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The SADQ-H, SADQ-H10 and SODS were all appropriate for screening for possible depression after stroke but not for screening for possible anxiety. The SADQ-H 10 had greater internal consistency and higher sensitivity and specificity than the SODS and is shorter than the SADQ-H. It was also significantly correlated with both the anxiety and depression scales of the HADS. The SADQ-H 10 was therefore recommended as the most appropriate for screening purposes. The VAMS and VASES provided no clear cut-offs for use in screening but scores were highly correlated with the HADS. They are therefore more suitable for assessing severity of low mood rather than for screening purposes. The cut-offs identified need further validation in an independent sample of stroke patients, including a higher proportion with low mood.

Case complexity as a guide for psychological treatment selection. Journal of Consulting and Clinical Psychology, 85 (9). pp. 835-853. ISSN 0022-006X https://doi.org/10.1037/ccp0000231 eprints@whiterose.ac.uk https://eprints.whiterose.ac.uk/ Reuse Unless indicated otherwise, fulltext items are protected by copyright with all rights reserved. The copyright exception in section 29 of the Copyright, Designs and Patents Act 1988 allows the making of a single copy solely for the purpose of non-commercial research or private study within the limits of fair dealing. The publisher or other rights-holder may allow further reproduction and re-use of this version -refer to the White Rose Research Online record for this item. Where records identify the publisher as the copyright holder, users can verify any specific terms of use on the publisher's website. TakedownIf you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing eprints@whiterose.ac.uk including the URL of the record and the reason for the withdrawal request. AbstractObjective: Some cases are thought to be more complex and difficult to treat, although there is little consensus on how to define complexity in psychological care. This study proposes an actuarial, data-driven method of identifying complex cases based on their individual characteristics.Method: Clinical records for 1512 patients accessing low and high intensity psychological treatments were partitioned in 2 random subsamples. Prognostic indices (PI) predicting post-treatment reliable and clinically significant improvement (RCSI) in depression (PHQ-9) and anxiety (GAD-7) symptoms were estimated in one subsample using penalized (Lasso) regressions with optimal scaling. A PI-based algorithm was used to classify patients as standard (St) or complex (Cx) cases in the second (cross-validation) subsample. RCSI rates were compared between Cx cases that accessed treatments of different intensities using logistic regression.Results: St cases had significantly higher RCSI rates compared to Cx cases (OR = 1.81 to 2.81). Cx cases tended to attain better depression outcomes if they were initially assigned to high intensity (vs. low intensity) interventions (OR = 2.23); a similar pattern was observed for anxiety but the odds ratio (1.74) was not statistically significant. Conclusions:Complex cases could be detected early and matched to high intensity interventions to improve outcomes. 3What is the public health significance of this article?Complex cases tend to have a poor prognosis after psychological treatment for depression and anxiety problems. An evidence-based model of defining complexity is proposed to guide therapists in matching patients to treatments of differing intensity. The findings indicate that this personalized method of treatment selection could lead to better outcomes for complex cases and could improve upon decisions that are informed by clinical judgment alone.

Depression and anxiety are common problems after stroke. The National Clinical Guidelines for stroke (Royal College Physicians, 2004) recommend that all patients are screened for low mood. The aim of the review was to identify measures which could be used for this purpose and to review the evidence for their sensitivity and specificity with stroke patients. A literature search was conducted using electronic databases, including Medline, Embase, PsycInfo and CINAHL, to identify articles published in peer reviewed journals on mood assessment after stroke. Questionnaire measures were identified which were appropriate only for those able to communicate verbally. In addition visual analogue and observer rating scales were identified which were considered appropriate for all stroke patients. The hospital anxiety and depression scale (HADS) and general health questionnaire (GHQ) had most evidence to support their use as screening measures for people without communication problems. The stroke aphasic depression questionnaire–hospital version (SADQ-H) had best support for use as a screening measure for those with communication problems. No measures were identified that had been validated as screening measures for anxiety after stroke. The HADS, GHQ12 and SADQ-H10 were recommended as short screening measures suitable for detecting depression after stroke. However the cut-offs giving good sensitivity and specificity were not well established for stroke patients and measures need to be developed for detecting anxiety.

Purpose Given the considerable variation in treatment effectiveness observed across Improving Access to Psychological Therapy (IAPT) services, the purpose of this study is to explore client- and service-related variables that predict successful treatment outcomes and clients’ dropout. Clinician-rated clients’ motivation to change was also explored as a potential predictor for both outcome variables. Design/methodology/approach A convenience sample of 1,135 (F = 752; Mage = 39.4) was collected from three IAPT services in the North West of England. The study adopts a quasi-experimental, observational design. The analysis involves the description of patients’ socio-demographic and clinical characteristics and the development of three outcome prediction models, using hierarchical logistic regression. Findings After adjusting for confounders, employment status and motivation to change as rated by clinicians were predictive of both recovery and reliable improvement. The higher number of IAPT re-referrals was negatively associated with recovery and positively with dropouts. Clients who indicated low motivation to change and received low intensity treatment at their last session presented a higher likelihood to dropout. Research limitations/implications Given that the evaluation of clients’ motivation to change was solely reliant on clinical judgement, as no validated measure was used, further robust research is recommended to draw sensible conclusions. Originality/value This is the first study evaluating clinician-rated motivation to change as a significant predictor of treatment outcomes and dropouts within the IAPT setting. Further research implications are discussed.