Little is known about the psychobiological mechanisms of cognitive behavioural therapy for psychosis (CBTp) and which specific processes are key in predicting favourable long-term outcomes. Following theoretical models of psychosis, this proof-of-concept study investigated whether the long-term recovery path of CBTp completers can be predicted by the neural changes in threat-based social affective processing that occur during CBTp. We followed up participants who had undergone a social affective processing task during functional MRI along with self-report and clinician-administered symptom measures, before and after receiving CBTp. Monthly ratings of psychotic and affective symptoms were obtained retrospectively across eight years since receiving CBTp, plus self-reported recovery at final follow-up. We investigated whether these long-term outcomes were predicted by CBTp-led changes in functional connections with dorsal prefrontal cortical and amygdala during the processing of threatening and prosocial facial affect. Whilst long-term psychotic symptoms were predicted by changes in prefrontal connections during prosocial facial affective processing, long-term affective symptoms were predicted by threat-related amygdalo-IPL connectivity. Greater increases in dorsolateral prefrontal cortex connectivity with amygdala following CBTp also predicted higher subjective ratings of recovery at long-term follow-up. These findings show that reorganisation occurring at the neural level following psychological therapy can predict the subsequent recovery path of people with psychosis across eight years. This novel methodology shows promise for further studies with larger sample size which are needed to better examine the sensitivity of psychobiological processes, in comparison to existing clinical measures, in predicting long-term outcomes.
Psychotic experiences can be highly distressing and people experiencing psychosis often also show high levels of emotional disturbances . Whilst effective pharmacological and psychological interventions exist, high rates of relapse remain and residual symptoms and distress typically persevere between episodes e.g. Identifying the treatment factors that predict favourable recovery pathways is an important step towards improving future interventions.
An important step forward in evidence-based practice, across psychiatric disorders, has been the use of objective clinical measures for the purpose of outcome monitoring in individuals, therapists and services . Whilst increasingly important in service-level clinical decisionmaking, including allocation of resources and funding, these measures remain poor in predicting long-term outcomes. In psychosis for example, a recent meta-analysis showed that both clinical and demographic variables are poor predictors of relapse, with non-significant effects observed for psychosis symptoms (either positive or negative), affective symptoms, or clinician-rated insight. Measuring change at the level of the psychological processes that generate and maintain these symptoms may be helpful in improving the treatment evaluation as well as for predicting long-term outcomes.
Theoretical models of psychosis postulate that aberrant threat processing is key in generating and maintaining positive symptoms. The psychological processes involved in threat are problematic to quantify by self-report measures due to subjective bias (both for patient and clinician). Functional neuroimaging has yielded robust and objective markers of threat processing in psychosis. Recently, there has been increasing interest in utilising these psychobiological markers to investigate the neural mechanisms of psychological therapies. In psychosis, two reports have arisen from an investigation of cognitive behavioural therapy for psychosis (CBTp) compared to treatment-as-usual . In the first study, we reported reduction in brain response to social threat from pre- to postCBTp fMRI measurements. Recently we further showed that these activation changes were accompanied by reorganisation of numerous connections with prefrontal cortical and with several limbic brain regions. In line with our hypotheses, we found that connectivity between dorsolateral prefrontal cortex (DLPFC) and amygdala increased following CBTp. Under cognitive neuroscience models of emotion regulation, this could indicate an increased ability to contextualise potential social threat and thereby cognitively regulate negative affect, which fits with psychological treatment models of CBTp . An important finding was that the vast majority of connectivity changes did not correlate with symptom change, suggesting that they captured other CBTp-specific changes involved in socio-affective processing, over and above the symptom improvement captured by routine clinical measures. The two connectivity changes to correlate with improvement in psychotic symptoms were increases in DLPFC connectivity with inferior parietal lobule (IPL, when processing social threat) and with postcentral gyrus (when processing prosocial facial affect). The IPL has previously been associated with theory of mind and cognitive insight in schizophrenia and cognitive insight, which includes self-reflectiveness, has been shown to increase following CBTp , providing a plausible route by which changes in functional threat-related connectivity may mediate improvement in positive psychotic symptoms. An unexpected finding was that symptom improvement was also associated with DLPFC-postcentral gyrus connectivity, which may be understood in terms of its putative involvement in the mirror neuron system, specifically in somatic aspects of empathy during the processing of facial affect. In support of this, abnormalities in this region have been associated with deficits in emotion recognition and to correlate with psychotic symptoms . In line with this view, we found the symptom association was present for the processing of prosocial (rather than threatening) facial affect, which may be related to the assertion that paranoia may be secondary to the misperception of benign affect as threatening e.g. .In the present study we sought to examine whether these CBTp-led changes in socio-affective processes are determinants of long-term clinical outcomes. To this end we employed novel investigation methods to retrospectively follow up a previously reported cohort over approximately eight years since they received CBTp. Given the high variability in psychotic symptoms over time, both in terms of relapse as well as between-episode fluctuation of residual symptoms, we obtained monthly measurements instead of relying on a single follow-up “snapshot” (see Methods). We predicted that the degree to which threat-related DLPFC-amygdala connectivity increased following CBTp would predict greater long-term remission in both positive psychotic symptoms and affective symptoms, given the importance of this connection in contextualising potential social threat and in regulating affect. Being key to affective wellbeing, we further predicted that this connectivity would determine subjective ratings of recovery at long-term follow-up. Finally, we predicted that the CBTp-led increases in amygdalo-IPL and DLPFC-postcentral gyrus connectivity that had previously been associated with improvement in psychotic symptoms following CBTp , would predict greater levels of remission in this symptom domain.
Participants and design
Participants were 22 outpatients with a confirmed diagnosis of paranoid schizophrenia (final N=15; see Table 1) who had taken part in our earlier studies. These participants had completed an fMRI implicit facial affective processing task and a battery of clinical measures on two occasions, pre (T1) and post (T2) receiving six months of CBTp. outpatients receiving treatment as usual were also scanned at these time points (data not analysed as part of the present study).
We retrospectively followed up these participants since their final fMRI scan (at T2), an average of 8 years (range 7-9 years) prior to the current study (T3). We obtained objective clinical outcomes for this entire period through case note review (T2 to T3; see Longitudinal Clinician Ratings) as well as current subjective ratings of recovery and well-being (at T3; see Outcome Measures).
Consent was obtained by seeking current contact details from consultant clinicians in the services providing care for the previously recruited participants. Participants were then contacted by phone and those expressing an interest received information about the study, a consent form for accessing their electronic clinic records, self-report questionnaires assessing well-being and recovery and a prepaid envelope. The final sample of participants who consented and returned the questionnaires were reimbursed £10 for their time. Ethical approval was granted by the National Health Service research ethics committee (reference: 2 14/LO/0325).
Functional neuroimaging procedure
As described in earlier reports, participants were presented with monochrome faces depicting fear, anger, happiness, or neutral expressions and had to indicate the sex of the face with a button press response. These were repeated in four blocks per condition, with counterbalancing across 16 blocks (see and Supplementary Material for further details of the scanning protocol). Changes in functional connectivity from T1 to T2 were quantified during social threat (angry faces) and prosocial social affect (happy faces) using the psychophysiological interaction approach . Seeds were left amygdala and right DLPFC; whilst bilateral activation was found, we selected the regions of maximum task activation that were reported previously . Seeds were defined functionally from the group-level maxima, with spheres around these maxima (3 mm and 4 mm radius for amygdala and DLPFC respectively). These were 15 additionally constrained within anatomical masks for these regions as defined by the PickAtlas toolbox. Significant connectivity changes following CBTp were tested by examining the interaction of group (CBTp vs treatment as usual) by time (T1 vs T2). There were exclusively increases in connectivity in the CBTp group across functional connections with amygdala and DLPFC.
For the present study, we focused our analyses on the change in DLPFC-amygdala connectivity that occurred during social threat processing, because of the strong theoretical link with cognitive regulation of affect and in turn the relevance to cognitive-behavioural models of positive symptoms of psychosis. We also included the two connectivity changes that previously correlated with improvement in positive psychotic symptoms: amygdala-IPL and DLPFC-postcentral gyrus, which had occurred for the processing of threat and prosocial facial affect, respectively.
Cross-sectional clinical measures
The following clinician-administered and self-report measures had previously been administered pre- and post- CBTp (T1 and T2). The Positive and Negative Syndrome Schedule PANSS;is a clinician-administered rating of positive, negative and general psychopathology symptoms. Affective symptoms were measured from the Beck Depression Inventory, second edition BDI;
We acquired additional measures at long-term follow-up (T3). We assessed subjective recovery using the Questionnaire about the Process of Recovery (QPR), a service-user led instrument that follows theoretical models of recovery and provides a measure of constructs such as hope, empowerment, confidence, connectedness to others. This was our primary measure as it has one of the best psychometric properties of recovery measures and can be expected to be relatively robust to fluctuations in clinical state, making it well suited to use a cross-sectional measurement of long-term outcome. Additional measures for well-being, satisfaction and functioning were acquired (see Supplementary Materials) but were not included in analyses because of missing observations, a high correlation with self-reported recovery and to reduce the number of analyses reported. These data are available on request from the first author.
Longitudinal clinician ratings of symptoms
We retrospectively determined symptoms and functioning from electronic case note data held by local National Health Service trusts in South London. This covered the entire period between participants’ final fMRI measurements (T2; circa 2007) and January 2015 (T3). Two raters followed validated operationalised criteria to infer presence of positive psychotic symptoms for each month independently, based on clinical note entries made by mental 8 health professionals. Participants were rated as being in “full remission” (no symptoms present), “partial remission” (symptoms of low intensity or frequency with clinicians noting at least partial insight), or “no remission” (moderate symptoms; see for fully detailed criteria).
Ratings of affective symptoms were based on both the intensity and frequency of affective disturbance as follows. Affective symptoms were rated as “low” when there was no indication of distress or only brief periods (< 3 days, maximum of two separate instances for that month) of mild-to-moderate severity (without expression of suicidality and that did not require intervention by mental health professionals). “Moderate” affective symptoms was rated where there was any period of distress lasting more than three days, where there was expression of suicidality not requiring severe management, or where there were three or more 18 instances of “low” affective symptoms present for that month. “Severe” was rated for any month in which there was severe distress and suicidality requiring severe management, including hospitalisation or home treatment care. This method was shown to have high reliability and clinical validity, with strong associations between the ratings of symptoms made by case note ratings and PANSS in the same participants. We confirmed that reliability was also high for ratings made in the present study, with inter-rater agreement ranging from “moderate” to “almost perfect” (see Supplementary Materials).
In addition to these symptom ratings, we also rated level of care needed (categories: care of general practitioner only; outpatient appointments in secondary care; daily home treatment; hospital treatment) and occupational functioning (paid employment; voluntary work or training course; unemployed), as a mean of validating the clinical ratings (Supplementary Table 1). There were significant positive associations between the non-remission measure and amount of severe care (hospitalisation and home treatment; See Supplementary Table 2)
Prediction of long-term outcomes from functional connectivity changes
Multivariate analysis of variance (MANOVA, Wilk’s Lambda) was used to relate the 11 longitudinal, month-by-month clinician ratings of psychotic and affective symptoms (T2 to 12 T3) as well as subjective recovery (T3), to the functional connectivity changes (T1 to T2) as follows. All tests were performed one-tailed.
Percentage of months spent in each of the three symptom states was computed for positive psychotic symptoms (full, partial or non-remission) and for affective symptoms (low, moderate, or severe). To simplify the analyses and to reduce model over-fitting, we computed a single residualised variable for each symptom domain (see Supplementary Materials for details). The effect of psychotic and affective symptom domains was tested separately, by entering the respective symptom variable as a regressor within MANOVA, along with our hypothesised changes in connectivity as dependent variables. Bonferroni correction was applied for multiple tests (p/2) across the two symptom domains and significant effects were followed up using correlation tests (Spearman; rρ) to clarify the direction of associations.
We also performed an exploratory analysis to address the hypothesis that the therapeutic effects of CBTp would be better captured by changes to core threat processes than by shortterm symptom reduction. Because of the exploratory nature, this analysis is reported as supplementary material.
Finally, we separately tested the relationship between the functional connectivity changes and long-term subjective recovery, the total score of which was entered as a regressor into MANOVA with the functional connectivity changes as dependent variables.