.K. primary care services. The main outcome was posttreatment reliable and clinically significant improvement (RCSI) on the Patient Health Questionnaire-9 (PHQ-9) depression measure. Machine-learning analyses were applied in a training sample (N = 2,425 patients treated by 68 therapists in Year 1), including a chi-squared automatic interaction detector (CHAID) algorithm and a random forest (RF) algorithm. The predictive models were cross-validated in a statistically independent test sample (N = 2,424 patients treated by the same therapists in Year 2) and evaluated using odds ratios (ORs) adjusted for baseline depression severity. RESULTS: We identified subgroups of therapists that were differentially effective for highly specific subgroups of patients, yielding 17 classes of patient-to-therapist matches. The overall base rate of RCSI in the sample was 40.4%, but this varied from 10.5% to 69.9% across classes. Cases classed by the prediction algorithms as expected responders in the test sample were ∼60% more likely to attain posttreatment RCSI compared with those classed as nonresponders (adjusted ORs = 1.59, 1.60; p < .001). CONCLUSIONS: Machine-learning approaches could help to improve treatment outcomes by enabling the strategic allocation of patients to therapists and therapists to supervisors. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Why are some cases not on track? An item analysis of the Assessment for Signal Cases during inpatient psychotherapy.

Within the Routine Outcome Monitoring system "OQ-Analyst," the questionnaire "Assessment for Signal Cases" (ASC) supports therapists in detecting potential reasons for not-on-track trajectories. Factor analysis and a machine learning algorithm (LASSO with 10-fold cross-validation) were applied, and potential predictors of not-on-track classifications were tested using logistic multilevel modeling methods. The factor analysis revealed a shortened (30 items) version of the ASC with good internal consistency (α = 0.72-0.89) and excellent predictive value (area under the curve = 0.98; positive predictive value = 0.95; negative predictive value = 0.94). Item-level analyses showed that interpersonal problems captured by specific ASC items (not feeling able to speak about problems with family members; feeling rejected or betrayed) are the most important predictors of not-on-track trajectories. It should be considered that our results are based on analyses of ASC items only. Our findings need to be replicated in future studies including other potential predictors of not-on-track trajectories (e.g., changes in medication, specific therapeutic techniques, or treatment adherence), which were not measured this study.

The influence of socio-demographic similarity and difference on adequate attendance of group psychoeducational cognitive behavioural therapy.

Aim: The study aimed to investigate the impact of socio-demographic similarity on the probability of attending an adequate dose of a psychoeducational group intervention (≥4 of 6 sessions). Method: The sample comprised 2071 patients (63% female, 93% White, 15% unemployed, mean age 43) who received the Stress Control intervention in the UK's national Improving Access to Psychological Therapies (IAPT) programme. Similarity indices were constructed to measure each patient's similarity to the rest of their group on four characteristics: age, gender, ethnicity, and neighbourhood deprivation (Index of Multiple Deprivation; IMD). Results: Multilevel analysis found that patients with greater IMD similarity to their group had significantly higher probabilities of attending an adequate dose of intervention (p = .026, controlling for absolute IMD). A cumulative effect of age similarity, ethnic similarity, and group size was also found, such that patients who were similar in age and ethnicity to their group had higher probabilities of adequate attendance in larger groups (p = .006). Conclusions: These results suggest that socio-demographic comparison (a.k.a. relational demography) may consciously or unconsciously impact on patients' attendance at group psychoeducational interventions, particularly regarding indicators of socio-economic similarity. Clinical implications include structuring group composition and/or intervention content to maximise attendance and therefore clinical effectiveness.

Feedback-informed treatment versus usual psychological treatment for depression and anxiety: a multisite, open-label, cluster randomised controlled trial.

BACKGROUND: Previous research suggests that the use of outcome feedback technology can enable psychological therapists to identify and resolve obstacles to clinical improvement. We aimed to assess the effectiveness of an outcome feedback quality assurance system applied in stepped care psychological services. METHODS: This multisite, open-label, cluster randomised controlled trial was done at eight National Health Service (NHS) Trusts in England, involving therapists who were qualified to deliver evidence-based low-intensity or high-intensity psychological interventions. Adult patients (18 years or older) who accessed individual therapy with participating therapists were eligible for inclusion, except patients who accessed group therapies and those who attended less than two individual therapy sessions. Therapists were randomly assigned (1:1) to an outcome feedback intervention group or a treatment-as-usual control group by use of a computer-generated randomisation algorithm. The allocation of patients to therapists was quasi-random, whereby patients on waiting lists were allocated sequentially on the basis of therapist availability. All patients received low-intensity (less than eight sessions) or high-intensity (up to 20 sessions) psychological therapies for the duration of the 1-year study period. An automated computer algorithm alerted therapists in the outcome feedback group to patients who were not on track, and primed them to review these patients in clinical supervision. The primary outcome was symptom severity on validated depression (Patient Health Questionnaire-9 [PHQ-9]) and anxiety (Generalised Anxiety Disorder-7 [GAD-7]) measures after treatment of varying durations, which were compared between groups with multilevel modelling, controlling for cluster (therapist) effects. We used an intention-to-treat approach. This trial was prospectively registered with ISRCTN, number ISRCTN12459454. FINDINGS: In total, 79 therapists were recruited to the study between Jan 8, 2016, and July 15, 2016, but two did not participate. Of these participants, 39 (51%) were randomly assigned to the outcome feedback group and 38 (49%) to the control group. Overall, 2233 patients were included in the trial (1176 [53%] were treated by therapists in the outcome feedback group, and 1057 [47%] by therapists in the control group). Patients classified as not on track had less severe symptoms after treatment if they were allocated to the outcome feedback group than those in the control group (PHQ-9 d=0·23, B=-1·03 [95% CI -1·84 to -0·23], p=0·012; GAD-7 d=0·19, B=-0·85 [-1·56 to -0·14], p=0·019). INTERPRETATION: Supplementing psychological therapy with low-cost feedback technology can reduce symptom severity in patients at risk of poor response to treatment. This evidence supports the implementation of outcome feedback in stepped care psychological services. FUNDING: English NHS and Department of Health Sciences, University of York, York, UK.

Associations between socioeconomic status and psychological therapy outcomes: A systematic review and meta-analysis.

BACKGROUND: Socioeconomic deprivation is associated with higher prevalence of mental health problems; however, the influence of socioeconomic status (SES) on psychological therapy outcomes is as yet unclear. AIM: To review published evidence on the association between indicators of SES (income, education, employment, neighborhood deprivation, social position) and the outcomes of psychological interventions for depression and anxiety. METHODS: Systematic review and meta-analysis of outcomes research studies published in the last 10 years. RESULTS: Seventeen studies including 165,574 patients measured at least one indicator of SES and its relationship with psychological therapy outcomes. Twelve of these studies found significant relationships between SES measures and mental health outcomes. Six studies focusing on employment status offered sufficient quantitative information to conduct meta-analysis. The overall effect of employment was not significant (-0.66, confidence of interval (CI) -1.33, 0.02). A sensitivity analysis (k = 5) showed a small effect (-0.22, CI -0.36, -0.09) of employment on treatment outcomes. CONCLUSIONS: There is some evidence to indicate that socioeconomic deprivation is associated with poorer treatment outcomes, although limitations of the available data warrant treating this as a preliminary conclusion.

CollAborative care for Screen-Positive EldeRs with major depression (CASPER plus): a multicentred randomised controlled trial of clinical effectiveness and cost-effectiveness.

BACKGROUND: Depression in older adults is common and is associated with poor quality of life, increased morbidity and early mortality, and increased health and social care use. Collaborative care, a low-intensity intervention for depression that is shown to be effective in working-age adults, has not yet been evaluated in older people with depression who are managed in UK primary care. The CollAborative care for Screen-Positive EldeRs (CASPER) plus trial fills the evidence gap identified by the most recent guidelines on depression management. OBJECTIVES: To establish the clinical effectiveness and cost-effectiveness of collaborative care for older adults with major depressive disorder in primary care. DESIGN: A pragmatic, multicentred, two-arm, parallel, individually randomised controlled trial with embedded qualitative study. Participants were automatically randomised by computer, by the York Trials Unit Randomisation Service, on a 1 : 1 basis using simple unstratified randomisation after informed consent and baseline measures were collected. Blinding was not possible. SETTING: Sixty-nine general practices in the north of England. PARTICIPANTS: A total of 485 participants aged ≥ 65 years with major depressive disorder. INTERVENTIONS: A low-intensity intervention of collaborative care, including behavioural activation, delivered by a case manager for an average of six sessions over 7-8 weeks, alongside usual general practitioner (GP) care. The control arm received only usual GP care. MAIN OUTCOME MEASURES: The primary outcome measure was Patient Health Questionnaire-9 items score at 4 months post randomisation. Secondary outcome measures included depression severity and caseness at 12 and 18 months, the EuroQol-5 Dimensions, Short Form questionnaire-12 items, Patient Health Questionnaire-15 items, Generalised Anxiety Disorder-7 items, Connor-Davidson Resilience Scale-2 items, a medication questionnaire, objective data and adverse events. Participants were followed up at 12 and 18 months. RESULTS: In total, 485 participants were randomised (collaborative care, n = 249; usual care, n = 236), with 390 participants (80%: collaborative care, 75%; usual care, 86%) followed up at 4 months, 358 participants (74%: collaborative care, 70%; usual care, 78%) followed up at 12 months and 344 participants (71%: collaborative care, 67%; usual care, 75%) followed up at 18 months. A total of 415 participants were included in primary analysis (collaborative care, n = 198; usual care, n = 217), which revealed a statistically significant effect in favour of collaborative care at the primary end point at 4 months [8.98 vs. 10.90 score points, mean difference 1.92 score points, 95% confidence interval (CI) 0.85 to 2.99 score points; p < 0.001], equivalent to a standard effect size of 0.34. However, treatment differences were not maintained in the longer term (at 12 months: 0.19 score points, 95% CI -0.92 to 1.29 score points; p = 0.741; at 18 months: < 0.01 score points, 95% CI -1.12 to 1.12 score points; p = 0.997). The study recorded details of all serious adverse events (SAEs), which consisted of 'unscheduled hospitalisation', 'other medically important condition' and 'death'. No SAEs were related to the intervention. Collaborative care showed a small but non-significant increase in quality-adjusted life-years (QALYs) over the 18-month period, with a higher cost. Overall, the mean cost per incremental QALY for collaborative care compared with usual care was £26,016; however, for participants attending six or more sessions, collaborative care appears to represent better value for money (£9876/QALY). LIMITATIONS: Study limitations are identified at different stages: design (blinding unfeasible, potential contamination), process (relatively low overall consent rate, differential attrition/retention rates) and analysis (no baseline health-care resource cost or secondary/social care data). CONCLUSION: Collaborative care was effective for older people with case-level depression across a range of outcomes in the short term though the reduction in depression severity was not maintained over the longer term of 12 or 18 months. Participants who received six or more sessions of collaborative care did benefit substantially more than those who received fewer treatment sessions but this difference was not statistically significant. FUTURE WORK RECOMMENDATIONS: Recommendations for future research include investigating the longer-term effect of the intervention. Depression is a recurrent disorder and it would be useful to assess its impact on relapse and the prevention of future case-level depression. TRIAL REGISTRATION: Current Controlled Trials ISRCTN45842879. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 21, No. 67. See the NIHR Journals Library website for further project information.

The Role of Practice Research Networks (PRN) in the Development and Implementation of Evidence: The Northern Improving Access to Psychological Therapies PRN Case Study.

Practice research networks (PRNs) can support the implementation of evidence based practice in routine services and generate practice based evidence. This paper describes the structure, processes and learning from a new PRN in the Improving Access to Psychological Therapies programme in England, in relation to an implementation framework and using one study as a case example. Challenges related to: ethics and governance processes; communications with multiple stakeholders; competing time pressures and linking outcome data. Enablers included: early tangible outputs and impact; a collaborative approach; engaging with local research leads; clarity of processes; effective dissemination; and committed leadership.

CollAborative care and active surveillance for Screen-Positive EldeRs with subthreshold depression (CASPER): a multicentred randomised controlled trial of clinical effectiveness and cost-effectiveness.

BACKGROUND: Efforts to reduce the burden of illness and personal suffering associated with depression in older adults have focused on those with more severe depressive syndromes. Less attention has been paid to those with mild disorders/subthreshold depression, but these patients also suffer significant impairments in their quality of life and level of functioning. There is currently no clear evidence-based guidance regarding treatment for this patient group. OBJECTIVES: To establish the clinical effectiveness and cost-effectiveness of a low-intensity intervention of collaborative care for primary care older adults who screened positive for subthreshold depression. DESIGN: A pragmatic, multicentred, two-arm, parallel, individually randomised controlled trial with a qualitative study embedded within the pilot. Randomisation occurred after informed consent and baseline measures were collected. SETTING: Thirty-two general practitioner (GP) practices in the north of England. PARTICIPANTS: A total of 705 participants aged ≥ 75 years during the pilot phase and ≥ 65 years during the main trial with subthreshold depression. INTERVENTIONS: Participants in the intervention group received a low-intensity intervention of collaborative care, which included behavioural activation delivered by a case manager for an average of six sessions over 7-8 weeks, alongside usual GP care. Control-arm participants received only usual GP care. MAIN OUTCOME MEASURES: The primary outcome measure was a self-reported measure of depression severity, the Patient Health Questionnaire-9 items PHQ-9 score at 4 months post randomisation. Secondary outcome measures included the European Quality of Life-5 Dimensions, Short Form questionnaire-12 items, Patient Health Questionnaire-15 items, Generalised Anxiety Disorder seven-item scale, Connor-Davidson Resilience Scale two-item version, a medication questionnaire and objective data. Participants were followed up for 12 months. RESULTS: In total, 705 participants were randomised (collaborative care n = 344, usual care n = 361), with 586 participants (83%; collaborative care 76%, usual care 90%) followed up at 4 months and 519 participants (74%; collaborative care 68%, usual care 79%) followed up at 12 months. Attrition was markedly greater in the collaborative care arm. Model estimates at the primary end point of 4 months revealed a statistically significant effect in favour of collaborative care compared with usual care [mean difference 1.31 score points, 95% confidence interval (CI) 0.67 to 1.95 score points; p < 0.001]. The difference equates to a standard effect size of 0.30, for which the trial was powered. Treatment differences measured by the PHQ-9 were maintained at 12 months' follow-up (mean difference 1.33 score points, 95% CI 0.55 to 2.10 score points; p = 0.001). Base-case cost-effectiveness analysis found that the incremental cost-effectiveness ratio was £9633 per quality-adjusted life-year (QALY). On average, participants allocated to collaborative care displayed significantly higher QALYs than those allocated to the control group (annual difference in adjusted QALYs of 0.044, 95% bias-corrected CI 0.015 to 0.072; p = 0.003). CONCLUSIONS: Collaborative care has been shown to be clinically effective and cost-effective for older adults with subthreshold depression and to reduce the proportion of people who go on to develop case-level depression at 12 months. This intervention could feasibly be delivered in the NHS at an acceptable cost-benefit ratio. Important future work would include investigating the longer-term effect of collaborative care on the CASPER population, which could be conducted by introducing an extension to follow-up, and investigating the impact of collaborative care on managing multimorbidities in people with subthreshold depression. TRIAL REGISTRATION: Current Controlled Trials ISRCTN02202951. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 21, No. 8. See the NIHR Journals Library website for further project information.

Can Low-Cost Strategies Improve Attendance Rates in Brief Psychological Therapy? Double-Blind Randomized Controlled Trial.

OBJECTIVES: To assess if telephone text message appointment reminders and orientation leaflets can increase the proportion of patients who attend brief interventions after being assessed as suitable for guided self-help following cognitive behavioral therapy principles. METHOD: Attendance was operationally defined as having accessed at least 1 therapy appointment. A secondary outcome was the proportion of attenders who completed or dropped out of therapy. After initial assessment, 254 patients with depression and anxiety disorders were randomly assigned to 1 of 3 groups: (a) usual waitlist control, (b) leaflet, (c) leaflet plus text message. Differences in the proportions of patients who started and completed therapy across groups were assessed using chi-square and logistic regression analyses. RESULTS: Overall, 63% of patients in this sample attended therapy. Between-group differences were not significant for attendance, x(2) (2) = 3.94, p = .14, or completion rates, x(2) (2) = 2.98, p = .23. These results were not confounded by demographic or clinical characteristics. CONCLUSIONS: Low-cost strategies appear to make no significant difference to therapy attendance and completion rates.

Confidence in the face of risk: the Risk Assessment and Management Self-Efficacy Study (RAMSES).

Aims and method To evaluate a comprehensive risk management programme. A Risk Assessment and Management Self-Efficacy Scale (RAMSES) was used to evaluate the impact of a clinical guideline and training course. Fifty-three psychological therapists were randomly allocated to training v. waiting list in a controlled, delayed-intervention design. Differences in mean self-efficacy scores between groups were examined using analysis of covariance (ANCOVA). Results The RAMSES measure had adequate factor structure, internal consistency and construct validity. When adjusting for baseline scores and cluster design, the group exposed to training had a higher mean self-efficacy score than controls. Mean differences between groups were not significant after the control group received training, nor at 6 months' follow-up. Clinical implications Exposure to training and clinical guidelines can improve self-efficacy in risk assessment and management. An important advance put forward by this study is the specification of areas of competence in risk assessment and management, which can be measured using a psychometrically sound tool.

Benchmarking routine psychological services: a discussion of challenges and methods.

BACKGROUND: Policy developments in recent years have led to important changes in the level of access to evidence-based psychological treatments. Several methods have been used to investigate the effectiveness of these treatments in routine care, with different approaches to outcome definition and data analysis. AIMS: To present a review of challenges and methods for the evaluation of evidence-based treatments delivered in routine mental healthcare. This is followed by a case example of a benchmarking method applied in primary care. METHOD: High, average and poor performance benchmarks were calculated through a meta-analysis of published data from services working under the Improving Access to Psychological Therapies (IAPT) Programme in England. Pre-post treatment effect sizes (ES) and confidence intervals were estimated to illustrate a benchmarking method enabling services to evaluate routine clinical outcomes. RESULTS: High, average and poor performance ES for routine IAPT services were estimated to be 0.91, 0.73 and 0.46 for depression (using PHQ-9) and 1.02, 0.78 and 0.52 for anxiety (using GAD-7). Data from one specific IAPT service exemplify how to evaluate and contextualize routine clinical performance against these benchmarks. CONCLUSIONS: The main contribution of this report is to summarize key recommendations for the selection of an adequate set of psychometric measures, the operational definition of outcomes, and the statistical evaluation of clinical performance. A benchmarking method is also presented, which may enable a robust evaluation of clinical performance against national benchmarks. Some limitations concerned significant heterogeneity among data sources, and wide variations in ES and data completeness.