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CBT for schizophrenia: a critical viewpoint

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S Jauhar, K R Laws, P J McKenna

Original languageEnglish
Pages (from-to)1233-1236
Number of pages4
JournalPsychological Medicine
Volume49
Issue number8
Early online date13 Feb 2019
DOIs
Accepted/In press19 Dec 2018
E-pub ahead of print13 Feb 2019
PublishedJun 2019

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Abstract

In England and Wales, cognitive behavioral therapy (cognitive therapy, CBT) has been part of official treatment guidelines for schizophrenia since 2002 (NICE, 2009, p. 212). The 2014 NICE guideline (NICE, 2014), which is based on the same meta-analytic evidence as its predecessor in 2009, recommends that it be offered to all people with schizophrenia, including first-episode patients and those with established illness, and to patients who are actively symptomatic and in remission. Similar recommendations are to be found in the Scottish SIGN guideline (SIGN, 2013) as well as those of several other countries (Rathod et al., 2010). In 2012, however, the Cochrane collaboration sounded a discordant note, concluding that '[t]rial-based evidence suggests no clear and convincing advantage for cognitive behavioural therapy over other-and sometimes much less sophisticated-therapies for people with schizo-phrenia' (Jones et al., 2012). A further challenge came from a 2014 meta-analysis carried out by ourselves (Jauhar et al., 2014), which found end of treatment effect sizes (ESs) that were uniformly in the small range [overall symptoms: 0.33 (95% CI 0.19-0.47), 34 studies; positive symptoms: 0.25 (95% CI 0.13-0.37), 33 studies; negative symptoms: 0.13 (95% CI 0.01-0.25), 34 studies] (note these and all further ESs are shown as a positive sign favoring CBT). A 2018 network meta-analysis of various psychological interventions to reduce positive symptoms in schizophrenia (Bighelli et al., 2018), carried out on a rather different dataset of 27 studies than us, again found pooled ESs for CBT in the small range, though this time at the upper end of this [v. treatment as usual (TAU): 0.30 (95% CI 0.14-0.45), 18 trials; v. inactive control interventions: 0.29 (95% CI 0.03-0.55), seven trials] (Bighelli et al., 2018). Most recently, a 2018 update of the 2012 Cochrane meta-analysis has continued to find no clear or convincing evidence of superiority on any measure apart from leaving the study early (Jones et al., 2018). In the wake of a 'viewpoint' article examining whether it is right to continue to regard CBT as a gold standard for depression and anxiety (Leichsenring and Steinert, 2017), we consider the current status of this form of therapy in schizophrenia and the related psychotic disorders that are typically included in trials (schizoaffective disorder, delusional disorder, and psychosis not otherwise specified). We draw on what can legitimately be regarded as the two best sources of evidence, namely meta-analyses and large, well-conducted individual trials. Is CBT effective in high-quality trials? Figure 1 shows pooled ESs for positive symptoms, the class of symptoms that CBT was originally developed to treat, in meta-analyses carried out since 2001. A fall over time is evident, with meta-analyses carried out in the last 5 years all finding pooled ESs in the small range (0.1-0.3). It seems likely that this reflects the larger sample sizes and increased attention to methodo-logical factors that have tended to characterize more recent trials. In our 2014 meta-analysis (Jauhar et al., 2014), we found a significant moderating effect of blinding: the pooled ES reduced from 0.33 to 0.15 (95% CI 0.03-0.27) in 20 trials of overall symptoms, and fell from 0.25 to non-significant levels [0.08 (95% CI −0.03-0.18) in 20 trials of positive symptoms (Jauhar et al., 2014)]. Bighelli et al. (2018) had more nuanced results in their network meta-analysis: they found the small but significant ES for CBT was maintained in blind studies when compared against TAU (0.27, 95% CI 0.13-0.41) but not against inactive control interventions (0.14, 95% CI −0.09-0.37). Of course, blinding is not the only measure that contributes to trial quality-others include randomization (especially allocation concealment, the taking of steps to ensure that the randomization code cannot be broken, typically by use of remote allocation) (Schulz and Grimes, 2002a), and the use of measures to deal with incomplete outcome data (Schulz and Grimes, 2002b). In our meta-analysis (Jauhar et al., 2014), we addressed this broader issue by pooling data from studies that were rated as being at low risk of bias from all three of these factors. ESs for overall and positive symptoms were small and non-significant in these studies [overall symptoms: 0.15 (95% CI −0.01-0.32), eight studies; positive symptoms: 0.10 (95% CI −0.09-0.28), nine studies] (Jauhar et al., 2014, p. 22014). However, pooling data only from trials deemed to be at low risk of bias not only severely restricts the study base but also depends on information given by authors about their methodology, which may be

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