Case complexity as a guide for psychological treatment selection.

Abstract

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.

Dose‐response patterns in low and high intensity cognitive behavioral therapy for common mental health problems

“…Other studies in primary care services which included HiCBT (among other treatments) have found an upper boundary ranging between 11 and 14 sessions (Howard et al, 1986; Wolgast, Lambert, & Puschner, 2003). As expected, predictors of time‐to‐remission were highly consistent with the prognostic factors highlighted by previous studies in similar services (Delgadillo et al, 2017; Delgadillo, Kellett et al, 2016; Delgadillo, Moreea et al, 2016). LiCBT adequate dose parameters were homogeneous across diagnostic groups; however, patients with social anxiety disorder, OCD and PTSD had poor response rates (<25%).…”

“…However, gradual responders require more sessions to benefit and tend to require HiCBT. Identifying the characteristics of these gradual responders (e.g., more complex cases) could inform the development of stratified models of care, in which such cases are immediately assigned to more intensive/longer treatments (Delgadillo et al, 2017; Delgadillo, Moreea et al, 2016). The case for stratified care is further supported by the present results, since the probability of improvement was comparable between cases that were directly allocated to HiCBT (stratified care) and cases that accessed the full stepped care pathway—which is lengthier and costly.…”

“…Cox regressions identified variables that might influence the relationship between treatment duration and outcomes. Candidate predictors were determined a priori, informed by previous outcome‐prediction studies in stepped care psychological services (Delgadillo et al, 2014; Delgadillo, Huey, Bennett, & McMillan, 2017; Delgadillo, Moreea, & Lutz, 2016). The regression models for HiCBT cases additionally included a variable that contrasted cases that did or did not access prior LiCBT in their treatment pathway, to assess if accessing consecutive stepped care interventions influenced the dose‐response findings.…”

“…However, gradual responders require more sessions to benefit and tend to require HiCBT. Identifying the characteristics of these gradual responders (e.g., more complex cases) could inform the development of stratified models of care, in which such cases are immediately assigned to more intensive/longer treatments (Delgadillo et al, 2017;Delgadillo, Moreea et al, 2016).…”

Individual treatment selection for patients with posttraumatic stress disorder

“…Until now, most of the PAI studies used a prescriptive approach (e.g., DeRubeis et al., ; Huibers et al., ). Others suggested using prognostic models in large observational treatment studies to answer questions concerning personalized predictions (e.g., Delgadillo et al., ; Kessler et al., ). Up to this point, there is no empirical evidence to guide us on the relative strengths, weaknesses, or differences between these modeling strategies.…”